Sample records for predict future environmental
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Elwood L. Shafer; George H. Moeller; Russell E. Getty
1974-01-01
As an aid to policy- and decision-making about future environmental problems, a panel of experts was asked to predict the probabilities of future events associated with natural-resource management, wildland-recreation management, environmental pollution, population-workforce-leisure, and urban environments. Though some of the predictions projected to the year 2050 may...
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National differences in environmental concern and performance are predicted by country age.
Hershfield, Hal E; Bang, H Min; Weber, Elke U
2014-01-01
There are obvious economic predictors of ability and willingness to invest in environmental sustainability. Yet, given that environmental decisions represent trade-offs between present sacrifices and uncertain future benefits, psychological factors may also play a role in country-level environmental behavior. Gott's principle suggests that citizens may use perceptions of their country's age to predict its future continuation, with longer pasts predicting longer futures. Using country- and individual-level analyses, we examined whether longer perceived pasts result in longer perceived futures, which in turn motivate concern for continued environmental quality. Study 1 found that older countries scored higher on an environmental performance index, even when the analysis controlled for country-level differences in gross domestic product and governance. Study 2 showed that when the United States was framed as an old country (vs. a young one), participants were willing to donate more money to an environmental organization. The findings suggest that framing a country as a long-standing entity may effectively prompt proenvironmental behavior.
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ERIC Educational Resources Information Center
Goudie, Andrew
1990-01-01
Traces the history of futuristic predictions of environmental changes. Focuses on particular documents published on environmental change predictions. Identifies particular instances of environmental change, such as the rate of species loss and the greenhouse effect. Maintains that predictions of future environmental changes are fraught with…
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NASA Astrophysics Data System (ADS)
Felkner, John Sames
The scale and extent of global land use change is massive, and has potentially powerful effects on the global climate and global atmospheric composition (Turner & Meyer, 1994). Because of this tremendous change and impact, there is an urgent need for quantitative, empirical models of land use change, especially predictive models with an ability to capture the trajectories of change (Agarwal, Green, Grove, Evans, & Schweik, 2000; Lambin et al., 1999). For this research, a spatial statistical predictive model of land use change was created and run in two provinces of Thailand. The model utilized an extensive spatial database, and used a classification tree approach for explanatory model creation and future land use (Breiman, Friedman, Olshen, & Stone, 1984). Eight input variables were used, and the trees were run on a dependent variable of land use change measured from 1979 to 1989 using classified satellite imagery. The derived tree models were used to create probability of change surfaces, and these were then used to create predicted land cover maps for 1999. These predicted 1999 maps were compared with actual 1999 landcover derived from 1999 Landsat 7 imagery. The primary research hypothesis was that an explanatory model using both economic and environmental input variables would better predict future land use change than would either a model using only economic variables or a model using only environmental. Thus, the eight input variables included four economic and four environmental variables. The results indicated a very slight superiority of the full models to predict future agricultural change and future deforestation, but a slight superiority of the economic models to predict future built change. However, the margins of superiority were too small to be statistically significant. The resulting tree structures were used, however, to derive a series of principles or "rules" governing land use change in both provinces. The model was able to predict future land use, given a series of assumptions, with 90 percent overall accuracies. The model can be used in other developing or developed country locations for future land use prediction, determination of future threatened areas, or to derive "rules" or principles driving land use change.
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Age and Environmental Concern: A Multivariate Analysis.
ERIC Educational Resources Information Center
Buttel, Frederick H.
1979-01-01
This paper provides detailed evidence on the relationships among age, education, and environmental values. The relative strengths of association of age and education in predicting environmental attitudes are evaluated. Present and future generational politics of environmentalism are discussed. (Author/EB)
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To predict the niche, model colonization and extinction
Yackulic, Charles B.; Nichols, James D.; Reid, Janice; Der, Ricky
2015-01-01
Ecologists frequently try to predict the future geographic distributions of species. Most studies assume that the current distribution of a species reflects its environmental requirements (i.e., the species' niche). However, the current distributions of many species are unlikely to be at equilibrium with the current distribution of environmental conditions, both because of ongoing invasions and because the distribution of suitable environmental conditions is always changing. This mismatch between the equilibrium assumptions inherent in many analyses and the disequilibrium conditions in the real world leads to inaccurate predictions of species' geographic distributions and suggests the need for theory and analytical tools that avoid equilibrium assumptions. Here, we develop a general theory of environmental associations during periods of transient dynamics. We show that time-invariant relationships between environmental conditions and rates of local colonization and extinction can produce substantial temporal variation in occupancy–environment relationships. We then estimate occupancy–environment relationships during three avian invasions. Changes in occupancy–environment relationships over time differ among species but are predicted by dynamic occupancy models. Since estimates of the occupancy–environment relationships themselves are frequently poor predictors of future occupancy patterns, research should increasingly focus on characterizing how rates of local colonization and extinction vary with environmental conditions.
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NASA Astrophysics Data System (ADS)
Singer, Anja; Millat, Gerald; Staneva, Joanna; Kröncke, Ingrid
2017-03-01
Small-scale spatial distribution patterns of seven macrofauna species, seagrass beds and mixed mussel/oyster reefs were modelled for the Jade Bay (North Sea, Germany) in response to climatic and environmental scenarios (representing 2050). For the species distribution models four presence-absence modelling methods were merged within the ensemble forecasting platform 'biomod2'. The present spatial distribution (representing 2009) was modelled by statistically related species presences, true species absences and six high-resolution environmental grids. The future spatial distribution was then predicted in response to expected climate change-induced ongoing (1) sea-level rise and (2) water temperature increase. Between 2009 and 2050, the present and future prediction maps revealed a significant range gain for two macrofauna species (Macoma balthica, Tubificoides benedii), whereas the species' range sizes of five macrofauna species remained relatively stable across space and time. The predicted probability of occurrence (PO) of two macrofauna species (Cerastoderma edule, Scoloplos armiger) decreased significantly under the potential future habitat conditions. In addition, a clear seagrass bed extension (Zostera noltii) on the lower intertidal flats (mixed sediments) and a decrease in the PO of mixed Mytilus edulis/Crassostrea gigas reefs was predicted for 2050. Until the mid-21st century, our future climatic and environmental scenario revealed significant changes in the range sizes (gains-losses) and/or the PO (increases-decreases) for seven of the 10 modelled species at the study site.
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Sun, Tian Yin; Mitrano, Denise M; Bornhöft, Nikolaus A; Scheringer, Martin; Hungerbühler, Konrad; Nowack, Bernd
2017-03-07
The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental emissions. Material flow models (MFA) have been used to provide predicted environmental emissions but most current nano-MFA models consider neither the rapid development of ENM production nor the fact that a large proportion of ENM are entering an in-use stock and are released from products over time (i.e., have a lag phase). Here we use dynamic probabilistic material flow modeling to predict scenarios of the future flows of four ENM (nano-TiO 2 , nano-ZnO, nano-Ag and CNT) to environmental compartments and to quantify their amounts in (temporary) sinks such as the in-use stock and ("final") environmental sinks such as soil and sediment. In these scenarios, we estimate likely future amounts if the use and distribution of ENM in products continues along current trends (i.e., a business-as-usual approach) and predict the effect of hypothetical trends in the market development of nanomaterials, such as the emergence of a new widely used product or the ban on certain substances, on the flows of nanomaterials to the environment in years to come. We show that depending on the scenario and the product type affected, significant changes of the flows occur over time, driven by the growth of stocks and delayed release dynamics.
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To predict the niche, model colonization and extinction
Charles B. Yackulic; James D. Nichols; Janice Reid; Ricky Der
2015-01-01
Ecologists frequently try to predict the future geographic distributions of species. Most studies assume that the current distribution of a species reflects its environmental requirements (i.e., the speciesâ niche). However, the current distributions of many species are unlikely to be at equilibrium with the current distribution of environmental conditions, both...
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Integrating environmental and genetic effects to predict responses of tree populations to climate.
Wang, Tongli; O'Neill, Gregory A; Aitken, Sally N
2010-01-01
Climate is a major environmental factor affecting the phenotype of trees and is also a critical agent of natural selection that has molded among-population genetic variation. Population response functions describe the environmental effect of planting site climates on the performance of a single population, whereas transfer functions describe among-population genetic variation molded by natural selection for climate. Although these approaches are widely used to predict the responses of trees to climate change, both have limitations. We present a novel approach that integrates both genetic and environmental effects into a single "universal response function" (URF) to better predict the influence of climate on phenotypes. Using a large lodgepole pine (Pinus contorta Dougl. ex Loud.) field transplant experiment composed of 140 populations planted on 62 sites to demonstrate the methodology, we show that the URF makes full use of data from provenance trials to: (1) improve predictions of climate change impacts on phenotypes; (2) reduce the size and cost of future provenance trials without compromising predictive power; (3) more fully exploit existing, less comprehensive provenance tests; (4) quantify and compare environmental and genetic effects of climate on population performance; and (5) predict the performance of any population growing in any climate. Finally, we discuss how the last attribute allows the URF to be used as a mechanistic model to predict population and species ranges for the future and to guide assisted migration of seed for reforestation, restoration, or afforestation and genetic conservation in a changing climate.
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2015-01-01
The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change. PMID:26057739
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Thomson, Robin B; Alderman, Rachael L; Tuck, Geoffrey N; Hobday, Alistair J
2015-01-01
The impacts of climate change on marine species are often compounded by other stressors that make direct attribution and prediction difficult. Shy albatrosses (Thalassarche cauta) breeding on Albatross Island, Tasmania, show an unusually restricted foraging range, allowing easier discrimination between the influence of non-climate stressors (fisheries bycatch) and environmental variation. Local environmental conditions (rainfall, air temperature, and sea-surface height, an indicator of upwelling) during the vulnerable chick-rearing stage, have been correlated with breeding success of shy albatrosses. We use an age-, stage- and sex-structured population model to explore potential relationships between local environmental factors and albatross breeding success while accounting for fisheries bycatch by trawl and longline fisheries. The model uses time-series of observed breeding population counts, breeding success, adult and juvenile survival rates and a bycatch mortality observation for trawl fishing to estimate fisheries catchability, environmental influence, natural mortality rate, density dependence, and productivity. Observed at-sea distributions for adult and juvenile birds were coupled with reported fishing effort to estimate vulnerability to incidental bycatch. The inclusion of rainfall, temperature and sea-surface height as explanatory variables for annual chick mortality rate was statistically significant. Global climate models predict little change in future local average rainfall, however, increases are forecast in both temperatures and upwelling, which are predicted to have detrimental and beneficial effects, respectively, on breeding success. The model shows that mitigation of at least 50% of present bycatch is required to offset losses due to future temperature changes, even if upwelling increases substantially. Our results highlight the benefits of using an integrated modeling approach, which uses available demographic as well as environmental data within a single estimation framework, to provide future predictions. Such predictions inform the development of management options in the face of climate change.
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(Q)SARs to predict environmental toxicities: current status and future needs.
Cronin, Mark T D
2017-03-22
The current state of the art of (Quantitative) Structure-Activity Relationships ((Q)SARs) to predict environmental toxicity is assessed along with recommendations to develop these models further. The acute toxicity of compounds acting by the non-polar narcotic mechanism of action can be well predicted, however other approaches, including read-across, may be required for compounds acting by specific mechanisms of action. The chronic toxicity of compounds to environmental species is more difficult to predict from (Q)SARs, with robust data sets and more mechanistic information required. In addition, the toxicity of mixtures is little addressed by (Q)SAR approaches. Developments in environmental toxicology including Adverse Outcome Pathways (AOPs) and omics responses should be utilised to develop better, more mechanistically relevant, (Q)SAR models.
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Francy, Donna S.; Graham, Jennifer L.; Stelzer, Erin A.; Ecker, Christopher D.; Brady, Amie M. G.; Pam Struffolino,; Loftin, Keith A.
2015-11-06
The results of this study showed that water-quality and environmental variables are promising for use in site-specific daily or long-term predictive models. In order to develop more accurate models to predict toxin concentrations at freshwater lake sites, data need to be collected more frequently and for consecutive days in future studies.
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Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.
Rajagopalan, Ramesh; Litvan, Irene; Jung, Tzyy-Ping
2017-11-01
Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems.
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Extinctions in ancient and modern seas.
Harnik, Paul G; Lotze, Heike K; Anderson, Sean C; Finkel, Zoe V; Finnegan, Seth; Lindberg, David R; Liow, Lee Hsiang; Lockwood, Rowan; McClain, Craig R; McGuire, Jenny L; O'Dea, Aaron; Pandolfi, John M; Simpson, Carl; Tittensor, Derek P
2012-11-01
In the coming century, life in the ocean will be confronted with a suite of environmental conditions that have no analog in human history. Thus, there is an urgent need to determine which marine species will adapt and which will go extinct. Here, we review the growing literature on marine extinctions and extinction risk in the fossil, historical, and modern records to compare the patterns, drivers, and biological correlates of marine extinctions at different times in the past. Characterized by markedly different environmental states, some past periods share common features with predicted future scenarios. We highlight how the different records can be integrated to better understand and predict the impact of current and projected future environmental changes on extinction risk in the ocean. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions
Rajagopalan, Ramesh; Jung, Tzyy-Ping
2017-01-01
Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems. PMID:29104256
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Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C
2016-01-01
Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.
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Future distribution of tundra refugia in northern Alaska
Hope, Andrew G.; Waltari, Eric; Payer, David C.; Cook, Joseph A.; Talbot, Sandra L.
2013-01-01
Climate change in the Arctic is a growing concern for natural resource conservation and management as a result of accelerated warming and associated shifts in the distribution and abundance of northern species. We introduce a predictive framework for assessing the future extent of Arctic tundra and boreal biomes in northern Alaska. We use geo-referenced museum specimens to predict the velocity of distributional change into the next century and compare predicted tundra refugial areas with current land-use. The reliability of predicted distributions, including differences between fundamental and realized niches, for two groups of species is strengthened by fossils and genetic signatures of demographic shifts. Evolutionary responses to environmental change through the late Quaternary are generally consistent with past distribution models. Predicted future refugia overlap managed areas and indicate potential hotspots for tundra diversity. To effectively assess future refugia, variable responses among closely related species to climate change warrants careful consideration of both evolutionary and ecological histories.
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Family Environmental and Genetic Influences on Children's Future Chemical Dependency.
ERIC Educational Resources Information Center
Kumpfer, Karol L.; DeMarsh, Joseph
1985-01-01
Discusses the following in relation to their predictability to future drug abuse in youth: (1) susceptibility of children of chemically dependent parents; (2) genetic transmutation; (3) family structure and management; (4) socialization; and (5) cognitive family characteristics. (Author/LHW)
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NASA Astrophysics Data System (ADS)
Hutchenson, K. D.; Hartley-McBride, S.; Saults, T.; Schmidt, D. P.
2006-05-01
The International Monitoring System (IMS) is composed in part of radionuclide particulate and gas monitoring systems. Monitoring the operational status of these systems is an important aspect of nuclear weapon test monitoring. Quality data, process control techniques, and predictive models are necessary to detect and predict system component failures. Predicting failures in advance provides time to mitigate these failures, thus minimizing operational downtime. The Provisional Technical Secretariat (PTS) requires IMS radionuclide systems be operational 95 percent of the time. The United States National Data Center (US NDC) offers contributing components to the IMS. This effort focuses on the initial research and process development using prognostics for monitoring and predicting failures of the RASA two (2) days into the future. The predictions, using time series methods, are input to an expert decision system, called SHADES (State of Health Airflow and Detection Expert System). The results enable personnel to make informed judgments about the health of the RASA system. Data are read from a relational database, processed, and displayed to the user in a GIS as a prototype GUI. This procedure mimics the real time application process that could be implemented as an operational system, This initial proof-of-concept effort developed predictive models focused on RASA components for a single site (USP79). Future work shall include the incorporation of other RASA systems, as well as their environmental conditions that play a significant role in performance. Similarly, SHADES currently accommodates specific component behaviors at this one site. Future work shall also include important environmental variables that play an important part of the prediction algorithms.
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Model Projections of Future Fluvial Sediment Delivery to Major Deltas Under Environmental Change
NASA Astrophysics Data System (ADS)
Darby, S. E.; Dunn, F.; Nicholls, R. J.; Cohen, S.; Zarfl, C.
2017-12-01
Deltas are important hot spots for climate change impacts on which over half a billion people live worldwide. Most of the world's deltas are sinking as a result of natural and anthropogenic subsidence and due to eustatic sea level rise. The ability to predict rates of delta aggradation is therefore critical to assessments of the extent to which sedimentation can potentially offset sea level rise, but our ability to make such predictions is severely hindered by a lack of insight into future trends of the fluvial sediment load supplied to their deltas by feeder watersheds. To address this gap we investigate fluvial sediment fluxes under future environmental change for a selection (47) of the world's major river deltas. Specifically, we employed the numerical model WBMsed to project future variations in mean annual fluvial sediment loads under a range of environmental change scenarios that account for changes in climate, socio-economics and dam construction. Our projections indicate a clear decrease (by 34 to 41% on average, depending on the specific scenario) in future fluvial sediment supply to most of the 47 deltas. These reductions in sediment delivery are driven primarily by anthropogenic disturbances, with reservoir construction being the most influential factor globally. Our results indicate the importance of developing new management strategies for reservoir construction and operation.
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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
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Environmental, Transient, Three-Dimensional, Hydrothermal, Mass Transport Code - FLESCOT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Onishi, Yasuo; Bao, Jie; Glass, Kevin A.
The purpose of the project was to modify and apply the transient, three-dimensional FLESCOT code to be able to effectively simulate cesium behavior in Fukushima lakes/dam reservoirs, river mouths, and coastal areas. The ultimate objective of the FLESCOT simulation is to predict future changes of cesium accumulation in Fukushima area reservoirs and costal water. These evaluation results will assist ongoing and future environmental remediation activities and policies in a systematic and comprehensive manner.
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Effects of temporal variation in temperature and density dependence on insect population dynamics
USDA-ARS?s Scientific Manuscript database
Understanding effects of environmental variation on insect populations is important in light of predictions about increasing future climatic variability. In order to understand the effects of changing environmental variation on population dynamics and life history evolution in insects one would need...
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Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...
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Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...
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Larsen, Peter; Hamada, Yuki; Gilbert, Jack
2012-07-31
Never has there been a greater opportunity for investigating microbial communities. Not only are the profound effects of microbial ecology on every aspect of Earth's geochemical cycles beginning to be understood, but also the analytical and computational tools for investigating microbial Earth are undergoing a rapid revolution. This environmental microbial interactome, the system of interactions between the microbiome and the environment, has shaped the planet's past and will undoubtedly continue to do so in the future. We review recent approaches for modeling microbial community structures and the interactions of microbial populations with their environments. Different modeling approaches consider the environmental microbial interactome from different aspects, and each provides insights to different facets of microbial ecology. We discuss the challenges and opportunities for the future of microbial modeling and describe recent advances in microbial community modeling that are extending current descriptive technologies into a predictive science. Copyright © 2012 Elsevier B.V. All rights reserved.
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Supple, Megan Ann; Bragg, Jason G; Broadhurst, Linda M; Nicotra, Adrienne B; Byrne, Margaret; Andrew, Rose L; Widdup, Abigail; Aitken, Nicola C; Borevitz, Justin O
2018-04-24
As species face rapid environmental change, we can build resilient populations through restoration projects that incorporate predicted future climates into seed sourcing decisions. Eucalyptus melliodora is a foundation species of a critically endangered community in Australia that is a target for restoration. We examined genomic and phenotypic variation to make empirical based recommendations for seed sourcing. We examined isolation by distance and isolation by environment, determining high levels of gene flow extending for 500 km and correlations with climate and soil variables. Growth experiments revealed extensive phenotypic variation both within and among sampling sites, but no site-specific differentiation in phenotypic plasticity. Model predictions suggest that seed can be sourced broadly across the landscape, providing ample diversity for adaptation to environmental change. Application of our landscape genomic model to E. melliodora restoration projects can identify genomic variation suitable for predicted future climates, thereby increasing the long term probability of successful restoration. © 2018, Supple et al.
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Bringing modeling to the masses: A web based system to predict potential species distributions
Graham, Jim; Newman, Greg; Kumar, Sunil; Jarnevich, Catherine S.; Young, Nick; Crall, Alycia W.; Stohlgren, Thomas J.; Evangelista, Paul
2010-01-01
Predicting current and potential species distributions and abundance is critical for managing invasive species, preserving threatened and endangered species, and conserving native species and habitats. Accurate predictive models are needed at local, regional, and national scales to guide field surveys, improve monitoring, and set priorities for conservation and restoration. Modeling capabilities, however, are often limited by access to software and environmental data required for predictions. To address these needs, we built a comprehensive web-based system that: (1) maintains a large database of field data; (2) provides access to field data and a wealth of environmental data; (3) accesses values in rasters representing environmental characteristics; (4) runs statistical spatial models; and (5) creates maps that predict the potential species distribution. The system is available online at www.niiss.org, and provides web-based tools for stakeholders to create potential species distribution models and maps under current and future climate scenarios.
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Working Group on Virtual Data Integration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Williams, Dean N.
2016-03-07
This report is the outcome of a workshop commissioned by the U.S. Department of Energy’s (DOE) Climate and Environmental Sciences Division (CESD) to examine current and future data infrastructure requirements foundational for achieving CESD scientific mission goals in advancing a robust, predictive understanding of Earth’s climate and environmental systems.
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O'Brien, Eleanor K; Higgie, Megan; Reynolds, Alan; Hoffmann, Ary A; Bridle, Jon R
2017-05-01
Predicting how species will respond to the rapid climatic changes predicted this century is an urgent task. Species distribution models (SDMs) use the current relationship between environmental variation and species' abundances to predict the effect of future environmental change on their distributions. However, two common assumptions of SDMs are likely to be violated in many cases: (i) that the relationship of environment with abundance or fitness is constant throughout a species' range and will remain so in future and (ii) that abiotic factors (e.g. temperature, humidity) determine species' distributions. We test these assumptions by relating field abundance of the rainforest fruit fly Drosophila birchii to ecological change across gradients that include its low and high altitudinal limits. We then test how such ecological variation affects the fitness of 35 D. birchii families transplanted in 591 cages to sites along two altitudinal gradients, to determine whether genetic variation in fitness responses could facilitate future adaptation to environmental change. Overall, field abundance was highest at cooler, high-altitude sites, and declined towards warmer, low-altitude sites. By contrast, cage fitness (productivity) increased towards warmer, lower-altitude sites, suggesting that biotic interactions (absent from cages) drive ecological limits at warmer margins. In addition, the relationship between environmental variation and abundance varied significantly among gradients, indicating divergence in ecological niche across the species' range. However, there was no evidence for local adaptation within gradients, despite greater productivity of high-altitude than low-altitude populations when families were reared under laboratory conditions. Families also responded similarly to transplantation along gradients, providing no evidence for fitness trade-offs that would favour local adaptation. These findings highlight the importance of (i) measuring genetic variation in key traits under ecologically relevant conditions, and (ii) considering the effect of biotic interactions when predicting species' responses to environmental change. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
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Environmental chemical exposures and human epigenetics
Hou, Lifang; Zhang, Xiao; Wang, Dong; Baccarelli, Andrea
2012-01-01
Every year more than 13 million deaths worldwide are due to environmental pollutants, and approximately 24% of diseases are caused by environmental exposures that might be averted through preventive measures. Rapidly growing evidence has linked environmental pollutants with epigenetic variations, including changes in DNA methylation, histone modifications and microRNAs. Environ mental chemicals and epigenetic changes All of these mechanisms are likely to play important roles in disease aetiology, and their modifications due to environmental pollutants might provide further understanding of disease aetiology, as well as biomarkers reflecting exposures to environmental pollutants and/or predicting the risk of future disease. We summarize the findings on epigenetic alterations related to environmental chemical exposures, and propose mechanisms of action by means of which the exposures may cause such epigenetic changes. We discuss opportunities, challenges and future directions for future epidemiology research in environmental epigenomics. Future investigations are needed to solve methodological and practical challenges, including uncertainties about stability over time of epigenomic changes induced by the environment, tissue specificity of epigenetic alterations, validation of laboratory methods, and adaptation of bioinformatic and biostatistical methods to high-throughput epigenomics. In addition, there are numerous reports of epigenetic modifications arising following exposure to environmental toxicants, but most have not been directly linked to disease endpoints. To complete our discussion, we also briefly summarize the diseases that have been linked to environmental chemicals-related epigenetic changes. PMID:22253299
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Steven E. Smith; Ma.G. Mendoza; Gerardo Zuniga; Kandres Kalbrook; J.L. Hayes; D.N. Byrne
2013-01-01
Understanding the distribution of key biotic elements of forest ecosystems is essential in contemporary forest management and in planning to meet future management needs. Habitat distribution (niche) models based on known occurrences provide geographical structure for such management as the environmental factors change....
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Computational intelligence in earth sciences and environmental applications: issues and challenges.
Cherkassky, V; Krasnopolsky, V; Solomatine, D P; Valdes, J
2006-03-01
This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The issues of data quality, selection of the error function, incorporation of the predictive learning methods into the existing modeling frameworks, expert knowledge, model uncertainty, and other application-domain specific problems are discussed. A brief overview of the papers in the Special Issue is provided, followed by discussion of open issues and directions for future research.
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Genetic interactions for heat stress and production level: predicting foreign from domestic data
USDA-ARS?s Scientific Manuscript database
Genetic by environmental interactions were estimated from U.S. national data by separately adding random regressions for heat stress (HS) and herd production level (HL) to the all-breed animal model to improve predictions of future records and rankings in other climate and production situations. Yie...
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Li, Ke; Zhang, Peng; Crittenden, John C; Guhathakurta, Subhrajit; Chen, Yongsheng; Fernando, Harindra; Sawhney, Anil; McCartney, Peter; Grimm, Nancy; Kahhat, Ramzy; Joshi, Himanshu; Konjevod, Goran; Choi, Yu-Jin; Fonseca, Ernesto; Allenby, Braden; Gerrity, Daniel; Torrens, Paul M
2007-07-15
To encourage sustainable development, engineers and scientists need to understand the interactions among social decision-making, development and redevelopment, land, energy and material use, and their environmental impacts. In this study, a framework that connects these interactions was proposed to guide more sustainable urban planning and construction practices. Focusing on the rapidly urbanizing setting of Phoenix, Arizona, complexity models and deterministic models were assembled as a metamodel, which is called Sustainable Futures 2100 and were used to predict land use and development, to quantify construction material demands, to analyze the life cycle environmental impacts, and to simulate future ground-level ozone formation.
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AEDT: A new concept for ecological dynamics in the ever-changing world.
Chesson, Peter
2017-05-01
The important concept of equilibrium has always been controversial in ecology, but a new, more general concept, an asymptotic environmentally determined trajectory (AEDT), overcomes many concerns with equilibrium by realistically incorporating long-term climate change while retaining much of the predictive power of a stable equilibrium. A population or ecological community is predicted to approach its AEDT, which is a function of time reflecting environmental history and biology. The AEDT invokes familiar questions and predictions but in a more realistic context in which consideration of past environments and a future changing profoundly due to human influence becomes possible. Strong applications are also predicted in population genetics, evolution, earth sciences, and economics.
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Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble
Jiang, Mingkai; Felzer, Benjamin S.; Sahagian, Dork
2016-01-01
Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950–2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040–2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment. PMID:27425819
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Predictability of Precipitation Over the Conterminous U.S. Based on the CMIP5 Multi-Model Ensemble.
Jiang, Mingkai; Felzer, Benjamin S; Sahagian, Dork
2016-07-18
Characterizing precipitation seasonality and variability in the face of future uncertainty is important for a well-informed climate change adaptation strategy. Using the Colwell index of predictability and monthly normalized precipitation data from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensembles, this study identifies spatial hotspots of changes in precipitation predictability in the United States under various climate scenarios. Over the historic period (1950-2005), the recurrent pattern of precipitation is highly predictable in the East and along the coastal Northwest, and is less so in the arid Southwest. Comparing the future (2040-2095) to the historic period, larger changes in precipitation predictability are observed under Representative Concentration Pathways (RCP) 8.5 than those under RCP 4.5. Finally, there are region-specific hotspots of future changes in precipitation predictability, and these hotspots often coincide with regions of little projected change in total precipitation, with exceptions along the wetter East and parts of the drier central West. Therefore, decision-makers are advised to not rely on future total precipitation as an indicator of water resources. Changes in precipitation predictability and the subsequent changes on seasonality and variability are equally, if not more, important factors to be included in future regional environmental assessment.
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McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian
2017-01-01
Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.
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Federal Register 2010, 2011, 2012, 2013, 2014
2012-12-07
... County, Arizona, has had one of the fastest growing human populations of any county in the United States... opportunities. Urban growth has resulted in significant development, which is expected to continue in the foreseeable future. A significant proportion of the predicted future development is anticipated to occur in...
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Risk terrain modeling predicts child maltreatment.
Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye
2016-12-01
As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Collective behaviour, uncertainty and environmental change.
Bentley, R Alexander; O'Brien, Michael J
2015-11-28
A central aspect of cultural evolutionary theory concerns how human groups respond to environmental change. Although we are painting with a broad brush, it is fair to say that prior to the twenty-first century, adaptation often happened gradually over multiple human generations, through a combination of individual and social learning, cumulative cultural evolution and demographic shifts. The result was a generally resilient and sustainable population. In the twenty-first century, however, considerable change happens within small portions of a human generation, on a vastly larger range of geographical and population scales and involving a greater degree of horizontal learning. As a way of gauging the complexity of societal response to environmental change in a globalized future, we discuss several theoretical tools for understanding how human groups adapt to uncertainty. We use our analysis to estimate the limits of predictability of future societal change, in the belief that knowing when to hedge bets is better than relying on a false sense of predictability. © 2015 The Author(s).
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Anderson-Cook, Christine M.; Morzinski, Jerome; Blecker, Kenneth D.
2015-08-19
Understanding the impact of production, environmental exposure and age characteristics on the reliability of a population is frequently based on underlying science and empirical assessment. When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. We describe a five-step process for exploring relationships between available summaries of age, usage and environmental exposure and reliability. The process involves first identifying potential candidatemore » inputs, then second organizing data for the analysis. Third, a variety of models with different combinations of the inputs are estimated, and fourth, flexible metrics are used to compare them. As a result, plots of the predicted relationships are examined to distill leading model contenders into a prioritized list for subject matter experts to understand and compare. The complexity of the model, quality of prediction and cost of future data collection are all factors to be considered by the subject matter experts when selecting a final model.« less
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Bayesian Analysis for Inference of an Emerging Epidemic: Citrus Canker in Urban Landscapes
Neri, Franco M.; Cook, Alex R.; Gibson, Gavin J.; Gottwald, Tim R.; Gilligan, Christopher A.
2014-01-01
Outbreaks of infectious diseases require a rapid response from policy makers. The choice of an adequate level of response relies upon available knowledge of the spatial and temporal parameters governing pathogen spread, affecting, amongst others, the predicted severity of the epidemic. Yet, when a new pathogen is introduced into an alien environment, such information is often lacking or of no use, and epidemiological parameters must be estimated from the first observations of the epidemic. This poses a challenge to epidemiologists: how quickly can the parameters of an emerging disease be estimated? How soon can the future progress of the epidemic be reliably predicted? We investigate these issues using a unique, spatially and temporally resolved dataset for the invasion of a plant disease, Asiatic citrus canker in urban Miami. We use epidemiological models, Bayesian Markov-chain Monte Carlo, and advanced spatial statistical methods to analyse rates and extent of spread of the disease. A rich and complex epidemic behaviour is revealed. The spatial scale of spread is approximately constant over time and can be estimated rapidly with great precision (although the evidence for long-range transmission is inconclusive). In contrast, the rate of infection is characterised by strong monthly fluctuations that we associate with extreme weather events. Uninformed predictions from the early stages of the epidemic, assuming complete ignorance of the future environmental drivers, fail because of the unpredictable variability of the infection rate. Conversely, predictions improve dramatically if we assume prior knowledge of either the main environmental trend, or the main environmental events. A contrast emerges between the high detail attained by modelling in the spatiotemporal description of the epidemic and the bottleneck imposed on epidemic prediction by the limits of meteorological predictability. We argue that identifying such bottlenecks will be a fundamental step in future modelling of weather-driven epidemics. PMID:24762851
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Slater, Hannah; Michael, Edwin
2013-01-01
There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194
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Belanger, Christina L.
2012-01-01
Modern climate change has a strong potential to shift earth systems and biological communities into novel states that have no present-day analog, leaving ecologists with no observational basis to predict the likely biotic effects. Fossil records contain long time-series of past environmental changes outside the range of modern observation, which are vital for predicting future ecological responses, and are capable of (a) providing detailed information on rates of ecological change, (b) illuminating the environmental drivers of those changes, and (c) recording the effects of environmental change on individual physiological rates. Outcrops of Early Miocene Newport Member of the Astoria Formation (Oregon) provide one such time series. This record of benthic foraminiferal and molluscan community change from continental shelf depths spans a past interval environmental change (∼20.3-16.7 mya) during which the region warmed 2.1–4.5°C, surface productivity and benthic organic carbon flux increased, and benthic oxygenation decreased, perhaps driven by intensified upwelling as on the modern Oregon coast. The Newport Member record shows that (a) ecological responses to natural environmental change can be abrupt, (b) productivity can be the primary driver of faunal change during global warming, (c) molluscs had a threshold response to productivity change while foraminifera changed gradually, and (d) changes in bivalve body size and growth rates parallel changes in taxonomic composition at the community level, indicating that, either directly or indirectly through some other biological parameter, the physiological tolerances of species do influence community change. Ecological studies in modern and fossil records that consider multiple ecological levels, environmental parameters, and taxonomic groups can provide critical information for predicting future ecological change and evaluating species vulnerability. PMID:22558424
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Mukhopadhyay, Anirban; Mondal, Parimal; Barik, Jyotiskona; Chowdhury, S M; Ghosh, Tuhin; Hazra, Sugata
2015-06-01
The composition and assemblage of mangroves in the Bangladesh Sundarbans are changing systematically in response to several environmental factors. In order to understand the impact of the changing environmental conditions on the mangrove forest, species composition maps for the years 1985, 1995 and 2005 were studied. In the present study, 1985 and 1995 species zonation maps were considered as base data and the cellular automata-Markov chain model was run to predict the species zonation for the year 2005. The model output was validated against the actual dataset for 2005 and calibrated. Finally, using the model, mangrove species zonation maps for the years 2025, 2055 and 2105 have been prepared. The model was run with the assumption that the continuation of the current tempo and mode of drivers of environmental factors (temperature, rainfall, salinity change) of the last two decades will remain the same in the next few decades. Present findings show that the area distribution of the following species assemblages like Goran (Ceriops), Sundari (Heritiera), Passur (Xylocarpus), and Baen (Avicennia) would decrease in the descending order, whereas the area distribution of Gewa (Excoecaria), Keora (Sonneratia) and Kankra (Bruguiera) dominated assemblages would increase. The spatial distribution of projected mangrove species assemblages shows that more salt tolerant species will dominate in the future; which may be used as a proxy to predict the increase of salinity and its spatial variation in Sundarbans. Considering the present rate of loss of forest land, 17% of the total mangrove cover is predicted to be lost by the year 2105 with a significant loss of fresh water loving mangroves and related ecosystem services. This paper describes a unique approach to assess future changes in species composition and future forest zonation in mangroves under the 'business as usual' scenario of climate change.
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Environmental compatibility of closed landfills - assessing future pollution hazards.
Laner, David; Fellner, Johann; Brunner, Paul H
2011-01-01
Municipal solid waste landfills need to be managed after closure. This so-called aftercare comprises the treatment and monitoring of residual emissions as well as the maintenance and control of landfill elements. The measures can be terminated when a landfill does not pose a threat to the environment any more. Consequently, the evaluation of landfill environmental compatibility includes an estimation of future pollution hazards as well as an assessment of the vulnerability of the affected environment. An approach to assess future emission rates is presented and discussed in view of long-term environmental compatibility. The suggested method consists (a) of a continuous model to predict emissions under the assumption of constant landfill conditions, and (b) different scenarios to evaluate the effects of changing conditions within and around the landfill. The model takes into account the actual status of the landfill, hence different methods to gain information about landfill characteristics have to be applied. Finally, assumptions, uncertainties, and limitations of the methodology are discussed, and the need for future research is outlined.
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Unravelling the structure of species extinction risk for predictive conservation science.
Lee, Tien Ming; Jetz, Walter
2011-05-07
Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.
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Using the satellite-derived NDVI to assess ecological responses to environmental change.
Pettorelli, Nathalie; Vik, Jon Olav; Mysterud, Atle; Gaillard, Jean-Michel; Tucker, Compton J; Stenseth, Nils Chr
2005-09-01
Assessing how environmental changes affect the distribution and dynamics of vegetation and animal populations is becoming increasingly important for terrestrial ecologists to enable better predictions of the effects of global warming, biodiversity reduction or habitat degradation. The ability to predict ecological responses has often been hampered by our rather limited understanding of trophic interactions. Indeed, it has proven difficult to discern direct and indirect effects of environmental change on animal populations owing to limited information about vegetation at large temporal and spatial scales. The rapidly increasing use of the Normalized Difference Vegetation Index (NDVI) in ecological studies has recently changed this situation. Here, we review the use of the NDVI in recent ecological studies and outline its possible key role in future research of environmental change in an ecosystem context.
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NASA Astrophysics Data System (ADS)
Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.
2015-12-01
Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.
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The Use of Planning in English and German (NRW) Geography School Textbooks
ERIC Educational Resources Information Center
Maier, Veit; Budke, Alexandra
2016-01-01
Although it is not possible to predict the future, at least some ideas can be developed through planning. Geography focuses on current social, environmental and spatial problems; however, it should, at the same time, teach us to plan its future handling. At school, this is a responsible role for the subject geography. This article compares how…
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Anwar, Mohammad Y; Lewnard, Joseph A; Parikh, Sunil; Pitzer, Virginia E
2016-11-22
Malaria remains endemic in Afghanistan. National control and prevention strategies would be greatly enhanced through a better ability to forecast future trends in disease incidence. It is, therefore, of interest to develop a predictive tool for malaria patterns based on the current passive and affordable surveillance system in this resource-limited region. This study employs data from Ministry of Public Health monthly reports from January 2005 to September 2015. Malaria incidence in Afghanistan was forecasted using autoregressive integrated moving average (ARIMA) models in order to build a predictive tool for malaria surveillance. Environmental and climate data were incorporated to assess whether they improve predictive power of models. Two models were identified, each appropriate for different time horizons. For near-term forecasts, malaria incidence can be predicted based on the number of cases in the four previous months and 12 months prior (Model 1); for longer-term prediction, malaria incidence can be predicted using the rates 1 and 12 months prior (Model 2). Next, climate and environmental variables were incorporated to assess whether the predictive power of proposed models could be improved. Enhanced vegetation index was found to have increased the predictive accuracy of longer-term forecasts. Results indicate ARIMA models can be applied to forecast malaria patterns in Afghanistan, complementing current surveillance systems. The models provide a means to better understand malaria dynamics in a resource-limited context with minimal data input, yielding forecasts that can be used for public health planning at the national level.
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Global ice-core research: Understanding and applying environmental records of the past
Cecil, L. DeWayne; Green, Jaromy R.; Naftz, David L.
2000-01-01
Environmental changes are of major concern at low- or mid-latitude regions of our Earth simply because this is where 80 to 90 percent of the world’s human population live. Ice cores collected from isolated polar regions are, at best, proxy indicators of low- and mid-latitude environmental changes. Because polar icecore research is limiting in this sense, ice cores from low- and mid-latitude glaciers are being used to study past environmental changes in order to better understand and predict future environmental changes that may affect the populated regions of the world.
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Forstmann, Matthias; Sagioglou, Christina
2017-08-01
In a large-scale ( N = 1487) general population online study, we investigated the relationship between past experience with classic psychedelic substances (e.g. LSD, psilocybin, mescaline), nature relatedness, and ecological behavior (e.g. saving water, recycling). Using structural equation modeling we found that experience with classic psychedelics uniquely predicted self-reported engagement in pro-environmental behaviors, and that this relationship was statistically explained by people's degree of self-identification with nature. Our model controlled for experiences with other classes of psychoactive substances (cannabis, dissociatives, empathogens, popular legal drugs) as well as common personality traits that usually predict drug consumption and/or nature relatedness (openness to experience, conscientiousness, conservatism). Although correlational in nature, results suggest that lifetime experience with psychedelics in particular may indeed contribute to people's pro-environmental behavior by changing their self-construal in terms of an incorporation of the natural world, regardless of core personality traits or general propensity to consume mind-altering substances. Thereby, the present research adds to the contemporary literature on the beneficial effects of psychedelic substance use on mental wellbeing, hinting at a novel area for future research investigating their potentially positive effects on a societal level. Limitations of the present research and future directions are discussed.
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Through the eyes of children: perceptions of environmental change in tropical forests.
Pellier, Anne-Sophie; Wells, Jessie A; Abram, Nicola K; Gaveau, David; Meijaard, Erik
2014-01-01
This study seeks to understand children's perceptions of their present and future environments in the highly biodiverse and rapidly changing landscapes of Kalimantan, Indonesian Borneo. We analyzed drawings by children (target age 10-15 years) from 22 villages, which show how children perceive the present conditions of forests and wildlife surrounding their villages and how they expect conditions to change over the next 15 years. Analyses of picture elements and their relationships to current landscape variables indicate that children have a sophisticated understanding of their environment and how different environmental factors interact, either positively or negatively. Children appear to have landscape-dependent environmental perceptions, showing awareness of past environmental conditions and many aspects of recent trends, and translating these into predictions for future environmental conditions. The further removed their present landscape is from the originally forested one, the more environmental change they expect in the future, particularly declines in forest cover, rivers, animal diversity and increases in temperature and natural disasters. This suggests that loss of past perceptions and associated "shifting environmental baselines" do not feature strongly among children on Borneo, at least not for the perceptions we investigated here. Our findings that children have negative expectations of their future environmental conditions have important political implications. More than other generations, children have a stake in ensuring that future environmental conditions support their long-term well-being. Understanding what drives environmental views among children, and how they consider trade-offs between economic development and social and environmental change, should inform optimal policies on land use. Our study illuminates part of the complex interplay between perceptions of land cover and land use change. Capturing the views of children through artistic expressions provides a potentially powerful tool to influence public and political opinions, as well as a valuable approach for developing localized education and nature conservation programs.
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Through the Eyes of Children: Perceptions of Environmental Change in Tropical Forests
Pellier, Anne-Sophie; Wells, Jessie A.; Abram, Nicola K.; Gaveau, David; Meijaard, Erik
2014-01-01
This study seeks to understand children's perceptions of their present and future environments in the highly biodiverse and rapidly changing landscapes of Kalimantan, Indonesian Borneo. We analyzed drawings by children (target age 10–15 years) from 22 villages, which show how children perceive the present conditions of forests and wildlife surrounding their villages and how they expect conditions to change over the next 15 years. Analyses of picture elements and their relationships to current landscape variables indicate that children have a sophisticated understanding of their environment and how different environmental factors interact, either positively or negatively. Children appear to have landscape-dependent environmental perceptions, showing awareness of past environmental conditions and many aspects of recent trends, and translating these into predictions for future environmental conditions. The further removed their present landscape is from the originally forested one, the more environmental change they expect in the future, particularly declines in forest cover, rivers, animal diversity and increases in temperature and natural disasters. This suggests that loss of past perceptions and associated “shifting environmental baselines” do not feature strongly among children on Borneo, at least not for the perceptions we investigated here. Our findings that children have negative expectations of their future environmental conditions have important political implications. More than other generations, children have a stake in ensuring that future environmental conditions support their long-term well-being. Understanding what drives environmental views among children, and how they consider trade-offs between economic development and social and environmental change, should inform optimal policies on land use. Our study illuminates part of the complex interplay between perceptions of land cover and land use change. Capturing the views of children through artistic expressions provides a potentially powerful tool to influence public and political opinions, as well as a valuable approach for developing localized education and nature conservation programs. PMID:25093658
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Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark
2015-01-01
Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241
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Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark
2015-01-01
Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.
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NASA Technical Reports Server (NTRS)
Zhu, Dongming; Ghosn, Louis J.
2014-01-01
Topics covered include: Environmental barrier coating system development: needs, challenges and limitations; Advanced environmental barrier coating systems (EBCs) for CMC airfoils and combustors; NASA EBC systems and material system evolutions, Current turbine and combustor EBC coating emphases, Advanced development, processing, testing and modeling, EBC and EBC bond coats: recent advances; Design tool and life prediction of coated CMC components; Advanced CMC-EBC rig demonstrations; Summary and future directions.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Harder, B.J.
1995-03-01
Louisiana wetlands require careful management to allow exploitation of non-renewable resources without destroying renewable resources. Current regulatory requirements have been moderately successful in meeting this goal by restricting development in wetland habitats. Continuing public emphasis on reducing environmental impacts of resource development is causing regulators to reassess their regulations and operators to rethink their compliance strategies. We examined the regulatory system and found that reducing the number of applications required by going to a single application process and having a coherent map of the steps required for operations in wetland areas would reduce regulatory burdens. Incremental changes can be mademore » to regulations to allow one agency to be the lead for wetland permitting at minimal cost to operators. Operators need cost effective means of access that will reduce environmental impacts, decrease permitting time, and limit future liability. Regulators and industry must partner to develop incentive based regulations that can provide significant environmental impact reduction for minimal economic cost. In addition regulators need forecasts of future E&P trends to estimate the impact of future regulations. To determine future activity we attempted to survey potential operators when this approach was unsuccessful we created two econometric models of north and south Louisiana relating drilling activity, success ratio, and price to predict future wetland activity. Results of the econometric models indicate that environmental regulations have a small but statistically significant effect on drilling operations in wetland areas of Louisiana. We examined current wetland practices and evaluated those practices comparing environmental versus economic costs and created a method for ranking the practices.« less
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The Creation of a Beneficial Bioshpere from Co2 in the Clouds of Venus
NASA Astrophysics Data System (ADS)
Linaraki, D. L.; Oungrinis, K. A.
2017-02-01
This research resulted in an architectural design for a Venus colony based on multiple factors combination, such as psychology of space, predicted near-future technology, and the identified environmental conditions on Venus.
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When Waves Collide: Future Conflict
1995-01-01
predictions merely guesswork, and forecasts often nothing more than co- herent fiction masquerading as fact.2 Trends and megatrends , which are linear...transportation, on-site inspection, and environmental cleanup—including radi- ological, chemical, and biological —as well as enforcement of the
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Nabavi-Pelesaraei, Ashkan; Rafiee, Shahin; Mohtasebi, Seyed Saeid; Hosseinzadeh-Bandbafha, Homa; Chau, Kwok-Wing
2018-08-01
Prediction of agricultural energy output and environmental impacts play important role in energy management and conservation of environment as it can help us to evaluate agricultural energy efficiency, conduct crops production system commissioning, and detect and diagnose faults of crop production system. Agricultural energy output and environmental impacts can be readily predicted by artificial intelligence (AI), owing to the ease of use and adaptability to seek optimal solutions in a rapid manner as well as the use of historical data to predict future agricultural energy use pattern under constraints. This paper conducts energy output and environmental impact prediction of paddy production in Guilan province, Iran based on two AI methods, artificial neural networks (ANNs), and adaptive neuro fuzzy inference system (ANFIS). The amounts of energy input and output are 51,585.61MJkg -1 and 66,112.94MJkg -1 , respectively, in paddy production. Life Cycle Assessment (LCA) is used to evaluate environmental impacts of paddy production. Results show that, in paddy production, in-farm emission is a hotspot in global warming, acidification and eutrophication impact categories. ANN model with 12-6-8-1 structure is selected as the best one for predicting energy output. The correlation coefficient (R) varies from 0.524 to 0.999 in training for energy input and environmental impacts in ANN models. ANFIS model is developed based on a hybrid learning algorithm, with R for predicting output energy being 0.860 and, for environmental impacts, varying from 0.944 to 0.997. Results indicate that the multi-level ANFIS is a useful tool to managers for large-scale planning in forecasting energy output and environmental indices of agricultural production systems owing to its higher speed of computation processes compared to ANN model, despite ANN's higher accuracy. Copyright © 2018 Elsevier B.V. All rights reserved.
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2008-01-01
Gas exchange between the plant and the atmosphere is regulated by controlling both the stomatal density and the aperture of the stomatal pore. Environmental factors such as light, the level of atmospheric CO2 and hormones regulate stomatal development and/or function. Because atmospheric CO2 levels have been rising since the Industrial Revolution, and it is predicted that they will continue doing so in the future, an understanding of the CO2 signalling mechanisms in the stomatal responses will help to know how plants were in the past and will allow predicting how they will respond to climate change in the near future. This article covers the recent knowledge of the CO2 signalling mechanisms that regulate both stomatal function and development. PMID:19513216
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NASA Astrophysics Data System (ADS)
Kennard, M. J.; Pusey, B. J.; Arthington, A. H.
2005-05-01
North-eastern Australia encompasses 18o of latitude, monsoonal/tropical to sub-tropical/temperate climates, geomorphologically diverse rivers, and flow regimes with markedly varied seasonality, constancy and predictability. Fish assemblages in the region vary in relation to the predictability of aquatic habitat availability and other topographic, climatic and/or biogeographic factors. This paper examines how environmental, biogeographic and phylogenetic factors may constrain ecological trait composition at local and regional scales. We derived 17 categories of ecological traits to describe the morphology, behaviour, habitat, life history and trophic characteristics of 114 fish species from 64 river basins. Trait composition varied substantially across the region. The number of riffle dwelling species, maximum size and longevity of fishes was greater in the hydrologically predictable and constant rivers of the Wet Tropics region than in more unpredictable or seasonal environments. The importance of herbivory was also greater in the tropics. Historical biogeographic and phylogenetic factors may confound our ability to understand the role of environmental factors in determining spatial variation in ecological trait composition. Understanding the functional linkages between environmental drivers of fish species distributions via their ecological characteristics should provide a foundation for predicting future impacts of environmental change in a region of Australia subject to increasing human pressures.
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Bevelhimer, Mark S.; DeRolph, Christopher R.; Schramm, Michael P.
2016-06-06
Uncertainty about environmental mitigation needs at existing and proposed hydropower projects makes it difficult for stakeholders to minimize environmental impacts. Hydropower developers and operators desire tools to better anticipate mitigation requirements, while natural resource managers and regulators need tools to evaluate different mitigation scenarios and order effective mitigation. Here we sought to examine the feasibility of using a suite of multidisciplinary explanatory variables within a spatially explicit modeling framework to fit predictive models for future environmental mitigation requirements at hydropower projects across the conterminous U.S. Using a database comprised of mitigation requirements from more than 300 hydropower project licenses, wemore » were able to successfully fit models for nearly 50 types of environmental mitigation and to apply the predictive models to a set of more than 500 non-powered dams identified as having hydropower potential. The results demonstrate that mitigation requirements have been a result of a range of factors, from biological and hydrological to political and cultural. Furthermore, project developers can use these models to inform cost projections and design considerations, while regulators can use the models to more quickly identify likely environmental issues and potential solutions, hopefully resulting in more timely and more effective decisions on environmental mitigation.« less
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DeRolph, Christopher R; Schramm, Michael P; Bevelhimer, Mark S
2016-10-01
Uncertainty about environmental mitigation needs at existing and proposed hydropower projects makes it difficult for stakeholders to minimize environmental impacts. Hydropower developers and operators desire tools to better anticipate mitigation requirements, while natural resource managers and regulators need tools to evaluate different mitigation scenarios and order effective mitigation. Here we sought to examine the feasibility of using a suite of multi-faceted explanatory variables within a spatially explicit modeling framework to fit predictive models for future environmental mitigation requirements at hydropower projects across the conterminous U.S. Using a database comprised of mitigation requirements from more than 300 hydropower project licenses, we were able to successfully fit models for nearly 50 types of environmental mitigation and to apply the predictive models to a set of more than 500 non-powered dams identified as having hydropower potential. The results demonstrate that mitigation requirements are functions of a range of factors, from biophysical to socio-political. Project developers can use these models to inform cost projections and design considerations, while regulators can use the models to more quickly identify likely environmental issues and potential solutions, hopefully resulting in more timely and more effective decisions on environmental mitigation. Copyright © 2016 Elsevier B.V. All rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Bevelhimer, Mark S.; DeRolph, Christopher R.; Schramm, Michael P.
Uncertainty about environmental mitigation needs at existing and proposed hydropower projects makes it difficult for stakeholders to minimize environmental impacts. Hydropower developers and operators desire tools to better anticipate mitigation requirements, while natural resource managers and regulators need tools to evaluate different mitigation scenarios and order effective mitigation. Here we sought to examine the feasibility of using a suite of multidisciplinary explanatory variables within a spatially explicit modeling framework to fit predictive models for future environmental mitigation requirements at hydropower projects across the conterminous U.S. Using a database comprised of mitigation requirements from more than 300 hydropower project licenses, wemore » were able to successfully fit models for nearly 50 types of environmental mitigation and to apply the predictive models to a set of more than 500 non-powered dams identified as having hydropower potential. The results demonstrate that mitigation requirements have been a result of a range of factors, from biological and hydrological to political and cultural. Furthermore, project developers can use these models to inform cost projections and design considerations, while regulators can use the models to more quickly identify likely environmental issues and potential solutions, hopefully resulting in more timely and more effective decisions on environmental mitigation.« less
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Meersmans, Jeroen; Arrouays, Dominique; Van Rompaey, Anton J. J.; Pagé, Christian; De Baets, Sarah; Quine, Timothy A.
2016-01-01
Many studies have highlighted significant interactions between soil C reservoir dynamics and global climate and environmental change. However, in order to estimate the future soil organic carbon sequestration potential and related ecosystem services well, more spatially detailed predictions are needed. The present study made detailed predictions of future spatial evolution (at 250 m resolution) of topsoil SOC driven by climate change and land use change for France up to the year 2100 by taking interactions between climate, land use and soil type into account. We conclude that climate change will have a much bigger influence on future SOC losses in mid-latitude mineral soils than land use change dynamics. Hence, reducing CO2 emissions will be crucial to prevent further loss of carbon from our soils. PMID:27808169
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Meersmans, Jeroen; Arrouays, Dominique; Van Rompaey, Anton J J; Pagé, Christian; De Baets, Sarah; Quine, Timothy A
2016-11-03
Many studies have highlighted significant interactions between soil C reservoir dynamics and global climate and environmental change. However, in order to estimate the future soil organic carbon sequestration potential and related ecosystem services well, more spatially detailed predictions are needed. The present study made detailed predictions of future spatial evolution (at 250 m resolution) of topsoil SOC driven by climate change and land use change for France up to the year 2100 by taking interactions between climate, land use and soil type into account. We conclude that climate change will have a much bigger influence on future SOC losses in mid-latitude mineral soils than land use change dynamics. Hence, reducing CO 2 emissions will be crucial to prevent further loss of carbon from our soils.
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Disruption of the ‘disease triangle’ by chemical and physical environmental change
A. H. Chappelka; N. E. Grulke; L. De Kok
2015-01-01
The physical and chemical environment of the Earth has changed rapidly over the last 100 years and is predicted to continue to change into the foreseeable future. One of the main concerns with potential alterations in climate is the propensity for increases in the magnitude and frequency of extremes to occur. Even though precipitation is predicted to increase in some...
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A Golden Ticket to Future Occupational and Environmental Health Monitoring
2015-10-01
by the BE career field, an assessment of the regulatory monitoring requirements and current detection capabilities was critical . The next step in...research criteria due to the inability to predict the cost of production for these detection systems. Until a standardization of mass scale production...the health risk assessment process and is critical to keeping the base population safe from occupational and environmental exposures. The predominant
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Transgenerational plasticity and climate change experiments: Where do we go from here?
Donelson, Jennifer M; Salinas, Santiago; Munday, Philip L; Shama, Lisa N S
2018-01-01
Phenotypic plasticity, both within and across generations, is an important mechanism that organisms use to cope with rapid climate change. While an increasing number of studies show that plasticity across generations (transgenerational plasticity or TGP) may occur, we have limited understanding of key aspects of TGP, such as the environmental conditions that may promote it, its relationship to within-generation plasticity (WGP) and its role in evolutionary potential. In this review, we consider how the detection of TGP in climate change experiments is affected by the predictability of environmental variation, as well as the timing and magnitude of environmental change cues applied. We also discuss the need to design experiments that are able to distinguish TGP from selection and TGP from WGP in multigenerational experiments. We conclude by suggesting future research directions that build on the knowledge to date and admit the limitations that exist, which will depend on the way environmental change is simulated and the type of experimental design used. Such an approach will open up this burgeoning area of research to a wider variety of organisms and allow better predictive capacity of the role of TGP in the response of organisms to future climate change. © 2017 John Wiley & Sons Ltd.
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Molina-García, Javier; Castillo, Isabel; Pablos, Carlos
2009-05-01
Few studies analyze determinants and patterns of physical activity among college students, so it has not been possible to carry out effective interventions to promote this practice. The aim of this study was to analyze the associations between some personal, social, and environmental determinants, practice of physical activity and future intention to practice in a sample of 639 university students (321 men and 318 women), mean age 21.43 years (+/- 2.78). Physical fitness self-perception, physical activity history, and coach's support to practice physical activity have a direct effect on the practice of physical activity and an indirect effect on future intention to practice, both in men and women. The practice of physical activity has also a direct effect on future intention to practice. Likewise, the participation in sport competitions predicts practice of physical activity and future intention in men, whereas being a member of a sports club predicts practice and future intention in women.
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Time perspective and attitude-behaviour consistency in future-oriented behaviours.
Rabinovich, Anna; Morton, Thomas; Postmes, Tom
2010-03-01
The authors propose that the salience of a distant-future time perspective, compared to a near-future time perspective, should increase attitude-behaviour and attitude-intention consistency for future-oriented behaviours. To test this prediction, time perspective was experimentally manipulated in three studies. Across studies, participants in the distant-future time perspective condition demonstrated a strong positive relationship between attitudes towards future-oriented behaviours (saving and environmental protection) and corresponding intentions, as well as between attitudes and behaviour. In the near-future time perspective condition, the relationship between attitudes and intentions and attitudes and behaviour was significantly weaker than in the distant-future time perspective condition. The theoretical implications of these results and suggestions for future research are discussed.
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Gugger, Paul F; Liang, Christina T; Sork, Victoria L; Hodgskiss, Paul; Wright, Jessica W
2018-02-01
Identifying and quantifying the importance of environmental variables in structuring population genetic variation can help inform management decisions for conservation, restoration, or reforestation purposes, in both current and future environmental conditions. Landscape genomics offers a powerful approach for understanding the environmental factors that currently associate with genetic variation, and given those associations, where populations may be most vulnerable under future environmental change. Here, we applied genotyping by sequencing to generate over 11,000 single nucleotide polymorphisms from 311 trees and then used nonlinear, multivariate environmental association methods to examine spatial genetic structure and its association with environmental variation in an ecologically and economically important tree species endemic to Hawaii, Acacia koa . Admixture and principal components analyses showed that trees from different islands are genetically distinct in general, with the exception of some genotypes that match other islands, likely as the result of recent translocations. Gradient forest and generalized dissimilarity models both revealed a strong association between genetic structure and mean annual rainfall. Utilizing a model for projected future climate on the island of Hawaii, we show that predicted changes in rainfall patterns may result in genetic offset, such that trees no longer may be genetically matched to their environment. These findings indicate that knowledge of current and future rainfall gradients can provide valuable information for the conservation of existing populations and also help refine seed transfer guidelines for reforestation or replanting of koa throughout the state.
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Envirotyping for deciphering environmental impacts on crop plants.
