Sample records for modelling environmental variation
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Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C
2008-03-01
The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.
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Environmental Variation Generates Environmental Opportunist Pathogen Outbreaks.
Anttila, Jani; Kaitala, Veijo; Laakso, Jouni; Ruokolainen, Lasse
2015-01-01
Many socio-economically important pathogens persist and grow in the outside host environment and opportunistically invade host individuals. The environmental growth and opportunistic nature of these pathogens has received only little attention in epidemiology. Environmental reservoirs are, however, an important source of novel diseases. Thus, attempts to control these diseases require different approaches than in traditional epidemiology focusing on obligatory parasites. Conditions in the outside-host environment are prone to fluctuate over time. This variation is a potentially important driver of epidemiological dynamics and affect the evolution of novel diseases. Using a modelling approach combining the traditional SIRS models to environmental opportunist pathogens and environmental variability, we show that epidemiological dynamics of opportunist diseases are profoundly driven by the quality of environmental variability, such as the long-term predictability and magnitude of fluctuations. When comparing periodic and stochastic environmental factors, for a given variance, stochastic variation is more likely to cause outbreaks than periodic variation. This is due to the extreme values being further away from the mean. Moreover, the effects of variability depend on the underlying biology of the epidemiological system, and which part of the system is being affected. Variation in host susceptibility leads to more severe pathogen outbreaks than variation in pathogen growth rate in the environment. Positive correlation in variation on both targets can cancel the effect of variation altogether. Moreover, the severity of outbreaks is significantly reduced by increase in the duration of immunity. Uncovering these issues helps in understanding and controlling diseases caused by environmental pathogens.
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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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Cassandra Y. Johnson; J. Michael Bowker; H. Ken Cordell
2004-01-01
We use national-level data to test a modified version of Stern, Dietz, & Guagnano's causal model of environmental belief and behavior. We focus on ethnic variation for four environmental behaviors: environmental reading, household recycling, environmental group joining, and participation in nature-based outdoor recreation. Blacks and foreign-born Latinos were...
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FIT: statistical modeling tool for transcriptome dynamics under fluctuating field conditions
Iwayama, Koji; Aisaka, Yuri; Kutsuna, Natsumaro
2017-01-01
Abstract Motivation: Considerable attention has been given to the quantification of environmental effects on organisms. In natural conditions, environmental factors are continuously changing in a complex manner. To reveal the effects of such environmental variations on organisms, transcriptome data in field environments have been collected and analyzed. Nagano et al. proposed a model that describes the relationship between transcriptomic variation and environmental conditions and demonstrated the capability to predict transcriptome variation in rice plants. However, the computational cost of parameter optimization has prevented its wide application. Results: We propose a new statistical model and efficient parameter optimization based on the previous study. We developed and released FIT, an R package that offers functions for parameter optimization and transcriptome prediction. The proposed method achieves comparable or better prediction performance within a shorter computational time than the previous method. The package will facilitate the study of the environmental effects on transcriptomic variation in field conditions. Availability and Implementation: Freely available from CRAN (https://cran.r-project.org/web/packages/FIT/). Contact: anagano@agr.ryukoku.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online PMID:28158396
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Nordey, Thibault; Léchaudel, Mathieu; Saudreau, Marc; Joas, Jacques; Génard, Michel
2014-01-01
Fruit physiology is strongly affected by both fruit temperature and water losses through transpiration. Fruit temperature and its transpiration vary with environmental factors and fruit characteristics. In line with previous studies, measurements of physical and thermal fruit properties were found to significantly vary between fruit tissues and maturity stages. To study the impact of these variations on fruit temperature and transpiration, a modelling approach was used. A physical model was developed to predict the spatial and temporal variations of fruit temperature and transpiration according to the spatial and temporal variations of environmental factors and thermal and physical fruit properties. Model predictions compared well to temperature measurements on mango fruits, making it possible to accurately simulate the daily temperature variations of the sunny and shaded sides of fruits. Model simulations indicated that fruit development induced an increase in both the temperature gradient within the fruit and fruit water losses, mainly due to fruit expansion. However, the evolution of fruit characteristics has only a very slight impact on the average temperature and the transpiration per surface unit. The importance of temperature and transpiration gradients highlighted in this study made it necessary to take spatial and temporal variations of environmental factors and fruit characteristics into account to model fruit physiology.
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Burghardt, Liana T; Metcalf, C Jessica E; Wilczek, Amity M; Schmitt, Johanna; Donohue, Kathleen
2015-02-01
Organisms develop through multiple life stages that differ in environmental tolerances. The seasonal timing, or phenology, of life-stage transitions determines the environmental conditions to which each life stage is exposed and the length of time required to complete a generation. Both environmental and genetic factors contribute to phenological variation, yet predicting their combined effect on life cycles across a geographic range remains a challenge. We linked submodels of the plasticity of individual life stages to create an integrated model that predicts life-cycle phenology in complex environments. We parameterized the model for Arabidopsis thaliana and simulated life cycles in four locations. We compared multiple "genotypes" by varying two parameters associated with natural genetic variation in phenology: seed dormancy and floral repression. The model predicted variation in life cycles across locations that qualitatively matches observed natural phenology. Seed dormancy had larger effects on life-cycle length than floral repression, and results suggest that a genetic cline in dormancy maintains a life-cycle length of 1 year across the geographic range of this species. By integrating across life stages, this approach demonstrates how genetic variation in one transition can influence subsequent transitions and the geographic distribution of life cycles more generally.
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Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster.
Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A; Maltecca, Christian; Mackay, Trudy F C
2015-05-06
Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon.
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Estimating linear temporal trends from aggregated environmental monitoring data
Erickson, Richard A.; Gray, Brian R.; Eager, Eric A.
2017-01-01
Trend estimates are often used as part of environmental monitoring programs. These trends inform managers (e.g., are desired species increasing or undesired species decreasing?). Data collected from environmental monitoring programs is often aggregated (i.e., averaged), which confounds sampling and process variation. State-space models allow sampling variation and process variations to be separated. We used simulated time-series to compare linear trend estimations from three state-space models, a simple linear regression model, and an auto-regressive model. We also compared the performance of these five models to estimate trends from a long term monitoring program. We specifically estimated trends for two species of fish and four species of aquatic vegetation from the Upper Mississippi River system. We found that the simple linear regression had the best performance of all the given models because it was best able to recover parameters and had consistent numerical convergence. Conversely, the simple linear regression did the worst job estimating populations in a given year. The state-space models did not estimate trends well, but estimated population sizes best when the models converged. We found that a simple linear regression performed better than more complex autoregression and state-space models when used to analyze aggregated environmental monitoring data.
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Contrasting patterns of fine-scale herb layer species composition in temperate forests
NASA Astrophysics Data System (ADS)
Chudomelová, Markéta; Zelený, David; Li, Ching-Feng
2017-04-01
Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.
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Widespread covariation of early environmental exposures and trait-associated polygenic variation.
Krapohl, E; Hannigan, L J; Pingault, J-B; Patel, H; Kadeva, N; Curtis, C; Breen, G; Newhouse, S J; Eley, T C; O'Reilly, P F; Plomin, R
2017-10-31
Although gene-environment correlation is recognized and investigated by family studies and recently by SNP-heritability studies, the possibility that genetic effects on traits capture environmental risk factors or protective factors has been neglected by polygenic prediction models. We investigated covariation between trait-associated polygenic variation identified by genome-wide association studies (GWASs) and specific environmental exposures, controlling for overall genetic relatedness using a genomic relatedness matrix restricted maximum-likelihood model. In a UK-representative sample ( n = 6,710), we find widespread covariation between offspring trait-associated polygenic variation and parental behavior and characteristics relevant to children's developmental outcomes-independently of population stratification. For instance, offspring genetic risk for schizophrenia was associated with paternal age ( R 2 = 0.002; P = 1e-04), and offspring education-associated variation was associated with variance in breastfeeding ( R 2 = 0.021; P = 7e-30), maternal smoking during pregnancy ( R 2 = 0.008; P = 5e-13), parental smacking ( R 2 = 0.01; P = 4e-15), household income ( R 2 = 0.032; P = 1e-22), watching television ( R 2 = 0.034; P = 5e-47), and maternal education ( R 2 = 0.065; P = 3e-96). Education-associated polygenic variation also captured covariation between environmental exposures and children's inattention/hyperactivity, conduct problems, and educational achievement. The finding that genetic variation identified by trait GWASs partially captures environmental risk factors or protective factors has direct implications for risk prediction models and the interpretation of GWAS findings.
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Gomez-Mestre, Ivan; Jovani, Roger
2013-11-22
An ongoing new synthesis in evolutionary theory is expanding our view of the sources of heritable variation beyond point mutations of fixed phenotypic effects to include environmentally sensitive changes in gene regulation. This expansion of the paradigm is necessary given ample evidence for a heritable ability to alter gene expression in response to environmental cues. In consequence, single genotypes are often capable of adaptively expressing different phenotypes in different environments, i.e. are adaptively plastic. We present an individual-based heuristic model to compare the adaptive dynamics of populations composed of plastic or non-plastic genotypes under a wide range of scenarios where we modify environmental variation, mutation rate and costs of plasticity. The model shows that adaptive plasticity contributes to the maintenance of genetic variation within populations, reduces bottlenecks when facing rapid environmental changes and confers an overall faster rate of adaptation. In fluctuating environments, plasticity is favoured by selection and maintained in the population. However, if the environment stabilizes and costs of plasticity are high, plasticity is reduced by selection, leading to genetic assimilation, which could result in species diversification. More broadly, our model shows that adaptive plasticity is a common consequence of selection under environmental heterogeneity, and hence a potentially common phenomenon in nature. Thus, taking adaptive plasticity into account substantially extends our view of adaptive evolution.
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Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits.
van Heerwaarden, Joost; van Zanten, Martijn; Kruijer, Willem
2015-10-01
Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation.
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Fitzpatrick, Matthew C.; Sanders, Nathan J.; Normand, Signe; Svenning, Jens-Christian; Ferrier, Simon; Gove, Aaron D.; Dunn, Robert R.
2013-01-01
A common approach for analysing geographical variation in biodiversity involves using linear models to determine the rate at which species similarity declines with geographical or environmental distance and comparing this rate among regions, taxa or communities. Implicit in this approach are weakly justified assumptions that the rate of species turnover remains constant along gradients and that this rate can therefore serve as a means to compare ecological systems. We use generalized dissimilarity modelling, a novel method that accommodates variation in rates of species turnover along gradients and between different gradients, to compare environmental and spatial controls on the floras of two regions with contrasting evolutionary and climatic histories: southwest Australia and northern Europe. We find stronger signals of climate history in the northern European flora and demonstrate that variation in rates of species turnover is persistent across regions, taxa and different gradients. Such variation may represent an important but often overlooked component of biodiversity that complicates comparisons of distance–decay relationships and underscores the importance of using methods that accommodate the curvilinear relationships expected when modelling beta diversity. Determining how rates of species turnover vary along and between gradients is relevant to understanding the sensitivity of ecological systems to environmental change. PMID:23926147
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The politics of environmental concern: A cross-national analysis*
Nawrotzki, Raphael J.
2016-01-01
Prior research in the U.S. has found that liberals are generally more environmentally concerned than conservatives. The present study explores whether conservatives’ opposition to environmental protection is solely a U.S. or a universal phenomenon and whether this association is contingent on country-level characteristics such as development, environmental conditions, and communist history. Employing data for 19 countries from the ISSP module “Environment II,” this paper explores inter-country variations in the relationship between individual conservatism and environmental concern using multilevel modeling with cross-level interactions. The models reveal a number of intriguing associations. Most important, conservatives’ support for environmental protection varies by country. This variation is a function of country-level characteristics. The strongest opposition of conservatives’ toward environmental protection was observed in developed, capitalist nations, with superior environmental conditions. On the other hand, in less developed countries, and countries characterized by poor environmental quality, conservatives are more environmentally concerned than liberals. PMID:27616877
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Genetic Architecture of Micro-Environmental Plasticity in Drosophila melanogaster
Morgante, Fabio; Sørensen, Peter; Sorensen, Daniel A.; Maltecca, Christian; Mackay, Trudy F. C.
2015-01-01
Individuals of the same genotype do not have the same phenotype for quantitative traits when reared under common macro-environmental conditions, a phenomenon called micro-environmental plasticity. Genetic variation in micro-environmental plasticity is assumed in models of the evolution of phenotypic variance, and is important in applied breeding and personalized medicine. Here, we quantified genetic variation for micro-environmental plasticity for three quantitative traits in the inbred, sequenced lines of the Drosophila melanogaster Genetic Reference Panel. We found substantial genetic variation for micro-environmental plasticity for all traits, with broad sense heritabilities of the same magnitude or greater than those of trait means. Micro-environmental plasticity is not correlated with residual segregating variation, is trait-specific, and has genetic correlations with trait means ranging from zero to near unity. We identified several candidate genes associated with micro-environmental plasticity of startle response, including Drosophila Hsp90, setting the stage for future genetic dissection of this phenomenon. PMID:25943032
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Owen-Smith, Norman
2011-07-01
1. There is a pressing need for population models that can reliably predict responses to changing environmental conditions and diagnose the causes of variation in abundance in space as well as through time. In this 'how to' article, it is outlined how standard population models can be modified to accommodate environmental variation in a heuristically conducive way. This approach is based on metaphysiological modelling concepts linking populations within food web contexts and underlying behaviour governing resource selection. Using population biomass as the currency, population changes can be considered at fine temporal scales taking into account seasonal variation. Density feedbacks are generated through the seasonal depression of resources even in the absence of interference competition. 2. Examples described include (i) metaphysiological modifications of Lotka-Volterra equations for coupled consumer-resource dynamics, accommodating seasonal variation in resource quality as well as availability, resource-dependent mortality and additive predation, (ii) spatial variation in habitat suitability evident from the population abundance attained, taking into account resource heterogeneity and consumer choice using empirical data, (iii) accommodating population structure through the variable sensitivity of life-history stages to resource deficiencies, affecting susceptibility to oscillatory dynamics and (iv) expansion of density-dependent equations to accommodate various biomass losses reducing population growth rate below its potential, including reductions in reproductive outputs. Supporting computational code and parameter values are provided. 3. The essential features of metaphysiological population models include (i) the biomass currency enabling within-year dynamics to be represented appropriately, (ii) distinguishing various processes reducing population growth below its potential, (iii) structural consistency in the representation of interacting populations and (iv) capacity to accommodate environmental variation in space as well as through time. Biomass dynamics provide a common currency linking behavioural, population and food web ecology. 4. Metaphysiological biomass loss accounting provides a conceptual framework more conducive for projecting and interpreting the population consequences of climatic shifts and human transformations of habitats than standard modelling approaches. © 2011 The Author. Journal of Animal Ecology © 2011 British Ecological Society.
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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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Genome-Wide Association Analysis of Adaptation Using Environmentally Predicted Traits
van Zanten, Martijn
2015-01-01
Current methods for studying the genetic basis of adaptation evaluate genetic associations with ecologically relevant traits or single environmental variables, under the implicit assumption that natural selection imposes correlations between phenotypes, environments and genotypes. In practice, observed trait and environmental data are manifestations of unknown selective forces and are only indirectly associated with adaptive genetic variation. In theory, improved estimation of these forces could enable more powerful detection of loci under selection. Here we present an approach in which we approximate adaptive variation by modeling phenotypes as a function of the environment and using the predicted trait in multivariate and univariate genome-wide association analysis (GWAS). Based on computer simulations and published flowering time data from the model plant Arabidopsis thaliana, we find that environmentally predicted traits lead to higher recovery of functional loci in multivariate GWAS and are more strongly correlated to allele frequencies at adaptive loci than individual environmental variables. Our results provide an example of the use of environmental data to obtain independent and meaningful information on adaptive genetic variation. PMID:26496492
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Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael
2015-11-26
Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.
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Spreading speeds for plant populations in landscapes with low environmental variation.
Gilbert, Mark A; Gaffney, Eamonn A; Bullock, James M; White, Steven M
2014-12-21
Characterising the spread of biological populations is crucial in responding to both biological invasions and the shifting of habitat under climate change. Spreading speeds can be studied through mathematical models such as the discrete-time integro-difference equation (IDE) framework. The usual approach in implementing IDE models has been to ignore spatial variation in the demographic and dispersal parameters and to assume that these are spatially homogeneous. On the other hand, real landscapes are rarely spatially uniform with environmental variation being very important in determining biological spread. This raises the question of under what circumstances spatial structure need not be modelled explicitly. Recent work has shown that spatial variation can be ignored for the specific case where the scale of landscape variation is much smaller than the spreading population׳s dispersal scale. We consider more general types of landscape, where the spatial scales of environmental variation are arbitrarily large, but the maximum change in environmental parameters is relatively small. We find that the difference between the wave-speeds of populations spreading in a spatially structured periodic landscape and its homogenisation is, in general, proportional to ϵ(2), where ϵ governs the degree of environmental variation. For stochastically generated landscapes we numerically demonstrate that the error decays faster than ϵ. In both cases, this means that for sufficiently small ϵ, the homogeneous approximation is better than might be expected. Hence, in many situations, the precise details of the landscape can be ignored in favour of spatially homogeneous parameters. This means that field ecologists can use the homogeneous IDE as a relatively simple modelling tool--in terms of both measuring parameter values and doing the modelling itself. However, as ϵ increases, this homogeneous approximation loses its accuracy. The change in wave-speed due to the extrinsic (landscape) variation can be positive or negative, which is in contrast to the reduction in wave-speed caused by intrinsic stochasticity. To deal with the loss of accuracy as ϵ increases, we formulate a second-order approximation to the wave-speed for periodic landscapes and compare both approximations against the results of numerical simulation and show that they are both accurate for the range of landscapes considered. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Feiner, Zachary S.; Bunnell, David B.; Hook, Tomas O.; Madenjian, Charles P.; Warner, David M.; Collingsworth, Paris D.
2015-01-01
Fish stock-recruitment dynamics may be difficult to elucidate because of nonstationary relationships resulting from shifting environmental conditions and fluctuations in important vital rates such as individual growth or maturation. The Great Lakes have experienced environmental stressors that may have changed population demographics and stock-recruitment relationships while causing the declines of several prey fish species, including rainbow smelt (Osmerus mordax). We investigated changes in the size and maturation of rainbow smelt in Lake Michigan and Lake Huron and recruitment dynamics of the Lake Michigan stock over the past four decades. Mean lengths and length-at-maturation of rainbow smelt generally declined over time in both lakes. To evaluate recruitment, we used both a Ricker model and a Kalman filter-random walk (KF-RW) model which incorporated nonstationarity in stock productivity by allowing the productivity term to vary over time. The KF-RW model explained nearly four times more variation in recruitment than the Ricker model, indicating the productivity of the Lake Michigan stock has increased. By accounting for this nonstationarity, we were able identify significant variations in stock productivity, evaluate its importance to rainbow smelt recruitment, and speculate on potential environmental causes for the shift. Our results suggest that investigating mechanisms driving nonstationary shifts in stock-recruit relationships can provide valuable insights into temporal variation in fish population dynamics.
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NASA Astrophysics Data System (ADS)
Jin, Seung-Seop; Jung, Hyung-Jo
2014-03-01
It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative study with conventional methods (i.e., fixed reference scheme) demonstrates the superior performance of the proposed method for structural damage detection.
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NASA Astrophysics Data System (ADS)
Thomas, Yoann; Mazurié, Joseph; Alunno-Bruscia, Marianne; Bacher, Cédric; Bouget, Jean-François; Gohin, Francis; Pouvreau, Stéphane; Struski, Caroline
2011-11-01
In order to assess the potential of various marine ecosystems for shellfish aquaculture and to evaluate their carrying capacities, there is a need to clarify the response of exploited species to environmental variations using robust ecophysiological models and available environmental data. For a large range of applications and comparison purposes, a non-specific approach based on 'generic' individual growth models offers many advantages. In this context, we simulated the response of blue mussel ( Mytilus edulis L.) to the spatio-temporal fluctuations of the environment in Mont Saint-Michel Bay (North Brittany) by forcing a generic growth model based on Dynamic Energy Budgets with satellite-derived environmental data (i.e. temperature and food). After a calibration step based on data from mussel growth surveys, the model was applied over nine years on a large area covering the entire bay. These simulations provide an evaluation of the spatio-temporal variability in mussel growth and also show the ability of the DEB model to integrate satellite-derived data and to predict spatial and temporal growth variability of mussels. Observed seasonal, inter-annual and spatial growth variations are well simulated. The large-scale application highlights the strong link between food and mussel growth. The methodology described in this study may be considered as a suitable approach to account for environmental effects (food and temperature variations) on physiological responses (growth and reproduction) of filter feeders in varying environments. Such physiological responses may then be useful for evaluating the suitability of coastal ecosystems for shellfish aquaculture.
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Whiteneck, Gale; Meade, Michelle A; Dijkers, Marcel; Tate, Denise G; Bushnik, Tamara; Forchheimer, Martin B
2004-11-01
To investigate environmental barriers reported by people with spinal cord injury (SCI), and to determine the relative impact of environmental barriers compared with demographic and injury characteristics and activity limitations in predicting variation in participation and life satisfaction. Cross-sectional, follow-up survey. Individuals rehabilitated at 16 federally designated Model Spinal Cord Injury Systems of care, now living in the community. People with SCI (N=2726) who completed routine follow-up research interviews between 2000 and 2002. Not applicable. The Craig Hospital Inventory of Environmental Factors-Short Form (CHIEF-SF), the Craig Handicap Assessment and Reporting Technique-Short Form, and the Satisfaction With Life Scale. The top 5 environmental barriers reported by subjects with SCI, in descending order of importance, were the natural environment, transportation, need for help in the home, availability of health care, and governmental policies. The CHIEF-SF subscales accounted for only 4% or less of the variation in participation; they accounted for 10% of the variation in life satisfaction. The inclusion of environmental factors in models of disability was supported, but were found to be more strongly related to life satisfaction than to societal participation.
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Shoults-Wilson, W. A.; Peterson, J.T.; Unrine, J.M.; Rickard, J.; Black, M.C.
2009-01-01
In the present study, specimens of the invasive clam, Corbicula fluminea, were collected above and below possible sources of potentially toxic trace elements (As, Cd, Cr, Cu, Hg, Pb, and Zn) in the Altamaha River system (Georgia, USA). Bioaccumulation of these elements was quantified, along with environmental (water and sediment) concentrations. Hierarchical linear models were used to account for variability in tissue concentrations related to environmental (site water chemistry and sediment characteristics) and individual (growth metrics) variables while identifying the strongest relations between these variables and trace element accumulation. The present study found significantly elevated concentrations of Cd, Cu, and Hg downstream of the outfall of kaolin-processing facilities, Zn downstream of a tire cording facility, and Cr downstream of both a nuclear power plant and a paper pulp mill. Models of the present study indicated that variation in trace element accumulation was linked to distance upstream from the estuary, dissolved oxygen, percentage of silt and clay in the sediment, elemental concentrations in sediment, shell length, and bivalve condition index. By explicitly modeling environmental variability, the Hierarchical linear modeling procedure allowed the identification of sites showing increased accumulation of trace elements that may have been caused by human activity. Hierarchical linear modeling is a useful tool for accounting for environmental and individual sources of variation in bioaccumulation studies. ?? 2009 SETAC.
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Estella Gilbert; James A. Powell; Jesse A. Logan; Barbara J. Bentz
2004-01-01
In all organisms, phenotypic variability is an evolutionary stipulation. Because the development of poikilothermic organisms depends directly on the temperature of their habitat, environmental variability is also an integral factor in models of their phenology. In this paper we present two existing phenology models, the distributed delay model and the Sharpe and...