Xu, Yunbi
2016-04-01
Global climate change imposes increasing impacts on our environments and crop production. To decipher environmental impacts on crop plants, the concept "envirotyping" is proposed, as a third "typing" technology, complementing with genotyping and phenotyping. Environmental factors can be collected through multiple environmental trials, geographic and soil information systems, measurement of soil and canopy properties, and evaluation of companion organisms. Envirotyping contributes to crop modeling and phenotype prediction through its functional components, including genotype-by-environment interaction (GEI), genes responsive to environmental signals, biotic and abiotic stresses, and integrative phenotyping. Envirotyping, driven by information and support systems, has a wide range of applications, including environmental characterization, GEI analysis, phenotype prediction, near-iso-environment construction, agronomic genomics, precision agriculture and breeding, and development of a four-dimensional profile of crop science involving genotype (G), phenotype (P), envirotype (E) and time (T) (developmental stage). In the future, envirotyping needs to zoom into specific experimental plots and individual plants, along with the development of high-throughput and precision envirotyping platforms, to integrate genotypic, phenotypic and envirotypic information for establishing a high-efficient precision breeding and sustainable crop production system based on deciphered environmental impacts.
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A methodology for post-EIS (environmental impact statement) monitoring
Marcus, Linda Graves
1979-01-01
A methodology for monitoring the impacts predicted in environmental impact statements (EIS's) was developed using the EIS on phosphate development in southeastern Idaho as a case study. A monitoring system based on this methodology: (1) coordinates a comprehensive, intergovernmental monitoring effort; (2) documents the major impacts that result, thereby improving the accuracy of impact predictions in future EIS's; (3) helps agencies control impacts by warning them when critical impact levels are reached and by providing feedback on the success of mitigating measures; and (4) limits monitoring data to the essential information that agencies need to carry out their regulatory and environmental protection responsibilities. The methodology is presented as flow charts accompanied by tables that describe the objectives, tasks, and products for each work element in the flow chart.
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UK Environmental Prediction - integration and evaluation at the convective scale
NASA Astrophysics Data System (ADS)
Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor
2016-04-01
It has long been understood that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. For example, high impact weather is typically manifested through various interactions and feedbacks between different components of the Earth System. Damaging high winds can lead to significant damage from the large waves and storm surge along coastlines. The impact of intense rainfall can be translated through saturated soils and land surface processes, high river flows and flooding inland. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system and discuss progress and initial results from further development to integrate wave interactions. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.
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Kodis, Mali'o; Galante, Peter; Sterling, Eleanor J; Blair, Mary E
2018-04-26
Under the threat of ongoing and projected climate change, communities in the Pacific Islands face challenges of adapting culture and lifestyle to accommodate a changing landscape. Few models can effectively predict how biocultural livelihoods might be impacted. Here, we examine how environmental and anthropogenic factors influence an ecological niche model (ENM) for the realized niche of cultivated taro (Colocasia esculenta) in Hawaii. We created and tuned two sets of ENMs: one using only environmental variables, and one using both environmental and cultural characteristics of Hawaii. These models were projected under two different Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) for 2070. Models were selected and evaluated using average omission rate and area under the receiver operating characteristic curve (AUC). We compared optimal model predictions by comparing the percentage of taro plots predicted present and measured ENM overlap using Schoener's D statistic. The model including only environmental variables consisted of 19 Worldclim bioclimatic variables, in addition to slope, altitude, distance to perennial streams, soil evaporation, and soil moisture. The optimal model with environmental variables plus anthropogenic features also included a road density variable (which we assumed as a proxy for urbanization) and a variable indicating agricultural lands of importance to the state of Hawaii. The model including anthropogenic features performed better than the environment-only model based on omission rate, AUC, and review of spatial projections. The two models also differed in spatial projections for taro under anticipated future climate change. Our results demonstrate how ENMs including anthropogenic features can predict which areas might be best suited to plant cultivated species in the future, and how these areas could change under various climate projections. These predictions might inform biocultural conservation priorities and initiatives. In addition, we discuss the incongruences that arise when traditional ENM theory is applied to species whose distribution has been significantly impacted by human intervention, particularly at a fine scale relevant to biocultural conservation initiatives. © 2018 by the Ecological Society of America.
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Beyond Climate and Weather Science: Expanding the Forecasting Family to Serve Societal Needs
NASA Astrophysics Data System (ADS)
Barron, E. J.
2009-05-01
The ability to "anticipate" the future is what makes information from the Earth sciences valuable to society - whether it is the prediction of severe weather or the future availability of water resources in response to climate change. An improved ability to anticipate or forecast has the potential to serve society by simultaneously improving our ability to (1) promote economic vitality, (2) enable environmental stewardship, (3) protect life and property, as well as (4) improve our fundamental knowledge of the earth system. The potential is enormous, yet many appear ready to move quickly toward specific mitigation and adaptation strategies assuming that the science is settled. Five important weakness must be addressed first: (1) the formation of a true "climate services" function and capability, (2) the deliberate investment in expanding the family of forecasting elements to incorporate a broader array of environmental factors and impacts, (3) the investment in the sciences that connect climate to society, (4) a deliberate focus on the problems associated with scale, in particular the difference between the scale of predictive models and the scale associated with societal decisions, and (5) the evolution from climate services and model predictions to the equivalent of "environmental intelligence centers." The objective is to bring the discipline of forecasting to a broader array of environmental challenges. Assessments of the potential impacts of global climate change on societal sectors such as water, human health, and agriculture provide good examples of this challenge. We have the potential to move from a largely reactive mode in addressing adverse health outcomes, for example, to one in which the ties between climate, land cover, infectious disease vectors, and human health are used to forecast and predict adverse human health conditions. The potential exists for a revolution in forecasting, that entrains a much broader set of societal needs and solutions. The argument is made that (for example) the current capabilities in the prediction of environmental health is similar to the capabilities (and potential) of weather forecasting in the 1960's.
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Seagrass meadows in a globally changing environment.
Unsworth, Richard K F; van Keulen, Mike; Coles, Rob G
2014-06-30
Seagrass meadows are valuable ecosystem service providers that are now being lost globally at an unprecedented rate, with water quality and other localised stressors putting their future viability in doubt. It is therefore critical that we learn more about the interactions between seagrass meadows and future environmental change in the anthropocene. This needs to be with particular reference to the consequences of poor water quality on ecosystem resilience and the effects of change on trophic interactions within the food web. Understanding and predicting the response of seagrass meadows to future environmental change requires an understanding of the natural long-term drivers of change and how these are currently influenced by anthropogenic stress. Conservation management of coastal and marine ecosystems now and in the future requires increased knowledge of how seagrass meadows respond to environmental change, and how they can be managed to be resilient to these changes. Finding solutions to such issues also requires recognising people as part of the social-ecological system. This special issue aims to further enhance this knowledge by bringing together global expertise across this field. The special issues considers issues such as ecosystem service delivery of seagrass meadows, the drivers of long-term seagrass change and the socio-economic consequences of environmental change to seagrass. Copyright © 2014 Elsevier Ltd. All rights reserved.
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AIR QUALITY MODELING OF HAZARDOUS POLLUTANTS: CURRENT STATUS AND FUTURE DIRECTIONS
The paper presents a review of current air toxics modeling applications and discusses possible advanced approaches. Many applications require the ability to predict hot spots from industrial sources or large roadways that are needed for community health and Environmental Justice...
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Statistical Accounting for Uncertainty in Modeling Transport in Environmental Systems
Models frequently are used to predict the future extent of ground-water contamination, given estimates of their input parameters and forcing functions. Although models have a well established scientific basis for understanding the interactions between complex phenomena and for g...
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Schwalm, Donelle; Epps, Clinton W; Rodhouse, Thomas J; Monahan, William B; Castillo, Jessica A; Ray, Chris; Jeffress, Mackenzie R
2016-04-01
Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas. © 2015 John Wiley & Sons Ltd.
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NASA Astrophysics Data System (ADS)
Plumlee, G. S.; Morman, S. A.; Alpers, C. N.; Hoefen, T. M.; Meeker, G. P.
2010-12-01
Disasters commonly pose immediate threats to human safety, but can also produce hazardous materials (HM) that pose short- and long-term environmental-health threats. The U.S. Geological Survey (USGS) has helped assess potential environmental health characteristics of HM produced by various natural and anthropogenic disasters, such as the 2001 World Trade Center collapse, 2005 hurricanes Katrina and Rita, 2007-2009 southern California wildfires, various volcanic eruptions, and others. Building upon experience gained from these responses, we are now developing methods to anticipate plausible environmental and health implications of the 2008 Great Southern California ShakeOut scenario (which modeled the impacts of a 7.8 magnitude earthquake on the southern San Andreas fault, http://urbanearth.gps.caltech.edu/scenario08/), and the recent ARkStorm scenario (modeling the impacts of a major, weeks-long winter storm hitting nearly all of California, http://urbanearth.gps.caltech.edu/winter-storm/). Environmental-health impacts of various past earthquakes and extreme storms are first used to identify plausible impacts that could be associated with the disaster scenarios. Substantial insights can then be gleaned using a Geographic Information Systems (GIS) approach to link ShakeOut and ARkStorm effects maps with data extracted from diverse database sources containing geologic, hazards, and environmental information. This type of analysis helps constrain where potential geogenic (natural) and anthropogenic sources of HM (and their likely types of contaminants or pathogens) fall within areas of predicted ShakeOut-related shaking, firestorms, and landslides, and predicted ARkStorm-related precipitation, flooding, and winds. Because of uncertainties in the event models and many uncertainties in the databases used (e.g., incorrect location information, lack of detailed information on specific facilities, etc.) this approach should only be considered as the first of multiple steps toward a more quantitative, predictive approach to understanding the potential sources, types, environmental behavior, and health implications of HM predicted to result from these disaster scenarios. Although only a first step, this qualitative approach will help enhance planning for, mitigation of, and resilience to environmental-health consequences of future disasters. This qualitative approach also requires careful communication to stakeholders that does not sensationalize or overstate potential problems, but rather conveys plausible impacts and next steps to improve understanding of potential risks and their mitigation.
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Parent–Child Injury Prevention Conversations Following a Trip to the Emergency Department
Plumert, Jodie M.; Peterson, Carole
2016-01-01
Objectives The goal of the study was to examine how parents use conversation to promote the internalization of safety values after their child has been seriously injured. Methods Parent interviews detailing postinjury conversations were coded for strategies mentioned to prevent injuries in the future and information about circumstances surrounding the injury. Results Logistic regression analyses revealed that parents were more likely to discuss why an activity was dangerous with older than younger children, and were more likely to urge daughters than sons to be more careful in the future. Injuries resulting from the presence of environmental hazards predicted parents telling children to be more careful in the future. Having others involved predicted parents urging children not to engage in the behavior again. Conclusions Findings suggest that parents modulated strategies according to age, gender, and injury circumstances to maximize the likelihood that children would behave differently in the future. PMID:26275976
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Stegen, James C.
2018-04-10
To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Stegen, James C.
To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less
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Stegen, James C
2018-01-01
To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.
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Dyer, Joseph J.; Brewer, Shannon K.; Worthington, Thomas A.; Bergey, Elizabeth A.
2013-01-01
1.A major limitation to effective management of narrow-range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2.Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate-change scenarios. 3.The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 6587% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4.Current models created using two spatial resolutions (1 and 4.5km2) showed that fine-resolution data more accurately represented current distributions. For three of the four species, the 1-km2 resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1-km2 resolution models were more accurate than 4.5-km2 resolution models. 5.Future projected (4.5-km2 resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low-emission scenario, whereas two of four species would be severely restricted in range under moderatehigh emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species-distribution models. 6.These model predictions illustrate possible impacts of climate change on narrow-range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.
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Defence mechanisms: the role of physiology in current and future environmental protection paradigms
Glover, Chris N
2018-01-01
Abstract Ecological risk assessments principally rely on simplified metrics of organismal sensitivity that do not consider mechanism or biological traits. As such, they are unable to adequately extrapolate from standard laboratory tests to real-world settings, and largely fail to account for the diversity of organisms and environmental variables that occur in natural environments. However, an understanding of how stressors influence organism health can compensate for these limitations. Mechanistic knowledge can be used to account for species differences in basal biological function and variability in environmental factors, including spatial and temporal changes in the chemical, physical and biological milieu. Consequently, physiological understanding of biological function, and how this is altered by stressor exposure, can facilitate proactive, predictive risk assessment. In this perspective article, existing frameworks that utilize physiological knowledge (e.g. biotic ligand models, adverse outcomes pathways and mechanistic effect models), are outlined, and specific examples of how mechanistic understanding has been used to predict risk are highlighted. Future research approaches and data needs for extending the incorporation of physiological information into ecological risk assessments are discussed. Although the review focuses on chemical toxicants in aquatic systems, physical and biological stressors and terrestrial environments are also briefly considered. PMID:29564135
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Genomic signals of selection predict climate-driven population declines in a migratory bird.
Bay, Rachael A; Harrigan, Ryan J; Underwood, Vinh Le; Gibbs, H Lisle; Smith, Thomas B; Ruegg, Kristen
2018-01-05
The ongoing loss of biodiversity caused by rapid climatic shifts requires accurate models for predicting species' responses. Despite evidence that evolutionary adaptation could mitigate climate change impacts, evolution is rarely integrated into predictive models. Integrating population genomics and environmental data, we identified genomic variation associated with climate across the breeding range of the migratory songbird, yellow warbler ( Setophaga petechia ). Populations requiring the greatest shifts in allele frequencies to keep pace with future climate change have experienced the largest population declines, suggesting that failure to adapt may have already negatively affected populations. Broadly, our study suggests that the integration of genomic adaptation can increase the accuracy of future species distribution models and ultimately guide more effective mitigation efforts. Copyright © 2018, American Association for the Advancement of Science.
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Xie, Yingying; Wang, Xiaojing; Silander, John A
2015-11-03
Changes in spring and autumn phenology of temperate plants in recent decades have become iconic bio-indicators of rapid climate change. These changes have substantial ecological and economic impacts. However, autumn phenology remains surprisingly little studied. Although the effects of unfavorable environmental conditions (e.g., frost, heat, wetness, and drought) on autumn phenology have been observed for over 60 y, how these factors interact to influence autumn phenological events remain poorly understood. Using remotely sensed phenology data from 2001 to 2012, this study identified and quantified significant effects of a suite of environmental factors on the timing of fall dormancy of deciduous forest communities in New England, United States. Cold, frost, and wet conditions, and high heat-stress tended to induce earlier dormancy of deciduous forests, whereas moderate heat- and drought-stress delayed dormancy. Deciduous forests in two eco-regions showed contrasting, nonlinear responses to variation in these explanatory factors. Based on future climate projection over two periods (2041-2050 and 2090-2099), later dormancy dates were predicted in northern areas. However, in coastal areas earlier dormancy dates were predicted. Our models suggest that besides warming in climate change, changes in frost and moisture conditions as well as extreme weather events (e.g., drought- and heat-stress, and flooding), should also be considered in future predictions of autumn phenology in temperate deciduous forests. This study improves our understanding of how multiple environmental variables interact to affect autumn phenology in temperate deciduous forest ecosystems, and points the way to building more mechanistic and predictive models.
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Practical implications for genetic modeling in the genomics era
USDA-ARS?s Scientific Manuscript database
Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...
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Villanueva, Paola A.; Lopez, Jorge; Torres, Rodrigo; Navarro, Jorge M.; Bacigalupe, Leonardo D.
2017-01-01
Phenotypic plasticity is expected to play a major adaptive role in the response of species to ocean acidification (OA), by providing broader tolerances to changes in pCO2 conditions. However, tolerances and sensitivities to future OA may differ among populations within a species because of their particular environmental context and genetic backgrounds. Here, using the climatic variability hypothesis (CVH), we explored this conceptual framework in populations of the sea urchin Loxechinus albus across natural fluctuating pCO2/pH environments. Although elevated pCO2 affected the morphology, physiology, development and survival of sea urchin larvae, the magnitude of these effects differed among populations. These differences were consistent with the predictions of the CVH showing greater tolerance to OA in populations experiencing greater local variation in seawater pCO2/pH. Considering geographical differences in plasticity, tolerances and sensitivities to increased pCO2 will provide more accurate predictions for species responses to future OA. PMID:28179409
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Gaitán-Espitia, Juan Diego; Villanueva, Paola A; Lopez, Jorge; Torres, Rodrigo; Navarro, Jorge M; Bacigalupe, Leonardo D
2017-02-01
Phenotypic plasticity is expected to play a major adaptive role in the response of species to ocean acidification (OA), by providing broader tolerances to changes in p CO 2 conditions. However, tolerances and sensitivities to future OA may differ among populations within a species because of their particular environmental context and genetic backgrounds. Here, using the climatic variability hypothesis (CVH), we explored this conceptual framework in populations of the sea urchin Loxechinus albus across natural fluctuating p CO 2 /pH environments. Although elevated p CO 2 affected the morphology, physiology, development and survival of sea urchin larvae, the magnitude of these effects differed among populations. These differences were consistent with the predictions of the CVH showing greater tolerance to OA in populations experiencing greater local variation in seawater p CO 2 /pH. Considering geographical differences in plasticity, tolerances and sensitivities to increased p CO 2 will provide more accurate predictions for species responses to future OA. © 2017 The Author(s).
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Environmental health impact assessment: evaluation of a ten-step model.
Fehr, R
1999-09-01
"Environmental impact assessment" denotes the attempt to predict and assess the impact of development projects on the environment. A component dealing specifically with human health is often called an "environmental health impact assessment." It is widely held that such impact assessment offers unique opportunities for the protection and promotion of human health. The following components were identified as key elements of an integrated environmental health impact assessment model: project analysis, analysis of status quo (including regional analysis, population analysis, and background situation), prediction of impact (including prognosis of future pollution and prognosis of health impact), assessment of impact, recommendations, communication of results, and evaluation of the overall procedure. The concept was applied to a project of extending a waste disposal facility and to a city bypass highway project. Currently, the coverage of human health aspects in environmental impact assessment still tends to be incomplete, and public health departments often do not participate. Environmental health impact assessment as a tool for health protection and promotion is underutilized. It would be useful to achieve consensus on a comprehensive generic concept. An international initiative to improve the situation seems worth some consideration.
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Prediction Accuracy of Error Rates for MPTB Space Experiment
NASA Technical Reports Server (NTRS)
Buchner, S. P.; Campbell, A. B.; Davis, D.; McMorrow, D.; Petersen, E. L.; Stassinopoulos, E. G.; Ritter, J. C.
1998-01-01
This paper addresses the accuracy of radiation-induced upset-rate predictions in space using the results of ground-based measurements together with standard environmental and device models. The study is focused on two part types - 16 Mb NEC DRAM's (UPD4216) and 1 Kb SRAM's (AMD93L422) - both of which are currently in space on board the Microelectronics and Photonics Test Bed (MPTB). To date, ground-based measurements of proton-induced single event upset (SEM cross sections as a function of energy have been obtained and combined with models of the proton environment to predict proton-induced error rates in space. The role played by uncertainties in the environmental models will be determined by comparing the modeled radiation environment with the actual environment measured aboard MPTB. Heavy-ion induced upsets have also been obtained from MPTB and will be compared with the "predicted" error rate following ground testing that will be done in the near future. These results should help identify sources of uncertainty in predictions of SEU rates in space.
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Thomassen, Henri A; Harrigan, Ryan J; Semple Delaney, Kathleen; Riley, Seth P D; Serieys, Laurel E K; Pease, Katherine; Wayne, Robert K; Smith, Thomas B
2018-02-01
Understanding the environmental contributors to population structure is of paramount importance for conservation in urbanized environments. We used spatially explicit models to determine genetic population structure under current and future environmental conditions across a highly fragmented, human-dominated environment in Southern California to assess the effects of natural ecological variation and urbanization. We focused on 7 common species with diverse habitat requirements, home-range sizes, and dispersal abilities. We quantified the relative roles of potential barriers, including natural environmental characteristics and an anthropogenic barrier created by a major highway, in shaping genetic variation. The ability to predict genetic variation in our models differed among species: 11-81% of intraspecific genetic variation was explained by environmental variables. Although an anthropogenically induced barrier (a major highway) severely restricted gene flow and movement at broad scales for some species, genetic variation seemed to be primarily driven by natural environmental heterogeneity at a local level. Our results show how assessing environmentally associated variation for multiple species under current and future climate conditions can help identify priority regions for maximizing population persistence under environmental change in urbanized regions. © 2017 Society for Conservation Biology.
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Modeling of rolling element bearing mechanics
NASA Technical Reports Server (NTRS)
Greenhill, L. M.
1991-01-01
Roller element bearings provide the primary mechanical interface between rotating and nonrotating components in the high performance turbomachinery of the Space Shuttle Main Engine (SSME). Knowledge of bearing behavior under various loading and environmental conditions is essential to predicting and understanding the overall behavior of turbopumps, including rotordynamic stability, critical speeds and bearing life. The objective is to develop mathematical models and computer programs to describe the mechanical behavior of ball and cylinder roller bearings under the loading and environmental conditions encountered in the SSME and future high performance rocket engines. This includes characteristics such as nonlinear load/motion relationships, stiffness and damping, rolling element loads for life prediction, and roller and cage stability.
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Global environmental change effects on ecosystems: the importance of land-use legacies.
Perring, Michael P; De Frenne, Pieter; Baeten, Lander; Maes, Sybryn L; Depauw, Leen; Blondeel, Haben; Carón, María M; Verheyen, Kris
2016-04-01
One of the major challenges in ecology is to predict how multiple global environmental changes will affect future ecosystem patterns (e.g. plant community composition) and processes (e.g. nutrient cycling). Here, we highlight arguments for the necessary inclusion of land-use legacies in this endeavour. Alterations in resources and conditions engendered by previous land use, together with influences on plant community processes such as dispersal, selection, drift and speciation, have steered communities and ecosystem functions onto trajectories of change. These trajectories may be modulated by contemporary environmental changes such as climate warming and nitrogen deposition. We performed a literature review which suggests that these potential interactions have rarely been investigated. This crucial oversight is potentially due to an assumption that knowledge of the contemporary state allows accurate projection into the future. Lessons from other complex dynamic systems, and the recent recognition of the importance of previous conditions in explaining contemporary and future ecosystem properties, demand the testing of this assumption. Vegetation resurvey databases across gradients of land use and environmental change, complemented by rigorous experiments, offer a means to test for interactions between land-use legacies and multiple environmental changes. Implementing these tests in the context of a trait-based framework will allow biologists to synthesize compositional and functional ecosystem responses. This will further our understanding of the importance of land-use legacies in determining future ecosystem properties, and soundly inform conservation and restoration management actions. © 2015 John Wiley & Sons Ltd.
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Antecedent conditions influence soil respiration differences in shrub and grass patches
USDA-ARS?s Scientific Manuscript database
Quantifying the response of soil respiration to past environmental conditions is critical for predicting how future climate and vegetation change will impact ecosystem carbon balance. Increased shrub dominance in semiarid grasslands has potentially large effects on soil carbon cycling. The goal of t...
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Predicting climate change impacts on polar bear litter size.
Molnár, Péter K; Derocher, Andrew E; Klanjscek, Tin; Lewis, Mark A
2011-02-08
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40-73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55-100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22-67% and 44-100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population.
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Predicting climate change impacts on polar bear litter size
Molnár, Péter K.; Derocher, Andrew E.; Klanjscek, Tin; Lewis, Mark A.
2011-01-01
Predicting the ecological impacts of climate warming is critical for species conservation. Incorporating future warming into population models, however, is challenging because reproduction and survival cannot be measured for yet unobserved environmental conditions. In this study, we use mechanistic energy budget models and data obtainable under current conditions to predict polar bear litter size under future conditions. In western Hudson Bay, we predict climate warming-induced litter size declines that jeopardize population viability: ∼28% of pregnant females failed to reproduce for energetic reasons during the early 1990s, but 40–73% could fail if spring sea ice break-up occurs 1 month earlier than during the 1990s, and 55–100% if break-up occurs 2 months earlier. Simultaneously, mean litter size would decrease by 22–67% and 44–100%, respectively. The expected timeline for these declines varies with climate-model-specific sea ice predictions. Similar litter size declines may occur in over one-third of the global polar bear population. PMID:21304515
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Menke, S.B.; Holway, D.A.; Fisher, R.N.; Jetz, W.
2009-01-01
Aim: Species distribution models (SDMs) or, more specifically, ecological niche models (ENMs) are a useful and rapidly proliferating tool in ecology and global change biology. ENMs attempt to capture associations between a species and its environment and are often used to draw biological inferences, to predict potential occurrences in unoccupied regions and to forecast future distributions under environmental change. The accuracy of ENMs, however, hinges critically on the quality of occurrence data. ENMs often use haphazardly collected data rather than data collected across the full spectrum of existing environmental conditions. Moreover, it remains unclear how processes affecting ENM predictions operate at different spatial scales. The scale (i.e. grain size) of analysis may be dictated more by the sampling regime than by biologically meaningful processes. The aim of our study is to jointly quantify how issues relating to region and scale affect ENM predictions using an economically important and ecologically damaging invasive species, the Argentine ant (Linepithema humile). Location: California, USA. Methods: We analysed the relationship between sampling sufficiency, regional differences in environmental parameter space and cell size of analysis and resampling environmental layers using two independently collected sets of presence/absence data. Differences in variable importance were determined using model averaging and logistic regression. Model accuracy was measured with area under the curve (AUC) and Cohen's kappa. Results: We first demonstrate that insufficient sampling of environmental parameter space can cause large errors in predicted distributions and biological interpretation. Models performed best when they were parametrized with data that sufficiently sampled environmental parameter space. Second, we show that altering the spatial grain of analysis changes the relative importance of different environmental variables. These changes apparently result from how environmental constraints and the sampling distributions of environmental variables change with spatial grain. Conclusions: These findings have clear relevance for biological inference. Taken together, our results illustrate potentially general limitations for ENMs, especially when such models are used to predict species occurrences in novel environments. We offer basic methodological and conceptual guidelines for appropriate sampling and scale matching. ?? 2009 The Authors Journal compilation ?? 2009 Blackwell Publishing.
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Prediction of future subsurface temperatures in Korea
NASA Astrophysics Data System (ADS)
Lee, Y.; Kim, S. K.; Jeong, J.; SHIN, E.
2017-12-01
The importance of climate change has been increasingly recognized because it has had the huge amount of impact on social, economic, and environmental aspect. For the reason, paleoclimate change has been studied intensively using different geological tools including borehole temperatures and future surface air temperatures (SATs) have been predicted for the local areas and the globe. Future subsurface temperatures can have also enormous impact on various areas and be predicted by an analytical method or a numerical simulation using measured and predicted SATs, and thermal diffusivity data of rocks. SATs have been measured at 73 meteorological observatories since 1907 in Korea and predicted at same locations up to the year of 2100. Measured SATs at the Seoul meteorological observatory increased by about 3.0 K from the year of 1907 to the present. Predicted SATs have 4 different scenarios depending on mainly CO2 concentration and national action plan on climate change in the future. The hottest scenario shows that SATs in Korea will increase by about 5.0 K from the present to the year of 2100. In addition, thermal diffusivity values have been measured on 2,903 rock samples collected from entire Korea. Data pretreatment based on autocorrelation analysis was conducted to control high frequency noise in thermal diffusivity data. Finally, future subsurface temperatures in Korea were predicted up to the year of 2100 by a FEM simulation code (COMSOL Multiphysics) using measured and predicted SATs, and thermal diffusivity data in Korea. At Seoul, the results of predictions show that subsurface temperatures will increase by about 5.4 K, 3.0 K, 1.5 K, and 0.2 K from the present to 2050 and then by about 7.9 K, 4.8 K, 2.5 K, and 0.5 K to 2100 at the depths of 10 m, 50 m, 100 m, and 200 m, respectively. We are now proceeding numerical simulations for subsurface temperature predictions for 73 locations in Korea.
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Impacts of West Nile Virus on wildlife
Saito, E.K.; Wild, M.A.
2004-01-01
The recent epidemic of West Nile virus in the United States proved to be unexpectedly active and was the largest epidemic of the virus ever recorded. Much remains to be discovered about the ecology and epidemiology of West Nile virus in the United States, including which species are important in maintaining the virus in nature, why some species are more susceptible to lethal infection, and what environmental factors are important in predicting future epidemics. These factors will likely vary regionally, depending on local ecological characteristics. Until scientists better understand the virus and factors influencing its activity, predicting its effects for future seasons is impossible. However, experts are certain about one thing: West Nile virus is here to stay.
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NASA Astrophysics Data System (ADS)
Rosner, A.; Letcher, B. H.; Vogel, R. M.
2014-12-01
Predicting streamflow in headwaters and over a broad spatial scale pose unique challenges due to limited data availability. Flow observation gages for headwaters streams are less common than for larger rivers, and gages with records lengths of ten year or more are even more scarce. Thus, there is a great need for estimating streamflows in ungaged or sparsely-gaged headwaters. Further, there is often insufficient basin information to develop rainfall-runoff models that could be used to predict future flows under various climate scenarios. Headwaters in the northeastern U.S. are of particular concern to aquatic biologists, as these stream serve as essential habitat for native coldwater fish. In order to understand fish response to past or future environmental drivers, estimates of seasonal streamflow are needed. While there is limited flow data, there is a wealth of data for historic weather conditions. Observed data has been modeled to interpolate a spatially continuous historic weather dataset. (Mauer et al 2002). We present a statistical model developed by pairing streamflow observations with precipitation and temperature information for the same and preceding time-steps. We demonstrate this model's use to predict flow metrics at the seasonal time-step. While not a physical model, this statistical model represents the weather drivers. Since this model can predict flows not directly tied to reference gages, we can generate flow estimates for historic as well as potential future conditions.
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Saupe, E. E.; Hendricks, J. R.; Portell, R. W.; Dowsett, H. J.; Haywood, A.; Hunter, S. J.; Lieberman, B. S.
2014-01-01
In order to predict the fate of biodiversity in a rapidly changing world, we must first understand how species adapt to new environmental conditions. The long-term evolutionary dynamics of species' physiological tolerances to differing climatic regimes remain obscure. Here, we unite palaeontological and neontological data to analyse whether species' environmental tolerances remain stable across 3 Myr of profound climatic changes using 10 phylogenetically, ecologically and developmentally diverse mollusc species from the Atlantic and Gulf Coastal Plains, USA. We additionally investigate whether these species' upper and lower thermal tolerances are constrained across this interval. We find that these species' environmental preferences are stable across the duration of their lifetimes, even when faced with significant environmental perturbations. The results suggest that species will respond to current and future warming either by altering distributions to track suitable habitat or, if the pace of change is too rapid, by going extinct. Our findings also support methods that project species' present-day environmental requirements to future climatic landscapes to assess conservation risks. PMID:25297868
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Saupe, E.E.; Hendricks, J.R.; Portell, R.W.; Dowsett, Harry J.; Haywood, A. M.; Hunter, S.J.; Lieberman, B.S.
2014-01-01
In order to predict the fate of biodiversity in a rapidly changing world, we must first understand how species adapt to new environmental conditions. The long-term evolutionary dynamics of species' physiological tolerances to differing climatic regimes remain obscure. Here, we unite palaeontological and neontological data to analyse whether species' environmental tolerances remain stable across 3 Myr of profound climatic changes using 10 phylogenetically, ecologically and developmentally diverse mollusc species from the Atlantic and Gulf Coastal Plains, USA. We additionally investigate whether these species' upper and lower thermal tolerances are constrained across this interval. We find that these species' environmental preferences are stable across the duration of their lifetimes, even when faced with significant environmental perturbations. The results suggest that species will respond to current and future warming either by altering distributions to track suitable habitat or, if the pace of change is too rapid, by going extinct. Our findings also support methods that project species' present-day environmental requirements to future climatic landscapes to assess conservation risks.
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Krinski, Kleverton; Machado, Daniel G S; Lirani, Luciana S; DaSilva, Sergio G; Costa, Eduardo C; Hardcastle, Sarah J; Elsangedy, Hassan M
2017-04-01
In order to examine whether environmental settings influence psychological and physiological responses of women with obesity during self-paced walking, 38 women performed two exercise sessions (treadmill and outdoors) for 30 min, where oxygen uptake, heart rate, ratings of perceived exertion, affect, attentional focus, enjoyment, and future intentions to walk were analyzed. Physiological responses were similar during both sessions. However, during outdoor exercise, participants displayed higher externally focused attention, positive affect, and lower ratings of perceived exertion, followed by greater enjoyment and future intention to participate in outdoor walking. The more externally focused attention predicted greater future intentions to participate in walking. Therefore, women with obesity self-selected an appropriate exercise intensity to improve fitness and health in both environmental settings. Also, self-paced outdoor walking presented improved psychological responses. Health care professionals should consider promoting outdoor forms of exercise to maximize psychological benefits and promote long-term adherence to a physically active lifestyle.
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Time perspective and environmental engagement: a meta-analysis.
Milfont, Taciano L; Wilson, Jessie; Diniz, Pollyane
2012-01-01
Environmental issues entail both a social conflict (private vs. public interests) and a temporal conflict (short- vs. long-term interests). This paper focuses on the role temporal concerns play in influencing environmental engagement by quantitatively integrating results of studies that assessed the associations between time perspective and proenvironmental attitudes and behaviors. The meta-analysis included a total of 19 independent samples and 6,301 participants from seven countries (Australia, Brazil, Germany, Mexico, New Zealand, Norway, and the United States). Results showed that the associations between time perspective and proenvironmental behaviors were higher than those for proenvironmental attitudes. Supporting predictions, the associations between future time perspective and proenvironmental behaviors were strong and nontrivial compared to those for the combined past-present time perspective. The findings indicate that future time perspective seems to play an important role in influencing individuals' attitudes and behaviors towards the environment. Implications of the findings for theory and practice are discussed.
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NASA Astrophysics Data System (ADS)
Zeng, Zhenzhong; Chen, Anping; Piao, Shilong; Rabin, Sam; Shen, Zehao
2014-07-01
The distributions of tropical ecosystems are rapidly being altered by climate change and anthropogenic activities. One possible trend—the loss of tropical forests and replacement by savannas—could result in significant shifts in ecosystem services and biodiversity loss. However, the influence and the relative importance of environmental factors in regulating the distribution of tropical forest and savanna biomes are still poorly understood, which makes it difficult to predict future tropical forest and savanna distributions in the context of climate change. Here we use boosted regression trees to quantitatively evaluate the importance of environmental predictors—mainly climatic, edaphic, and fire factors—for the tropical forest-savanna distribution at a mesoscale across the tropics (between 15°N and 35°S). Our results demonstrate that climate alone can explain most of the distribution of tropical forest and savanna at the scale considered; dry season average precipitation is the single most important determinant across tropical Asia-Australia, Africa, and South America. Given the strong tendency of increased seasonality and decreased dry season precipitation predicted by global climate models, we estimate that about 28% of what is now tropical forest would likely be lost to savanna by the late 21st century under the future scenario considered. This study highlights the importance of climate seasonality and interannual variability in predicting the distribution of tropical forest and savanna, supporting the climate as the primary driver in the savanna biogeography.
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Community dynamics and ecosystem simplification in a high-CO2 ocean.
Kroeker, Kristy J; Gambi, Maria Cristina; Micheli, Fiorenza
2013-07-30
Disturbances are natural features of ecosystems that promote variability in the community and ultimately maintain diversity. Although it is recognized that global change will affect environmental disturbance regimes, our understanding of the community dynamics governing ecosystem recovery and the maintenance of functional diversity in future scenarios is very limited. Here, we use one of the few ecosystems naturally exposed to future scenarios of environmental change to examine disturbance and recovery dynamics. We examine the recovery patterns of marine species from a physical disturbance across different acidification regimes caused by volcanic CO2 vents. Plots of shallow rocky reef were cleared of all species in areas of ambient, low, and extreme low pH that correspond to near-future and extreme scenarios for ocean acidification. Our results illustrate how acidification decreases the variability of communities, resulting in homogenization and reduced functional diversity at a landscape scale. Whereas the recovery trajectories in ambient pH were highly variable and resulted in a diverse range of assemblages, recovery was more predictable with acidification and consistently resulted in very similar algal-dominated assemblages. Furthermore, low pH zones had fewer signs of biological disturbance (primarily sea urchin grazing) and increased recovery rates of the dominant taxa (primarily fleshy algae). Together, our results highlight how environmental change can cause ecosystem simplification via environmentally mediated changes in community dynamics in the near future, with cascading impacts on functional diversity and ecosystem function.
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Environmental drivers of deadwood dynamics in woodlands and forests
M. Garbarino; R. Marzano; John Shaw; J. N. Long
2015-01-01
Deadwood dynamics play a key role in many forest ecosystems. Understanding the mechanisms involved in the accumulation and depletion of deadwood can enhance our understanding of fundamental processes such as carbon sequestration and disturbance regimes, allowing better predictions of future changes related to alternative management and climate scenarios. A...
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Practical implications for genetic modeling in the genomics era for the dairy industry
USDA-ARS?s Scientific Manuscript database
Genetic models convert data into estimated breeding values and other information useful to breeders. The goal is to provide accurate and timely predictions of the future performance for each animal (or embryo). Modeling involves defining traits, editing raw data, removing environmental effects, incl...
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Environmental Scan: A Strategic Planning Document.
ERIC Educational Resources Information Center
Osborn, Frances
Information, perceptions, and predictions from a variety of sources are brought together in this document to help guide planning and decision making at Monroe Community College (MCC). The first section examines national events and trends with implications for the future of MCC, including employment projections; educational norms; data on community…
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Marie Oliver; David W. Peterson; Becky Kerns
2016-01-01
Earth's climate is changing, as evidenced by warming temperatures, increased temperature variability, fluctuating precipitation patterns, and climate-related environmental disturbances. And with considerable uncertainty about the future, Forest Service land managers are now considering climate change adaptation in their planning efforts. They want practical...
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Branching out: Agroforestry as a climate change mitigation and adaptation tool for agriculture
USDA-ARS?s Scientific Manuscript database
The United States and Canadian agricultural lands are being targeted to provide more environmental and economic services while at the same time their capacity to provide these services under potential climate change (CC) is being questioned. Predictions of future climate conditions include longer gr...
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The Cornucopian Fallacies: The Myth of Perpetual Growth.
ERIC Educational Resources Information Center
Grant, Lindsey
1983-01-01
Julian Simon and Herman Kahn argue that population growth is good, not bad; they ignore or dismiss critical environmental issues. Fallacies in their arguments about predicting the future from the past, climate change, population growth, air quality, resource expansion, the finite earth, and technological growth are examined. (SR)
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The Response of Fish Habitat to Environmental Flows in the Albemarle-Pamlico Watershed
The provision of habitat for fish is an important service provided by rivers. Future land development and climate change will likely alter several aspects of habitat, including flow. We have used hierarchical models to predict the presence of 25 fish species within the Albemarle-...
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A Report by the Air Pollution Committee
ERIC Educational Resources Information Center
Kirkpatrick, Lane
1972-01-01
Description of a Symposium on Air Resource Protection and the Environment,'' held at the 1972 Environmental Health Conference and Exposition. Reports included a mathematical model for predicting future levels of air pollution, evaluation and identification of transportation controls, and a panel discussion of points raised by the speakers. (LK)
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Assessment of soil organic carbon stocks under future climate and land cover changes in Europe.
Yigini, Yusuf; Panagos, Panos
2016-07-01
Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950-2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
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UK Environmental Prediction - integration and evaluation at the convective scale
NASA Astrophysics Data System (ADS)
Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor
2016-04-01
Traditionally, the simulation of regional ocean, wave and atmosphere components of the Earth System have been considered separately, with some information on other components provided by means of boundary or forcing conditions. More recently, the potential value of a more integrated approach, as required for global climate and Earth System prediction, for regional short-term applications has begun to gain increasing research effort. In the UK, this activity is motivated by an understanding that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system, including a new eddy-permitting resolution ocean component, and discuss progress and initial results from further development to integrate wave interactions in this relatively high resolution system. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.
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Integrating geological archives and climate models for the mid-Pliocene warm period.
Haywood, Alan M; Dowsett, Harry J; Dolan, Aisling M
2016-02-16
The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change.
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Integrating geological archives and climate models for the mid-Pliocene warm period
Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.
2016-01-01
The mid-Pliocene Warm Period (mPWP) offers an opportunity to understand a warmer-than-present world and assess the predictive ability of numerical climate models. Environmental reconstruction and climate modelling are crucial for understanding the mPWP, and the synergy of these two, often disparate, fields has proven essential in confirming features of the past and in turn building confidence in projections of the future. The continual development of methodologies to better facilitate environmental synthesis and data/model comparison is essential, with recent work demonstrating that time-specific (time-slice) syntheses represent the next logical step in exploring climate change during the mPWP and realizing its potential as a test bed for understanding future climate change. PMID:26879640
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Ready or Not: Microbial Adaptive Responses in Dynamic Symbiosis Environments.
Cao, Mengyi; Goodrich-Blair, Heidi
2017-08-01
In mutually beneficial and pathogenic symbiotic associations, microbes must adapt to the host environment for optimal fitness. Both within an individual host and during transmission between hosts, microbes are exposed to temporal and spatial variation in environmental conditions. The phenomenon of phenotypic variation, in which different subpopulations of cells express distinctive and potentially adaptive characteristics, can contribute to microbial adaptation to a lifestyle that includes rapidly changing environments. The environments experienced by a symbiotic microbe during its life history can be erratic or predictable, and each can impact the evolution of adaptive responses. In particular, the predictability of a rhythmic or cyclical series of environments may promote the evolution of signal transduction cascades that allow preadaptive responses to environments that are likely to be encountered in the future, a phenomenon known as adaptive prediction. In this review, we summarize environmental variations known to occur in some well-studied models of symbiosis and how these may contribute to the evolution of microbial population heterogeneity and anticipatory behavior. We provide details about the symbiosis between Xenorhabdus bacteria and Steinernema nematodes as a model to investigate the concept of environmental adaptation and adaptive prediction in a microbial symbiosis. Copyright © 2017 American Society for Microbiology.
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Wang, Kai; Ye, Xiansen; Zhang, Huajun; Chen, Heping; Zhang, Demin; Liu, Lian
2016-01-01
Knowledge about the drivers of benthic prokaryotic diversity and metabolic potential in interconnected coastal sediments at regional scales is limited. We collected surface sediments across six zones covering ~200 km in coastal northern Zhejiang, East China Sea and combined 16 S rRNA gene sequencing, community-level metabolic prediction, and sediment physicochemical measurements to investigate variations in prokaryotic diversity and metabolic gene composition with geographic distance and under local environmental conditions. Geographic distance was the most influential factor in prokaryotic β-diversity compared with major environmental drivers, including temperature, sediment texture, acid-volatile sulfide, and water depth, but a large unexplained variation in community composition suggested the potential effects of unmeasured abiotic/biotic factors and stochastic processes. Moreover, prokaryotic assemblages showed a biogeographic provincialism across the zones. The predicted metabolic gene composition similarly shifted as taxonomic composition did. Acid-volatile sulfide was strongly correlated with variation in metabolic gene composition. The enrichments in the relative abundance of sulfate-reducing bacteria and genes relevant with dissimilatory sulfate reduction were observed and predicted, respectively, in the Yushan area. These results provide insights into the relative importance of geographic distance and environmental condition in driving benthic prokaryotic diversity in coastal areas and predict specific biogeochemically-relevant genes for future studies. PMID:27917954
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less
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Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.; ...
2017-07-26
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less
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NASA Astrophysics Data System (ADS)
Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.
2017-07-01
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
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Staunton, Kyran M; Robson, Simon K A; Burwell, Chris J; Reside, April E; Williams, Stephen E
2014-01-01
With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group's primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region.
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Staunton, Kyran M.; Robson, Simon K. A.; Burwell, Chris J.; Reside, April E.; Williams, Stephen E.
2014-01-01
With the impending threat of climate change, greater understanding of patterns of species distributions and richness and the environmental factors driving them are required for effective conservation efforts. Species distribution models enable us to not only estimate geographic extents of species and subsequent patterns of species richness, but also generate hypotheses regarding environmental factors determining these spatial patterns. Projected changes in climate can then be used to predict future patterns of species distributions and richness. We created distribution models for most of the flightless ground beetles (Carabidae) within the Wet Tropics World Heritage Area of Australia, a major component of regionally endemic invertebrates. Forty-three species were modelled and the environmental correlates of these distributions and resultant patterns of species richness were examined. Flightless ground beetles generally inhabit upland areas characterised by stable, cool and wet environmental conditions. These distribution and richness patterns are best explained using the time-stability hypothesis as this group’s primary habitat, upland rainforest, is considered to be the most stable regional habitat. Projected changes in distributions indicate that as upward shifts in distributions occur, species currently confined to lower and drier mountain ranges will be more vulnerable to climate change impacts than those restricted to the highest and wettest mountains. Distribution models under projected future climate change suggest that there will be reductions in range size, population size and species richness under all emission scenarios. Eighty-eight per cent of species modelled are predicted to decline in population size by over 80%, for the most severe emission scenario by the year 2080. These results suggest that flightless ground beetles are among the most vulnerable taxa to climate change impacts so far investigated in the Wet Tropics World Heritage Area. These findings have dramatic implications for all other flightless insect taxa and the future biodiversity of this region. PMID:24586362
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Impacts of Climate Change on the Global Invasion Potential of the African Clawed Frog Xenopus laevis
Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G. John; Lillo, Francesco; De Villiers, F. André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis
2016-01-01
By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species’ native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain. PMID:27248830
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Ihlow, Flora; Courant, Julien; Secondi, Jean; Herrel, Anthony; Rebelo, Rui; Measey, G John; Lillo, Francesco; De Villiers, F André; Vogt, Solveig; De Busschere, Charlotte; Backeljau, Thierry; Rödder, Dennis
2016-01-01
By altering or eliminating delicate ecological relationships, non-indigenous species are considered a major threat to biodiversity, as well as a driver of environmental change. Global climate change affects ecosystems and ecological communities, leading to changes in the phenology, geographic ranges, or population abundance of several species. Thus, predicting the impacts of global climate change on the current and future distribution of invasive species is an important subject in macroecological studies. The African clawed frog (Xenopus laevis), native to South Africa, possesses a strong invasion potential and populations have become established in numerous countries across four continents. The global invasion potential of X. laevis was assessed using correlative species distribution models (SDMs). SDMs were computed based on a comprehensive set of occurrence records covering South Africa, North America, South America and Europe and a set of nine environmental predictors. Models were built using both a maximum entropy model and an ensemble approach integrating eight algorithms. The future occurrence probabilities for X. laevis were subsequently computed using bioclimatic variables for 2070 following four different IPCC scenarios. Despite minor differences between the statistical approaches, both SDMs predict the future potential distribution of X. laevis, on a global scale, to decrease across all climate change scenarios. On a continental scale, both SDMs predict decreasing potential distributions in the species' native range in South Africa, as well as in the invaded areas in North and South America, and in Australia where the species has not been introduced. In contrast, both SDMs predict the potential range size to expand in Europe. Our results suggest that all probability classes will be equally affected by climate change. New regional conditions may promote new invasions or the spread of established invasive populations, especially in France and Great Britain.
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NASA Astrophysics Data System (ADS)
Wang, L.; Kerr, L. A.; Bridger, E.
2016-02-01
Changes in species distributions have been widely associated with climate change. Understanding how ocean temperatures influence species distributions is critical for elucidating the role of climate in ecosystem change as well as for forecasting how species may be distributed in the future. As such, species distribution modeling (SDM) is increasingly useful in marine ecosystems research, as it can enable estimation of the likelihood of encountering marine fish in space or time as a function of a set of environmental and ecosystem conditions. Many traditional SDM approaches are applied to species data collected through standardized methods that include both presence and absence records, but are incapable of using presence-only data, such as those collected from fisheries or through citizen science programs. Maximum entropy (MaxEnt) models provide promising tools as they can predict species distributions from incomplete information (presence-only data). We developed a MaxEnt framework to relate the occurrence records of several marine fish species (e.g. Atlantic herring, Atlantic mackerel, and butterfish) to environmental conditions. Environmental variables derived from remote sensing, such as monthly average sea surface temperature (SST), are matched with fish species data, and model results indicate the relative occurrence rate of the species as a function of the environmental variables. The results can be used to provide hindcasts of where species might have been in the past in relation to historical environmental conditions, nowcasts in relation to current conditions, and forecasts of future species distributions. In this presentation, we will assess the relative influence of several environmental factors on marine fish species distributions, and evaluate the effects of data coverage on these presence-only models. We will also discuss how the information from species distribution forecasts can support climate adaptation planning in marine fisheries.
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The Prehistory of Antibiotic Resistance.
Perry, Julie; Waglechner, Nicholas; Wright, Gerard
2016-06-01
Antibiotic resistance is a global problem that is reaching crisis levels. The global collection of resistance genes in clinical and environmental samples is the antibiotic "resistome," and is subject to the selective pressure of human activity. The origin of many modern resistance genes in pathogens is likely environmental bacteria, including antibiotic producing organisms that have existed for millennia. Recent work has uncovered resistance in ancient permafrost, isolated caves, and in human specimens preserved for hundreds of years. Together with bioinformatic analyses on modern-day sequences, these studies predict an ancient origin of resistance that long precedes the use of antibiotics in the clinic. Understanding the history of antibiotic resistance is important in predicting its future evolution. Copyright © 2016 Cold Spring Harbor Laboratory Press; all rights reserved.
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Future climate stimulates population out-breaks by relaxing constraints on reproduction.
Heldt, Katherine A; Connell, Sean D; Anderson, Kathryn; Russell, Bayden D; Munguia, Pablo
2016-09-14
When conditions are stressful, reproduction and population growth are reduced, but when favourable, reproduction and population size can boom. Theory suggests climate change is an increasingly stressful environment, predicting extinctions or decreased abundances. However, if favourable conditions align, such as an increase in resources or release from competition and predation, future climate can fuel population growth. Tests of such population growth models and the mechanisms by which they are enabled are rare. We tested whether intergenerational increases in population size might be facilitated by adjustments in reproductive success to favourable environmental conditions in a large-scale mesocosm experiment. Herbivorous amphipod populations responded to future climate by increasing 20 fold, suggesting that future climate might relax environmental constraints on fecundity. We then assessed whether future climate reduces variation in mating success, boosting population fecundity and size. The proportion of gravid females doubled, and variance in phenotypic variation of male secondary sexual characters (i.e. gnathopods) was significantly reduced. While future climate can enhance individual growth and survival, it may also reduce constraints on mechanisms of reproduction such that enhanced intra-generational productivity and reproductive success transfers to subsequent generations. Where both intra and intergenerational production is enhanced, population sizes might boom.
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Can future land use change be usefully predicted?
NASA Astrophysics Data System (ADS)
Ramankutty, N.; Coomes, O.
2011-12-01
There has been increasing recognition over the last decade that land use and land cover change is an important driver of global environmental change. Consequently, there have been growing efforts to understanding processes of land change from local-to-global scales, and to develop models to predict future changes in the land. However, we believe that such efforts are hampered by limited attention being paid to the critical points of land change. Here, we present a framework for understanding land use change by distinguishing within-regime land-use dynamics from land-use regime shifts. Illustrative historical examples reveal the significance of land-use regime shifts. We further argue that the land-use literature predominantly demonstrates a good understanding (with predictive power) of within-regime dynamics, while understanding of land-use regime shifts is limited to ex post facto explanations with limited predictive capability. The focus of land use change science needs to be redirected toward studying land-use regime shifts if we are to have any hope of making useful future projections. We present a preliminary framework for understanding land-use regime-shifts, using two case studies in Latin America as examples. We finally discuss the implications of our proposal for land change science.
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Modelling ecological systems in a changing world
Evans, Matthew R.
2012-01-01
The world is changing at an unprecedented rate. In such a situation, we need to understand the nature of the change and to make predictions about the way in which it might affect systems of interest; often we may also wish to understand what might be done to mitigate the predicted effects. In ecology, we usually make such predictions (or forecasts) by making use of mathematical models that describe the system and projecting them into the future, under changed conditions. Approaches emphasizing the desirability of simple models with analytical tractability and those that use assumed causal relationships derived statistically from data currently dominate ecological modelling. Although such models are excellent at describing the way in which a system has behaved, they are poor at predicting its future state, especially in novel conditions. In order to address questions about the impact of environmental change, and to understand what, if any, action might be taken to ameliorate it, ecologists need to develop the ability to project models into novel, future conditions. This will require the development of models based on understanding the processes that result in a system behaving the way it does, rather than relying on a description of the system, as a whole, remaining valid indefinitely. PMID:22144381
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Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jacobs, John M.; Rhodes, M.; Brown, C. W.
The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity aremore » capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.« less
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Biodiversity scenarios neglect future land-use changes.
Titeux, Nicolas; Henle, Klaus; Mihoub, Jean-Baptiste; Regos, Adrián; Geijzendorffer, Ilse R; Cramer, Wolfgang; Verburg, Peter H; Brotons, Lluís
2016-07-01
Efficient management of biodiversity requires a forward-looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land-use and land-cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land-use and land-cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward-looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge. © 2016 John Wiley & Sons Ltd.
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NASA Astrophysics Data System (ADS)
Shnoro, R. S.; Eicken, H.; Francis, J. A.; Scambos, T. A.; Schuur, E. A.; Straneo, F.; Wiggins, H. V.
2013-12-01
SEARCH is an interdisciplinary, interagency program that works with academic and government agency scientists and stakeholders to plan, conduct, and synthesize studies of Arctic change. Over the past three years, SEARCH has developed a new vision and mission, a set of prioritized cross-disciplinary 5-year goals, an integrated set of activities, and an organizational structure. The vision of SEARCH is to provide scientific understanding of arctic environmental change to help society understand and respond to a rapidly changing Arctic. SEARCH's 5-year science goals include: 1. Improve understanding, advance prediction, and explore consequences of changing Arctic sea ice. 2. Document and understand how degradation of near-surface permafrost will affect Arctic and global systems. 3. Improve predictions of future land-ice loss and impacts on sea level. 4. Analyze societal and policy implications of Arctic environmental change. Action Teams organized around each of the 5-year goals will serve as standing groups responsible for implementing specific goal activities. Members will be drawn from academia, different agencies and stakeholders, with a range of disciplinary backgrounds and perspectives. 'Arctic Futures 2050' scenarios tasks will describe plausible future states of the arctic system based on recent trajectories and projected changes. These scenarios will combine a range of data including climate model output, paleo-data, results from data synthesis and systems modeling, as well as expert scientific and traditional knowledge. Current activities include: - Arctic Observing Network (AON) - coordinating a system of atmospheric, land- and ocean-based environmental monitoring capabilities that will significantly advance our observations of arctic environmental conditions. - Arctic Sea Ice Outlook - an international effort that provides monthly summer reports synthesizing community estimates of the expected sea ice minimum. A newly-launched Sea Ice Prediction Network will create a network of scientists and stakeholders to generate, assess and communicate Arctic seasonal sea ice forecasts. - Collaboration with the Interagency Arctic Research Policy Committee (IARPC) to implement mutual science goals. SEARCH is sponsored by 8 U.S. agencies, including: the National Science Foundation, the National Oceanic and Atmospheric Administration, the National Aeronautics and Space Administration, the Department of Defense, the Department of Energy, the Department of the Interior, the Smithsonian Institution, and the U.S. Department of Agriculture. The U.S. Arctic Research Commission participates as an observer. For more information: http://www.arcus.org/search.
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Morello-Frosch, Rachel; Pastor, Manuel; Porras, Carlos; Sadd, James
2002-01-01
Environmental justice offers researchers new insights into the juncture of social inequality and public health and provides a framework for policy discussions on the impact of discrimination on the environmental health of diverse communities in the United States. Yet, causally linking the presence of potentially hazardous facilities or environmental pollution with adverse health effects is difficult, particularly in situations in which diverse populations are exposed to complex chemical mixtures. A community-academic research collaborative in southern California sought to address some of these methodological challenges by conducting environmental justice research that makes use of recent advances in air emissions inventories and air exposure modeling data. Results from several of our studies indicate that communities of color bear a disproportionate burden in the location of treatment, storage, and disposal facilities and Toxic Release Inventory facilities. Longitudinal analysis further suggests that facility siting in communities of color, not market-based "minority move-in," accounts for these disparities. The collaborative also investigated the health risk implications of outdoor air toxics exposures from mobile and stationary sources and found that race plays an explanatory role in predicting cancer risk distributions among populations in the region, even after controlling for other socioeconomic and demographic indicators. Although it is unclear whether study results from southern California can be meaningfully generalized to other regions in the United States, they do have implications for approaching future research in the realm of environmental justice. The authors propose a political economy and social inequality framework to guide future research that could better elucidate the origins of environmental inequality and reasons for its persistence. PMID:11929723
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Maximizing the Aviation Combat Element of the Future
2012-05-01
35 Table 3. Logistics Footprint Assesment : Courses of Action ................................................. 36...ships operating in a reduced stability status for the full range of environmental conditions in which they were tested.20 These findings predicted that...detachment of aircraft to the LPD in COA 4. Emphasis was placed on increasing operational footprint while minimizing operational impact of
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ERIC Educational Resources Information Center
Zhu, Chen; Rehrey, George; Treadwell, Brooke; Johnson, Claudia C.
2012-01-01
This Scholarship of Teaching and Learning project discusses the effectiveness of using distance metaphor-building activities along with a case study exam to help undergraduate nonscience majors understand and apply geologic time. Using action research, we describe how a scholarly teacher integrated previously published and often-used teaching…
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Ohio Environmental Education Areas.
ERIC Educational Resources Information Center
Melvin, Ruth W.
This is a guide to regional sites in Ohio which can be studied in regard to resource management; land use; the quality of air, water, soil; and reclamation. The first section of the guide includes brief descriptions of Ohio's natural features at the present time, accounts of past appearances and events, and predictions for the future. In the…
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High-order computational fluid dynamics tools for aircraft design
Wang, Z. J.
2014-01-01
Most forecasts predict an annual airline traffic growth rate between 4.5 and 5% in the foreseeable future. To sustain that growth, the environmental impact of aircraft cannot be ignored. Future aircraft must have much better fuel economy, dramatically less greenhouse gas emissions and noise, in addition to better performance. Many technical breakthroughs must take place to achieve the aggressive environmental goals set up by governments in North America and Europe. One of these breakthroughs will be physics-based, highly accurate and efficient computational fluid dynamics and aeroacoustics tools capable of predicting complex flows over the entire flight envelope and through an aircraft engine, and computing aircraft noise. Some of these flows are dominated by unsteady vortices of disparate scales, often highly turbulent, and they call for higher-order methods. As these tools will be integral components of a multi-disciplinary optimization environment, they must be efficient to impact design. Ultimately, the accuracy, efficiency, robustness, scalability and geometric flexibility will determine which methods will be adopted in the design process. This article explores these aspects and identifies pacing items. PMID:25024419
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NASA Astrophysics Data System (ADS)
Zamani Sabzi, H.; Moreno, H. A.; Neeson, T. M.; Rosendahl, D. H.; Bertrand, D.; Xue, X.; Hong, Y.; Kellog, W.; Mcpherson, R. A.; Hudson, C.; Austin, B. N.
2017-12-01
Previous periods of severe drought followed by exceptional flooding in the Red River Basin (RRB) have significantly affected industry, agriculture, and the environment in the region. Therefore, projecting how climate may change in the future and being prepared for potential impacts on the RRB is crucially important. In this study, we investigated the impacts of climate change on water availability across the RRB. We used three down-scaled global climate models and three potential greenhouse gas emission scenarios to assess precipitation, temperature, streamflow and lake levels throughout the RRB from 1961 to 2099 at a spatial resolution of 1/10°. Unit-area runoff and streamflow were obtained using the Variable Infiltration Capacity (VIC) model applied across the entire basin. We found that most models predict less precipitation in the western side of the basin and more in the eastern side. In terms of temperature, the models predict that average temperature could increase as much as 6°C. Most models project slightly more precipitation and streamflow values in the future, specifically in the eastern side of the basin. Finally, we analyzed the projected meteorological and hydrologic parameters alongside regional water demand for different sectors to identify the areas on the RRB that will need water-environmental conservation actions in the future. These hotspots of future low water availability are locations where regional environmental managers, water policy makers, and the agricultural and industrial sectors must proactively prepare to deal with declining water availability over the coming decades.
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NASA Technical Reports Server (NTRS)
Ward, Charles; Bravo, Jessica; De Luna, Rosalia; Lopez, Gerardo; Pichardo, Itza; Trejo, Danny; Vargas, Gabriel
1997-01-01
One of the research groups at the Pan American Center for Earth and Environmental Studies (PACES) is researching the northward migration path of Africanized Honey Bees or often referred to in the popular press as killer bees. The goal of the Killer Bee Research Group (KBRG) is to set up a database in the form of a geographical information system, which will be used to track and predict the bees future migration path. Included in this paper is background information on geographical information systems, the SPANS Explorer software package which was used to implement the database, and Advanced Very High Resolution Radiometer data and how each of these is being incorporated in the research. With an accurate means of predicting future migration paths, the negative effects of the Africanized honey bees maybe reduced.
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Genome analysis of Legionella pneumophila strains using a mixed-genome microarray.
Euser, Sjoerd M; Nagelkerke, Nico J; Schuren, Frank; Jansen, Ruud; Den Boer, Jeroen W
2012-01-01
Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.
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McCluney, Kevin E.; Belnap, Jayne; Collins, Scott L.; González, Angélica L.; Hagen, Elizabeth M.; Holland, J. Nathaniel; Kotler, Burt P.; Maestre, Fernando T.; Smith, Stanley D.; Wolf, Blair O.
2012-01-01
Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems.
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Iterative ecological forecasting: Needs, opportunities, and challenges
Dietze, Michael C.; Fox, Andrew; Betancourt, Julio L.; Hooten, Mevin B.; Jarnevich, Catherine S.; Keitt, Tim H.; Kenney, Melissa; Laney, Christine; Larsen, Laurel; Loescher, Henry W.; Lunch, Claire; Pijanowski, Bryan; Randerson, James T.; Read, Emily; Tredennick, Andrew T.; Weathers, Kathleen; White, Ethan P.
2016-01-01
A fundamental environmental challenge facing humanity in the 21st century and beyond is predicting the impacts of global environmental change. This challenge is complicated by the fact that we live on a non-stationary, unreplicated planet that is rapidly moving outside the envelope of natural variability into an historical non-analog world. In other words, while the past helps inform us about how the world has worked, it may no longer be the relevant frame of reference for management, conservation, and sustainability. In this future world the two questions at the foundation of sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect this trajectory?” These are, at their heart, questions about ecological forecasting.
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Blonder, Benjamin; Nogués-Bravo, David; Borregaard, Michael K; Donoghue, John C; Jørgensen, Peter M; Kraft, Nathan J B; Lessard, Jean-Philippe; Morueta-Holme, Naia; Sandel, Brody; Svenning, Jens-Christian; Violle, Cyrille; Rahbek, Carsten; Enquist, Brian J
2015-04-01
We present a framework to measure the strength of environmental filtering and disequilibrium of the species composition of a local community across time, relative to past, current, and future climates. We demonstrate the framework by measuring the impact of climate change on New World forests, integrating data for climate niches of more than 14000 species, community composition of 471 New World forest plots, and observed climate across the most recent glacial-interglacial interval. We show that a majority of communities have species compositions that are strongly filtered and are more in equilibrium with current climate than random samples from the regional pool. Variation in the level of current community disequilibrium can be predicted from Last Glacial Maximum climate and will increase with near-future climate change.
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Occupational physicians and environmental medicine
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ducatman, A.M.
1993-03-01
Physicians who practice environmental medicine seek to identify and to prevent patient and population exposures that cause adverse human health outcomes. Epidemiologic, toxicologic, clinical, and public health skills essential to this enterprise are indistinguishable from those of the occupational physician. Several important controversies illustrate the essential role of occupational physicians in environmental health science and policy, including environmental asbestos, dioxin, electromagnetic fields, and carcinogenicity testing. Our continuing involvement in environmental issues is predicted by three conditions, each unlikely to change. The human remains the animal of greatest interest; the natural experiment will have been performed (however unwittingly); and the workmore » site will continue to provide that first and clearest setting for measuring the outcome. Therefore, residency training must be expanded so that future occupational and environmental physicians will recognize their fundamental role in environmental health. The results of our industry cross factory walls with ease. So must our efforts.« less
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Current and Future Patterns of Global Marine Mammal Biodiversity
Kaschner, Kristin; Tittensor, Derek P.; Ready, Jonathan; Gerrodette, Tim; Worm, Boris
2011-01-01
Quantifying the spatial distribution of taxa is an important prerequisite for the preservation of biodiversity, and can provide a baseline against which to measure the impacts of climate change. Here we analyse patterns of marine mammal species richness based on predictions of global distributional ranges for 115 species, including all extant pinnipeds and cetaceans. We used an environmental suitability model specifically designed to address the paucity of distributional data for many marine mammal species. We generated richness patterns by overlaying predicted distributions for all species; these were then validated against sightings data from dedicated long-term surveys in the Eastern Tropical Pacific, the Northeast Atlantic and the Southern Ocean. Model outputs correlated well with empirically observed patterns of biodiversity in all three survey regions. Marine mammal richness was predicted to be highest in temperate waters of both hemispheres with distinct hotspots around New Zealand, Japan, Baja California, the Galapagos Islands, the Southeast Pacific, and the Southern Ocean. We then applied our model to explore potential changes in biodiversity under future perturbations of environmental conditions. Forward projections of biodiversity using an intermediate Intergovernmental Panel for Climate Change (IPCC) temperature scenario predicted that projected ocean warming and changes in sea ice cover until 2050 may have moderate effects on the spatial patterns of marine mammal richness. Increases in cetacean richness were predicted above 40° latitude in both hemispheres, while decreases in both pinniped and cetacean richness were expected at lower latitudes. Our results show how species distribution models can be applied to explore broad patterns of marine biodiversity worldwide for taxa for which limited distributional data are available. PMID:21625431
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NASA Technical Reports Server (NTRS)
Lee, Jae K.; Randolph, J. C.; Lulla, Kamlesh P.; Helfert, Michael R.
1993-01-01
Because changes in the Earth's environment have become major global issues, continuous, longterm scientific information is required to assess global problems such as deforestation, desertification, greenhouse effects and climate variations. Global change studies require understanding of interactions of complex processes regulating the Earth system. Space-based Earth observation is an essential element in global change research for documenting changes in Earth environment. It provides synoptic data for conceptual predictive modeling of future environmental change. This paper provides a brief overview of remote sensing technology from the perspective of global change research.
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Orsini, Luisa; Schwenk, Klaus; De Meester, Luc; Colbourne, John K.; Pfrender, Michael E.; Weider, Lawrence J.
2013-01-01
Evolutionary changes are determined by a complex assortment of ecological, demographic and adaptive histories. Predicting how evolution will shape the genetic structures of populations coping with current (and future) environmental challenges has principally relied on investigations through space, in lieu of time, because long-term phenotypic and molecular data are scarce. Yet, dormant propagules in sediments, soils and permafrost are convenient natural archives of population-histories from which to trace adaptive trajectories along extended time periods. DNA sequence data obtained from these natural archives, combined with pioneering methods for analyzing both ecological and population genomic time-series data, are likely to provide predictive models to forecast evolutionary responses of natural populations to environmental changes resulting from natural and anthropogenic stressors, including climate change. PMID:23395434
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Silva, Carmen; Cabral, João Alexandre; Hughes, Samantha Jane; Santos, Mário
2017-03-01
Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynamic methodology (StDM) principles, to predict bat activity on mountain ridges with wind farms. We illustrate the framework application using regional data from North Portugal by merging information from several environmental monitoring programmes associated with diverse wind energy facilities that enable integrating the multifactorial influences of meteorological conditions, land cover and geographical variables on bat activity patterns. Output from this innovative methodology can anticipate episodes of exceptional bat activity, which, if correlated with collision probability, can be used to guide wind farm management strategy such as halting wind turbines during hazardous periods. If properly calibrated with regional gradients of environmental variables from mountain ridges with windfarms, the proposed methodology can be used as a complementary tool in environmental impact assessments and ecological monitoring, using predicted bat activity to assist decision making concerning the future location of wind farms and the implementation of effective mitigation measures. Copyright © 2016 Elsevier B.V. All rights reserved.
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Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David
2012-01-01
Predicting the future spread of non-native aquatic species continues to be a high priority for natural resource managers striving to maintain biodiversity and ecosystem function. Modeling the potential distributions of alien aquatic species through spatially explicit mapping is an increasingly important tool for risk assessment and prediction. Habitat modeling also facilitates the identification of key environmental variables influencing species distributions. We modeled the potential distribution of an aggressive invasive minnow, the red shiner (Cyprinella lutrensis), in waterways of the conterminous United States using maximum entropy (Maxent). We used inventory records from the USGS Nonindigenous Aquatic Species Database, native records for C. lutrensis from museum collections, and a geographic information system of 20 raster climatic and environmental variables to produce a map of potential red shiner habitat. Summer climatic variables were the most important environmental predictors of C. lutrensis distribution, which was consistent with the high temperature tolerance of this species. Results from this study provide insights into the locations and environmental conditions in the US that are susceptible to red shiner invasion.
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Comparing methods for measuring the rate of spread of invading populations
Marius Gilbert; Andrew Liebhold
2010-01-01
Measuring rates of spread during biological invasions is important for predicting where and when invading organisms will spread in the future as well as for quantifying the influence of environmental conditions on invasion speed. While several methods have been proposed in the literature to measure spread rates, a comprehensive comparison of their accuracy when applied...
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Method and system for vehicle refueling
Surnilla, Gopichandra; Leone, Thomas G; Prasad, Krishnaswamy Venkatesh; Agarwal, Apoorv; Hinds, Brett Stanley
2014-06-10
Methods and systems are provided for facilitating refueling operations in vehicles operating with multiple fuels. A vehicle operator may be assisted in refueling the multiple fuel tanks of the vehicle by being provided one or more refueling profiles that take into account the vehicle's future trip plans, the predicted environmental conditions along a planned route, and the operator's preferences.
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M. Concilio; J. Chen; S. Ma; M. North
2009-01-01
Predictions of future climate change rely on models of how both environmental conditions and disturbance impact carbon cycling at various temporal and spatial scales. Few multi-year studies, however, have examined how carbon efflux is affected by the interaction of disturbance and interannual climate variation. We measured daytime soil respiration (R...
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Medium density fiberboards from plantation grown Eucalyptus saligna
Andrzej Krzysik; John A. Youngquist; James H. Muehl; Fabio Spina Franca
1999-01-01
The production of industrial wood from natural forests is predicted to decline in the future. Factors that will contribute to this decline include changes in land use patterns, depletion of resources in some parts of the world, and the withdrawal of forest areas from industrial production in order to provide for environmental, recreational, and other social needs....
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Method and system for vehicle refueling
Surnilla, Gopichandra; Leone, Thomas G; Prasad, Krishnaswamy Venkatesh; Argarwal, Apoorv; Hinds, Brett Stanley
2012-11-20
Methods and systems are provided for facilitating refueling operations in vehicles operating with multiple fuels. A vehicle operator may be assisted in refueling the multiple fuel tanks of the vehicle by being provided one or more refueling profiles that take into account the vehicle's future trip plans, the predicted environmental conditions along a planned route, and the operator's preferences.
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Applications of aerospace technology in the environmental sciences
NASA Technical Reports Server (NTRS)
1972-01-01
Detailed information is reported on the operations and accomplishments of the RTI Technology Application Team for the period October 11, 1971 to March 10, 1972. Mathematical models for prediction of pollutant formation during combustion are discussed along with generic areas of air pollution problems, which NASA technology offers a high potential for solving. Recommendations for future work are included.
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Techniques of data analysis and presentation for planners of the metropolitan environment
Joelee Normand
1977-01-01
Relationships between the characteristics of the physical environment of a metropolitan area and the activities of its human inhabitants can be used to predict probable future dynamic trends, both demographic and environmental. Using simple linear regression, we were able to highlight several dynamic features of the metropolitan area of Tulsa, Oklahoma. Computer movies...
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Federal Register 2010, 2011, 2012, 2013, 2014
2012-08-01
... regulations after they were implemented (ex post). To improve future benefit-cost analyses, EPA is seeking to compare its predictions of costs (ex ante costs) with actual (ex post) costs and, if they differ substantially, to understand why. EPA has requested the SAB's review of its approach to assessing ex post costs...
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Peter B. Woodbury; James E. Smith; David A. Weinstein; John A. Laurence
1998-01-01
Most models of the potential effects of climate change on forest growth have produced deterministic predictions. However, there are large uncertainties in data on regional forest condition, estimates of future climate, and quantitative relationships between environmental conditions and forest growth rate. We constructed a new model to analyze these uncertainties...
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Al-Kindi, Khalifa M.; Andrew, Nigel; Welch, Mitchell
2017-01-01
Date palm cultivation is economically important in the Sultanate of Oman, with significant financial investment coming from both the government and from private individuals. However, a global infestation of Dubas bug (Ommatissus lybicus Bergevin) has impacted the Middle East region, and infestations of date palms have been widespread. In this study, spatial analysis and geostatistical techniques were used to model the spatial distribution of Dubas bug infestations to (a) identify correlations between Dubas bug densities and different environmental variables, and (b) predict the locations of future Dubas bug infestations in Oman. Firstly, we considered individual environmental variables and their correlations with infestation locations. Then, we applied more complex predictive models and regression analysis techniques to investigate the combinations of environmental factors most conducive to the survival and spread of the Dubas bug. Environmental variables including elevation, geology, and distance to drainage pathways were found to significantly affect Dubas bug infestations. In contrast, aspect and hillshade did not significantly impact on Dubas bug infestations. Understanding their distribution and therefore applying targeted controls on their spread is important for effective mapping, control and management (e.g., resource allocation) of Dubas bug infestations. PMID:28558069
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Al-Kindi, Khalifa M; Kwan, Paul; Andrew, Nigel; Welch, Mitchell
2017-01-01
Date palm cultivation is economically important in the Sultanate of Oman, with significant financial investment coming from both the government and from private individuals. However, a global infestation of Dubas bug (Ommatissus lybicus Bergevin) has impacted the Middle East region, and infestations of date palms have been widespread. In this study, spatial analysis and geostatistical techniques were used to model the spatial distribution of Dubas bug infestations to (a) identify correlations between Dubas bug densities and different environmental variables, and (b) predict the locations of future Dubas bug infestations in Oman. Firstly, we considered individual environmental variables and their correlations with infestation locations. Then, we applied more complex predictive models and regression analysis techniques to investigate the combinations of environmental factors most conducive to the survival and spread of the Dubas bug. Environmental variables including elevation, geology, and distance to drainage pathways were found to significantly affect Dubas bug infestations. In contrast, aspect and hillshade did not significantly impact on Dubas bug infestations. Understanding their distribution and therefore applying targeted controls on their spread is important for effective mapping, control and management (e.g., resource allocation) of Dubas bug infestations.
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Chile confronts its environmental health future after 25 years of accelerated growth
Pino, Paulina; Iglesias, Verónica; Garreaud, René; Cortés, Sandra; Canals, Mauricio; Folch, Walter; Burgos, Soledad; Levy, Karen; Naeher, Luke P.; Steenland, Kyle
2015-01-01
Background Chile has recently been reclassified by the World Bank from an upper middle income country to a higher income country. There has been great progress in the last 20–30 years in relation to air and water pollution in Chile. Yet after 25 years of unrestrained growth there remain clear challenges posed by air and water, as well as climate change. Methods: In late 2013 a three-day workshop on environmental health was held in Santiago, bringing together researchers and government policy makers. As a follow-up to that workshop, here we review the progress made in environmental health in the past 20–30 years, and discuss the challenges of the future. We focus on air and water pollution, and climate change, which we believe are among the most important areas of environmental health in Chile. Results Air pollution in some cities remains among the highest in the continent. Potable water is generally available, but weak state supervision has led to serious outbreaks of infectious disease and ongoing issues with arsenic exposure in some regions. Climate change modeling in Chile is quite sophisticated, and a number of the impacts of climate change can be reasonably predicted in terms of which areas of the country are most likely to be affected by increased temperature and decreased availability of water, as well as expansion of vector territory. Some health effects, including change vector-borne diseases and excess heat mortality, can be predicted. However, there has yet to be an integration of such research with government planning. Conclusion While great progress has been made, currently there are a number of problems. We suspect that the Chilean experience in environmental health may be of some use for other Latin American countries with rapid economic development. PMID:26615070
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Current situation and future prospects for beef production in Europe.
Hocquette, Jean-Francois; Ellies-Oury, Marie-Pierre; Lherm, Michel; Pineau, Christele; Deblitz, Claus; Farmer, Linda
2018-05-24
The European Union (EU) is the world's third largest producer of beef. This contributes to the economy, rural development, social life, culture and gastronomy of Europe. The diversity of breeds, animal types (cows, bulls, steers, heifers) and farming systems (intensive, extensive on permanent or temporary pastures, mixed, breeders, feeders, etc) is a strength, and a weakness as the industry is often fragmented and poorly connected. There are also societal concerns regarding animal welfare and environmental issues, despite some positive environmental impacts of farming systems. The EU is amongst the most efficient for beef production as demonstrated by a relative low production of greenhouse gases. Due to regional differences in terms of climate, pasture availability, livestock practices and farms characteristics, productivity and incomes of beef producers vary widely across regions, being among the lowest of the agricultural systems. The beef industry is facing unprecedented challenges related to animal welfare, environmental impact, origin, authenticity, nutritional benefits and eating quality of beef. These may affect the whole industry, especially its farmers. It is therefore essential to bring the beef industry together to spread best practice and better exploit research in order to maintain and develop an economically viable and sustainable beef industry. Meeting consumers' expectations may be achieved by a better prediction of beef palatability using a modelling approach, such as in Australia. There is a need for accurate information and dissemination on the benefits and issues of beef for human health and for environmental impact. A better objective description of goods and services derived from livestock farming is also required. Putting into practice "agroecology" and organic farming principles are other potential avenues for the future. Different future scenarios can be written depending on the major driving forces, notably meat consumption, climate change, environmental policies and future organization of the supply chain.
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Towards Bridging the Gaps in Holistic Transition Prediction via Numerical Simulations
NASA Technical Reports Server (NTRS)
Choudhari, Meelan M.; Li, Fei; Duan, Lian; Chang, Chau-Lyan; Carpenter, Mark H.; Streett, Craig L.; Malik, Mujeeb R.
2013-01-01
The economic and environmental benefits of laminar flow technology via reduced fuel burn of subsonic and supersonic aircraft cannot be realized without minimizing the uncertainty in drag prediction in general and transition prediction in particular. Transition research under NASA's Aeronautical Sciences Project seeks to develop a validated set of variable fidelity prediction tools with known strengths and limitations, so as to enable "sufficiently" accurate transition prediction and practical transition control for future vehicle concepts. This paper provides a summary of selected research activities targeting the current gaps in high-fidelity transition prediction, specifically those related to the receptivity and laminar breakdown phases of crossflow induced transition in a subsonic swept-wing boundary layer. The results of direct numerical simulations are used to obtain an enhanced understanding of the laminar breakdown region as well as to validate reduced order prediction methods.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Pavlickova, Katarina; Vyskupova, Monika, E-mail: vyskupova@fns.uniba.sk
Cumulative environmental impact assessment deals with the occasional use in practical application of environmental impact assessment process. The main reasons are the difficulty of cumulative impact identification caused by lack of data, inability to measure the intensity and spatial effect of all types of impacts and the uncertainty of their future evolution. This work presents a method proposal to predict cumulative impacts on the basis of landscape vulnerability evaluation. For this purpose, qualitative assessment of landscape ecological stability is conducted and major vulnerability indicators of environmental and socio-economic receptors are specified and valuated. Potential cumulative impacts and the overall impactmore » significance are predicted quantitatively in modified Argonne multiple matrixes while considering the vulnerability of affected landscape receptors and the significance of impacts identified individually. The method was employed in the concrete environmental impact assessment process conducted in Slovakia. The results obtained in this case study reflect that this methodology is simple to apply, valid for all types of impacts and projects, inexpensive and not time-consuming. The objectivity of the partial methods used in this procedure is improved by quantitative landscape ecological stability evaluation, assignment of weights to vulnerability indicators based on the detailed characteristics of affected factors, and grading impact significance. - Highlights: • This paper suggests a method proposal for cumulative impact prediction. • The method includes landscape vulnerability evaluation. • The vulnerability of affected receptors is determined by their sensitivity. • This method can increase the objectivity of impact prediction in the EIA process.« less
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Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost
2012-02-01
We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.
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Urban, Mark C; De Meester, Luc; Vellend, Mark; Stoks, Robby; Vanoverbeke, Joost
2012-01-01
We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The ‘evolving metacommunity’ framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats. PMID:25568038
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NASA Astrophysics Data System (ADS)
Eyre, Bradley; McConchie, David
1993-05-01
Sedimentology is of increasing importance in environmental research, particularly environmental pollution studies, where past trends in environmental processes need to be combined with data on present conditions to predict likely future changes—the past and present as a key to the future. Two examples are used to illustrate the role of sedimentology in assessing the influence of major processes on the transport, accumulation, deposition and modification of contaminants in fluvial/estuarine systems and in developing environmental management plans. Example 1 shows that when assessing nutrient behaviour in fluvial/estuarine depositional settings, it is important to examine the partitioning of phosphorus between grain size fractions to evaluate the sedimentological processes which control the dispersion and trapping of these contaminants. Example 2 shows that in studies of anthropogenic metal inputs to modern depositional settings, lateral and stratigraphic trends in sediment texture and mineralogy should be examined, in addition to trends in metal loads and evaluation of the prevailing physical, chemical and biological processes that may influence metal mobility and dispersion. Clearly, basic sedimentological data should form part of any assessment of potentially contaminated sites and part of investigations into the dispersion and trapping of contaminants in fluvial systems. These data are also required for rational environmental management to ensure that planning decisions are compatible with natural environmental constraints.
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Predicting the geographical distribution of two invasive termite species from occurrence data.
Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H
2014-10-01
Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.
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,
1995-01-01
The Earth's global environment--its interrelated climate, land, oceans, fresh water, atmospheric and ecological systems-has changed continually throughout Earth history. Human activities are having ever-increasing effects on these systems. Sustaining our environment as population and demands for resources increase requires a sound understanding of the causes and cycles of natural change and the effects of human activities on the Earth's environmental systems. The U.S. Global Change Research Program was authorized by Congress in 1989 to provide the scientific understanding necessary to develop national and international policies concerning global environmental issues, particularly global climate change. The program addresses questions such as: what factors determine global climate; have humans already begun to change the global climate; will the climate of the future be very different; what will be the effects of climate change; and how much confidence do we have in our predictions? Through understanding, we can improve our capability to predict change, reduce the adverse effects of human activities, and plan strategies for adapting to natural and human-induced environmental change.
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Establishment of the Northeast Coastal Watershed Geospatial Data Network (NECWGDN)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hannigan, Robyn
The goals of NECWGDN were to establish integrated geospatial databases that interfaced with existing open-source (water.html) environmental data server technologies (e.g., HydroDesktop) and included ecological and human data to enable evaluation, prediction, and adaptation in coastal environments to climate- and human-induced threats to the coastal marine resources within the Gulf of Maine. We have completed the development and testing of a "test bed" architecture that is compatible with HydroDesktop and have identified key metadata structures that will enable seamless integration and delivery of environmental, ecological, and human data as well as models to predict threats to end-users. Uniquely this databasemore » integrates point as well as model data and so offers capacities to end-users that are unique among databases. Future efforts will focus on the development of integrated environmental-human dimension models that can serve, in near real time, visualizations of threats to coastal resources and habitats.« less
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Jones, Alice R; Bull, C Michael; Brook, Barry W; Wells, Konstans; Pollock, Kenneth H; Fordham, Damien A
2016-03-01
Assessing the impacts of multiple, often synergistic, stressors on the population dynamics of long-lived species is becoming increasingly important due to recent and future global change. Tiliqua rugosa (sleepy lizard) is a long-lived skink (>30 years) that is adapted to survive in semi-arid environments with varying levels of parasite exposure and highly seasonal food availability. We used an exhaustive database of 30 years of capture-mark-recapture records to quantify the impacts of both parasite exposure and environmental conditions on the lizard's survival rates and long-term population dynamics. Lizard abundance was relatively stable throughout the study period; however, there were changing patterns in adult and juvenile apparent survival rates, driven by spatial and temporal variation in levels of tick exposure and temporal variation in environmental conditions. Extreme weather events during the winter and spring seasons were identified as important environmental drivers of survival. Climate models predict a dramatic increase in the frequency of extreme hot and dry winter and spring seasons in our South Australian study region; from a contemporary probability of 0.17 up to 0.47-0.83 in 2080 depending on the emissions scenario. Our stochastic population model projections showed that these future climatic conditions will induce a decline in the abundance of this long-lived reptile of up to 67% within 30 years from 2080, under worst case scenario modelling. The results have broad implications for future work investigating the drivers of population dynamics and persistence. We highlight the importance of long-term data sets and accounting for synergistic impacts between multiple stressors. We show that predicted increases in the frequency of extreme climate events have the potential to considerably and negatively influence a long-lived species, which might previously have been assumed to be resilient to environmental perturbations. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.
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Parent-Child Injury Prevention Conversations Following a Trip to the Emergency Department.
O'Neal, Elizabeth E; Plumert, Jodie M; Peterson, Carole
2016-03-01
The goal of the study was to examine how parents use conversation to promote the internalization of safety values after their child has been seriously injured. Parent interviews detailing postinjury conversations were coded for strategies mentioned to prevent injuries in the future and information about circumstances surrounding the injury. Logistic regression analyses revealed that parents were more likely to discuss why an activity was dangerous with older than younger children, and were more likely to urge daughters than sons to be more careful in the future. Injuries resulting from the presence of environmental hazards predicted parents telling children to be more careful in the future. Having others involved predicted parents urging children not to engage in the behavior again. Findings suggest that parents modulated strategies according to age, gender, and injury circumstances to maximize the likelihood that children would behave differently in the future. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Road structural elements temperature trends diagnostics using sensory system of own design
NASA Astrophysics Data System (ADS)
Dudak, Juraj; Gaspar, Gabriel; Sedivy, Stefan; Pepucha, Lubomir; Florkova, Zuzana
2017-09-01
A considerable funds is spent for the roads maintenance in large areas during the winter. The road maintenance is significantly affected by the temperature change of the road structure. In remote locations may occur a situation, when it is not clear whether the sanding is actually needed because the lack of information on road conditions. In these cases, the actual road conditions are investigated by a personal inspection or by sending out a gritting vehicle. Here, however, is a risk of unnecessary trip the sanding vehicle. This situation is economically and environmentally unfavorable. The proposed system solves the problem of measuring the temperature profile of the road and the utilization of the predictive model to determine the future development trend of temperature. The system was technically designed as a set of sensors to monitor environmental values such as the temperature of the road, ambient temperature, relative air humidity, solar radiation and atmospheric pressure at the measuring point. An important part of the proposal is prediction model which based on the inputs from sensors and historical measurements can, with some probability, predict temperature trends at the measuring point. The proposed system addresses the economic and environmental aspects of winter road maintenance.
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Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans
Nolet, Bart A.; Gyimesi, Abel; van Krimpen, Roderick R. D.; de Boer, Willem F.; Stillman, Richard A.
2016-01-01
Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging coastal bird populations. How many birds make use of staging sites is mostly determined by food availability and accessibility, which in the case of many waterbirds in turn is affected by water level. Many water systems are regulated and water levels are maintained at target levels, set by management authorities. We used an individual-based modelling framework (MORPH) to analyse how different target water levels affect the number of migratory Bewick’s swans Cygnus columbianus bewickii staging at a shallow freshwater lake (Lauwersmeer, the Netherlands) in autumn. As an emerging property of the model, we found strong non-linear responses of swan usage to changes in water level, with a sudden drop in peak numbers as well as bird-days with a 0.20 m rise above the current target water level. Such strong non-linear responses are probably common and should be taken into account in environmental impact assessments. PMID:26862895
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Predicting Effects of Water Regime Changes on Waterbirds: Insights from Staging Swans.
Nolet, Bart A; Gyimesi, Abel; van Krimpen, Roderick R D; de Boer, Willem F; Stillman, Richard A
2016-01-01
Predicting the environmental impact of a proposed development is notoriously difficult, especially when future conditions fall outside the current range of conditions. Individual-based approaches have been developed and applied to predict the impact of environmental changes on wintering and staging coastal bird populations. How many birds make use of staging sites is mostly determined by food availability and accessibility, which in the case of many waterbirds in turn is affected by water level. Many water systems are regulated and water levels are maintained at target levels, set by management authorities. We used an individual-based modelling framework (MORPH) to analyse how different target water levels affect the number of migratory Bewick's swans Cygnus columbianus bewickii staging at a shallow freshwater lake (Lauwersmeer, the Netherlands) in autumn. As an emerging property of the model, we found strong non-linear responses of swan usage to changes in water level, with a sudden drop in peak numbers as well as bird-days with a 0.20 m rise above the current target water level. Such strong non-linear responses are probably common and should be taken into account in environmental impact assessments.
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Uncertainties in radiation effect predictions for the natural radiation environments of space.
McNulty, P J; Stassinopoulos, E G
1994-10-01
Future manned missions beyond low earth orbit require accurate predictions of the risk to astronauts and to critical systems from exposure to ionizing radiation. For low-level exposures, the hazards are dominated by rare single-event phenomena where individual cosmic-ray particles or spallation reactions result in potentially catastrophic changes in critical components. Examples might be a biological lesion leading to cancer in an astronaut or a memory upset leading to an undesired rocket firing. The risks of such events appears to depend on the amount of energy deposited within critical sensitive volumes of biological cells and microelectronic components. The critical environmental information needed to estimate the risks posed by the natural space environments, including solar flares, is the number of times more than a threshold amount of energy for an event will be deposited in the critical microvolumes. These predictions are complicated by uncertainties in the natural environments, particularly the composition of flares, and by the effects of shielding. Microdosimetric data for large numbers of orbits are needed to improve the environmental models and to test the transport codes used to predict event rates.
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Uncertainties in radiation effect predictions for the natural radiation environments of space
NASA Technical Reports Server (NTRS)
Mcnulty, P. J.; Stassinopoulos, E. G.
1994-01-01
Future manned missions beyond low earth orbit require accurate predictions of the risk to astronauts and to critical systems from exposure to ionizing radiation. For low-level exposures, the hazards are dominated by rare single-event phenomena where individual cosmic-ray particles or spallation reactions result in potentially catastrophic changes in critical components. Examples might be a biological lesion leading to cancer in an astronaut or a memory upset leading to an undesired rocket firing. The risks of such events appears to depend on the amount of energy deposited within critical sensitive volumes of biological cells and microelectronic components. The critical environmental information needed to estimate the risks posed by the natural space environments, including solar flares, is the number of times more than a threshold amount of energy for an event will be deposited in the critical microvolumes. These predictions are complicated by uncertainties in the natural environments, particularly the composition of flares, and by the effects of shielding. Microdosimetric data for large numbers of orbits are needed to improve the environmental models and to test the transport codes used to predict event rates.
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Satellite remote sensing, biodiversity research and conservation of the future
Pettorelli, Nathalie; Safi, Kamran; Turner, Woody
2014-01-01
Assessing and predicting ecosystem responses to global environmental change and its impacts on human well-being are high priority targets for the scientific community. The potential for synergies between remote sensing science and ecology, especially satellite remote sensing and conservation biology, has been highlighted by many in the past. Yet, the two research communities have only recently begun to coordinate their agendas. Such synchronization is the key to improving the potential for satellite data effectively to support future environmental management decision-making processes. With this themed issue, we aim to illustrate how integrating remote sensing into ecological research promotes a better understanding of the mechanisms shaping current changes in biodiversity patterns and improves conservation efforts. Added benefits include fostering innovation, generating new research directions in both disciplines and the development of new satellite remote sensing products. PMID:24733945
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Auralization Architectures for NASA?s Next Generation Aircraft Noise Prediction Program
NASA Technical Reports Server (NTRS)
Rizzi, Stephen A.; Lopes, Leonard V.; Burley, Casey L.; Aumann, Aric R.
2013-01-01
Aircraft community noise is a significant concern due to continued growth in air traffic, increasingly stringent environmental goals, and operational limitations imposed by airport authorities. The assessment of human response to noise from future aircraft can only be afforded through laboratory testing using simulated flyover noise. Recent work by the authors demonstrated the ability to auralize predicted flyover noise for a state-of-the-art reference aircraft and a future hybrid wing body aircraft concept. This auralization used source noise predictions from NASA's Aircraft NOise Prediction Program (ANOPP) as input. The results from this process demonstrated that auralization based upon system noise predictions is consistent with, and complementary to, system noise predictions alone. To further develop and validate the auralization process, improvements to the interfaces between the synthesis capability and the system noise tools are required. This paper describes the key elements required for accurate noise synthesis and introduces auralization architectures for use with the next-generation ANOPP (ANOPP2). The architectures are built around a new auralization library and its associated Application Programming Interface (API) that utilize ANOPP2 APIs to access data required for auralization. The architectures are designed to make the process of auralizing flyover noise a common element of system noise prediction.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Read, J.L.
1994-06-01
The merits of the fauna section of the Olympic Dam Project Environmental Impact Statement (EIS) are discussed. The values of different survey methods and monitoring organisms used in this document are evaluated following 10 years of fauna monitoring and research subsequent to the preparation of the EIS. The pilot fauna reconnaissance was found to be of little value, although the associated literature review formed an integral part of the EIS. Over 95% of all amphibian, reptile and bird species recorded at Olympic Dam were confirmed or predicted to occur in the EIS. Mammal predictions were less accurate because of themore » sparse populations and irruptive nature of several arid-zone species. Prediction and monitoring of rare species were demonstrably difficult. The Olympic Dam Project EIS was found in general to be an accurate and useful document. However, it is suggested that more emphasis be placed on establishing monitoring programmes for future EISs, particularly for invertebrates. 35 refs., 1 fig., 3 tabs.« less
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Using System Dynamic Model and Neural Network Model to Analyse Water Scarcity in Sudan
NASA Astrophysics Data System (ADS)
Li, Y.; Tang, C.; Xu, L.; Ye, S.
2017-07-01
Many parts of the world are facing the problem of Water Scarcity. Analysing Water Scarcity quantitatively is an important step to solve the problem. Water scarcity in a region is gauged by WSI (water scarcity index), which incorporate water supply and water demand. To get the WSI, Neural Network Model and SDM (System Dynamic Model) that depict how environmental and social factors affect water supply and demand are developed to depict how environmental and social factors affect water supply and demand. The uneven distribution of water resource and water demand across a region leads to an uneven distribution of WSI within this region. To predict WSI for the future, logistic model, Grey Prediction, and statistics are applied in predicting variables. Sudan suffers from severe water scarcity problem with WSI of 1 in 2014, water resource unevenly distributed. According to the result of modified model, after the intervention, Sudan’s water situation will become better.
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NASA Astrophysics Data System (ADS)
Cuyckens, G. A. E.; Christie, D. A.; Domic, A. I.; Malizia, L. R.; Renison, D.
2016-02-01
Climate change is becoming an increasing threat to biodiversity. Consequently, methods for delineation, establishment and management of protected areas must consider the species' future distribution in response to future climate conditions. Biodiversity in high altitude semiarid regions may be particularly threatened by future climate change. In this study we assess the main environmental variables that best explain present day presence of the world's highest elevation woodlands in the South American Altiplano, and model how climate change may affect the future distribution of this unique ecosystem under different climate change scenarios. These woodlands are dominated by Polylepis tarapacana (Rosaceae), a species that forms unique biological communities with important conservation value. Our results indicate that five environmental variables are responsible for 91% and 90.3% of the present and future P. tarapacana distribution models respectively, and suggest that at the end of the 21st century, there will be a significant reduction (56%) in the potential habitat for this species due to more arid conditions. Since it is predicted that P. tarapacana's potential distribution will be severely reduced in the future, we propose a new network of national protected areas across this species distribution range in order to insure the future conservation of this unique ecosystem. Based on an extensive literature review we identify research topics and recommendations for on-ground conservation and management of P. tarapacana woodlands.
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Oke, Tobi A; Hager, Heather A
2017-01-01
The fate of Northern peatlands under climate change is important because of their contribution to global carbon (C) storage. Peatlands are maintained via greater plant productivity (especially of Sphagnum species) than decomposition, and the processes involved are strongly mediated by climate. Although some studies predict that warming will relax constraints on decomposition, leading to decreased C sequestration, others predict increases in productivity and thus increases in C sequestration. We explored the lack of congruence between these predictions using single-species and integrated species distribution models as proxies for understanding the environmental correlates of North American Sphagnum peatland occurrence and how projected changes to the environment might influence these peatlands under climate change. Using Maximum entropy and BIOMOD modelling platforms, we generated single and integrated species distribution models for four common Sphagnum species in North America under current climate and a 2050 climate scenario projected by three general circulation models. We evaluated the environmental correlates of the models and explored the disparities in niche breadth, niche overlap, and climate suitability among current and future models. The models consistently show that Sphagnum peatland distribution is influenced by the balance between soil moisture deficit and temperature of the driest quarter-year. The models identify the east and west coasts of North America as the core climate space for Sphagnum peatland distribution. The models show that, at least in the immediate future, the area of suitable climate for Sphagnum peatland could expand. This result suggests that projected warming would be balanced effectively by the anticipated increase in precipitation, which would increase Sphagnum productivity.
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Oke, Tobi A.; Hager, Heather A.
2017-01-01
The fate of Northern peatlands under climate change is important because of their contribution to global carbon (C) storage. Peatlands are maintained via greater plant productivity (especially of Sphagnum species) than decomposition, and the processes involved are strongly mediated by climate. Although some studies predict that warming will relax constraints on decomposition, leading to decreased C sequestration, others predict increases in productivity and thus increases in C sequestration. We explored the lack of congruence between these predictions using single-species and integrated species distribution models as proxies for understanding the environmental correlates of North American Sphagnum peatland occurrence and how projected changes to the environment might influence these peatlands under climate change. Using Maximum entropy and BIOMOD modelling platforms, we generated single and integrated species distribution models for four common Sphagnum species in North America under current climate and a 2050 climate scenario projected by three general circulation models. We evaluated the environmental correlates of the models and explored the disparities in niche breadth, niche overlap, and climate suitability among current and future models. The models consistently show that Sphagnum peatland distribution is influenced by the balance between soil moisture deficit and temperature of the driest quarter-year. The models identify the east and west coasts of North America as the core climate space for Sphagnum peatland distribution. The models show that, at least in the immediate future, the area of suitable climate for Sphagnum peatland could expand. This result suggests that projected warming would be balanced effectively by the anticipated increase in precipitation, which would increase Sphagnum productivity. PMID:28426754
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Gómez Fernández, María Jimena; Boston, Emma S M; Gaggiotti, Oscar E; Kittlein, Marcelo J; Mirol, Patricia M
2016-12-01
In this study we combine information from landscape characteristics, demographic inference and species distribution modelling to identify environmental factors that shape the genetic distribution of the fossorial rodent Ctenomys. We sequenced the mtDNA control region and amplified 12 microsatellites from 27 populations distributed across the Iberá wetland ecosystem. Hierarchical Bayesian modelling was used to construct phylogenies and estimate divergence times. We developed species distribution models to determine what climatic variables and soil parameters predicted species presence by comparing the current to the historic and predicted future distribution of the species. Finally, we explore the impact of environmental variables on the genetic structure of Ctenomys based on current and past species distributions. The variables that consistently correlated with the predicted distribution of the species and explained the observed genetic differentiation among populations included the distribution of well-drained sandy soils and temperature seasonality. A core region of stable suitable habitat was identified from the Last Interglacial, which is projected to remain stable into the future. This region is also the most genetically diverse and is currently under strong anthropogenic pressure. Results reveal complex demographic dynamics, which have been in constant change in both time and space, and are likely linked to the evolution of the Paraná River. We suggest that any alteration of soil properties (climatic or anthropic) may significantly impact the availability of suitable habitat and consequently the ability of individuals to disperse. The protection of this core stable habitat is of prime importance given the increasing levels of human disturbance across this wetland system and the threat of climate change.
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Sarah Wilkinson; Jerome Ogee; Jean-Christophe Domec; Mark Rayment; Lisa Wingate
2015-01-01
Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus...
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Joseph A. E. Stewart; John D. Perrine; Lyle B. Nichols; James H. Thorne; Constance I. Millar; Kenneth E. Goehring; Cody P. Massing; David H. Wright; Brett Riddle
2015-01-01
Aim The American pika (Ochotona princeps) appears to have experienced climate mediated upslope range contraction in the Great Basin of North America, but this result has not yet been extended to other portions of the pikaâs range. Our goals were: first, to determine the environmental parameters that most influence...
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ERIC Educational Resources Information Center
Caplan, Joel M.; Kennedy, Leslie W.; Piza, Eric L.
2013-01-01
Violent crime incidents occurring in Irvington, New Jersey, in 2007 and 2008 are used to assess the joint analytical capabilities of point pattern analysis, hotspot mapping, near-repeat analysis, and risk terrain modeling. One approach to crime analysis suggests that the best way to predict future crime occurrence is to use past behavior, such as…
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Doctoral Social Work Education: Responding to Trends in Society and the Academy
ERIC Educational Resources Information Center
Cnaan, Ram A.; Ghose, Toorjo
2018-01-01
This article is intended to forecast major environmental changes that may impact social work doctoral education and assess what should be done in anticipation of these changes. We apply an open system and future studies perspective to guide our work. We present a set of predicted societal changes that will impact social work as a profession and…
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Global megatrends and their implications for environmental assessment practice
DOE Office of Scientific and Technical Information (OSTI.GOV)
Retief, Francois, E-mail: francois.retief@nwu.ac.za; Bond, Alan; Research Unit for Environmental Sciences and Management, North-West University
This paper addresses the future of environmental assessment (EA) practice in light of a rapidly changing world. We apply a literature review-based methodology to firstly identify key global megatrends and then reflect upon the implications for EA practice based on some known challenges. The key megatrends identified are synthesised into six categories: i) demographics, ii) urbanization, iii) technological innovation, iv) power shifts, v) resource scarcity and vi) climate change. We then discuss the implications of these megatrends for EA practice against four known EA challenges namely: dealing with i) complexity and uncertainty, ii) efficiency, iii) significance and iv) communication andmore » participation. Our analysis suggests important implications for EA practice such as: increased difficulties with accuracy of prediction; the need for facilitative adaptation; an increase in the occurrence of unexpected events; higher expectations for procedural efficiency; challenges with information and communication management; dealing with significance judgements; and mitigation amidst resource scarcity and increasing pressures on earth systems. The megatrends underscore the need for continued evolution of EA thinking and practice, especially moving away from seeking a predictable single future or outcome towards the possibility of multiple scenarios with associated adaptability and enhanced system resilience capable of responding to rapid change.« less
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Swartz, Johnna R; Knodt, Annchen R; Radtke, Spenser R; Hariri, Ahmad R
2018-01-31
We have previously reported that threat-related amygdala activity measured during a baseline fMRI scan predicts the experience of depression and anxiety associated with stressful life events years later. Here, we examine whether two broad measures of childhood environmental enrichment, namely parental educational achievement and subjective parental socioeconomic status, buffer against the effects of amygdala activity on future vulnerability to stress. Analyses of data available from 579 young adults revealed that maternal, but not paternal, educational achievement moderates the association between amygdala activity, recent life stress, and changes in mood and anxiety symptoms, even when controlling for participants' current subjective socioeconomic status. Specifically, only participants reporting lower maternal educational achievement exhibited our previously observed interaction between amygdala activity and future life stress predicting increases in depression and anxiety. These results suggest that higher maternal educational achievement may help buffer stress sensitivity associated with heightened threat-related amygdala activity. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Sheridan, Jennifer A; Caruso, Nicholas M; Apodaca, Joseph J; Rissler, Leslie J
2018-01-01
Changes in body size and breeding phenology have been identified as two major ecological consequences of climate change, yet it remains unclear whether climate acts directly or indirectly on these variables. To better understand the relationship between climate and ecological changes, it is necessary to determine environmental predictors of both size and phenology using data from prior to the onset of rapid climate warming, and then to examine spatially explicit changes in climate, size, and phenology, not just general spatial and temporal trends. We used 100 years of natural history collection data for the wood frog, Lithobates sylvaticus with a range >9 million km 2 , and spatially explicit environmental data to determine the best predictors of size and phenology prior to rapid climate warming (1901-1960). We then tested how closely size and phenology changes predicted by those environmental variables reflected actual changes from 1961 to 2000. Size, phenology, and climate all changed as expected (smaller, earlier, and warmer, respectively) at broad spatial scales across the entire study range. However, while spatially explicit changes in climate variables accurately predicted changes in phenology, they did not accurately predict size changes during recent climate change (1961-2000), contrary to expectations from numerous recent studies. Our results suggest that changes in climate are directly linked to observed phenological shifts. However, the mechanisms driving observed body size changes are yet to be determined, given the less straightforward relationship between size and climate factors examined in this study. We recommend that caution be used in "space-for-time" studies where measures of a species' traits at lower latitudes or elevations are considered representative of those under future projected climate conditions. Future studies should aim to determine mechanisms driving trends in phenology and body size, as well as the impact of climate on population density, which may influence body size.
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Stevens, Jeffrey R; Marewski, Julian N; Schooler, Lael J; Gilby, Ian C
2016-08-01
In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees ( Pan troglodytes ) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition.
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Reflections of the social environment in chimpanzee memory: applying rational analysis beyond humans
Marewski, Julian N.; Schooler, Lael J.; Gilby, Ian C.
2016-01-01
In cognitive science, the rational analysis framework allows modelling of how physical and social environments impose information-processing demands onto cognitive systems. In humans, for example, past social contact among individuals predicts their future contact with linear and power functions. These features of the human environment constrain the optimal way to remember information and probably shape how memory records are retained and retrieved. We offer a primer on how biologists can apply rational analysis to study animal behaviour. Using chimpanzees (Pan troglodytes) as a case study, we modelled 19 years of observational data on their social contact patterns. Much like humans, the frequency of past encounters in chimpanzees linearly predicted future encounters, and the recency of past encounters predicted future encounters with a power function. Consistent with the rational analyses carried out for human memory, these findings suggest that chimpanzee memory performance should reflect those environmental regularities. In re-analysing existing chimpanzee memory data, we found that chimpanzee memory patterns mirrored their social contact patterns. Our findings hint that human and chimpanzee memory systems may have evolved to solve similar information-processing problems. Overall, rational analysis offers novel theoretical and methodological avenues for the comparative study of cognition. PMID:27853606
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The power of connections: Psychological sense of community as a predictor of volunteerism.
Omoto, Allen M; Packard, Cody D
2016-01-01
Two studies explored psychological antecedents of volunteerism, including several dispositional constructs and psychological sense of community (PSOC). In Study 1, 140 retirees completed measures of empathy, self-esteem, generativity, and PSOC, as well as involvement in volunteer organizations and weekly volunteering hours at two points in time. PSOC predicted concurrent and future volunteerism even after controlling for the other predictors. In Study 2 (n = 427), PSOC and measures of environmental concern and connectedness were used to predict current environmental volunteerism and activism. PSOC was the only measure reliably and uniquely related to these behaviors. Across two different domains and operationalizations of PSOC, the findings support the validity and utility of PSOC for understanding general and issue-specific volunteerism. More generally, they highlight social relationships and psychological connections as potential pathways to volunteerism and social action.
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Evans, Matthew R.; Bithell, Mike; Cornell, Stephen J.; Dall, Sasha R. X.; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K. J.; Petchey, Owen; Smith, Matthew; Travis, Justin M. J.; Benton, Tim G.
2013-01-01
Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive. PMID:24089332
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Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G
2013-11-22
Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.
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Influence versus intent for predictive analytics in situation awareness
NASA Astrophysics Data System (ADS)
Cui, Biru; Yang, Shanchieh J.; Kadar, Ivan
2013-05-01
Predictive analytics in situation awareness requires an element to comprehend and anticipate potential adversary activities that might occur in the future. Most work in high level fusion or predictive analytics utilizes machine learning, pattern mining, Bayesian inference, and decision tree techniques to predict future actions or states. The emergence of social computing in broader contexts has drawn interests in bringing the hypotheses and techniques from social theory to algorithmic and computational settings for predictive analytics. This paper aims at answering the question on how influence and attitude (some interpreted such as intent) of adversarial actors can be formulated and computed algorithmically, as a higher level fusion process to provide predictions of future actions. The challenges in this interdisciplinary endeavor include drawing existing understanding of influence and attitude in both social science and computing fields, as well as the mathematical and computational formulation for the specific context of situation to be analyzed. The study of `influence' has resurfaced in recent years due to the emergence of social networks in the virtualized cyber world. Theoretical analysis and techniques developed in this area are discussed in this paper in the context of predictive analysis. Meanwhile, the notion of intent, or `attitude' using social theory terminologies, is a relatively uncharted area in the computing field. Note that a key objective of predictive analytics is to identify impending/planned attacks so their `impact' and `threat' can be prevented. In this spirit, indirect and direct observables are drawn and derived to infer the influence network and attitude to predict future threats. This work proposes an integrated framework that jointly assesses adversarial actors' influence network and their attitudes as a function of past actions and action outcomes. A preliminary set of algorithms are developed and tested using the Global Terrorism Database (GTD). Our results reveals the benefits to perform joint predictive analytics with both attitude and influence. At the same time, we discover significant challenges in deriving influence and attitude from indirect observables for diverse adversarial behavior. These observations warrant further investigation of optimal use of influence and attitude for predictive analytics, as well as the potential inclusion of other environmental or capability elements for the actors.
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Prospective time-resolved LCA of fully electric supercap vehicles in Germany.
Zimmermann, Benedikt M; Dura, Hanna; Baumann, Manuel J; Weil, Marcel R
2015-07-01
The ongoing transition of the German electricity supply toward a higher share of renewable and sustainable energy sources, called Energiewende in German, has led to dynamic changes in the environmental impact of electricity over the last few years. Prominent scenario studies predict that comparable dynamics will continue in the coming decades, which will further improve the environmental performance of Germany's electricity supply. Life cycle assessment (LCA) is the methodology commonly used to evaluate environmental performance. Previous LCA studies on electric vehicles have shown that the electricity supply for the vehicles' operation is responsible for the major part of their environmental impact. The core question of this study is how the prospective dynamic development of the German electricity mix will affect the impact of electric vehicles operated in Germany and how LCA can be adapted to analyze this impact in a more robust manner. The previously suggested approach of time-resolved LCA, which is located between static and dynamic LCA, is used in this study and compared with several static approaches. Furthermore, the uncertainty issue associated with scenario studies is addressed in general and in relation to time-resolved LCA. Two scenario studies relevant to policy making have been selected, but a moderate number of modifications have been necessary to adapt the data to the requirements of a life cycle inventory. A potential, fully electric vehicle powered by a supercapacitor energy storage system is used as a generic example. The results show that substantial improvements in the environmental repercussions of the electricity supply and, consequentially, of electric vehicles will be achieved between 2020 and 2031 on the basis of the energy mixes predicted in both studies. This study concludes that although scenarios might not be able to predict the future, they should nonetheless be used as data sources in prospective LCA studies, because in many cases historic data appears to be unsuitable for providing realistic information on the future. The time-resolved LCA approach improves the assessment's robustness substantially, especially when nonlinear developments are foreseen in the future scenarios. This allows for a reduction of bias in LCA-based decision making. However, a deeper integration of time-resolved data in the life cycle inventory and the implementation of a more suitable software framework are desirable. The study describes how life cycle assessment's (LCA) robustness can be improved by respecting prospective fluctuations, like the transition of the German electricity mix, in the modeling of the life cycle inventory. It presents a feasible and rather simple process to add time-resolved data to LCA. The study selects 2 different future scenarios from important German studies and processes their data systematically to make them compatible with the requirements of a life cycle inventory. The use of external scenarios as basis for future-oriented LCA is reflected critically. A case study on electric mobility is presented and used to compare historic, prospective static, and prospective time-resolved electricity mix modeling approaches. The case study emphasizes the benefits of time-resolved LCA in direct comparison with the currently used approaches. © 2015 SETAC.
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Hickey, Clayton; Peelen, Marius V
2017-08-02
Theories of reinforcement learning and approach behavior suggest that reward can increase the perceptual salience of environmental stimuli, ensuring that potential predictors of outcome are noticed in the future. However, outcome commonly follows visual processing of the environment, occurring even when potential reward cues have long disappeared. How can reward feedback retroactively cause now-absent stimuli to become attention-drawing in the future? One possibility is that reward and attention interact to prime lingering visual representations of attended stimuli that sustain through the interval separating stimulus and outcome. Here, we test this idea using multivariate pattern analysis of fMRI data collected from male and female humans. While in the scanner, participants searched for examples of target categories in briefly presented pictures of cityscapes and landscapes. Correct task performance was followed by reward feedback that could randomly have either high or low magnitude. Analysis showed that high-magnitude reward feedback boosted the lingering representation of target categories while reducing the representation of nontarget categories. The magnitude of this effect in each participant predicted the behavioral impact of reward on search performance in subsequent trials. Other analyses show that sensitivity to reward-as expressed in a personality questionnaire and in reactivity to reward feedback in the dopaminergic midbrain-predicted reward-elicited variance in lingering target and nontarget representations. Credit for rewarding outcome thus appears to be assigned to the target representation, causing the visual system to become sensitized for similar objects in the future. SIGNIFICANCE STATEMENT How do reward-predictive visual stimuli become salient and attention-drawing? In the real world, reward cues precede outcome and reward is commonly received long after potential predictors have disappeared. How can the representation of environmental stimuli be affected by outcome that occurs later in time? Here, we show that reward acts on lingering representations of environmental stimuli that sustain through the interval between stimulus and outcome. Using naturalistic scene stimuli and multivariate pattern analysis of fMRI data, we show that reward boosts the representation of attended objects and reduces the representation of unattended objects. This interaction of attention and reward processing acts to prime vision for stimuli that may serve to predict outcome. Copyright © 2017 the authors 0270-6474/17/377297-08$15.00/0.
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2012-01-01
Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154
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Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.
2013-01-01
Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820
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The UKC2 regional coupled environmental prediction system
NASA Astrophysics Data System (ADS)
Lewis, Huw W.; Castillo Sanchez, Juan Manuel; Graham, Jennifer; Saulter, Andrew; Bornemann, Jorge; Arnold, Alex; Fallmann, Joachim; Harris, Chris; Pearson, David; Ramsdale, Steven; Martínez-de la Torre, Alberto; Bricheno, Lucy; Blyth, Eleanor; Bell, Victoria A.; Davies, Helen; Marthews, Toby R.; O'Neill, Clare; Rumbold, Heather; O'Dea, Enda; Brereton, Ashley; Guihou, Karen; Hines, Adrian; Butenschon, Momme; Dadson, Simon J.; Palmer, Tamzin; Holt, Jason; Reynard, Nick; Best, Martin; Edwards, John; Siddorn, John
2018-01-01
It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere-land-ocean-wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed.
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Predictions of LDEF radioactivity and comparison with measurements
NASA Technical Reports Server (NTRS)
Armstrong, T. W.; Colborn, B. L.; Harmon, B. A.; Laird, C. E.
1995-01-01
As part of the program to utilize LDEF data for evaluation and improvement of current ionizing radiation environmental models and related predictive methods for future LEO missions, calculations have been carried out to compare with the induced radioactivity measured in metal samples placed on LDEF. The predicted activation is about a factor of two lower than observed, which is attributed to deficiencies in the AP8 trapped proton model. It is shown that this finding based on activation sample data is consistent with comparisons made with other LDEF activation and dose data. Plans for confirming these results utilizing additional LDEF data sets, and plans for model modifications to improve the agreement with LDEF data, are discussed.
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Environmental effects on the structure of the G-matrix.
Wood, Corlett W; Brodie, Edmund D
2015-11-01
Genetic correlations between traits determine the multivariate response to selection in the short term, and thereby play a causal role in evolutionary change. Although individual studies have documented environmentally induced changes in genetic correlations, the nature and extent of environmental effects on multivariate genetic architecture across species and environments remain largely uncharacterized. We reviewed the literature for estimates of the genetic variance-covariance (G) matrix in multiple environments, and compared differences in G between environments to the divergence in G between conspecific populations (measured in a common garden). We found that the predicted evolutionary trajectory differed as strongly between environments as it did between populations. Between-environment differences in the underlying structure of G (total genetic variance and the relative magnitude and orientation of genetic correlations) were equal to or greater than between-population differences. Neither environmental novelty, nor the difference in mean phenotype predicted these differences in G. Our results suggest that environmental effects on multivariate genetic architecture may be comparable to the divergence that accumulates over dozens or hundreds of generations between populations. We outline avenues of future research to address the limitations of existing data and characterize the extent to which lability in genetic correlations shapes evolution in changing environments. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
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Steen, Paul J.; Wiley, Michael J.; Schaeffer, Jeffrey S.
2010-01-01
Future alterations in land cover and climate are likely to cause substantial changes in the ranges of fish species. Predictive distribution models are an important tool for assessing the probability that these changes will cause increases or decreases in or the extirpation of species. Classification tree models that predict the probability of game fish presence were applied to the streams of the Muskegon River watershed, Michigan. The models were used to study three potential future scenarios: (1) land cover change only, (2) land cover change and a 3°C increase in air temperature by 2100, and (3) land cover change and a 5°C increase in air temperature by 2100. The analysis indicated that the expected change in air temperature and subsequent change in water temperatures would result in the decline of coldwater fish in the Muskegon watershed by the end of the 21st century while cool- and warmwater species would significantly increase their ranges. The greatest decline detected was a 90% reduction in the probability that brook trout Salvelinus fontinalis would occur in Bigelow Creek. The greatest increase was a 276% increase in the probability that northern pike Esox lucius would occur in the Middle Branch River. Changes in land cover are expected to cause large changes in a few fish species, such as walleye Sander vitreus and Chinook salmon Oncorhynchus tshawytscha, but not to drive major changes in species composition. Managers can alter stream environmental conditions to maximize the probability that species will reside in particular stream reaches through application of the classification tree models. Such models represent a good way to predict future changes, as they give quantitative estimates of the n-dimensional niches for particular species.
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Global Tree Range Shifts Under Forecasts from Two Alternative GCMs Using Two Future Scenarios
NASA Astrophysics Data System (ADS)
Hargrove, W. W.; Kumar, J.; Potter, K. M.; Hoffman, F. M.