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Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation
MANEL, STÉPHANIE; GUGERLI, FELIX; THUILLER, WILFRIED; ALVAREZ, NADIR; LEGENDRE, PIERRE; HOLDEREGGER, ROLF; GIELLY, LUDOVIC; TABERLET, PIERRE
2014-01-01
Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran’s eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps. PMID:22680783
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Pacheco-Villalobos, David; Hardtke, Christian S
2012-06-05
Root system architecture is a trait that displays considerable plasticity because of its sensitivity to environmental stimuli. Nevertheless, to a significant degree it is genetically constrained as suggested by surveys of its natural genetic variation. A few regulators of root system architecture have been isolated as quantitative trait loci through the natural variation approach in the dicotyledon model, Arabidopsis. This provides proof of principle that allelic variation for root system architecture traits exists, is genetically tractable, and might be exploited for crop breeding. Beyond Arabidopsis, Brachypodium could serve as both a credible and experimentally accessible model for root system architecture variation in monocotyledons, as suggested by first glimpses of the different root morphologies of Brachypodium accessions. Whether a direct knowledge transfer gained from molecular model system studies will work in practice remains unclear however, because of a lack of comprehensive understanding of root system physiology in the native context. For instance, apart from a few notable exceptions, the adaptive value of genetic variation in root system modulators is unknown. Future studies should thus aim at comprehensive characterization of the role of genetic players in root system architecture variation by taking into account the native environmental conditions, in particular soil characteristics.
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ERIC Educational Resources Information Center
Silberg, Judy L.; And Others
1994-01-01
Applied structural equation modeling to twin data to assess impact of genetic and environmental factors on children's behavioral and emotional functioning. Applied models to maternal ratings of behavior of 515 monozygotic and 749 dizygotic twin pairs. Importance of genetic, shared, and specific environmental factors for explaining variation was…
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NASA Astrophysics Data System (ADS)
Fayad, Ibrahim; Baghdadi, Nicolas; Guitet, Stéphane; Bailly, Jean-Stéphane; Hérault, Bruno; Gond, Valéry; El Hajj, Mahmoud; Tong Minh, Dinh Ho
2016-10-01
Mapping forest aboveground biomass (AGB) has become an important task, particularly for the reporting of carbon stocks and changes. AGB can be mapped using synthetic aperture radar data (SAR) or passive optical data. However, these data are insensitive to high AGB levels (>150 Mg/ha, and >300 Mg/ha for P-band), which are commonly found in tropical forests. Studies have mapped the rough variations in AGB by combining optical and environmental data at regional and global scales. Nevertheless, these maps cannot represent local variations in AGB in tropical forests. In this paper, we hypothesize that the problem of misrepresenting local variations in AGB and AGB estimation with good precision occurs because of both methodological limits (signal saturation or dilution bias) and a lack of adequate calibration data in this range of AGB values. We test this hypothesis by developing a calibrated regression model to predict variations in high AGB values (mean >300 Mg/ha) in French Guiana by a methodological approach for spatial extrapolation with data from the optical geoscience laser altimeter system (GLAS), forest inventories, radar, optics, and environmental variables for spatial inter- and extrapolation. Given their higher point count, GLAS data allow a wider coverage of AGB values. We find that the metrics from GLAS footprints are correlated with field AGB estimations (R2 = 0.54, RMSE = 48.3 Mg/ha) with no bias for high values. First, predictive models, including remote-sensing, environmental variables and spatial correlation functions, allow us to obtain ;wall-to-wall; AGB maps over French Guiana with an RMSE for the in situ AGB estimates of ∼50 Mg/ha and R2 = 0.66 at a 1-km grid size. We conclude that a calibrated regression model based on GLAS with dependent environmental data can produce good AGB predictions even for high AGB values if the calibration data fit the AGB range. We also demonstrate that small temporal and spatial mismatches between field data and GLAS footprints are not a problem for regional and global calibrated regression models because field data aim to predict large and deep tendencies in AGB variations from environmental gradients and do not aim to represent high but stochastic and temporally limited variations from forest dynamics. Thus, we advocate including a greater variety of data, even if less precise and shifted, to better represent high AGB values in global models and to improve the fitting of these models for high values.
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Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael
2015-01-01
Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814
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Random genetic drift, natural selection, and noise in human cranial evolution.
Roseman, Charles C
2016-08-01
This study assesses the extent to which relationships among groups complicate comparative studies of adaptation in recent human cranial variation and the extent to which departures from neutral additive models of evolution hinder the reconstruction of population relationships among groups using cranial morphology. Using a maximum likelihood evolutionary model fitting approach and a mixed population genomic and cranial data set, I evaluate the relative fits of several widely used models of human cranial evolution. Moreover, I compare the goodness of fit of models of cranial evolution constrained by genomic variation to test hypotheses about population specific departures from neutrality. Models from population genomics are much better fits to cranial variation than are traditional models from comparative human biology. There is not enough evolutionary information in the cranium to reconstruct much of recent human evolution but the influence of population history on cranial variation is strong enough to cause comparative studies of adaptation serious difficulties. Deviations from a model of random genetic drift along a tree-like population history show the importance of environmental effects, gene flow, and/or natural selection on human cranial variation. Moreover, there is a strong signal of the effect of natural selection or an environmental factor on a group of humans from Siberia. The evolution of the human cranium is complex and no one evolutionary process has prevailed at the expense of all others. A holistic unification of phenome, genome, and environmental context, gives us a strong point of purchase on these problems, which is unavailable to any one traditional approach alone. Am J Phys Anthropol 160:582-592, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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Towards a universal trait-based model of terrestrial primary production
NASA Astrophysics Data System (ADS)
Wang, H.; Prentice, I. C.; Cornwell, W.; Keenan, T. F.; Davis, T.; Wright, I. J.; Evans, B. J.; Peng, C.
2015-12-01
Systematic variations of plant traits along environmental gradients have been observed for decades. For example, the tendencies of leaf nitrogen per unit area to increase, and of the leaf-internal to ambient CO2 concentration ratio (ci:ca) to decrease, with aridity are well established. But ecosystem models typically represent trait variation based purely on empirical relationships, or on untested conjectures, or not at all. Neglect of quantitative trait variation and its adapative significance probably contributes to the persistent large uncertainties among models in predicting the response of the carbon cycle to environmental change. However, advances in ecological theory and the accumulation of extensive data sets during recent decades suggest that theoretically based and testable predictions of trait variation could be achieved. Based on well-established ecophysiological principles and consideration of the adaptive significance of traits, we propose universal relationships between photosynthetic traits (ci:ca, carbon fixation capacity, and the ratio of electron transport capacity to carbon fixation capacity) and primary environmental variables, which capture observed trait variations both within and between plant functional types. Moreover, incorporating these traits into the standard model of C3photosynthesis allows gross primary production (GPP) of natural vegetation to be predicted by a single equation with just two free parameters, which can be estimated from independent observations. The resulting model performs as well as much more complex models. Our results provide a fresh perspective with potentially high reward: the possibility of a deeper understanding of the relationships between plant traits and environment, simpler and more robust and reliable representation of land processes in Earth system models, and thus improved predictability for biosphere-atmosphere interactions and climate feedbacks.
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Comparing species interaction networks along environmental gradients.
Pellissier, Loïc; Albouy, Camille; Bascompte, Jordi; Farwig, Nina; Graham, Catherine; Loreau, Michel; Maglianesi, Maria Alejandra; Melián, Carlos J; Pitteloud, Camille; Roslin, Tomas; Rohr, Rudolf; Saavedra, Serguei; Thuiller, Wilfried; Woodward, Guy; Zimmermann, Niklaus E; Gravel, Dominique
2018-05-01
Knowledge of species composition and their interactions, in the form of interaction networks, is required to understand processes shaping their distribution over time and space. As such, comparing ecological networks along environmental gradients represents a promising new research avenue to understand the organization of life. Variation in the position and intensity of links within networks along environmental gradients may be driven by turnover in species composition, by variation in species abundances and by abiotic influences on species interactions. While investigating changes in species composition has a long tradition, so far only a limited number of studies have examined changes in species interactions between networks, often with differing approaches. Here, we review studies investigating variation in network structures along environmental gradients, highlighting how methodological decisions about standardization can influence their conclusions. Due to their complexity, variation among ecological networks is frequently studied using properties that summarize the distribution or topology of interactions such as number of links, connectance, or modularity. These properties can either be compared directly or using a procedure of standardization. While measures of network structure can be directly related to changes along environmental gradients, standardization is frequently used to facilitate interpretation of variation in network properties by controlling for some co-variables, or via null models. Null models allow comparing the deviation of empirical networks from random expectations and are expected to provide a more mechanistic understanding of the factors shaping ecological networks when they are coupled with functional traits. As an illustration, we compare approaches to quantify the role of trait matching in driving the structure of plant-hummingbird mutualistic networks, i.e. a direct comparison, standardized by null models and hypothesis-based metaweb. Overall, our analysis warns against a comparison of studies that rely on distinct forms of standardization, as they are likely to highlight different signals. Fostering a better understanding of the analytical tools available and the signal they detect will help produce deeper insights into how and why ecological networks vary along environmental gradients. © 2017 Cambridge Philosophical Society.
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Environmental Stochasticity and the Speed of Evolution
NASA Astrophysics Data System (ADS)
Danino, Matan; Kessler, David A.; Shnerb, Nadav M.
2018-03-01
Biological populations are subject to two types of noise: demographic stochasticity due to fluctuations in the reproductive success of individuals, and environmental variations that affect coherently the relative fitness of entire populations. The rate in which the average fitness of a community increases has been considered so far using models with pure demographic stochasticity; here we present some theoretical considerations and numerical results for the general case where environmental variations are taken into account. When the competition is pairwise, fitness fluctuations are shown to reduce the speed of evolution, while under global competition the speed increases due to environmental stochasticity.
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Environmental Stochasticity and the Speed of Evolution
NASA Astrophysics Data System (ADS)
Danino, Matan; Kessler, David A.; Shnerb, Nadav M.
2018-07-01
Biological populations are subject to two types of noise: demographic stochasticity due to fluctuations in the reproductive success of individuals, and environmental variations that affect coherently the relative fitness of entire populations. The rate in which the average fitness of a community increases has been considered so far using models with pure demographic stochasticity; here we present some theoretical considerations and numerical results for the general case where environmental variations are taken into account. When the competition is pairwise, fitness fluctuations are shown to reduce the speed of evolution, while under global competition the speed increases due to environmental stochasticity.
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Genetic and Environmental Influences on Behavior: Capturing All the Interplay
ERIC Educational Resources Information Center
Johnson, Wendy
2007-01-01
Basic quantitative genetic models of human behavioral variation have made clear that individual differences in behavior cannot be understood without acknowledging the importance of genetic influences. Yet these basic models estimate average, population-level genetic and environmental influences, obscuring differences that might exist within the…
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Cottrell, Gilles; Kouwaye, Bienvenue; Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André
2012-01-01
Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission--even at a very local scale--is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors.As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages.This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.
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Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André
2012-01-01
Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission—even at a very local scale—is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors. As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages. This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics. PMID:22238582
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NASA Astrophysics Data System (ADS)
Anderegg, L. D.; Berner, L. T.; Badgley, G.; Hillerislambers, J.; Law, B. E.
2017-12-01
Functional traits could facilitate ecological prediction by provide scale-free tools for modeling ecosystem function. Yet much of their utility lies in three key assumptions: 1) that global patterns of trait covariation are the result of universal trade-offs independent of taxonomic scale, so empirical trait-trait relationships can be used to constrain vegetation models 2) that traits respond predictably to environmental gradients and can therefore be reliably quantified to parameterize models and 3) that well sampled traits influence productivity. We use an extensive dataset of within-species leaf trait variation in North American conifers combined with global leaf trait datasets to test these assumptions. We examine traits central to the `leaf economics spectrum', and quantify patterns of trait variation at multiple taxonomic scales. We also test whether site environment explains geographic trait variation within conifers, and ask whether foliar traits explain geographic variation in relative growth rates. We find that most leaf traits vary primarily between rather than within species globally, but that a large fraction of within-PFT trait variation is within-species. We also find that some leaf economics spectrum relationships differ in sign within versus between species, particularly the relationship between leaf lifespan and LMA. In conifers, we find weak and inconsistent relationships between site environment and leaf traits, making it difficult capture within-species leaf trait variation for regional model parameterization. Finally, we find limited relationships between tree relative growth rate and any foliar trait other than leaf lifespan, with leaf traits jointly explaining 42% of within-species growth variation but environmental factors explaining 77% of variation. We suggest that additional traits, particularly whole plant allometry/allocation traits may be better than leaf traits for improving vegetation model performance at smaller taxonomic and spatial scales.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Jin; Guan, Kaiyu; Hayek, Matthew
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model wasmore » able to explain most of the variability in GEP at hourly (R 2 = 0.77) to interannual (R 2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). Lastly, this work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.« less
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Wu, Jin; Guan, Kaiyu; Hayek, Matthew; ...
2016-09-19
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model wasmore » able to explain most of the variability in GEP at hourly (R 2 = 0.77) to interannual (R 2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). Lastly, this work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms.« less
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Wu, Jin; Guan, Kaiyu; Hayek, Matthew; Restrepo-Coupe, Natalia; Wiedemann, Kenia T; Xu, Xiangtao; Wehr, Richard; Christoffersen, Bradley O; Miao, Guofang; da Silva, Rodrigo; de Araujo, Alessandro C; Oliviera, Raimundo C; Camargo, Plinio B; Monson, Russell K; Huete, Alfredo R; Saleska, Scott R
2017-03-01
Gross ecosystem productivity (GEP) in tropical forests varies both with the environment and with biotic changes in photosynthetic infrastructure, but our understanding of the relative effects of these factors across timescales is limited. Here, we used a statistical model to partition the variability of seven years of eddy covariance-derived GEP in a central Amazon evergreen forest into two main causes: variation in environmental drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with model parameters that govern photosynthesis and biotic variation in canopy photosynthetic light-use efficiency associated with changes in the parameters themselves. Our fitted model was able to explain most of the variability in GEP at hourly (R 2 = 0.77) to interannual (R 2 = 0.80) timescales. At hourly timescales, we found that 75% of observed GEP variability could be attributed to environmental variability. When aggregating GEP to the longer timescales (daily, monthly, and yearly), however, environmental variation explained progressively less GEP variability: At monthly timescales, it explained only 3%, much less than biotic variation in canopy photosynthetic light-use efficiency, which accounted for 63%. These results challenge modeling approaches that assume GEP is primarily controlled by the environment at both short and long timescales. Our approach distinguishing biotic from environmental variability can help to resolve debates about environmental limitations to tropical forest photosynthesis. For example, we found that biotically regulated canopy photosynthetic light-use efficiency (associated with leaf phenology) increased with sunlight during dry seasons (consistent with light but not water limitation of canopy development) but that realized GEP was nonetheless lower relative to its potential efficiency during dry than wet seasons (consistent with water limitation of photosynthesis in given assemblages of leaves). This work highlights the importance of accounting for differential regulation of GEP at different timescales and of identifying the underlying feedbacks and adaptive mechanisms. © 2016 John Wiley & Sons Ltd.
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Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Michael D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot
2006-01-01
The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...
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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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Mulder, Han A; Rönnegård, Lars; Fikse, W Freddy; Veerkamp, Roel F; Strandberg, Erling
2013-07-04
Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike's information criterion using h-likelihood to select the best fitting model. We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike's information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike's information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.
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A Drosophila model for toxicogenomics: Genetic variation in susceptibility to heavy metal exposure
Luoma, Sarah E.; St. Armour, Genevieve E.; Thakkar, Esha
2017-01-01
The genetic factors that give rise to variation in susceptibility to environmental toxins remain largely unexplored. Studies on genetic variation in susceptibility to environmental toxins are challenging in human populations, due to the variety of clinical symptoms and difficulty in determining which symptoms causally result from toxic exposure; uncontrolled environments, often with exposure to multiple toxicants; and difficulty in relating phenotypic effect size to toxic dose, especially when symptoms become manifest with a substantial time lag. Drosophila melanogaster is a powerful model that enables genome-wide studies for the identification of allelic variants that contribute to variation in susceptibility to environmental toxins, since the genetic background, environmental rearing conditions and toxic exposure can be precisely controlled. Here, we used extreme QTL mapping in an outbred population derived from the D. melanogaster Genetic Reference Panel to identify alleles associated with resistance to lead and/or cadmium, two ubiquitous environmental toxins that present serious health risks. We identified single nucleotide polymorphisms (SNPs) associated with variation in resistance to both heavy metals as well as SNPs associated with resistance specific to each of them. The effects of these SNPs were largely sex-specific. We applied mutational and RNAi analyses to 33 candidate genes and functionally validated 28 of them. We constructed networks of candidate genes as blueprints for orthologous networks of human genes. The latter not only provided functional contexts for known human targets of heavy metal toxicity, but also implicated novel candidate susceptibility genes. These studies validate Drosophila as a translational toxicogenomics gene discovery system. PMID:28732062
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Sparse modeling of spatial environmental variables associated with asthma
Chang, Timothy S.; Gangnon, Ronald E.; Page, C. David; Buckingham, William R.; Tandias, Aman; Cowan, Kelly J.; Tomasallo, Carrie D.; Arndt, Brian G.; Hanrahan, Lawrence P.; Guilbert, Theresa W.
2014-01-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin’s Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5–50 years over a three-year period. Each patient’s home address was geocoded to one of 3,456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin’s geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. PMID:25533437
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Sparse modeling of spatial environmental variables associated with asthma.
Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W
2015-02-01
Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.
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Linking body mass and group dynamics in an obligate cooperative breeder.
Ozgul, Arpat; Bateman, Andrew W; English, Sinead; Coulson, Tim; Clutton-Brock, Tim H
2014-11-01
Social and environmental factors influence key life-history processes and population dynamics by affecting fitness-related phenotypic traits such as body mass. The role of body mass is particularly pronounced in cooperative breeders due to variation in social status and consequent variation in access to resources. Investigating the mechanisms underlying variation in body mass and its demographic consequences can help elucidate how social and environmental factors affect the dynamics of cooperatively breeding populations. In this study, we present an analysis of the effect of individual variation in body mass on the temporal dynamics of group size and structure of a cooperatively breeding mongoose, the Kalahari meerkat, Suricata suricatta. First, we investigate how body mass interacts with social (dominance status and number of helpers) and environmental (rainfall and season) factors to influence key life-history processes (survival, growth, emigration and reproduction) in female meerkats. Next, using an individual-based population model, we show that the models explicitly including individual variation in body mass predict group dynamics better than those ignoring this morphological trait. Body mass influences group dynamics mainly through its effects on helper emigration and dominant reproduction. Rainfall has a trait-mediated, destabilizing effect on group dynamics, whereas the number of helpers has a direct and stabilizing effect. Counteracting effects of number of helpers on different demographic rates, despite generating temporal fluctuations, stabilizes group dynamics in the long term. Our study demonstrates that social and environmental factors interact to produce individual variation in body mass and accounting for this variation helps to explain group dynamics in this cooperatively breeding population. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.
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Selection of trilateral continuums of life history strategies under food web interactions.
Fujiwara, Masami
2018-03-14
The study of life history strategies has a long history in ecology and evolution, but determining the underlying mechanisms driving the evolution of life history variation and its consequences for population regulation remains a major challenge. In this study, a food web model with constant environmental conditions was used to demonstrate how multi-species consumer-resource interactions (food-web interactions) can create variation in the duration of the adult stage, age of maturation, and fecundity among species. The model included three key ecological processes: size-dependent species interactions, energetics, and transition among developmental stages. Resultant patterns of life history variation were consistent with previous empirical observations of the life history strategies of aquatic organisms referred to as periodic, equilibrium, and opportunistic strategies (trilateral continuums of life history strategies). Results from the simulation model suggest that these three life history strategies can emerge from food web interactions even when abiotic environmental conditions are held constant.
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Hauck, Mara; Huijbregts, Mark A J; Hollander, Anne; Hendriks, A Jan; van de Meent, Dik
2010-08-15
We evaluated various modeling options for estimating concentrations of PCB-153 in the environment and in biota across Europe, using a nested multimedia fate model coupled with a bioaccumulation model. The most detailed model set up estimates concentrations in air, soil, fresh water sediment and fresh water biota with spatially explicit environmental characteristics and spatially explicit emissions to air and water in the period 1930-2005. Model performance was evaluated with the root mean square error (RMSE(log)), based on the difference between estimated and measured concentrations. The RMSE(log) was 5.4 for air, 5.6-6.3 for sediment and biota, and 5.5 for soil in the most detailed model scenario. Generally, model estimations tended to underestimate observed values for all compartments, except air. The decline in observed concentrations was also slightly underestimated by the model for the period where measurements were available (1989-2002). Applying a generic model setup with averaged emissions and averaged environmental characteristics, the RMSE(log) increased to 21 for air and 49 for sediment. For soil the RMSE(log) decreased to 3.5. We found that including spatial variation in emissions was most relevant for all compartments, except soil, while including spatial variation in environmental characteristics was less influential. For improving predictions of concentrations in sediment and aquatic biota, including emissions to water was found to be relevant as well. Copyright 2009 Elsevier B.V. All rights reserved.
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Leibold, Mathew A; Loeuille, Nicolas
2015-12-01
Metacommunity theory indicates that variation in local community structure can be partitioned into components including those related to local environmental conditions vs. spatial effects and that these can be quantified using statistical methods based on variation partitioning. It has been hypothesized that joint associations of community composition with environment and space could be due to patch dynamics involving colonization-extinction processes in environmentally heterogeneous landscapes but this has yet to be theoretically shown. We develop a two-patch, type-two, species competition model in such a "harlequin" landscape (where different patches have different environments) to evaluate how composition is related to environmental and spatial effects as a function of background extinction rate. Using spatially implicit analytical models, we find that the environmental association of community composition declines with extinction rate as expected. Using spatially explicit simulation models, we further find that there is an increase in the spatial structure with extinction due to spatial patterning into clusters that are not related to environmental conditions but that this increase is limited. Natural metacommunities often show both environment and spatial determination even under conditions of relatively high isolation and these could be more easily explained by our model than alternative metacommunity models.
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Vandegehuchte, Maurits W; Guyot, Adrien; Hubeau, Michiel; De Swaef, Tom; Lockington, David A; Steppe, Kathy
2014-09-01
Stem diameter variations are mainly determined by the radial water transport between xylem and storage tissues. This radial transport results from the water potential difference between these tissues, which is influenced by both hydraulic and carbon related processes. Measurements have shown that when subjected to the same environmental conditions, the co-occurring mangrove species Avicennia marina and Rhizophora stylosa unexpectedly show a totally different pattern in daily stem diameter variation. Using in situ measurements of stem diameter variation, stem water potential and sap flow, a mechanistic flow and storage model based on the cohesion-tension theory was applied to assess the differences in osmotic storage water potential between Avicennia marina and Rhizophora stylosa. Both species, subjected to the same environmental conditions, showed a resembling daily pattern in simulated osmotic storage water potential. However, the osmotic storage water potential of R. stylosa started to decrease slightly after that of A. marina in the morning and increased again slightly later in the evening. This small shift in osmotic storage water potential likely underlaid the marked differences in daily stem diameter variation pattern between the two species. The results show that in addition to environmental dynamics, endogenous changes in the osmotic storage water potential must be taken into account in order to accurately predict stem diameter variations, and hence growth.
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Engen, Steinar; Saether, Bernt-Erik
2014-03-01
We analyze the stochastic components of the Robertson-Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
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DOT National Transportation Integrated Search
2007-08-01
This research outlines three major challenges of incorporating Environmental Justice (EJ) into metropolitan transportation planning and proposes a new variation of the user equilibrium discrete network design problem (UEDNDP) for achieving EJ amongst...
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Environmental Variables Explain Genetic Structure in a Beetle-Associated Nematode
McGaughran, Angela; Morgan, Katy; Sommer, Ralf J.