2013-12-01
Global shifts in the environmentally suitable ranges of 215 tree species were predicted under forecasts from two GCMs (the Parallel Climate Model (PCM), and the Hadley Model), each under two IPCC future climatic scenarios (A1 and B1), each at two future dates (2050 and 2100). The analysis considers all global land surface at a resolution of 4 km2. A statistical multivariate clustering procedure was used to quantitatively delineate 30 thousand environmentally homogeneous ecoregions across present and 8 potential future global locations at once, using global maps of 17 environmental characteristics describing temperature, precipitation, soils, topography and solar insolation. Presence of each tree species on Forest Inventory Analysis (FIA) plots and in Global Biodiversity Information Facility (GBIF) samples was used to select a subset of suitable ecoregions from the full set of 30 thousand. Once identified, this suitable subset of ecoregions was compared to the known current range of the tree species under present conditions. Predicted present ranges correspond well with current understanding for all but a few of the 215 tree species. The subset of suitable ecoregions for each tree species can then be tracked into the future to determine whether the suitable home range for this species remains the same, moves, grows, shrinks, or disappears under each model/scenario combination. Occurrence and growth performance measurements for various tree species across the U.S. are limited to FIA plots. We present a new, general-purpose empirical imputation method which associates sparse measurements of dependent variables with particular multivariate clustered combinations of the independent variables, and then estimates values for unmeasured clusters, based on directional proximity in multidimensional data space, at both the cluster and map-cell levels of resolution. Using Associative Clustering, we scaled up the FIA point measurements into contonuous maps that show the expected growth and suitability for individual tree species across the continental US. Maps were generated for each tree species showing the Minimum Required Movement (MRM) straight-line distance from each currently suitable location to the geographically nearest "lifeboat" location having suitable conditions in the future. Locations that are the closest "lifeboats" for many MRM propagules originating from wide surrounding areas may constitute high-priority preservation targets as a refugium against climatic change.
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Chemical Risk Assessment: Traditional vs Public Health ...
Preventing adverse health impacts from exposures to environmental chemicals is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and impacts of environmentally-induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices (Birnbaum, Burke, & Jones, 2016) for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Given these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease. Preventing adverse health impacts from exposures to environmental chemicals is fundamental to protecting individual and public health. Chemical risk assessments
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Evolution and behavioural responses to human-induced rapid environmental change
Sih, Andrew; Ferrari, Maud C O; Harris, David J
2011-01-01
Almost all organisms live in environments that have been altered, to some degree, by human activities. Because behaviour mediates interactions between an individual and its environment, the ability of organisms to behave appropriately under these new conditions is crucial for determining their immediate success or failure in these modified environments. While hundreds of species are suffering dramatically from these environmental changes, others, such as urbanized and pest species, are doing better than ever. Our goal is to provide insights into explaining such variation. We first summarize the responses of some species to novel situations, including novel risks and resources, habitat loss/fragmentation, pollutants and climate change. Using a sensory ecology approach, we present a mechanistic framework for predicting variation in behavioural responses to environmental change, drawing from models of decision-making processes and an understanding of the selective background against which they evolved. Where immediate behavioural responses are inadequate, learning or evolutionary adaptation may prove useful, although these mechanisms are also constrained by evolutionary history. Although predicting the responses of species to environmental change is difficult, we highlight the need for a better understanding of the role of evolutionary history in shaping individuals’ responses to their environment and provide suggestion for future work. PMID:25567979
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Saelens, Brian E; Arteaga, S Sonia; Berrigan, David; Ballard, Rachel M; Gorin, Amy A; Powell-Wiley, Tiffany M; Pratt, Charlotte; Reedy, Jill; Zenk, Shannon N
2018-04-01
There is growing interest in how environment is related to adults' weight and activity and eating behaviors. However, little is known about whether environmental factors are related to the individual variability seen in adults' intentional weight loss or maintenance outcomes. The environmental domain subgroup of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project sought to identify a parsimonious set of objective and perceived neighborhood and social environment constructs and corresponding measures to include in the assessment of response to adult weight-loss treatment. Starting with the home address, the environmental domain subgroup recommended for inclusion in future weight-loss or maintenance studies constructs and measures related to walkability, perceived land use mix, food outlet accessibility (perceived and objective), perceived food availability, socioeconomics, and crime-related safety (perceived and objective) to characterize the home neighborhood environment. The subgroup also recommended constructs and measures related to social norms (perceived and objective) and perceived support to characterize an individual's social environment. The 12 neighborhood and social environment constructs and corresponding measures provide a succinct and comprehensive set to allow for more systematic examination of the impact of environment on adults' weight loss and maintenance. © 2018 The Obesity Society.
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Evolution and behavioural responses to human-induced rapid environmental change.
Sih, Andrew; Ferrari, Maud C O; Harris, David J
2011-03-01
Almost all organisms live in environments that have been altered, to some degree, by human activities. Because behaviour mediates interactions between an individual and its environment, the ability of organisms to behave appropriately under these new conditions is crucial for determining their immediate success or failure in these modified environments. While hundreds of species are suffering dramatically from these environmental changes, others, such as urbanized and pest species, are doing better than ever. Our goal is to provide insights into explaining such variation. We first summarize the responses of some species to novel situations, including novel risks and resources, habitat loss/fragmentation, pollutants and climate change. Using a sensory ecology approach, we present a mechanistic framework for predicting variation in behavioural responses to environmental change, drawing from models of decision-making processes and an understanding of the selective background against which they evolved. Where immediate behavioural responses are inadequate, learning or evolutionary adaptation may prove useful, although these mechanisms are also constrained by evolutionary history. Although predicting the responses of species to environmental change is difficult, we highlight the need for a better understanding of the role of evolutionary history in shaping individuals' responses to their environment and provide suggestion for future work.
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Ecological suitability modeling for anthrax in the Kruger National Park, South Africa.
Steenkamp, Pieter Johan; van Heerden, Henriette; van Schalkwyk, Ockert Louis
2018-01-01
The spores of the soil-borne bacterium, Bacillus anthracis, which causes anthrax are highly resistant to adverse environmental conditions. Under ideal conditions, anthrax spores can survive for many years in the soil. Anthrax is known to be endemic in the northern part of Kruger National Park (KNP) in South Africa (SA), with occasional epidemics spreading southward. The aim of this study was to identify and map areas that are ecologically suitable for the harboring of B. anthracis spores within the KNP. Anthrax surveillance data and selected environmental variables were used as inputs to the maximum entropy (Maxent) species distribution modeling method. Anthrax positive carcasses from 1988-2011 in KNP (n = 597) and a total of 40 environmental variables were used to predict and evaluate their relative contribution to suitability for anthrax occurrence in KNP. The environmental variables that contributed the most to the occurrence of anthrax were soil type, normalized difference vegetation index (NDVI) and precipitation. Apart from the endemic Pafuri region, several other areas within KNP were classified as ecologically suitable. The outputs of this study could guide future surveillance efforts to focus on predicted suitable areas for anthrax, since the KNP currently uses passive surveillance to detect anthrax outbreaks.
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Mass gathering medicine: a predictive model for patient presentation and transport rates.
Arbon, P; Bridgewater, F H; Smith, C
2001-01-01
This paper reports on research into the influence of environmental factors (including crowd size, temperature, humidity, and venue type) on the number of patients and the patient problems presenting to first-aid services at large, public events in Australia. Regression models were developed to predict rates of patient presentation and of transportation-to-a-hospital for future mass gatherings. To develop a data set and predictive model that can be applied across venues and types of mass gathering events that is not venue or event specific. Data collected will allow informed event planning for future mass gatherings for which health care services are required. Mass gatherings were defined as public events attended by in excess of 25,000 people. Over a period of 12 months, 201 mass gatherings attended by a combined audience in excess of 12 million people were surveyed throughout Australia. The survey was undertaken by St. John Ambulance Australia personnel. The researchers collected data on the incidence and type of patients presenting for treatment and on the environmental factors that may influence these presentations. A standard reporting format and definition of event geography was employed to overcome the event-specific nature of many previous surveys. There are 11,956 patients in the sample. The patient presentation rate across all event types was 0.992/1,000 attendees, and the transportation-to-hospital rate was 0.027/1,000 persons in attendance. The rates of patient presentations declined slightly as crowd sizes increased. The weather (particularly the relative humidity) was related positively to an increase in the rates of presentations. Other factors that influenced the number and type of patients presenting were the mobility of the crowd, the availability of alcohol, the event being enclosed by a boundary, and the number of patient-care personnel on duty. Three regression models were developed to predict presentation rates at future events. Several features of the event environment influence patient presentation rates, and that the prediction of patient load at these events is complex and multifactorial. The use of regression modeling and close attention to existing historical data for an event can improve planning and the provision of health care services at mass gatherings.
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Impact of European Union Legislation On The Wash Catchment, U.k.
NASA Astrophysics Data System (ADS)
Daldorph, P.; Wheater, H.; Saunders, A.
A case study is presented which shows the impact of existing European Legislation (Urban Waste Water Directive, Nitrate Directive, Bathing Waters Directive, Habitats Directive) on aquatic nutrient concentrations in the 16112 km2 catchment area of The Wash in eastern England , including both the inland and coastal zones. Information is provided on the implementation process (administrative and economic) and the observed impacts of measures to reduce environmental nutrient levels. Impacts are compared with simulations of nutrients in the inland and coastal zones, and the modeling tools are further used to predict impacts of future management change, e.g. to meet possible requirements of the Water Framework Directive. The issues in setting future environmental targets and research needs to underpin this process are discussed in the context of developing river basin management plans to support the Common Implementation Strategy for the Water Framework Directive.
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NASA Technical Reports Server (NTRS)
Campbell, Anthony B.; Nair, Satish S.; Miles, John B.; Iovine, John V.; Lin, Chin H.
1998-01-01
The present NASA space suit (the Shuttle EMU) is a self-contained environmental control system, providing life support, environmental protection, earth-like mobility, and communications. This study considers the thermal dynamics of the space suit as they relate to astronaut thermal comfort control. A detailed dynamic lumped capacitance thermal model of the present space suit is used to analyze the thermal dynamics of the suit with observations verified using experimental and flight data. Prior to using the model to define performance characteristics and limitations for the space suit, the model is first evaluated and improved. This evaluation includes determining the effect of various model parameters on model performance and quantifying various temperature prediction errors in terms of heat transfer and heat storage. The observations from this study are being utilized in two future design efforts, automatic thermal comfort control design for the present space suit and design of future space suit systems for Space Station, Lunar, and Martian missions.
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Wang, Wen J; He, Hong S; Thompson, Frank R; Spetich, Martin A; Fraser, Jacob S
2018-09-01
Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic controls, to simulate the distribution shifts of four representative tree species with distinct biological traits in the central hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200myear -1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and environmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribution shifts in response to changing climates. Copyright © 2018 Elsevier B.V. All rights reserved.
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Pathogenesis and Prediction of Future Rheumatoid Arthritis
2014-10-01
characterized by abnormalities of the immune system prior to the onset of the clinically apparent inflammatory joint disease that currently defines RA. The...the clinically apparent inflammatory joint disease that currently defines RA. The primary goal of this project is to investigate this preclinical...environmental exposures such as smoking, periodontal disease were ascertained. Goal 2. Local and governmental IRB approvals, and HRPO approval, were obtained
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Perspectives on the future of the electric utility industry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tonn, B.; Schaffhauser, A.
1994-04-01
This report offers perspectives on the future of the electric utility industry. These perspectives will be used in further research to assess the prospects for Integrated Resource Planning (IRP). The perspectives are developed first by examining economic, political and regulatory, societal, technological, and environmental trends that are (1) national and global in scope and (2) directly related to the electric utility industry. Major national and global trends include increasing global economic competition, increasing political and ethnic strife, rapidly changing technologies, and increasing worldwide concern about the environment. Major trends in the utility industry include increasing competition in generation; changing patternsmore » of electricity demand; increasing use of information technology to control power systems; and increasing implementation of environmental controls. Ways in which the national and global trends may directly affect the utility industry are also explored. The trends are used to construct three global and national scenarios- ``business as usual,`` ``technotopia future,`` and ``fortress state`` -and three electric utility scenarios- ``frozen in headlights,`` ``megaelectric,`` and ``discomania.`` The scenarios are designed to be thought provoking descriptions of potential futures, not predictions of the future, although three key variables are identified that will have significant impacts on which future evolves-global climate change, utility technologies, and competition. While emphasis needs to be placed on understanding the electric utility scenarios, the interactions between the two sets of scenarios is also of interest.« less
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Monitoring Urban Land Cover/land Use Change in Algiers City Using Landsat Images (1987-2016)
NASA Astrophysics Data System (ADS)
Bouchachi, B.; Zhong, Y.
2017-09-01
Monitoring the Urban Land Cover/Land Use change detection is important as one of the main driving forces of environmental change because Urbanization is the biggest changes in form of Land, resulting in a decrease in cultivated areas. Using remote sensing ability to solve land resources problems. The purpose of this research is to map the urban areas at different times to monitor and predict possible urban changes, were studied the annual growth urban land during the last 29 years in Algiers City. Improving the productiveness of long-term training in land mapping, were have developed an approach by the following steps: 1) pre-processing for improvement of image characteristics; 2) extract training sample candidates based on the developed methods; and 3) Derive maps and analyzed of Algiers City on an annual basis from 1987 to 2016 using a Supervised Classifier Support Vector Machine (SVMs). Our result shows that the strategy of urban land followed in the region of Algiers City, developed areas mostly were extended to East, West, and South of Central Regions. The urban growth rate is linked with National Office of Statistics data. Future studies are required to understand the impact of urban rapid lands on social, economy and environmental sustainability, it will also close the gap in data of urbanism available, especially on the lack of reliable data, environmental and urban planning for each municipality in Algiers, develop experimental models to predict future land changes with statistically significant confidence.
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Mo isotopes as redox indicators for the Southern Tethys during the PETM
NASA Astrophysics Data System (ADS)
Wouters, H.; Dickson, A.; Porcelli, D.; Hesselbo, S. P.; van den Boorn, S.; Gomez, V. G.; Mutterlose, J.
2014-12-01
As several ocean and climate models predict a decline in dissolved ocean oxygen concentrations associated with future global warming [1], recent research is increasingly focusing on past episodes of low ocean oxygen levels. Trace metals are generally enriched in organic-rich sediments deposited under such low oxygen conditions, and the concentration and isotopic signatures of several of these elements (e.g. Mo, U, Cr) may be applied as proxies to reconstruct the processes involved in these redox changes [2,3]. This project investigates the use of the molybdenum isotope system as a proxy for redox changes during an interval of abrupt environmental change spanning the Paleocene/Eocene boundary (the Paleocene/Eocene Thermal Maximum, PETM, ~56 Ma). The PETM is characterized by global warming and environmental and ecological changes including decreased ocean oxygen levels [4]. Study of the PETM can therefore offer us a valuable insight into how marine ecosystems and biogeochemical cycles may respond to future climate changes, and the predicted decrease of oxygen concentrations in seawater. The molybdenum concentrations and isotope compositions of organic-rich sediments spanning the PETM have been obtained from a Jordan oil shale drill core (OS-28). The obtained δ98/95Mo isotopic ratios range between -0.12‰ and 1.59‰ and coincide with significant fluctuations in trace metal abundances. The data together demonstrate that the global environmental changes associated with the PETM were manifest in the Jordanian basin as significant changes in basin hydrography and dissolved oxygen levels.
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McCluney, Kevin E; Belnap, Jayne; Collins, Scott L; González, Angélica L; Hagen, Elizabeth M; Nathaniel Holland, J; Kotler, Burt P; Maestre, Fernando T; Smith, Stanley D; Wolf, Blair O
2012-08-01
Species interactions play key roles in linking the responses of populations, communities, and ecosystems to environmental change. For instance, species interactions are an important determinant of the complexity of changes in trophic biomass with variation in resources. Water resources are a major driver of terrestrial ecology and climate change is expected to greatly alter the distribution of this critical resource. While previous studies have documented strong effects of global environmental change on species interactions in general, responses can vary from region to region. Dryland ecosystems occupy more than one-third of the Earth's land mass, are greatly affected by changes in water availability, and are predicted to be hotspots of climate change. Thus, it is imperative to understand the effects of environmental change on these globally significant ecosystems. Here, we review studies of the responses of population-level plant-plant, plant-herbivore, and predator-prey interactions to changes in water availability in dryland environments in order to develop new hypotheses and predictions to guide future research. To help explain patterns of interaction outcomes, we developed a conceptual model that views interaction outcomes as shifting between (1) competition and facilitation (plant-plant), (2) herbivory, neutralism, or mutualism (plant-herbivore), or (3) neutralism and predation (predator-prey), as water availability crosses physiological, behavioural, or population-density thresholds. We link our conceptual model to hypothetical scenarios of current and future water availability to make testable predictions about the influence of changes in water availability on species interactions. We also examine potential implications of our conceptual model for the relative importance of top-down effects and the linearity of patterns of change in trophic biomass with changes in water availability. Finally, we highlight key research needs and some possible broader impacts of our findings. Overall, we hope to stimulate and guide future research that links changes in water availability to patterns of species interactions and the dynamics of populations and communities in dryland ecosystems. © 2011 The Authors. Biological Reviews © 2011 Cambridge Philosophical Society.
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NASA Technical Reports Server (NTRS)
2002-01-01
The air on this mostly sunny January day is crisp and the wind is blustery. The morning's National Weather Service 6-hour forecast had accurately predicted these conditions for the Baltimore-Washington area and the 2-3 day extended outlook was almost perfect. The previous week, the National Center for Environmental Prediction's (NCEP) 6-10 day temperature and precipitation outlook for the general trends for the' region was correct as well. However, no forecast could have predicted specific details about this day. It is 28.5 F in the sunshine bright enough for dark sunglasses, and windy enough to blow off a hat. Such details are impossible to foresee with any accuracy and are outside the scope of routine weather prediction. Equally difficult is accurately forecasting weather beyond about 2 weeks.
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Zoonosis emergence linked to agricultural intensification and environmental change.
Jones, Bryony A; Grace, Delia; Kock, Richard; Alonso, Silvia; Rushton, Jonathan; Said, Mohammed Y; McKeever, Declan; Mutua, Florence; Young, Jarrah; McDermott, John; Pfeiffer, Dirk Udo
2013-05-21
A systematic review was conducted by a multidisciplinary team to analyze qualitatively best available scientific evidence on the effect of agricultural intensification and environmental changes on the risk of zoonoses for which there are epidemiological interactions between wildlife and livestock. The study found several examples in which agricultural intensification and/or environmental change were associated with an increased risk of zoonotic disease emergence, driven by the impact of an expanding human population and changing human behavior on the environment. We conclude that the rate of future zoonotic disease emergence or reemergence will be closely linked to the evolution of the agriculture-environment nexus. However, available research inadequately addresses the complexity and interrelatedness of environmental, biological, economic, and social dimensions of zoonotic pathogen emergence, which significantly limits our ability to predict, prevent, and respond to zoonotic disease emergence.
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Arciszewski, Tim J; Munkittrick, Kelly R; Scrimgeour, Garry J; Dubé, Monique G; Wrona, Fred J; Hazewinkel, Rod R
2017-09-01
The primary goals of environmental monitoring are to indicate whether unexpected changes related to development are occurring in the physical, chemical, and biological attributes of ecosystems and to inform meaningful management intervention. Although achieving these objectives is conceptually simple, varying scientific and social challenges often result in their breakdown. Conceptualizing, designing, and operating programs that better delineate monitoring, management, and risk assessment processes supported by hypothesis-driven approaches, strong inference, and adverse outcome pathways can overcome many of the challenges. Generally, a robust monitoring program is characterized by hypothesis-driven questions associated with potential adverse outcomes and feedback loops informed by data. Specifically, key and basic features are predictions of future observations (triggers) and mechanisms to respond to success or failure of those predictions (tiers). The adaptive processes accelerate or decelerate the effort to highlight and overcome ignorance while preventing the potentially unnecessary escalation of unguided monitoring and management. The deployment of the mutually reinforcing components can allow for more meaningful and actionable monitoring programs that better associate activities with consequences. Integr Environ Assess Manag 2017;13:877-891. © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC). © 2017 The Authors. Integrated Environmental Assessment and Management Published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).
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Tomimatsu, Hajime; Tang, Yanhong
2016-05-01
Understanding the photosynthetic responses of terrestrial plants to environments with high levels of CO2 is essential to address the ecological effects of elevated atmospheric CO2. Most photosynthetic models used for global carbon issues are based on steady-state photosynthesis, whereby photosynthesis is measured under constant environmental conditions; however, terrestrial plant photosynthesis under natural conditions is highly dynamic, and photosynthetic rates change in response to rapid changes in environmental factors. To predict future contributions of photosynthesis to the global carbon cycle, it is necessary to understand the dynamic nature of photosynthesis in relation to high CO2 levels. In this review, we summarize the current body of knowledge on the photosynthetic response to changes in light intensity under experimentally elevated CO2 conditions. We found that short-term exposure to high CO2 enhances photosynthetic rate, reduces photosynthetic induction time, and reduces post-illumination CO2 burst, resulting in increased leaf carbon gain during dynamic photosynthesis. However, long-term exposure to high CO2 during plant growth has varying effects on dynamic photosynthesis. High levels of CO2 increase the carbon gain in photosynthetic induction in some species, but have no significant effects in other species. Some studies have shown that high CO2 levels reduce the biochemical limitation on RuBP regeneration and Rubisco activation during photosynthetic induction, whereas the effects of high levels of CO2 on stomatal conductance differ among species. Few studies have examined the influence of environmental factors on effects of high levels of CO2 on dynamic photosynthesis. We identified several knowledge gaps that should be addressed to aid future predictions of photosynthesis in high-CO2 environments.
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Van Wyngaarden, Mallory; Snelgrove, Paul V R; DiBacco, Claudio; Hamilton, Lorraine C; Rodríguez-Ezpeleta, Naiara; Zhan, Luyao; Beiko, Robert G; Bradbury, Ian R
2018-03-01
Environmental factors can influence diversity and population structure in marine species and accurate understanding of this influence can both improve fisheries management and help predict responses to environmental change. We used 7163 SNPs derived from restriction site-associated DNA sequencing genotyped in 245 individuals of the economically important sea scallop, Placopecten magellanicus , to evaluate the correlations between oceanographic variation and a previously identified latitudinal genomic cline. Sea scallops span a broad latitudinal area (>10 degrees), and we hypothesized that climatic variation significantly drives clinal trends in allele frequency. Using a large environmental dataset, including temperature, salinity, chlorophyll a, and nutrient concentrations, we identified a suite of SNPs (285-621, depending on analysis and environmental dataset) potentially under selection through correlations with environmental variation. Principal components analysis of different outlier SNPs and environmental datasets revealed similar northern and southern clusters, with significant associations between the first axes of each ( R 2 adj = .66-.79). Multivariate redundancy analysis of outlier SNPs and the environmental principal components indicated that environmental factors explained more than 32% of the variance. Similarly, multiple linear regressions and random-forest analysis identified winter average and minimum ocean temperatures as significant parameters in the link between genetic and environmental variation. This work indicates that oceanographic variation is associated with the observed genomic cline in this species and that seasonal periods of extreme cold may restrict gene flow along a latitudinal gradient in this marine benthic bivalve. Incorporating this finding into management may improve accuracy of management strategies and future predictions.
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2013-01-01
Considerable variation is evident in response to psychological therapies for mood and anxiety disorders. Genetic factors alongside environmental variables and gene-environment interactions are implicated in the etiology of these disorders and it is plausible that these same factors may also be important in predicting individual differences in response to psychological treatment. In this article, we review the evidence that genetic variation influences psychological treatment outcomes with a primary focus on mood and anxiety disorders. Unlike most past work, which has considered prediction of response to pharmacotherapy, this article reviews recent work in the field of therapygenetics, namely the role of genes in predicting psychological treatment response. As this is a field in its infancy, methodological recommendations are made and opportunities for future research are identified. PMID:23388219
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Kaplan, Brent A; Reed, Derek D; Jarmolowicz, David P
2016-03-01
Many everyday choices are associated with both delayed and probabilistic outcomes. The temporal attention hypothesis suggests that individuals' decision making can be improved by focusing attention on temporally distal events and implies that environmental manipulations that bring temporally distal outcomes into focus may alter an individual's degree of discounting. One such manipulation, episodic future thinking, has shown to lower discount rates; however, several questions remain about the applicability of episodic future thinking to domains other than delay discounting. The present experiments examine the effects of a modified episodic-future-thinking procedure in which participants viewed age-progressed computer-generated images of themselves and answered questions related to their future, on probability discounting in the context of both a delayed health gain and loss. Results indicate that modified episodic future thinking effectively altered individuals' degree of discounting in the predicted directions and demonstrate the applicability of episodic future thinking to decision making of socially significant outcomes. © 2015 Society for the Experimental Analysis of Behavior.
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Unpredictable food supply modifies costs of reproduction and hampers individual optimization.
Török, János; Hegyi, Gergely; Tóth, László; Könczey, Réka
2004-11-01
Investment into the current reproductive attempt is thought to be at the expense of survival and/or future reproduction. Individuals are therefore expected to adjust their decisions to their physiological state and predictable aspects of environmental quality. The main predictions of the individual optimization hypothesis for bird clutch sizes are: (1) an increase in the number of recruits with an increasing number of eggs in natural broods, with no corresponding impairment of parental survival or future reproduction, and (2) a decrease in the fitness of parents in response to both negative and positive brood size manipulation, as a result of a low number of recruits, poor future reproduction of parents, or both. We analysed environmental influences on costs and optimization of reproduction on 6 years of natural and experimentally manipulated broods in a Central European population of the collared flycatcher. Based on dramatic differences in caterpillar availability, we classified breeding seasons as average and rich food years. The categorization was substantiated by the majority of present and future fitness components of adults and offspring. Neither observational nor experimental data supported the individual optimization hypothesis, in contrast to a Scandinavian population of the species. The quality of fledglings deteriorated, and the number of recruits did not increase with natural clutch size. Manipulation revealed significant costs of reproduction to female parents in terms of future reproductive potential. However, the influence of manipulation on recruitment was linear, with no significant polynomial effect. The number of recruits increased with manipulation in rich food years and tended to decrease in average years, so control broods did not recruit more young than manipulated broods in any of the year types. This indicates that females did not optimize their clutch size, and that they generally laid fewer eggs than optimal in rich food years. Mean yearly clutch size did not follow food availability, which suggests that females cannot predict food supply of the brood-rearing period at the beginning of the season. This lack of information on future food conditions seems to prevent them from accurately estimating their optimal clutch size for each season. Our results suggest that individual optimization may not be a general pattern even within a species, and alternative mechanisms are needed to explain clutch size variation.
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Viewing Marine Bacteria, Their Activity and Response to Environmental Drivers from Orbit
Grimes, D. Jay; Ford, Tim E.; Colwell, Rita R.; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G.
2014-01-01
Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions. PMID:24477922
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Ecological Forecasting in the Applied Sciences Program and Input to the Decadal Survey
NASA Technical Reports Server (NTRS)
Skiles, Joseph
2015-01-01
Ecological forecasting uses knowledge of physics, ecology and physiology to predict how ecosystems will change in the future in response to environmental factors. Further, Ecological Forecasting employs observations and models to predict the effects of environmental change on ecosystems. In doing so, it applies information from the physical, biological, and social sciences and promotes a scientific synthesis across the domains of physics, geology, chemistry, biology, and psychology. The goal is reliable forecasts that allow decision makers access to science-based tools in order to project changes in living systems. The next decadal survey will direct the development Earth Observation sensors and satellites for the next ten years. It is important that these new sensors and satellites address the requirements for ecosystem models, imagery, and other data for resource management. This presentation will give examples of these model inputs and some resources needed for NASA to continue effective Ecological Forecasting.
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Grimes, D Jay; Ford, Tim E; Colwell, Rita R; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G
2014-04-01
Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions.
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Influence of Photoperiod on Hormones, Behavior, and Immune Function
Walton, James C.; Weil, Zachary M.; Nelson, Randy J.
2011-01-01
Photoperiodism is the ability of plants and animals to measure environmental day length to ascertain time of year. Central to the evolution of photoperiodism in animals is the adaptive distribution of energetically challenging activities across the year to optimize reproductive fitness while balancing the energetic tradeoffs necessary for seasonally- appropriate survival strategies. The ability to accurately predict future events requires endogenous mechanisms to permit physiological anticipation of annual conditions. Day length provides a virtually noise free environmental signal to monitor and accurately predict time of the year. In mammals, melatonin provides the hormonal signal transducing day length. Duration of pineal melatonin is inversely related to day length and its secretion drives enduring changes in many physiological systems, including the HPA, HPG, and brain-gut axes, the autonomic nervous system, and the immune system. Thus, melatonin is the fulcrum mediating redistribution of energetic investment among physiological processes to maximize fitness and survival. PMID:21156187
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Pai, T Y; Chiou, R J; Wen, H H
2008-01-01
In this study, the impact levels in environmental impact assessment (EIA) reports of 10 incinerator plants were quantified and discussed. The relationship between the quantified impact levels and the plant scale factors of BeiTou, LiZe, BaLi, LuTsao, RenWu, PingTung, SiJhou and HsinChu were constructed, and the impact levels of the GangShan (GS) and YongKong (YK) plants were predicted using grey model GM (1, N). Finally, the effects of plant scale factors on impact levels were evaluated using grey model GM (1, N) too. According to the predicted results of GM, the relative errors of topography/geology/soil, air quality, hydrology/water quality, solid waste, noise, terrestrial fauna/flora, aquatic fauna/flora and traffic in the GS plant were 17%, 14%, 15%, 17%, 75%, 16%, 13%, and 37%, respectively. The relative errors of the same environmental items in the YK plant were 1%, 18%, 10%, 40%, 37%, 3%, 25% and 33%, respectively. According to GM (1, N), design capacity (DC) and heat value (HV) were the plant scale factors that affected the impact levels significantly in each environmental item, and thus were the most significant plant scale factors. GM (1, N) was effective in predicting the environmental impact and analyzing the reasonableness of the impact. If there is an EIA for a new incinerator plant to be reviewed in the future, the official committee of the Taiwan EPA could review the reasonableness of impact levels in EIA reports quickly.
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Impacts of climate change on distributions and diversity of ungulates on the Tibetan Plateau.
Luo, Zhenhua; Jiang, Zhigang; Tang, Songhua
2015-01-01
Climate change has significant impacts on species' distributions and diversity patterns. Understanding range shifts and changes in richness gradients under climate change is crucial for conservation. The Tibetan Plateau, home to wild yak, chiru, and kiang, contains a biome with many endemic ungulates. It is highly sensitive to climate change and a region that merits particular attention with regard to the impacts of global climate change on its biomes. Maximum entropy approaches were used to estimate current and future potential distributions, in response to climate change, for 22 ungulate species. We used three general circulation (MK3, HADCM3, MIROC3_2-MED) and three emissions scenarios (Bl, A1B, A2) to derive estimated future measurements of 14 environmental variables over three time periods (2020, 2050, 2080), and then modeled species distributions using these predicted environmental measurements for each time period under two dispersal hypotheses (full and zero, respectively). This resulted in a total of 6160 prediction models. We found that these ungulates, on average, may lose 30-50% of their distributional areas, depending on the dispersal scenarios. In addition, 55-68% of the ungulate species were predicted to become locally endangered under the different dispersal assumptions, 23-32% to become locally critically endangered, and 4-7 endemic species to become globally endangered. Furthermore, ungulate species ranges may experience average poleward shifts of ~300 km. We also predict west-to-east reductions in species richness: southeastern mountainous areas currently have the highest species richness, but are predicted to face the greatest diversity losses, whereas the northern areas are predicted to see increasing numbers of ungulate species in the 21st century. Our study indicates much more severe range reductions of ungulates on the Tibetan Plateau than those anticipated elsewhere in the world, and species richness patterns will change dramatically with climate change. For conservation, we suggest (1) securing existing protected areas, and (2) establishing new nature reserves to counterbalance climate change impacts.
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Species Pool Functional Diversity Plays a Hidden Role in Generating β-Diversity.
Patrick, Christopher J; Brown, Bryan L
2018-05-01
Functional trait diversity is used as a way to infer mechanistic processes that drive community assembly. While functional diversity within communities is often viewed as a response variable, here we present and test a framework for how functional diversity among taxa in the regional species pool drives the assembly of communities among habitats. We predicted that species pool functional diversity should work with environmental heterogeneity to drive β-diversity. We tested these predictions by modeling empirical patterns in invertebrate communities from 570 streams in 52 watersheds. Our analysis of the field data provided strong support for the inclusion of both functional diversity and environmental heterogeneity in the models, and our predictions were supported when the community was analyzed all together. However, analyses within individual functional feeding guilds revealed strong context dependency in the relative importance of functional diversity, γ-richness, and environmental heterogeneity to β-diversity. We interpret the results to mean that functional diversity can play an important role in driving β-diversity; however, within guilds the nature of interspecific interactions and species pool size complicate the relationship. Future research should test this conceptual model across different ecosystems and in experimental settings using metacommunity mesocosms to enhance our understanding of the role that functional variation plays in generating spatial biodiversity patterns.
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Potential of satellite-derived ecosystem functional attributes to anticipate species range shifts
NASA Astrophysics Data System (ADS)
Alcaraz-Segura, Domingo; Lomba, Angela; Sousa-Silva, Rita; Nieto-Lugilde, Diego; Alves, Paulo; Georges, Damien; Vicente, Joana R.; Honrado, João P.
2017-05-01
In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001-2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species.
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Acevedo, Pelayo; Ruiz-Fons, Francisco; Estrada, Rosa; Márquez, Ana Luz; Miranda, Miguel Angel; Gortázar, Christian; Lucientes, Javier
2010-12-06
Bluetongue (BT) is still present in Europe and the introduction of new serotypes from endemic areas in the African continent is a possible threat. Culicoides imicola remains one of the most relevant BT vectors in Spain and research on the environmental determinants driving its life cycle is key to preventing and controlling BT. Our aim was to improve our understanding of the biotic and abiotic determinants of C. imicola by modelling its present abundance, studying the spatial pattern of predicted abundance in relation to BT outbreaks, and investigating how the predicted current distribution and abundance patterns might change under future (2011-2040) scenarios of climate change according to the Intergovernmental Panel on Climate Change. C. imicola abundance data from the bluetongue national surveillance programme were modelled with spatial, topoclimatic, host and soil factors. The influence of these factors was further assessed by variation partitioning procedures. The predicted abundance of C. imicola was also projected to a future period. Variation partitioning demonstrated that the pure effect of host and topoclimate factors explained a high percentage (>80%) of the variation. The pure effect of soil followed in importance in explaining the abundance of C. imicola. A close link was confirmed between C. imicola abundance and BT outbreaks. To the best of our knowledge, this study is the first to consider wild and domestic hosts in predictive modelling for an arthropod vector. The main findings regarding the near future show that there is no evidence to suggest that there will be an important increase in the distribution range of C. imicola; this contrasts with an expected increase in abundance in the areas where it is already present in mainland Spain. What may be expected regarding the future scenario for orbiviruses in mainland Spain, is that higher predicted C. imicola abundance may significantly change the rate of transmission of orbiviruses.
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Chemical Risk Assessment: Traditional vs Public Health Perspectives
Axelrad, Daniel A.; Bahadori, Tina; Bussard, David; Cascio, Wayne E.; Deener, Kacee; Dix, David; Thomas, Russell S.; Kavlock, Robert J.; Burke, Thomas A.
2017-01-01
Preventing adverse health effects of environmental chemical exposure is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and effects of environmentally induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Considering these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease. PMID:28520487
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Predicting future glacial lakes in Austria using different modelling approaches
NASA Astrophysics Data System (ADS)
Otto, Jan-Christoph; Helfricht, Kay; Prasicek, Günther; Buckel, Johannes; Keuschnig, Markus
2017-04-01
Glacier retreat is one of the most apparent consequences of temperature rise in the 20th and 21th centuries in the European Alps. In Austria, more than 240 new lakes have formed in glacier forefields since the Little Ice Age. A similar signal is reported from many mountain areas worldwide. Glacial lakes can constitute important environmental and socio-economic impacts on high mountain systems including water resource management, sediment delivery, natural hazards, energy production and tourism. Their development significantly modifies the landscape configuration and visual appearance of high mountain areas. Knowledge on the location, number and extent of these future lakes can be used to assess potential impacts on high mountain geo-ecosystems and upland-lowland interactions. Information on new lakes is critical to appraise emerging threads and potentials for society. The recent development of regional ice thickness models and their combination with high resolution glacier surface data allows predicting the topography below current glaciers by subtracting ice thickness from glacier surface. Analyzing these modelled glacier bed surfaces reveals overdeepenings that represent potential locations for future lakes. In order to predict the location of future glacial lakes below recent glaciers in the Austrian Alps we apply different ice thickness models using high resolution terrain data and glacier outlines. The results are compared and validated with ice thickness data from geophysical surveys. Additionally, we run the models on three different glacier extents provided by the Austrian Glacier Inventories from 1969, 1998 and 2006. Results of this historical glacier extent modelling are compared to existing glacier lakes and discussed focusing on geomorphological impacts on lake evolution. We discuss model performance and observed differences in the results in order to assess the approach for a realistic prediction of future lake locations. The presentation delivers intermediate results from the FUTURELAKES project, which aims at generating the first nation-wide data set on future glacial lakes in Austria.
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NASA Astrophysics Data System (ADS)
Little, David L., II
Ongoing changes in values, pedagogy, and curriculum concerning sustainability education necessitate that strong curricular elements are identified in sustainability education. However, quantitative research in sustainability education is largely undeveloped or relies on outdated instruments. In part, this is because no widespread quantitative instrument for measuring related educational outcomes has been developed for the field, though their development is pivotal for future efforts in sustainability education related to STEM majors. This research study details the creation, evaluation, and validation of an instrument -- the STEM Sustainability Engagement Instrument (STEMSEI) -- designed to measure sustainability engagement in post-secondary STEM majors. The study was conducted in three phases, using qualitative methods in phase 1, a concurrent mixed methods design in phase 2, and a sequential mixed methods design in phase 3. The STEMSEI was able to successfully predict statistically significant differences in the sample (n= 1017) that were predicted by prior research in environmental education. The STEMSEI also revealed statistically significant differences between STEM majors' sustainability engagement with a large effect size (.203 ≤ eta2 ≤ .211). As hypothesized, statistically significant differences were found on the environmental scales across gender and present religion. With respect to gender, self-perceived measures of emotional engagement with environmental sustainability was higher with females while males had higher measures in cognitive engagement with respect to knowing information related to environmental sustainability. With respect to present religion, self-perceived measures of general engagement and emotional engagement in environmental sustainability were higher for non-Christians as compared to Christians. On the economic scales, statistically significant differences were found across gender. Specifically, measures of males' self-perceived cognitive engagement in knowing information related to economic sustainability were greater than those of females. Future research should establish the generalizability of these results and further test the validity of the STEMSEI.
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Coops, Nicholas C; Coggins, Sam B; Kurz, Werner A
2007-06-01
Coastal Douglas-fir (Pseudotsuga menziesii spp. menziesii (Mirb.) Franco) occurs over a wide range of environmental conditions on Vancouver Island, British Columbia. Although ecological zones have been drawn, no formal spatial analysis of environmental limitations on tree growth has been carried out. Such an exercise is desirable to identify areas that may warrant intensive management and to evaluate the impacts of predicted climate change this century. We applied a physiologically based forest growth model, 3-PG (Physiological Principles Predicting Growth), to interpret and map current limitations to Douglas-fir growth across Vancouver Island at 100-m cell resolution. We first calibrated the model to reproduce the regional productivity estimates reported in yield table growth curves. Further analyses indicated that slope exposure is important; southwest slopes of 30 degrees receive 40% more incident radiation than similarly inclined northeast slopes. When combined with other environmental differences associated with aspect, the model predicted 60% more growth on southwest exposures than on northeast exposures. The model simulations support field observations that drought is rare in the wetter zones, but common on the eastern side of Vancouver Island at lower elevations and on more exposed slopes. We illustrate the current limitations on growth caused by suboptimal temperature, high vapor pressure deficits and other factors. The modeling approach complements ecological classifications and offers the potential to identify the most favorable sites for management of other native tree species under current and future climatic conditions.
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Human Health Effects of Ozone Depletion From Stratospheric Aircraft
NASA Technical Reports Server (NTRS)
Wey, Chowen (Technical Monitor)
2001-01-01
This report presents EPA's initial response to NASA's request to advise on potential environmental policy issues associated with the future development of supersonic flight technologies. Consistent with the scope of the study to which NASA and EPA agreed, EPA has evaluated only the environmental concerns related to the stratospheric ozone impacts of a hypothetical HSCT fleet, although recent research indicates that a fleet of HSCT is predicted to contribute to climate warming as well. This report also briefly describes the international and domestic institutional frameworks established to address stratospheric ozone depletion, as well as those established to control pollution from aircraft engine exhaust emissions.
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Ozone Response to Aircraft Emissions: Sensitivity Studies with Two-dimensional Models
NASA Technical Reports Server (NTRS)
Ko, Malcolm K. W.; Weisenstein, Debra; Jackman, Charles H.; Douglass, Anne R.; Bureske, K.; Weubbles, Donald J.; Kinnison, Douglas E.; Brasseur, G.; Pyle, J.; Jones, Anna
1992-01-01
Our first intercomparison/assessment of the effects of a proposed high-speed civil transport (HSCT) fleet on the stratosphere is presented. These model calculations should be considered more as sensitivity studies, primarily designed to serve the following purposes: (1) to allow for intercomparison of model predictions; (2) to focus on the range of fleet operations and engine specifications giving minimal environmental impact; and (3) to provide the basis for future assessment studies. The basic scenarios were chosen to be as realistic as possible, using the information available on anticipated developments in technology. They are not to be interpreted as a commitment or goal for environmental acceptability.
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Event Locations in Extra-Familial Child Sexual Molestation Cases: The Istanbul Example.
Gönültaş, Burak M; Sahin, Bahadir
2018-04-01
A great deal of attention has been devoted to sexual molestation cases, both in theory and in practice. Child molesters are versatile and are not easily identified. Various theories and tactics, the most contemporary of which is environmental criminology, have been developed to find those criminals. Locations of victims, crime scenes, and distances among them as well as other situational variables are used to predict possible future offences in environmental criminology. This study applies the theory to sexual molestation crimes in Istanbul. Dependent distance variables are found to be correlated with several situational variables in a selected sample of 127 extra-familial child sexual molestation cases.
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Microbial contributions to the persistence of coral reefs.
Webster, Nicole S; Reusch, Thorsten B H
2017-10-01
On contemplating the adaptive capacity of reef organisms to a rapidly changing environment, the microbiome offers significant and greatly unrecognised potential. Microbial symbionts contribute to the physiology, development, immunity and behaviour of their hosts, and can respond very rapidly to changing environmental conditions, providing a powerful mechanism for acclimatisation and also possibly rapid evolution of coral reef holobionts. Environmentally acquired fluctuations in the microbiome can have significant functional consequences for the holobiont phenotype upon which selection can act. Environmentally induced changes in microbial abundance may be analogous to host gene duplication, symbiont switching / shuffling as a result of environmental change can either remove or introduce raw genetic material into the holobiont; and horizontal gene transfer can facilitate rapid evolution within microbial strains. Vertical transmission of symbionts is a key feature of many reef holobionts and this would enable environmentally acquired microbial traits to be faithfully passed to future generations, ultimately facilitating microbiome-mediated transgenerational acclimatisation (MMTA) and potentially even adaptation of reef species in a rapidly changing climate. In this commentary, we highlight the capacity and mechanisms for MMTA in reef species, propose a modified Price equation as a framework for assessing MMTA and recommend future areas of research to better understand how microorganisms contribute to the transgenerational acclimatisation of reef organisms, which is essential if we are to reliably predict the consequences of global change for reef ecosystems.
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Polce, Chiara; Garratt, Michael P; Termansen, Mette; Ramirez-Villegas, Julian; Challinor, Andrew J; Lappage, Martin G; Boatman, Nigel D; Crowe, Andrew; Endalew, Ayenew Melese; Potts, Simon G; Somerwill, Kate E; Biesmeijer, Jacobus C
2014-01-01
Understanding how climate change can affect crop-pollinator systems helps predict potential geographical mismatches between a crop and its pollinators, and therefore identify areas vulnerable to loss of pollination services. We examined the distribution of orchard species (apples, pears, plums and other top fruits) and their pollinators in Great Britain, for present and future climatic conditions projected for 2050 under the SRES A1B Emissions Scenario. We used a relative index of pollinator availability as a proxy for pollination service. At present, there is a large spatial overlap between orchards and their pollinators, but predictions for 2050 revealed that the most suitable areas for orchards corresponded to low pollinator availability. However, we found that pollinator availability may persist in areas currently used for fruit production, which are predicted to provide suboptimal environmental suitability for orchard species in the future. Our results may be used to identify mitigation options to safeguard orchard production against the risk of pollination failure in Great Britain over the next 50 years; for instance, choosing fruit tree varieties that are adapted to future climatic conditions, or boosting wild pollinators through improving landscape resources. Our approach can be readily applied to other regions and crop systems, and expanded to include different climatic scenarios. PMID:24638986
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NASA Astrophysics Data System (ADS)
Duval, B.; Ghimire, R.; Hartman, M. D.; Marsalis, M.
2016-12-01
Large tracts of semi-arid land in the Southwestern USA are relatively less important for food production than the US Corn Belt, and represent a promising area for expansion of biofuel/bioproduct crops. However, high temperatures, low available water and high solar radiation in the SW represent a challenge to suitable feedstock development, and future climate change scenarios predict that portions of the SW will experience increased temperature and temporal shifts in precipitation distribution. Sorghum (Sorghum bicolor) is a valuable forage crop with promise as a biofuel feedstock, given its high biomass under semi-arid conditions, relatively lower N fertilizer requirements compared to corn, and salinity tolerance. To evaluate the environmental impact of expanded sorghum cultivation under future climate in the SW USA, we used the DayCent model in concert with a suite of downscaled future weather projections to predict biogeochemical consequences (greenhouse gas flux and impacts on soil carbon) of sorghum cultivation in New Mexico. The model showed good correspondence with yield data from field trials including both dryland and irrigated sorghum (measured vs. modeled; r2 = 0.75). Simulation experiments tested the effect of dryland production versus irrigation, low N versus high N inputs and delayed fertilizer application. Nitrogen application timing and irrigation impacted yield and N2O emissions less than N rate and climate. Across N and irrigation treatments, future climate simulations resulted in 6% increased yield and 20% lower N2O emissions compared to current climate. Soil C pools declined under future climate. The greatest declines in soil C were from low N input sorghum simulations, regardless of irrigation (>20% declines in SOM in both cases), and requires further evaluation to determine if changing future climate is driving these declines, or if they are a function of prolonged sorghum-fallow rotations in the model. The relatively small gain in yield for irrigated sorghum, and strong control of N rate on N2O emissions suggests that a dryland sorghum bioproduct system could be environmentally sustainable in the Southwestern US with effective N management, and warrants further investigation in field trials.
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NASA Astrophysics Data System (ADS)
Lombardozzi, D.; Levis, S.; Bonan, G.; Sparks, J. P.
2012-08-01
Plants exchange greenhouse gases carbon dioxide and water with the atmosphere through the processes of photosynthesis and transpiration, making them essential in climate regulation. Carbon dioxide and water exchange are typically coupled through the control of stomatal conductance, and the parameterization in many models often predict conductance based on photosynthesis values. Some environmental conditions, like exposure to high ozone (O3) concentrations, alter photosynthesis independent of stomatal conductance, so models that couple these processes cannot accurately predict both. The goals of this study were to test direct and indirect photosynthesis and stomatal conductance modifications based on O3 damage to tulip poplar (Liriodendron tulipifera) in a coupled Farquhar/Ball-Berry model. The same modifications were then tested in the Community Land Model (CLM) to determine the impacts on gross primary productivity (GPP) and transpiration at a constant O3 concentration of 100 parts per billion (ppb). Modifying the Vcmax parameter and directly modifying stomatal conductance best predicts photosynthesis and stomatal conductance responses to chronic O3 over a range of environmental conditions. On a global scale, directly modifying conductance reduces the effect of O3 on both transpiration and GPP compared to indirectly modifying conductance, particularly in the tropics. The results of this study suggest that independently modifying stomatal conductance can improve the ability of models to predict hydrologic cycling, and therefore improve future climate predictions.
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NASA Astrophysics Data System (ADS)
Davis, Tom R.; Harasti, David; Smith, Stephen D. A.; Kelaher, Brendan P.
2016-11-01
Climate change induced sea level rise will affect shallow estuarine habitats, which are already under threat from multiple anthropogenic stressors. Here, we present the results of modelling to predict potential impacts of climate change associated processes on seagrass distributions. We use a novel application of relative environmental suitability (RES) modelling to examine relationships between variables of physiological importance to seagrasses (light availability, wave exposure, and current flow) and seagrass distributions within 5 estuarine embayments. Models were constructed separately for Posidonia australis and Zostera muelleri subsp. capricorni using seagrass data from Port Stephens estuary, New South Wales, Australia. Subsequent testing of models used independent datasets from four other estuarine embayments (Wallis Lake, Lake Illawarra, Merimbula Lake, and Pambula Lake) distributed along 570 km of the east Australian coast. Relative environmental suitability models provided adequate predictions for seagrass distributions within Port Stephens and the other estuarine embayments, indicating that they may have broad regional application. Under the predictions of RES models, both sea level rise and increased turbidity are predicted to cause substantial seagrass losses in deeper estuarine areas, resulting in a net shoreward movement of seagrass beds. Seagrass species distribution models developed in this study provide a valuable tool to predict future shifts in estuarine seagrass distributions, allowing identification of areas for protection, monitoring and rehabilitation.
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Forecasting peak asthma admissions in London: an application of quantile regression models.
Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe
2013-07-01
Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.
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Forecasting peak asthma admissions in London: an application of quantile regression models
NASA Astrophysics Data System (ADS)
Soyiri, Ireneous N.; Reidpath, Daniel D.; Sarran, Christophe
2013-07-01
Asthma is a chronic condition of great public health concern globally. The associated morbidity, mortality and healthcare utilisation place an enormous burden on healthcare infrastructure and services. This study demonstrates a multistage quantile regression approach to predicting excess demand for health care services in the form of asthma daily admissions in London, using retrospective data from the Hospital Episode Statistics, weather and air quality. Trivariate quantile regression models (QRM) of asthma daily admissions were fitted to a 14-day range of lags of environmental factors, accounting for seasonality in a hold-in sample of the data. Representative lags were pooled to form multivariate predictive models, selected through a systematic backward stepwise reduction approach. Models were cross-validated using a hold-out sample of the data, and their respective root mean square error measures, sensitivity, specificity and predictive values compared. Two of the predictive models were able to detect extreme number of daily asthma admissions at sensitivity levels of 76 % and 62 %, as well as specificities of 66 % and 76 %. Their positive predictive values were slightly higher for the hold-out sample (29 % and 28 %) than for the hold-in model development sample (16 % and 18 %). QRMs can be used in multistage to select suitable variables to forecast extreme asthma events. The associations between asthma and environmental factors, including temperature, ozone and carbon monoxide can be exploited in predicting future events using QRMs.
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Prognostics Applied to Electric Propulsion UAV
NASA Technical Reports Server (NTRS)
Goebel, Kai; Saha, Bhaskar
2013-01-01
Health management plays an important role in operations of UAV. If there is equipment malfunction on critical components, safe operation of the UAV might possibly be compromised. A technology with particular promise in this arena is equipment prognostics. This technology provides a state assessment of the health of components of interest and, if a degraded state has been found, it estimates how long it will take before the equipment will reach a failure threshold, conditional on assumptions about future operating conditions and future environmental conditions. This chapter explores the technical underpinnings of how to perform prognostics and shows an implementation on the propulsion of an electric UAV. A particle filter is shown as the method of choice in performing state assessment and predicting future degradation. The method is then applied to the batteries that provide power to the propeller motors. An accurate run-time battery life prediction algorithm is of critical importance to ensure the safe operation of the vehicle if one wants to maximize in-air time. Current reliability based techniques turn out to be insufficient to manage the use of such batteries where loads vary frequently in uncertain environments.
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NASA Technical Reports Server (NTRS)
Anthes, Richard; Schoeberl, Mark
2000-01-01
Fast-forward twenty years to the nightly simultaneous TV/webcast. Accurate 8-14 day regional forecasts will be available as will be a whole host of linked products including economic impact, travel, energy usage, etc. On-demand, personalized street-level forecasts will be downloaded into your PDA. Your home system will automatically update the products of interest to you (e.g. severe storm forecasts, hurricane predictions, etc). Short and long range climate forecasts will be used by your "Quicken 2020" to make suggest changes in your "futures" investment portfolio. Through a lively and informative multi-media presentation, leading Space-Earth Science Researchers and Technologists will share their vision for the year 2020, offering a possible futuristic forecast enabled through the application of new technologies under development today. Copies of the 'broadcast' will be available on Beta Tape for your own future use. If sufficient interest exists, the program may also be made available for broadcasters wishing to do stand-ups with roll-ins from the San Francisco meeting for their viewers back home.
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NASA Astrophysics Data System (ADS)
O'Connor, Alison; Kirtman, Benjamin; Harrison, Scott; Gorman, Joe
2016-05-01
The US Navy faces several limitations when planning operations in regard to forecasting environmental conditions. Currently, mission analysis and planning tools rely heavily on short-term (less than a week) forecasts or long-term statistical climate products. However, newly available data in the form of weather forecast ensembles provides dynamical and statistical extended-range predictions that can produce more accurate predictions if ensemble members can be combined correctly. Charles River Analytics is designing the Climatological Observations for Maritime Prediction and Analysis Support Service (COMPASS), which performs data fusion over extended-range multi-model ensembles, such as the North American Multi-Model Ensemble (NMME), to produce a unified forecast for several weeks to several seasons in the future. We evaluated thirty years of forecasts using machine learning to select predictions for an all-encompassing and superior forecast that can be used to inform the Navy's decision planning process.
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Towards Actionable Waterborne and Vector-borne Disease Forecasts
NASA Astrophysics Data System (ADS)
Zaitchik, B. F.
2015-12-01
Numerous studies have shown that remote sensing (RS) and Earth System Models (ESM) can make important contributions to the analysis, monitoring and prediction of waterborne and vector-borne illnesses. Unsurprisingly, however, the great majority of these studies have been proof-of-concept investigations, and vanishingly few have been translated into operational and utilized disease early warning systems. To some extent this is simply an example of the general challenge of translating research findings into decision-relevant operations. Disease early warning, however, entails specific challenges that distinguish it from many other fields of environmental monitoring and prediction. Some of these challenges stem from predictability and data constraints, while others relate to the difficulty of communicating predictions and the particularly high price of false alarms. This presentation will review progress on the translation of analysis to decision making, identify avenues for enhancing forecast utility, and propose priorities for future RS and ESM investments in disease monitoring and prediction.
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Murphy, E; King, E A
2010-04-01
This paper explores methodological issues and policy implications concerning the implementation of the EU Environmental Noise Directive (END) across Member States. Methodologically, the paper focuses on two key thematic issues relevant to the Directive: (1) calculation methods and (2) mapping methods. For (1), the paper focuses, in particular, on how differing calculation methods influence noise prediction results as well as the value of the EU noise indicator L(den) and its associated implications for comparability of noise data across EU states. With regard to (2), emphasis is placed on identifying the issues affecting strategic noise mapping, estimating population exposure, noise action planning and dissemination of noise mapping results to the general public. The implication of these issues for future environmental noise policy is also examined. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
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Aerial Observation Needs Workshop, May 13-14, 2015
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nasiri, Shaima; Serbin, Shawn; Lesmes, David
2015-10-01
The mission of the Climate and Environmental Sciences Division (CESD) of the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy's (DOE) Office of Science is "to advance a robust, predictive understanding of Earth's climate and environmental systems and to inform the development of sustainable solutions to the nation's energy and environmental challenges." Accomplishing this mission requires aerial observations of the atmospheric and terrestrial components of the climate system. CESD is assessing its current and future aerial observation needs to develop a strategy and roadmap of capability requirements for the next decade. To facilitate this process,more » a workshop was convened that consisted of invited experts in the atmospheric and terrestrial sciences, airborne observations, and modeling. This workshop report summarizes the community input prior to and during the workshop on research challenges and opportunities, as well as specific science questions and observational needs that require aerial observations to address.« less
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Spencer, Ricky-John; Janzen, Fredric J
2011-07-01
Incubation temperature plays a prominent role in shaping the phenotypes and fitness of embryos, including affecting developmental rates. In many taxa, including turtles, eggs are deposited in layers such that thermal gradients alter developmental rates within a nest. Despite this thermal effect, a nascent body of experimental work on environmentally cued hatching in turtles has revealed unexpected synchronicity in hatching behavior. This review discusses environmental cues for hatching, physiological mechanisms behind synchronous hatching, proximate and ultimate causes for this behavior, and future directions for research. Four freshwater turtle species have been investigated experimentally, with hatching in each species elicited by different environmental cues and responding via various physiological mechanisms. Hatching of groups of eggs in turtles apparently involves some level of embryo-embryo communication and thus is not a purely passive activity. Although turtles are not icons of complex social behavior, life-history theory predicts that the group environment of the nest can drive the evolution of environmentally cued hatching.
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Biodiversity and Resilience of Ecosystem Functions.
Oliver, Tom H; Heard, Matthew S; Isaac, Nick J B; Roy, David B; Procter, Deborah; Eigenbrod, Felix; Freckleton, Rob; Hector, Andy; Orme, C David L; Petchey, Owen L; Proença, Vânia; Raffaelli, David; Suttle, K Blake; Mace, Georgina M; Martín-López, Berta; Woodcock, Ben A; Bullock, James M
2015-11-01
Accelerating rates of environmental change and the continued loss of global biodiversity threaten functions and services delivered by ecosystems. Much ecosystem monitoring and management is focused on the provision of ecosystem functions and services under current environmental conditions, yet this could lead to inappropriate management guidance and undervaluation of the importance of biodiversity. The maintenance of ecosystem functions and services under substantial predicted future environmental change (i.e., their 'resilience') is crucial. Here we identify a range of mechanisms underpinning the resilience of ecosystem functions across three ecological scales. Although potentially less important in the short term, biodiversity, encompassing variation from within species to across landscapes, may be crucial for the longer-term resilience of ecosystem functions and the services that they underpin. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Fitzpatrick, Matthew C; Keller, Stephen R
2015-01-01
Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism-environment relationships that combines genomic data and community-level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA-5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community-level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species-level assessments of climate change vulnerability. © 2014 John Wiley & Sons Ltd/CNRS.
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A Vision for the Future of Environmental Research: Creating Environmental Intelligence Centers
NASA Astrophysics Data System (ADS)
Barron, E. J.
2002-12-01
The nature of the environmental issues facing our nation demands a capability that allows us to enhance economic vitality, maintain environmental quality, and limit threats to life and property through more fundamental understanding of the Earth. It is "advanced" knowledge of how the system may respond that gives environmental information most of its power and utility. This fact is evident in the demand for new forecasting products, involving air quality, energy demand, water quality and quantity, ultraviolet radiation, and human health indexes. As we demonstrate feasibility and benefit, society is likely to demand a growing number of new operational forecast products on prediction time scales of days to decades into the future. The driving forces that govern our environment are widely recognized, involving primarily weather and climate, patterns of land use and land cover, and resource use with its associated waste products. The importance of these driving forces has been demonstrated by a decade of research on greenhouse gas emissions, ozone depletion and deforestation, and through the birth of Earth System Science. But, there are also major challenges. We find the strongest intersection between human activity, environmental stresses, system interactions and human decision-making in regional analysis coupled to larger spatial scales. In addition, most regions are influenced by multiple-stresses. Multiple, cumulative, and interactive stresses are clearly the most difficult to understand and hence the most difficult to assess and to manage. Currently, we are incapable of addressing these issues in a truly integrated fashion at global scales. The lack of an ability to combine global and regional forcing and to assess the response of the system to multiple stresses at the spatial and temporal scales of interest to humans limits our ability to assess the impacts of specific human perturbations, to assess advantages and risks, and to enhance economic and societal well being in the context of global, national and regional stewardship. These societal needs lead to a vision that uses a regional framework as a stepping-stone to a comprehensive national or global capability. The development of a comprehensive regional framework depends on a new approach to environmental research - the creation of regional Environmental Intelligence Centers. A key objective is to bring a demanding level of discipline to "forecasting" in a broad arena of environmental issues. The regional vision described above is designed to address a broad range of current and future environmental issues by creating a capability based on integrating diverse observing systems, making data readily accessible, developing an increasingly comprehensive predictive capability at the spatial and temporal scales appropriate for examining societal issues, and creating a vigorous intersection with decision-makers. With demonstrated success over a few large-scale regions of the U.S., this strategy will very likely grow into a national capability that far exceeds current capabilities.
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Neural effects of environmental advertising: An fMRI analysis of voice age and temporal framing.
Casado-Aranda, Luis-Alberto; Martínez-Fiestas, Myriam; Sánchez-Fernández, Juan
2018-01-15
Ecological information offered to society through advertising enhances awareness of environmental issues, encourages development of sustainable attitudes and intentions, and can even alter behavior. This paper, by means of functional Magnetic Resonance Imaging (fMRI) and self-reports, explores the underlying mechanisms of processing ecological messages. The study specifically examines brain and behavioral responses to persuasive ecological messages that differ in temporal framing and in the age of the voice pronouncing them. The findings reveal that attitudes are more positive toward future-framed messages presented by young voices. The whole-brain analysis reveals that future-framed (FF) ecological messages trigger activation in brain areas related to imagery, prospective memories and episodic events, thus reflecting the involvement of past behaviors in future ecological actions. Past-framed messages (PF), in turn, elicit brain activations within the episodic system. Young voices (YV), in addition to triggering stronger activation in areas involved with the processing of high-timbre, high-pitched and high-intensity voices, are perceived as more emotional and motivational than old voices (OV) as activations in anterior cingulate cortex and amygdala. Messages expressed by older voices, in turn, exhibit stronger activation in areas formerly linked to low-pitched voices and voice gender perception. Interestingly, a link is identified between neural and self-report responses indicating that certain brain activations in response to future-framed messages and young voices predicted higher attitudes toward future-framed and young voice advertisements, respectively. The results of this study provide invaluable insight into the unconscious origin of attitudes toward environmental messages and indicate which voice and temporal frame of a message generate the greatest subconscious value. Copyright © 2017 Elsevier Ltd. All rights reserved.
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We'll Meet Again: Revealing Distributional and Temporal Patterns of Social Contact
Pachur, Thorsten; Schooler, Lael J.; Stevens, Jeffrey R.
2014-01-01
What are the dynamics and regularities underlying social contact, and how can contact with the people in one's social network be predicted? In order to characterize distributional and temporal patterns underlying contact probability, we asked 40 participants to keep a diary of their social contacts for 100 consecutive days. Using a memory framework previously used to study environmental regularities, we predicted that the probability of future contact would follow in systematic ways from the frequency, recency, and spacing of previous contact. The distribution of contact probability across the members of a person's social network was highly skewed, following an exponential function. As predicted, it emerged that future contact scaled linearly with frequency of past contact, proportionally to a power function with recency of past contact, and differentially according to the spacing of past contact. These relations emerged across different contact media and irrespective of whether the participant initiated or received contact. We discuss how the identification of these regularities might inspire more realistic analyses of behavior in social networks (e.g., attitude formation, cooperation). PMID:24475073
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Castillo, Karl D.; Ries, Justin B.; Weiss, Jack M.
2011-01-01
Background Natural and anthropogenic stressors are predicted to have increasingly negative impacts on coral reefs. Understanding how these environmental stressors have impacted coral skeletal growth should improve our ability to predict how they may affect coral reefs in the future. We investigated century-scale variations in skeletal extension for the slow-growing massive scleractinian coral Siderastrea siderea inhabiting the forereef, backreef, and nearshore reefs of the Mesoamerican Barrier Reef System (MBRS) in the western Caribbean Sea. Methodology/Principal Findings Thirteen S. siderea cores were extracted, slabbed, and X-rayed. Annual skeletal extension was estimated from adjacent low- and high-density growth bands. Since the early 1900s, forereef S. siderea colonies have shifted from exhibiting the fastest to the slowest average annual skeletal extension, while values for backreef and nearshore colonies have remained relatively constant. The rates of change in annual skeletal extension were −0.020±0.005, 0.011±0.006, and −0.008±0.006 mm yr−1 per year [mean±SE] for forereef, backreef, and nearshore colonies respectively. These values for forereef and nearshore S. siderea were significantly lower by 0.031±0.008 and by 0.019±0.009 mm yr−1 per year, respectively, than for backreef colonies. However, only forereef S. siderea exhibited a statistically significant decline in annual skeletal extension over the last century. Conclusions/Significance Our results suggest that forereef S. siderea colonies are more susceptible to environmental stress than backreef and nearshore counterparts, which may have historically been exposed to higher natural baseline stressors. Alternatively, sediment plumes, nutrients, and pollution originating from watersheds of Guatemala and Honduras may disproportionately impact the forereef environment of the MBRS. We are presently reconstructing the history of environmental stressors that have impacted the MBRS to constrain the cause(s) of the observed reductions in coral skeletal growth. This should improve our ability to predict and potentially mitigate the effects of future environmental stressors on coral reef ecosystems. PMID:21359203
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Jovicić, Dobrica
2012-06-01
Trying to anticipate the future of tourism may be a particularly fraught task. However, this does not mean that trying to predict the future of tourism is not without value. From a business perspective, examining the future enables firms to anticipate new business conditions and develop new strategies. From a destination perspective, reflections on the future enable consideration of how to maintain or improve the qualities of a destination. The paper is focused on an analysis of the impacts of the energy and ecological macro environments on tourism trends in 21st century. Mass international tourism has thrived on the abundant and cheap supply of energy, and this may be about to change as the world moves towards 'Peak Oil'. The resultant scarcity and high price of all energy fuels will produce changes in human activities, specifically in tourism. The basis of the health of the economy is the health of the environment. Therefore issues of global environmental changes are increasingly influencing consideration of trends in tourism. In this looming transitional era tourism needs to make some dramatic changes to harmonize with the new realities of a post-energy world affected additionaly by global warming and other environmental changes.
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Health impacts of an environmental disaster: a polemic
NASA Astrophysics Data System (ADS)
Dorling, Danny; Barford, Anna; Wheeler, Ben
2007-10-01
At this early point in the 21st century a major concern that we face is the future possible effects of people-induced global warming. The predicted effects are severe, but argued by some to be avoidable if we act now. Here we consider the dimensions of another disaster: one for which not only the causes, but also their horrific consequences, are current worldwide. The implicit question is 'why are we more worried about future disasters than those already occurring?' The worldmapper collection of cartograms (where a map is used like a pie-chart to present data) is used here to illustrate the extent of international inequalities in health and living conditions, discussed in relation to other aspects of human lives. Though the shape that we can see the world is in is shocking, we can also envisage a positive future. We compare these current global times to more local past times experienced during the ravaging inequalities of Victorian Britain. We use Britain simply as an example. We end by suggesting a further step the current British Prime Minister could make in his thinking. Doing this we can see the potential for environmental reconstruction, which would result (as it did before) in considerable reductions in infant mortality. Our common future is not already mapped out; it is still to be won.
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Sani-Kast, Nicole; Scheringer, Martin; Slomberg, Danielle; Labille, Jérôme; Praetorius, Antonia; Ollivier, Patrick; Hungerbühler, Konrad
2015-12-01
Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rhône River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these regions, the fate of the ENPs can be readily predicted. Copyright © 2014 Elsevier B.V. All rights reserved.
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Zhang, Keliang; Yao, Linjun; Meng, Jiasong; Tao, Jun
2018-09-01
Paeonia (Paeoniaceae), an economically important plant genus, includes many popular ornamentals and medicinal plant species used in traditional Chinese medicine. Little is known about the properties of the habitat distribution and the important eco-environmental factors shaping the suitability. Based on high-resolution environmental data for current and future climate scenarios, we modeled the present and future suitable habitat for P. delavayi and P. rockii by Maxent, evaluated the importance of environmental factors in shaping their distribution, and identified distribution shifts under climate change scenarios. The results showed that the moderate and high suitable areas for P. delavayi and P. rockii encompassed ca. 4.46×10 5 km 2 and 1.89×10 5 km 2 , respectively. Temperature seasonality and isothermality were identified as the most critical factors shaping P. delavayi distribution, and UVB-4 and annual precipitation were identified as the most critical for shaping P. rockii distribution. Under the scenario with a low concentration of greenhouse gas emissions (RCP2.6), the range of both species increased as global warming intensified; however, under the scenario with higher concentrations of emissions (RCP8.5), the suitable habitat range of P. delavayi decreased while P. rockii increased. Overall, our prediction showed that a shift in distribution of suitable habitat to higher elevations would gradually become more significant. The information gained from this study should provide a useful reference for implementing long-term conservation and management strategies for these species. Copyright © 2018. Published by Elsevier B.V.
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Are there other persistent organic pollutants? A challenge for environmental chemists.
Muir, Derek C G; Howard, Philip H
2006-12-01
The past 5 years have seen some major successes in terms of global measurement and regulation of persistent, bioaccumulative, and toxic (PB&T) chemicals and persistent organic pollutants (POPs). The Stockholm Convention, a global agreement on POPs, came into force in 2004. There has been a major expansion of measurements and risk assessments of new chemical contaminants in the global environment, particularly brominated diphenyl ethers and perfluorinated alkyl acids. However, the list of chemicals measured represents only a small fraction of the approximately 30,000 chemicals widely used in commerce (>1 t/y). The vast majority of existing and new chemical substances in commerce are not monitored in environmental media. Assessment and screening of thousands of existing chemicals in commerce in the United States, Europe, and Canada have yielded lists of potentially persistent and bioaccumulative chemicals. Here we review recent screening and categorization studies of chemicals in commerce and address the question of whether there is now sufficient information to permit a broader array of chemicals to be determined in environmental matrices. For example, Environment Canada's recent categorization of the Domestic (existing) Substances list, using a wide array of quantitative structure activity relationships for PB&T characteristics, has identified about 5.5% of 11,317 substances as meeting P & B criteria. Using data from the Environment Canada categorization, we have listed, for discussion purposes, 30 chemicals with high predicted bioconcentration and low rate of biodegradation and 28 with long range atmospheric transport potential based on predicted atmospheric oxidation half-lives >2 days and log air-water partition coefficients > or =5 and < or =1. These chemicals are a diverse group including halogenated organics, cyclic siloxanes, and substituted aromatics. Some of these chemicals and their transformation products may be candidates for future environmental monitoring. However, to improve these predictions data on emissions from end use are needed to refine environmental fate predictions, and analytical methods may need to be developed.
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Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.; ...
2017-07-06
Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.
2017-07-06
Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO2 which shows almost twice the variability in cumulative land uptake sincemore » 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Huntzinger, D. N.; Michalak, A. M.; Schwalm, C.
Terrestrial ecosystems play a vital role in regulating the accumulation of carbon (C) in the atmosphere. Understanding the factors controlling land C uptake is critical for reducing uncertainties in projections of future climate. The relative importance of changing climate, rising atmospheric CO 2, and other factors, however, remains unclear despite decades of research. Here, we use an ensemble of land models to show that models disagree on the primary driver of cumulative C uptake for 85% of vegetated land area. Disagreement is largest in model sensitivity to rising atmospheric CO 2 which shows almost twice the variability in cumulative landmore » uptake since 1901 (1 s.d. of 212.8 PgC vs. 138.5 PgC, respectively). We find that variability in CO 2 and temperature sensitivity is attributable, in part, to their compensatory effects on C uptake, whereby comparable estimates of C uptake can arise by invoking different sensitivities to key environmental conditions. Conversely, divergent estimates of C uptake can occur despite being based on the same environmental sensitivities. Together, these findings imply an important limitation to the predictability of C cycling and climate under unprecedented environmental conditions. We suggest that the carbon modeling community prioritize a probabilistic multi-model approach to generate more robust C cycle projections.« less
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Ecological suitability modeling for anthrax in the Kruger National Park, South Africa
Steenkamp, Pieter Johan; van Schalkwyk, Ockert Louis
2018-01-01
The spores of the soil-borne bacterium, Bacillus anthracis, which causes anthrax are highly resistant to adverse environmental conditions. Under ideal conditions, anthrax spores can survive for many years in the soil. Anthrax is known to be endemic in the northern part of Kruger National Park (KNP) in South Africa (SA), with occasional epidemics spreading southward. The aim of this study was to identify and map areas that are ecologically suitable for the harboring of B. anthracis spores within the KNP. Anthrax surveillance data and selected environmental variables were used as inputs to the maximum entropy (Maxent) species distribution modeling method. Anthrax positive carcasses from 1988–2011 in KNP (n = 597) and a total of 40 environmental variables were used to predict and evaluate their relative contribution to suitability for anthrax occurrence in KNP. The environmental variables that contributed the most to the occurrence of anthrax were soil type, normalized difference vegetation index (NDVI) and precipitation. Apart from the endemic Pafuri region, several other areas within KNP were classified as ecologically suitable. The outputs of this study could guide future surveillance efforts to focus on predicted suitable areas for anthrax, since the KNP currently uses passive surveillance to detect anthrax outbreaks. PMID:29377918
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Biological indicators for monitoring water quality of MTF canals system
NASA Technical Reports Server (NTRS)
Sethi, S. L.
1975-01-01
Biological models, diversity indexes, were developed to predict environmental effects of NASA's Mississippi test facility (MTF) chemical operations on canal systems in the area. To predict the effects on local streams, a physical model of unpolluted streams was established. The model is fed by artesian well water free of background levels of pollutants. The species diversity and biota composition of unpolluted MTF stream was determined; resulting information will be used to form baseline data for future comparisons. Biological modeling was accomplished by adding controlled quantities or kinds of chemical pollutants and evaluating the effects of these chemicals on the biological life of the stream.
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ERIC Educational Resources Information Center
Liu, Shu-Chiu; Lin, Huann-shyang
2018-01-01
The purpose of the study was to explore undergraduate students' views about environmental futures that are preferred or desirable for them, and to further examine relationships between specific future-related views and general environmental attitudes. 96 students from one reputable public university in Taiwan participated in a survey that included…
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The fast debris evolution model
NASA Astrophysics Data System (ADS)
Lewis, H. G.; Swinerd, G. G.; Newland, R. J.; Saunders, A.
2009-09-01
The 'particles-in-a-box' (PIB) model introduced by Talent [Talent, D.L. Analytic model for orbital debris environmental management. J. Spacecraft Rocket, 29 (4), 508-513, 1992.] removed the need for computer-intensive Monte Carlo simulation to predict the gross characteristics of an evolving debris environment. The PIB model was described using a differential equation that allows the stability of the low Earth orbit (LEO) environment to be tested by a straightforward analysis of the equation's coefficients. As part of an ongoing research effort to investigate more efficient approaches to evolutionary modelling and to develop a suite of educational tools, a new PIB model has been developed. The model, entitled Fast Debris Evolution (FADE), employs a first-order differential equation to describe the rate at which new objects ⩾10 cm are added and removed from the environment. Whilst Talent [Talent, D.L. Analytic model for orbital debris environmental management. J. Spacecraft Rocket, 29 (4), 508-513, 1992.] based the collision theory for the PIB approach on collisions between gas particles and adopted specific values for the parameters of the model from a number of references, the form and coefficients of the FADE model equations can be inferred from the outputs of future projections produced by high-fidelity models, such as the DAMAGE model. The FADE model has been implemented as a client-side, web-based service using JavaScript embedded within a HTML document. Due to the simple nature of the algorithm, FADE can deliver the results of future projections immediately in a graphical format, with complete user-control over key simulation parameters. Historical and future projections for the ⩾10 cm LEO debris environment under a variety of different scenarios are possible, including business as usual, no future launches, post-mission disposal and remediation. A selection of results is presented with comparisons with predictions made using the DAMAGE environment model. The results demonstrate that the FADE model is able to capture comparable time-series of collisions and number of objects as predicted by DAMAGE in several scenarios. Further, and perhaps more importantly, its speed and flexibility allows the user to explore and understand the evolution of the space debris environment.
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Changes in extreme events and the potential impacts on human health.
Bell, Jesse E; Brown, Claudia Langford; Conlon, Kathryn; Herring, Stephanie; Kunkel, Kenneth E; Lawrimore, Jay; Luber, George; Schreck, Carl; Smith, Adam; Uejio, Christopher
2018-04-01
Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future. Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.
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Small, Daniel P; Calosi, Piero; Boothroyd, Dominic; Widdicombe, Steve; Spicer, John I
2015-01-01
An organism's physiological processes form the link between its life-history traits and the prevailing environmental conditions, especially in species with complex life cycles. Understanding how these processes respond to changing environmental conditions, thereby affecting organismal development, is critical if we are to predict the biological implications of current and future global climate change. However, much of our knowledge is derived from adults or single developmental stages. Consequently, we investigated the metabolic rate, organic content, carapace mineralization, growth, and survival across each larval stage of the European lobster Homarus gammarus, reared under current and predicted future ocean warming and acidification scenarios. Larvae exhibited stage-specific changes in the temperature sensitivity of their metabolic rate. Elevated Pco2 increased C∶N ratios and interacted with elevated temperature to affect carapace mineralization. These changes were linked to concomitant changes in survivorship and growth, from which it was concluded that bottlenecks were evident during H. gammarus larval development in stages I and IV, the transition phases between the embryonic and pelagic larval stages and between the larval and megalopa stages, respectively. We therefore suggest that natural changes in optimum temperature during ontogeny will be key to larvae survival in a future warmer ocean. The interactions of these natural changes with elevated temperature and Pco2 significantly alter physiological condition and body size of the last larval stage before the transition from a planktonic to a benthic life style. Thus, living and growing in warm, hypercapnic waters could compromise larval lobster growth, development, and recruitment.
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The fate of threatened coastal dune habitats in Italy under climate change scenarios.
Prisco, Irene; Carboni, Marta; Acosta, Alicia T R
2013-01-01
Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an "indirect" plant-species-based one and a simple "direct" one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the "direct" approach was unsatisfactory, "indirect" models had a good predictive performance, highlighting the importance of using species' responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats' distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future.
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The Fate of Threatened Coastal Dune Habitats in Italy under Climate Change Scenarios
Prisco, Irene; Carboni, Marta; Acosta, Alicia T. R.
2013-01-01
Coastal dunes worldwide harbor threatened habitats characterized by high diversity in terms of plant communities. In Italy, recent assessments have highlighted the insufficient state of conservation of these habitats as defined by the EU Habitats Directive. The effects of predicted climate change could have dramatic consequences for coastal environments in the near future. An assessment of the efficacy of protection measures under climate change is thus a priority. Here, we have developed environmental envelope models for the most widespread dune habitats in Italy, following two complementary approaches: an “indirect” plant-species-based one and a simple “direct” one. We analyzed how habitats distribution will be altered under the effects of two climate change scenarios and evaluated if the current Italian network of protected areas will be effective in the future after distribution shifts. While modeling dune habitats with the “direct” approach was unsatisfactory, “indirect” models had a good predictive performance, highlighting the importance of using species’ responses to climate change for modeling these habitats. The results showed that habitats closer to the sea may even increase their geographical distribution in the near future. The transition dune habitat is projected to remain stable, although mobile and fixed dune habitats are projected to lose most of their actual geographical distribution, the latter being more sensitive to climate change effects. Gap analysis highlighted that the habitats’ distribution is currently adequately covered by protected areas, achieving the conservation target. However, according to predictions, protection level for mobile and fixed dune habitats is predicted to drop drastically under the climate change scenarios which we examined. Our results provide useful insights for setting management priorities and better addressing conservation efforts to preserve these threatened habitats in future. PMID:23874787
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Science from genes to landscapes
,
2015-08-26
The quality of life and economic strength in America hinges on healthy ecosystems that support living things and natural processes. Ecosystem science better enables society to understand how and why ecosystems change, to predict and forecast future changes, and to guide actions that can prevent damage to, and restore and sustain ecosystems. It is through this knowledge that informed decisions are made about natural resources that can enhance our Nation's economic and environmental well-being.
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Change We Can Fight Over: The Relationship between Arable Land Supply and Substate Conflict
2010-01-01
environmental impact of global warming has spurred a parallel discussion among national security academics and policymakers about the security...consequences of climate change. Roughly speaking, there are two camps in this discussion -one that ominously predicts the potential for global warming to spark...future climate change, but the stark reality is that global warming is already upon us. Thus, policymakers need to know -both now and in the coming
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Changes in Cleanup Strategies and Long-Term Monitoring Costs for DOE FUSRAP Sites-17241
DOE Office of Scientific and Technical Information (OSTI.GOV)
Castillo, Darina; Carpenter, Cliff; Roberts, Rebecca
2017-03-05
LM is preparing for the transfer of 11 new FUSRAP sites within the next 10 years from USACE, many of which will have substantially greater LTSM requirements than the current Completed sites. LM is analyzing the estimates for the level of effort required to monitor the new sites in order to make more customized and accurate predictions of future life cycle costs and environmental liabilities of these sites.
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Deruytter, David; Baert, Jan M; Nevejan, Nancy; De Schamphelaere, Karel A C; Janssen, Colin R
2017-12-01
Little is known about the effect of metal mixtures on marine organisms, especially after exposure to environmentally realistic concentrations. This information is, however, required to evaluate the need to include mixtures in future environmental risk assessment procedures. We assessed the effect of copper (Cu)-Nickel (Ni) binary mixtures on Mytilus edulis larval development using a full factorial design that included environmentally relevant metal concentrations and ratios. The reproducibility of the results was assessed by repeating this experiment 5 times. The observed mixture effects were compared with the effects predicted with the concentration addition model. Deviations from the concentration addition model were estimated using a Markov chain Monte-Carlo algorithm. This enabled the accurate estimation of the deviations and their uncertainty. The results demonstrated reproducibly that the type of interaction-synergism or antagonism-mainly depended on the Ni concentration. Antagonism was observed at high Ni concentrations, whereas synergism occurred at Ni concentrations as low as 4.9 μg Ni/L. This low (and realistic) Ni concentration was 1% of the median effective concentration (EC50) of Ni or 57% of the Ni predicted-no-effect concentration (PNEC) in the European Union environmental risk assessment. It is concluded that results from mixture studies should not be extrapolated to concentrations or ratios other than those investigated and that significant mixture interactions can occur at environmentally realistic concentrations. This should be accounted for in (marine) environmental risk assessment of metals. Environ Toxicol Chem 2017;36:3471-3479. © 2017 SETAC. © 2017 SETAC.
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[The Free Trade Agreement and environmental health in Mexico].
Hernández-Peña, P; Gutiérrez-Zúñiga, C; Zurutuza-Fernández, R; Jiménez-González, O
1993-01-01
This work offers an overview of the state of the art and future state of environmental health in our country from a viewpoint of the impact of the commercial opening established in the Free Trade Agreement among Mexico, the USA, and Canada. In the first section of this work, we analyze the expected economic changes resulting from the implementation of the FTA and foretells the way in which those changes will influence the present environmental and epidemiologic profiles of this country in the medium and long term. The main changes predicted by the analysis are, in the epidemiologic context, the acceleration of the transference of occupational, consumption, environmental and population risks, characteristic of industrialized countries, to the country's polarized epidemiologic profile; and, in the environmental context, a transition consisting of a broadening and composition of the spectrum of pollutants, including and important lagging of bacteriologic control. The second section offers an analysis of the predicted response capacity facing the new environmental risk dynamics in the country, encompassing regulation, normativeness and enforcement of environmental and consumer protection, as well as obstacles found in health services to the implementation of surveillance, detection and treatment of health damages caused by environmental factors. The analysis of the organized social response to these problems discloses a relative flexibility of the normativeness and enforcement functions in comparison with our northern neighbors, a paramount factor for the possible transference of environmental risks, as well as the informational and research deficiency about environmental issues, basic elements for sustaining environmental health in the country, aiming at speeding up the development and transference of technologies for prevention, detection and management of environmental risks in the country, drawing upon the systematization of our experience and that of our neighbors. This speeding process ought to match, in the medium term, the velocity of risk transference produced by the commercial opening. In this way, the commercial integration of North America will become a favorable context for the development of the environmental health infrastructure of the country.
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A predictive framework to understand forest responses to global change.
McMahon, Sean M; Dietze, Michael C; Hersh, Michelle H; Moran, Emily V; Clark, James S
2009-04-01
Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.
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A Novel Method for Satellite Maneuver Prediction
NASA Astrophysics Data System (ADS)
Shabarekh, C.; Kent-Bryant, J.; Keselman, G.; Mitidis, A.
2016-09-01
A space operations tradecraft consisting of detect-track-characterize-catalog is insufficient for maintaining Space Situational Awareness (SSA) as space becomes increasingly congested and contested. In this paper, we apply analytical methodology from the Geospatial-Intelligence (GEOINT) community to a key challenge in SSA: predicting where and when a satellite may maneuver in the future. We developed a machine learning approach to probabilistically characterize Patterns of Life (PoL) for geosynchronous (GEO) satellites. PoL are repeatable, predictable behaviors that an object exhibits within a context and is driven by spatio-temporal, relational, environmental and physical constraints. An example of PoL are station-keeping maneuvers in GEO which become generally predictable as the satellite re-positions itself to account for orbital perturbations. In an earlier publication, we demonstrated the ability to probabilistically predict maneuvers of the Galaxy 15 (NORAD ID: 28884) satellite with high confidence eight days in advance of the actual maneuver. Additionally, we were able to detect deviations from expected PoL within hours of the predicted maneuver [6]. This was done with a custom unsupervised machine learning algorithm, the Interval Similarity Model (ISM), which learns repeating intervals of maneuver patterns from unlabeled historical observations and then predicts future maneuvers. In this paper, we introduce a supervised machine learning algorithm that works in conjunction with the ISM to produce a probabilistic distribution of when future maneuvers will occur. The supervised approach uses a Support Vector Machine (SVM) to process the orbit state whereas the ISM processes the temporal intervals between maneuvers and the physics-based characteristics of the maneuvers. This multiple model approach capitalizes on the mathematical strengths of each respective algorithm while incorporating multiple features and inputs. Initial findings indicate that the combined approach can predict 70% of maneuver times within 3 days of a true maneuver time and 22% of maneuver times within 24 hours of a maneuver. We have also been able to detect deviations from expected maneuver patterns up to a week in advance.
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How Sustainable is Groundwater Abstraction? A Global Assessment.
NASA Astrophysics Data System (ADS)
de Graaf, I.; Van Beek, R.; Gleeson, T. P.; Sutanudjaja, E.; Wada, Y.; Bierkens, M. F.
2016-12-01
Groundwater is the world's largest accessible freshwater resource and is of critical importance for irrigation, and thus for global food security. For regions with high demands, groundwater abstractions often exceed recharge and persistent groundwater depletion occurs. The direct effects of depletion are falling groundwater levels, increased pumping costs, land subsidence, and reduced baseflows to rivers. Water demands are expected to increase further due to growing population, economic development, and climate change, posing the urgent question how sustainable current water abstractions are worldwide and where and when these abstractions approach conceivable economic and environmental limits. In this study we estimated trends over 1960-2100 in groundwater levels, resulting from changes in demand and climate. We explored the limits of groundwater abstraction by predicting where and when groundwater levels drop that deep that groundwater gets unattainable for abstraction (economic limit) or, that groundwater baseflows to rivers drop below environmental requirements (environmental limit). We used a global hydrological model coupled to a groundwater model, meaning lateral groundwater flows, river infiltration and drainage, and infiltration and capillary-rise are simulated dynamically. Historical data and projections are used to prescribe water demands and climate forcing to the model. For the near future we used RCP8.5 and applied globally driest, average, and wettest GCM to test climate sensitivity. Results show that in general environmental limits are reached before economic limits, for example starting as early as the 1970s compared to the 1980s for economic limits in the upper Ganges basin. Economic limits are mostly related to regions with depletion, while environmental limits are reached also in regions were groundwater and surface water withdrawals are significant but depletion is not taking place (yet), for example in Spain and Portugal. In the near future, more regions will reach their limits, current depletion regions will expand and new regions experiencing depletion will develop. Regionally the increasing level of groundwater stress, economically and environmentally, will be an important factor in future economic development and could lead to socio-economic tension.
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How Sustainable is Groundwater Abstraction? A Global Assessment.
NASA Astrophysics Data System (ADS)
de Graaf, I.; Van Beek, R.; Gleeson, T. P.; Sutanudjaja, E.; Wada, Y.; Bierkens, M. F.
2017-12-01
Groundwater is the world's largest accessible freshwater resource and is of critical importance for irrigation, and thus for global food security. For regions with high demands, groundwater abstractions often exceed recharge and persistent groundwater depletion occurs. The direct effects of depletion are falling groundwater levels, increased pumping costs, land subsidence, and reduced baseflows to rivers. Water demands are expected to increase further due to growing population, economic development, and climate change, posing the urgent question how sustainable current water abstractions are worldwide and where and when these abstractions approach conceivable economic and environmental limits. In this study we estimated trends over 1960-2100 in groundwater levels, resulting from changes in demand and climate. We explored the limits of groundwater abstraction by predicting where and when groundwater levels drop that deep that groundwater gets unattainable for abstraction (economic limit) or, that groundwater baseflows to rivers drop below environmental requirements (environmental limit). We used a global hydrological model coupled to a groundwater model, meaning lateral groundwater flows, river infiltration and drainage, and infiltration and capillary-rise are simulated dynamically. Historical data and projections are used to prescribe water demands and climate forcing to the model. For the near future we used RCP8.5 and applied globally driest, average, and wettest GCM to test climate sensitivity. Results show that in general environmental limits are reached before economic limits, for example starting as early as the 1970s compared to the 1980s for economic limits in the upper Ganges basin. Economic limits are mostly related to regions with depletion, while environmental limits are reached also in regions were groundwater and surface water withdrawals are significant but depletion is not taking place (yet), for example in Spain and Portugal. In the near future, more regions will reach their limits, current depletion regions will expand and new regions experiencing depletion will develop. Regionally the increasing level of groundwater stress, economically and environmentally, will be an important factor in future economic development and could lead to socio-economic tension.
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Kwan, Paul; Welch, Mitchell
2017-01-01
In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus. An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops. PMID:28875085
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Al-Kindi, Khalifa M; Kwan, Paul; R Andrew, Nigel; Welch, Mitchell
2017-01-01
In order to understand the distribution and prevalence of Ommatissus lybicus (Hemiptera: Tropiduchidae) as well as analyse their current biographical patterns and predict their future spread, comprehensive and detailed information on the environmental, climatic, and agricultural practices are essential. The spatial analytical techniques such as Remote Sensing and Spatial Statistics Tools, can help detect and model spatial links and correlations between the presence, absence and density of O. lybicus in response to climatic, environmental, and human factors. The main objective of this paper is to review remote sensing and relevant analytical techniques that can be applied in mapping and modelling the habitat and population density of O. lybicus . An exhaustive search of related literature revealed that there are very limited studies linking location-based infestation levels of pests like the O. lybicus with climatic, environmental, and human practice related variables. This review also highlights the accumulated knowledge and addresses the gaps in this area of research. Furthermore, it makes recommendations for future studies, and gives suggestions on monitoring and surveillance methods in designing both local and regional level integrated pest management strategies of palm tree and other affected cultivated crops.
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Haynes, Vena N; Ward, J Evan; Russell, Brandon J; Agrios, Alexander G
2017-04-01
Nanoparticles are entering natural systems through product usage, industrial waste and post-consumer material degradation. As the production of nanoparticles is expected to increase in the next decade, so too are predicted environmental loads. Engineered metal-oxide nanomaterials, such as titanium dioxide, are known for their photocatalytic capabilities. When these nanoparticles are exposed to ultraviolet radiation in the environment, however, they can produce radicals that are harmful to aquatic organisms. There have been a number of studies that have reported the toxicity of titanium dioxide nanoparticles in the absence of light. An increasing number of studies are assessing the interactive effects of nanoparticles and ultraviolet light. However, most of these studies neglect environmentally-relevant experimental conditions. For example, researchers are using nanoparticle concentrations and light intensities that are too high for natural systems, and are ignoring water constituents that can alter the light field. The purpose of this review is to summarize the current knowledge of the photocatalytic effects of TiO 2 nanoparticles on aquatic organisms, discuss the limitations of these studies, and outline environmentally-relevant factors that need to be considered in future experiments. Copyright © 2017 Elsevier B.V. All rights reserved.
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The impact of future climate on historic interiors.
Lankester, Paul; Brimblecombe, Peter
2012-02-15
The socio-economic significance of climate change is widely recognised. However, its potential to affect our cultural heritage has not been discussed in detail (i.e. not explicit in IPCC 4) even though the cultural impacts of future outdoor climate have been the focus of some European Commission projects (e.g. NOAH'S ARK) and World Heritage Centre reports. Recently there have been a few projects that have examined the changing environmental threats to tangible heritage indoors (e.g. Preparing Historic Collections for Climate Change and Climate for Culture). Here we predict future indoor temperature and humidity, and damage arising from changes to climate in historic rooms in Southern England with little climate control, using simple building simulations coupled with high resolution (~5 km) climate predictions. The calculations suggest an increase in indoor temperature over the next century that is slightly less than that outdoors. Annual relative humidity shows little change, but the seasonal cycles suggest drier summers and slightly damper winters indoors. Damage from mould growth and pests is likely to increase in the future, while humidity driven dimensional change to materials (e.g. wood) should decrease somewhat. The results allow collection managers to prepare for the impact of long-term climate change, putting strategic measures in place to prevent increased damage, and thus preserve our heritage for future generations. Copyright © 2011 Elsevier B.V. All rights reserved.
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Spatio-temporal patterns of major bacterial groups in alpine waters.
Freimann, Remo; Bürgmann, Helmut; Findlay, Stuart E G; Robinson, Christopher T
2014-01-01
Glacial alpine landscapes are undergoing rapid transformation due to changes in climate. The loss of glacial ice mass has directly influenced hydrologic characteristics of alpine floodplains. Consequently, hyporheic sediment conditions are likely to change in the future as surface waters fed by glacial water (kryal) become groundwater dominated (krenal). Such environmental shifts may subsequently change bacterial community structure and thus potential ecosystem functioning. We quantitatively investigated the structure of major bacterial groups in glacial and groundwater-fed streams in three alpine floodplains during different hydrologic periods. Our results show the importance of several physico-chemical variables that reflect local geological characteristics as well as water source in structuring bacterial groups. For instance, Alpha-, Betaproteobacteria and Cytophaga-Flavobacteria were influenced by pH, conductivity and temperature as well as by inorganic and organic carbon compounds, whereas phosphorous compounds and nitrate showed specific influence on single bacterial groups. These results can be used to predict future bacterial group shifts, and potential ecosystem functioning, in alpine landscapes under environmental transformation.
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Hannigan, L J; Walaker, N; Waszczuk, M A; McAdams, T A; Eley, T C
2017-01-01
Emotional and behavioural problems in childhood and adolescence can be chronic and are predictive of future psychiatric problems. Understanding what factors drive the development and maintenance of these problems is therefore crucial. Longitudinal behavioural genetic studies using twin, sibling or adoption data can be used to explore the developmental aetiology of stability and change in childhood and adolescent psychopathology. We present a systematic review of longitudinal, behavioural genetic analyses of emotional and behavioural problems between ages 0 to 18 years. We identified 58 studies, of which 19 examined emotional problems, 30 examined behavioural problems, and 9 examined both. In the majority of studies, stability in emotional and behavioural problems was primarily genetically influenced. Stable environmental factors were also widely found, although these typically played a smaller role. Both genetic and environmental factors were involved in change across development. We discuss the findings in the context of the wider developmental literature and make recommendations for future research.
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Hannigan, L.J.; Walaker, N.; Waszczuk, M.A.; McAdams, T.A.; Eley, T.C.
2016-01-01
Emotional and behavioural problems in childhood and adolescence can be chronic and are predictive of future psychiatric problems. Understanding what factors drive the development and maintenance of these problems is therefore crucial. Longitudinal behavioural genetic studies using twin, sibling or adoption data can be used to explore the developmental aetiology of stability and change in childhood and adolescent psychopathology. We present a systematic review of longitudinal, behavioural genetic analyses of emotional and behavioural problems between ages 0 to 18 years. We identified 58 studies, of which 19 examined emotional problems, 30 examined behavioural problems, and 9 examined both. In the majority of studies, stability in emotional and behavioural problems was primarily genetically influenced. Stable environmental factors were also widely found, although these typically played a smaller role. Both genetic and environmental factors were involved in change across development. We discuss the findings in the context of the wider developmental literature and make recommendations for future research. PMID:28337341
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NASA Astrophysics Data System (ADS)
Gohardani, Omid; Elola, Maialen Chapartegui; Elizetxea, Cristina
2014-10-01
Carbon nanotubes have instigated the interest of many different scientific fields since their authenticated introduction, more than two decades ago. Particularly in aerospace applications, the potential implementations of these advanced materials have been predicted to have a large impact on future aircraft and space vehicles, mainly due to their distinct features, which include superior mechanical, thermal and electrical properties. This article provides the very first consolidated review of the imminent prospects of utilizing carbon nanotubes and nanoparticles in aerospace sciences, based on their recent implementations and predicted future applications. Explicitly, expected carbon nanotube employment in aeronautics and astronautics are identified for commercial aircraft, military aircraft, rotorcraft, unmanned aerial vehicles, satellites, and space launch vehicles. Attention is devoted to future utilization of carbon nanotubes, which may comprise hydrogen storage encapsulation, composite material implementation, lightning protection for aircraft, aircraft icing mitigation, reduced weight of airframes/satellites, and alleviation of challenges related to future space launch. This study further sheds light onto recent actualized implementations of carbon nanotubes in aerospace applications, as well as current and prospective challenges related to their usage in aerospace sciences, encompassing health and safety hazards, large scale manufacturing, achievement of optimum properties, recycling, and environmental impacts.
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Adapting environmental management to uncertain but inevitable change.
Nicol, Sam; Fuller, Richard A; Iwamura, Takuya; Chadès, Iadine
2015-06-07
Implementation of adaptation actions to protect biodiversity is limited by uncertainty about the future. One reason for this is the fear of making the wrong decisions caused by the myriad future scenarios presented to decision-makers. We propose an adaptive management (AM) method for optimally managing a population under uncertain and changing habitat conditions. Our approach incorporates multiple future scenarios and continually learns the best management strategy from observations, even as conditions change. We demonstrate the performance of our AM approach by applying it to the spatial management of migratory shorebird habitats on the East Asian-Australasian flyway, predicted to be severely impacted by future sea-level rise. By accounting for non-stationary dynamics, our solution protects 25,000 more birds per year than the current best stationary approach. Our approach can be applied to many ecological systems that require efficient adaptation strategies for an uncertain future. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
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Household location choices: implications for biodiversity conservation.
Peterson, M Nils; Chen, Xiaodong; Liu, Jianguo
2008-08-01
Successful conservation efforts require understanding human behaviors that directly affect biodiversity. Choice of household location represents an observable behavior that has direct effects on biodiversity conservation, but no one has examined the sociocultural predictors of this choice relative to its environmental impacts. We conducted a case study of the Teton Valley of Idaho and Wyoming (U.S.A.) that (1) explored relationships between sociodemographic variables, environmental attitudes, and the environmental impact of household location choices, (2) assessed the potential for small household sizes in natural areas to multiply the environmental impacts of household location decisions, and (3) evaluated how length of residency predicted the environmental attitudes of people living in natural areas. We collected sociodemographic data, spatial coordinates, and land-cover information in a survey of 416 households drawn from a random sample of Teton Valley residents (95% compliance rate). Immigrants (respondents not born in the study area) with the lowest education levels and least environmentally oriented attitudes lived in previously established residential areas in disproportionately high numbers, and older and more educated immigrants with the most environmentally oriented attitudes lived in natural areas in disproportionately high numbers. Income was not a significant predictor of household location decisions. Those living in natural areas had more environmental impact per person because of the location and because small households (<3 people/household) were 4 times as likely in natural areas as large households. Longer residency in natural areas predicted less environmentally oriented attitudes, suggesting that living in natural areas does not foster more concern for nature. Because populaces are rapidly aging, growing more educated, and potentially growing more environmentally oriented, these patterns are troubling for biodiversity conservation. Our results demonstrate a need for environmentalists to make household location decisions that reflect their environmental attitudes and future research to address how interactions between education level, environmental attitudes, population aging, and household location choices influence biodiversity conservation.
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Plumlee, Geoffrey S.; Alpers, Charles N.; Morman, Suzette A.; San Juan, Carma A.
2016-01-01
The ARkStorm Scenario predicts that a prolonged winter storm event across California would cause extreme precipitation, flooding, winds, physical damages, and economic impacts. This study uses a literature review and geographic information system-based analysis of national and state databases to infer how and where ARkStorm could cause environmental damages, release contamination from diverse natural and anthropogenic sources, affect ecosystem and human health, and cause economic impacts from environmental-remediation, liability, and health-care costs. Examples of plausible ARkStorm environmental and health concerns include complex mixtures of contaminants such as petroleum, mercury, asbestos, persistent organic pollutants, molds, and pathogens; adverse physical and contamination impacts on riverine and coastal marine ecosystems; and increased incidences of mold-related health concerns, some vector-borne diseases, and valley fever. Coastal cities, the San Francisco Bay area, the Sacramento-San Joaquin River Delta, parts of the Central Valley, and some mountainous areas would likely be most affected. This type of screening analysis, coupled with follow-up local assessments, can help stakeholders in California and disaster-prone areas elsewhere better plan for, mitigate, and respond to future environmental disasters.
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OCEAN THERMAL ENERGY CONVERSION (OTEC) PROGRAMMATIC ENVIRONMENTAL ANALYSIS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sands, M. D.
1980-01-01
This programmatic environmental analysis is an initial assessment of OTEC technology considering development, demonstration and commercialization; it is concluded that the OTEC development program should continue because the development, demonstration, and commercialization on a single-plant deployment basis should not present significant environmental impacts. However, several areas within the OTEC program require further investigation in order to assess the potential for environmental impacts from OTEC operation, particularly in large-scale deployments and in defining alternatives to closed-cycle biofouling control: (1) Larger-scale deployments of OTEC clusters or parks require further investigations in order to assess optimal platform siting distances necessary to minimize adversemore » environmental impacts. (2) The deployment and operation of the preoperational platform (OTEC-1) and future demonstration platforms must be carefully monitored to refine environmental assessment predictions, and to provide design modifications which may mitigate or reduce environmental impacts for larger-scale operations. These platforms will provide a valuable opportunity to fully evaluate the intake and discharge configurations, biofouling control methods, and both short-term and long-term environmental effects associated with platform operations. (3) Successful development of OTEC technology to use the maximal resource capabilities and to minimize environmental effects will require a concerted environmental management program, encompassing many different disciplines and environmental specialties.« less
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Who Should Pick the Winners of Climate Change?
Webster, Michael S; Colton, Madhavi A; Darling, Emily S; Armstrong, Jonathan; Pinsky, Malin L; Knowlton, Nancy; Schindler, Daniel E
2017-03-01
Many conservation strategies identify a narrow subset of genotypes, species, or geographic locations that are predicted to be favored under different scenarios of future climate change. However, a focus on predicted winners, which might not prove to be correct, risks undervaluing the balance of biological diversity from which climate-change winners could otherwise emerge. Drawing on ecology, evolutionary biology, and portfolio theory, we propose a conservation approach designed to promote adaptation that is less dependent on uncertain predictions about the identity of winners and losers. By designing actions to facilitate numerous opportunities for selection across biological and environmental conditions, we can allow nature to pick the winners and increase the probability that ecosystems continue to provide services to humans and other species. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Prevedouros, K; Jones, K C; Sweetman, A J
2004-11-15
The results from a modeling exercise utilizing the European variant (EVn) BETR multimedia environmental fate model are presented for selected polybrominated diphenyl ethers (PBDEs) of the technical penta- (Pe-) bromodiphenyl ether (BDE) product. The objectives of this study were to test PeBDE emission estimates from the literature for Europe by investigating the consistency between model predictions and ambient measurements to address the ability of the model to predict spatial variability and differences between congeners. Concurrently sampled and analyzed passive sampling air data, together with soil and grass data, were used as key model validation tools. The model steady-state simulations gave generally good agreement with measured data for BDE-47 and -99 with greater discrepancies for heavier congeners (e.g., BDE-153). To predict future atmospheric concentration trends, the model was used in its fully dynamic mode over the period 1970--2010. It was predicted that atmospheric concentrations peaked around 1997, declining with an overall "disappearance" half-life of 4.8 years. Soil and grass levels were underestimated by the model; possible reasons for differences with measurement data are further explored. Finally, the importance of temporally and spatially resolved environmental data sets is highlighted, while improved quantification of degradation half-lives is essential to better understand and predict the behavior of BDE congeners in PeBDE.
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Tools for beach health data management, data processing, and predictive model implementation
,
2013-01-01
This fact sheet describes utilities created for management of recreational waters to provide efficient data management, data aggregation, and predictive modeling as well as a prototype geographic information system (GIS)-based tool for data visualization and summary. All of these utilities were developed to assist beach managers in making decisions to protect public health. The Environmental Data Discovery and Transformation (EnDDaT) Web service identifies, compiles, and sorts environmental data from a variety of sources that help to define climatic, hydrologic, and hydrodynamic characteristics including multiple data sources within the U.S. Geological Survey and the National Oceanic and Atmospheric Administration. The Great Lakes Beach Health Database (GLBH-DB) and Web application was designed to provide a flexible input, export, and storage platform for beach water quality and sanitary survey monitoring data to compliment beach monitoring programs within the Great Lakes. A real-time predictive modeling strategy was implemented by combining the capabilities of EnDDaT and the GLBH-DB for timely, automated prediction of beach water quality. The GIS-based tool was developed to map beaches based on their physical and biological characteristics, which was shared with multiple partners to provide concepts and information for future Web-accessible beach data outlets.
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Holdway, Douglas A
2002-03-01
A review of the acute and chronic effects of produced formation water (PFW), drilling fluids (muds) including oil-based cutting muds, water-based cutting muds, ester-based cutting muds and chemical additives, and crude oils associated with offshore oil and gas production was undertaken in relation to both temperate and tropical marine ecological processes. The main environmental effects are summarized, often in tabular form. Generally, the temporal and spatial scales of these studies, along with the large levels of inherent variation in natural environments, have precluded our ability to predict the potential long-term environmental impacts of the offshore oil and gas production industry. A series of critical questions regarding the environmental effects of the offshore oil and gas production industry that still remain unanswered are provided for future consideration.
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Population impact of familial and environmental risk factors for schizophrenia: a nationwide study.
Sørensen, Holger J; Nielsen, Philip R; Pedersen, Carsten B; Benros, Michael E; Nordentoft, Merete; Mortensen, Preben B
2014-03-01
Although several studies have examined the relative contributions of familial and environmental risk factors for schizophrenia, few have additionally examined the predictive power on the individual level and simultaneously examined the population impact associated with a wide range of familial and environmental risk factors. The authors present rate ratios (IRR), population-attributable risks (PAR) and sex-specific cumulative incidences of the following risk factors: parental history of mental illness, urban place of birth, advanced paternal age, parental loss and immigration status. We established a population-based cohort of 2,486,646million persons born in Denmark between 1 January 1955 and 31 December 1993 using Danish registers. We found that PAR associated with urban birth was 11.73%; PAR associated with one, respectively 2, parent(s) with schizophrenia was 2.67% and 0.12%. PAR associated with second-generation immigration was 0.70%. Highest cumulative incidence (CI=20.23%; 95% CI=18.10-22.62) was found in male offspring of 2 parents with schizophrenia. Cumulative incidences for male offspring or female offspring of a parent with schizophrenia were 9.53% (95% CI=7.71-11.79), and 4.89%, (95% CI 4.50-5.31). The study showed that risk factors with highest predictive power on the individual level have a relatively low population impact. The challenge in future studies with direct genetic data is to examine gene-environmental interactions that can move research beyond current approaches and seek to achieve higher predictive power on the individual level and higher population impact. Copyright © 2014 Elsevier B.V. All rights reserved.
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Tapping environmental history to recreate America's colonial hydrology
Pastore, Christopher L.; Green, Mark B.; Bain, Daniel J.; Muñoz-Hernandez, Andrea; Vorosmarty, Charles J.; Arrigo, Jennifer; Brandt, Sara; Duncan, Jonathan M.; Greco, Francesca; Kim, Hyojin; Kumar, Sanjiv; Lally, Michael; Parolari, Anthony J.; Pellerin, Brian A.; Salant, Nira; Schlosser, Adam; Zalzal, Kate
2010-01-01
As scientists labor to understand present-day hydrologic systems and make predictions about the future, the value of expanding the geographic (1, 2) and temporal scopes (3, 4) of their studies has become increasingly evident. Pollen and tree-ring analyses have helped shed light on past climate and land-use patterns. But other nonscientific sources and methods can be equally revealing and in some cases complement empirical studies (5). This paper argues that environmental science, particularly that concerned with the human dimensions of water resources, stands to profit from using historical literature and archival sources. By considering work in environmental history, forging closer working relationships between the geophysical and social sciences, and seriously entertaining narratives as a form of evidence, environmental scientists can not only look farther into the past and across broader geographic areas, but they can also more accurately describe the nuances and complexities that define the ways humans have changed the world around them. In this paper, we present the recommendations of a multidisciplinary summer institute that developed 1) a conceptual and methodological framework for conducting historical hydrology, and 2) suggestions for ways that historical information can be used to inform the hydrologic sciences. Our intent here is to encourage further work along these or similar lines. We believe that future efforts that build on our famework and draw and expand upon the sources referenced below will produce scholarship of great utility to both environmental and social sciences.
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Delineating environmental control of phytoplankton biomass and phenology in the Southern Ocean
NASA Astrophysics Data System (ADS)
Ardyna, Mathieu; Claustre, Hervé; Sallée, Jean-Baptiste; D'Ovidio, Francesco; Gentili, Bernard; van Dijken, Gert; D'Ortenzio, Fabrizio; Arrigo, Kevin R.
2017-05-01
The Southern Ocean (SO), an area highly sensitive to climate change, is currently experiencing rapid warming and freshening. Such drastic physical changes might significantly alter the SO's biological pump. For more accurate predictions of the possible evolution of this pump, a better understanding of the environmental factors controlling SO phytoplankton dynamics is needed. Here we present a satellite-based study deciphering the complex environmental control of phytoplankton biomass (PB) and phenology (PH; timing and magnitude of phytoplankton blooms) in the SO. We reveal that PH and PB are mostly organized in the SO at two scales: a large latitudinal scale and a regional scale. Latitudinally, a clear gradient in the timing of bloom occurrence appears tightly linked to the seasonal cycle in irradiance, with some exceptions in specific light-limited regimes (i.e., well-mixed areas). Superimposed on this latitudinal scale, zonal asymmetries, up to 3 orders of magnitude, in regional-scale PB are mainly driven by local advective and iron supply processes. These findings provide a global understanding of PB and PH in the SO, which is of fundamental interest for identifying and explaining ongoing changes as well as predicting future changes in the SO biological pump.
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Environmental futures research at the U.S. Environmental Protection Agency
Robert L. Olson
2012-01-01
Relatively little research on environmental futures has been carried out in the United States. An exception is the long-running futures research that the U.S. Environmental Protection Agency (EPA) has been conducting since the 1970s. This paper reviews past and current efforts toward developing a capacity for environmental foresight within the EPA, and discusses some...
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Satellite remote sensing data can be used to model marine microbial metabolite turnover
Larsen, Peter E; Scott, Nicole; Post, Anton F; Field, Dawn; Knight, Rob; Hamada, Yuki; Gilbert, Jack A
2015-01-01
Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ∼3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology. PMID:25072414
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Thorne, Lesley H; Johnston, David W; Urban, Dean L; Tyne, Julian; Bejder, Lars; Baird, Robin W; Yin, Suzanne; Rickards, Susan H; Deakos, Mark H; Mobley, Joseph R; Pack, Adam A; Chapla Hill, Marie
2012-01-01
Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood.
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Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando
2014-03-01
Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.
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Satellite remote sensing data can be used to model marine microbial metabolite turnover
DOE Office of Scientific and Technical Information (OSTI.GOV)
Larsen, Peter E.; Scott, Nicole; Post, Anton F.
Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relativemore » abundance was highly correlated (Pearson Correlation 0.72, P-value <10-6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.« less
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Thorne, Lesley H.; Johnston, David W.; Urban, Dean L.; Tyne, Julian; Bejder, Lars; Baird, Robin W.; Yin, Suzanne; Rickards, Susan H.; Deakos, Mark H.; Mobley, Joseph R.; Pack, Adam A.; Chapla Hill, Marie
2012-01-01
Predictive habitat models can provide critical information that is necessary in many conservation applications. Using Maximum Entropy modeling, we characterized habitat relationships and generated spatial predictions of spinner dolphin (Stenella longirostris) resting habitat in the main Hawaiian Islands. Spinner dolphins in Hawai'i exhibit predictable daily movements, using inshore bays as resting habitat during daylight hours and foraging in offshore waters at night. There are growing concerns regarding the effects of human activities on spinner dolphins resting in coastal areas. However, the environmental factors that define suitable resting habitat remain unclear and must be assessed and quantified in order to properly address interactions between humans and spinner dolphins. We used a series of dolphin sightings from recent surveys in the main Hawaiian Islands and a suite of environmental variables hypothesized as being important to resting habitat to model spinner dolphin resting habitat. The model performed well in predicting resting habitat and indicated that proximity to deep water foraging areas, depth, the proportion of bays with shallow depths, and rugosity were important predictors of spinner dolphin habitat. Predicted locations of suitable spinner dolphin resting habitat provided in this study indicate areas where future survey efforts should be focused and highlight potential areas of conflict with human activities. This study provides an example of a presence-only habitat model used to inform the management of a species for which patterns of habitat availability are poorly understood. PMID:22937022
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Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi
2015-08-28
This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement.
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Underwater noise modelling for environmental impact assessment
DOE Office of Scientific and Technical Information (OSTI.GOV)
Farcas, Adrian; Thompson, Paul M.; Merchant, Nathan D., E-mail: nathan.merchant@cefas.co.uk
Assessment of underwater noise is increasingly required by regulators of development projects in marine and freshwater habitats, and noise pollution can be a constraining factor in the consenting process. Noise levels arising from the proposed activity are modelled and the potential impact on species of interest within the affected area is then evaluated. Although there is considerable uncertainty in the relationship between noise levels and impacts on aquatic species, the science underlying noise modelling is well understood. Nevertheless, many environmental impact assessments (EIAs) do not reflect best practice, and stakeholders and decision makers in the EIA process are often unfamiliarmore » with the concepts and terminology that are integral to interpreting noise exposure predictions. In this paper, we review the process of underwater noise modelling and explore the factors affecting predictions of noise exposure. Finally, we illustrate the consequences of errors and uncertainties in noise modelling, and discuss future research needs to reduce uncertainty in noise assessments.« less
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Cooper, Andrew James; Redman, Chelsea Anne; Stoneham, David Mark; Gonzalez, Luis Felipe; Etse, Victor Kwesi
2015-01-01
This paper presents an unmanned aircraft system (UAS) that uses a probabilistic model for autonomous front-on environmental sensing or photography of a target. The system is based on low-cost and readily-available sensor systems in dynamic environments and with the general intent of improving the capabilities of dynamic waypoint-based navigation systems for a low-cost UAS. The behavioural dynamics of target movement for the design of a Kalman filter and Markov model-based prediction algorithm are included. Geometrical concepts and the Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of a target, thus delivering a new waypoint for autonomous navigation. The results of the application to aerial filming with low-cost UAS are presented, achieving the desired goal of maintained front-on perspective without significant constraint to the route or pace of target movement. PMID:26343680
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The vegetation outlook (VegOut): a new method for predicting vegetation seasonal greenness
Tadesse, T.; Wardlow, B.; Hayes, M.; Svoboda, M.; Brown, J.
2010-01-01
The vegetation outlook (VegOut) is a geospatial tool for predicting general vegetation condition patterns across large areas. VegOut predicts a standardized seasonal greenness (SSG) measure, which represents a general indicator of relative vegetation health. VegOut predicts SSG values at multiple time steps (two to six weeks into the future) based on the analysis of "historical patterns" (i.e., patterns at each 1 km grid cell and time of the year) of satellite, climate, and oceanic data over an 18-year period (1989 to 2006). The model underlying VegOut capitalizes on historical climate-vegetation interactions and ocean-climate teleconnections (such as El Niño and the Southern Oscillation, ENSO) expressed over the 18-year data record and also considers several environmental characteristics (e.g., land use/cover type and soils) that influence vegetation's response to weather conditions to produce 1 km maps that depict future general vegetation conditions. VegOut provides regionallevel vegetation monitoring capabilities with local-scale information (e.g., county to sub-county level) that can complement more traditional remote sensing-based approaches that monitor "current" vegetation conditions. In this paper, the VegOut approach is discussed and a case study over the central United States for selected periods of the 2008 growing season is presented to demonstrate the potential of this new tool for assessing and predicting vegetation conditions.
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The UKC2 regional coupled prediction system
NASA Astrophysics Data System (ADS)
Castillo, Juan; Lewis, Huw; Graham, Jennifer; Saulter, Andrew; Arnold, Alex; Fallmann, Joachim; Martinez de la Torre, Alberto; Blyth, Eleanor; Bricheno, Lucy
2017-04-01
It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather through the environment, requires a more integrated approach to forecasting. This approach also delivers research benefits through providing tools with which to explore the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land. This hypothesis is being tested in a UK regional context at km-scale through the UK Environmental Prediction Project. This presentation will provide an introduction to the UKC2 UK Environmental Prediction research system. This incorporates models of the atmosphere (Met Office Unified Model), land surface (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled (via OASIS3-MCT libraries) at unprecedentedly high resolution across the UK and the wider north-west European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a unique new research tool for UK environmental science. The presentation will highlight work undertaken to review and improve the computational cost of running these systems for efficient research application. Research will be presented highlighting case study evaluation on the sensitivity of the ocean and surface waves to the representation of feedbacks to the atmosphere, and on the sensitivity of weather systems and boundary layer cloud development to the exchange of heat and momentum at the ocean surface modified through sea surface temperature and wave-induced roughness. The presentation will discuss plans for future development through UKC3 and beyond.
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Predicting asthma exacerbations in children.
Forno, Erick; Celedón, Juan C
2012-01-01
This review critically assesses recently published literature on predicting asthma exacerbations in children, while also providing general recommendations for future research in this field. Current evidence suggests that every effort should be made to provide optimal treatment to achieve adequate asthma control, as this will significantly reduce the risk of severe disease exacerbations. Children who have had at least one asthma exacerbation in the previous year are at highest risk for subsequent exacerbations, regardless of disease severity and/or control. Although several tools and biomarkers to predict asthma exacerbations have been recently developed, these approaches need further validation and/or have only had partial success in identifying children at risk. Although considerable progress has been made, much remains to be done. Future studies should clearly differentiate severe asthma exacerbations due to inadequate asthma control from those occurring in children whose asthma is well controlled, utilize standardized definitions of asthma exacerbations, and use a systematic approach to identify the best predictors after accounting for the multiple dimensions of the problem. Our ability to correctly predict the development of severe asthma exacerbations in an individual child should improve in parallel with increased knowledge and/or understanding of the complex interactions among genetic, environmental (e.g. viral infections) and lifestyle (e.g. adherence to treatment) factors underlying these events.
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Concepts and tools for predictive modeling of microbial dynamics.