2014-01-01
The distribution of a species is a complex expression of its ecological and evolutionary history and integrating population genetic, environmental, and ecological data can provide new insights into the effects of the environment on the population structure of species. Previous work demonstrated strong patterns of genetic differentiation in natural populations of the hermaphroditic nematode Pristionchus pacificus in its La Réunion Island habitat, but gave no clear understanding of the role of the environment in structuring this variation. Here, we present what is to our knowledge the first study to statistically evaluate the role of the environment in shaping the structure and distribution of nematode populations. We test the hypothesis that genetic structure in P. pacificus is influenced by environmental variables, by combining population genetic analyses of microsatellite data from 18 populations and 370 strains, with multivariate statistics on environmental data, and species distribution modelling. We assess and quantify the relative importance of environmental factors (geographic distance, altitude, temperature, precipitation, and beetle host) on genetic variation among populations. Despite the fact that geographic populations of P. pacificus comprise vast genetic diversity sourced from multiple ancestral lineages, we find strong evidence for local associations between environment and genetic variation. Further, we show that significantly more genetic variation in P. pacificus populations is explained by environmental variation than by geographic distances. This supports a strong role for environmental heterogeneity vs. genetic drift in the divergence of populations, which we suggest may be influenced by adaptive forces. PMID:24498073
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Jacobson, K C; Rowe, D C
1999-07-01
This study investigated (a) genetic and environmental contributions to the relationship between family and school environment and depressed mood and (b) potential sex differences in genetic and environmental contributions to both variation in and covariation between family connectedness, school connectedness, and adolescent depressed mood. Data are from 2,302 adolescent sibling pairs (mean age = 16 years) who were part of the National Longitudinal Study of Adolescent Health. Although genetic factors appeared to be important overall, model-fitting analyses revealed that the best-fitting model was a model that allowed for different parameters for male and female adolescents. Genetic contributions to variation in all 3 variables were greater among female adolescents than male adolescents, especially for depressed mood. Genetic factors also contributed to the correlations between family and school environment and adolescent depressed mood, although, again, these factors were stronger for female than for male adolescents.
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Manhard, Christopher V.; Som, Nicholas A.; Perry, Russell W.; Faukner, Jimmy; Soto, Toz
2018-01-01
An area of great importance to resource management and conservation biology in the Klamath Basin is balancing water usage against the life history requirements of threatened Coho Salmon. One tool for addressing this topic is a freshwater dynamics model to forecast Coho Salmon productivity based on environmental inputs. Constructing such a forecasting tool requires local data to quantify the unique life history processes of Coho Salmon inhabiting this region. Here, we describe analytical methods for estimating a series of sub-models, each capturing a different life history process, which will eventually be synchronized as part of a freshwater dynamics model for Klamath River Coho Salmon. Specifically, we draw upon extensive population monitoring data collected in the basin to estimate models of freshwater productivity, overwinter survival, and migration patterns. Our models of freshwater productivity indicated that high summer temperatures and high winter flows can both adversely affect smolt production and that such relationships are more likely in tributaries with naturally regulated flows due to substantial intraannual environmental variation. Our models of overwinter survival demonstrated extensive variability in survival among years, but not among rearing locations, and demonstrated that a substantial proportion (~ 20%) of age-0+ fish emigrate from some rearing sites in the winter. Our models of migration patterns indicated that many age-0+ fish redistribute in the basin during the summer and winter. Further, we observed that these redistributions can entail long migrations in the mainstem where environmental stressors likely play a role in cueing refuge entry. Finally, our models of migration patterns indicated that changes in discharge are important in cueing the seaward migration of smolts, but that the nature of this behavioral response can differ dramatically between tributaries with naturally and artificially regulated flows. Collectively, these analyses demonstrate that environmental variation interacts with most phases of the freshwater life history of Klamath River Coho Salmon and that anthropogenic environmental variation can have a particularly large bearing on productivity.
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Warner, Daniel A
2014-11-01
Environmental factors strongly influence phenotypic variation within populations. The environment contributes to this variation in two ways: (1) by acting as a determinant of phenotypic variation (i.e., plastic responses) and (2) as an agent of selection that "chooses" among existing phenotypes. Understanding how these two environmental forces contribute to phenotypic variation is a major goal in the field of evolutionary biology and a primary objective of my research program. The objective of this article is to provide a framework to guide studies of environmental sources of phenotypic variation (specifically, developmental plasticity and maternal effects, and their adaptive significance). Two case studies from my research on reptiles are used to illustrate the general approaches I have taken to address these conceptual topics. Some key points for advancing our understanding of environmental influences on phenotypic variation include (1) merging laboratory-based research that identifies specific environmental effects with field studies to validate ecological relevance; (2) using controlled experimental approaches that mimic complex environments found in nature; (3) integrating data across biological fields (e.g., genetics, morphology, physiology, behavior, and ecology) under an evolutionary framework to provide novel insights into the underlying mechanisms that generate phenotypic variation; (4) assessing fitness consequences using measurements of survival and/or reproductive success across ontogeny (from embryos to adults) and under multiple ecologically-meaningful contexts; and (5) quantifying the strength and form of natural selection in multiple populations over multiple periods of time to understand the spatial and temporal consistency of phenotypic selection. Research programs that focus on organisms that are amenable to these approaches will provide the most promise for advancing our understanding of the environmental factors that generate the remarkable phenotypic diversity observed within populations. © The Author 2014. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.
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Al-Ghamdi, Sami G; Bilec, Melissa M
2015-04-07
This research investigates the relationship between energy use, geographic location, life cycle environmental impacts, and Leadership in Energy and Environmental Design (LEED). The researchers studied worldwide variations in building energy use and associated life cycle impacts in relation to the LEED rating systems. A Building Information Modeling (BIM) of a reference 43,000 ft(2) office building was developed and situated in 400 locations worldwide while making relevant changes to the energy model to meet reference codes, such as ASHRAE 90.1. Then life cycle environmental and human health impacts from the buildings' energy consumption were calculated. The results revealed considerable variations between sites in the U.S. and international locations (ranging from 394 ton CO2 equiv to 911 ton CO2 equiv, respectively). The variations indicate that location specific results, when paired with life cycle assessment, can be an effective means to achieve a better understanding of possible adverse environmental impacts as a result of building energy consumption in the context of green building rating systems. Looking at these factors in combination and using a systems approach may allow rating systems like LEED to continue to drive market transformation toward sustainable development, while taking into consideration both energy sources and building efficiency.
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Environmental and community controls on plant canopy chemistry in a Mediterranean-type ecosystem.
Dahlin, Kyla M; Asner, Gregory P; Field, Christopher B
2013-04-23
Understanding how and why plant communities vary across space has long been a goal of ecology, yet parsing the relative importance of different influences has remained a challenge. Species-specific models are not generalizable, whereas broad plant functional type models lack important detail. Here we consider plant trait patterns at the local scale and ask whether plant chemical traits are more closely linked to environmental gradients or to changes in species composition. We used the visible-to-shortwave infrared (VSWIR) spectrometer of the Carnegie Airborne Observatory to develop maps of four plant chemical traits--leaf nitrogen per mass, leaf carbon per mass, leaf water concentration, and canopy water content--across a diverse Mediterranean-type ecosystem (Jasper Ridge Biological Preserve, CA). For all four traits, plant community alone was the strongest predictor of trait variation (explaining 46-61% of the heterogeneity), whereas environmental gradients accounted for just one fourth of the variation in the traits. This result emphasizes the critical role that species composition plays in mediating nutrient and carbon cycling within and among different communities. Environmental filtering and limits to similarity can act strongly, simultaneously, in a spatially heterogeneous environment, but the local-scale environmental gradients alone cannot account for the variation across this landscape.
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Mapping evolutionary process: a multi-taxa approach to conservation prioritization
Thomassen, Henri A; Fuller, Trevon; Buermann, Wolfgang; Milá, Borja; Kieswetter, Charles M; Jarrín-V, Pablo; Cameron, Susan E; Mason, Eliza; Schweizer, Rena; Schlunegger, Jasmin; Chan, Janice; Wang, Ophelia; Peralvo, Manuel; Schneider, Christopher J; Graham, Catherine H; Pollinger, John P; Saatchi, Sassan; Wayne, Robert K; Smith, Thomas B
2011-01-01
Human-induced land use changes are causing extensive habitat fragmentation. As a result, many species are not able to shift their ranges in response to climate change and will likely need to adapt in situ to changing climate conditions. Consequently, a prudent strategy to maintain the ability of populations to adapt is to focus conservation efforts on areas where levels of intraspecific variation are high. By doing so, the potential for an evolutionary response to environmental change is maximized. Here, we use modeling approaches in conjunction with environmental variables to model species distributions and patterns of genetic and morphological variation in seven Ecuadorian amphibian, bird, and mammal species. We then used reserve selection software to prioritize areas for conservation based on intraspecific variation or species-level diversity. Reserves selected using species richness and complementarity showed little overlap with those based on genetic and morphological variation. Priority areas for intraspecific variation were mainly located along the slopes of the Andes and were largely concordant among species, but were not well represented in existing reserves. Our results imply that in order to maximize representation of intraspecific variation in reserves, genetic and morphological variation should be included in conservation prioritization. PMID:25567981
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Mapping evolutionary process: a multi-taxa approach to conservation prioritization.
Thomassen, Henri A; Fuller, Trevon; Buermann, Wolfgang; Milá, Borja; Kieswetter, Charles M; Jarrín-V, Pablo; Cameron, Susan E; Mason, Eliza; Schweizer, Rena; Schlunegger, Jasmin; Chan, Janice; Wang, Ophelia; Peralvo, Manuel; Schneider, Christopher J; Graham, Catherine H; Pollinger, John P; Saatchi, Sassan; Wayne, Robert K; Smith, Thomas B
2011-03-01
Human-induced land use changes are causing extensive habitat fragmentation. As a result, many species are not able to shift their ranges in response to climate change and will likely need to adapt in situ to changing climate conditions. Consequently, a prudent strategy to maintain the ability of populations to adapt is to focus conservation efforts on areas where levels of intraspecific variation are high. By doing so, the potential for an evolutionary response to environmental change is maximized. Here, we use modeling approaches in conjunction with environmental variables to model species distributions and patterns of genetic and morphological variation in seven Ecuadorian amphibian, bird, and mammal species. We then used reserve selection software to prioritize areas for conservation based on intraspecific variation or species-level diversity. Reserves selected using species richness and complementarity showed little overlap with those based on genetic and morphological variation. Priority areas for intraspecific variation were mainly located along the slopes of the Andes and were largely concordant among species, but were not well represented in existing reserves. Our results imply that in order to maximize representation of intraspecific variation in reserves, genetic and morphological variation should be included in conservation prioritization.
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Lotka-Volterra system in a random environment.
Dimentberg, Mikhail F
2002-03-01
Classical Lotka-Volterra (LV) model for oscillatory behavior of population sizes of two interacting species (predator-prey or parasite-host pairs) is conservative. This may imply unrealistically high sensitivity of the system's behavior to environmental variations. Thus, a generalized LV model is considered with the equation for preys' reproduction containing the following additional terms: quadratic "damping" term that accounts for interspecies competition, and term with white-noise random variations of the preys' reproduction factor that simulates the environmental variations. An exact solution is obtained for the corresponding Fokker-Planck-Kolmogorov equation for stationary probability densities (PDF's) of the population sizes. It shows that both population sizes are independent gamma-distributed stationary random processes. Increasing level of the environmental variations does not lead to extinction of the populations. However it may lead to an intermittent behavior, whereby one or both population sizes experience very rare and violent short pulses or outbreaks while remaining on a very low level most of the time. This intermittency is described analytically by direct use of the solutions for the PDF's as well as by applying theory of excursions of random functions and by predicting PDF of peaks in the predators' population size.
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Lotka-Volterra system in a random environment
NASA Astrophysics Data System (ADS)
Dimentberg, Mikhail F.
2002-03-01
Classical Lotka-Volterra (LV) model for oscillatory behavior of population sizes of two interacting species (predator-prey or parasite-host pairs) is conservative. This may imply unrealistically high sensitivity of the system's behavior to environmental variations. Thus, a generalized LV model is considered with the equation for preys' reproduction containing the following additional terms: quadratic ``damping'' term that accounts for interspecies competition, and term with white-noise random variations of the preys' reproduction factor that simulates the environmental variations. An exact solution is obtained for the corresponding Fokker-Planck-Kolmogorov equation for stationary probability densities (PDF's) of the population sizes. It shows that both population sizes are independent γ-distributed stationary random processes. Increasing level of the environmental variations does not lead to extinction of the populations. However it may lead to an intermittent behavior, whereby one or both population sizes experience very rare and violent short pulses or outbreaks while remaining on a very low level most of the time. This intermittency is described analytically by direct use of the solutions for the PDF's as well as by applying theory of excursions of random functions and by predicting PDF of peaks in the predators' population size.
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2012-08-15
Environmental Model ( GDEM ) 72 levels) was conserved in the interpolated profiles and small variations in the vertical field may have lead to large...Planner ETKF Ensemble Transform Kalman Filter G8NCOM 1/8⁰ Global NCOM GA Genetic Algorithm GDEM Generalized Digital Environmental Model GOST
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Smart Climatology Applications for Undersea Warfare
2008-09-01
Comparisons of these climatologies with existing Navy climatologies based on the Generalized Digital Environmental Model ( GDEM ) reveal differences in sonic...undersea warfare. 15. NUMBER OF PAGES 117 14. SUBJECT TERMS antisubmarine warfare, climate variations, climatology, GDEM , ocean, re...climatologies based on the Generalized Digital Environmental Model ( GDEM ) to our smart ocean climatologies reveal a number of differences. The
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Background/Question/Methods Many environmental factors influence human mortality simultaneously. However, assessing their cumulative effects remains a challenging task. In this study we used the Environmental Quality Index (EQI), developed by the U.S. EPA, as a measure of overall...
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Genetic and Environmental Influences on Depressive Symptoms in Chinese Adolescents
Chen, Jie; Li, Xinying; Natsuaki, Misaki N.; Leve, Leslie D.; Harold, Gordon T.
2016-01-01
Adolescent depression is common and has become a major public health concern in China, yet little research has examined the etiology of depression in Chinese adolescents. In the present study, genetic and environmental influences on Chinese adolescent depressive symptoms were investigated in 1181 twin pairs residing in Beijing, China (ages 11 to 19 years). Child- and parent-versions of the Children’s Depression Inventory (CDI) were used to measure adolescents’ depressive symptoms. For self-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 50%, 5%, and 45% of the variation in depressive symptoms, respectively; for parent-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 51%, 18%, and 31% of the variation, respectively. These estimates are generally consistent with previous findings in Western adolescents, supporting the cross-cultural generalizability of etiological model of adolescent depression. Neither qualitative nor quantitative sex differences were found in the etiological model. Future studies are needed to investigate how genes and environments work together (gene-environment interaction, gene-environment correlation) to influence depression in Chinese adolescents. PMID:24311200
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Genetic and environmental influences on depressive symptoms in Chinese adolescents.
Chen, Jie; Li, Xinying; Natsuaki, Misaki N; Leve, Leslie D; Harold, Gordon T
2014-01-01
Adolescent depression is common and has become a major public health concern in China, yet little research has examined the etiology of depression in Chinese adolescents. In the present study, genetic and environmental influences on Chinese adolescent depressive symptoms were investigated in 1,181 twin pairs residing in Beijing, China (ages 11-19 years). Child- and parent-versions of the children's depression inventory were used to measure adolescents' depressive symptoms. For self-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 50, 5, and 45 % of the variation in depressive symptoms, respectively; for parent-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 51, 18, and 31 % of the variation, respectively. These estimates are generally consistent with previous findings in Western adolescents, supporting the cross-cultural generalizability of etiological model of adolescent depression. Neither qualitative nor quantitative sex differences were found in the etiological model. Future studies are needed to investigate how genes and environments work together (gene-environment interaction, gene-environment correlation) to influence depression in Chinese adolescents.
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Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Mike D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot
2006-01-01
The purpose of this study was to compare the sensitivity of nlodelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...
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Katapally, Tarun Reddy; Rainham, Daniel; Muhajarine, Nazeem
2016-01-01
With emerging evidence indicating that independent of physical activity, sedentary behaviour (SB) can be detrimental to health, researchers are increasingly aiming to understand the influence of multiple contexts such as urban design and built environment on SB. However, weather variation, a factor that continuously interacts with all other environmental variables, has been consistently underexplored. This study investigated the influence of diverse environmental exposures (including weather variation, urban design and built environment) on SB in children. This cross-sectional observational study is part of an active living research initiative set in the Canadian prairie city of Saskatoon. Saskatoon's neighbourhoods were classified based on urban street design into grid-pattern, fractured grid-pattern and curvilinear types of neighbourhoods. Diverse environmental exposures were measured including, neighbourhood built environment, and neighbourhood and household socioeconomic environment. Actical accelerometers were deployed between April and June 2010 (spring-summer) to derive SB of 331 10-14 year old children in 25 one week cycles. Each cycle of accelerometry was conducted on a different cohort of children within the total sample. Accelerometer data were matched with localized weather patterns derived from Environment Canada weather data. Multilevel modeling using Hierarchical Linear and Non-linear Modeling software was conducted by factoring in weather variation to depict the influence of diverse environmental exposures on SB. Both weather variation and urban design played a significant role in SB. After factoring in weather variation, it was observed that children living in grid-pattern neighbourhoods closer to the city centre (with higher diversity of destinations) were less likely to be sedentary. This study demonstrates a methodology that could be replicated to integrate geography-specific weather patterns with existing cross-sectional accelerometry data to understand the influence of urban design and built environment on SB in children.
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2013-01-01
Background Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring. PMID:23827014
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NASA Astrophysics Data System (ADS)
Ye, Ran; Cai, Yanhong; Wei, Yongjie; Li, Xiaoming
2017-04-01
The spatial pattern of phytoplankton community can indicate potential environmental variation in different water bodies. In this context, spatial pattern of phytoplankton community and its response to environmental and spatial factors were studied in the coastal waters of northern Zhejiang, East China Sea using multivariate statistical techniques. Results showed that 94 species belonging to 40 genera, 5 phyla were recorded (the remaining 9 were identified to genus level) with diatoms being the most dominant followed by dinoflagellates. Hierarchical clustering analysis (HCA), nonmetric multidimentional scaling (NMDS), and analysis of similarity (ANOSIM) all demomstrated that the whole study area could be divided into 3 subareas with significant differences. Indicator species analysis (ISA) further confirmed that the indicator species of each subarea correlated significantly with specific environmental factors. Distance-based linear model (Distlm) and Mantel test revealed that silicate (SiO32-), phosphate (PO43-), pH, and dissolved oxygen (DO) were the most important environmental factors influencing phytoplankton community. Variation portioning (VP) finally concluded that the shared fractions of environmental and spatial factors were higher than either the pure environmental effects or the pure spatial effects, suggesting phytoplankton biogeography were mainly affected by both the environmental variability and dispersal limitation. Additionally, other factors (eg., trace metals, biological grazing, climate change, and time-scale variation) may also be the sources of the unexplained variation which need further study.
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Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.
Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming
2015-05-27
Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China. A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences. Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences. Although this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.
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NASA Astrophysics Data System (ADS)
Ye, Liming; Yang, Guixia; Van Ranst, Eric; Tang, Huajun
2013-03-01
A generalized, structural, time series modeling framework was developed to analyze the monthly records of absolute surface temperature, one of the most important environmental parameters, using a deterministicstochastic combined (DSC) approach. Although the development of the framework was based on the characterization of the variation patterns of a global dataset, the methodology could be applied to any monthly absolute temperature record. Deterministic processes were used to characterize the variation patterns of the global trend and the cyclic oscillations of the temperature signal, involving polynomial functions and the Fourier method, respectively, while stochastic processes were employed to account for any remaining patterns in the temperature signal, involving seasonal autoregressive integrated moving average (SARIMA) models. A prediction of the monthly global surface temperature during the second decade of the 21st century using the DSC model shows that the global temperature will likely continue to rise at twice the average rate of the past 150 years. The evaluation of prediction accuracy shows that DSC models perform systematically well against selected models of other authors, suggesting that DSC models, when coupled with other ecoenvironmental models, can be used as a supplemental tool for short-term (˜10-year) environmental planning and decision making.
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DOT National Transportation Integrated Search
2013-07-01
The study provides estimation of site specific variation in environmental factors that can be : used in predicting seasonal and long-term variations in moduli of unbound materials. Using : these site specific estimates, the EICM climatic input files ...
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Andrew D. Richardson; David Y. Hollinger; John D. Aber; Scott V. Ollinger; Bobby H. Braswell
2007-01-01
Tower-based eddy covariance measurements of forest-atmosphere carbon dioxide (CO2) exchange from many sites around the world indicate that there is considerable year-to-year variation in net ecosystem exchange (NEE). Here, we use a statistical modeling approach to partition the interannual variability in NEE (and its component fluxes, ecosystem...
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Direct and inverse modelling for environmental risk assessment and emission control
NASA Astrophysics Data System (ADS)
Penenko, V.; Baklanov, A.; Tsvetova, E.; Mahura, A.
2009-04-01
A concept of environmental modelling and its applications for Siberian regions are presented. The regions are considered both as sources and receptors of pollution as elements of the global climatic system. A methodology has been developed to build the combined methods of forward and inverse modelling for the problems of the air quality, environmental risk assessment and control. It is based on variational principles and methods of adjoint sensitivity theory. This allows obtaining the optimal numerical schemes and universal algorithm of the forward-inverse modelling. Following the concept, the functionals (describing the generalised characteristics of the processes, data, and models) are considered together with the basic model components. To combine all these elements in the frames of forward and inverse relations, we suppose that each of them may contain uncertainty. In this case, it is naturally to formulate a weak-constraint variational principle for the augmented functional which contains the model description in the form of integral identity and the cost functional including the total measure of all uncertainties. The stationary conditions for the augmented functional with respect to the variations its functional arguments define the mutually agreed structure of numerical schemes for forward and adjoint problems, and sensitivity relations. For quantitative risk assessment the following characteristics are useful: (i) values of goal functionals and their variations in a form of sensitivity relations; (ii) risk and sensitivity functions to the variations of the sources. It is convenient to take the risk function multiplied by the source function as a distributed risk measure. The variational technique provides the backward propagation of information, contained in the target functionals, to parameters and sources of the models through the sensitivity and uncertainty functions. This gives a base for realisation of the feedback algorithms and methods of control theory, which are necessary for formulation of multi-criteria optimisation accounting different constraints of ecological, economical, and social essence while solving environmental problems such as air pollution control, placement design for new industrial units, etc. The problems of the long-term environmental forecasting demand revealing the dynamical active zones and the areas of increased sensitivity to the variations of forcings (model parameters). The proposed methodology of accounting the climatic data into environmental studies is suitable for studying such problems. Analysis of the long-term behaviour of the global climatic system and orthogonal decomposition of the multivariate series of meteorological data with respect to the scales of processes allows identifying the activity centers and using this information for construction of scenarios for assessment of risk/vulnerability for sources/receptors. Such analysis for Siberian regions showed that Siberia is situated in areas which separate circulation systems of high energy activity. For winter, they are the Pacific and Atlantic energy-active zones, whereas the Arctic and South-Asian zones withstand in Siberia in summer. These facts allow an interpretation of climatic instability inherent in the region. During the autumn-winter season, the instability expresses as sharp alteration of weather cycles. The formation of Altai-Sayan cyclogenesis (which is of the same intensity as the Mediterranean) is observed for the warm seasons in the southern Siberia. In climatology it is referred as a lee-type cyclogenesis. This is the large scale phenomenon in the climatic system of the central part of Eurasia. Such specific hydrodynamic background defines environment quality in Siberia. From the point of view of system analysis, the methods of sensitivity theory, risk assessment and control along with scenario approach offer a tool which allows bringing the results of the global atmospheric and climatic studies onto the regional level. Namely, this level puts the concrete questions on the environment quality and its changes such as a choice of plausible strategy for sources control and mitigation of the man-induced impact on environment. Some environmental problems for Siberian regions are discussed, and a number of forward, adjoint and inverse problems for different risk sites and goal functionals are presented.
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Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.; ...
2017-11-22
Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.
Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less
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Nicholas C. Coops; Richard H. Waring; Todd A. Schroeder
2009-01-01
Although long-lived tree species experience considerable environmental variation over their life spans, their geographical distributions reflect sensitivity mainly to mean monthly climatic conditions.We introduce an approach that incorporates a physiologically based growth model to illustrate how a half-dozen tree species differ in their responses to monthly variation...
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Responses of leaf traits to climatic gradients: adaptive variation versus compositional shifts
NASA Astrophysics Data System (ADS)
Meng, T.-T.; Wang, H.; Harrison, S. P.; Prentice, I. C.; Ni, J.; Wang, G.