Bernaerts, Kristel; Dens, Els; Vereecken, Karen; Geeraerd, Annemie H; Standaert, Arnout R; Devlieghere, Frank; Debevere, Johan; Van Impe, Jan F
2004-09-01
Description of microbial cell (population) behavior as influenced by dynamically changing environmental conditions intrinsically needs dynamic mathematical models. In the past, major effort has been put into the modeling of microbial growth and inactivation within a constant environment (static models). In the early 1990s, differential equation models (dynamic models) were introduced in the field of predictive microbiology. Here, we present a general dynamic model-building concept describing microbial evolution under dynamic conditions. Starting from an elementary model building block, the model structure can be gradually complexified to incorporate increasing numbers of influencing factors. Based on two case studies, the fundamentals of both macroscopic (population) and microscopic (individual) modeling approaches are revisited. These illustrations deal with the modeling of (i) microbial lag under variable temperature conditions and (ii) interspecies microbial interactions mediated by lactic acid production (product inhibition). Current and future research trends should address the need for (i) more specific measurements at the cell and/or population level, (ii) measurements under dynamic conditions, and (iii) more comprehensive (mechanistically inspired) model structures. In the context of quantitative microbial risk assessment, complexity of the mathematical model must be kept under control. An important challenge for the future is determination of a satisfactory trade-off between predictive power and manageability of predictive microbiology models.
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Integrated environmental modeling: a vision and roadmap for the future
Laniak, Gerard F.; Olchin, Gabriel; Goodall, Jonathan; Voinov, Alexey; Hill, Mary; Glynn, Pierre; Whelan, Gene; Geller, Gary; Quinn, Nigel; Blind, Michiel; Peckham, Scott; Reaney, Sim; Gaber, Noha; Kennedy, Philip R.; Hughes, Andrew
2013-01-01
Integrated environmental modeling (IEM) is inspired by modern environmental problems, decisions, and policies and enabled by transdisciplinary science and computer capabilities that allow the environment to be considered in a holistic way. The problems are characterized by the extent of the environmental system involved, dynamic and interdependent nature of stressors and their impacts, diversity of stakeholders, and integration of social, economic, and environmental considerations. IEM provides a science-based structure to develop and organize relevant knowledge and information and apply it to explain, explore, and predict the behavior of environmental systems in response to human and natural sources of stress. During the past several years a number of workshops were held that brought IEM practitioners together to share experiences and discuss future needs and directions. In this paper we organize and present the results of these discussions. IEM is presented as a landscape containing four interdependent elements: applications, science, technology, and community. The elements are described from the perspective of their role in the landscape, current practices, and challenges that must be addressed. Workshop participants envision a global scale IEM community that leverages modern technologies to streamline the movement of science-based knowledge from its sources in research, through its organization into databases and models, to its integration and application for problem solving purposes. Achieving this vision will require that the global community of IEM stakeholders transcend social, and organizational boundaries and pursue greater levels of collaboration. Among the highest priorities for community action are the development of standards for publishing IEM data and models in forms suitable for automated discovery, access, and integration; education of the next generation of environmental stakeholders, with a focus on transdisciplinary research, development, and decision making; and providing a web-based platform for community interactions (e.g., continuous virtual workshops).
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Egbendewe-Mondzozo, Aklesso; Swinton, S.; Izaurralde, Roberto C.
2013-03-01
This paper evaluates environmental policy effects on ligno-cellulosic biomass production and environ- mental outcomes using an integrated bioeconomic optimization model. The environmental policy integrated climate (EPIC) model is used to simulate crop yields and environmental indicators in current and future potential bioenergy cropping systems based on weather, topographic and soil data. The crop yield and environmental outcome parameters from EPIC are combined with biomass transport costs and economic parameters in a representative farmer profit-maximizing mathematical optimization model. The model is used to predict the impact of alternative policies on biomass production and environmental outcomes. We find that without environmental policy,more » rising biomass prices initially trigger production of annual crop residues, resulting in increased greenhouse gas emissions, soil erosion, and nutrient losses to surface and ground water. At higher biomass prices, perennial bioenergy crops replace annual crop residues as biomass sources, resulting in lower environmental impacts. Simulations of three environmental policies namely a carbon price, a no-till area subsidy, and a fertilizer tax reveal that only the carbon price policy systematically mitigates environmental impacts. The fertilizer tax is ineffectual and too costly to farmers. The no-till subsidy is effective only at low biomass prices and is too costly to government.« less
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Welcome to NASA's Earth Science Enterprise: Educational CD-ROM Activity Supplement
NASA Technical Reports Server (NTRS)
1999-01-01
Since its inception in 1958, NASA has been studying the Earth and its changing environment by observing the atmosphere, oceans, land, ice, and snow, and their influence on weather and climate. We now understand that the key to gaining a better understanding of the global environment is exploring how the Earth's systems of air, land, water, and life interact with each other. This approach-called Earth Systems Science-blends together fields like meteorology, oceanography, geology, and biology. In 1991, NASA launched a more comprehensive program to study the Earth as an integrated environmental system. They call it NASA's Earth Science Enterprise. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). EOS is series of satellites to be launched over the next two decades that will be used to intensively study the Earth, with the hopes of expanding our under- standing of how natural processes affect us, and how we might be affecting them. Such studies will yield improved weather forecasts, tools for managing agriculture and forests, information for fishermen and local planners, and, eventually, the ability to predict how the climate will change in the future. Today's program is laying the foundation for long-term environmental and climate monitoring and prediction. Potentially, this will provide the understanding needed in the future to support difficult decisions regarding the Earth's environment.
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Jarnevich, Catherine S.; Young, Nicholas E; Sheffels, Trevor R.; Carter, Jacoby; Systma, Mark D.; Talbert, Colin
2017-01-01
Invasive species provide a unique opportunity to evaluate factors controlling biogeographic distributions; we can consider introduction success as an experiment testing suitability of environmental conditions. Predicting potential distributions of spreading species is not easy, and forecasting potential distributions with changing climate is even more difficult. Using the globally invasive coypu (Myocastor coypus [Molina, 1782]), we evaluate and compare the utility of a simplistic ecophysiological based model and a correlative model to predict current and future distribution. The ecophysiological model was based on winter temperature relationships with nutria survival. We developed correlative statistical models using the Software for Assisted Habitat Modeling and biologically relevant climate data with a global extent. We applied the ecophysiological based model to several global circulation model (GCM) predictions for mid-century. We used global coypu introduction data to evaluate these models and to explore a hypothesized physiological limitation, finding general agreement with known coypu distribution locally and globally and support for an upper thermal tolerance threshold. Global circulation model based model results showed variability in coypu predicted distribution among GCMs, but had general agreement of increasing suitable area in the USA. Our methods highlighted the dynamic nature of the edges of the coypu distribution due to climate non-equilibrium, and uncertainty associated with forecasting future distributions. Areas deemed suitable habitat, especially those on the edge of the current known range, could be used for early detection of the spread of coypu populations for management purposes. Combining approaches can be beneficial to predicting potential distributions of invasive species now and in the future and in exploring hypotheses of factors controlling distributions.
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Yin, Guanyi; Liu, Liming; Yuan, Chengcheng
2015-07-01
This study primarily examined the assessment of environmental risk in high intensity agricultural areas. Dongting Lake basin was taken as a case study, which is one of the major grain producing areas in China. Using data obtained from 1989 to 2012, we applied Material Flow Analysis (MFA) to show the material consumption, pollutant output and production storage in the agricultural-environmental system and assessed the environmental risk index on the basis of the MFA results. The results predicted that the status of the environmental quality of the Dongting Lake area is unsatisfactory for the foreseeable future. The direct material input (DMI) declined by 13.9%, the domestic processed output (DPO) increased by 28.21%, the intensity of material consumption (IMC) decreased by 36.7%, the intensity of material discharge (IMD) increased by 10%, the material productivity (MP) increased by 27 times, the environmental efficiency (EE) increased by 15.31 times, and the material storage (PAS) increased by 0.23%. The DMI and DPO was higher at rural places on the edge of cities, whereas the risk of urban agriculture has arisen due to the higher increasing rate of DMI and DPO in cities compared with the counties. The composite environmental risk index increased from 0.33 to 0.96, indicating that the total environmental risk changed gradually but seriously during the 24 years assessed. The driving factors that affect environmental risk in high intensity agriculture can be divided into five classes: social, economic, human, natural and disruptive incidents. This study discussed a number of effective measures for protecting the environment while ensuring food production yields. Additional research in other areas and certain improvements of this method in future studies may be necessary to develop a more effective method of managing and controlling agricultural-environmental interactions.
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A global map of suitability for coastal Vibrio cholerae under current and future climate conditions.
Escobar, Luis E; Ryan, Sadie J; Stewart-Ibarra, Anna M; Finkelstein, Julia L; King, Christine A; Qiao, Huijie; Polhemus, Mark E
2015-09-01
Vibrio cholerae is a globally distributed water-borne pathogen that causes severe diarrheal disease and mortality, with current outbreaks as part of the seventh pandemic. Further understanding of the role of environmental factors in potential pathogen distribution and corresponding V. cholerae disease transmission over time and space is urgently needed to target surveillance of cholera and other climate and water-sensitive diseases. We used an ecological niche model (ENM) to identify environmental variables associated with V. cholerae presence in marine environments, to project a global model of V. cholerae distribution in ocean waters under current and future climate scenarios. We generated an ENM using published reports of V. cholerae in seawater and freely available remotely sensed imagery. Models indicated that factors associated with V. cholerae presence included chlorophyll-a, pH, and sea surface temperature (SST), with chlorophyll-a demonstrating the greatest explanatory power from variables selected for model calibration. We identified specific geographic areas for potential V. cholerae distribution. Coastal Bangladesh, where cholera is endemic, was found to be environmentally similar to coastal areas in Latin America. In a conservative climate change scenario, we observed a predicted increase in areas with environmental conditions suitable for V. cholerae. Findings highlight the potential for vulnerability maps to inform cholera surveillance, early warning systems, and disease prevention and control. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Caffarra, Amelia; Zottele, Fabio; Gleeson, Emily; Donnelly, Alison
2014-05-01
In order to predict the impact of future climate warming on trees it is important to quantify the effect climate has on their development. Our understanding of the phenological response to environmental drivers has given rise to various mathematical models of the annual growth cycle of plants. These models simulate the timing of phenophases by quantifying the relationship between development and its triggers, typically temperature. In addition, other environmental variables have an important role in determining the timing of budburst. For example, photoperiod has been shown to have a strong influence on phenological events of a number of tree species, including Betula pubescens (birch). A recently developed model for birch (DORMPHOT), which integrates the effects of temperature and photoperiod on budburst, was applied to future temperature projections from a 19-member ensemble of regional climate simulations (on a 25 km grid) generated as part of the ENSEMBLES project, to simulate the timing of birch budburst in Ireland each year up to the end of the present century. Gridded temperature time series data from the climate simulations were used as input to the DORMPHOT model to simulate future budburst timing. The results showed an advancing trend in the timing of birch budburst over most regions in Ireland up to 2100. Interestingly, this trend appeared greater in the northeast of the country than in the southwest, where budburst is currently relatively early. These results could have implications for future forest planning, species distribution modeling, and the birch allergy season.
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Modeling behavioral thermoregulation in a climate change sentinel.
Moyer-Horner, Lucas; Mathewson, Paul D; Jones, Gavin M; Kearney, Michael R; Porter, Warren P
2015-12-01
When possible, many species will shift in elevation or latitude in response to rising temperatures. However, before such shifts occur, individuals will first tolerate environmental change and then modify their behavior to maintain heat balance. Behavioral thermoregulation allows animals a range of climatic tolerances and makes predicting geographic responses under future warming scenarios challenging. Because behavioral modification may reduce an individual's fecundity by, for example, limiting foraging time and thus caloric intake, we must consider the range of behavioral options available for thermoregulation to accurately predict climate change impacts on individual species. To date, few studies have identified mechanistic links between an organism's daily activities and the need to thermoregulate. We used a biophysical model, Niche Mapper, to mechanistically model microclimate conditions and thermoregulatory behavior for a temperature-sensitive mammal, the American pika (Ochotona princeps). Niche Mapper accurately simulated microclimate conditions, as well as empirical metabolic chamber data for a range of fur properties, animal sizes, and environmental parameters. Niche Mapper predicted pikas would be behaviorally constrained because of the need to thermoregulate during the hottest times of the day. We also showed that pikas at low elevations could receive energetic benefits by being smaller in size and maintaining summer pelage during longer stretches of the active season under a future warming scenario. We observed pika behavior for 288 h in Glacier National Park, Montana, and thermally characterized their rocky, montane environment. We found that pikas were most active when temperatures were cooler, and at sites characterized by high elevations and north-facing slopes. Pikas became significantly less active across a suite of behaviors in the field when temperatures surpassed 20°C, which supported a metabolic threshold predicted by Niche Mapper. In general, mechanistic predictions and empirical observations were congruent. This research is unique in providing both an empirical and mechanistic description of the effects of temperature on a mammalian sentinel of climate change, the American pika. Our results suggest that previously underinvestigated characteristics, specifically fur properties and body size, may play critical roles in pika populations' response to climate change. We also demonstrate the potential importance of considering behavioral thermoregulation and microclimate variability when predicting animal responses to climate change.
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NASA Technical Reports Server (NTRS)
Urquhart, Erin A.; Zaitchik, Benjamin F.; Waugh, Darryn W.; Guikema, Seth D.; Del Castillo, Carlos E.
2014-01-01
The effect that climate change and variability will have on waterborne bacteria is a topic of increasing concern for coastal ecosystems, including the Chesapeake Bay. Surface water temperature trends in the Bay indicate a warming pattern of roughly 0.3-0.4 C per decade over the past 30 years. It is unclear what impact future warming will have on pathogens currently found in the Bay, including Vibrio spp. Using historical environmental data, combined with three different statistical models of Vibrio vulnificus probability, we explore the relationship between environmental change and predicted Vibrio vulnificus presence in the upper Chesapeake Bay. We find that the predicted response of V. vulnificus probability to high temperatures in the Bay differs systematically between models of differing structure. As existing publicly available datasets are inadequate to determine which model structure is most appropriate, the impact of climatic change on the probability of V. vulnificus presence in the Chesapeake Bay remains uncertain. This result points to the challenge of characterizing climate sensitivity of ecological systems in which data are sparse and only statistical models of ecological sensitivity exist.
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From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine
Everett, Jeremy R.
2016-01-01
Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments. PMID:27660611
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The Changing Science of Urban Transportation Planning
NASA Astrophysics Data System (ADS)
Kloster, Tom
2010-03-01
The last half of the 20th Century was the age of the automobile, and the development of bigger and faster roads defined urban planning for more than 50 years. During this period, transportation planners developed sophisticated behavior models to help predict future travel patterns in an attempt to keep pace with ever-growing congestion and public demand for more roads. By the 1990s, however, it was clear that eliminating congestion with new road capacity was an unattainable outcome, and had unintended effects that were never considered when the automobile era first emerged. Today, public expectations are rapidly evolving beyond ``building our way out'' of congestion, and toward more complex definitions of desired outcomes in transportation planning. In this new century, planners must improve behavior models to predict not only the travel patterns of the future, but also the subsequent environmental, social and public health effects associated with growth and changes in travel behavior, and provide alternative transportation solutions that respond to these broader outcomes.
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Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters
NASA Astrophysics Data System (ADS)
Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.
2016-12-01
Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.
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Optimising Habitat-Based Models for Wide-Ranging Marine Predators: Scale Matters
NASA Astrophysics Data System (ADS)
Scales, K. L.; Hazen, E. L.; Jacox, M.; Edwards, C. A.; Bograd, S. J.
2016-02-01
Predicting the responses of marine top predators to dynamic oceanographic conditions requires habitat-based models that sufficiently capture environmental preferences. Spatial resolution and temporal averaging of environmental data layers is a key aspect of model construction. The utility of surfaces contemporaneous to animal movement (e.g. daily, weekly), versus synoptic products (monthly, seasonal, climatological) is currently under debate, as is the optimal spatial resolution for predictive products. Using movement simulations with built-in environmental preferences (correlated random walks, multi-state hidden Markov-type models) together with modeled (Regional Oceanographic Modeling System, ROMS) and remotely-sensed (MODIS-Aqua) datasets, we explored the effects of degrading environmental surfaces (3km - 1 degree, daily - climatological) on model inference. We simulated the movements of a hypothetical wide-ranging marine predator through the California Current system over a three month period (May-June-July), based on metrics derived from previously published blue whale Balaenoptera musculus tracking studies. Results indicate that models using seasonal or climatological data fields can overfit true environmental preferences, in both presence-absence and behaviour-based model formulations. Moreover, the effects of a degradation in spatial resolution are more pronounced when using temporally averaged fields than when using daily, weekly or monthly datasets. In addition, we observed a notable divergence between the `best' models selected using common methods (e.g. AUC, AICc) and those that most accurately reproduced built-in environmental preferences. These findings have important implications for conservation and management of marine mammals, seabirds, sharks, sea turtles and large teleost fish, particularly in implementing dynamic ocean management initiatives and in forecasting responses to future climate-mediated ecosystem change.
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Climate Change Assessment of Precipitation in Tandula Reservoir System
NASA Astrophysics Data System (ADS)
Jaiswal, Rahul Kumar; Tiwari, H. L.; Lohani, A. K.
2018-02-01
The precipitation is the principle input of hydrological cycle affect availability of water in spatial and temporal scale of basin due to widely accepted climate change. The present study deals with the statistical downscaling using Statistical Down Scaling Model for rainfall of five rain gauge stations (Ambagarh, Bhanpura, Balod, Chamra and Gondli) in Tandula, Kharkhara and Gondli reservoirs of Chhattisgarh state of India to forecast future rainfall in three different periods under SRES A1B and A2 climatic forcing conditions. In the analysis, twenty-six climatic variables obtained from National Centers for Environmental Prediction were used and statistically tested for selection of best-fit predictors. The conditional process based statistical correlation was used to evolve multiple linear relations in calibration for period of 1981-1995 was tested with independent data of 1996-2003 for validation. The developed relations were further used to predict future rainfall scenarios for three different periods 2020-2035 (FP-1), 2046-2064 (FP-2) and 2081-2100 (FP-3) and compared with monthly rainfalls during base period (1981-2003) for individual station and all three reservoir catchments. From the analysis, it has been found that most of the rain gauge stations and all three reservoir catchments may receive significant less rainfall in future. The Thiessen polygon based annual and seasonal rainfall for different catchments confirmed a reduction of seasonal rainfall from 5.1 to 14.1% in Tandula reservoir, 11-19.2% in Kharkhara reservoir and 15.1-23.8% in Gondli reservoir. The Gondli reservoir may be affected the most in term of water availability in future prediction periods.
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Lagerholm, Vendela K; Sandoval-Castellanos, Edson; Vaniscotte, Amélie; Potapova, Olga R; Tomek, Teresa; Bochenski, Zbigniew M; Shepherd, Paul; Barton, Nick; Van Dyck, Marie-Claire; Miller, Rebecca; Höglund, Jacob; Yoccoz, Nigel G; Dalén, Love; Stewart, John R
2017-04-01
Global warming is predicted to cause substantial habitat rearrangements, with the most severe effects expected to occur in high-latitude biomes. However, one major uncertainty is whether species will be able to shift their ranges to keep pace with climate-driven environmental changes. Many recent studies on mammals have shown that past range contractions have been associated with local extinctions rather than survival by habitat tracking. Here, we have used an interdisciplinary approach that combines ancient DNA techniques, coalescent simulations and species distribution modelling, to investigate how two common cold-adapted bird species, willow and rock ptarmigan (Lagopus lagopus and Lagopus muta), respond to long-term climate warming. Contrary to previous findings in mammals, we demonstrate a genetic continuity in Europe over the last 20 millennia. Results from back-casted species distribution models suggest that this continuity may have been facilitated by uninterrupted habitat availability and potentially also the greater dispersal ability of birds. However, our predictions show that in the near future, some isolated regions will have little suitable habitat left, implying a future decrease in local populations at a scale unprecedented since the last glacial maximum. © 2016 John Wiley & Sons Ltd.
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Wu, Xiaolin; Davie-Martin, Cleo L; Steinlin, Christine; Hageman, Kimberly J; Cullen, Nicolas J; Bogdal, Christian
2017-10-17
Melting glaciers release previously ice-entrapped chemicals to the surrounding environment. As glacier melting accelerates under future climate warming, chemical release may also increase. This study investigated the behavior of semivolatile pesticides over the course of one year and predicted their behavior under two future climate change scenarios. Pesticides were quantified in air, lake water, glacial meltwater, and streamwater in the catchment of Lake Brewster, an alpine glacier-fed lake located in the Southern Alps of New Zealand. Two historic-use pesticides (endosulfan I and hexachlorobenzene) and three current-use pesticides (dacthal, triallate, and chlorpyrifos) were frequently found in both air and water samples from the catchment. Regression analysis indicated that the pesticide concentrations in glacial meltwater and lake water were strongly correlated. A multimedia environmental fate model was developed for these five chemicals in Brewster Lake. Modeling results indicated that seasonal lake ice cover melt, and varying contributions of input from glacial melt and streamwater, created pulses in pesticide concentrations in lake water. Under future climate scenarios, the concentration pulse was altered and glacial melt made a greater contribution (as mass flux) to pesticide input in the lake water.
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Li, Jin; Tran, Maggie; Siwabessy, Justy
2016-01-01
Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia’s marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to ‘small p and large n’ problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models. PMID:26890307
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Li, Jin; Tran, Maggie; Siwabessy, Justy
2016-01-01
Spatially continuous predictions of seabed hardness are important baseline environmental information for sustainable management of Australia's marine jurisdiction. Seabed hardness is often inferred from multibeam backscatter data with unknown accuracy and can be inferred from underwater video footage at limited locations. In this study, we classified the seabed into four classes based on two new seabed hardness classification schemes (i.e., hard90 and hard70). We developed optimal predictive models to predict seabed hardness using random forest (RF) based on the point data of hardness classes and spatially continuous multibeam data. Five feature selection (FS) methods that are variable importance (VI), averaged variable importance (AVI), knowledge informed AVI (KIAVI), Boruta and regularized RF (RRF) were tested based on predictive accuracy. Effects of highly correlated, important and unimportant predictors on the accuracy of RF predictive models were examined. Finally, spatial predictions generated using the most accurate models were visually examined and analysed. This study confirmed that: 1) hard90 and hard70 are effective seabed hardness classification schemes; 2) seabed hardness of four classes can be predicted with a high degree of accuracy; 3) the typical approach used to pre-select predictive variables by excluding highly correlated variables needs to be re-examined; 4) the identification of the important and unimportant predictors provides useful guidelines for further improving predictive models; 5) FS methods select the most accurate predictive model(s) instead of the most parsimonious ones, and AVI and Boruta are recommended for future studies; and 6) RF is an effective modelling method with high predictive accuracy for multi-level categorical data and can be applied to 'small p and large n' problems in environmental sciences. Additionally, automated computational programs for AVI need to be developed to increase its computational efficiency and caution should be taken when applying filter FS methods in selecting predictive models.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Mishra, Umakant; Drewniak, Beth; Jastrow, Julie D.
Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation datamore » for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.« less
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Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David
2011-05-20
The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.
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NASA Technical Reports Server (NTRS)
Zhu, Dongming; Nemeth, Noel N.
2017-01-01
Advanced environmental barrier coatings will play an increasingly important role in future gas turbine engines because of their ability to protect emerging light-weight SiC/SiC ceramic matrix composite (CMC) engine components, further raising engine operating temperatures and performance. Because the environmental barrier coating systems are critical to the performance, reliability and durability of these hot-section ceramic engine components, a prime-reliant coating system along with established life design methodology are required for the hot-section ceramic component insertion into engine service. In this paper, we have first summarized some observations of high temperature, high-heat-flux environmental degradation and failure mechanisms of environmental barrier coating systems in laboratory simulated engine environment tests. In particular, the coating surface cracking morphologies and associated subsequent delamination mechanisms under the engine level high-heat-flux, combustion steam, and mechanical creep and fatigue loading conditions will be discussed. The EBC compostion and archtechture improvements based on advanced high heat flux environmental testing, and the modeling advances based on the integrated Finite Element Analysis Micromechanics Analysis Code/Ceramics Analysis and Reliability Evaluation of Structures (FEAMAC/CARES) program will also be highlighted. The stochastic progressive damage simulation successfully predicts mud flat damage pattern in EBCs on coated 3-D specimens, and a 2-D model of through-the-thickness cross-section. A 2-parameter Weibull distribution was assumed in characterizing the coating layer stochastic strength response and the formation of damage was therefore modeled. The damage initiation and coalescence into progressively smaller mudflat crack cells was demonstrated. A coating life prediction framework may be realized by examining the surface crack initiation and delamination propagation in conjunction with environmental degradation under high-heat-flux and environment load test conditions.
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NASA Astrophysics Data System (ADS)
Xu, Xijin; Tang, Qian; Xia, Haiyue; Zhang, Yuling; Li, Weiqiu; Huo, Xia
2016-04-01
Chaotic time series prediction based on nonlinear systems showed a superior performance in prediction field. We studied prenatal exposure to polychlorinated biphenyls (PCBs) by chaotic time series prediction using the least squares self-exciting threshold autoregressive (SEATR) model in umbilical cord blood in an electronic waste (e-waste) contaminated area. The specific prediction steps basing on the proposal methods for prenatal PCB exposure were put forward, and the proposed scheme’s validity was further verified by numerical simulation experiments. Experiment results show: 1) seven kinds of PCB congeners negatively correlate with five different indices for birth status: newborn weight, height, gestational age, Apgar score and anogenital distance; 2) prenatal PCB exposed group at greater risks compared to the reference group; 3) PCBs increasingly accumulated with time in newborns; and 4) the possibility of newborns suffering from related diseases in the future was greater. The desirable numerical simulation experiments results demonstrated the feasibility of applying mathematical model in the environmental toxicology field.
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Xu, Xijin; Tang, Qian; Xia, Haiyue; Zhang, Yuling; Li, Weiqiu; Huo, Xia
2016-01-01
Chaotic time series prediction based on nonlinear systems showed a superior performance in prediction field. We studied prenatal exposure to polychlorinated biphenyls (PCBs) by chaotic time series prediction using the least squares self-exciting threshold autoregressive (SEATR) model in umbilical cord blood in an electronic waste (e-waste) contaminated area. The specific prediction steps basing on the proposal methods for prenatal PCB exposure were put forward, and the proposed scheme’s validity was further verified by numerical simulation experiments. Experiment results show: 1) seven kinds of PCB congeners negatively correlate with five different indices for birth status: newborn weight, height, gestational age, Apgar score and anogenital distance; 2) prenatal PCB exposed group at greater risks compared to the reference group; 3) PCBs increasingly accumulated with time in newborns; and 4) the possibility of newborns suffering from related diseases in the future was greater. The desirable numerical simulation experiments results demonstrated the feasibility of applying mathematical model in the environmental toxicology field. PMID:27118260
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Global Pyrogeography: the Current and Future Distribution of Wildfire
Krawchuk, Meg A.; Moritz, Max A.; Parisien, Marc-André; Van Dorn, Jeff; Hayhoe, Katharine
2009-01-01
Climate change is expected to alter the geographic distribution of wildfire, a complex abiotic process that responds to a variety of spatial and environmental gradients. How future climate change may alter global wildfire activity, however, is still largely unknown. As a first step to quantifying potential change in global wildfire, we present a multivariate quantification of environmental drivers for the observed, current distribution of vegetation fires using statistical models of the relationship between fire activity and resources to burn, climate conditions, human influence, and lightning flash rates at a coarse spatiotemporal resolution (100 km, over one decade). We then demonstrate how these statistical models can be used to project future changes in global fire patterns, highlighting regional hotspots of change in fire probabilities under future climate conditions as simulated by a global climate model. Based on current conditions, our results illustrate how the availability of resources to burn and climate conditions conducive to combustion jointly determine why some parts of the world are fire-prone and others are fire-free. In contrast to any expectation that global warming should necessarily result in more fire, we find that regional increases in fire probabilities may be counter-balanced by decreases at other locations, due to the interplay of temperature and precipitation variables. Despite this net balance, our models predict substantial invasion and retreat of fire across large portions of the globe. These changes could have important effects on terrestrial ecosystems since alteration in fire activity may occur quite rapidly, generating ever more complex environmental challenges for species dispersing and adjusting to new climate conditions. Our findings highlight the potential for widespread impacts of climate change on wildfire, suggesting severely altered fire regimes and the need for more explicit inclusion of fire in research on global vegetation-climate change dynamics and conservation planning. PMID:19352494
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NBIC-Convergence of Machinery and Basic Technologies as the Ecological Factor of Wellbeing
NASA Astrophysics Data System (ADS)
Zhironkin, S. A.; Kolotov, K. A.; Genin, A. E.; Agafonov, F. V.; Kovalevsky, S. A.
2017-01-01
The development of science and technology in the XXI century is on the way of the extensive use of natural resources. As a result, the scientific and technical progress does not initiate the reduction of environmental damage but encourages its cumulative growth. So the environmental problems have become a serious threat to social wellbeing of all mankind. The development of the core technologies doesn’t allow creating the situation in which the new knowledge would generate positive changes in the environment. Therefore, among the issues that define the future of advanced environmental technologies, and potentially significant for the understanding of the humanities, there is the phenomenon of technological convergence and, in particular, the predicted convergence of the nano-, bio-, information and cognitive technologies (NBIC). The consequence of NBIC-convergence may be the transformation of the humanity into a single global mind, which can be linked into a solid set of technologies, establishing united standards for social wellbeing and environmental technologies.
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Lauria, V; Garofalo, G; Gristina, M; Fiorentino, F
2016-08-01
Conservation of fish habitat requires a deeper knowledge of how species distribution patterns are related to environmental factors. Habitat suitability modelling is an essential tool to quantify species' realised niches and understand species-environment relationships. Cephalopods are important players in the marine food web and a significant resource for fisheries; they are also very sensitive to environmental changes. Here a time series of fishery-independent data (1998-2011) was used to construct habitat suitability models and investigate the influence of environmental variables on four commercial cephalopods: Todaropsis eblanae, Illex coindetii, Eledone moschata and Eledone cirrhosa, in the central Mediterranean Sea. The main environmental predictors of cephalopod habitat suitability were depth, seafloor morphology, chlorophyll-a concentration, sea surface temperature and surface salinity. Predictive maps highlighted contrasting habitat selection amongst species. This study identifies areas where the important commercial species of cephalopods are concentrated and provides significant information for a future spatial based approach to fisheries management in the Mediterranean Sea. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Using environmental heterogeneity to plan for sea-level rise.
Hunter, Elizabeth A; Nibbelink, Nathan P
2017-12-01
Environmental heterogeneity is increasingly being used to select conservation areas that will provide for future biodiversity under a variety of climate scenarios. This approach, termed conserving nature's stage (CNS), assumes environmental features respond to climate change more slowly than biological communities, but will CNS be effective if the stage were to change as rapidly as the climate? We tested the effectiveness of using CNS to select sites in salt marshes for conservation in coastal Georgia (U.S.A.), where environmental features will change rapidly as sea level rises. We calculated species diversity based on distributions of 7 bird species with a variety of niches in Georgia salt marshes. Environmental heterogeneity was assessed across six landscape gradients (e.g., elevation, salinity, and patch area). We used 2 approaches to select sites with high environmental heterogeneity: site complementarity (environmental diversity [ED]) and local environmental heterogeneity (environmental richness [ER]). Sites selected based on ER predicted present-day species diversity better than randomly selected sites (up to an 8.1% improvement), were resilient to areal loss from SLR (1.0% average areal loss by 2050 compared with 0.9% loss of randomly selected sites), and provided habitat to a threatened species (0.63 average occupancy compared with 0.6 average occupancy of randomly selected sites). Sites selected based on ED predicted species diversity no better or worse than random and were not resilient to SLR (2.9% average areal loss by 2050). Despite the discrepancy between the 2 approaches, CNS is a viable strategy for conservation site selection in salt marshes because the ER approach was successful. It has potential for application in other coastal areas where SLR will affect environmental features, but its performance may depend on the magnitude of geological changes caused by SLR. Our results indicate that conservation planners that had heretofore excluded low-lying coasts from CNS planning could include coastal ecosystems in regional conservation strategies. © 2017 Society for Conservation Biology.
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REG1B as a predictor of childhood stunting in Bangladesh and Peru123
Peterson, Kristine M; Buss, Janice; Easley, Rebecca; Yang, Zhengyu; Korpe, Poonum S; Niu, Feiyang; Ma, Jennie Z; Olortegui, Maribel Paredes; Haque, Rashidul; Kosek, Margaret N; Petri, William A
2013-01-01
Background: Undernutrition remains a significant problem worldwide, with environmental enteropathy implicated as a contributing factor. An understanding of the pathogenesis and identification of children at risk are critical to the design of more-effective interventions. Objective: The stool regenerating gene 1β (REG1B) protein, which is a putative measure of intestinal injury and repair, was tested as a noninvasive biomarker of future childhood stunting. Design: A total of 222 children from Bangladesh and 97 children from Peru, who were from impoverished communities, were followed from birth through 24 mo of age with anthropometric measures obtained every 3 mo. Stool REG1B protein concentrations were obtained by using an REG1B polyclonal-polyclonal ELISA at 3 mo of age. We tested for the ability of REG1B to forecast future anthropometric shortfalls, independent of known predictors of undernutrition of family income and baseline height and weight. Results: In the Bangladesh cohort of 222 children, higher REG1B concentrations at month 3 were significantly and independently associated with a growth shortfall in a linear regression analysis at months 9, 12, 18, 21, and 24 and, in the Peru cohort, at months 12, 15, 18, 21, and 24. With the use of a mixed model for repeated measurements, higher stool REG1B concentrations at 3 mo were also independently predictive of a lower future length-for-age z score through 24 mo of age (Bangladesh P = 0.006; Peru P = 0.058). Conclusion: The ability of fecal REG1B to predict growth shortfall in independent cohorts of impoverished children from the developing world offers promise as a malnutrition biomarker and supports a role for environmental enteropathy in the pathogenesis of growth shortfall. PMID:23553156
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NASA Astrophysics Data System (ADS)
Bucklin, A. C.; Batta Lona, P. G.; Maas, A. E.; O'Neill, R. J.; Wiebe, P. H.
2015-12-01
In response to the changing Antarctic climate, the Southern Ocean salp Salpa thompsoni has shown altered patterns of distribution and abundance that are anticipated to have profound impacts on pelagic food webs and ecosystem dynamics. The physiological and molecular processes that underlay ecological function and biogeographical distribution are key to understanding present-day dynamics and predicting future trajectories. This study examined transcriptome-wide patterns of gene expression in relation to biological and physical oceanographic conditions in coastal, shelf and offshore waters of the Western Antarctic Peninsula (WAP) region during austral spring and summer 2011. Based on field observations and collections, seasonal changes in the distribution and abundance of salps of different life stages were associated with differences in water mass structure of the WAP. Our observations are consistent with previous suggestions that bathymetry and currents in Bransfield Strait could generate a retentive cell for an overwintering population of S. thompsoni, which may generate the characteristic salp blooms found throughout the region later in summer. The statistical analysis of transcriptome-wide patterns of gene expression revealed differences among salps collected in different seasons and from different habitats (i.e., coastal versus offshore) in the WAP. Gene expression patterns also clustered by station in austral spring - but not summer - collections, suggesting stronger heterogeneity of environmental conditions. During the summer, differentially expressed genes covered a wider range of functions, including those associated with stress responses. Future research using novel molecular transcriptomic / genomic characterization of S. thompsoni will allow more complete understanding of individual-, population-, and species-level responses to environmental variability and prediction of future dynamics of Southern Ocean food webs and ecosystems.
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Angeli, Nicole F; Lundgren, Ian F; Pollock, Clayton G; Hillis-Starr, Zandy M; Fitzgerald, Lee A
2018-03-01
Population size is widely used as a unit of ecological analysis, yet to estimate population size requires accounting for observed and latent heterogeneity influencing dispersion of individuals across landscapes. In newly established populations, such as when animals are translocated for conservation, dispersal and availability of resources influence patterns of abundance. We developed a process to estimate population size using N-mixture models and spatial models for newly established and dispersing populations. We used our approach to estimate the population size of critically endangered St. Croix ground lizards (Ameiva polops) five years after translocation of 57 individuals to Buck Island, an offshore island of St. Croix, United States Virgin Islands. Estimates of population size incorporated abiotic variables, dispersal limits, and operative environmental temperature available to the lizards to account for low species detection. Operative environmental temperature and distance from the translocation site were always important in fitting the N-mixture model indicating effects of dispersal and species biology on estimates of population size. We found that the population is increasing its range across the island by 5-10% every six months. We spatially interpolated site-specific abundance from the N-mixture model to the entire island, and we estimated 1,473 (95% CI, 940-1,802) St. Croix ground lizards on Buck Island in 2013 corresponding to survey results. This represents a 26-fold increase since the translocation. We predicted the future dispersal of the lizards to all habitats on Buck Island, with the potential for the population to increase by another five times in the future. Incorporating biologically relevant covariates as explicit parameters in population models can improve predictions of population size and the future spread of species introduced to new localities. © 2018 by the Ecological Society of America.
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Serra-Varela, María Jesús; Alía, Ricardo; Pórtoles, Javier; Gonzalo, Julián; Soliño, Mario; Grivet, Delphine; Raposo, Rosa
2017-01-01
Climate change is gravely affecting forest ecosystems, resulting in large distribution shifts as well as in increasing infection diseases and biological invasions. Accordingly, forest management requires an evaluation of exposure to climate change that should integrate both its abiotic and biotic components. Here we address the implications of climate change in an emerging disease by analysing both the host species (Pinus pinaster, Maritime pine) and the pathogen's (Fusarium circinatum, pitch canker) environmental suitability i.e. estimating the host's risk of habitat loss and the disease`s future environmental range. We constrained our study area to the Spanish Iberian Peninsula, where accurate climate and pitch canker occurrence databases were available. While P. pinaster is widely distributed across the study area, the disease has only been detected in its north-central and north-western edges. We fitted species distribution models for the current distribution of the conifer and the disease. Then, these models were projected into nine Global Climate Models and two different climatic scenarios which totalled to 18 different future climate predictions representative of 2050. Based on the level of agreement among them, we created future suitability maps for the pine and for the disease independently, which were then used to assess exposure of current populations of P. pinaster to abiotic and biotic effects of climate change. Almost the entire distribution of P. pinaster in the Spanish Iberian Peninsula will be subjected to abiotic exposure likely to be driven by the predicted increase in drought events in the future. Furthermore, we detected a reduction in exposure to pitch canker that will be concentrated along the north-western edge of the study area. Setting up breeding programs is recommended in highly exposed and productive populations, while silvicultural methods and monitoring should be applied in those less productive, but still exposed, populations.
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Serra-Varela, María Jesús; Alía, Ricardo; Pórtoles, Javier; Gonzalo, Julián; Soliño, Mario; Grivet, Delphine; Raposo, Rosa
2017-01-01
Climate change is gravely affecting forest ecosystems, resulting in large distribution shifts as well as in increasing infection diseases and biological invasions. Accordingly, forest management requires an evaluation of exposure to climate change that should integrate both its abiotic and biotic components. Here we address the implications of climate change in an emerging disease by analysing both the host species (Pinus pinaster, Maritime pine) and the pathogen’s (Fusarium circinatum, pitch canker) environmental suitability i.e. estimating the host’s risk of habitat loss and the disease`s future environmental range. We constrained our study area to the Spanish Iberian Peninsula, where accurate climate and pitch canker occurrence databases were available. While P. pinaster is widely distributed across the study area, the disease has only been detected in its north-central and north-western edges. We fitted species distribution models for the current distribution of the conifer and the disease. Then, these models were projected into nine Global Climate Models and two different climatic scenarios which totalled to 18 different future climate predictions representative of 2050. Based on the level of agreement among them, we created future suitability maps for the pine and for the disease independently, which were then used to assess exposure of current populations of P. pinaster to abiotic and biotic effects of climate change. Almost the entire distribution of P. pinaster in the Spanish Iberian Peninsula will be subjected to abiotic exposure likely to be driven by the predicted increase in drought events in the future. Furthermore, we detected a reduction in exposure to pitch canker that will be concentrated along the north-western edge of the study area. Setting up breeding programs is recommended in highly exposed and productive populations, while silvicultural methods and monitoring should be applied in those less productive, but still exposed, populations. PMID:28192454
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NASA Astrophysics Data System (ADS)
Li, Deying; Yin, Kunlong; Gao, Huaxi; Liu, Changchun
2009-10-01
Although the project of the Three Gorges Dam across the Yangtze River in China can utilize this huge potential source of hydroelectric power, and eliminate the loss of life and damage by flood, it also causes environmental problems due to the big rise and fluctuation of the water, such as geo-hazards. In order to prevent and predict geo-hazards, the establishment of prediction system of geo-hazards is very necessary. In order to implement functions of hazard prediction of regional and urban geo-hazard, single geo-hazard prediction, prediction of landslide surge and risk evaluation, logical layers of the system consist of data capturing layer, data manipulation and processing layer, analysis and application layer, and information publication layer. Due to the existence of multi-source spatial data, the research on the multi-source transformation and fusion data should be carried on in the paper. Its applicability of the system was testified on the spatial prediction of landslide hazard through spatial analysis of GIS in which information value method have been applied aims to identify susceptible areas that are possible to future landslide, on the basis of historical record of past landslide, terrain parameter, geology, rainfall and anthropogenic activity. Detailed discussion was carried out on spatial distribution characteristics of landslide hazard in the new town of Badong. These results can be used for risk evaluation. The system can be implemented as an early-warning and emergency management tool by the relevant authorities of the Three Gorges Reservoir in the future.
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Neven, Kristof Y; Nawrot, Tim S; Bollati, Valentina
2017-03-01
To summarize the scientific evidence regarding the effects of environmental exposures on extracellular vesicle (EV) release and their contents. As environmental exposures might influence the aging phenotype in a very strict way, we will also report the role of EVs in the biological aging process. EV research is a new and quickly developing field. With many investigations conducted so far, only a limited number of studies have explored the potential role EVs play in the response and adaptation to environmental stimuli. The investigations available to date have identified several exposures or lifestyle factors able to modify EV trafficking including air pollutants, cigarette smoke, alcohol, obesity, nutrition, physical exercise, and oxidative stress. EVs are a very promising tool, as biological fluids are easily obtainable biological media that, if successful in identifying early alterations induced by the environment and predictive of disease, would be amenable to use for potential future preventive and diagnostic applications.
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Environmental impacts on the diversity of methane-cycling microbes and their resultant function
Aronson, Emma L.; Allison, Steven D.; Helliker, Brent R.
2013-01-01
Methane is an important anthropogenic greenhouse gas that is produced and consumed in soils by microorganisms responding to micro-environmental conditions. Current estimates show that soil consumption accounts for 5–15% of methane removed from the atmosphere on an annual basis. Recent variability in atmospheric methane concentrations has called into question the reliability of estimates of methane consumption and calls for novel approaches in order to predict future atmospheric methane trends. This review synthesizes the environmental and climatic factors influencing the consumption of methane from the atmosphere by non-wetland, terrestrial soil microorganisms. In particular, we focus on published efforts to connect community composition and diversity of methane-cycling microbial communities to observed rates of methane flux. We find abundant evidence for direct connections between shifts in the methane-cycling microbial community, due to climate and environmental changes, and observed methane flux levels. These responses vary by ecosystem and associated vegetation type. This information will be useful in process-based models of ecosystem methane flux responses to shifts in environmental and climatic parameters. PMID:23966984
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The past is the key to the future
Doe, B.R.
1983-01-01
A new major frontier of geological research, which was initiated in the 1970's, involves predicting future geologic trends or events through study of the present and past, rather than trying to understand the past, often using what one knows about the present. Like most scientific frontiers, this one began from practical considerations-environmental concerns. The lack of formal recognition of this frontier results from fragmentation among many Federal agencies and highly focused mission-oriented programs (e.g., earthquake prediction, CO2, nuclear-energy safety, etc.). Most programs aim to predict only the next 50-100 years, but much longer periods of the past need to be studied to do this. Nuclear-waste disposal has sometimes been considered in terms of the next million years, a period of time permitting significant and broad geologic changes. Decreasing public interest in environmental concerns relegates many questions from the realm of applied research back to that of basic research. Most of these questions are so fascinating, however, that the frontier is still worth pursuing. Such questions include whether a phenomenon will or will not take place and the rates at which it can develop (e.g., how fast do rifts form, how fast can a caldera event begin, and how quickly can a glacial maximum arrive?). Common elements of all studies include the historic record, trends in the Quaternary, analogues in various periods of the geologic time scale, and allowance for phenomena never experienced before. Other examples of studies include the Cretaceous as a period of a climatic extreme, an especially interesting time period; establishing the amount of paleocloudiness, a particularly challenging and important research area; acid rain as a possible new phenomenon. Geochemistry has much to contribute to this frontier science. ?? 1983.
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The Rapidly Diminishing Arctic ice Cover and its Potential Impact on Navy Operational Considerations
NASA Astrophysics Data System (ADS)
Muench, R. D.; Conlon, D.; Lamb, D.
2001-12-01
Observations made from U.S. Navy Fleet submarines during the 1990s have revealed a dramatic decrease in thickness, when compared to historical values, of the central Arctic Ocean pack ice cover. Estimates of this decrease have been as high as 40%. Remote sensing observations have shown a coincident decrease in the areal extent of the pack. The areal decrease has been especially apparent during winter. The overall loss of ice appears to have accelerated over the past decade, raising the possibility that the Northwest Passage and the Northern Sea Route may become seasonally navigable on a regular basis in the coming decade. The ice loss has been most evident in the peripheral seas and continental shelf areas. For example, during winter 2000-2001 the Bering Sea was effectively ice-free, with strong and immediate impacts on the surrounding indigenous populations. Lessening of the peripheral pack ice cover will presumably, lead to accelerated development of the resource-rich regions that surround the deep, central Arctic Ocean basin. This raises potential issues with respect to national security and commercial interests, and has implicit strategic concerns for the Navy. The timeline for a significantly navigable Arctic may extend decades into the future; however, operational requirements must be identified in the nearer term to ensure that the necessary capabilities exist when future Arctic missions do present themselves. A first step is to improve the understanding of the coupled atmosphere/ice/ocean system. Current environmental measurement and prediction, including Arctic weather and ice prediction, shallow water acoustic performance prediction, dynamic ocean environmental changes and data to support navigation is inadequate to support sustained naval operations in the Arctic. A new focus on data collection is required in order to measure, map, monitor and model Arctic weather, ice and oceanographic conditions.
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2010-03-04
Cape Canaveral AFS, Fla. - A United Launch Alliance Delta IV rocket sits poised on its launch pad with the NASA/NOAA Geostationary Operational Environmental Satellite P (GOES P) at Space Launch Complex-37. GOES P will provide NOAA and NASA scientists with data to support weather, solar and space operations, and will enable future science improvements in weather prediction and remote sensing. Additionally, GOES-P will provide data on global climate changes and capability for search and rescue. Photo credit: Carleton Bailie, The Boeing Company
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Aviation Noise Impacts: State of the Science.
Basner, Mathias; Clark, Charlotte; Hansell, Anna; Hileman, James I; Janssen, Sabine; Shepherd, Kevin; Sparrow, Victor
2017-01-01
Noise is defined as "unwanted sound." Aircraft noise is one, if not the most detrimental environmental effect of aviation. It can cause community annoyance, disrupt sleep, adversely affect academic performance of children, and could increase the risk for cardiovascular disease of people living in the vicinity of airports. In some airports, noise constrains air traffic growth. This consensus paper was prepared by the Impacts of Science Group of the Committee for Aviation Environmental Protection of the International Civil Aviation Organization and summarizes the state of the science of noise effects research in the areas of noise measurement and prediction, community annoyance, children's learning, sleep disturbance, and health. It also briefly discusses civilian supersonic aircraft as a future source of aviation noise.
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Aviation Noise Impacts: State of the Science
Basner, Mathias; Clark, Charlotte; Hansell, Anna; Hileman, James I.; Janssen, Sabine; Shepherd, Kevin; Sparrow, Victor
2017-01-01
Noise is defined as “unwanted sound.” Aircraft noise is one, if not the most detrimental environmental effect of aviation. It can cause community annoyance, disrupt sleep, adversely affect academic performance of children, and could increase the risk for cardiovascular disease of people living in the vicinity of airports. In some airports, noise constrains air traffic growth. This consensus paper was prepared by the Impacts of Science Group of the Committee for Aviation Environmental Protection of the International Civil Aviation Organization and summarizes the state of the science of noise effects research in the areas of noise measurement and prediction, community annoyance, children’s learning, sleep disturbance, and health. It also briefly discusses civilian supersonic aircraft as a future source of aviation noise. PMID:29192612
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The Essential Role for Laboratory Studies in Atmospheric Chemistry.
Burkholder, James B; Abbatt, Jonathan P D; Barnes, Ian; Roberts, James M; Melamed, Megan L; Ammann, Markus; Bertram, Allan K; Cappa, Christopher D; Carlton, Annmarie G; Carpenter, Lucy J; Crowley, John N; Dubowski, Yael; George, Christian; Heard, Dwayne E; Herrmann, Hartmut; Keutsch, Frank N; Kroll, Jesse H; McNeill, V Faye; Ng, Nga Lee; Nizkorodov, Sergey A; Orlando, John J; Percival, Carl J; Picquet-Varrault, Bénédicte; Rudich, Yinon; Seakins, Paul W; Surratt, Jason D; Tanimoto, Hiroshi; Thornton, Joel A; Tong, Zhu; Tyndall, Geoffrey S; Wahner, Andreas; Weschler, Charles J; Wilson, Kevin R; Ziemann, Paul J
2017-03-07
Laboratory studies of atmospheric chemistry characterize the nature of atmospherically relevant processes down to the molecular level, providing fundamental information used to assess how human activities drive environmental phenomena such as climate change, urban air pollution, ecosystem health, indoor air quality, and stratospheric ozone depletion. Laboratory studies have a central role in addressing the incomplete fundamental knowledge of atmospheric chemistry. This article highlights the evolving science needs for this community and emphasizes how our knowledge is far from complete, hindering our ability to predict the future state of our atmosphere and to respond to emerging global environmental change issues. Laboratory studies provide rich opportunities to expand our understanding of the atmosphere via collaborative research with the modeling and field measurement communities, and with neighboring disciplines.
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Goodnight, Jackson A.; Donahue, Kelly L.; Waldman, Irwin D.; Van Hulle, Carol A.; Rathouz, Paul J.; Lahey, Benjamin B.; D’Onofrio, Brian M.
2016-01-01
Previous research suggests that fussy temperament in infancy predicts risk for later antisocial behavior (ASB) in childhood and adolescence. It remains unclear, however, to what extent infant fussiness is related to later ASB through causal processes or if they both reflect the same family risk factors for ASB. The current study used two approaches, the comparison of siblings and bivariate biometric modeling, to reduce familial confounding and examine genetic and environmental influences on associations between fussiness in the first two years of life and ASB in childhood and late adolescence. Analyses were conducted on data from a prospective cohort (9,237 at 4-9 years and 7,034 at 14-17years) who are the offspring of a nationally representative sample of U.S. women. In the full sample, fussiness predicted both child and adolescent ASB to small but significant extents, controlling for a wide range of measured child and family-level covariates. When siblings who differed in their fussiness were compared, fussiness predicted ASB in childhood, but not ASB during adolescence. Furthermore, results from a bivariate Cholesky model suggested that even the association of fussiness with childhood ASB found when comparing siblings is attributable to familial factors. That is, although families with infants who are higher in fussiness also tend to have children and adolescents who engage in greater ASB, the hypothesis that infant fussiness has an environmentally mediated impact on the development of future ASB was not strongly supported. PMID:27105627
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Proactive aquatic ecotoxicological assessment of room-temperature ionic liquids
Kulacki, K.J.; Chaloner, D.T.; Larson, J.H.; Costello, D.M.; Evans-White, M. A.; Docherty, K.M.; Bernot, R.J.; Brueseke, M.A.; Kulpa, C.F.; Lamberti, G.A.
2011-01-01
Aquatic environments are being contaminated with a myriad of anthropogenic chemicals, a problem likely to continue due to both unintentional and intentional releases. To protect valuable natural resources, novel chemicals should be shown to be environmentally safe prior to use and potential release into the environment. Such proactive assessment is currently being applied to room-temperature ionic liquids (ILs). Because most ILs are water-soluble, their effects are likely to manifest in aquatic ecosystems. Information on the impacts of ILs on numerous aquatic organisms, focused primarily on acute LC50 and EC50 endpoints, is now available, and trends in toxicity are emerging. Cation structure tends to influence IL toxicity more so than anion structure, and within a cation class, the length of alkyl chain substituents is positively correlated with toxicity. While the effects of ILs on several aquatic organisms have been studied, the challenge for aquatic toxicology is now to predict the effects of ILs in complex natural environments that often include diverse mixtures of organisms, abiotic conditions, and additional stressors. To make robust predictions about ILs will require coupling of ecologically realistic laboratory and field experiments with standard toxicity bioassays and models. Such assessments would likely discourage the development of especially toxic ILs while shifting focus to those that are more environmentally benign. Understanding the broader ecological effects of emerging chemicals, incorporating that information into predictive models, and conveying the conclusions to those who develop, regulate, and use those chemicals, should help avoid future environmental degradation. ?? 2011 Bentham Science Publishers Ltd.
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Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay.
Jacobs, J M; Rhodes, M; Brown, C W; Hood, R R; Leight, A; Long, W; Wood, R
2014-11-01
To construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters of Chesapeake Bay for implementation in ecological forecasting systems. We evaluated and applied previously published qPCR assays to water samples (n = 1636) collected from Chesapeake Bay from 2007-2010 in conjunction with State water quality monitoring programmes. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions. This article has been contributed to by US Government employees and their work is in the public domain in the USA.
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Ocean Thermal Energy Conversion (OTEC) Programmatic Environmental Analysis--Appendices
DOE Office of Scientific and Technical Information (OSTI.GOV)
Authors, Various
1980-01-01
The programmatic environmental analysis is an initial assessment of Ocean Thermal Energy Conversion (OTEC) technology considering development, demonstration and commercialization. It is concluded that the OTEC development program should continue because the development, demonstration, and commercialization on a single-plant deployment basis should not present significant environmental impacts. However, several areas within the OTEC program require further investigation in order to assess the potential for environmental impacts from OTEC operation, particularly in large-scale deployments and in defining alternatives to closed-cycle biofouling control: (1) Larger-scale deployments of OTEC clusters or parks require further investigations in order to assess optimal platform siting distancesmore » necessary to minimize adverse environmental impacts. (2) The deployment and operation of the preoperational platform (OTEC-1) and future demonstration platforms must be carefully monitored to refine environmental assessment predictions, and to provide design modifications which may mitigate or reduce environmental impacts for larger-scale operations. These platforms will provide a valuable opportunity to fully evaluate the intake and discharge configurations, biofouling control methods, and both short-term and long-term environmental effects associated with platform operations. (3) Successful development of OTEC technology to use the maximal resource capabilities and to minimize environmental effects will require a concerted environmental management program, encompassing many different disciplines and environmental specialties. This volume contains these appendices: Appendix A -- Deployment Scenario; Appendix B -- OTEC Regional Characterization; and Appendix C -- Impact and Related Calculations.« less
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Feng, Yongjiu; Liu, Yan
2016-09-01
The world's coastal regions are experiencing rapid urbanization coupled with increased risk of ecological damage and storm surge related to global climate and sea level rising. This urban development issue is particularly important in China, where many emerging coastal cities are being developed. Lingang New City, southeast of Shanghai, is an excellent example of a coastal city that is increasingly vulnerable to environmental change. Sustainable urban development requires planning that classifies and allocates coastal lands using objective procedures that incorporate changing environmental conditions. In this paper, we applied cellular automata (CA) modeling based on self-adaptive genetic algorithm (SAGA) to predict future scenarios and explore sustainable urban development options for Lingang. The CA model was calibrated using the 2005 initial status, 2015 final status, and a set of spatial variables. We implemented specific ecological and environmental conditions as spatial constraints for the model and predicted four 2030 scenarios: (a) an urban planning-oriented Plan Scenario; (b) an ecosystem protection-oriented Eco Scenario; (c) a storm surge-affected Storm Scenario; and (d) a scenario incorporating both ecosystem protection and the effects of storm surge, called the Ecostorm Scenario. The Plan Scenario has been taken as the baseline, with the Lingang urban area increasing from 45.8 km(2) in 2015 to 66.8 km(2) in 2030, accounting for 23.9 % of the entire study area. The simulated urban land size of the Plan Scenario in 2030 was taken as the target to accommodate the projected population increase in this city, which was then applied in the remaining three development scenarios. We used CA modeling to reallocate the urban cells to other unconstrained areas in response to changing spatial constraints. Our predictions should be helpful not only in assessing and adjusting the urban planning schemes for Lingang but also for evaluating urban planning in coastal cities elsewhere.
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Wallenstein, Matthew D.; Hall, Edward K.
2012-01-01
As the earth system changes in response to human activities, a critical objective is to predict how biogeochemical process rates (e.g. nitrification, decomposition) and ecosystem function (e.g. net ecosystem productivity) will change under future conditions. A particular challenge is that the microbial communities that drive many of these processes are capable of adapting to environmental change in ways that alter ecosystem functioning. Despite evidence that microbes can adapt to temperature, precipitation regimes, and redox fluctuations, microbial communities are typically not optimally adapted to their local environment. For example, temperature optima for growth and enzyme activity are often greater than in situ temperatures in their environment. Here we discuss fundamental constraints on microbial adaptation and suggest specific environments where microbial adaptation to climate change (or lack thereof) is most likely to alter ecosystem functioning. Our framework is based on two principal assumptions. First, there are fundamental ecological trade-offs in microbial community traits that occur across environmental gradients (in time and space). These trade-offs result in shifting of microbial function (e.g. ability to take up resources at low temperature) in response to adaptation of another trait (e.g. limiting maintenance respiration at high temperature). Second, the mechanism and level of microbial community adaptation to changing environmental parameters is a function of the potential rate of change in community composition relative to the rate of environmental change. Together, this framework provides a basis for developing testable predictions about how the rate and degree of microbial adaptation to climate change will alter biogeochemical processes in aquatic and terrestrial ecosystems across the planet.
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Castillo, Andrea G; Alò, Dominique; González, Benito A; Samaniego, Horacio
2018-01-01
The main goal of this contribution was to define the ecological niche of the guanaco ( Lama guanicoe ), to describe potential distributional changes, and to assess the relative importance of niche conservatism and divergence processes between the two lineages described for the species ( L.g. cacsilensis and L.g. guanicoe ). We used maximum entropy to model lineage's climate niche from 3,321 locations throughout continental Chile, and developed future niche models under climate change for two extreme greenhouse gas emission scenarios (RCP2.6 and RCP8.5). We evaluated changes of the environmental niche and future distribution of the largest mammal in the Southern Cone of South America. Evaluation of niche conservatism and divergence were based on identity and background similarity tests. We show that: (a) the current geographic distribution of lineages is associated with different climatic requirements that are related to the geographic areas where these lineages are located; (b) future distribution models predict a decrease in the distribution surface under both scenarios; (c) a 3% decrease of areal protection is expected if the current distribution of protected areas is maintained, and this is expected to occur at the expense of a large reduction of high quality habitats under the best scenario; (d) current and future distribution ranges of guanaco mostly adhere to phylogenetic niche divergence hypotheses between lineages. Associating environmental variables with species ecological niche seems to be an important aspect of unveiling the particularities of, both evolutionary patterns and ecological features that species face in a changing environment. We report specific descriptions of how these patterns may play out under the most extreme climate change predictions and provide a grim outlook of the future potential distribution of guanaco in Chile. From an ecological perspective, while a slightly smaller distribution area is expected, this may come with an important reduction of available quality habitats. From the evolutionary perspective, we describe the limitations of this taxon as it experiences forces imposed by climate change dynamics.
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Castillo, Andrea G.; González, Benito A.