2015-09-01
Dynamic global vegetation models (DGVMs) typically rely on plant functional types (PFTs), which are assigned distinct environmental tolerances and replace one another progressively along environmental gradients. Fixed values of traits are assigned to each PFT; modelled trait variation along gradients is thus driven by PFT replacement. But empirical studies have revealed "universal" scaling relationships (quantitative trait variations with climate that are similar within and between species, PFTs and communities); and continuous, adaptive trait variation has been proposed to replace PFTs as the basis for next-generation DGVMs. Here we analyse quantitative leaf-trait variation on long temperature and moisture gradients in China with a view to understanding the relative importance of PFT replacement vs. continuous adaptive variation within PFTs. Leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC) and nitrogen content of dry matter were measured on all species at 80 sites ranging from temperate to tropical climates and from dense forests to deserts. Chlorophyll fluorescence traits and carbon, phosphorus and potassium contents were measured at 47 sites. Generalized linear models were used to relate log-transformed trait values to growing-season temperature and moisture indices, with or without PFT identity as a predictor, and to test for differences in trait responses among PFTs. Continuous trait variation was found to be ubiquitous. Responses to moisture availability were generally similar within and between PFTs, but biophysical traits (LA, SLA and LDMC) of forbs and grasses responded differently from woody plants. SLA and LDMC responses to temperature were dominated by the prevalence of evergreen PFTs with thick, dense leaves at the warm end of the gradient. Nutrient (N, P and K) responses to climate gradients were generally similar within all PFTs. Area-based nutrients generally declined with moisture; Narea and Karea declined with temperature, but Parea increased with temperature. Although the adaptive nature of many of these trait-climate relationships is understood qualitatively, a key challenge for modelling is to predict them quantitatively. Models must take into account that community-level responses to climatic gradients can be influenced by shifts in PFT composition, such as the replacement of deciduous by evergreen trees, which may run either parallel or counter to trait variation within PFTs. The importance of PFT shifts varies among traits, being important for biophysical traits but less so for physiological and chemical traits. Finally, models should take account of the diversity of trait values that is found in all sites and PFTs, representing the "pool" of variation that is locally available for the natural adaptation of ecosystem function to environmental change.
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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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NASA Astrophysics Data System (ADS)
Xu, Yi; Rose, Kenneth A.; Chai, Fei; Chavez, Francisco P.; Ayón, Patricia
2015-11-01
We used a 3-dimensional individual-based model (3-D IBM) of Peruvian anchovy to examine how spatial variation in environmental conditions affects larval and juvenile growth and survival, and recruitment. Temperature, velocity, and phytoplankton and zooplankton concentrations generated from a coupled hydrodynamic Nutrients-Phytoplankton-Zooplankton-Detritus (NPZD) model, mapped to a three dimensional rectangular grid, were used to simulate anchovy populations. The IBM simulated individuals as they progressed from eggs to recruitment at 10 cm. Eggs and yolk-sac larvae were followed hourly through the processes of development, mortality, and movement (advection), and larvae and juveniles were followed daily through the processes of growth, mortality, and movement (advection plus behavior). A bioenergetics model was used to grow larvae and juveniles. The NPZD model provided prey fields which influence both food consumption rate as well as behavior mediated movement with individuals going to grids cells having optimal growth conditions. We compared predicted recruitment for monthly cohorts for 1990 through 2004 between the full 3-D IBM and a point (0-D) model that used spatially-averaged environmental conditions. The 3-D and 0-D versions generated similar interannual patterns in monthly recruitment for 1991-2004, with the 3-D results yielding consistently higher survivorship. Both versions successfully captured the very poor recruitment during the 1997-1998 El Niño event. Higher recruitment in the 3-D simulations was due to higher survival during the larval stage resulting from individuals searching for more favorable temperatures that lead to faster growth rates. The strong effect of temperature was because both model versions provided saturating food conditions for larval and juvenile anchovies. We conclude with a discussion of how explicit treatment of spatial variation affected simulated recruitment, other examples of fisheries modeling analyses that have used a similar approach to assess the influence of spatial variation, and areas for further model development.
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NASA Astrophysics Data System (ADS)
Wagener, Thorsten; Pianosi, Francesca
2016-04-01
Sensitivity Analysis (SA) investigates how the variation in the output of a numerical model can be attributed to variations of its input factors. SA is increasingly being used in earth and environmental modelling for a variety of purposes, including uncertainty assessment, model calibration and diagnostic evaluation, dominant control analysis and robust decision-making. Here we provide some practical advice regarding best practice in SA and discuss important open questions based on a detailed recent review of the existing body of work in SA. Open questions relate to the consideration of input factor interactions, methods for factor mapping and the formal inclusion of discrete factors in SA (for example for model structure comparison). We will analyse these questions using relevant examples and discuss possible ways forward. We aim at stimulating the discussion within the community of SA developers and users regarding the setting of good practices and on defining priorities for future research.
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Takahashi, Kazuo H
2017-02-01
Drosophila wings have been a model system to study the effect of HSP90 on quantitative trait variation. The effect of HSP90 inhibition on environmental buffering of wing morphology varies among studies while the genetic buffering effect of it was examined in only one study and was not detected. Variable results so far might show that the genetic background influences the environmental and genetic buffering effect of HSP90. In the previous studies, the number of the genetic backgrounds used is limited. To examine the effect of HSP90 inhibition with a larger number of genetic backgrounds than the previous studies, 20 wild-type strains of Drosophila melanogaster were used in this study. Here I investigated the effect of HSP90 inhibition on the environmental buffering of wing shape and size by assessing within-individual and among-individual variations, and as a result, I found little or very weak effects on environmental and genetic buffering. The current results suggest that the role of HSP90 as a global regulator of environmental and genetic buffering is limited at least in quantitative traits.
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Variation in probability of first reproduction of Weddell seals.
Hadley, Gillian L; Rotella, Jay J; Garrott, Robert A; Nichols, James D
2006-09-01
1. For many species, when to begin reproduction is an important life-history decision that varies by individual and can have substantial implications for lifetime reproductive success and fitness. 2. We estimated age-specific probabilities of first-time breeding and modelled variation in these rates to determine age at first reproduction and understand why it varies in a population of Weddell seals in Erebus Bay, Antarctica. We used multistate mark-recapture modelling methods and encounter histories of 4965 known-age female seals to test predictions about age-related variation in probability of first reproduction and the effects of annual variation, cohort and population density. 3. Mean age at first reproduction in this southerly located study population (7.62 years of age, SD=1.71) was greater than age at first reproduction for a Weddell seal population at a more northerly and typical latitude for breeding Weddell seals (mean=4-5 years of age). This difference suggests that age at first reproduction may be influenced by whether a population inhabits the core or periphery of its range. 4. Age at first reproduction varied from 4 to 14 years, but there was no age by which all seals recruited to the breeding population, suggesting that individual heterogeneity exists among females in this population. 5. In the best model, the probability of breeding for the first time varied by age and year, and the amount of annual variation varied with age (average variance ratio for age-specific rates=4.3%). 6. Our results affirmed the predictions of life-history theory that age at first reproduction in long-lived mammals will be sensitive to environmental variation. In terms of life-history evolution, this variability suggests that Weddell seals display flexibility in age at first reproduction in order to maximize reproductive output under varying environmental conditions. Future analyses will attempt to test predictions regarding relationships between environmental covariates and annual variation in age at first reproduction and evaluate the relationship between age at first reproduction and lifetime reproductive success.
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Collective Functionality through Bacterial Individuality
NASA Astrophysics Data System (ADS)
Ackermann, Martin
According to the conventional view, the properties of an organism are a product of nature and nurture - of its genes and the environment it lives in. Recent experiments with unicellular organisms have challenged this view: several molecular mechanisms generate phenotypic variation independently of environmental signals, leading to variation in clonal groups. My presentation will focus on the causes and consequences of this microbial individuality. Using examples from bacterial genetic model systems, I will first discuss different molecular and cellular mechanisms that give rise to bacterial individuality. Then, I will discuss the consequences of individuality, and focus on how phenotypic variation in clonal populations of bacteria can promote interactions between individuals, lead to the division of labor, and allow clonal groups of bacteria to cope with environmental uncertainty. Variation between individuals thus provides clonal groups with collective functionality.
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A global Fine-Root Ecology Database to address below-ground challenges in plant ecology
Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer; ...
2017-02-28
Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less
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A global Fine-Root Ecology Database to address below-ground challenges in plant ecology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer
Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less
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Shekar, Sri N.; Zietsch, Brendan P.; Eaves, Lindon J.; Bailey, J. Michael; Boomsma, Dorret I.; Martin, Nicholas G.
2008-01-01
Previous research has shown that many heterosexuals hold negative attitudes toward homosexuals and homosexuality (homophobia). Although a great deal of research has focused on the profile of homophobic individuals, this research provides little theoretical insight into the aetiology of homophobia. To examine genetic and environmental influences on variation in attitudes toward homophobia, we analysed data from 4,688 twins who completed a questionnaire concerning sexual behaviour and attitudes, including attitudes toward homosexuality. Results show that, in accordance with literature, males have significantly more negative attitudes toward homosexuality than females and non-heterosexuals are less homophobic than heterosexuals. In contrast with some earlier findings, age had no significant effect on the homophobia scores in this study. Genetic modelling showed that variation in homophobia scores could be explained by additive genetic (36%), shared environmental (18%) and unique environmental factors (46%). However, corrections based on previous findings show that the shared environmental estimate may be almost entirely accounted for as extra additive genetic variance arising from assortative mating for homophobic attitudes. The results suggest that variation in attitudes toward homosexuality is substantially inherited, and that social environmental influences are relatively minor. PMID:18347968
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Intraspecific variation buffers projected climate change impacts on Pinus contorta
Oney, Brian; Reineking, Björn; O'Neill, Gregory; Kreyling, Juergen
2013-01-01
Species distribution modeling (SDM) is an important tool to assess the impact of global environmental change. Many species exhibit ecologically relevant intraspecific variation, and few studies have analyzed its relevance for SDM. Here, we compared three SDM techniques for the highly variable species Pinus contorta. First, applying a conventional SDM approach, we used MaxEnt to model the subject as a single species (species model), based on presence–absence observations. Second, we used MaxEnt to model each of the three most prevalent subspecies independently and combined their projected distributions (subspecies model). Finally, we used a universal growth transfer function (UTF), an approach to incorporate intraspecific variation utilizing provenance trial tree growth data. Different model approaches performed similarly when predicting current distributions. MaxEnt model discrimination was greater (AUC – species model: 0.94, subspecies model: 0.95, UTF: 0.89), but the UTF was better calibrated (slope and bias – species model: 1.31 and −0.58, subspecies model: 1.44 and −0.43, UTF: 1.01 and 0.04, respectively). Contrastingly, for future climatic conditions, projections of lodgepole pine habitat suitability diverged. In particular, when the species' intraspecific variability was acknowledged, the species was projected to better tolerate climatic change as related to suitable habitat without migration (subspecies model: 26% habitat loss or UTF: 24% habitat loss vs. species model: 60% habitat loss), and given unlimited migration may increase amount of suitable habitat (subspecies model: 8% habitat gain or UTF: 12% habitat gain vs. species model: 51% habitat loss) in the climatic period 2070–2100 (SRES A2 scenario, HADCM3). We conclude that models derived from within-species data produce different and better projections, and coincide with ecological theory. Furthermore, we conclude that intraspecific variation may buffer against adverse effects of climate change. A key future research challenge lies in assessing the extent to which species can utilize intraspecific variation under rapid environmental change. PMID:23467191
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Li, Xiang; Basu, Saonli; Miller, Michael B; Iacono, William G; McGue, Matt
2011-01-01
Genome-wide association studies (GWAS) using family data involve association analyses between hundreds of thousands of markers and a trait for a large number of related individuals. The correlations among relatives bring statistical and computational challenges when performing these large-scale association analyses. Recently, several rapid methods accounting for both within- and between-family variation have been proposed. However, these techniques mostly model the phenotypic similarities in terms of genetic relatedness. The familial resemblances in many family-based studies such as twin studies are not only due to the genetic relatedness, but also derive from shared environmental effects and assortative mating. In this paper, we propose 2 generalized least squares (GLS) models for rapid association analysis of family-based GWAS, which accommodate both genetic and environmental contributions to familial resemblance. In our first model, we estimated the joint genetic and environmental variations. In our second model, we estimated the genetic and environmental components separately. Through simulation studies, we demonstrated that our proposed approaches are more powerful and computationally efficient than a number of existing methods are. We show that estimating the residual variance-covariance matrix in the GLS models without SNP effects does not lead to an appreciable bias in the p values as long as the SNP effect is small (i.e. accounting for no more than 1% of trait variance). Copyright © 2011 S. Karger AG, Basel.
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Chen, Bor-Sen; Yeh, Chin-Hsun
2017-12-01
We review current static and dynamic evolutionary game strategies of biological networks and discuss the lack of random genetic variations and stochastic environmental disturbances in these models. To include these factors, a population of evolving biological networks is modeled as a nonlinear stochastic biological system with Poisson-driven genetic variations and random environmental fluctuations (stimuli). To gain insight into the evolutionary game theory of stochastic biological networks under natural selection, the phenotypic robustness and network evolvability of noncooperative and cooperative evolutionary game strategies are discussed from a stochastic Nash game perspective. The noncooperative strategy can be transformed into an equivalent multi-objective optimization problem and is shown to display significantly improved network robustness to tolerate genetic variations and buffer environmental disturbances, maintaining phenotypic traits for longer than the cooperative strategy. However, the noncooperative case requires greater effort and more compromises between partly conflicting players. Global linearization is used to simplify the problem of solving nonlinear stochastic evolutionary games. Finally, a simple stochastic evolutionary model of a metabolic pathway is simulated to illustrate the procedure of solving for two evolutionary game strategies and to confirm and compare their respective characteristics in the evolutionary process. Copyright © 2017 Elsevier B.V. All rights reserved.
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Mdladla, K; Dzomba, E F; Muchadeyi, F C
2018-04-01
In Africa, extensively raised livestock populations in most smallholder farming communities are exposed to harsh and heterogeneous climatic conditions and disease pathogens that they adapt to in order to survive. Majority of these livestock species, including goats, are of non-descript and uncharacterized breeds and their response to natural selection presented by heterogeneous environments is still unresolved. This study investigated genetic diversity and its association with environmental and geographic conditions in 194 South African indigenous goats from different geographic locations genotyped on the Illumina goat SNP50K panel. Population structure analysis revealed a homogeneous genetic cluster of the Tankwa goats, restricted to the Northern Cape province. Overall, the Boer, Kalahari Red, and Savanna showed a wide geographic spread of shared genetic components, whereas the village ecotypes revealed a longitudinal distribution. The relative importance of environmental factors on genetic variation of goat populations was assessed using redundancy analysis (RDA). Climatic and geographic variables explained 22% of the total variation while climatic variables alone accounted for 17% of the diversity. Geographic variables solitarily explained 1% of the total variation. The first axis (Model I) of the RDA analysis revealed 329 outlier SNPs. Landscape genomic approaches of spatial analysis method (SAM) identified a total of 843 (1.75%) SNPs, while latent factor mixed models (LFMM) identified 714 (1.48%) SNPs significantly associated with environmental variables. Significant markers were within genes involved in biological functions potentially important for environmental adaptation. Overall, the study suggested environmental factors to have some effect in shaping the genetic variation of South African indigenous goat populations. Loci observed to be significant and under selection may be responsible for the adaption of the goat populations to local production systems.
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Semiparametric Modeling of Daily Ammonia Levels in Naturally Ventilated Caged-Egg Facilities
Gutiérrez-Zapata, Diana María; Galeano-Vasco, Luis Fernando; Cerón-Muñoz, Mario Fernando
2016-01-01
Ammonia concentration (AMC) in poultry facilities varies depending on different environmental conditions and management; however, this is a relatively unexplored subject in Colombia (South America). The objective of this study was to model daily AMC variations in a naturally ventilated caged-egg facility using generalized additive models. Four sensor nodes were used to record AMC, temperature, relative humidity and wind speed on a daily basis, with 10 minute intervals for 12 weeks. The following variables were included in the model: Heat index, Wind, Hour, Location, Height of the sensor to the ground level, and Period of manure accumulation. All effects included in the model were highly significant (p<0.001). The AMC was higher during the night and early morning when the wind was not blowing (0.0 m/s) and the heat index was extreme. The average and maximum AMC were 5.94±3.83 and 31.70 ppm, respectively. Temperatures above 25°C and humidity greater than 80% increased AMC levels. In naturally ventilated caged-egg facilities the daily variations observed in AMC primarily depend on cyclic variations of the environmental conditions and are also affected by litter handling (i.e., removal of the bedding material). PMID:26812150
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Bird-landscape relations in the Chihuahuan Desert: Coping with uncertainties about predictive models
Gutzwiller, K.J.; Barrow, W.C.
2001-01-01
During the springs of 1995-1997, we studied birds and landscapes in the Chihuahuan Desert along part of the Texas-Mexico border. Our objectives were to assess bird-landscape relations and their interannual consistency and to identify ways to cope with associated uncertainties that undermine confidence in using such relations in conservation decision processes. Bird distributions were often significantly associated with landscape features, and many bird-landscape models were valid and useful for predictive purposes. Differences in early spring rainfall appeared to influence bird abundance, but there was no evidence that annual differences in bird abundance affected model consistency. Model consistency for richness (42%) was higher than mean model consistency for 26 focal species (mean 30%, range 0-67%), suggesting that relations involving individual species are, on average, more subject to factors that cause variation than are richness-landscape relations. Consistency of bird-landscape relations may be influenced by such factors as plant succession, exotic species invasion, bird species' tolerances for environmental variation, habitat occupancy patterns, and variation in food density or weather. The low model consistency that we observed for most species indicates the high variation in bird-landscape relations that managers and other decision makers may encounter. The uncertainty of interannual variation in bird-landscape relations can be reduced by using projections of bird distributions from different annual models to determine the likely range of temporal and spatial variation in a species' distribution. Stochastic simulation models can be used to incorporate the uncertainty of random environmental variation into predictions of bird distributions based on bird-landscape relations and to provide probabilistic projections with which managers can weigh the costs and benefits of various decisions, Uncertainty about the true structure of bird-landscape relations (structural uncertainty) can be reduced by ensuring that models meet important statistical assumptions, designing studies with sufficient statistical power, validating the predictive ability of models, and improving model accuracy through continued field sampling and model fitting. Un certainty associated with sampling variation (partial observability) can be reduced by ensuring that sample sizes are large enough to provide precise estimates of both bird and landscape parameters. By decreasing the uncertainty due to partial observability, managers will improve their ability to reduce structural uncertainty.
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Physiological system integrations with emphasis on the respiratory-cardiovascular system
NASA Technical Reports Server (NTRS)
Gallagher, R. R.
1975-01-01
The integration of two types of physiological system simulations is presented. The long term model is a circulatory system model which simulates long term blood flow variations and compartmental fluid shifts. The short term models simulate transient phenomena of the respiratory, thermoregulatory, and pulsatile cardiovascular systems as they respond to stimuli such as LBNP, exercise, and environmental gaseous variations. An overview of the interfacing approach is described. Descriptions of the variable interface for long term to short term and between the three short term models are given.
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Intraspecific variability and reaction norms of forest understory plant species traits
Burton, Julia I.; Perakis, Steven; McKenzie, Sean C.; Lawrence, Caitlin E.; Puettmann, Klaus J.
2017-01-01
Trait-based models of ecological communities typically assume intraspecific variation in functional traits is not important, though such variation can change species trait rankings along gradients in resources and environmental conditions, and thus influence community structure and function.We examined the degree of intraspecific relative to interspecific variation, and reaction norms of 11 functional traits for 57 forest understory plant species, including: intrinsic water-use efficiency (iWUE), Δ15N, 5 leaf traits, 2 stem traits and 2 root traits along gradients in light, nitrogen, moisture and understory cover.Our results indicate that interspecific trait variation exceeded intraspecific variation by at least 50% for most, but not all traits. Intraspecific variation in Δ15N, iWUE, leaf nitrogen content and root traits was high (47-70%) compared with most leaf traits and stem traits (13-38%).Δ15N varied primarily along gradients in abiotic conditions, while light and understory cover were relatively less important. iWUE was related primarily to light transmission, reflecting increases in photosynthesis relative to stomatal conductance. Leaf traits varied mainly as a function of light availability, with some reaction norms depending on understory cover. Plant height increased with understory cover, while stem specific density was related primarily to light. Resources, environmental conditions and understory cover did not contribute strongly to the observed variation in root traits.Gradients in resources, environmental conditions and competition all appear to control intraspecific variability in most traits to some extent. However, our results suggest that species cross-over (i.e., trait rank reversals) along the gradients measured here are generally not a concern.Intraspecific variability in understory plant species traits can be considerable. However, trait data collected under a narrow range of environmental conditions appears sufficient to establish species rankings and scale between community and ecosystem levels using trait-based models. Investigators may therefore focus on obtaining a sufficient sample size within a single set of conditions rather than characterizing trait variation across entire gradients in order to optimize sampling efforts.
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Understanding and monitoring the consequences of human impacts on intraspecific variation.
Mimura, Makiko; Yahara, Tetsukazu; Faith, Daniel P; Vázquez-Domínguez, Ella; Colautti, Robert I; Araki, Hitoshi; Javadi, Firouzeh; Núñez-Farfán, Juan; Mori, Akira S; Zhou, Shiliang; Hollingsworth, Peter M; Neaves, Linda E; Fukano, Yuya; Smith, Gideon F; Sato, Yo-Ichiro; Tachida, Hidenori; Hendry, Andrew P
2017-02-01
Intraspecific variation is a major component of biodiversity, yet it has received relatively little attention from governmental and nongovernmental organizations, especially with regard to conservation plans and the management of wild species. This omission is ill-advised because phenotypic and genetic variations within and among populations can have dramatic effects on ecological and evolutionary processes, including responses to environmental change, the maintenance of species diversity, and ecological stability and resilience. At the same time, environmental changes associated with many human activities, such as land use and climate change, have dramatic and often negative impacts on intraspecific variation. We argue for the need for local, regional, and global programs to monitor intraspecific genetic variation. We suggest that such monitoring should include two main strategies: (i) intensive monitoring of multiple types of genetic variation in selected species and (ii) broad-brush modeling for representative species for predicting changes in variation as a function of changes in population size and range extent. Overall, we call for collaborative efforts to initiate the urgently needed monitoring of intraspecific variation.
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Genetic and physiological bases for phenological responses to current and predicted climates
Wilczek, A. M.; Burghardt, L. T.; Cobb, A. R.; Cooper, M. D.; Welch, S. M.; Schmitt, J.