2018-01-01
Background The main goal of this contribution was to define the ecological niche of the guanaco (Lama guanicoe), to describe potential distributional changes, and to assess the relative importance of niche conservatism and divergence processes between the two lineages described for the species (L.g. cacsilensis and L.g. guanicoe). Methods We used maximum entropy to model lineage’s climate niche from 3,321 locations throughout continental Chile, and developed future niche models under climate change for two extreme greenhouse gas emission scenarios (RCP2.6 and RCP8.5). We evaluated changes of the environmental niche and future distribution of the largest mammal in the Southern Cone of South America. Evaluation of niche conservatism and divergence were based on identity and background similarity tests. Results We show that: (a) the current geographic distribution of lineages is associated with different climatic requirements that are related to the geographic areas where these lineages are located; (b) future distribution models predict a decrease in the distribution surface under both scenarios; (c) a 3% decrease of areal protection is expected if the current distribution of protected areas is maintained, and this is expected to occur at the expense of a large reduction of high quality habitats under the best scenario; (d) current and future distribution ranges of guanaco mostly adhere to phylogenetic niche divergence hypotheses between lineages. Discussion Associating environmental variables with species ecological niche seems to be an important aspect of unveiling the particularities of, both evolutionary patterns and ecological features that species face in a changing environment. We report specific descriptions of how these patterns may play out under the most extreme climate change predictions and provide a grim outlook of the future potential distribution of guanaco in Chile. From an ecological perspective, while a slightly smaller distribution area is expected, this may come with an important reduction of available quality habitats. From the evolutionary perspective, we describe the limitations of this taxon as it experiences forces imposed by climate change dynamics. PMID:29868293
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Harray, Amelia J; Meng, Xingqiong; Kerr, Deborah A; Pollard, Christina M
2018-06-01
To determine the level of community concern about future food supplies and perception of the importance placed on government regulation over the supply of environmentally friendly food and identify dietary and other factors associated with these beliefs in Western Australia. Data from the 2009 and 2012 Nutrition Monitoring Survey Series computer-assisted telephone interviews were pooled. Level of concern about the effect of the environment on future food supplies and importance of government regulating the supply of environmentally friendly food were measured. Multivariate regression analysed potential associations with sociodemographic variables, dietary health consciousness, weight status and self-reported intake of eight foods consistent with a sustainable diet. Western Australia. Community-dwelling adults aged 18-64 years (n = 2832). Seventy nine per cent of Western Australians were 'quite' or 'very' concerned about the effect of the environment on future food supplies. Respondents who paid less attention to the health aspects of their diet were less likely than those who were health conscious ('quite' or 'very' concerned) (OR = 0.53, 95% CI [0.35, 0.8] and 0.38 [0.17, 0.81] respectively). The majority of respondents (85.3%) thought it was 'quite' or 'very' important that government had regulatory control over an environmentally friendly food supply. Females were more likely than males to rate regulatory control as 'quite' or 'very' important' (OR = 1.63, 95% CI [1.09, 2.44], p = .02). Multiple regression modeling found that no other factors predicted concern or importance. There is a high level of community concern about the impact of the environment on future food supplies and most people believe it is important that the government regulates the issue. These attitudes dominate regardless of sociodemographic characteristics, weight status or sustainable dietary behaviours. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Summaries of FY 1996 geosciences research
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
1996-12-01
The Geosciences Research Program is directed by the Department of Energy`s (DOE`s) Office of Energy Research (OER) through its Office of Basic Energy Sciences (OBES). Activities in the Geosciences Research Program are directed toward building the long-term fundamental knowledge base necessary to provide for energy technologies of the future. Future energy technologies and their individual roles in satisfying the nations energy needs cannot be easily predicted. It is clear, however, that these future energy technologies will involve consumption of energy and mineral resources and generation of technological wastes. The earth is a source for energy and mineral resources and ismore » also the host for wastes generated by technological enterprise. Viable energy technologies for the future must contribute to a national energy enterprise that is efficient, economical, and environmentally sound. The Geosciences Research Program emphasizes research leading to fundamental knowledge of the processes that transport, modify, concentrate, and emplace (1) the energy and mineral resources of the earth and (2) the energy by-products of man.« less
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NASA Astrophysics Data System (ADS)
Aalto, J.; Karjalainen, O.; Hjort, J.; Luoto, M.
2018-05-01
Mean annual ground temperature (MAGT) and active layer thickness (ALT) are key to understanding the evolution of the ground thermal state across the Arctic under climate change. Here a statistical modeling approach is presented to forecast current and future circum-Arctic MAGT and ALT in relation to climatic and local environmental factors, at spatial scales unreachable with contemporary transient modeling. After deploying an ensemble of multiple statistical techniques, distance-blocked cross validation between observations and predictions suggested excellent and reasonable transferability of the MAGT and ALT models, respectively. The MAGT forecasts indicated currently suitable conditions for permafrost to prevail over an area of 15.1 ± 2.8 × 106 km2. This extent is likely to dramatically contract in the future, as the results showed consistent, but region-specific, changes in ground thermal regime due to climate change. The forecasts provide new opportunities to assess future Arctic changes in ground thermal state and biogeochemical feedback.
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The burden of typhoid fever in low- and middle-income countries: A meta-regression approach.
Antillón, Marina; Warren, Joshua L; Crawford, Forrest W; Weinberger, Daniel M; Kürüm, Esra; Pak, Gi Deok; Marks, Florian; Pitzer, Virginia E
2017-02-01
Upcoming vaccination efforts against typhoid fever require an assessment of the baseline burden of disease in countries at risk. There are no typhoid incidence data from most low- and middle-income countries (LMICs), so model-based estimates offer insights for decision-makers in the absence of readily available data. We developed a mixed-effects model fit to data from 32 population-based studies of typhoid incidence in 22 locations in 14 countries. We tested the contribution of economic and environmental indices for predicting typhoid incidence using a stochastic search variable selection algorithm. We performed out-of-sample validation to assess the predictive performance of the model. We estimated that 17.8 million cases of typhoid fever occur each year in LMICs (95% credible interval: 6.9-48.4 million). Central Africa was predicted to experience the highest incidence of typhoid, followed by select countries in Central, South, and Southeast Asia. Incidence typically peaked in the 2-4 year old age group. Models incorporating widely available economic and environmental indicators were found to describe incidence better than null models. Recent estimates of typhoid burden may under-estimate the number of cases and magnitude of uncertainty in typhoid incidence. Our analysis permits prediction of overall as well as age-specific incidence of typhoid fever in LMICs, and incorporates uncertainty around the model structure and estimates of the predictors. Future studies are needed to further validate and refine model predictions and better understand year-to-year variation in cases.
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Tanentzap, Andrew J; Lee, William G
2017-01-01
Abiotic filters have been found either to increase or reduce evolutionary relatedness in plant communities, making it difficult to generalize responses of this major feature of biodiversity to future environmental change. Here, we hypothesized that the responses of phylogenetic structure to environmental change ultimately depend on how species have evolved traits for tolerating the resulting abiotic changes. Working within ephemeral wetlands, we tested whether species were increasingly related as flooding duration intensified. We also identified the mechanisms underlying increased relatedness by measuring root aerenchyma volume (RAV), a trait which promotes waterlogging tolerance. We found that species-specific responses to flooding explained most of the variation in occurrence for 63 vascular plant species across 5170 plots. For a subset of 22 species, we attributed these responses to variation in RAV. Large RAV specifically increased occurrence when flooding lasted for longer time periods, because large RAV reduced above-ground biomass loss. As large RAV was evolutionarily conserved within obligate wetland species, communities were more phylogenetically related as flooding increased. Our study shows how reconstructing the evolutionary history of traits that influence the responses of species to environmental change can help to predict future patterns in phylogenetic structure. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
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Climate Change and Civil Violence
NASA Astrophysics Data System (ADS)
van der Vink, G.; Plancherel, Y.; Hennet, C.; Jones, K. D.; Abdullah, A.; Bradshaw, J.; Dee, S.; Deprez, A.; Pasenello, M.; Plaza-Jennings, E.; Roseman, D.; Sopher, P.; Sung, E.
2009-05-01
The manifestations of climate change can result in humanitarian impacts that reverse progress in poverty- reduction, create shortages of food and resources, lead to migration, and ultimately result in civil violence and conflict. Within the continent of Africa, we have found that environmentally-related variables are either the cause or the confounding factor for over 80% of the civil violence events during the last 10 years. Using predictive climate models and land-use data, we are able to identify populations in Africa that are likely to experience the most severe climate-related shocks. Through geospatial analysis, we are able to overlay these areas of high risk with assessments of both the local population's resiliency and the region's capacity to respond to climate shocks should they occur. The net result of the analysis is the identification of locations that are becoming particularly vulnerable to future civil violence events (vulnerability hotspots) as a result of the manifestations of climate change. For each population group, over 600 social, economic, political, and environmental indicators are integrated statistically to measures the vulnerability of African populations to environmental change. The indicator time-series are filtered for data availability and redundancy, broadly ordered into four categories (social, political, economic and environmental), standardized and normalized. Within each category, the dominant modes of variability are isolated by principal component analysis and the loadings of each component for each variable are used to devise composite index scores. Comparisons of past vulnerability with known environmentally-related conflicts demonstrates the role that such vulnerability hotspot maps can play in evaluating both the potential for, and the significance of, environmentally-related civil violence events. Furthermore, the analysis reveals the major variables that are responsible for the population's vulnerability and therefore provides an opportunity for targeted proactive measures to mitigate certain classes of future civil violence events.
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Sen, Sandeep; Gode, Ameya; Ramanujam, Srirama; Ravikanth, G; Aravind, N A
2016-11-01
The center of diversity of Piper nigrum L. (Black Pepper), one of the highly valued spice crops is reported to be from India. Black pepper is naturally distributed in India in the Western Ghats biodiversity hotspot and is the only known existing source of its wild germplasm in the world. We used ecological niche models to predict the potential distribution of wild P. nigrum in the present and two future climate change scenarios viz (A1B) and (A2A) for the year 2080. Three topographic and nine uncorrelated bioclim variables were used to develop the niche models. The environmental variables influencing the distribution of wild P. nigrum across different climate change scenarios were identified. We also assessed the direction and magnitude of the niche centroid shift and the change in niche breadth to estimate the impact of projected climate change on the distribution of P. nigrum. The study shows a niche centroid shift in the future climate scenarios. Both the projected future climate scenarios predicted a reduction in the habitat of P. nigrum in Southern Western Ghats, which harbors many wild accessions of P. nigrum. Our results highlight the impact of future climate change on P. nigrum and provide useful information for designing sound germplasm conservation strategies for P. nigrum.
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Camp, Emma F; Smith, David J; Evenhuis, Chris; Enochs, Ian; Manzello, Derek; Woodcock, Stephen; Suggett, David J
2016-05-25
Corals are acclimatized to populate dynamic habitats that neighbour coral reefs. Habitats such as seagrass beds exhibit broad diel changes in temperature and pH that routinely expose corals to conditions predicted for reefs over the next 50-100 years. However, whether such acclimatization effectively enhances physiological tolerance to, and hence provides refuge against, future climate scenarios remains unknown. Also, whether corals living in low-variance habitats can tolerate present-day high-variance conditions remains untested. We experimentally examined how pH and temperature predicted for the year 2100 affects the growth and physiology of two dominant Caribbean corals (Acropora palmata and Porites astreoides) native to habitats with intrinsically low (outer-reef terrace, LV) and/or high (neighbouring seagrass, HV) environmental variance. Under present-day temperature and pH, growth and metabolic rates (calcification, respiration and photosynthesis) were unchanged for HV versus LV populations. Superimposing future climate scenarios onto the HV and LV conditions did not result in any enhanced tolerance to colonies native to HV. Calcification rates were always lower for elevated temperature and/or reduced pH. Together, these results suggest that seagrass habitats may not serve as refugia against climate change if the magnitude of future temperature and pH changes is equivalent to neighbouring reef habitats. © 2016 The Author(s).
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Smith, David J.; Evenhuis, Chris; Enochs, Ian; Manzello, Derek; Woodcock, Stephen; Suggett, David J.
2016-01-01
Corals are acclimatized to populate dynamic habitats that neighbour coral reefs. Habitats such as seagrass beds exhibit broad diel changes in temperature and pH that routinely expose corals to conditions predicted for reefs over the next 50–100 years. However, whether such acclimatization effectively enhances physiological tolerance to, and hence provides refuge against, future climate scenarios remains unknown. Also, whether corals living in low-variance habitats can tolerate present-day high-variance conditions remains untested. We experimentally examined how pH and temperature predicted for the year 2100 affects the growth and physiology of two dominant Caribbean corals (Acropora palmata and Porites astreoides) native to habitats with intrinsically low (outer-reef terrace, LV) and/or high (neighbouring seagrass, HV) environmental variance. Under present-day temperature and pH, growth and metabolic rates (calcification, respiration and photosynthesis) were unchanged for HV versus LV populations. Superimposing future climate scenarios onto the HV and LV conditions did not result in any enhanced tolerance to colonies native to HV. Calcification rates were always lower for elevated temperature and/or reduced pH. Together, these results suggest that seagrass habitats may not serve as refugia against climate change if the magnitude of future temperature and pH changes is equivalent to neighbouring reef habitats. PMID:27194698
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Nanotoxicity prediction using computational modelling - review and future directions
NASA Astrophysics Data System (ADS)
Saini, Bhavna; Srivastava, Sumit
2018-04-01
Nanomaterials has stimulated various outlooks for future in a number of industries and scientific ventures. A number of applications such as cosmetics, medicines, and electronics are employing nanomaterials due to their various compelling properties. The unending growth of nanomaterials usage in our daily life has escalated the health and environmental risks. Early nanotoxicity recognition is a big challenge. Various researches are going on in the field of nanotoxicity, which comprised of several problems such as inadequacy of proper datasets, lack of appropriate rules and characterization of nanomaterials. Computational modelling would be beneficial asset for nanomaterials researchers because it can foresee the toxicity, rest on previous experimental data. In this study, we have reviewed sufficient work demonstrating a proper pathway to proceed with QSAR analysis of Nanomaterials for toxicity modelling. The paper aims at providing comprehensive insight of Nano QSAR, various theories, tools and approaches used, along with an outline for future research directions to work on.
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Impact of climate change and seasonal trends on the fate of Arctic oil spills.
Nordam, Tor; Dunnebier, Dorien A E; Beegle-Krause, C J; Reed, Mark; Slagstad, Dag
2017-12-01
We investigated the effects of a warmer climate, and seasonal trends, on the fate of oil spilled in the Arctic. Three well blowout scenarios, two shipping accidents and a pipeline rupture were considered. We used ensembles of numerical simulations, using the OSCAR oil spill model, with environmental data for the periods 2009-2012 and 2050-2053 (representing a warmer future) as inputs to the model. Future atmospheric forcing was based on the IPCC's A1B scenario, with the ocean data generated by the hydrodynamic model SINMOD. We found differences in "typical" outcome of a spill in a warmer future compared to the present, mainly due to a longer season of open water. We have demonstrated that ice cover is extremely important for predicting the fate of an Arctic oil spill, and find that oil spills in a warming climate will in some cases result in greater areal coverage and shoreline exposure.
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Probabilistic fatigue life prediction of metallic and composite materials
NASA Astrophysics Data System (ADS)
Xiang, Yibing
Fatigue is one of the most common failure modes for engineering structures, such as aircrafts, rotorcrafts and aviation transports. Both metallic materials and composite materials are widely used and affected by fatigue damage. Huge uncertainties arise from material properties, measurement noise, imperfect models, future anticipated loads and environmental conditions. These uncertainties are critical issues for accurate remaining useful life (RUL) prediction for engineering structures in service. Probabilistic fatigue prognosis considering various uncertainties is of great importance for structural safety. The objective of this study is to develop probabilistic fatigue life prediction models for metallic materials and composite materials. A fatigue model based on crack growth analysis and equivalent initial flaw size concept is proposed for metallic materials. Following this, the developed model is extended to include structural geometry effects (notch effect), environmental effects (corroded specimens) and manufacturing effects (shot peening effects). Due to the inhomogeneity and anisotropy, the fatigue model suitable for metallic materials cannot be directly applied to composite materials. A composite fatigue model life prediction is proposed based on a mixed-mode delamination growth model and a stiffness degradation law. After the development of deterministic fatigue models of metallic and composite materials, a general probabilistic life prediction methodology is developed. The proposed methodology combines an efficient Inverse First-Order Reliability Method (IFORM) for the uncertainty propogation in fatigue life prediction. An equivalent stresstransformation has been developed to enhance the computational efficiency under realistic random amplitude loading. A systematical reliability-based maintenance optimization framework is proposed for fatigue risk management and mitigation of engineering structures.
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Arctic in Rapid Transition: Priorities for the future of marine and coastal research in the Arctic
NASA Astrophysics Data System (ADS)
Werner, Kirstin; Fritz, Michael; Morata, Nathalie; Keil, Kathrin; Pavlov, Alexey; Peeken, Ilka; Nikolopoulos, Anna; Findlay, Helen S.; Kędra, Monika; Majaneva, Sanna; Renner, Angelika; Hendricks, Stefan; Jacquot, Mathilde; Nicolaus, Marcel; O'Regan, Matt; Sampei, Makoto; Wegner, Carolyn
2016-09-01
Understanding and responding to the rapidly occurring environmental changes in the Arctic over the past few decades require new approaches in science. This includes improved collaborations within the scientific community but also enhanced dialogue between scientists and societal stakeholders, especially with Arctic communities. As a contribution to the Third International Conference on Arctic Research Planning (ICARPIII), the Arctic in Rapid Transition (ART) network held an international workshop in France, in October 2014, in order to discuss high-priority requirements for future Arctic marine and coastal research from an early-career scientists (ECS) perspective. The discussion encompassed a variety of research fields, including topics of oceanographic conditions, sea-ice monitoring, marine biodiversity, land-ocean interactions, and geological reconstructions, as well as law and governance issues. Participants of the workshop strongly agreed on the need to enhance interdisciplinarity in order to collect comprehensive knowledge about the modern and past Arctic Ocean's geo-ecological dynamics. Such knowledge enables improved predictions of Arctic developments and provides the basis for elaborate decision-making on future actions under plausible environmental and climate scenarios in the high northern latitudes. Priority research sheets resulting from the workshop's discussions were distributed during the ICARPIII meetings in April 2015 in Japan, and are publicly available online.
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NASA Astrophysics Data System (ADS)
Harrington, David M.; Sueoka, Stacey R.
2018-01-01
Data products from high spectral resolution astronomical polarimeters are often limited by fringes. Fringes can skew derived magnetic field properties from spectropolarimetric data. Fringe removal algorithms can also corrupt the data if the fringes and object signals are too similar. For some narrow-band imaging polarimeters, fringes change the calibration retarder properties and dominate the calibration errors. Systems-level engineering tools for polarimetric instrumentation require accurate predictions of fringe amplitudes, periods for transmission, diattenuation, and retardance. The relevant instabilities caused by environmental, thermal, and optical properties can be modeled and mitigation tools developed. We create spectral polarization fringe amplitude and temporal instability predictions by applying the Berreman calculus and simple interferometric calculations to optics in beams of varying F/ number. We then apply the formalism to superachromatic six-crystal retarders in converging beams under beam thermal loading in outdoor environmental conditions for two of the world's largest observatories: the 10-m Keck telescope and the Daniel K. Inouye Solar Telescope (DKIST). DKIST will produce a 300-W optical beam, which has imposed stringent requirements on the large diameter six-crystal retarders, dichroic beamsplitters, and internal optics. DKIST retarders are used in a converging beam with F/ ratios between 8 and 62. The fringe spectral periods, amplitudes, and thermal models of retarder behavior assisted DKIST optical designs and calibration plans with future application to many astronomical spectropolarimeters. The Low Resolution Imaging Spectrograph with polarimetry instrument at Keck also uses six-crystal retarders in a converging F / 13 beam in a Cassegrain focus exposed to summit environmental conditions providing observational verification of our predictions.
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Consequences of a warming climate for social organisation in sweat bees.
Schürch, Roger; Accleton, Christopher; Field, Jeremy
The progression from solitary living to caste-based sociality is commonly regarded as a major evolutionary transition. However, it has recently been shown that in some taxa, sociality may be plastic and dependent on local conditions. If sociality can be environmentally driven, the question arises as to how projected climate change will influence features of social organisation that were previously thought to be of macroevolutionary proportions. Depending on the time available in spring during which a foundress can produce worker offspring, the sweat bee Halictus rubicundus is either social or solitary. We analysed detailed foraging data in relation to climate change predictions for Great Britain to assess when and where switches from a solitary to social lifestyle may be expected. We demonstrate that worker numbers should increase throughout Great Britain under predicted climate change scenarios, and importantly, that sociality should appear in northern areas where it has never before been observed. This dramatic shift in social organisation due to climate change should lead to a bigger workforce being available for summer pollination and may contribute towards mitigating the current pollinator crisis. The sweat bee Halictus rubicundus is socially polymorphic, expressing both solitary and social forms, and is socially plastic, capable of transitioning from solitary to social forms, depending on local environmental conditions. Here, we analyse detailed foraging data in relation to climate change predictions for Great Britain to show that worker numbers and sociality both increase under predicted climate change scenarios. Especially dramatic will be the appearance of social H. rubicundus nests in the north of Britain, where previously only solitary forms are found. Particularly, if more taxa are found to be socially plastic, environmentally driven shifts in social organisation may help to mitigate future pollinator crises by providing more individuals for pollination.
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Zhang, Wenting; Wang, Haijun; Han, Fengxiang; Gao, Juan; Nguyen, Thuminh; Chen, Yarong; Huang, Bo; Zhan, F Benjamin; Zhou, Lequn; Hong, Song
2014-11-01
Urban growth is an unavoidable process caused by economic development and population growth. Traditional urban growth models represent the future urban growth pattern by repeating the historical urban growth regulations, which can lead to a lot of environmental problems. The Yangtze watershed is the largest and the most prosperous economic area in China, and it has been suffering from rapid urban growth from the 1970s. With the built-up area increasing from 23,238 to 31,054 km(2) during the period from 1980 to 2005, the watershed has suffered from serious nonpoint source (NPS) pollution problems, which have been mainly caused by the rapid urban growth. To protect the environment and at the same time maintain the economic development, a multiobjective optimization (MOP) is proposed to tradeoff the multiple objectives during the urban growth process of the Yangtze watershed. In particular, the four objectives of minimization of NPS pollution, maximization of GDP value, minimization of the spatial incompatibility between the land uses, and minimization of the cost of land-use change are considered by the MOP approach. Conventionally, a genetic algorithm (GA) is employed to search the Pareto solution set. In our MOP approach, a two-dimensional GA, rather than the traditional one-dimensional GA, is employed to assist with the search for the spatial optimization solution, where the land-use cells in the two-dimensional space act as genes in the GA. Furthermore, to confirm the superiority of the MOP approach over the traditional prediction approaches, a widely used urban growth prediction model, cellular automata (CA), is also carried out to allow a comparison with the Pareto solution of MOP. The results indicate that the MOP approach can make a tradeoff between the multiple objectives and can achieve an optimal urban growth pattern for Yangtze watershed, while the CA prediction model just represents the historical urban growth pattern as the future growth pattern. Moreover, according to the spatial clustering index, the urban growth pattern predicted through MOP is more reasonable. In summary, the proposed model provides a set of Pareto urban growth solutions, which compromise environmental and economic issues for the Yangtze watershed.
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Irving, Paul; Moncrieff, Ian
2004-12-01
Ecological systems have limits or thresholds that vary by pollutant type, emissions sources and the sensitivity of a given location. Human health can also indicate sensitivity. Good environmental management requires any problem to be defined to obtain efficient and effective solutions. Cities are where transport activities, effects and resource management decisions are often most focussed. The New Zealand Ministry of Transport has developed two environmental management tools. The Vehicle Fleet Model (VFM) is a predictive database of the environmental performance of the New Zealand traffic fleet (and rail fleet). It calculates indices of local air quality, stormwater, and greenhouse gases emissions. The second is an analytical process based on Environmental Capacity Analysis (ECA). Information on local traffic is combined with environmental performance data from the Vehicle Fleet Model. This can be integrated within a live, geo-spatially defined analysis of the overall environmental effects within a defined local area. Variations in urban form and activity (traffic and other) that contribute to environmental effects can be tracked. This enables analysis of a range of mitigation strategies that may contribute, now or in the future, to maintaining environmental thresholds or meeting targets. A case study of the application of this approach was conducted within Waitakere City. The focus was on improving the understanding of the relative significance of stormwater contaminants derived from land transport.
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Treading lightly on shifting ground: The direction and motivation of future geological research
Witt, A.C.
2011-01-01
The future of the geosciences and geological research will involve complex scientific challenges, primarily concerning global and regional environmental issues, in the next 20-30 years. It is quite reasonable to suspect, based on current political and socioeconomic events, that young geoscientists will be faced with and involved in helping to resolve some well defined problems: water and energy security, the effects of anthropogenic climate change, coastal sea level rise and development, and the mitigation of geohazards. It is how we choose to approach these challenges that will define our future. Interdisciplinary applied research, improved modeling and prediction augmented with faster and more sophisticated computing, and a greater role in creating and guiding public policy, will help us achieve our goals of a cleaner and safer Earth environment in the next 30 years. In the far future, even grander possibilities for eliminating the risk of certain geohazards and finding sustainable solutions to our energy needs can be envisioned. Looking deeper into the future, the possibilities for geoscience research push the limits of the imagination.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Pan, Y.
1993-01-01
Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less
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Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah
2015-01-01
We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages. PMID:26091266
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Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah
2015-01-01
We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages.
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Dryland photoautotrophic soil surface communities endangered by global change
Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina
2018-01-01
Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth’s terrestrial surface will decrease by about 25–40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.
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Dryland photoautotrophic soil surface communities endangered by global change
NASA Astrophysics Data System (ADS)
Rodriguez-Caballero, Emilio; Belnap, Jayne; Büdel, Burkhard; Crutzen, Paul J.; Andreae, Meinrat O.; Pöschl, Ulrich; Weber, Bettina
2018-03-01
Photoautotrophic surface communities forming biological soil crusts (biocrusts) are crucial for soil stability as well as water, nutrient and trace gas cycling at regional and global scales. Quantitative information on their global coverage and the environmental factors driving their distribution patterns, however, are not readily available. We use observations and environmental modelling to estimate the global distribution of biocrusts and their response to global change using future projected scenarios. We find that biocrusts currently covering approximately 12% of Earth's terrestrial surface will decrease by about 25-40% within 65 years due to anthropogenically caused climate change and land-use intensification, responding far more drastically than vascular plants. Our results illustrate that current biocrust occurrence is mainly driven by a combination of precipitation, temperature and land management, and future changes are expected to be affected by land-use and climate change in similar proportion. The predicted loss of biocrusts may substantially reduce the microbial contribution to nitrogen cycling and enhance the emissions of soil dust, which affects the functioning of ecosystems as well as human health and should be considered in the modelling, mitigation and management of global change.
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NASA Technical Reports Server (NTRS)
Zhu, Dong-Ming; Miller, Robert A.
2004-01-01
The development of low conductivity and high temperature capable thermal barrier coatings requires advanced testing techniques that can accurately and effectively evaluate coating thermal conductivity under future high-performance and low-emission engine heat-flux conditions. In this paper, a unique steady-state CO2 laser (wavelength 10.6 microns) heat-flux approach is described for determining the thermal conductivity and conductivity deduced cyclic durability of ceramic thermal and environmental barrier coating systems at very high temperatures (up to 1700 C) under large thermal gradients. The thermal conductivity behavior of advanced thermal and environmental barrier coatings for metallic and Si-based ceramic matrix composite (CMC) component applications has also been investigated using the laser conductivity approach. The relationships between the lattice and radiation conductivities as a function of heat flux and thermal gradient at high temperatures have been examined for the ceramic coating systems. The steady-state laser heat-flux conductivity approach has been demonstrated as a viable means for the development and life prediction of advanced thermal barrier coatings for future turbine engine applications.
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Integrated modeling approach for optimal management of water, energy and food security nexus
NASA Astrophysics Data System (ADS)
Zhang, Xiaodong; Vesselinov, Velimir V.
2017-03-01
Water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-period socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. The obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.
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Norms and values in sociohydrological models
NASA Astrophysics Data System (ADS)
Roobavannan, Mahendran; van Emmerik, Tim H. M.; Elshafei, Yasmina; Kandasamy, Jaya; Sanderson, Matthew R.; Vigneswaran, Saravanamuthu; Pande, Saket; Sivapalan, Murugesu
2018-02-01
Sustainable water resources management relies on understanding how societies and water systems coevolve. Many place-based sociohydrology (SH) modeling studies use proxies, such as environmental degradation, to capture key elements of the social component of system dynamics. Parameters of assumed relationships between environmental degradation and the human response to it are usually obtained through calibration. Since these relationships are not yet underpinned by social-science theories, confidence in the predictive power of such place-based sociohydrologic models remains low. The generalizability of SH models therefore requires major advances in incorporating more realistic relationships, underpinned by appropriate hydrological and social-science data and theories. The latter is a critical input, since human culture - especially values and norms arising from it - influences behavior and the consequences of behaviors. This paper reviews a key social-science theory that links cultural factors to environmental decision-making, assesses how to better incorporate social-science insights to enhance SH models, and raises important questions to be addressed in moving forward. This is done in the context of recent progress in sociohydrological studies and the gaps that remain to be filled. The paper concludes with a discussion of challenges and opportunities in terms of generalization of SH models and the use of available data to allow future prediction and model transfer to ungauged basins.
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Bonilla, Sylvia; Aubriot, Luis; Soares, Maria Carolina S; González-Piana, Mauricio; Fabre, Amelia; Huszar, Vera L M; Lürling, Miquel; Antoniades, Dermot; Padisák, Judit; Kruk, Carla
2012-03-01
The cyanobacteria Planktothrix agardhii and Cylindrospermopsis raciborskii are bloom-forming species common in eutrophic freshwaters. These filamentous species share certain physiological traits which imply that they might flourish under similar environmental conditions. We compared the distribution of the two species in a large database (940 samples) covering different climatic regions and the Northern and Southern hemispheres, and carried out laboratory experiments to compare their morphological and physiological responses. The environmental ranges of the two species overlapped with respect to temperature, light and total phosphorus (TP); however, they responded differently to environmental gradients; C. raciborskii biovolume changed gradually while P. agardhii shifted sharply from being highly dominated to a rare component of the phytoplankton. As expected, P. agardhii dominates the phytoplankton with high TP and low light availability conditions. Contrary to predictions, C. raciborskii succeeded in all climates and at temperatures as low as 11 °C. Cylindrospermopsis raciborskii had higher phenotypic plasticity than P. agardhii in terms of pigments, individual size and growth rates. We conclude that the phenotypic plasticity of C. raciborskii could explain its ongoing expansion to temperate latitudes and suggest its future predominance under predicted climate-change scenarios. © 2011 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.
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Nature and nurture- genes and environment- predict onset and progression of macular degeneration.
Sobrin, Lucia; Seddon, Johanna M
2014-05-01
Age-related macular degeneration (AMD) is a common cause of irreversible visual loss and the disease burden is rising world-wide as the population ages. Both environmental and genetic factors contribute to the development of this disease. Among environmental factors, smoking, obesity and dietary factors including antioxidants and dietary fat intake influence onset and progression of AMD. There are also several lines of evidence that link cardiovascular, immune and inflammatory biomarkers to AMD. The genetic etiology of AMD has been and continues to be an intense and fruitful area of investigation. Genome-wide association studies have revealed numerous common variants associated with AMD and sequencing is increasing our knowledge of how rare genetic variants strongly impact disease. Evidence for interactions between environmental, therapeutic and genetic factors is emerging and elucidating the mechanisms of this interplay remains a major challenge in the field. Genotype-phenotype associations are evolving. The knowledge of non-genetic, modifiable risk factors along with information about heritability and genetic risk variants for this disease acquired over the past 25 years have greatly improved patient management and our ability to predict which patients will develop or progress to advanced forms of AMD. Personalized medicine and individualized prevention and treatment strategies may become a reality in the near future. Copyright © 2014. Published by Elsevier Ltd.
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[Reliability and validity of a Mexican version of the Pro Children Project questionnaire].
Ochoa-Meza, Gerardo; Sierra, Juan Carlos; Pérez-Rodrigo, Carmen; Aranceta Bartrina, Javier; Esparza-Del Villar, Óscar A
2014-08-01
To determine the test-retest reliability, the internal consistency, and the predictive validity of the constructs of the Mexican version of the Pro Children Project questionnaire (PCHP) for assessing personal and environmental factors related to fruit and vegetable intake in 10-12 year-old schoolchildren. Test-retest design with a 14 days interval. A sample of 957 children completed the questionnaire with 82 items. The study was conducted at eight primary schools in 2012 in Ciudad Juarez, Chihuahua, Mexico. For all fruit constructs and vegetable constructs, the test-retest reliability was moderate (intraclass correlation coefficient (ICC) > 0.60). Cronbach s alpha values were from moderate to high (range of 0.54 to 0.92) similar to those in the original study. Values for predictive validity ranged from moderate to good with Spearman correlations between 0.23 and 0.60 for personal factors and between 0.14 and 0.40 for environmental factors. The results of the Mexican version of the PCHP questionnaire provide a sufficient reliability and validity for assessing personal and environmental factors of fruit and vegetable intake in 10-12 year old schoolchildren. Finally, implications to administer this instrument in scholar settings and guidelines for futures studies are discussed. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.
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Extreme Events and Disaster Risk Reduction - a Future Earth KAN initiative
NASA Astrophysics Data System (ADS)
Frank, Dorothea; Reichstein, Markus
2017-04-01
The topic of Extreme Events in the context of global environmental change is both a scientifically challenging and exciting topic, and of very high societal relevance. The Future Earth Cluster initiative E3S organized in 2016 a cross-community/co-design workshop on Extreme Events and Environments from Climate to Society (http://www.e3s-future-earth.eu/index.php/ConferencesEvents/ConferencesAmpEvents). Based on the results, co-design research strategies and established network of the workshop, and previous activities, E3S is thriving to establish the basis for a longer-term research effort under the umbrella of Future Earth. These led to an initiative for a Future Earth Knowledge Action Network on Extreme Events and Disaster Risk Reduction. Example initial key question in this context include: What are meaningful indices to describe and quantify impact-relevant (e.g. climate) extremes? Which system properties yield resistance and resilience to extreme conditions? What are the key interactions between global urbanization processes, extreme events, and social and infrastructure vulnerability and resilience? The long-term goal of this KAN is to contribute to enhancing the resistance, resilience, and adaptive capacity of socio-ecological systems across spatial, temporal and institutional scales, in particular in the light of hazards affected by ongoing environmental change (e.g. climate change, global urbanization and land use/land cover change). This can be achieved by enhanced understanding, prediction, improved and open data and knowledge bases for detection and early warning decision making, and by new insights on natural and societal conditions and governance for resilience and adaptive capacity.
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Pharmaceutical management through environmental product labeling in Sweden.
Wennmalm, Ake; Gunnarsson, Bo
2009-07-01
There is an increased awareness that medicinal products for human use may cause negative effects in the environment. In Sweden a voluntary environmental classification system for drugs has been established in collaboration between producers, authorities and the public health care, and used for five years. The idea is to enhance the market demand for medicines with less environmental impact, which in turn will stimulate the producers to design future medicines to be more environmentally friendly. The system is open to the public and based on assessment of the active ingredient in the medicinal product into several classes of risk and hazard, respectively. It is closely related to the EMEA guidelines. Risk is expressed as the ratio between the predicted environmental concentration (PEC) of the active ingredient (AI) and its predicted no effect concentration (PNEC). The hazard is expressed in terms of the AI's persistence, potential to bioaccumulation, and eco-toxicity. Drug data for the classification are delivered by the respective producers. Hitherto more than 300 AI, representing more than 50% of the Swedish volume of drug use, have been classified. Data for risk assessment were missing in 47% of AI. Among drugs with data 7% had a PEC/PNEC ratio >1, and another 7% had a ratio between 0.1 and 1. The AIs with highest ratio (>10) were two estrogens. Data for hazard assessment were lacking in 16% of the AI. Among drugs with environmental data 92% were not ready biodegradable, 23% had potential to bioaccumulation, and 61% were toxic to aquatic organisms at a concentration below 1 mg/l. These data are utilized by regional pharmaceutical expert groups when selecting substances to be recommended in public health care in Sweden. They may also be used by prescribing doctors who want to identify the environmentally most favourable substance among several with equivalent medical effect. We conclude that environmental data on human medicinal products are often missing, or reveal unfavourable environmental properties. A proper judgement of the environmental impact of an AI requires a joint evaluation of its risk and hazard. We suggest that the pharmaceutical producers should highlight environmental precaution when designing new AIs, and that the environmental data should be transparent to the general public.
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A 120-year record of resilience to environmental change in brachiopods.
Cross, Emma L; Harper, Elizabeth M; Peck, Lloyd S
2018-06-01
The inability of organisms to cope in changing environments poses a major threat to their survival. Rising carbon dioxide concentrations, recently exceeding 400 μatm, are rapidly warming and acidifying our oceans. Current understanding of organism responses to this environmental phenomenon is based mainly on relatively short- to medium-term laboratory and field experiments, which cannot evaluate the potential for long-term acclimation and adaptation, the processes identified as most important to confer resistance. Here, we present data from a novel approach that assesses responses over a centennial timescale showing remarkable resilience to change in a species predicted to be vulnerable. Utilising museum collections allows the assessment of how organisms have coped with past environmental change. It also provides a historical reference for future climate change responses. We evaluated a unique specimen collection of a single species of brachiopod (Calloria inconspicua) collected every decade from 1900 to 2014 from one sampling site. The majority of brachiopod shell characteristics remained unchanged over the past century. One response, however, appears to reinforce their shell by constructing narrower punctae (shell perforations) and laying down more shell. This study indicates one of the most calcium-carbonate-dependent species globally to be highly resilient to environmental change over the last 120 years and provides a new insight for how similar species might react and possibly adapt to future change. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
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Clark, Melody S; Thorne, Michael A S; Amaral, Ana; Vieira, Florbela; Batista, Frederico M; Reis, João; Power, Deborah M
2013-01-01
Understanding the environmental responses of an invasive species is critical in predicting how ecosystem composition may be transformed in the future, especially under climate change. In this study, Crassostrea gigas, a species well adapted to the highly variable intertidal environment, was exposed to the chronic environmental challenges of temperature (19 and 24°C) and pH (ambient seawater and a reduction of 0.4 pH units) in an extended 3-month laboratory-based study. Physiological parameters were measured (condition index, shell growth, respiration, excretion rates, O:N ratios, and ability to repair shell damage) alongside molecular analyses. Temperature was by far the most important stressor, as demonstrated by reduced condition indexes and shell growth at 24°C, with relatively little effect detected for pH. Transcriptional profiling using candidate genes and SOLiD sequencing of mantle tissue revealed that classical “stress” genes, previously reported to be upregulated under acute temperature challenges, were not significantly expressed in any of the treatments, emphasizing the different response between acute and longer term chronic stress. The transcriptional profiling also elaborated on the cellular responses underpinning the physiological results, including the identification of the PI3K/AKT/mTOR pathway as a potentially novel marker for chronic environmental challenge. This study represents a first attempt to understand the energetic consequences of cumulative thermal stress on the intertidal C. gigas which could significantly impact on coastal ecosystem biodiversity and function in the future. PMID:24223268
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Gilham, Clare; Rake, Christine; Burdett, Garry; Nicholson, Andrew G; Davison, Leslie; Franchini, Angelo; Carpenter, James; Hodgson, John; Darnton, Andrew; Peto, Julian
2016-01-01
Background We have conducted a population-based study of pleural mesothelioma patients with occupational histories and measured asbestos lung burdens in occupationally exposed workers and in the general population. The relationship between lung burden and risk, particularly at environmental exposure levels, will enable future mesothelioma rates in people born after 1965 who never installed asbestos to be predicted from their asbestos lung burdens. Methods Following personal interview asbestos fibres longer than 5 µm were counted by transmission electron microscopy in lung samples obtained from 133 patients with mesothelioma and 262 patients with lung cancer. ORs for mesothelioma were converted to lifetime risks. Results Lifetime mesothelioma risk is approximately 0.02% per 1000 amphibole fibres per gram of dry lung tissue over a more than 100-fold range, from 1 to 4 in the most heavily exposed building workers to less than 1 in 500 in most of the population. The asbestos fibres counted were amosite (75%), crocidolite (18%), other amphiboles (5%) and chrysotile (2%). Conclusions The approximate linearity of the dose–response together with lung burden measurements in younger people will provide reasonably reliable predictions of future mesothelioma rates in those born since 1965 whose risks cannot yet be seen in national rates. Burdens in those born more recently will indicate the continuing occupational and environmental hazards under current asbestos control regulations. Our results confirm the major contribution of amosite to UK mesothelioma incidence and the substantial contribution of non-occupational exposure, particularly in women. PMID:26715106
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Optimality Based Dynamic Plant Allocation Model: Predicting Acclimation Response to Climate Change
NASA Astrophysics Data System (ADS)
Srinivasan, V.; Drewry, D.; Kumar, P.; Sivapalan, M.
2009-12-01
Allocation of assimilated carbon to different plant parts determines the future plant status and is important to predict long term (months to years) vegetated land surface fluxes. Plants have the ability to modify their allometry and exhibit plasticity by varying the relative proportions of the structural biomass contained in each of its tissue. The ability of plants to be plastic provides them with the potential to acclimate to changing environmental conditions in order to enhance their probability of survival. Allometry based allocation models and other empirical allocation models do not account for plant plasticity cause by acclimation due to environmental changes. In the absence of a detailed understanding of the various biophysical processes involved in plant growth and development an optimality approach is adopted here to predict carbon allocation in plants. Existing optimality based models of plant growth are either static or involve considerable empiricism. In this work, we adopt an optimality based approach (coupled with limitations on plant plasticity) to predict the dynamic allocation of assimilated carbon to different plant parts. We explore the applicability of this approach using several optimization variables such as net primary productivity, net transpiration, realized growth rate, total end of growing season reproductive biomass etc. We use this approach to predict the dynamic nature of plant acclimation in its allocation of carbon to different plant parts under current and future climate scenarios. This approach is designed as a growth sub-model in the multi-layer canopy plant model (MLCPM) and is used to obtain land surface fluxes and plant properties over the growing season. The framework of this model is such that it retains the generality and can be applied to different types of ecosystems. We test this approach using the data from free air carbon dioxide enrichment (FACE) experiments using soybean crop at the Soy-FACE research site. Our results show that there are significant changes in the allocation patterns of vegetation when subjected to elevated CO2 indicating that our model is able to account for plant plasticity arising from acclimation. Soybeans when grown under elevated CO2, increased their allocation to structural components such as leaves and decreased their allocation to reproductive biomass. This demonstrates that plant acclimation causes lower than expected crop yields when grown under elevated CO2. Our findings can have serious implications in estimating future crop yields under climate change scenarios where it is widely expected that rising CO2 will fully offset losses due to climate change.
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Caring about Tomorrow: Future Orientation, Environmental Attitudes and Behaviors
ERIC Educational Resources Information Center
Carmi, Nurit
2013-01-01
Almost any pro-environmental behavior arouses a temporal conflict, as protecting long-term interests requires the sacrifice of short-term ones. Similarly, many health promoting behaviors may involve present discomfort for the sake of future well-being. In both contexts, health or environmental, developed future orientation (FO) is required to…
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NASA Technical Reports Server (NTRS)
Groves, Curtis Edward
2014-01-01
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.
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NASA Technical Reports Server (NTRS)
Groves, Curtis Edward
2014-01-01
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System spacecraft system.Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.
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NASA Technical Reports Server (NTRS)
Groves, Curtis E.
2013-01-01
Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This proposal describes an approach to validate the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft. The research described here is absolutely cutting edge. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional"validation by test only'' mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computationaf Fluid Dynamics can be used to veritY these requirements; however, the model must be validated by test data. The proposed research project includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT and OPEN FOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid . . . Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. To date, the author is the only person to look at the uncertainty in the entire computational domain. For the flow regime being analyzed (turbulent, threedimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.
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NASA Astrophysics Data System (ADS)
Tommasi, D.; Stock, C. A.
2016-02-01
It is well established that environmental fluctuations affect the productivity of numerous fish stocks. Recent advances in prediction capability of dynamical global forecast systems, such as the state of the art NOAA Geophysical Fluid dynamics Laboratory (GFDL) 2.5-FLOR model, allow for climate predictions of fisheries-relevant variables at temporal scales relevant to the fishery management decision making process. We demonstrate that the GFDL FLOR model produces skillful seasonal SST anomaly predictions over the continental shelf , where most of the global fish yield is generated. The availability of skillful SST projections at this "fishery relevant" scale raises the potential for better constrained estimates of future fish biomass and improved harvest decisions. We assessed the utility of seasonal SST coastal shelf predictions for fisheries management using the case study of Pacific sardine. This fishery was selected because it is one of the few to already incorporate SST into its harvest guideline, and show a robust recruitment-SST relationship. We quantified the effectiveness of management under the status quo harvest guideline (HG) and under alternative HGs including future information at different levels of uncertainty. Usefulness of forecast SST to management was dependent on forecast uncertainty. If the standard deviation of the SST anomaly forecast residuals was less than 0.65, the alternative HG produced higher long-term yield and stock biomass, and reduced the probability of either catch or stock biomass falling below management-set threshold values as compared to the status quo. By contrast, probability of biomass falling to extremely low values increased as compared to the status quo for all alternative HGs except for a perfectly known future SST case. To safeguard against occurrence of such low probability but costly events, a harvest cutoff biomass also has to be implemented into the HG.
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NASA Astrophysics Data System (ADS)
Luo, Y.; Huang, Y.; Jiang, J.; MA, S.; Saruta, V.; Liang, G.; Hanson, P. J.; Ricciuto, D. M.; Milcu, A.; Roy, J.
2017-12-01
The past two decades have witnessed rapid development in sensor technology. Built upon the sensor development, large research infrastructure facilities, such as National Ecological Observatory Network (NEON) and FLUXNET, have been established. Through networking different kinds of sensors and other data collections at many locations all over the world, those facilities generate large volumes of ecological data every day. The big data from those facilities offer an unprecedented opportunity for advancing our understanding of ecological processes, educating teachers and students, supporting decision-making, and testing ecological theory. The big data from the major research infrastructure facilities also provides foundation for developing predictive ecology. Indeed, the capability to predict future changes in our living environment and natural resources is critical to decision making in a world where the past is no longer a clear guide to the future. We are living in a period marked by rapid climate change, profound alteration of biogeochemical cycles, unsustainable depletion of natural resources, and deterioration of air and water quality. Projecting changes in future ecosystem services to the society becomes essential not only for science but also for policy making. We will use this panel format to outline major opportunities and challenges in integrating research infrastructure and ecosystem models toward developing predictive ecology. Meanwhile, we will also show results from an interactive model-experiment System - Ecological Platform for Assimilating Data into models (EcoPAD) - that have been implemented at the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment in Northern Minnesota and Montpellier Ecotron, France. EcoPAD is developed by integrating web technology, eco-informatics, data assimilation techniques, and ecosystem modeling. EcoPAD is designed to streamline data transfer seamlessly from research infrastructure facilities to model simulation, data assimilation, and ecological forecasting.
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Prediction of high incidence of dengue in the Philippines.
Buczak, Anna L; Baugher, Benjamin; Babin, Steven M; Ramac-Thomas, Liane C; Guven, Erhan; Elbert, Yevgeniy; Koshute, Phillip T; Velasco, John Mark S; Roque, Vito G; Tayag, Enrique A; Yoon, In-Kyu; Lewis, Sheri H
2014-04-01
Accurate prediction of dengue incidence levels weeks in advance of an outbreak may reduce the morbidity and mortality associated with this neglected disease. Therefore, models were developed to predict high and low dengue incidence in order to provide timely forewarnings in the Philippines. Model inputs were chosen based on studies indicating variables that may impact dengue incidence. The method first uses Fuzzy Association Rule Mining techniques to extract association rules from these historical epidemiological, environmental, and socio-economic data, as well as climate data indicating future weather patterns. Selection criteria were used to choose a subset of these rules for a classifier, thereby generating a Prediction Model. The models predicted high or low incidence of dengue in a Philippines province four weeks in advance. The threshold between high and low was determined relative to historical incidence data. Model accuracy is described by Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, and Specificity computed on test data not previously used to develop the model. Selecting a model using the F0.5 measure, which gives PPV more importance than Sensitivity, gave these results: PPV = 0.780, NPV = 0.938, Sensitivity = 0.547, Specificity = 0.978. Using the F3 measure, which gives Sensitivity more importance than PPV, the selected model had PPV = 0.778, NPV = 0.948, Sensitivity = 0.627, Specificity = 0.974. The decision as to which model has greater utility depends on how the predictions will be used in a particular situation. This method builds prediction models for future dengue incidence in the Philippines and is capable of being modified for use in different situations; for diseases other than dengue; and for regions beyond the Philippines. The Philippines dengue prediction models predicted high or low incidence of dengue four weeks in advance of an outbreak with high accuracy, as measured by PPV, NPV, Sensitivity, and Specificity.
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Prediction of High Incidence of Dengue in the Philippines
Buczak, Anna L.; Baugher, Benjamin; Babin, Steven M.; Ramac-Thomas, Liane C.; Guven, Erhan; Elbert, Yevgeniy; Koshute, Phillip T.; Velasco, John Mark S.; Roque, Vito G.; Tayag, Enrique A.; Yoon, In-Kyu; Lewis, Sheri H.
2014-01-01
Background Accurate prediction of dengue incidence levels weeks in advance of an outbreak may reduce the morbidity and mortality associated with this neglected disease. Therefore, models were developed to predict high and low dengue incidence in order to provide timely forewarnings in the Philippines. Methods Model inputs were chosen based on studies indicating variables that may impact dengue incidence. The method first uses Fuzzy Association Rule Mining techniques to extract association rules from these historical epidemiological, environmental, and socio-economic data, as well as climate data indicating future weather patterns. Selection criteria were used to choose a subset of these rules for a classifier, thereby generating a Prediction Model. The models predicted high or low incidence of dengue in a Philippines province four weeks in advance. The threshold between high and low was determined relative to historical incidence data. Principal Findings Model accuracy is described by Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, and Specificity computed on test data not previously used to develop the model. Selecting a model using the F0.5 measure, which gives PPV more importance than Sensitivity, gave these results: PPV = 0.780, NPV = 0.938, Sensitivity = 0.547, Specificity = 0.978. Using the F3 measure, which gives Sensitivity more importance than PPV, the selected model had PPV = 0.778, NPV = 0.948, Sensitivity = 0.627, Specificity = 0.974. The decision as to which model has greater utility depends on how the predictions will be used in a particular situation. Conclusions This method builds prediction models for future dengue incidence in the Philippines and is capable of being modified for use in different situations; for diseases other than dengue; and for regions beyond the Philippines. The Philippines dengue prediction models predicted high or low incidence of dengue four weeks in advance of an outbreak with high accuracy, as measured by PPV, NPV, Sensitivity, and Specificity. PMID:24722434
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Postma, E
2006-03-01
The ability to predict individual breeding values in natural populations with known pedigrees has provided a powerful tool to separate phenotypic values into their genetic and environmental components in a nonexperimental setting. This has allowed sophisticated analyses of selection, as well as powerful tests of evolutionary change and differentiation. To date, there has, however, been no evaluation of the reliability or potential limitations of the approach. In this article, I address these gaps. In particular, I emphasize the differences between true and predicted breeding values (PBVs), which as yet have largely been ignored. These differences do, however, have important implications for the interpretation of, firstly, the relationship between PBVs and fitness, and secondly, patterns in PBVs over time. I subsequently present guidelines I believe to be essential in the formulation of the questions addressed in studies using PBVs, and I discuss possibilities for future research.
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Diversity of deep-water cetaceans in relation to temperature: implications for ocean warming.
Whitehead, Hal; McGill, Brian; Worm, Boris
2008-11-01
Understanding the effects of natural environmental variation on biodiversity can help predict response to future anthropogenic change. Here we analyse a large, long-term data set of sightings of deep-water cetaceans from the Atlantic, Pacific and Indian Oceans. Seasonal and geographic changes in the diversity of these genera are well predicted by a convex function of sea-surface temperature peaking at c. 21 degrees C. Thus, diversity is highest at intermediate latitudes - an emerging general pattern for the pelagic ocean. When applied to a range of Intergovernmental Panel on Climate Change global change scenarios, the predicted response is a decline of cetacean diversity across the tropics and increases at higher latitudes. This suggests that deep-water oceanic communities that dominate > 60% of the planet's surface may reorganize in response to ocean warming, with low-latitude losses of diversity and resilience.
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Simulating seasonal tropical cyclone intensities at landfall along the South China coast
NASA Astrophysics Data System (ADS)
Lok, Charlie C. F.; Chan, Johnny C. L.
2018-04-01
A numerical method is developed using a regional climate model (RegCM3) and the Weather Forecast and Research (WRF) model to predict seasonal tropical cyclone (TC) intensities at landfall for the South China region. In designing the model system, three sensitivity tests have been performed to identify the optimal choice of the RegCM3 model domain, WRF horizontal resolution and WRF physics packages. Driven from the National Centers for Environmental Prediction Climate Forecast System Reanalysis dataset, the model system can produce a reasonable distribution of TC intensities at landfall on a seasonal scale. Analyses of the model output suggest that the strength and extent of the subtropical ridge in the East China Sea are crucial to simulating TC landfalls in the Guangdong and Hainan provinces. This study demonstrates the potential for predicting TC intensities at landfall on a seasonal basis as well as projecting future climate changes using numerical models.
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Making Predictions in a Changing World: The Benefits of Individual-Based Ecology
Stillman, Richard A.; Railsback, Steven F.; Giske, Jarl; Berger, Uta; Grimm, Volker
2014-01-01
Ecologists urgently need a better ability to predict how environmental change affects biodiversity. We examine individual-based ecology (IBE), a research paradigm that promises better a predictive ability by using individual-based models (IBMs) to represent ecological dynamics as arising from how individuals interact with their environment and with each other. A key advantage of IBMs is that the basis for predictions—fitness maximization by individual organisms—is more general and reliable than the empirical relationships that other models depend on. Case studies illustrate the usefulness and predictive success of long-term IBE programs. The pioneering programs had three phases: conceptualization, implementation, and diversification. Continued validation of models runs throughout these phases. The breakthroughs that make IBE more productive include standards for describing and validating IBMs, improved and standardized theory for individual traits and behavior, software tools, and generalized instead of system-specific IBMs. We provide guidelines for pursuing IBE and a vision for future IBE research. PMID:26955076
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Assis, Jorge; Lucas, Ana Vaz; Bárbara, Ignacio; Serrão, Ester Álvares
2016-02-01
Global climate change is shifting species distributions worldwide. At rear edges (warmer, low latitude range margins), the consequences of small variations in environmental conditions can be magnified, producing large negative effects on species ranges. A major outcome of shifts in distributions that only recently received attention is the potential to reduce the levels of intra-specific diversity and consequently the global evolutionary and adaptive capacity of species to face novel disturbances. This is particularly important for low dispersal marine species, such as kelps, that generally retain high and unique genetic diversity at rear ranges resulting from long-term persistence, while ranges shifts during climatic glacial/interglacial cycles. Using ecological niche modelling, we (1) infer the major environmental forces shaping the distribution of a cold-temperate kelp, Laminaria hyperborea (Gunnerus) Foslie, and we (2) predict the effect of past climate changes in shaping regions of long-term persistence (i.e., climatic refugia), where this species might hypothetically harbour higher genetic diversity given the absence of bottlenecks and local extinctions over the long term. We further (3) assessed the consequences of future climate for the fate of L. hyperborea using different scenarios of greenhouse gas emissions (RCP 2.6 and RCP 8.5). Results show NW Iberia, SW Ireland and W English Channel, Faroe Islands and S Iceland, as regions where L. hyperborea may have persisted during past climate extremes until present day. All predictions for the future showed expansions to northern territories coupled with the significant loss of suitable habitats at low latitude range margins, where long-term persistence was inferred (e.g., NW Iberia). This pattern was particularly evident in the most agressive scenario of climate change (RCP 8.5), likely driving major biodiversity loss, changes in ecosystem functioning and the impoverishment of the global gene pool of L. hyperborea. Because no genetic baseline is currently available for this species, our results may represent a first step in informing conservation and mitigation strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Beyond mice and men: Environmental change, immunity and infections in wild ungulates
Jolles, Anna E.; Beechler, Brianna R.; Dolan, Brian P.
2014-01-01
In the face of rapid environmental change, anticipating shifts in microparasite and macroparasite dynamics, including emergence events, is an enormous challenge. We argue that immunological studies in natural populations are pivotal to meeting this challenge: Many components of environmental change – shifts in biotic assemblages, altered climate patterns, and reduced environmental predictability – may affect host immunity. We suggest that wild ungulates can serve as model systems aiding the discovery of immunological mechanisms that link environmental change with parasite transmission dynamics. Our review of eco-immunological studies in wild ungulates reveals progress in understanding how co-infections affect immunity and parasite transmission; and how environmental and genetic factors interact to shape immunity. Changes in bioavailability of micronutrients have been linked to immunity and health in wild ungulates. Although physiological stress in response to environmental change has been assessed, downstream effects on immunity have not been studied. Moreover, the taxonomic range of ungulates studied is limited to bovids (bighorn sheep, Soay sheep, chamois, musk oxen, bison, African buffalo) and a few cervids (red deer, black-tailed deer). We discuss areas where future studies in ungulates could lead to significant contributions in understanding patterns of immunity and infection in natural populations and across species. PMID:25354672
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Predicted deep-sea coral habitat suitability for the U.S. West coast.
Guinotte, John M; Davies, Andrew J
2014-01-01
Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled.
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Predicted Deep-Sea Coral Habitat Suitability for the U.S. West Coast
Guinotte, John M.; Davies, Andrew J.
2014-01-01
Regional scale habitat suitability models provide finer scale resolution and more focused predictions of where organisms may occur. Previous modelling approaches have focused primarily on local and/or global scales, while regional scale models have been relatively few. In this study, regional scale predictive habitat models are presented for deep-sea corals for the U.S. West Coast (California, Oregon and Washington). Model results are intended to aid in future research or mapping efforts and to assess potential coral habitat suitability both within and outside existing bottom trawl closures (i.e. Essential Fish Habitat (EFH)) and identify suitable habitat within U.S. National Marine Sanctuaries (NMS). Deep-sea coral habitat suitability was modelled at 500 m×500 m spatial resolution using a range of physical, chemical and environmental variables known or thought to influence the distribution of deep-sea corals. Using a spatial partitioning cross-validation approach, maximum entropy models identified slope, temperature, salinity and depth as important predictors for most deep-sea coral taxa. Large areas of highly suitable deep-sea coral habitat were predicted both within and outside of existing bottom trawl closures and NMS boundaries. Predicted habitat suitability over regional scales are not currently able to identify coral areas with pin point accuracy and probably overpredict actual coral distribution due to model limitations and unincorporated variables (i.e. data on distribution of hard substrate) that are known to limit their distribution. Predicted habitat results should be used in conjunction with multibeam bathymetry, geological mapping and other tools to guide future research efforts to areas with the highest probability of harboring deep-sea corals. Field validation of predicted habitat is needed to quantify model accuracy, particularly in areas that have not been sampled. PMID:24759613
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The Maternal Legacy: Female Identity Predicts Offspring Sex Ratio in the Loggerhead Sea Turtle.