2010-01-01
We are now reaching the stage at which specific genetic factors with known physiological effects can be tied directly and quantitatively to variation in phenology. With such a mechanistic understanding, scientists can better predict phenological responses to novel seasonal climates. Using the widespread model species Arabidopsis thaliana, we explore how variation in different genetic pathways can be linked to phenology and life-history variation across geographical regions and seasons. We show that the expression of phenological traits including flowering depends critically on the growth season, and we outline an integrated life-history approach to phenology in which the timing of later life-history events can be contingent on the environmental cues regulating earlier life stages. As flowering time in many plants is determined by the integration of multiple environmentally sensitive gene pathways, the novel combinations of important seasonal cues in projected future climates will alter how phenology responds to variation in the flowering time gene network with important consequences for plant life history. We discuss how phenology models in other systems—both natural and agricultural—could employ a similar framework to explore the potential contribution of genetic variation to the physiological integration of cues determining phenology. PMID:20819808
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Thuiller, Wilfried; Albert, Cécile H.; Dubuis, Anne; Randin, Christophe; Guisan, Antoine
2010-01-01
Habitat suitability models, which relate species occurrences to environmental variables, are assumed to predict suitable conditions for a given species. If these models are reliable, they should relate to change in plant growth and function. In this paper, we ask the question whether habitat suitability models are able to predict variation in plant functional traits, often assumed to be a good surrogate for a species' overall health and vigour. Using a thorough sampling design, we show a tight link between variation in plant functional traits and habitat suitability for some species, but not for others. Our contrasting results pave the way towards a better understanding of how species cope with varying habitat conditions and demonstrate that habitat suitability models can provide meaningful descriptions of the functional niche in some cases, but not in others. PMID:19793738
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Katapally, Tarun Reddy; Rainham, Daniel; Muhajarine, Nazeem
2016-01-01
With emerging evidence indicating that independent of physical activity, sedentary behaviour (SB) can be detrimental to health, researchers are increasingly aiming to understand the influence of multiple contexts such as urban design and built environment on SB. However, weather variation, a factor that continuously interacts with all other environmental variables, has been consistently underexplored. This study investigated the influence of diverse environmental exposures (including weather variation, urban design and built environment) on SB in children. This cross-sectional observational study is part of an active living research initiative set in the Canadian prairie city of Saskatoon. Saskatoon's neighbourhoods were classified based on urban street design into grid-pattern, fractured grid-pattern and curvilinear types of neighbourhoods. Diverse environmental exposures were measured including, neighbourhood built environment, and neighbourhood and household socioeconomic environment. Actical accelerometers were deployed between April and June 2010 (spring-summer) to derive SB of 331 10–14 year old children in 25 one week cycles. Each cycle of accelerometry was conducted on a different cohort of children within the total sample. Accelerometer data were matched with localized weather patterns derived from Environment Canada weather data. Multilevel modeling using Hierarchical Linear and Non-linear Modeling software was conducted by factoring in weather variation to depict the influence of diverse environmental exposures on SB. Both weather variation and urban design played a significant role in SB. After factoring in weather variation, it was observed that children living in grid-pattern neighbourhoods closer to the city centre (with higher diversity of destinations) were less likely to be sedentary. This study demonstrates a methodology that could be replicated to integrate geography-specific weather patterns with existing cross-sectional accelerometry data to understand the influence of urban design and built environment on SB in children. PMID:29546188
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Katapally, Tarun Reddy; Muhajarine, Nazeem
2015-01-01
Objectives In curbing physical inactivity, as behavioural interventions directed at individuals have not produced a population-level change, an ecological perspective called active living research has gained prominence. However, active living research consistently underexplores the role played by a perennial phenomenon encompassing all other environmental exposures—variation in weather. After factoring in weather variation, this study investigated the influence of diverse environmental exposures (including urban design and built environment) on the accumulation of globally recommended moderate to vigorous physical activity levels (MVPA) in children. Design This cross-sectional observational study is part of an active living initiative set in the Canadian prairie city of Saskatoon. As part of this study, Saskatoon's neighbourhoods were classified based on urban street design into grid-pattern, fractured grid-pattern and curvilinear types of neighbourhoods. Moreover, diverse environmental exposures were measured including, neighbourhood built environment, and neighbourhood and household socioeconomic environment. Actical accelerometers were deployed between April and June 2010 (spring-summer) to derive MVPA of 331 10–14-year-old children in 25 1-week cycles. Each cycle of accelerometry was conducted on a different cohort of children within the total sample and matched with weather data obtained from Environment Canada. Multilevel modelling using Hierarchical Linear and Non-linear Modelling software was conducted by factoring in weather variation to depict the influence of diverse environmental exposures on the accumulation of recommended MVPA. Results Urban design, including diversity of destinations within neighbourhoods played a significant role in the accumulation of MVPA. After factoring in weather variation, it was observed that children living in neighbourhoods closer to the city centre (with higher diversity of destinations) were more likely to accumulate recommended MVPA. Conclusions The findings indicate that after factoring in weather variation, certain types of urban design are more likely to be associated with MVPA accumulation. PMID:26621516
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Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models
USDA-ARS?s Scientific Manuscript database
Leaf shape traits have long been a focus of many disciplines, but searching for complex genetic and environmental interactive mechanisms regulating leaf shape variation has not yet been well developed. The question of the respective roles of gene and environment and how they interplay to modulate l...
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Rood, Ente J J; Goris, Marga G A; Pijnacker, Roan; Bakker, Mirjam I; Hartskeerl, Rudy A
2017-01-01
Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.
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Goris, Marga G. A.; Pijnacker, Roan; Bakker, Mirjam I.; Hartskeerl, Rudy A.
2017-01-01
Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995–2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas. PMID:29065186
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From stage to age in variable environments: life expectancy and survivorship.
Tuljapurkar, Shripad; Horvitz, Carol C
2006-06-01
Stage-based demographic data are now available on many species of plants and some animals, and they often display temporal and spatial variability. We provide exact formulas to compute age-specific life expectancy and survivorship from stage-based data for three models of temporal variability: cycles, serially independent random variation, and a Markov chain. These models provide a comprehensive description of patterns of temporal variation. Our formulas describe the effects of cohort (birth) environmental condition on mortality at all ages, and of the effects on survivorship of environmental variability experienced over the course of life. This paper complements existing methods for time-invariant stage-based data, and adds to the information on population growth and dynamics available from stochastic demography.
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Modeling Gene-Environment Interactions With Quasi-Natural Experiments.
Schmitz, Lauren; Conley, Dalton
2017-02-01
This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.
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ERIC Educational Resources Information Center
Davidhizar, Ruth; Giger, Joyce Newman
2001-01-01
Presents a method for integrating cultural competence throughout the nursing curriculum. The model contains six cultural phenomena: communication, space, social organization, time, environmental control, and biological variation. Contains 17 references. (SK)
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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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Temunović, Martina; Franjić, Jozo; Satovic, Zlatko; Grgurev, Marin; Frascaria-Lacoste, Nathalie; Fernández-Manjarrés, Juan F
2012-01-01
Tree species with wide distributions often exhibit different levels of genetic structuring correlated to their environment. However, understanding how environmental heterogeneity influences genetic variation is difficult because the effects of gene flow, drift and selection are confounded. We investigated the genetic variation and its ecological correlates in a wind-pollinated Mediterranean tree species, Fraxinus angustifolia Vahl, within a recognised glacial refugium in Croatia. We sampled 11 populations from environmentally divergent habitats within the Continental and Mediterranean biogeographical regions. We combined genetic data analyses based on nuclear microsatellite loci, multivariate statistics on environmental data and ecological niche modelling (ENM). We identified a geographic structure with a high genetic diversity and low differentiation in the Continental region, which contrasted with the significantly lower genetic diversity and higher population divergence in the Mediterranean region. The positive and significant correlation between environmental and genetic distances after controlling for geographic distance suggests an important influence of ecological divergence of the sites in shaping genetic variation. The ENM provided support for niche differentiation between the populations from the Continental and Mediterranean regions, suggesting that contemporary populations may represent two divergent ecotypes. Ecotype differentiation was also supported by multivariate environmental and genetic distance analyses. Our results suggest that despite extensive gene flow in continental areas, long-term stability of heterogeneous environments have likely promoted genetic divergence of ashes in this region and can explain the present-day genetic variation patterns of these ancient populations.
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Temunović, Martina; Franjić, Jozo; Satovic, Zlatko; Grgurev, Marin; Frascaria-Lacoste, Nathalie; Fernández-Manjarrés, Juan F.
2012-01-01
Tree species with wide distributions often exhibit different levels of genetic structuring correlated to their environment. However, understanding how environmental heterogeneity influences genetic variation is difficult because the effects of gene flow, drift and selection are confounded. We investigated the genetic variation and its ecological correlates in a wind-pollinated Mediterranean tree species, Fraxinus angustifolia Vahl, within a recognised glacial refugium in Croatia. We sampled 11 populations from environmentally divergent habitats within the Continental and Mediterranean biogeographical regions. We combined genetic data analyses based on nuclear microsatellite loci, multivariate statistics on environmental data and ecological niche modelling (ENM). We identified a geographic structure with a high genetic diversity and low differentiation in the Continental region, which contrasted with the significantly lower genetic diversity and higher population divergence in the Mediterranean region. The positive and significant correlation between environmental and genetic distances after controlling for geographic distance suggests an important influence of ecological divergence of the sites in shaping genetic variation. The ENM provided support for niche differentiation between the populations from the Continental and Mediterranean regions, suggesting that contemporary populations may represent two divergent ecotypes. Ecotype differentiation was also supported by multivariate environmental and genetic distance analyses. Our results suggest that despite extensive gene flow in continental areas, long-term stability of heterogeneous environments have likely promoted genetic divergence of ashes in this region and can explain the present-day genetic variation patterns of these ancient populations. PMID:22905171
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This paper shows that rat models of cardiovascular diseases have differential degrees of underlying pathologies at a young age. Rodent models of cardiovascular diseases (CVD) and metabolic disorders are used for examining susceptibility variations to environmental exposures. How...
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Pérez-López, Paula; Montazeri, Mahdokht; Feijoo, Gumersindo; Moreira, María Teresa; Eckelman, Matthew J
2018-06-01
The economic and environmental performance of microalgal processes has been widely analyzed in recent years. However, few studies propose an integrated process-based approach to evaluate economic and environmental indicators simultaneously. Biodiesel is usually the single product and the effect of environmental benefits of co-products obtained in the process is rarely discussed. In addition, there is wide variation of the results due to inherent variability of some parameters as well as different assumptions in the models and limited knowledge about the processes. In this study, two standardized models were combined to provide an integrated simulation tool allowing the simultaneous estimation of economic and environmental indicators from a unique set of input parameters. First, a harmonized scenario was assessed to validate the joint environmental and techno-economic model. The findings were consistent with previous assessments. In a second stage, a Monte Carlo simulation was applied to evaluate the influence of variable and uncertain parameters in the model output, as well as the correlations between the different outputs. The simulation showed a high probability of achieving favorable environmental performance for the evaluated categories and a minimum selling price ranging from $11gal -1 to $106gal -1 . Greenhouse gas emissions and minimum selling price were found to have the strongest positive linear relationship, whereas eutrophication showed weak correlations with the other indicators (namely greenhouse gas emissions, cumulative energy demand and minimum selling price). Process parameters (especially biomass productivity and lipid content) were the main source of variation, whereas uncertainties linked to the characterization methods and economic parameters had limited effect on the results. Copyright © 2018 Elsevier B.V. All rights reserved.
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Browder, Joan A.; Restrepo, V.R.; Rice, J.K.; Robblee, M.B.; Zein-Eldin, Z.
1999-01-01
Two modeling approaches were used to explore the basis for variation in recruitment of pink shrimp, Farfantepenaeus duorarum, to the Tortugas fishing grounds. Emphasis was on development and juvenile densities on the nursery grounds. An exploratory simulation modeling exercise demonstrated large year-to-year variations in recruitment contributions to the Tortugas rink shrimp fishery may occur on some nursery grounds, and production may differ considerably among nursery grounds within the same year, simply on the basis of differences in temperature and salinity. We used a growth and survival model to simulate cumulative harvests from a July-centered cohort of early-settlement-stage postlarvae from two parts of Florida Bay (western Florida Bay and northcentral Florida Bay), using historic temperature and salinity data from these areas. Very large year-to-year differences in simulated cumulative harvests were found for recruits from Whipray Basin. Year-to-year differences in simulated harvests of recruits from Johnson Key Basin were much smaller. In a complementary activity, generalized linear and additive models and intermittent, historic density records were used to develop an uninterrupted multi-year time series of monthly density estimates for juvenile rink shrimp in the Johnson Key Basin. The developed data series was based on relationships of density with environmental variables. The strongest relationship was with sea-surface temperature. Three other environmental variables (rainfall, water level at Everglades National Park Well P35, and mean wind speed) also contributed significantly to explaining variation in juvenile densities. Results of the simulation model and two of the three statistical models yielded similar interannual patterns for Johnson Key Basin. While it is not possible to say that one result validates the other, the concordance of the annual patterns from the two models is supportive of both approaches.
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A global Fine-Root Ecology Database to address below-ground challenges in plant ecology.
Iversen, Colleen M; McCormack, M Luke; Powell, A Shafer; Blackwood, Christopher B; Freschet, Grégoire T; Kattge, Jens; Roumet, Catherine; Stover, Daniel B; Soudzilovskaia, Nadejda A; Valverde-Barrantes, Oscar J; van Bodegom, Peter M; Violle, Cyrille
2017-07-01
Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. While fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of root traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. Continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.
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Genetic and environmental influences on mean diffusivity and volume in subcortical brain regions.
Gillespie, Nathan A; Neale, Michael C; Hagler, Donald J; Eyler, Lisa T; Fennema-Notestine, Christine; Franz, Carol E; Lyons, Michael J; McEvoy, Linda K; Dale, Anders M; Panizzon, Matthew S; Kremen, William S
2017-05-01
Increased mean diffusivity (MD) is hypothesized to reflect tissue degeneration and may provide subtle indicators of neuropathology as well as age-related brain changes in the absence of volumetric differences. Our aim was to determine the degree to which genetic and environmental variation in subcortical MD is distinct from variation in subcortical volume. Data were derived from a sample of 387 male twins (83 MZ twin pairs, 55 DZ twin pairs, and 111 incomplete twin pairs) who were MRI scanned as part of the Vietnam Era Twin Study of Aging. Quantitative estimates of MD and volume for 7 subcortical regions were obtained: thalamus, caudate nucleus, putamen, pallidum, hippocampus, amygdala, and nucleus accumbens. After adjusting for covariates, bivariate twin models were fitted to estimate the size and significance of phenotypic, genotypic, and environmental correlations between MD and volume at each subcortical region. With the exception of the amygdala, familial aggregation in MD was entirely explained by additive genetic factors across all subcortical regions with estimates ranging from 46 to 84%. Based on bivariate twin modeling, variation in subcortical MD appears to be both genetically and environmentally unrelated to individual differences in subcortical volume. Therefore, subcortical MD may be an alternative biomarker of brain morphology for complex traits worthy of future investigation. Hum Brain Mapp 38:2589-2598, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
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Resco de Dios, Víctor; Gessler, Arthur; Ferrio, Juan Pedro; Alday, Josu G; Bahn, Michael; Del Castillo, Jorge; Devidal, Sébastien; García-Muñoz, Sonia; Kayler, Zachary; Landais, Damien; Martín-Gómez, Paula; Milcu, Alexandru; Piel, Clément; Pirhofer-Walzl, Karin; Ravel, Olivier; Salekin, Serajis; Tissue, David T; Tjoelker, Mark G; Voltas, Jordi; Roy, Jacques
2016-10-20
Molecular clocks drive oscillations in leaf photosynthesis, stomatal conductance, and other cell and leaf-level processes over ~24 h under controlled laboratory conditions. The influence of such circadian regulation over whole-canopy fluxes remains uncertain; diurnal CO 2 and H 2 O vapor flux dynamics in the field are currently interpreted as resulting almost exclusively from direct physiological responses to variations in light, temperature and other environmental factors. We tested whether circadian regulation would affect plant and canopy gas exchange at the Montpellier European Ecotron. Canopy and leaf-level fluxes were constantly monitored under field-like environmental conditions, and under constant environmental conditions (no variation in temperature, radiation, or other environmental cues). We show direct experimental evidence at canopy scales of the circadian regulation of daytime gas exchange: 20-79 % of the daily variation range in CO 2 and H 2 O fluxes occurred under circadian entrainment in canopies of an annual herb (bean) and of a perennial shrub (cotton). We also observed that considering circadian regulation improved performance by 8-17 % in commonly used stomatal conductance models. Our results show that circadian controls affect diurnal CO 2 and H 2 O flux patterns in entire canopies in field-like conditions, and its consideration significantly improves model performance. Circadian controls act as a 'memory' of the past conditions experienced by the plant, which synchronizes metabolism across entire plant canopies.
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Hess, Moritz; Wildhagen, Henning; Junker, Laura Verena; Ensminger, Ingo
2016-08-26
Local adaptation and phenotypic plasticity are important components of plant responses to variations in environmental conditions. While local adaptation has been widely studied in trees, little is known about plasticity of gene expression in adult trees in response to ever changing environmental conditions in natural habitats. Here we investigate plasticity of gene expression in needle tissue between two Douglas-fir provenances represented by 25 adult trees using deep RNA sequencing (RNA-Seq). Using linear mixed models we investigated the effect of temperature, soil water availability and photoperiod on the abundance of 59189 detected transcripts. Expression of more than 80 % of all identified transcripts revealed a response to variations in environmental conditions in the field. GO term overrepresentation analysis revealed gene expression responses to temperature, soil water availability and photoperiod that are highly conserved among many plant taxa. However, expression differences between the two Douglas-fir provenances were rather small compared to the expression differences observed between individual trees. Although the effect of environment on global transcript expression was high, the observed genotype by environment (GxE) interaction of gene expression was surprisingly low, since only 21 of all detected transcripts showed a GxE interaction. The majority of the transcriptome responses in plant leaf tissue is driven by variations in environmental conditions. The small variation between individuals and populations suggests strong conservation of this response within Douglas-fir. Therefore we conclude that plastic transcriptome responses to variations in environmental conditions are only weakly affected by local adaptation in Douglas-fir.
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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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Fyllas, Nikolaos M; Bentley, Lisa Patrick; Shenkin, Alexander; Asner, Gregory P; Atkin, Owen K; Díaz, Sandra; Enquist, Brian J; Farfan-Rios, William; Gloor, Emanuel; Guerrieri, Rossella; Huasco, Walter Huaraca; Ishida, Yoko; Martin, Roberta E; Meir, Patrick; Phillips, Oliver; Salinas, Norma; Silman, Miles; Weerasinghe, Lasantha K; Zaragoza-Castells, Joana; Malhi, Yadvinder
2017-06-01
One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale. © 2017 John Wiley & Sons Ltd/CNRS.
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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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Su, G; Madsen, P; Lund, M S
2009-05-01
Crossbreeding is currently increasing in dairy cattle production. Several studies have shown an environment-dependent heterosis [i.e., an interaction between heterosis and environment (H x E)]. An H x E interaction is usually estimated from a few discrete environment levels. The present study proposes a reaction norm model to describe H x E interaction, which can deal with a large number of environment levels using few parameters. In the proposed model, total heterosis consists of an environment-independent part, which is described as a function of heterozygosity, and an environment-dependent part, which is described as a function of heterozygosity and environmental value (e.g., herd-year effect). A Bayesian approach is developed to estimate the environmental covariates, the regression coefficients of the reaction norm, and other parameters of the model simultaneously in both linear and nonlinear reaction norms. In the nonlinear reaction norm model, the H x E is approximated using linear splines. The approach was tested using simulated data, which were generated using an animal model with a reaction norm for heterosis. The simulation study includes 4 scenarios (the combinations of moderate vs. low heritability and moderate vs. low herd-year variation) of H x E interaction in a nonlinear form. In all scenarios, the proposed model predicted total heterosis very well. The correlation between true heterosis and predicted heterosis was 0.98 in the scenarios with low herd-year variation and 0.99 in the scenarios with moderate herd-year variation. This suggests that the proposed model and method could be a good approach to analyze H x E interactions and predict breeding values in situations in which heterosis changes gradually and continuously over an environmental gradient. On the other hand, it was found that a model ignoring H x E interaction did not significantly harm the prediction of breeding value under the simulated scenarios in which the variance for environment-dependent heterosis effects was small (as it generally is), and sires were randomly used over production environments.
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Xiao, Hong; Huang, Ru; Gao, Li-Dong; Huang, Cun-Rui; Lin, Xiao-Ling; Li, Na; Liu, Hai-Ning; Tong, Shi-Lu; Tian, Huai-Yu
2016-01-01
Infection rates of rodents have a significant influence on the transmission of hemorrhagic fever with renal syndrome (HFRS). In this study, four cities and two counties with high HFRS incidence in eastern Hunan Province in China were studied, and surveillance data of rodents, as well as HFRS cases and related environmental variables from 2007 to 2010, were collected. Results indicate that the distribution and infection rates of rodents are closely associated with environmental conditions. Hantavirus infections in rodents were positively correlated with temperature vegetation dryness index and negatively correlated with elevation. The predictive risk maps based on multivariate regression model revealed that the annual variation of infection risks is small, whereas monthly variation is large and corresponded well to the seasonal variation of human HFRS incidence. The identification of risk factors and risk prediction provides decision support for rodent surveillance and the prevention and control of HFRS. PMID:26711521
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Playing by the rules? Phenotypic adaptation to temperate environments in an American marsupial
Harrigan, Ryan J.; Wayne, Robert K.
2018-01-01
Phenotypic variation along environmental gradients can provide evidence suggesting local adaptation has shaped observed morphological disparities. These differences, in traits such as body and extremity size, as well as skin and coat pigmentation, may affect the overall fitness of individuals in their environments. The Virginia opossum (Didelphis virginiana) is a marsupial that shows phenotypic variation across its range, one that has recently expanded into temperate environments. It is unknown, however, whether the variation observed in the species fits adaptive ecogeographic patterns, or if phenotypic change is associated with any environmental factors. Using phenotypic measurements of over 300 museum specimens of Virginia opossum, collected throughout its distribution range, we applied regression analysis to determine if phenotypes change along a latitudinal gradient. Then, using predictors from remote-sensing databases and a random forest algorithm, we tested environmental models to find the most important variables driving the phenotypic variation. We found that despite the recent expansion into temperate environments, the phenotypic variation in the Virginia opossum follows a latitudinal gradient fitting three adaptive ecogeographic patterns codified under Bergmann’s, Allen’s and Gloger’s rules. Temperature seasonality was an important predictor of body size variation, with larger opossums occurring at high latitudes with more seasonal environments. Annual mean temperature predicted important variation in extremity size, with smaller extremities found in northern populations. Finally, we found that precipitation and temperature seasonality as well as low temperatures were strong environmental predictors of skin and coat pigmentation variation; darker opossums are distributed at low latitudes in warmer environments with higher precipitation seasonality. These results indicate that the adaptive mechanisms underlying the variation in body size, extremity size and pigmentation are related to the resource seasonality, heat conservation, and pathogen-resistance hypotheses, respectively. Our findings suggest that marsupials may be highly susceptible to environmental changes, and in the case of the Virginia opossum, the drastic phenotypic evolution in northern populations may have arisen rapidly, facilitating the colonization of seasonal and colder habitats of temperate North America. PMID:29607255
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Wei, Xiaojing; Savage, Jessica A; Riggs, Charlotte E; Cavender-Bares, Jeannine
2017-05-01
Environmental filtering is an important community assembly process influencing species distributions. Contrasting species abundance patterns along environmental gradients are commonly used to provide evidence for environmental filtering. However, the same abundance patterns may result from alternative or concurrent assembly processes. Experimental tests are an important means to decipher whether species fitness varies with environment, in the absence of dispersal constraints and biotic interactions, and to draw conclusions about the importance of environmental filtering in community assembly. We performed an experimental test of environmental filtering in 14 closely related willow and poplar species (family Salicaceae) by transplanting cuttings of each species into 40 common gardens established along a natural hydrologic gradient in the field, where competition was minimized and herbivory was controlled. We analyzed species fitness responses to the hydrologic environment based on cumulative growth and survival over two years using aster fitness models. We also examined variation in nine drought and flooding tolerance traits expected to contribute to performance based on a priori understanding of plant function in relation to water availability and stress. We found substantial evidence that environmental filtering along the hydrologic gradient played a critical role in determining species distributions. Fitness variation of each species in the field experiment was used to model their water table depth optima. These optima predicted 68% of the variation in species realized hydrologic niches based on peak abundance in naturally assembled communities in the surrounding region. Multiple traits associated with water transport efficiency and water stress tolerance were correlated with species hydrologic niches, but they did not necessarily covary with each other. As a consequence, species occupying similar hydrologic niches had different combinations of trait values. Moreover, individual traits were less phylogenetically conserved than species hydrologic niches and integrated water stress tolerance as determined by multiple traits. We conclude that differential fitness among species along the hydrologic gradient was the consequence of multiple traits associated with water transport and water stress tolerance, expressed in different combinations by different species. Varying environmental tolerance, in turn, played a critical role in driving niche segregation among close relatives along the hydrologic gradient. © 2017 by the Ecological Society of America.
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Variation in probability of first reproduction of Weddell seals
Hadley, G.L.; Rotella, J.J.; Garrott, R.A.; Nichols, J.D.
2006-01-01
Summary 1. For many species, when to begin reproduction is an important life-history decision that varies by individual and can have substantial implications for lifetime reproductive success and fitness. 2. We estimated age-specific probabilities of first-time breeding and modelled variation in these rates to determine age at first reproduction and understand why it varies in a population of Weddell seals in Erebus Bay, Antarctica. We used multistate mark?recapture modelling methods and encounter histories of 4965 known-age female seals to test predictions about age-related variation in probability of first reproduction and the effects of annual variation, cohort and population density. 3. Mean age at first reproduction in this southerly located study population (7.62 years of age, SD =1.71) was greater than age at first reproduction for a Weddell seal population at a more northerly and typical latitude for breeding Weddell seals (mean =4?5 years of age). This difference suggests that age at first reproduction may be influenced by whether a population inhabits the core or periphery of its range. 4. Age at first reproduction varied from 4 to 14 years, but there was no age by which all seals recruited to the breeding population, suggesting that individual heterogeneity exists among females in this population. 5. In the best model, the probability of breeding for the first time varied by age and year, and the amount of annual variation varied with age (average variance ratio for age-specific rates =4.3%). 6. Our results affirmed the predictions of life-history theory that age at first reproduction in long-lived mammals will be sensitive to environmental variation. In terms of life history evolution, this variability suggests that Weddell seals display flexibility in age at first reproduction in order to maximize reproductive output under varying environmental conditions. Future analyses will attempt to test predictions regarding relationships between environmental covariates and annual variation in age at first reproduction and evaluate the relationship between age at first reproduction and lifetime reproductive success.
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The evolution of environmental and genetic sex determination in fluctuating environments.
Van Dooren, Tom J M; Leimar, Olof
2003-12-01
Twenty years ago, Bulmer and Bull suggested that disruptive selection, produced by environmental fluctuations, can result in an evolutionary transition from environmental sex determination (ESD) to genetic sex determination (GSD). We investigated the feasibility of such a process, using mutation-limited adaptive dynamics and individual-based computer simulations. Our model describes the evolution of a reaction norm for sex determination in a metapopulation setting with partial migration and variation in an environmental variable both within and between local patches. The reaction norm represents the probability of becoming a female as a function of environmental state and was modeled as a sigmoid function with two parameters, one giving the location (i.e., the value of the environmental variable for which an individual has equal chance of becoming either sex) and the other giving the slope of the reaction norm for that environment. The slope can be interpreted as being set by the level of developmental noise in morph determination, with less noise giving a steeper slope and a more switchlike reaction norm. We found convergence stable reaction norms with intermediate to large amounts of developmental noise for conditions characterized by low migration rates, small differential competitive advantages between the sexes over environments, and little variation between individual environments within patches compared to variation between patches. We also considered reaction norms with the slope parameter constrained to a high value, corresponding to little developmental noise. For these we found evolutionary branching in the location parameter and a transition from ESD toward GSD, analogous to the original analysis by Bulmer and Bull. Further evolutionary change, including dominance evolution, produced a polymorphism acting as a GSD system with heterogamety. Our results point to the role of developmental noise in the evolution of sex determination.
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Abdullah, N; Abdul Murad, N A; Mohd Haniff, E A; Syafruddin, S E; Attia, J; Oldmeadow, C; Kamaruddin, M A; Abd Jalal, N; Ismail, N; Ishak, M; Jamal, R; Scott, R J; Holliday, E G
2017-08-01
Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R 2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. The models including environmental risk factors only had pseudo R 2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10 -4 -4.83 × 10 -12 ) and increased the pseudo R 2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. Copyright © 2017 The Royal Society for Public Health. All rights reserved.
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The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China.
Di, Hui; Liu, Xingpeng; Zhang, Jiquan; Tong, Zhijun; Ji, Meichen
2018-03-15
Water environmental risk is the probability of the occurrence of events caused by human activities or the interaction of human activities and natural processes that will damage a water environment. This study proposed a water environmental risk index (WERI) model to assess the water environmental risk in the Yinma River Basin based on hazards, exposure, vulnerability, and regional management ability indicators in a water environment. The data for each indicator were gathered from 2000, 2005, 2010, and 2015 to assess the spatial and temporal variations in water environmental risk using particle swarm optimization and the analytic hierarchy process (PSO-AHP) method. The results showed that the water environmental risk in the Yinma River Basin decreased from 2000 to 2015. The risk level of the water environment was high in Changchun, while the risk levels in Yitong and Yongji were low. The research methods provide information to support future decision making by the risk managers in the Yinma River Basin, which is in a high-risk water environment. Moreover, water environment managers could reduce the risks by adjusting the indicators that affect water environmental risks.
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Micro-scale environmental variation amplifies physiological variation among individual mussels.
Jimenez, Ana Gabriela; Jayawardene, Sarah; Alves, Shaina; Dallmer, Jeremiah; Dowd, W Wesley
2015-12-07
The contributions of temporal and spatial environmental variation to physiological variation remain poorly resolved. Rocky intertidal zone populations are subjected to thermal variation over the tidal cycle, superimposed with micro-scale variation in individuals' body temperatures. Using the sea mussel (Mytilus californianus), we assessed the consequences of this micro-scale environmental variation for physiological variation among individuals, first by examining the latter in field-acclimatized animals, second by abolishing micro-scale environmental variation via common garden acclimation, and third by restoring this variation using a reciprocal outplant approach. Common garden acclimation reduced the magnitude of variation in tissue-level antioxidant capacities by approximately 30% among mussels from a wave-protected (warm) site, but it had no effect on antioxidant variation among mussels from a wave-exposed (cool) site. The field-acclimatized level of antioxidant variation was restored only when protected-site mussels were outplanted to a high, thermally stressful site. Variation in organismal oxygen consumption rates reflected antioxidant patterns, decreasing dramatically among protected-site mussels after common gardening. These results suggest a highly plastic relationship between individuals' genotypes and their physiological phenotypes that depends on recent environmental experience. Corresponding context-dependent changes in the physiological mean-variance relationships within populations complicate prediction of responses to shifts in environmental variability that are anticipated with global change. © 2015 The Author(s).
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Williams, Richard AJ; Peterson, A Townsend
2009-01-01
Background The emerging highly pathogenic avian influenza strain H5N1 ("HPAI-H5N1") has spread broadly in the past decade, and is now the focus of considerable concern. We tested the hypothesis that spatial distributions of HPAI-H5N1 cases are related consistently and predictably to coarse-scale environmental features in the Middle East and northeastern Africa. We used ecological niche models to relate virus occurrences to 8 km resolution digital data layers summarizing parameters of monthly surface reflectance and landform. Predictive challenges included a variety of spatial stratification schemes in which models were challenged to predict case distributions in broadly unsampled areas. Results In almost all tests, HPAI-H5N1 cases were indeed occurring under predictable sets of environmental conditions, generally predicted absent from areas with low NDVI values and minimal seasonal variation, and present in areas with a broad range of and appreciable seasonal variation in NDVI values. Although we documented significant predictive ability of our models, even between our study region and West Africa, case occurrences in the Arabian Peninsula appear to follow a distinct environmental regime. Conclusion Overall, we documented a variable environmental "fingerprint" for areas suitable for HPAI-H5N1 transmission. PMID:19619336
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Cornillon, P A; Pontier, D; Rochet, M J
2000-02-21
Comparative methods are used to investigate the attributes of present species or higher taxa. Difficulties arise from the phylogenetic heritage: taxa are not independent and neglecting phylogenetic inertia can lead to inaccurate results. Within-species variations in life-history traits are also not negligible, but most comparative methods are not designed to take them into account. Taxa are generally described by a single value for each trait. We have developed a new model which permits the incorporation of both the phylogenetic relationships among populations and within-species variations. This is an extension of classical autoregressive models. This family of models was used to study the effect of fishing on six demographic traits measured on 77 populations of teleost fishes. Copyright 2000 Academic Press.
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Nuclear DNA contents of Echinchloa crus-galli and its Gaussian relationships with environments
NASA Astrophysics Data System (ADS)
Li, Dan-Dan; Lu, Yong-Liang; Guo, Shui-Liang; Yin, Li-Ping; Zhou, Ping; Lou, Yu-Xia
2017-02-01
Previous studies on plant nuclear DNA content variation and its relationships with environmental gradients produced conflicting results. We speculated that the relationships between nuclear DNA content of a widely-distributed species and its environmental gradients might be non-linear if it was sampled in a large geographical gradient. Echinochloa crus-galli (L.) P. Beauv. is a worldwide species, but without documents on its intraspecific variation of nuclear DNA content. Our objectives are: 1) to detect intraspecific variation scope of E. crus-galli in its nuclear DNA content, and 2) to testify whether nuclear DNA content of the species changes with environmental gradients following Gaussian models if its populations were sampled in a large geographical gradient. We collected seeds of 36 Chinese populations of E. crus-galli across a wide geographical gradient, and sowed them in a homogeneous field to get their offspring to determine their nuclear DNA content. We analyzed the relationships of nuclear DNA content of these populations with latitude, longitude, and nineteen bioclimatic variables by using Gaussian and linear models. (1) Nuclear DNA content varied from 2.113 to 2.410 pg among 36 Chinese populations of E. crus-galli, with a mean value of 2.256 pg. (2) Gaussian correlations of nuclear DNA content (y) with geographical gradients were detected, with latitude (x) following y = 2.2923*e -(x - 24.9360)2/2*63.79452 (r = 0.546, P < 0.001), and with longitude (x) following y = 2.2933*e -(x - 116.1801)2/2*44.74502 (r = 0.672, P < 0.001). (3) Among the nineteen bioclimatic variables, except temperature isothermality, precipitations of the wettest month, the wettest quarter and the warmest quarter, the others could be better fit with nuclear DNA content by using Gaussian models than by linear models. There exists intra-specific variation among 36 Chinese populations of E. crus-galli, Gaussian models could be applied to fit the correlations of its Nuclear DNA content with geographical and most bioclimatic gradients.
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Incorporating temporal heterogeneity in environmental conditions into a somatic growth model
Dzul, Maria C.; Yackulic, Charles B.; Korman, Josh; Yard, Michael D.; Muehlbauer, Jeffrey D.
2017-01-01
Evaluating environmental effects on fish growth can be challenging because environmental conditions may vary at relatively fine temporal scales compared to sampling occasions. Here we develop a Bayesian state-space growth model to evaluate effects of monthly environmental data on growth of fish that are observed less frequently (e.g., from mark-recapture data where time between captures can range from months to years). We assess effects of temperature, turbidity duration, food availability, flow variability, and trout abundance on subadult humpback chub (Gila cypha) growth in two rivers, the Colorado River (CR) and the Little Colorado River (LCR), and we use out-of-sample prediction to rank competing models. Environmental covariates explained a high proportion of the variation in growth in both rivers; however, the best growth models were river-specific and included either positive temperature and turbidity duration effects (CR) or positive temperature and food availability effects (LCR). Our approach to analyzing environmental controls on growth should be applicable in other systems where environmental data vary over relatively short time scales compared to animal observations.
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Heritability of the Number of Teeth in Middle-Aged and Older Danish Twins.
Kurushima, Y; Silventoinen, K; Dokkedal, U; Skytthe, A; Mucci, L A; Christensen, K; Hjelmborg, J V B
2017-12-01
Tooth loss is a common health concern in older adults. We aimed to estimate the relative contributions of genetic and environmental factors to the variation in the number of teeth in middle-aged and older populations using a population-based cohort of Danish twins. The study included 5,269 Danish middle-aged or older twins who provided data on the number of teeth at baseline by structured interviews. The data were analyzed using univariate liability threshold modeling, stratified by sex and age, to estimate familial risk of tooth loss as well as estimates of heritability. In the whole cohorts, 23% of participants were edentate and 53% had retained 20 or more teeth. A statistical model including additive genetic factors and environmental factors partly shared by co-twins and partly unique to each individual twin gave the best statistical fit for the number of teeth in both age categories as well as in men and women. Overall, additive genetic factors explained 36% (95% confidence interval [CI]: 23% to 49%), common environmental factors 20% (95% CI: 9% to 31%), and unique environmental factors 44% (95% CI: 40% to 48%) of the total variation of the number of teeth. This study indicates that a substantial part of the variation in tooth loss is explained by genetic as well as environmental factors shared by co-twins. Our results implied that family background importantly affects tooth loss in both the middle-aged and the older populations. Family history is thus an important factor to take into account in dental health care.
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Yokoyama, Yoshie; Jelenkovic, Aline; Hur, Yoon-Mi; Sund, Reijo; Fagnani, Corrado; Stazi, Maria A; Brescianini, Sonia; Ji, Fuling; Ning, Feng; Pang, Zengchang; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Rebato, Esther; Hopper, John L; Cutler, Tessa L; Saudino, Kimberly J; Nelson, Tracy L; Whitfield, Keith E; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Llewellyn, Clare H; Fisher, Abigail; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Bartels, Meike; van Beijsterveldt, Catharina E M; Willemsen, Gonneke; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas S; Craig, Jeffrey M; Saffery, Richard; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Haworth, Claire M A; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Rasmussen, Finn; Tynelius, Per; Tarnoki, Adam D; Tarnoki, David L; Ooki, Syuichi; Rose, Richard J; Pietiläinen, Kirsi H; Sørensen, Thorkild I A; Boomsma, Dorret I; Kaprio, Jaakko; Silventoinen, Karri
2018-05-19
The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birthweight, length and ponderal index (PI) across geographical-cultural regions (Europe, North America and Australia, and East Asia) and across birth cohorts, and how gestational age modifies these effects. Data from 26 twin cohorts in 16 countries including 57 613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modelling. The variance of birthweight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographical-cultural regions, but shared environmental variance was smaller in East Asia than in Europe and North America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-99 onwards compared with the birth cohorts from 1970-79 to 1980-89. The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographical-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.
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Variational approach to direct and inverse problems of atmospheric pollution studies
NASA Astrophysics Data System (ADS)
Penenko, Vladimir; Tsvetova, Elena; Penenko, Alexey
2016-04-01
We present the development of a variational approach for solving interrelated problems of atmospheric hydrodynamics and chemistry concerning air pollution transport and transformations. The proposed approach allows us to carry out complex studies of different-scale physical and chemical processes using the methods of direct and inverse modeling [1-3]. We formulate the problems of risk/vulnerability and uncertainty assessment, sensitivity studies, variational data assimilation procedures [4], etc. A computational technology of constructing consistent mathematical models and methods of their numerical implementation is based on the variational principle in the weak constraint formulation specifically designed to account for uncertainties in models and observations. Algorithms for direct and inverse modeling are designed with the use of global and local adjoint problems. Implementing the idea of adjoint integrating factors provides unconditionally monotone and stable discrete-analytic approximations for convection-diffusion-reaction problems [5,6]. The general framework is applied to the direct and inverse problems for the models of transport and transformation of pollutants in Siberian and Arctic regions. The work has been partially supported by the RFBR grant 14-01-00125 and RAS Presidium Program I.33P. References: 1. V. Penenko, A.Baklanov, E. Tsvetova and A. Mahura . Direct and inverse problems in a variational concept of environmental modeling //Pure and Applied Geoph.(2012) v.169: 447-465. 2. V. V. Penenko, E. A. Tsvetova, and A. V. Penenko Development of variational approach for direct and inverse problems of atmospheric hydrodynamics and chemistry, Izvestiya, Atmospheric and Oceanic Physics, 2015, Vol. 51, No. 3, p. 311-319, DOI: 10.1134/S0001433815030093. 3. V.V. Penenko, E.A. Tsvetova, A.V. Penenko. Methods based on the joint use of models and observational data in the framework of variational approach to forecasting weather and atmospheric composition quality// Russian meteorology and hydrology, V. 40, Issue: 6, Pages: 365-373, DOI: 10.3103/S1068373915060023. 4. A.V. Penenko and V.V. Penenko. Direct data assimilation method for convection-diffusion models based on splitting scheme. Computational technologies, 19(4):69-83, 2014. 5. V.V. Penenko, E.A. Tsvetova, A.V. Penenko Variational approach and Euler's integrating factors for environmental studies// Computers and Mathematics with Applications, 2014, V.67, Issue 12, Pages 2240-2256, DOI:10.1016/j.camwa.2014.04.004 6. V.V. Penenko, E.A. Tsvetova. Variational methods of constructing monotone approximations for atmospheric chemistry models // Numerical analysis and applications, 2013, V. 6, Issue 3, pp 210-220, DOI 10.1134/S199542391303004X
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Global variability in leaf respiration in relation to climate and leaf traits
NASA Astrophysics Data System (ADS)
Atkin, Owen K.
2015-04-01
Leaf respiration plays a vital role in regulating ecosystem functioning and the Earth's climate. Because of this, it is imperative that that Earth-system, climate and ecosystem-level models be able to accurately predict variations in rates of leaf respiration. In the field of photosynthesis research, the F/vC/B model has enabled modellers to accurately predict variations in photosynthesis through time and space. By contrast, we lack an equivalent biochemical model to predict variations in leaf respiration. Consequently, we need to rely on phenomenological approaches to model variations in respiration across the Earth's surface. Such approaches require that we develop a thorough understanding of how rates of respiration vary among species and whether global environmental gradients play a role in determining variations in leaf respiration. Dealing with these issues requires that data sets be assembled on rates of leaf respiration in biomes across the Earth's surface. In this talk, I will use a newly-assembled global database on leaf respiration and associated traits (including photosynthesis) to highlight variation in leaf respiration (and the balance between respiration and photosynthesis) across global gradients in growth temperature and aridity.
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Luo, Zhenhua; Tang, Songhua; Li, Chunwang; Fang, Hongxia; Hu, Huijian; Yang, Ji; Ding, Jingjing; Jiang, Zhigang
2012-01-01
Explaining species richness patterns is a central issue in biogeography and macroecology. Several hypotheses have been proposed to explain the mechanisms driving biodiversity patterns, but the causes of species richness gradients remain unclear. In this study, we aimed to explain the impacts of energy, environmental stability, and habitat heterogeneity factors on variation of vertebrate species richness (VSR), based on the VSR pattern in China, so as to test the energy hypothesis, the environmental stability hypothesis, and the habitat heterogeneity hypothesis. A dataset was compiled containing the distributions of 2,665 vertebrate species and eleven ecogeographic predictive variables in China. We grouped these variables into categories of energy, environmental stability, and habitat heterogeneity and transformed the data into 100 × 100 km quadrat systems. To test the three hypotheses, AIC-based model selection was carried out between VSR and the variables in each group and correlation analyses were conducted. There was a decreasing VSR gradient from the southeast to the northwest of China. Our results showed that energy explained 67.6% of the VSR variation, with the annual mean temperature as the main factor, which was followed by annual precipitation and NDVI. Environmental stability factors explained 69.1% of the VSR variation and both temperature annual range and precipitation seasonality had important contributions. By contrast, habitat heterogeneity variables explained only 26.3% of the VSR variation. Significantly positive correlations were detected among VSR, annual mean temperature, annual precipitation, and NDVI, whereas the relationship of VSR and temperature annual range was strongly negative. In addition, other variables showed moderate or ambiguous relations to VSR. The energy hypothesis and the environmental stability hypothesis were supported, whereas little support was found for the habitat heterogeneity hypothesis.
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Luo, Zhenhua; Tang, Songhua; Li, Chunwang; Fang, Hongxia; Hu, Huijian; Yang, Ji; Ding, Jingjing; Jiang, Zhigang
2012-01-01
Background Explaining species richness patterns is a central issue in biogeography and macroecology. Several hypotheses have been proposed to explain the mechanisms driving biodiversity patterns, but the causes of species richness gradients remain unclear. In this study, we aimed to explain the impacts of energy, environmental stability, and habitat heterogeneity factors on variation of vertebrate species richness (VSR), based on the VSR pattern in China, so as to test the energy hypothesis, the environmental stability hypothesis, and the habitat heterogeneity hypothesis. Methodology/Principal Findings A dataset was compiled containing the distributions of 2,665 vertebrate species and eleven ecogeographic predictive variables in China. We grouped these variables into categories of energy, environmental stability, and habitat heterogeneity and transformed the data into 100×100 km quadrat systems. To test the three hypotheses, AIC-based model selection was carried out between VSR and the variables in each group and correlation analyses were conducted. There was a decreasing VSR gradient from the southeast to the northwest of China. Our results showed that energy explained 67.6% of the VSR variation, with the annual mean temperature as the main factor, which was followed by annual precipitation and NDVI. Environmental stability factors explained 69.1% of the VSR variation and both temperature annual range and precipitation seasonality had important contributions. By contrast, habitat heterogeneity variables explained only 26.3% of the VSR variation. Significantly positive correlations were detected among VSR, annual mean temperature, annual precipitation, and NDVI, whereas the relationship of VSR and temperature annual range was strongly negative. In addition, other variables showed moderate or ambiguous relations to VSR. Conclusions/Significance The energy hypothesis and the environmental stability hypothesis were supported, whereas little support was found for the habitat heterogeneity hypothesis. PMID:22530038
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Silventoinen, Karri; Jelenkovic, Aline; Sund, Reijo; Hur, Yoon-Mi; Yokoyama, Yoshie; Honda, Chika; Hjelmborg, Jacob vB; Möller, Sören; Ooki, Syuichi; Aaltonen, Sari; Ji, Fuling; Ning, Feng; Pang, Zengchang; Rebato, Esther; Busjahn, Andreas; Kandler, Christian; Saudino, Kimberly J; Jang, Kerry L; Cozen, Wendy; Hwang, Amie E; Mack, Thomas M; Gao, Wenjing; Yu, Canqing; Li, Liming; Corley, Robin P; Huibregtse, Brooke M; Christensen, Kaare; Skytthe, Axel; Kyvik, Kirsten O; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth Jf; Heikkilä, Kauko; Wardle, Jane; Llewellyn, Clare H; Fisher, Abigail; McAdams, Tom A; Eley, Thalia C; Gregory, Alice M; He, Mingguang; Ding, Xiaohu; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Tarnoki, Adam D; Tarnoki, David L; Stazi, Maria A; Fagnani, Corrado; D'Ippolito, Cristina; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Burt, S Alexandra; Klump, Kelly L; Silberg, Judy L; Eaves, Lindon J; Maes, Hermine H; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Gatz, Margaret; Butler, David A; Bartels, Meike; van Beijsterveldt, Toos Cem; Craig, Jeffrey M; Saffery, Richard; Freitas, Duarte L; Maia, José Antonio; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Martin, Nicholas G; Medland, Sarah E; Montgomery, Grant W; Chong, Youngsook; Swan, Gary E; Krasnow, Ruth; Magnusson, Patrik Ke; Pedersen, Nancy L; Tynelius, Per; Lichtenstein, Paul; Haworth, Claire Ma; Plomin, Robert; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Harden, K Paige; Tucker-Drob, Elliot M; Öncel, Sevgi Y; Aliev, Fazil; Spector, Timothy; Mangino, Massimo; Lachance, Genevieve; Baker, Laura A; Tuvblad, Catherine; Duncan, Glen E; Buchwald, Dedra; Willemsen, Gonneke; Rasmussen, Finn; Goldberg, Jack H; Sørensen, Thorkild Ia; Boomsma, Dorret I; Kaprio, Jaakko
2016-08-01
Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking. We analyzed the genetic and environmental contributions to BMI variation from infancy to early adulthood and the ways they differ by sex and geographic regions representing high (North America and Australia), moderate (Europe), and low levels (East Asia) of obesogenic environments. Data were available for 87,782 complete twin pairs from 0.5 to 19.5 y of age from 45 cohorts. Analyses were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and environmental components through genetic structural equation modeling. The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive genetic factors was lowest at 4 y of age in boys (a(2) = 0.42) and girls (a(2) = 0.41) and then generally increased to 0.75 in both sexes at 19 y of age. This was because of a stronger influence of environmental factors shared by co-twins in midchildhood. After 15 y of age, the effect of shared environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained roughly similar across different regions. Environmental factors shared by co-twins affect BMI in childhood, but little evidence for their contribution was found in late adolescence. Our results suggest that genetic factors play a major role in the variation of BMI in adolescence among populations of different ethnicities exposed to different environmental factors related to obesity. © 2016 American Society for Nutrition.
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Senescence in the wild: Insights from a long-term study on Seychelles warblers.