Reneker, Jaymie L; Kamel, Stephanie J
2016-07-01
In organisms with temperature-dependent sex determination, the incubation environment plays a key role in determining offspring sex ratios. Given that global temperatures have warmed approximately 0.6 °C in the last century, it is necessary to consider how organisms will adjust to climate change. To better understand the degree to which mothers influence the sex ratios of their offspring, we use 24 years of nesting data for individual female loggerhead sea turtles (Caretta caretta) observed on Bald Head Island, North Carolina. We find that maternal identity is the best predictor of nest sex ratio in univariate and multivariate predictive models. We find significant variability in estimated nest sex ratios among mothers, but a high degree of consistency within mothers, despite substantial spatial and temporal thermal variation. Our results suggest that individual differences in nesting preferences are the main driver behind divergences in nest sex ratios. As such, a female's ability to plastically adjust her nest sex ratios in response to environmental conditions is constrained, potentially limiting how individuals behaviorally mitigate the effects of environmental change. Given that many loggerhead populations already show female-biased offspring sex ratios, understanding maternal behavioral responses is critical for predicting the future of long-lived species vulnerable to extinction.
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The Maternal Legacy: Female Identity Predicts Offspring Sex Ratio in the Loggerhead Sea Turtle
Reneker, Jaymie L.; Kamel, Stephanie J.
2016-01-01
In organisms with temperature-dependent sex determination, the incubation environment plays a key role in determining offspring sex ratios. Given that global temperatures have warmed approximately 0.6 °C in the last century, it is necessary to consider how organisms will adjust to climate change. To better understand the degree to which mothers influence the sex ratios of their offspring, we use 24 years of nesting data for individual female loggerhead sea turtles (Caretta caretta) observed on Bald Head Island, North Carolina. We find that maternal identity is the best predictor of nest sex ratio in univariate and multivariate predictive models. We find significant variability in estimated nest sex ratios among mothers, but a high degree of consistency within mothers, despite substantial spatial and temporal thermal variation. Our results suggest that individual differences in nesting preferences are the main driver behind divergences in nest sex ratios. As such, a female’s ability to plastically adjust her nest sex ratios in response to environmental conditions is constrained, potentially limiting how individuals behaviorally mitigate the effects of environmental change. Given that many loggerhead populations already show female-biased offspring sex ratios, understanding maternal behavioral responses is critical for predicting the future of long-lived species vulnerable to extinction. PMID:27363786
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INTEGRATED CHEMICAL INFORMATION TECHNOLOGIES ...
A central regulatory mandate of the Environmental Protection Agency, spanning many Program Offices and issues, is to assess the potential health and environmental risks of large numbers of chemicals released into the environment, often in the absence of relevant test data. Models for predicting potential adverse effects of chemicals based primarily on chemical structure play a central role in prioritization and screening strategies yet are highly dependent and conditional upon the data used for developing such models. Hence, limits on data quantity, quality, and availability are considered by many to be the largest hurdles to improving prediction models in diverse areas of toxicology. Generation of new toxicity data for additional chemicals and endpoints, development of new high-throughput, mechanistically relevant bioassays, and increased generation of genomics and proteomics data that can clarify relevant mechanisms will all play important roles in improving future SAR prediction models. The potential for much greater immediate gains, across large domains of chemical and toxicity space, comes from maximizing the ability to mine and model useful information from existing toxicity data, data that represent huge past investment in research and testing expenditures. In addition, the ability to place newer “omics” data, data that potentially span many possible domains of toxicological effects, in the broader context of historical data is the means for opti
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Chen, Han-Shen
2017-01-30
In this paper, the overall ecological and environmental sustainability in the Cing-Jing region in Taiwan is examined. As land use and cover change has been found to be an important analysis method, an emergy ecological footprint model was applied and the eco-security assessed to ensure authorities maintain a balance between ecological preservation and tourism development. While the ecological environment in the Cing-Jing region from 2008 to 2014 was found to be within safe levels, all related indices had increased considerably. A Grey model was used to predict the 2015-2024 ecological carrying capacities, from which it was found that there is expected to be a large increase in per capita ecological footprints (EFs), meaning that in the future there is going to be a larger ecological deficit and a higher ecological pressure index (EFI), with the eco-security predicted to reach a Grade 2 intermediate level in 2022. As the Cing-Jing region is predicted to become ecologically unsustainable, local, regional, and national governments need to implement regulations to strictly control the land use in the Cing-Jing region. This study demonstrated that emergy EF (EEF) theory application can give objective guidance to decision-makers to ensure that recreational non-urban eco-security can be maintained at a safe level.
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Predicting pre-Columbian anthropogenic soils in Amazonia
McMichael, C. H.; Palace, M. W.; Bush, M. B.; Braswell, B.; Hagen, S.; Neves, E. G.; Silman, M. R.; Tamanaha, E. K.; Czarnecki, C.
2014-01-01
The extent and intensity of pre-Columbian impacts on lowland Amazonia have remained uncertain and controversial. Various indicators can be used to gauge the impact of pre-Columbian societies, but the formation of nutrient-enriched terra preta soils has been widely accepted as an indication of long-term settlement and site fidelity. Using known and newly discovered terra preta sites and maximum entropy algorithms (Maxent), we determined the influence of regional environmental conditions on the likelihood that terra pretas would have been formed at any given location in lowland Amazonia. Terra pretas were most frequently found in central and eastern Amazonia along the lower courses of the major Amazonian rivers. Terrain, hydrologic and soil characteristics were more important predictors of terra preta distributions than climatic conditions. Our modelling efforts indicated that terra pretas are likely to be found throughout ca 154 063 km2 or 3.2% of the forest. We also predict that terra preta formation was limited in most of western Amazonia. Model results suggested that the distribution of terra preta was highly predictable based on environmental parameters. We provided targets for future archaeological surveys under the vast forest canopy and also highlighted how few of the long-term forest inventory sites in Amazonia are able to capture the effects of historical disturbance. PMID:24403329
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Uncertainty in Wildfire Behavior
NASA Astrophysics Data System (ADS)
Finney, M.; Cohen, J. D.
2013-12-01
The challenge of predicting or modeling fire behavior is well recognized by scientists and managers who attempt predictions of fire spread rate or growth. At the scale of the spreading fire, the uncertainty in winds, moisture, fuel structure, and fire location make accurate predictions difficult, and the non-linear response of fire spread to these conditions means that average behavior is poorly represented by average environmental parameters. Even more difficult are estimations of threshold behaviors (e.g. spread/no-spread, crown fire initiation, ember generation and spotting) because the fire responds as a step-function to small changes in one or more environmental variables, translating to dynamical feedbacks and unpredictability. Recent research shows that ignition of fuel particles, itself a threshold phenomenon, depends on flame contact which is absolutely not steady or uniform. Recent studies of flame structure in both spreading and stationary fires reveals that much of the non-steadiness of the flames as they contact fuel particles results from buoyant instabilities that produce quasi-periodic flame structures. With fuel particle ignition produced by time-varying heating and short-range flame contact, future improvements in fire behavior modeling will likely require statistical approaches to deal with the uncertainty at all scales, including the level of heat transfer, the fuel arrangement, and weather.
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Predicting pre-Columbian anthropogenic soils in Amazonia.
McMichael, C H; Palace, M W; Bush, M B; Braswell, B; Hagen, S; Neves, E G; Silman, M R; Tamanaha, E K; Czarnecki, C
2014-02-22
The extent and intensity of pre-Columbian impacts on lowland Amazonia have remained uncertain and controversial. Various indicators can be used to gauge the impact of pre-Columbian societies, but the formation of nutrient-enriched terra preta soils has been widely accepted as an indication of long-term settlement and site fidelity. Using known and newly discovered terra preta sites and maximum entropy algorithms (Maxent), we determined the influence of regional environmental conditions on the likelihood that terra pretas would have been formed at any given location in lowland Amazonia. Terra pretas were most frequently found in central and eastern Amazonia along the lower courses of the major Amazonian rivers. Terrain, hydrologic and soil characteristics were more important predictors of terra preta distributions than climatic conditions. Our modelling efforts indicated that terra pretas are likely to be found throughout ca 154 063 km(2) or 3.2% of the forest. We also predict that terra preta formation was limited in most of western Amazonia. Model results suggested that the distribution of terra preta was highly predictable based on environmental parameters. We provided targets for future archaeological surveys under the vast forest canopy and also highlighted how few of the long-term forest inventory sites in Amazonia are able to capture the effects of historical disturbance.
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Chen, Han-Shen
2017-01-01
In this paper, the overall ecological and environmental sustainability in the Cing-Jing region in Taiwan is examined. As land use and cover change has been found to be an important analysis method, an emergy ecological footprint model was applied and the eco-security assessed to ensure authorities maintain a balance between ecological preservation and tourism development. While the ecological environment in the Cing-Jing region from 2008 to 2014 was found to be within safe levels, all related indices had increased considerably. A Grey model was used to predict the 2015–2024 ecological carrying capacities, from which it was found that there is expected to be a large increase in per capita ecological footprints (EFs), meaning that in the future there is going to be a larger ecological deficit and a higher ecological pressure index (EFI), with the eco-security predicted to reach a Grade 2 intermediate level in 2022. As the Cing-Jing region is predicted to become ecologically unsustainable, local, regional, and national governments need to implement regulations to strictly control the land use in the Cing-Jing region. This study demonstrated that emergy EF (EEF) theory application can give objective guidance to decision-makers to ensure that recreational non-urban eco-security can be maintained at a safe level. PMID:28146086
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David N. Bengston
2012-01-01
Environmental foresight is insight into future environmental challenges and opportunities, and the ability to apply that insight to prepare wisely for a sustainable future. Successful environmental planning, management, and policy require the development and continual updating of foresight. U.S. Environmental Protection Agency (EPA) Administrator Stephen Johnson has...
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49 CFR 266.19 - Environmental impact.
Code of Federal Regulations, 2010 CFR
2010-10-01
... environmental assessment concludes that the future use significantly affects the quality of human environment... improvement assistance—(1) Environmental assessment. (i) When an applicant requests substitute service... shall: (A) Prepare an environmental assessment to determine whether the future use of the property will...
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Contrasted demographic responses facing future climate change in Southern Ocean seabirds.
Barbraud, Christophe; Rivalan, Philippe; Inchausti, Pablo; Nevoux, Marie; Rolland, Virginie; Weimerskirch, Henri
2011-01-01
1. Recent climate change has affected a wide range of species, but predicting population responses to projected climate change using population dynamics theory and models remains challenging, and very few attempts have been made. The Southern Ocean sea surface temperature and sea ice extent are projected to warm and shrink as concentrations of atmospheric greenhouse gases increase, and several top predator species are affected by fluctuations in these oceanographic variables. 2. We compared and projected the population responses of three seabird species living in sub-tropical, sub-Antarctic and Antarctic biomes to predicted climate change over the next 50 years. Using stochastic population models we combined long-term demographic datasets and projections of sea surface temperature and sea ice extent for three different IPCC emission scenarios (from most to least severe: A1B, A2, B1) from general circulation models of Earth's climate. 3. We found that climate mostly affected the probability to breed successfully, and in one case adult survival. Interestingly, frequent nonlinear relationships in demographic responses to climate were detected. Models forced by future predicted climatic change provided contrasted population responses depending on the species considered. The northernmost distributed species was predicted to be little affected by a future warming of the Southern Ocean, whereas steep declines were projected for the more southerly distributed species due to sea surface temperature warming and decrease in sea ice extent. For the most southerly distributed species, the A1B and B1 emission scenarios were respectively the most and less damaging. For the two other species, population responses were similar for all emission scenarios. 4. This is among the first attempts to study the demographic responses for several populations with contrasted environmental conditions, which illustrates that investigating the effects of climate change on core population dynamics is feasible for different populations using a common methodological framework. Our approach was limited to single populations and have neglected population settlement in new favourable habitats or changes in inter-specific relations as a potential response to future climate change. Predictions may be enhanced by merging demographic population models and climatic envelope models. © 2010 The Authors. Journal compilation © 2010 British Ecological Society.
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Moncrieff, Glenn R; Scheiter, Simon; Bond, William J; Higgins, Steven I
2014-02-01
The dominant vegetation over much of the global land surface is not predetermined by contemporary climate, but also influenced by past environmental conditions. This confounds attempts to predict current and future biome distributions, because even a perfect model would project multiple possible biomes without knowledge of the historical vegetation state. Here we compare the distribution of tree- and grass-dominated biomes across Africa simulated using a dynamic global vegetation model (DGVM). We explicitly evaluate where and under what conditions multiple stable biome states are possible for current and projected future climates. Our simulation results show that multiple stable biomes states are possible for vast areas of tropical and subtropical Africa under current conditions. Widespread loss of the potential for multiple stable biomes states is projected in the 21st Century, driven by increasing atmospheric CO2 . Many sites where currently both tree-dominated and grass-dominated biomes are possible become deterministically tree-dominated. Regions with multiple stable biome states are widespread and require consideration when attempting to predict future vegetation changes. Testing for behaviour characteristic of systems with multiple stable equilibria, such as hysteresis and dependence on historical conditions, and the resulting uncertainty in simulated vegetation, will lead to improved projections of global change impacts. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.
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Schaefer, Jonathan D; Scult, Matthew A; Caspi, Avshalom; Arseneault, Louise; Belsky, Daniel W; Hariri, Ahmad R; Harrington, Honalee; Houts, Renate; Ramrakha, Sandhya; Poulton, Richie; Moffitt, Terrie E
2017-11-16
Cognitive impairment has been identified as an important aspect of major depressive disorder (MDD). We tested two theories regarding the association between MDD and cognitive functioning using data from longitudinal cohort studies. One theory, the cognitive reserve hypothesis, suggests that higher cognitive ability in childhood decreases risk of later MDD. The second, the scarring hypothesis, instead suggests that MDD leads to persistent cognitive deficits following disorder onset. We tested both theories in the Dunedin Study, a population-representative cohort followed from birth to midlife and assessed repeatedly for both cognitive functioning and psychopathology. We also used data from the Environmental Risk Longitudinal Twin Study to test whether childhood cognitive functioning predicts future MDD risk independent of family-wide and genetic risk using a discordant twin design. Contrary to both hypotheses, we found that childhood cognitive functioning did not predict future risk of MDD, nor did study members with a past history of MDD show evidence of greater cognitive decline unless MDD was accompanied by other comorbid psychiatric conditions. Our results thus suggest that low cognitive functioning is related to comorbidity, but is neither an antecedent nor an enduring consequence of MDD. Future research may benefit from considering cognitive deficits that occur during depressive episodes from a transdiagnostic perspective.
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Toward Malaria Risk Prediction in Afghanistan Using Remote Sensing
NASA Technical Reports Server (NTRS)
Safi, N.; Adimi, F.; Soebiyanto, R. P.; Kiang, R. K.
2010-01-01
Malaria causes more than one million deaths every year worldwide, with most of the mortality in Sub-Saharan Africa. It is also a significant public health concern in Afghanistan, with approximately 60% of the population, or nearly 14 million people, living in a malaria-endemic area. Malaria transmission has been shown to be dependent on a number of environmental and meteorological variables. For countries in the tropics and the subtropics, rainfall is normally the most important variable, except for regions with high altitude where temperature may also be important. Afghanistan s diverse landscape contributes to the heterogeneous malaria distribution. Understanding the environmental effects on malaria transmission is essential to the effective control of malaria in Afghanistan. Provincial malaria data gathered by Health Posts in 23 provinces during 2004-2007 are used in this study. Remotely sensed geophysical parameters, including precipitation from TRMM, and surface temperature and vegetation index from MODIS are used to derive the empirical relationship between malaria cases and these geophysical parameters. Both neural network methods and regression analyses are used to examine the environmental dependency of malaria transmission. And the trained models are used for predicting future transmission. While neural network methods are intrinsically more adaptive for nonlinear relationship, the regression approach lends itself in providing statistical significance measures. Our results indicate that NDVI is the strongest predictor. This reflects the role of irrigation, instead of precipitation, in Afghanistan for agricultural production. The second strongest prediction is surface temperature. Precipitation is not shown as a significant predictor, contrary to other malarious countries in the tropics or subtropics. With the regression approach, the malaria time series are modelled well, with average R2 of 0.845. For cumulative 6-month prediction of malaria cases, the average provincial accuracy reaches 91%. The developed predictive and early warning capabilities support the Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan.
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NASA Astrophysics Data System (ADS)
Xiao, Wupeng; Wang, Lei; Laws, Edward; Xie, Yuyuan; Chen, Jixin; Liu, Xin; Chen, Bingzhang; Huang, Bangqin
2018-03-01
A basic albeit elusive goal of ocean science is to predict the structure of biological communities from the multitude of environmental conditions they experience. Estimates of the realized niche-based traits (realized traits) of phytoplankton species or functional groups in temperate seas have shown that response traits can help reveal the mechanisms responsible for structuring phytoplankton communities, but such approaches have not been tested in tropical and subtropical marginal seas. Here, we used decadal-scale studies of pigment-based phytoplankton groups and environmental conditions in the South China Sea to test whether realized traits could explain the biogeographic patterns of phytoplankton variability. We estimated the mean and breadth of the phytoplankton realized niches based on responses of the group-specific phytoplankton composition to key environmental factors, and we showed that variations of major phytoplankton groups in this system can be explained by different adaptive trade-offs to constraints imposed by temperature, irradiance, and nutrient concentrations. Differences in the patterns of trade-offs clearly separated the dominant groups from one another and generated four sets of realized traits that mirrored the observed biogeographic distribution patterns. The phytoplankton realized niches and their associated traits that we characterized in the present study could help to predict responses of phytoplankton to changes in environmental conditions in the South China Sea and could be incorporated into global biogeochemical models to anticipate shifts in community structure under future climate scenarios.
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Pires, Marcel Viana; da Cunha, Dênis Antônio; de Matos Carlos, Sabrina; Costa, Marcos Heil
2015-01-01
The agriculture sector has historically been a major source of greenhouse gas (GHG) emissions into the atmosphere. Although the use of synthetic fertilizers is one of the most common widespread agricultural practices, over-fertilization can lead to negative economic and environmental consequences, such as high production costs, depletion of energy resources, and increased GHG emissions. Here, we provide an analysis to understand the evolution of cereal production and consumption of nitrogen (N) fertilizers in Brazil and to correlate N use efficiency (NUE) with economic and environmental losses as N2O emissions. Our results show that the increased consumption of N fertilizers is associated with a large decrease in NUE in recent years. The CO2 eq. of N2O emissions originating from N fertilization for cereal production were approximately 12 times higher in 2011 than in 1970, indicating that the inefficient use of N fertilizers is directly related to environmental losses. The projected N fertilizer forecasts are 2.09 and 2.37 million ton for 2015 and 2023, respectively. An increase of 0.02% per year in the projected NUE was predicted for the same time period. However, decreases in the projected CO2 eq. emissions for future years were not predicted. In a hypothetical scenario, a 2.39% increase in cereal NUE would lead to $ 21 million savings in N fertilizer costs. Thus, increases in NUE rates would lead not only to agronomic and environmental benefits but also to economic improvement.
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Pires, Marcel Viana; da Cunha, Dênis Antônio; de Matos Carlos, Sabrina; Costa, Marcos Heil
2015-01-01
The agriculture sector has historically been a major source of greenhouse gas (GHG) emissions into the atmosphere. Although the use of synthetic fertilizers is one of the most common widespread agricultural practices, over-fertilization can lead to negative economic and environmental consequences, such as high production costs, depletion of energy resources, and increased GHG emissions. Here, we provide an analysis to understand the evolution of cereal production and consumption of nitrogen (N) fertilizers in Brazil and to correlate N use efficiency (NUE) with economic and environmental losses as N2O emissions. Our results show that the increased consumption of N fertilizers is associated with a large decrease in NUE in recent years. The CO2 eq. of N2O emissions originating from N fertilization for cereal production were approximately 12 times higher in 2011 than in 1970, indicating that the inefficient use of N fertilizers is directly related to environmental losses. The projected N fertilizer forecasts are 2.09 and 2.37 million ton for 2015 and 2023, respectively. An increase of 0.02% per year in the projected NUE was predicted for the same time period. However, decreases in the projected CO2 eq. emissions for future years were not predicted. In a hypothetical scenario, a 2.39% increase in cereal NUE would lead to $ 21 million savings in N fertilizer costs. Thus, increases in NUE rates would lead not only to agronomic and environmental benefits but also to economic improvement. PMID:26252377
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The Essential Role for Laboratory Studies in Atmospheric Chemistry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Burkholder, James B.; Abbatt, Jonathan P. D.; Barnes, Ian
Laboratory studies of atmospheric chemistry characterize the nature of atmospherically relevant processes down to the molecular level, providing fundamental information used to assess how human activities drive environmental phenomena such as climate change, urban air pollution, ecosystem health, indoor air quality, and stratospheric ozone depletion. Laboratory studies have a central role in addressing the incomplete fundamental knowledge of atmospheric chemistry. This paper highlights the evolving science needs for this community and emphasizes how our knowledge is far from complete, hindering our ability to predict the future state of our atmosphere and to respond to emerging global environmental change issues. Finally,more » laboratory studies provide rich opportunities to expand our understanding of the atmosphere via collaborative research with the modeling and field measurement communities, and with neighboring disciplines.« less
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Anticipating Their Future: Adolescent Values for the Future Predict Adult Behaviors
Finlay, Andrea; Wray-Lake, Laura; Warren, Michael; Maggs, Jennifer L.
2014-01-01
Adolescent future values – beliefs about what will matter to them in the future – may shape their adult behavior. Utilizing a national longitudinal British sample, this study examined whether adolescent future values in six domains (i.e., family responsibility, full-time job, personal responsibility, autonomy, civic responsibility, and hedonistic privilege) predicted adult social roles, civic behaviors, and alcohol use. Future values positively predicted behaviors within the same domain; fewer cross-domain associations were evident. Civic responsibility positively predicted adult civic behaviors, but negatively predicted having children. Hedonistic privilege positively predicted adult alcohol use and negatively predicted civic behaviors. Results suggest that attention should be paid to how adolescents are thinking about their futures due to the associated links with long-term social and health behaviors. PMID:26279595
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Christensen, A. J.; Srinivasan, V.; Hart, J. C.; ...
2018-03-17
Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less
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NASA Astrophysics Data System (ADS)
Del Vasto-Terrientes, L.; Kumar, V.; Chao, T.-C.; Valls, A.
2016-03-01
Global change refers to climate changes, but also demographic, technological and economic changes. Predicted water scarcity will be critical in the coastal Mediterranean region, especially for provision to mid-sized and large-sized cities. This paper studies the case of the city of Tarragona, located at the Mediterranean area of north-eastern Spain (Catalonia). Several scenarios have been constructed to evaluate different sectorial water allocation policies to mitigate the water scarcity induced by global change. Future water supply and demand predictions have been made for three time spans. The decision support system presented is based on the outranking model, which constructs a partial pre-order based on pairwise preference relations among all the possible actions. The system analyses a hierarchical structure of criteria, including environmental and economic criteria. We compare several adaptation measures including alternative water sources, inter-basin water transfer and sectorial demand management coming from industry, agriculture and domestic sectors. Results indicate that the most appropriate water allocation strategies depend on the severity of the global change effects.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Christensen, A. J.; Srinivasan, V.; Hart, J. C.
Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less
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Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy
2018-05-01
Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in "big data" analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.
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Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy
2018-01-01
Abstract Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields. PMID:29562368
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DNA Methylation Biomarkers: Cancer and Beyond
Mikeska, Thomas; Craig, Jeffrey M.
2014-01-01
Biomarkers are naturally-occurring characteristics by which a particular pathological process or disease can be identified or monitored. They can reflect past environmental exposures, predict disease onset or course, or determine a patient’s response to therapy. Epigenetic changes are such characteristics, with most epigenetic biomarkers discovered to date based on the epigenetic mark of DNA methylation. Many tissue types are suitable for the discovery of DNA methylation biomarkers including cell-based samples such as blood and tumor material and cell-free DNA samples such as plasma. DNA methylation biomarkers with diagnostic, prognostic and predictive power are already in clinical trials or in a clinical setting for cancer. Outside cancer, strong evidence that complex disease originates in early life is opening up exciting new avenues for the detection of DNA methylation biomarkers for adverse early life environment and for estimation of future disease risk. However, there are a number of limitations to overcome before such biomarkers reach the clinic. Nevertheless, DNA methylation biomarkers have great potential to contribute to personalized medicine throughout life. We review the current state of play for DNA methylation biomarkers, discuss the barriers that must be crossed on the way to implementation in a clinical setting, and predict their future use for human disease. PMID:25229548
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Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M; Aguiar, Javier M; Carro, Belén
2012-10-17
This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed.
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Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks
Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir
2014-01-01
Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950
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Martínez-Martínez, Víctor; Baladrón, Carlos; Gomez-Gil, Jaime; Ruiz-Ruiz, Gonzalo; Navas-Gracia, Luis M.; Aguiar, Javier M.; Carro, Belén
2012-01-01
This paper presents a system based on an Artificial Neural Network (ANN) for estimating and predicting environmental variables related to tobacco drying processes. This system has been validated with temperature and relative humidity data obtained from a real tobacco dryer with a Wireless Sensor Network (WSN). A fitting ANN was used to estimate temperature and relative humidity in different locations inside the tobacco dryer and to predict them with different time horizons. An error under 2% can be achieved when estimating temperature as a function of temperature and relative humidity in other locations. Moreover, an error around 1.5 times lower than that obtained with an interpolation method can be achieved when predicting the temperature inside the tobacco mass as a function of its present and past values with time horizons over 150 minutes. These results show that the tobacco drying process can be improved taking into account the predicted future value of the monitored variables and the estimated actual value of other variables using a fitting ANN as proposed. PMID:23202032
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Predicting physical time series using dynamic ridge polynomial neural networks.
Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir
2014-01-01
Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.
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Water quality management using statistical analysis and time-series prediction model
NASA Astrophysics Data System (ADS)
Parmar, Kulwinder Singh; Bhardwaj, Rashmi
2014-12-01
This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.
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Langevin dynamics encapsulate the microscopic and emergent macroscopic properties of midge swarms
2018-01-01
In contrast to bird flocks, fish schools and animal herds, midge swarms maintain cohesion but do not possess global order. High-speed imaging techniques are now revealing that these swarms have surprising properties. Here, I show that simple models found on the Langevin equation are consistent with this wealth of recent observations. The models predict correctly that large accelerations, exceeding 10 g, will be common and they predict correctly the coexistence of core condensed phases surrounded by dilute vapour phases. The models also provide new insights into the influence of environmental conditions on swarm dynamics. They predict that correlations between midges increase the strength of the effective force binding the swarm together. This may explain why such correlations are absent in laboratory swarms but present in natural swarms which contend with the wind and other disturbances. Finally, the models predict that swarms have fluid-like macroscopic mechanical properties and will slosh rather than slide back and forth after being abruptly displaced. This prediction offers a promising avenue for future experimentation that goes beyond current quasi-static testing which has revealed solid-like responses. PMID:29298958
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NASA Astrophysics Data System (ADS)
Fer, Istem; Tietjen, Britta; Jeltsch, Florian; Wolff, Christian
2017-09-01
The El Niño-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
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Future generations, environmental ethics, and global environmental change
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tonn, B.E.
1994-12-31
The elements of a methodology to be employed by the global community to investigate the consequences of global environmental change upon future generations and global ecosystems are outlined in this paper. The methodology is comprised of two major components: A possible future worlds model; and a formal, citizen-oriented process to judge whether the possible future worlds potentially inheritable by future generations meet obligational standards. A broad array of descriptors of future worlds can be encompassed within this framework, including survival of ecosystems and other species and satisfaction of human concerns. The methodology expresses fundamental psychological motivations and human myths journey,more » renewal, mother earth, and being-in-nature-and incorporates several viewpoints on obligations to future generations-maintaining options, fairness, humility, and the cause of humanity. The methodology overcomes several severe drawbacks of the economic-based methods most commonly used for global environmental policy analysis.« less
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Post, Eric; Forchhammer, Mads C
2004-06-22
According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.
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The Simulations of Wildland Fire Smoke PM25 in the NWS Air Quality Forecasting Systems
NASA Astrophysics Data System (ADS)
Huang, H. C.; Pan, L.; McQueen, J.; Lee, P.; ONeill, S. M.; Ruminski, M.; Shafran, P.; Huang, J.; Stajner, I.; Upadhayay, S.; Larkin, N. K.
2017-12-01
The increase of wildland fire intensity and frequency in the United States (U.S.) has led to property loss, human fatality, and poor air quality due to elevated particulate matters and surface ozone concentrations. The NOAA/National Weather Service (NWS) built the National Air Quality Forecast Capability (NAQFC) based on the U.S. Environmental Protection Agency (EPA) Community Multi-scale Air Quality (CMAQ) Modeling System driven by the NCEP North American Mesoscale Forecast System meteorology to provide ozone and fine particulate matter (PM2.5) forecast guidance publicly. State and local forecasters use the NWS air quality forecast guidance to issue air quality alerts in their area. The NAQFC PM2.5 predictions include emissions from anthropogenic and biogenic sources, as well as natural sources such as dust storms and wildland fires. The wildland fire emission inputs to the NAQFC is derived from the NOAA National Environmental Satellite, Data, and Information Service Hazard Mapping System fire and smoke detection product and the emission module of the U.S. Forest Service (USFS) BlueSky Smoke Modeling Framework. Wildland fires are unpredictable and can be ignited by natural causes such as lightning or be human-caused. It is extremely difficult to predict future occurrences and behavior of wildland fires, as is the available bio-fuel to be burned for real-time air quality predictions. Assumptions of future day's wildland fire behavior often have to be made from older observed wildland fire information. The comparisons between the NAQFC modeled PM2.5 and the EPA AirNow surface observation show that large errors in PM2.5 prediction can occur if fire smoke emissions are sometimes placed at the wrong location and/or time. A configuration of NAQFC CMAQ-system to re-run previous 24 hours, during which wildland fires were observed from satellites has been included recently. This study focuses on the effort performed to minimize the error in NAQFC PM2.5 predictions resulting from incorporating fire smoke emissions into the NAQFC from a recently updated newer version of USFS BlueSky system. This study will show how new approaches has improved the PM2.5 predictions at both nearby and downstream areas from fire sources. Furthermore, Environment and Climate Change Canada (ECCC) fire emissions data are being tested.
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Kim, Jaeshin; Mackay, Donald; Whelan, Michael John
2018-03-01
We investigated the response times of eight volatile methylsiloxanes (VMSs) in environmental systems at different scales from local to global, with a particular focus on overall loss rates after cessation of emissions. In part, this is driven by proposals to restrict the use of some of these compounds in certain products in Europe. The GloboPOP model estimated low absolute Arctic Contamination Potentials for all VMSs and rapid response times in all media except sediment. VMSs are predicted to be distributed predominantly in air where they react with OH radicals, leading to short response times. After cessation of emissions VMSs concentrations in the environment are expected to decrease rapidly from current levels. Response times in specific water and sediment systems were evaluated using a dynamic QWASI model. Response times were sensitive to both physico-chemical properties and environmental characteristics. Degradation was predicted to play the most important role in determining response times in water and sediment. In the case of the lowest molecular weight VMSs such as L2 and D3, response times were essentially independent of environmental characteristics due to fast hydrolysis in water and sediment. However, response times for the other VMSs are system-specific. They are relatively short in shallow water bodies but increase with depth due to the diminishing role of volatilization on concentration change as volume to surface area ratio increases. In sediment, degradation and resuspension rates also contribute most to the response times. The estimated response times for local environments are useful for planning future monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Helmuth, Brian; Broitman, Bernardo R; Yamane, Lauren; Gilman, Sarah E; Mach, Katharine; Mislan, K A S; Denny, Mark W
2010-03-15
Predicting when, where and with what magnitude climate change is likely to affect the fitness, abundance and distribution of organisms and the functioning of ecosystems has emerged as a high priority for scientists and resource managers. However, even in cases where we have detailed knowledge of current species' range boundaries, we often do not understand what, if any, aspects of weather and climate act to set these limits. This shortcoming significantly curtails our capacity to predict potential future range shifts in response to climate change, especially since the factors that set range boundaries under those novel conditions may be different from those that set limits today. We quantitatively examine a nine-year time series of temperature records relevant to the body temperatures of intertidal mussels as measured using biomimetic sensors. Specifically, we explore how a 'climatology' of body temperatures, as opposed to long-term records of habitat-level parameters such as air and water temperatures, can be used to extrapolate meaningful spatial and temporal patterns of physiological stress. Using different metrics that correspond to various aspects of physiological stress (seasonal means, cumulative temperature and the return time of extremes) we show that these potential environmental stressors do not always occur in synchrony with one another. Our analysis also shows that patterns of animal temperature are not well correlated with simple, commonly used metrics such as air temperature. Detailed physiological studies can provide guidance to predicting the effects of global climate change on natural ecosystems but only if we concomitantly record, archive and model environmental signals at appropriate scales.
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A Sense of Place: Integrating Environmental Psychology into Marine Socio-Ecological Models
NASA Astrophysics Data System (ADS)
van Putten, I. E.; Fleming, A.; Fulton, E.; Plaganyi-Lloyd, E.
2016-02-01
Sense of place is a concept that is increasingly applied in different social research contexts where it can act as a bridge between disciplines that might otherwise work in parallel. A sense of place is a well established and flexible concept that has been empirically measured using different survey methods. The psychological principals and theories that underpin sense of place have been inextricably linked to the quality of ecological systems and the impact on development of the system, and vice versa. Ecological models and scenario analyses play an important role in characterising, assessing and predicting the potential impacts of alternative developments and other changes affecting ecological systems. To improve the predictive accuracy of ecological models, human drivers, interactions, and uses have been dynamically incorporated, for instance, through management strategy evaluation applied to marine ecosystem models. However, to date no socio-ecological models (whether terrestrial or marine) have been developed that incorporate a dynamic feedback between ecosystem characteristics and peoples' sense of place. These models thus essentially ignore the influence of environmental psychology on the way people use and interact with ecosystems. We develop a proof of concept and provide a mathematical basis for a Sense of Place Index (SoPI) that allows the quantitative integration of environmental psychology into socio-ecological models. Incorporating dynamic feedback between the SoPI for different resource user groups and the ecological system improves the accuracy and precision of predictions regarding future resource use as well as, ultimately, the potential state of the resource to be developed.
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Hydrological responses to dynamically and statistically downscaled climate model output
Wilby, R.L.; Hay, L.E.; Gutowski, W.J.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.
2000-01-01
Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Voynikova, D. S., E-mail: desi-sl2000@yahoo.com; Gocheva-Ilieva, S. G., E-mail: snegocheva@yahoo.com; Ivanov, A. V., E-mail: aivanov-99@yahoo.com
Numerous time series methods are used in environmental sciences allowing the detailed investigation of air pollution processes. The goal of this study is to present the empirical analysis of various aspects of stochastic modeling and in particular the ARIMA/SARIMA methods. The subject of investigation is air pollution in the town of Kardzhali, Bulgaria with 2 problematic pollutants – sulfur dioxide (SO2) and particulate matter (PM10). Various SARIMA Transfer Function models are built taking into account meteorological factors, data transformations and the use of different horizons selected to predict future levels of concentrations of the pollutants.
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NASA Astrophysics Data System (ADS)
Boori, Mukesh S.; Choudhary, Komal; Kupriyanov, Alexander; Sugimoto, Atsuko; Evers, Mariele
2016-10-01
The aim of this research work is to understand natural and environmental vulnerability situation and its cause such as intensity, distribution and socio-economic effect in the Indigirka River basin, Eastern Siberia, Russia. This paper identifies, assess and classify natural and environmental vulnerability using landscape pattern from multidisciplinary approach, based on remote sensing and Geographical Information System (GIS) techniques. A model was developed by following thematic layers: land use/cover, vegetation, wetland, geology, geomorphology and soil in ArcGIS 10.2 software. According to numerical results vulnerability classified into five levels: low, sensible, moderate, high and extreme vulnerability by mean of cluster principal. Results are shows that in natural vulnerability maximum area covered by moderate (29.84%) and sensible (38.61%) vulnerability and environmental vulnerability concentrated by moderate (49.30%) vulnerability. So study area has at medial level vulnerability. The results found that the methodology applied was effective enough in the understanding of the current conservation circumstances of the river basin in relation to their environment with the help of remote sensing and GIS. This study is helpful for decision making for eco-environmental recovering and rebuilding as well as predicting the future development.
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The burden of typhoid fever in low- and middle-income countries: A meta-regression approach
Warren, Joshua L.; Crawford, Forrest W.; Weinberger, Daniel M.; Kürüm, Esra; Pak, Gi Deok; Marks, Florian; Pitzer, Virginia E.
2017-01-01
Background Upcoming vaccination efforts against typhoid fever require an assessment of the baseline burden of disease in countries at risk. There are no typhoid incidence data from most low- and middle-income countries (LMICs), so model-based estimates offer insights for decision-makers in the absence of readily available data. Methods We developed a mixed-effects model fit to data from 32 population-based studies of typhoid incidence in 22 locations in 14 countries. We tested the contribution of economic and environmental indices for predicting typhoid incidence using a stochastic search variable selection algorithm. We performed out-of-sample validation to assess the predictive performance of the model. Results We estimated that 17.8 million cases of typhoid fever occur each year in LMICs (95% credible interval: 6.9–48.4 million). Central Africa was predicted to experience the highest incidence of typhoid, followed by select countries in Central, South, and Southeast Asia. Incidence typically peaked in the 2–4 year old age group. Models incorporating widely available economic and environmental indicators were found to describe incidence better than null models. Conclusions Recent estimates of typhoid burden may under-estimate the number of cases and magnitude of uncertainty in typhoid incidence. Our analysis permits prediction of overall as well as age-specific incidence of typhoid fever in LMICs, and incorporates uncertainty around the model structure and estimates of the predictors. Future studies are needed to further validate and refine model predictions and better understand year-to-year variation in cases. PMID:28241011
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Predicting the Timing of Maturational Spurts in Skeletal Age
Nahhas, Ramzi W.; Sherwood, Richard J.; Chumlea, Wm. Cameron; Towne, Bradford; Duren, Dana L.
2014-01-01
Measures of maturity provide windows into the timing and tempo of childhood growth and maturation. Delayed maturation in a single child, or systemically in a population, can result from either genetic or environmental factors. In terms of the skeleton, delayed maturation may result in short stature or indicate another underlying issue. Thus, prediction of the timing of a maturational spurt is often desirable in order to determine the likelihood that a child will catch up to their chronological age peers. Serial data from the Fels Longitudinal Study were used to predict future skeletal age conditional on current skeletal age and to predict the timing of maturational spurts. For children who were delayed relative to their chronological age peers, the like-lihood of catch-up maturation increased through the average age of onset of puberty and decreased prior to the average age of peak height velocity. For boys, the probability of an imminent maturational spurt was higher for those who were less mature. For girls aged 11 to 13 years, however, this probability was higher for those who were more mature, potentially indicating the presence of a skeletal maturation plateau between multiple spurts. The prediction model, available on the web, is most relevant to children of European ancestry living in the Midwestern US. Our model may also provide insight into the tempo of maturation for children in other populations, but must be applied with caution if those populations are known to have high burdens of environmental stressors not typical of the Midwestern US. Am J Phys Anthropol 150:68–75, 2013. PMID:23283666
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National Centers for Environmental Prediction
Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Environmental Prediction Environmental Modeling Center NOAA Center for Weather and Climate Prediction (NCWCP
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Heslot, Nicolas; Akdemir, Deniz; Sorrells, Mark E; Jannink, Jean-Luc
2014-02-01
Development of models to predict genotype by environment interactions, in unobserved environments, using environmental covariates, a crop model and genomic selection. Application to a large winter wheat dataset. Genotype by environment interaction (G*E) is one of the key issues when analyzing phenotypes. The use of environment data to model G*E has long been a subject of interest but is limited by the same problems as those addressed by genomic selection methods: a large number of correlated predictors each explaining a small amount of the total variance. In addition, non-linear responses of genotypes to stresses are expected to further complicate the analysis. Using a crop model to derive stress covariates from daily weather data for predicted crop development stages, we propose an extension of the factorial regression model to genomic selection. This model is further extended to the marker level, enabling the modeling of quantitative trait loci (QTL) by environment interaction (Q*E), on a genome-wide scale. A newly developed ensemble method, soft rule fit, was used to improve this model and capture non-linear responses of QTL to stresses. The method is tested using a large winter wheat dataset, representative of the type of data available in a large-scale commercial breeding program. Accuracy in predicting genotype performance in unobserved environments for which weather data were available increased by 11.1% on average and the variability in prediction accuracy decreased by 10.8%. By leveraging agronomic knowledge and the large historical datasets generated by breeding programs, this new model provides insight into the genetic architecture of genotype by environment interactions and could predict genotype performance based on past and future weather scenarios.
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Evangelista, P.H.; Kumar, S.; Stohlgren, T.J.; Young, N.E.
2011-01-01
The aim of our study was to estimate forest vulnerability and potential distribution of three bark beetles (Curculionidae: Scolytinae) under current and projected climate conditions for 2020 and 2050. Our study focused on the mountain pine beetle (Dendroctonus ponderosae), western pine beetle (Dendroctonus brevicomis), and pine engraver (Ips pini). This study was conducted across eight states in the Interior West of the US covering approximately 2.2millionkm2 and encompassing about 95% of the Rocky Mountains in the contiguous US. Our analyses relied on aerial surveys of bark beetle outbreaks that occurred between 1991 and 2008. Occurrence points for each species were generated within polygons created from the aerial surveys. Current and projected climate scenarios were acquired from the WorldClim database and represented by 19 bioclimatic variables. We used Maxent modeling technique fit with occurrence points and current climate data to model potential beetle distributions and forest vulnerability. Three available climate models, each having two emission scenarios, were modeled independently and results averaged to produce two predictions for 2020 and two predictions for 2050 for each analysis. Environmental parameters defined by current climate models were then used to predict conditions under future climate scenarios, and changes in different species' ranges were calculated. Our results suggested that the potential distribution for bark beetles under current climate conditions is extensive, which coincides with infestation trends observed in the last decade. Our results predicted that suitable habitats for the mountain pine beetle and pine engraver beetle will stabilize or decrease under future climate conditions, while habitat for the western pine beetle will continue to increase over time. The greatest increase in habitat area was for the western pine beetle, where one climate model predicted a 27% increase by 2050. In contrast, the predicted habitat of the mountain pine beetle from another climate model suggested a decrease in habitat areas as great as 46% by 2050. Generally, 2020 and 2050 models that tested the three climate scenarios independently had similar trends, though one climate scenario for the western pine beetle produced contrasting results. Ranges for all three species of bark beetles shifted considerably geographically suggesting that some host species may become more vulnerable to beetle attack in the future, while others may have a reduced risk over time. ?? 2011 Elsevier B.V.
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Sweat loss prediction using a multi-model approach
NASA Astrophysics Data System (ADS)
Xu, Xiaojiang; Santee, William R.
2011-07-01
A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.
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Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.
2013-01-01
Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.
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Muzari, M. Odwell; English, Sinead
2018-01-01
Theory suggests females should optimize resource allocation across reproductive bouts to maximize lifetime reproduction, balancing current and future reproductive efforts according to physiological state and projected survival and reproduction. Tests of these ideas focus on long-lived vertebrates: few measure age-related reproductive output in iteroparous invertebrates, or partition reserves between those allocated to offspring versus mothers. We investigated how maternal age, and environmental and physiological factors influence reproductive investment in wild tsetse, Glossina pallidipes Austen and G. morsitans morsitans Westwood. Tsetse provide a tractable system to measure reproductive allocation. Females exhibit high maternal investment, producing single, large offspring that rely exclusively on maternal reserves. We find that mothers in better physiological condition and experiencing cooler temperatures produce larger offspring. Pupal size increases significantly but weakly with age. In both species, females with less fat invest proportionately more in offspring. Post-partum fat decreases in flies with badly frayed wings: poor flight capability may limit their feeding efficiency, or they may sacrifice more reserves as a terminal investment. Our results support evidence that offspring size increases with maternal size, investment depends on the environment, and females with lower chances of future reproduction invest more into current offspring. We discuss the implications of maternal effects for predicting vector population responses to environmental change. PMID:29515882
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High-Heat-Flux Cyclic Durability of Thermal and Environmental Barrier Coatings
NASA Technical Reports Server (NTRS)
Zhu, Dongming; Ghosn, Louis L.; Miller, Robert A.
2007-01-01
Advanced ceramic thermal and environmental barrier coatings will play an increasingly important role in future gas turbine engines because of their ability to protect the engine components and further raise engine temperatures. For the supersonic vehicles currently envisioned in the NASA fundamental aeronautics program, advanced gas turbine engines will be used to provide high power density thrust during the extended supersonic flight of the aircraft, while meeting stringent low emission requirements. Advanced ceramic coating systems are critical to the performance, life and durability of the hot-section components of the engine systems. In this work, the laser and burner rig based high-heat-flux testing approaches were developed to investigate the coating cyclic response and failure mechanisms under simulated supersonic long-duration cruise mission. The accelerated coating cracking and delamination mechanism under the engine high-heat-flux, and extended supersonic cruise time conditions will be addressed. A coating life prediction framework may be realized by examining the crack initiation and propagation in conjunction with environmental degradation under high-heat-flux test conditions.
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Anderson, Paul A; Poe, Russell B; Thompson, Laura A; Weber, Nansen; Romano, Tracy A
2017-12-01
Some Arctic estuaries serve as substrate rubbing sites for beluga whales (Delphinapterus leucas) in the summer, representing a specialized resource for the species. Understanding how environmental variation affects the species' behavior is essential to management of these habitats in coming years as the climate changes. Spatiotemporal and environmental variables were recorded for behavioral observations, during which focal groups of whales in an estuary were video-recorded for enumeration and behavioral analysis. Multiple polynomial linear regression models were optimized to identify the effects of spatiotemporal and environmental conditions on group size, composition, and the frequency of behaviors being performed. Results suggest that belugas take advantage of environmental variation to express behaviors that 1) protect young, e.g., bringing calves close to shore during cloudier days, obscuring visualization from terrestrial predators; 2) avoid predation, e.g., rubbing against substrates at higher Beaufort sea states to obscure visualization, and resting during low tides while swimming on outgoing tides to avoid stranding; and 3) optimize bioenergetic resources, e.g., swimming during lower Beaufort sea states and clearer days. Predictive models like the ones presented in this study can inform conservation management strategies as environmental conditions change in future years. Copyright © 2017 Elsevier B.V. All rights reserved.
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GLOBAL ALTERNATIVE FUTURE SCENARIOS
One way to examine possible future outcomes for environmental protection is through the development and analysis of alternative future scenarios. This type of assessment postulates two or more different paths that social and environmental development might take, using correspond...
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Warm climates of the past—a lesson for the future?
Lunt, D. J.; Elderfield, H.; Pancost, R.; Ridgwell, A.; Foster, G. L.; Haywood, A.; Kiehl, J.; Sagoo, N.; Shields, C.; Stone, E. J.; Valdes, P.
2013-01-01
This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10–11 October 2011. The Discussion Meeting, entitled ‘Warm climates of the past: a lesson for the future?’, brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change. PMID:24043873
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Warm climates of the past--a lesson for the future?
Lunt, D J; Elderfield, H; Pancost, R; Ridgwell, A; Foster, G L; Haywood, A; Kiehl, J; Sagoo, N; Shields, C; Stone, E J; Valdes, P
2013-10-28
This Discussion Meeting Issue of the Philosophical Transactions A had its genesis in a Discussion Meeting of the Royal Society which took place on 10-11 October 2011. The Discussion Meeting, entitled 'Warm climates of the past: a lesson for the future?', brought together 16 eminent international speakers from the field of palaeoclimate, and was attended by over 280 scientists and members of the public. Many of the speakers have contributed to the papers compiled in this Discussion Meeting Issue. The papers summarize the talks at the meeting, and present further or related work. This Discussion Meeting Issue asks to what extent information gleaned from the study of past climates can aid our understanding of future climate change. Climate change is currently an issue at the forefront of environmental science, and also has important sociological and political implications. Most future predictions are carried out by complex numerical models; however, these models cannot be rigorously tested for scenarios outside of the modern, without making use of past climate data. Furthermore, past climate data can inform our understanding of how the Earth system operates, and can provide important contextual information related to environmental change. All past time periods can be useful in this context; here, we focus on past climates that were warmer than the modern climate, as these are likely to be the most similar to the future. This introductory paper is not meant as a comprehensive overview of all work in this field. Instead, it gives an introduction to the important issues therein, using the papers in this Discussion Meeting Issue, and other works from all the Discussion Meeting speakers, as exemplars of the various ways in which past climates can inform projections of future climate. Furthermore, we present new work that uses a palaeo constraint to quantitatively inform projections of future equilibrium ice sheet change.
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A global scale mechanistic model of photosynthetic capacity (LUNA V1.0)
Ali, Ashehad A.; Xu, Chonggang; Rogers, Alistair; ...
2016-02-12
Although plant photosynthetic capacity as determined by the maximum carboxylation rate (i.e., V c,max25) and the maximum electron transport rate (i.e., J max25) at a reference temperature (generally 25 °C) is known to vary considerably in space and time in response to environmental conditions, it is typically parameterized in Earth system models (ESMs) with tabulated values associated with plant functional types. In this study, we have developed a mechanistic model of leaf utilization of nitrogen for assimilation (LUNA) to predict photosynthetic capacity at the global scale under different environmental conditions. We adopt an optimality hypothesis to nitrogen allocation among lightmore » capture, electron transport, carboxylation and respiration. The LUNA model is able to reasonably capture the measured spatial and temporal patterns of photosynthetic capacity as it explains ~55 % of the global variation in observed values of V c,max25 and ~65 % of the variation in the observed values of J max25. Model simulations with LUNA under current and future climate conditions demonstrate that modeled values of V c,max25 are most affected in high-latitude regions under future climates. In conclusion, ESMs that relate the values of V c,max25 or J max25 to plant functional types only are likely to substantially overestimate future global photosynthesis.« less
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Plant water potential improves prediction of empirical stomatal models.
Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen
2017-01-01
Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.
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The Response of Environmental Capacity for Malaria Transmission in West Africa to Climate Change
NASA Astrophysics Data System (ADS)
Yamana, T. K.; Eltahir, E. A.
2011-12-01
The climate of West Africa is characterized by north-south gradients in temperature and rainfall. Environmental capacity for malaria transmission (e.g. as measured by vectorial capacity) is strongly tied to these two variables; temperature affects the development rate of the malaria parasite, as well as the lifespan of the mosquitoes that transmit the disease, and rainfall is tied to mosquito abundance, as the vector lays its eggs in rain-fed water pools. A change in climate is therefore expected to lead to changes in the distribution of malaria transmission. Current general circulation models agree that the temperature in West Africa is expected to increase by several degrees in the next century. However they predict a wide range of possible rainfall scenarios in the future, from intense drying to significant increases in rainfall (Christensen et al., 2007). The effects these changes will have on environmental capacity for malaria transmission depend on the magnitude and direction of the changes, and on current conditions. For example, malaria transmission will be more sensitive to positive changes in rainfall in dry areas where mosquito populations are currently limited by water availability than in relatively wet areas. Here, we analyze combinations of changes in rainfall and temperature within the ranges predicted by GCMs, and assess the impact these combinations will have on the environmental capacity for malaria transmission. In particular, we identify climate change scenarios that are likely to have the greatest impact on environmental capacity for malaria transmission, as well as geographic "hot spots" where the greatest changes are to be expected. Christensen, J. H., Busuioc, A., & et al. (2007). Regional climate projections. In S. Solomon (Ed.), Climate change 2007: The physical science basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change.
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Winter, Matthew J; Owen, Stewart F; Murray-Smith, Richard; Panter, Grace H; Hetheridge, Malcolm J; Kinter, Lewis B
2010-01-01
Over recent years, human pharmaceuticals have been detected in the aquatic environment. This, combined with the fact that many are (by design) biologically active compounds, has raised concern about potential impacts in wildlife species. This concern was realized with two high-profile cases of unforeseen environmental impact (i.e., estrogens and diclofenac), which have led to a flurry of work addressing how best to predict such effects in the future. One area in which considerable research effort has been made, partially in response to regulatory requirements, has been on the potential use of preclinical and clinical pharmacological and toxicological data (generated during drug development from nonhuman mammals and humans) to predict possible effects in nontarget, environmentally relevant species: so-called read across. This approach is strengthened by the fact that many physiological systems are conserved between mammals and certain environmentally relevant species. Consequently, knowledge of how a pharmaceutical works (the “mode-of-action,” or MoA) in nonclinical species and humans could assist in the selection of appropriate test species, study designs, and endpoints, in an approach referred to as “intelligent testing.” Here we outline the data available from the human drug development process and suggest how this might be used to design a testing strategy best suited to the specific characteristics of the drug in question. In addition, we review published data that support this type of approach, discuss the potential pitfalls associated with read across, and identify knowledge gaps that require filling to ensure accuracy in the extrapolation of data from preclinical and clinical studies, for use in the environmental risk assessment of human pharmaceuticals.
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Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik
2017-10-01
Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
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Madronich, S; Shao, M; Wilson, S R; Solomon, K R; Longstreth, J D; Tang, X Y
2015-01-01
UV radiation is an essential driver for the formation of photochemical smog, which includes ground-level ozone and particulate matter (PM). Recent analyses support earlier work showing that poor outdoor air quality is a major environmental hazard as well as quantifying health effects on regional and global scales more accurately. Greater exposure to these pollutants has been linked to increased risks of cardiovascular and respiratory diseases in humans and is associated globally with several million premature deaths per year. Ozone also has adverse effects on yields of crops, leading to loss of billions of US dollars each year. These detrimental effects also may alter biological diversity and affect the function of natural ecosystems. Future air quality will depend mostly on changes in emission of pollutants and their precursors, but changes in UV radiation and climate will contribute as well. Significant reductions in emissions, mainly from the energy and transportation sectors, have already led to improved air quality in many locations. Air quality will continue to improve in those cities/states that can afford controls, and worsen where the regulatory infrastructure is not available. Future changes in UV radiation and climate will alter the rates of formation of ground-level ozone and photochemically-generated particulate matter and must be considered in predictions of air quality. The decrease in UV radiation associated with recovery of stratospheric ozone will, according to recent global atmospheric model simulations, lead to increases in ground-level ozone at most locations. If correct, this will add significantly to future ground-level ozone trends. However, the spatial resolution of these global models is insufficient to inform policy at this time, especially for urban areas. UV radiation affects the atmospheric concentration of hydroxyl radicals, ˙OH, which are responsible for the self-cleaning of the atmosphere. Recent measurements confirm that, on a local scale, ˙OH radicals respond rapidly to changes in UV radiation. However, on large (global) scales, models differ in their predictions by nearly a factor of two, with consequent uncertainties for estimating the atmospheric lifetime and concentrations of key greenhouse gases and air pollutants. Projections of future climate need to consider these uncertainties. No new negative environmental effects of substitutes for ozone depleting substances or their breakdown-products have been identified. However, some substitutes for the ozone depleting substances will continue to contribute to global climate change if concentrations rise above current levels.
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Hugo, Sanet; Van Rensburg, Berndt J.; Van Wyk, Abraham E.; Steenkamp, Yolande
2012-01-01
The distributions of naturalised alien plant species that have invaded natural or semi-natural habitat are often geographically restricted by the environmental conditions in their new range, implying that alien species with similar environmental requirements and tolerances may form assemblages and characterise particular areas. The aim of this study was to use objective numerical techniques to reveal any possible alien phytogeographic regions (i.e. geographic areas with characteristic alien plant assemblages) in southern Africa. Quarter degree resolution presence records of naturalised alien plant species of South Africa, Lesotho, Swaziland, Namibia and Botswana were analysed through a divisive hierarchical classification technique, and the output was plotted on maps for further interpretation. The analyses revealed two main alien phytogeographic regions that could be subdivided into eight lower level phytogeographic regions. Along with knowledge of the environmental requirements of the characteristic species and supported by further statistical analyses, we hypothesised on the main drivers of alien phytogeographic regions, and suggest that environmental features such as climate and associated biomes were most important, followed by human activities that modify climatic and vegetation features, such as irrigation and agriculture. Most of the characteristic species are not currently well-known as invasive plant species, but many may have potential to become troublesome in the future. Considering the possibility of biotic homogenization, these findings have implications for predicting the characteristics of the plant assemblages of the future. However, the relatively low quality of the dataset necessitates further more in-depth studies with improved data before the findings could be directly beneficial for management. PMID:22574145
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Berry, Meredith S; Nickerson, Norma P; Odum, Amy L
2017-09-01
Poor air quality and resulting annual deaths represent significant public health concerns. Recently, rapid delay discounting (the devaluation of future outcomes) of air quality has been considered a potential barrier for engaging in long term, sustainable behaviors that might help to reduce emissions (e.g., reducing private car use, societal support for clean air initiatives). Delay discounting has been shown to be predictive of real world behavior outside of laboratory settings, and therefore may offer an important framework beyond traditional variables thought to measure sustainable behavior such as importance of an environmental issue, or environmental attitudes/values, although more research is needed in this area. We examined relations between discounting of air quality, respiratory health, and monetary gains and losses. We also examined, relations between discounting and self-reported importance of air quality and respiratory health, and nature relatedness. Results showed rapid delay discounting of all outcomes across the time frames assessed, and significant positive correlations between delay discounting of air quality, respiratory health, and monetary outcomes. Steeper discounting of monetary outcomes relative to air quality and respiratory health outcomes was observed in the context of gains; however, no differences in discounting were observed across losses of monetary, air quality, and respiratory health. Replicating the sign effect, monetary outcomes were discounted more steeply than monetary losses. Importance of air quality, respiratory health and nature relatedness were significantly and positively correlated with one another, but not with degree of delay discounting of any outcome, demonstrating the need for more comprehensive measures that predict pro-environmental behaviors that might benefit individuals and public health over time. These results add to our understanding of decision-making, and demonstrate alarming rates of delay discounting of air quality and health. These results implicate a major public health concern and potential barriers to individual and societal behavior that reduce pollution and emissions for conservation of clean air.
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How to make a tree ring: Coupling stem water flow and cambial activity in mature Alpine conifers
NASA Astrophysics Data System (ADS)
Peters, Richard L.; Frank, David C.; Treydte, Kerstin; Steppe, Kathy; Kahmen, Ansgar; Fonti, Patrick
2017-04-01
Inter-annual tree-ring measurements are used to understand tree-growth responses to climatic variability and reconstruct past climate conditions. In parallel, mechanistic models use experimentally defined plant-atmosphere interactions to explain past growth responses and predict future environmental impact on forest productivity. Yet, substantial inconsistencies within mechanistic model ensembles and mismatches with empirical data indicate that significant progress is still needed to understand the processes occurring at an intra-annual resolution that drive annual growth. However, challenges arise due to i) few datasets describing climatic responses of high-resolution physiological processes over longer time-scales, ii) uncertainties on the main mechanistic process limiting radial stem growth and iii) complex interactions between multiple environmental factors which obscure detection of the main stem growth driver, generating a gap between our understanding of intra- and inter-annual growth mechanisms. We attempt to bridge the gap between inter-annual tree-ring width and sub-daily radial stem-growth and provide a mechanistic perspective on how environmental conditions affect physiological processes that shape tree rings in conifers. We combine sub-hourly sap flow and point dendrometer measurements performed on mature Alpine conifers (Larix decidua) into an individual-based mechanistic tree-growth model to simulate sub-hourly cambial activity. The monitored trees are located along a high elevational transect in the Swiss Alps (Lötschental) to analyse the effect of increasing temperature. The model quantifies internal tree hydraulic pathways that regulate the turgidity within the cambial zone and induce cell enlargement for radial growth. The simulations are validated against intra-annual growth patterns derived from xylogenesis data and anatomical analyses. Our efforts advance the process-based understanding of how climate shapes the annual tree-ring structures and could potentially improve our ability to reconstruct the climate of the past and predict future growth under changing climate.