Hammers, Martijn; Kingma, Sjouke A; Bebbington, Kat; van de Crommenacker, Janske; Spurgin, Lewis G; Richardson, David S; Burke, Terry; Dugdale, Hannah L; Komdeur, Jan
2015-11-01
Senescence--the progressive age-dependent decline in performance--occurs in most organisms. There is considerable variation in the onset and rate of senescence between and within species. Yet the causes of this variation are still poorly understood, despite being central to understanding the evolution of senescence. Long-term longitudinal studies on wild animals are extremely well-suited to studying the impact of environmental and individual characteristics (and the interaction between the two) on senescence, and can help us to understand the mechanisms that shape the evolution of senescence. In this review, we summarize and discuss the insights gained from our comprehensive long-term individual-based study of the Seychelles warbler (Acrocephalus sechellensis). This species provides an excellent model system in which to investigate the evolution of senescence in the wild. We found that Seychelles warblers show senescent declines in survival and reproduction, and discuss how individual characteristics (body condition, body size) and environmental effects (low- versus high-quality environments) may affect the onset and rate of senescence. Further, we highlight the evidence for trade-offs between early-life investment and senescence. We describe how key cellular and physiological processes (oxidative stress and telomere shortening) underpinning senescence are affected by individual and environmental characteristics in the Seychelles warbler (e.g. food availability, reproductive investment, disease) and we discuss how such physiological variation may mediate the relationship between environmental characteristics and senescence. Based on our work using Seychelles warblers as a model system, we show how insights from long-term studies of wild animals may help unravel the causes of the remarkable variation in senescence observed in natural systems, and highlight areas for promising future research.
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Variation in Airway Responsiveness of Male C57BL/6 Mice from 5 Vendors
Chang, Herng-Yu Sucie; Mitzner, Wayne; Watson, Julie
2012-01-01
Mice are now the most commonly used animal model for the study of asthma. The mouse asthma model has many characteristics of the human pathology, including allergic sensitization and airway hyperresponsiveness. Inbred strains are commonly used to avoid variations due to genetic background, but variations due to rearing environment are not as well recognized. After a change in mouse vendors and a switch from C57BL/6J mice to C57BL/6N mice, we noted significant differences in airway responsiveness between the substrains. To further investigate the effect of vendor, we tested C57BL/6N mice from 3 other vendors and found significant differences between several of the substrains. To test whether this difference was due to genetic drift or rearing environment, we purchased new groups of mice from all 5 vendors, bred them in separate vendor-specific groups under uniform environmental conditions, and tested male first generation (F1) offspring at 8 to 10 wk of age. These F1 mice showed no significant differences in airway responsiveness, indicating that the rearing environment rather than genetic differences was responsible for the initial variation in pulmonary phenotype. The environmental factors that caused the phenotypic variation are unknown. However, differences between vendor in feed components, bedding type, or microbiome could have contributed. Whatever the basis, investigators using mouse models of asthma should be cautious in comparing data from mice obtained from different vendors. PMID:23043804
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NASA Astrophysics Data System (ADS)
Miao, Guofang; Noormets, Asko; Domec, Jean-Christophe; Trettin, Carl C.; McNulty, Steve G.; Sun, Ge; King, John S.
2013-12-01
and environmental pressures on wetland hydrology may trigger changes in carbon (C) cycling, potentially exposing vast amounts of soil C to rapid decomposition. We measured soil CO2 efflux (Rs) continuously from 2009 to 2010 in a lower coastal plain forested wetland in North Carolina, U.S., to characterize its main environmental drivers. To understand and quantify the spatial variation due to microtopography and associated differences in hydrology, measurements were conducted at three microsites along a microtopographic gradient. The seasonal hysteresis in Rs differed by microtopographic location and was caused by the transitions between flooded and nonflooded conditions. Because flooded Rs was small, we reported Rs dynamics mainly during nonflooded periods. A nested model, modified from conventional Q10 (temperature sensitivity) model with dynamic parameters, provided a significantly better simulation on the observed variation of Rs. The model performed better with daily data, indicating that soil temperature (Ts) and water table depth (WTD) were the primary drivers for seasonal variation. The diel variation of Rs was high and independent of Ts and WTD, which both had small diel variations, suggesting the likely association with plant activity. Overall, the site-average soil CO2 efflux was approximately 960-1103 g C m-2 yr-1 in 2010, of which 93% was released during nonflooded periods. Our study indicates that Rs is highly linked to hydroperiod and microtopography in forested wetlands and droughts in wetlands will accelerate soil C loss.
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Seeing the forest and the trees: multilevel models reveal both species and community patterns
Michelle M. Jackson; Monica G. Turner; Scott M. Pearson; Anthony R. Ives
2012-01-01
Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-...
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USDA-ARS?s Scientific Manuscript database
Feed efficiency (FE), characterized as the ability to convert feed nutrients into saleable milk or meat directly affects the profitability of dairy production, is of increasing economic importance in the dairy industry. We conjecture that FE is a complex trait whose variation and relationships or pa...
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Ip, Ryan H L; Li, W K; Leung, Kenneth M Y
2013-09-15
Large scale environmental remediation projects applied to sea water always involve large amount of capital investments. Rigorous effectiveness evaluations of such projects are, therefore, necessary and essential for policy review and future planning. This study aims at investigating effectiveness of environmental remediation using three different Seemingly Unrelated Regression (SUR) time series models with intervention effects, including Model (1) assuming no correlation within and across variables, Model (2) assuming no correlation across variable but allowing correlations within variable across different sites, and Model (3) allowing all possible correlations among variables (i.e., an unrestricted model). The results suggested that the unrestricted SUR model is the most reliable one, consistently having smallest variations of the estimated model parameters. We discussed our results with reference to marine water quality management in Hong Kong while bringing managerial issues into consideration. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Farno, E; Coventry, K; Slatter, P; Eshtiaghi, N
2018-06-15
Sludge pumps in wastewater treatment plants are often oversized due to uncertainty in calculation of pressure drop. This issue costs millions of dollars for industry to purchase and operate the oversized pumps. Besides costs, higher electricity consumption is associated with extra CO 2 emission which creates huge environmental impacts. Calculation of pressure drop via current pipe flow theory requires model estimation of flow curve data which depends on regression analysis and also varies with natural variation of rheological data. This study investigates impact of variation of rheological data and regression analysis on variation of pressure drop calculated via current pipe flow theories. Results compare the variation of calculated pressure drop between different models and regression methods and suggest on the suitability of each method. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Trejo, Laura; Alvarado-Cárdenas, Leonardo O; Scheinvar, Enrique; Eguiarte, Luis E
2016-06-01
Is there an association between bioclimatic variables and genetic variation within species? This question can be approached by a detailed analysis of population genetics parameters along environmental gradients in recently originated species (so genetic drift does not further obscure the patterns). The genus Agave, with more than 200 recent species encompassing a diversity of morphologies and distributional patterns, is an adequate system for such analyses. We studied Agave striata, a widely distributed species from the Chihuahuan Desert, with a distinctive iteroparous reproductive ecology and two recognized subspecies with clear morphological differences. We used population genetic analyses along with bioclimatic studies to understand the effect of environment on the genetic variation and differentiation of this species. We analyzed six populations of the subspecies A. striata subsp. striata, with a southern distribution, and six populations of A. striata subsp. falcata, with a northern distribution, using 48 ISSR loci and a total of 541 individuals (averaging 45 individuals per population). We assessed correlations between population genetics parameters (the levels of genetic variation and differentiation) and the bioclimatic variables of each population. We modeled each subspecies distribution and used linear correlations and multifactorial analysis of variance. Genetic variation (measured as expected heterozygosity) increased at higher latitudes. Higher levels of genetic variation in populations were associated with a higher variation in environmental temperature and lower precipitation. Stronger population differentiation was associated with wetter and more variable precipitation in the southern distribution of the species. The two subspecies have genetic differences, which coincide with their climatic differences and potential distributions. Differences in genetic variation among populations and the genetic differentiation between A. striata subsp. striata and A. striata subsp. falcata is correlated with differences in environmental climatic variables along their distribution. We found two distinct gene pools that suggest active differentiation and perhaps incipient speciation. The detected association between genetic variation and environment variables indicates that climatic variables are playing an important role in the differentiation of A. striata. © 2016 Botanical Society of America.
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Information theory and the neuropeptidergic regulation of seasonal reproduction in mammals and birds
Stevenson, Tyler J.; Ball, Gregory F.
2011-01-01
Seasonal breeding in the temperate zone is a dramatic example of a naturally occurring change in physiology and behaviour. Cues that predict periods of environmental amelioration favourable for breeding must be processed by the brain so that the appropriate responses in reproductive physiology can be implemented. The neural integration of several environmental cues converges on discrete hypothalamic neurons in order to regulate reproductive physiology. Gonadotrophin-releasing hormone-1 (GnRH1) and Kisspeptin (Kiss1) neurons in avian and mammalian species, respectively, show marked variation in expression that is positively associated with breeding state. We applied the constancy/contingency model of predictability to investigate how GnRH1 and Kiss1 integrate different environmental cues to regulate reproduction. We show that variation in GnRH1 from a highly seasonal avian species exhibits a predictive change that is primarily based on contingency information. Opportunistic species have low measures of predictability and exhibit a greater contribution of constancy information that is sex-dependent. In hamsters, Kiss1 exhibited a predictive change in expression that was predominantly contingency information and is anatomically localized. The model applied here provides a framework for studies geared towards determining the impact of variation in climate patterns to reproductive success in vertebrate species. PMID:21208957
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Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre
2014-12-05
Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.
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NASA Astrophysics Data System (ADS)
Liu, Lu; Hejazi, Mohamad; Li, Hongyi; Forman, Barton; Zhang, Xiao
2017-08-01
Previous modelling studies suggest that thermoelectric power generation is vulnerable to climate change, whereas studies based on historical data suggest the impact will be less severe. Here we explore the vulnerability of thermoelectric power generation in the United States to climate change by coupling an Earth system model with a thermoelectric power generation model, including state-level representation of environmental regulations on thermal effluents. We find that the impact of climate change is lower than in previous modelling estimates due to an inclusion of a spatially disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. More specifically, our results indicate that climate change alone may reduce average generating capacity by 2-3% by the 2060s, while reductions of up to 12% are expected if environmental requirements are enforced without waivers for thermal variation. Our work highlights the significance of accounting for legal constructs and underscores the effects of provisional variances in addition to environmental requirements.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Resco de Dios, Víctor; Gessler, Arthur; Ferrio, Juan Pedro
Background Molecular clocks drive oscillations in leaf photosynthesis, stomatal conductance, and other cell and leaf-level processes over ~24 h under controlled laboratory conditions. The influence of such circadian regulation over whole-canopy fluxes remains uncertain; diurnal CO 2 and H 2O vapor flux dynamics in the field are currently interpreted as resulting almost exclusively from direct physiological responses to variations in light, temperature and other environmental factors. We tested whether circadian regulation would affect plant and canopy gas exchange at the Montpellier European Ecotron. Canopy and leaf-level fluxes were constantly monitored under field-like environmental conditions, and under constant environmental conditions (nomore » variation in temperature, radiation, or other environmental cues). Results We show direct experimental evidence at canopy scales of the circadian regulation of daytime gas exchange: 20–79 % of the daily variation range in CO 2 and H 2O fluxes occurred under circadian entrainment in canopies of an annual herb (bean) and of a perennial shrub (cotton). We also observed that considering circadian regulation improved performance by 8–17 % in commonly used stomatal conductance models. Conclusions Our results show that circadian controls affect diurnal CO 2 and H 2O flux patterns in entire canopies in field-like conditions, and its consideration significantly improves model performance. Lastly, circadian controls act as a ‘memory’ of the past conditions experienced by the plant, which synchronizes metabolism across entire plant canopies.« less
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Resco de Dios, Víctor; Gessler, Arthur; Ferrio, Juan Pedro; ...
2016-10-20
Background Molecular clocks drive oscillations in leaf photosynthesis, stomatal conductance, and other cell and leaf-level processes over ~24 h under controlled laboratory conditions. The influence of such circadian regulation over whole-canopy fluxes remains uncertain; diurnal CO 2 and H 2O vapor flux dynamics in the field are currently interpreted as resulting almost exclusively from direct physiological responses to variations in light, temperature and other environmental factors. We tested whether circadian regulation would affect plant and canopy gas exchange at the Montpellier European Ecotron. Canopy and leaf-level fluxes were constantly monitored under field-like environmental conditions, and under constant environmental conditions (nomore » variation in temperature, radiation, or other environmental cues). Results We show direct experimental evidence at canopy scales of the circadian regulation of daytime gas exchange: 20–79 % of the daily variation range in CO 2 and H 2O fluxes occurred under circadian entrainment in canopies of an annual herb (bean) and of a perennial shrub (cotton). We also observed that considering circadian regulation improved performance by 8–17 % in commonly used stomatal conductance models. Conclusions Our results show that circadian controls affect diurnal CO 2 and H 2O flux patterns in entire canopies in field-like conditions, and its consideration significantly improves model performance. Lastly, circadian controls act as a ‘memory’ of the past conditions experienced by the plant, which synchronizes metabolism across entire plant canopies.« less
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Gravel, Dominique; Beaudet, Marilou; Messier, Christian
2008-10-01
Understanding coexistence of highly shade-tolerant tree species is a longstanding challenge for forest ecologists. A conceptual model for the coexistence of sugar maple (Acer saccharum) and American beech (Fagus grandibfolia) has been proposed, based on a low-light survival/high-light growth trade-off, which interacts with soil fertility and small-scale spatiotemporal variation in the environment. In this study, we first tested whether the spatial distribution of seedlings and saplings can be predicted by the spatiotemporal variability of light availability and soil fertility, and second, the manner in which the process of environmental filtering changes with regeneration size. We evaluate the support for this hypothesis relative to the one for a neutral model, i.e., for seed rain density predicted from the distribution of adult trees. To do so, we performed intensive sampling over 86 quadrats (5 x 5 m) in a 0.24-ha plot in a mature maple-beech community in Quebec, Canada. Maple and beech abundance, soil characteristics, light availability, and growth history (used as a proxy for spatiotemporal variation in light availability) were finely measured to model variation in sapling composition across different size classes. Results indicate that the variables selected to model species distribution do effectively change with size, but not as predicted by the conceptual model. Our results show that variability in the environment is not sufficient to differentiate these species' distributions in space. Although species differ in their spatial distribution in the small size classes, they tend to correlate at the larger size class in which recruitment occurs. Overall, the results are not supportive of a model of coexistence based on small-scale variations in the environment. We propose that, at the scale of a local stand, the lack of fit of the model could result from the high similarity of species in the range of environmental conditions encountered, and we suggest that coexistence would be stable only at larger spatial scales at which variability in the environment is greater.
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Verheijen, Lieneke M; Aerts, Rien; Brovkin, Victor; Cavender-Bares, Jeannine; Cornelissen, Johannes H C; Kattge, Jens; van Bodegom, Peter M
2015-08-01
Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called 'habitat filtering', is an important ecological assembly rule and allows for determination of global scale trait-environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO2 , were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment-driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr(-1) ) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid- and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait-induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change. © 2015 John Wiley & Sons Ltd.
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Lotka-Volterra systems in environments with randomly disordered temporal periodicity
NASA Astrophysics Data System (ADS)
Naess, Arvid; Dimentberg, Michael F.; Gaidai, Oleg
2008-08-01
A generalized Lotka-Volterra model for a pair of interacting populations of predators and prey is studied. The model accounts for the prey’s interspecies competition and therefore is asymptotically stable, whereas its oscillatory behavior is induced by temporal variations in environmental conditions simulated by those in the prey’s reproduction rate. Two models of the variations are considered, each of them combining randomness with “hidden” periodicity. The stationary joint probability density function (PDF) of the number of predators and prey is calculated numerically by the path integration (PI) method based on the use of characteristic functions and the fast Fourier transform. The numerical results match those for the asymptotic case of white-noise variations for which an analytical solution is available. Several examples are studied, with calculations of important characteristics of oscillations, for example the expected rate of up-crossings given the level of the predator number. The calculated PDFs may be of predominantly random (unimodal) or predominantly periodic nature (bimodal). Thus, the PI method has been demonstrated to be a powerful tool for studies of the dynamics of predator-prey pairs. The method captures the random oscillations as observed in nature, taking into account potential periodicity in the environmental conditions.
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Lotka-Volterra systems in environments with randomly disordered temporal periodicity.
Naess, Arvid; Dimentberg, Michael F; Gaidai, Oleg
2008-08-01
A generalized Lotka-Volterra model for a pair of interacting populations of predators and prey is studied. The model accounts for the prey's interspecies competition and therefore is asymptotically stable, whereas its oscillatory behavior is induced by temporal variations in environmental conditions simulated by those in the prey's reproduction rate. Two models of the variations are considered, each of them combining randomness with "hidden" periodicity. The stationary joint probability density function (PDF) of the number of predators and prey is calculated numerically by the path integration (PI) method based on the use of characteristic functions and the fast Fourier transform. The numerical results match those for the asymptotic case of white-noise variations for which an analytical solution is available. Several examples are studied, with calculations of important characteristics of oscillations, for example the expected rate of up-crossings given the level of the predator number. The calculated PDFs may be of predominantly random (unimodal) or predominantly periodic nature (bimodal). Thus, the PI method has been demonstrated to be a powerful tool for studies of the dynamics of predator-prey pairs. The method captures the random oscillations as observed in nature, taking into account potential periodicity in the environmental conditions.
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Katapally, Tarun Reddy; Rainham, Daniel; Muhajarine, Nazeem
2015-11-30
In curbing physical inactivity, as behavioural interventions directed at individuals have not produced a population-level change, an ecological perspective called active living research has gained prominence. However, active living research consistently underexplores the role played by a perennial phenomenon encompassing all other environmental exposures-variation in weather. After factoring in weather variation, this study investigated the influence of diverse environmental exposures (including urban design and built environment) on the accumulation of globally recommended moderate to vigorous physical activity levels (MVPA) in children. This cross-sectional observational study is part of an active living initiative set in the Canadian prairie city of Saskatoon. As part of this study, Saskatoon's neighbourhoods were classified based on urban street design into grid-pattern, fractured grid-pattern and curvilinear types of neighbourhoods. Moreover, diverse environmental exposures were measured including, neighbourhood built environment, and neighbourhood and household socioeconomic environment. Actical accelerometers were deployed between April and June 2010 (spring-summer) to derive MVPA of 331 10-14-year-old children in 25 1-week cycles. Each cycle of accelerometry was conducted on a different cohort of children within the total sample and matched with weather data obtained from Environment Canada. Multilevel modelling using Hierarchical Linear and Non-linear Modelling software was conducted by factoring in weather variation to depict the influence of diverse environmental exposures on the accumulation of recommended MVPA. Urban design, including diversity of destinations within neighbourhoods played a significant role in the accumulation of MVPA. After factoring in weather variation, it was observed that children living in neighbourhoods closer to the city centre (with higher diversity of destinations) were more likely to accumulate recommended MVPA. The findings indicate that after factoring in weather variation, certain types of urban design are more likely to be associated with MVPA accumulation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
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NASA Astrophysics Data System (ADS)
Bodegom, P. V.
2015-12-01
Most global vegetation models used to evaluate climate change impacts rely on plant functional types to describe vegetation responses to environmental stresses. In a traditional set-up in which vegetation characteristics are considered constant within a vegetation type, the possibility to implement and infer feedback mechanisms are limited as feedback mechanisms will likely involve a changing expression of community trait values. Based on community assembly concepts, we implemented functional trait-environment relationships into a global dynamic vegetation model to quantitatively assess this feature. For the current climate, a different global vegetation distribution was calculated with and without the inclusion of trait variation, emphasizing the importance of feedbacks -in interaction with competitive processes- for the prevailing global patterns. These trait-environmental responses do, however, not necessarily imply adaptive responses of vegetation to changing conditions and may locally lead to a faster turnover in vegetation upon climate change. Indeed, when running climate projections, simulations with trait variation did not yield a more stable or resilient vegetation than those without. Through the different feedback expressions, global and regional carbon and water fluxes were -however- strongly altered. At a global scale, model projections suggest an increased productivity and hence an increased carbon sink in the next decades to come, when including trait variation. However, by the end of the century, a reduced carbon sink is projected. This effect is due to a downregulation of photosynthesis rates, particularly in the tropical regions, even when accounting for CO2-fertilization effects. Altogether, the various global model simulations suggest the critical importance of including vegetation functional responses to changing environmental conditions to grasp terrestrial feedback mechanisms at global scales in the light of climate change.
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NASA Astrophysics Data System (ADS)
Ramanujam, Padma
1999-08-01
Public concern over the state of the environment has grown over the past decade. All indications are that this concern will continue to influence policy making into the foreseeable future. Road transport is seen as the major contributor to environmental degradation. Transportation planners around the world face the question: cleaner air and/or faster commutes? While individual vehicles can be made more environmentally friendly, the sheer scale of growth in world-wide vehicle numbers is projected to cause significant environmental degradation in the longer run, and in the absence of newer and stricter polices. It is a challenge for governments to find policies that ensure congestion-free metropolitan areas while guaranteeing both critical environmental quality levels and a sufficient infrastructure access to all groups involved. The objective of the dissertation is to provide a mathematical framework to study transportation policy models for the purpose of controlling congestion and pollution. Towards this objective. a series of transportation policy models are developed to study travel behavior and to quantity the reductions in congestion and automobile emissions. The dissertation begins with a brief historical overview of some of the pioneering works in urban transportation economics and later presents the theoretical foundation for the transportation policy models developed. The dissertation introduces single modal and multimodal transportation network policy models that accomplish road pricing with the imposition of goal targets on link loads. as well as, integrated traffic equilibrium models with marketable mobile emission permits. Furthermore, equilibrium conditions are derived for each model, and both qualitative analysis and computational procedures are studied. Finally, the dissertation concludes with a comparative study of the relationship between regulatory pricing models and marketable emission permit transportation models and a discussion on key factors that influence implementation of the proposed policy models. The framework of variational inequalities has been utilized in our dissertation, because it is ideal for equilibrium systems. With the addition of pricing policy interventions and the integration of marketable mobile emission permits, traffic equilibrium models become extremely complex. Consequently, the computation of the equilibrium is made more difficult. However, it is shown in the dissertation that in addition to pricing interventions and the integration of a marketable emission permit system that it is possible to incorporate multiple modes of transport and even to handle the issue of noncompliance, using the framework of variational inequalities.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhou, Sha; Yu, Bofu; Schwalm, Christopher R.
Here, water use efficiency (WUE), defined as the ratio of gross primary productivity and evapotranspiration at the ecosystem scale, is a critical variable linking the carbon and water cycles. Incorporating a dependency on vapor pressure deficit, apparent underlying WUE (uWUE) provides a better indicator of how terrestrial ecosystems respond to environmental changes than other WUE formulations. Here we used 20th century simulations from four terrestrial biosphere models to develop a novel variance decomposition method. With this method, we attributed variations in apparent uWUE to both the trend and interannual variation of environmental drivers. The secular increase in atmospheric CO 2more » explained a clear majority of total variation (66 ± 32%: mean ± one standard deviation), followed by positive trends in nitrogen deposition and climate, as well as a negative trend in land use change. In contrast, interannual variation was mostly driven by interannual climate variability. To analyze the mechanism of the CO 2 effect, we partitioned the apparent uWUE into the transpiration ratio (transpiration over evapotranspiration) and potential uWUE. The relative increase in potential uWUE parallels that of CO 2, but this direct CO 2 effect was offset by 20 ± 4% by changes in ecosystem structure, that is, leaf area index for different vegetation types. However, the decrease in transpiration due to stomatal closure with rising CO 2 was reduced by 84% by an increase in leaf area index, resulting in small changes in the transpiration ratio. CO 2 concentration thus plays a dominant role in driving apparent uWUE variations over time, but its role differs for the two constituent components: potential uWUE and transpiration.« less
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NASA Astrophysics Data System (ADS)
Zhou, Sha; Yu, Bofu; Schwalm, Christopher R.; Ciais, Philippe; Zhang, Yao; Fisher, Joshua B.; Michalak, Anna M.; Wang, Weile; Poulter, Benjamin; Huntzinger, Deborah N.; Niu, Shuli; Mao, Jiafu; Jain, Atul; Ricciuto, Daniel M.; Shi, Xiaoying; Ito, Akihiko; Wei, Yaxing; Huang, Yuefei; Wang, Guangqian
2017-11-01
Water use efficiency (WUE), defined as the ratio of gross primary productivity and evapotranspiration at the ecosystem scale, is a critical variable linking the carbon and water cycles. Incorporating a dependency on vapor pressure deficit, apparent underlying WUE (uWUE) provides a better indicator of how terrestrial ecosystems respond to environmental changes than other WUE formulations. Here we used 20th century simulations from four terrestrial biosphere models to develop a novel variance decomposition method. With this method, we attributed variations in apparent uWUE to both the trend and interannual variation of environmental drivers. The secular increase in atmospheric CO2 explained a clear majority of total variation (66 ± 32%: mean ± one standard deviation), followed by positive trends in nitrogen deposition and climate, as well as a negative trend in land use change. In contrast, interannual variation was mostly driven by interannual climate variability. To analyze the mechanism of the CO2 effect, we partitioned the apparent uWUE into the transpiration ratio (transpiration over evapotranspiration) and potential uWUE. The relative increase in potential uWUE parallels that of CO2, but this direct CO2 effect was offset by 20 ± 4% by changes in ecosystem structure, that is, leaf area index for different vegetation types. However, the decrease in transpiration due to stomatal closure with rising CO2 was reduced by 84% by an increase in leaf area index, resulting in small changes in the transpiration ratio. CO2 concentration thus plays a dominant role in driving apparent uWUE variations over time, but its role differs for the two constituent components: potential uWUE and transpiration.
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Epidemiological, evolutionary and co-evolutionary implications of context-dependent parasitism
Vale, Pedro F.; Wilson, Alastair J.; Best, Alex; Boots, Mike; Little, Tom J.
2013-01-01
Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster growing parasites do not appear to cause more damage and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa we show how easily an interaction can shift from a severe interaction, i.e. when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modelling pathogen evolution and disease spread under different levels of infection severity, and find that environmental shifts that promote tolerance ultimately result in populations harbouring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus our results suggest two mechanisms that could underlie co-evolutionary hot- and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection. PMID:21460572
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Epidemiological, evolutionary, and coevolutionary implications of context-dependent parasitism.
Vale, Pedro F; Wilson, Alastair J; Best, Alex; Boots, Mike; Little, Tom J
2011-04-01
Abstract Victims of infection are expected to suffer increasingly as parasite population growth increases. Yet, under some conditions, faster-growing parasites do not appear to cause more damage, and infections can be quite tolerable. We studied these conditions by assessing how the relationship between parasite population growth and host health is sensitive to environmental variation. In experimental infections of the crustacean Daphnia magna and its bacterial parasite Pasteuria ramosa, we show how easily an interaction can shift from a severe interaction, that is, when host fitness declines substantially with each unit of parasite growth, to a tolerable relationship by changing only simple environmental variables: temperature and food availability. We explored the evolutionary and epidemiological implications of such a shift by modeling pathogen evolution and disease spread under different levels of infection severity and found that environmental shifts that promote tolerance ultimately result in populations harboring more parasitized individuals. We also find that the opportunity for selection, as indicated by the variance around traits, varied considerably with the environmental treatment. Thus, our results suggest two mechanisms that could underlie coevolutionary hotspots and coldspots: spatial variation in tolerance and spatial variation in the opportunity for selection.
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Thermal and hydric aspects of environmental heterogeneity in the pitcher plant mosquito
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kingsolver, J.G.
1979-12-01
In an attempt to define environmental heteogeneity and uncertainty in a meaningful manner, thermal and hydric aspects of the microenvironment of the pitcher plant mosquito (Wyeomyia smithii) were studied. Mechanistic mass and energy balance models were developed to predict surface temperatures in a Sphagnum bog and temperatures and water losses in Sarracenia purpurea pitchers. Field tests indicate that the models predicted surface and pitcher temperatures within 2 to 3/sup 0/C, and hourly and daily water losses from pitchers to within 30%, using only basic meteorological data as inputs. Experiments and observations in a natural population of W. smithii in northernmore » Michigan, USA revealed significant differences in larval developmental rate, voltinism, and larval mortality due to microclimatic effects. The model predicts larval developmental rates and voltinism for each micmicroclimate within 10%. Water loss smulations predict, and field observations confirm, that pitcher desiccation is a function of microclimate and pitcher size, and that rainfall patterns on the order of 5 to 30 d determine desiccation patterns. Identification of the spatial and temporal scale of both the environment and the organismic (population) phenomena in question is crucial to constructing a meaningful definition of environmental heterogeneity. Thermal and hydric components of environmental variation may plan an important role in the maintenance of fitness variation in W. smithii. These results support the hypothesis of Istock (1978) that environmental uncertainty favors mixed life history strategies in Wyeomyia.« less
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NASA Astrophysics Data System (ADS)
Xu, Mengjia; Zou, Changxin; Zhao, Yanwei
2017-04-01
Environmental/ecological models are widely used for lake management as they provide a means to understand physical, chemical and biological processes in highly complex ecosystems. Most research focused on the development of environmental (water quality) and ecological models, separately. Limited studies were developed to couple the two models, and in these limited coupled models, a lake was regarded as a whole for analysis (i.e., considering the lake to be one well-mixed box), which was appropriate for small-scale lakes and was not sufficient to capture spatial variations within middle-scale or large-scale lakes. This paper seeks to establish a zoning-based environmental-ecological-coupled model for a lake. The Baiyangdian Lake, the largest freshwater lake in Northern China, was adopted as the study case. The coupled lake models including a hydrodynamics and water quality model established by MIKE21 and a compartmental ecological model used STELLA software have been established for middle-sized Baiyangdian Lake to realize the simulation of spatial variations of ecological conditions. On the basis of the flow field distribution results generated by MIKE21 hydrodynamics model, four water area zones were used as an example for compartmental ecological model calibration and validation. The results revealed that the developed coupled lake models can reasonably reflected the changes of the key state variables although there remain some state variables that are not well represented by the model due to the low quality of field monitoring data. Monitoring sites in a compartment may not be representative of the water quality and ecological conditions in the entire compartment even though that is the intention of compartment-based model design. There was only one ecological observation from a single monitoring site for some periods. This single-measurement issue may cause large discrepancies particularly when sampled site is not representative of the whole compartment. The coupled models have been applied to simulate the spatial variation trends of ecological condition under ecological water supplement as an example to reflect the application effect in lake restoration and management. The simulation results indicate that the models can provide a useful tool for lake restoration and management. The simulated spatial variation trends can provide a foundation for establishing permissible ranges for a selected set of water quality indices for a series of management measures such as watershed pollution load control and ecological water transfer. Meanwhile, the coupled models can help us to understand processes taking place and the relations of interaction between components in the lake ecosystem and external conditions. Taken together, the proposed models we established show some promising applications as middle-scale or large-scale lake management tools for pollution load control and ecological water transfer. These tools quantify the implications of proposed future water management decisions.
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Scheiner, Samuel M
2014-02-01
One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.
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Weigel, B.M.; Robertson, Dale M.
2007-01-01
We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII-Mostly Glaciated Dairy Region, and VIII-Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (~0.06 mg/l) and total nitrogen (~0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R 2 = 60.6%) and fish (R 2 = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses. ?? 2007 Springer Science+Business Media, LLC.
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Weigel, Brian M; Robertson, Dale M
2007-10-01
We sampled 41 sites on 34 nonwadeable rivers that represent the types of rivers in Wisconsin, and the kinds and intensities of nutrient and other anthropogenic stressors upon each river type. Sites covered much of United States Environmental Protection Agency national nutrient ecoregions VII--Mostly Glaciated Dairy Region, and VIII--Nutrient Poor, Largely Glaciated upper Midwest. Fish, macroinvertebrates, and three categories of environmental variables including nutrients, other water chemistry, and watershed features were collected using standard protocols. We summarized fish assemblages by index of biotic integrity (IBI) and its 10 component measures, and macroinvertebrates by 2 organic pollution tolerance and 12 proportional richness measures. All biotic and environmental variables represented a wide range of conditions, with biotic measures ranging from poor to excellent status, despite nutrient concentrations being consistently higher than reference concentrations reported for the regions. Regression tree analyses of nutrients on a suite of biotic measures identified breakpoints in total phosphorus (approximately 0.06 mg/l) and total nitrogen (approximately 0.64 mg/l) concentrations at which biotic assemblages were consistently impaired. Redundancy analyses (RDA) were used to identify the most important variables within each of the three environmental variable categories, which were then used to determine the relative influence of each variable category on the biota. Nutrient measures, suspended chlorophyll a, water clarity, and watershed land cover type (forest or row-crop agriculture) were the most important variables and they explained significant amounts of variation within the macroinvertebrate (R(2) = 60.6%) and fish (R(2) = 43.6%) assemblages. The environmental variables selected in the macroinvertebrate model were correlated to such an extent that partial RDA analyses could not attribute variation explained to individual environmental categories, assigning 89% of the explained variation to interactions among the categories. In contrast, partial RDA attributed much of the explained variation to the nutrient (25%) and other water chemistry (38%) categories for the fish model. Our analyses suggest that it would be beneficial to develop criteria based upon a suite of biotic and nutrient variables simultaneously to deem waters as not meeting their designated uses.
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NASA Astrophysics Data System (ADS)
Siegwolf, R. T. W.; Buchmann, N.; Frank, D.; Joos, F.; Kahmen, A.; Treydte, K.; Leuenberger, M.; Saurer, M.
2012-04-01
Trees play are a critical role in the carbon cycle - their photosynthetic assimilation is one of the largest terrestrial carbon fluxes and their standing biomass represents the largest carbon pool of the terrestrial biosphere. Understanding how tree physiology and growth respond to long-term environmental change is pivotal to predict the magnitude and direction of the terrestrial carbon sink. iTREE is an interdisciplinary research framework to capitalize on synergies among leading dendroclimatologists, plant physiologists, isotope specialists, and global carbon cycle modelers with the objectives of reducing uncertainties related to tree/forest growth in the context of changing natural environments. Cross-cutting themes in our project are tree rings, stable isotopes, and mechanistic modelling. We will (i) establish a European network of tree-ring based isotope time-series to retrodict interannual to long-term tree physiological changes, (ii) conduct laboratory and field experiments to adapt a mechanistic isotope model to derive plant physiological variables from tree-ring isotopes, (iii) implement this model into a dynamic global vegetation model, and perform subsequent model-data validation exercises to refine model representation of plant physiological processes and (iv) attribute long-term variation in tree growth to plant physiological and environmental drivers, and identify how our refined knowledge revises predictions of the coupled carbon-cycle climate system. We will contribute to i) advanced quantifications of long-term variation in tree growth across Central Europe, ii) novel long-term information on key physiological processes that underlie variations in tree growth, and iii) improved carbon cycle models that can be employed to revise predictions of the coupled carbon-cycle climate system. Hence iTREE will significantly contribute towards a seamless understanding of the responses of terrestrial ecosystems to long-term environmental change, and ultimately help reduce uncertainties of the magnitude and direction of the past and future terrestrial carbon sink.
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Yañez-Arenas, Carlos; Peterson, A. Townsend; Mokondoko, Pierre; Rojas-Soto, Octavio; Martínez-Meyer, Enrique
2014-01-01
Background Many authors have claimed that snakebite risk is associated with human population density, human activities, and snake behavior. Here we analyzed whether environmental suitability of vipers can be used as an indicator of snakebite risk. We tested several hypotheses to explain snakebite incidence, through the construction of models incorporating both environmental suitability and socioeconomic variables in Veracruz, Mexico. Methodology/Principal Findings Ecological niche modeling (ENM) was used to estimate potential geographic and ecological distributions of nine viper species' in Veracruz. We calculated the distance to the species' niche centroid (DNC); this distance may be associated with a prediction of abundance. We found significant inverse relationships between snakebites and DNCs of common vipers (Crotalus simus and Bothrops asper), explaining respectively 15% and almost 35% of variation in snakebite incidence. Additionally, DNCs for these two vipers, in combination with marginalization of human populations, accounted for 76% of variation in incidence. Conclusions/Significance Our results suggest that niche modeling and niche-centroid distance approaches can be used to mapping distributions of environmental suitability for venomous snakes; combining this ecological information with socioeconomic factors may help with inferring potential risk areas for snakebites, since hospital data are often biased (especially when incidences are low). PMID:24963989
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Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.
2015-01-01
Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.
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Evaluating abundance and trends in a Hawaiian avian community using state-space analysis
Camp, Richard J.; Brinck, Kevin W.; Gorresen, P.M.; Paxton, Eben H.
2016-01-01
Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.
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NASA Astrophysics Data System (ADS)
Zhou, L. B.; Akiyoshi, H.; Kawahira, K.
2003-10-01
The year-to-year ozone variation over the subtropical western Pacific region is studied, especially the ozone lows in the 1996/1997, 1998/1999, and 2001/2002 winters, using the Earth Probe Total Ozone Mapping Spectrometer (EP_TOMS) ozone data from August 1996 to July 2002. Regression analyses show that dynamical signals, such as the quasi-biennial oscillation, play an important role in determining total ozone variation. A nudging chemical transport model (CTM) is used to simulate the year-to-year ozone variation and explain the mechanism for producing ozone lows in a three-dimensional distribution of ozone. The CTM was developed using the Center for Climate System Research/National Institute for Environmental Studies (CCSR/NIES) atmospheric general circulation model and introducing a nudging process for temperature and horizontal wind velocity. The year-to-year ozone variation, especially the winter ozone low, is well simulated by the model excluding heterogeneous reaction processes between 45°S and 45°N latitude. Results show that the year-to-year ozone variation is mainly controlled by dynamical transport processes.
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Estimating the spatial scales of landscape effects on abundance
Richard Chandler; Jeffrey Hepinstall-Cymerman
2016-01-01
Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering...
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Background/Question/Methods Solar radiation is a significant environmental driver that impacts the quality and resilience of terrestrial and aquatic habitats, yet its spatiotemporal variations are complicated to model accurately at high resolution over large, complex watersheds. ...
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Roff, Derek A; Mostowy, Serge; Fairbairn, Daphne J
2002-01-01
The concept of phenotypic trade-offs is a central element in evolutionary theory. In general, phenotypic models assume a fixed trade-off function, whereas quantitative genetic theory predicts that the trade-off function will change as a result of selection. For a linear trade-off function selection will readily change the intercept but will have to be relatively stronger to change the slope. We test these predictions by examining the trade-off between fecundity and flight capability, as measured by dorso-longitudinal muscle mass, in four different populations of the sand cricket, Gryllus firmus. Three populations were recently derived from the wild, and the fourth had been in the laboratory for 19 years. We hypothesized that the laboratory population had most likely undergone more and different selection from the three wild populations and therefore should differ from these in respect to both slope and intercept. Because of geographic variation in selection, we predicted a general difference in intercept among the four populations. We further tested the hypothesis that this intercept will be correlated with proportion macropterous and that this relationship will itself vary with environmental conditions experienced during both the nymphal and adult period. Observed variation in the phenotypic trade-off was consistent with the predictions of the quantitative genetic model. These results point to the importance of modeling trade-offs as dynamic rather than static relationships. We discuss how phenotypic models can incorporate such variation. The phenotypic trade-off between fecundity and dorso-longitudinal muscle mass is determined in part by variation in body size, illustrating the necessity of considering trade-offs to be multi factorial rather than simply bivariate relationships.
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NASA Astrophysics Data System (ADS)
França, Susana; Vasconcelos, Rita P.; Fonseca, Vanessa F.; Tanner, Susanne E.; Reis-Santos, Patrick; Costa, Maria José; Cabral, Henrique N.
2012-07-01
Statistical models predicting species distributions are essential not only to increase knowledge on species but for their application in conservation and ecologically-based management. The variation of fish species richness and abundance in the most representative habitats (saltmarsh, mudflat and subtidal) in five estuaries along the Portuguese coast was analysed through seasonal sampling surveys in 2009. Generalized additive models (GAM) were developed to describe the variation of species richness and abundances with a set of geomorphologic, hydrologic and environmental characteristics from the sampled estuaries and habitats. GAM were chosen as the complex interactions dominating these ecosystems and species distribution are non-linear. Final models built for each estuary and for all estuaries together performed well during the calibration phase and also during the validation phase, where an unused data sub-set from each estuary was used. There was not a similar combination of variables retained by the models for the studied estuaries but factors such as the area of the habitat, the distance to estuary mouth, percentage of mud in the sediment and depth were commonly retained. The partial effect of these predictor variables on the variation of species richness and abundance in the estuaries varied markedly and the importance of preserving the heterogeneity of habitats within estuaries was highlighted. Models for each individual estuary performed better than models for estuaries combined. Predictive models could be useful as a preliminary tool to prepare long-term conservation plans at different scales.
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Mayfield, Helen J; Lowry, John H; Watson, Conall H; Kama, Mike; Nilles, Eric J; Lau, Colleen L
2018-05-01
Leptospirosis is a globally important zoonotic disease, with complex exposure pathways that depend on interactions between human beings, animals, and the environment. Major drivers of outbreaks include flooding, urbanisation, poverty, and agricultural intensification. The intensity of these drivers and their relative importance vary between geographical areas; however, non-spatial regression methods are incapable of capturing the spatial variations. This study aimed to explore the use of geographically weighted logistic regression (GWLR) to provide insights into the ecoepidemiology of human leptospirosis in Fiji. We obtained field data from a cross-sectional community survey done in 2013 in the three main islands of Fiji. A blood sample obtained from each participant (aged 1-90 years) was tested for anti-Leptospira antibodies and household locations were recorded using GPS receivers. We used GWLR to quantify the spatial variation in the relative importance of five environmental and sociodemographic covariates (cattle density, distance to river, poverty rate, residential setting [urban or rural], and maximum rainfall in the wettest month) on leptospirosis transmission in Fiji. We developed two models, one using GWLR and one with standard logistic regression; for each model, the dependent variable was the presence or absence of anti-Leptospira antibodies. GWLR results were compared with results obtained with standard logistic regression, and used to produce a predictive risk map and maps showing the spatial variation in odds ratios (OR) for each covariate. The dataset contained location information for 2046 participants from 1922 households representing 81 communities. The Aikaike information criterion value of the GWLR model was 1935·2 compared with 1254·2 for the standard logistic regression model, indicating that the GWLR model was more efficient. Both models produced similar OR for the covariates, but GWLR also detected spatial variation in the effect of each covariate. Maximum rainfall had the least variation across space (median OR 1·30, IQR 1·27-1·35), and distance to river varied the most (1·45, 1·35-2·05). The predictive risk map indicated that the highest risk was in the interior of Viti Levu, and the agricultural region and southern end of Vanua Levu. GWLR provided a valuable method for modelling spatial heterogeneity of covariates for leptospirosis infection and their relative importance over space. Results of GWLR could be used to inform more place-specific interventions, particularly for diseases with strong environmental or sociodemographic drivers of transmission. WHO, Australian National Health & Medical Research Council, University of Queensland, UK Medical Research Council, Chadwick Trust. Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.
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Wu, Sheng-Hui; Ozaki, Koken; Reed, Terry; Krasnow, Ruth E; Dai, Jun
2017-07-01
This study examined genetic and environmental influences on the lipid concentrations of 1028 male twins using the novel univariate non-normal structural equation modeling (nnSEM) ADCE and ACE models. In the best fitting nnSEM ADCE model that was also better than the nnSEM ACE model, additive genetic factors (A) explained 4%, dominant genetic factors (D) explained 17%, and common (C) and unique (E) environmental factors explained 47% and 33% of the total variance of high-density lipoprotein cholesterol (HDL-C). The percentage of variation explained for other lipids was 0% (A), 30% (D), 34% (C) and 37% (E) for low-density lipoprotein cholesterol (LDL-C); 30, 0, 31 and 39% for total cholesterol; and 0, 31, 12 and 57% for triglycerides. It was concluded that additive and dominant genetic factors simultaneously affected HDL-C concentrations but not other lipids. Common and unique environmental factors influenced concentrations of all lipids.
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Ntie, Stephan; Davis, Anne R; Hils, Katrin; Mickala, Patrick; Thomassen, Henri A; Morgan, Katy; Vanthomme, Hadrien; Gonder, Mary K; Anthony, Nicola M
2017-09-06
This study aims to assess the role that Pleistocene refugia, rivers and local habitat conditions may have played in the evolutionary diversification of three central African duiker species (Cephalophus dorsalis, C. callipygus and Philantomba monticola). Genetic data from geo-referenced feces were collected from a wide range of sites across Central Africa. Historical patterns of population genetic structure were assessed using a ~ 650 bp fragment of the mitochondrial control region and contemporary patterns of genetic differentiation were evaluated using 12 polymorphic microsatellite loci. Mitochondrial analyses revealed that populations of C. callipygus and P. monticola in the Gulf of Guinea refugium are distinct from other populations in west central Africa. All three species exhibit signatures of past population expansion across much of the study area consistent with a history of postglacial expansion. There was no strong evidence for a riverine barrier effect in any of the three species, suggesting that duikers can readily cross major rivers. Generalized dissimilarity models (GDM) showed that environmental variation explains most of the nuclear genetic differentiation in both C. callipygus and P. monticola. The forest-savanna transition across central Cameroon and the Plateaux Batéké region in southeastern Gabon show the highest environmentally-associated turnover in genetic variability. A pattern of genetic differentiation was also evident between the coast and forest interior that may reflect differences in precipitation and/or vegetation. Findings from this study highlight the historical impact of Pleistocene fragmentation and current influence of environmental variation on genetic structure in duikers. Conservation efforts should therefore target areas that harbor as much environmentally-associated genetic variation as possible in order to maximize species' capacity to adapt to environmental change.
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Robustness and flexibility in nematode vulva development.
Félix, Marie-Anne; Barkoulas, Michalis
2012-04-01
The Caenorhabditis elegans vulva has served as a paradigm for how conserved developmental pathways, such as EGF-Ras-MAPK, Notch and Wnt signaling, participate in networks driving animal organogenesis. Here, we discuss an emerging direction in the field, which places vulva research in a quantitative and microevolutionary framework. The final vulval cell fate pattern is known to be robust to change, but only recently has the variation of vulval traits been measured under stochastic, environmental or genetic variation. Whereas the resulting cell fate pattern is invariant among rhabditid nematodes, recent studies indicate that the developmental system has accumulated cryptic variation, even among wild C. elegans isolates. Quantitative differences in the signaling network have emerged through experiments and modeling as the driving force behind cryptic variation in Caenorhabditis species. On a wider evolutionary scale, the establishment of new model species has informed about the presence of qualitative variation in vulval signaling pathways. Copyright © 2012 Elsevier Ltd. All rights reserved.
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The Spatial Distributions and Variations of Water Environmental Risk in Yinma River Basin, China
Di, Hui; Liu, Xingpeng; Tong, Zhijun; Ji, Meichen
2018-01-01
Water environmental risk is the probability of the occurrence of events caused by human activities or the interaction of human activities and natural processes that will damage a water environment. This study proposed a water environmental risk index (WERI) model to assess the water environmental risk in the Yinma River Basin based on hazards, exposure, vulnerability, and regional management ability indicators in a water environment. The data for each indicator were gathered from 2000, 2005, 2010, and 2015 to assess the spatial and temporal variations in water environmental risk using particle swarm optimization and the analytic hierarchy process (PSO-AHP) method. The results showed that the water environmental risk in the Yinma River Basin decreased from 2000 to 2015. The risk level of the water environment was high in Changchun, while the risk levels in Yitong and Yongji were low. The research methods provide information to support future decision making by the risk managers in the Yinma River Basin, which is in a high-risk water environment. Moreover, water environment managers could reduce the risks by adjusting the indicators that affect water environmental risks. PMID:29543706
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NASA Astrophysics Data System (ADS)
Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.
2005-05-01
Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.
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Baldissera, Ronei; Rodrigues, Everton N L; Hartz, Sandra M
2012-01-01
The distribution of beta diversity is shaped by factors linked to environmental and spatial control. The relative importance of both processes in structuring spider metacommunities has not yet been investigated in the Atlantic Forest. The variance explained by purely environmental, spatially structured environmental, and purely spatial components was compared for a metacommunity of web spiders. The study was carried out in 16 patches of Atlantic Forest in southern Brazil. Field work was done in one landscape mosaic representing a slight gradient of urbanization. Environmental variables encompassed plot- and patch-level measurements and a climatic matrix, while principal coordinates of neighbor matrices (PCNMs) acted as spatial variables. A forward selection procedure was carried out to select environmental and spatial variables influencing web-spider beta diversity. Variation partitioning was used to estimate the contribution of pure environmental and pure spatial effects and their shared influence on beta-diversity patterns, and to estimate the relative importance of selected environmental variables. Three environmental variables (bush density, land use in the surroundings of patches, and shape of patches) and two spatial variables were selected by forward selection procedures. Variation partitioning revealed that 15% of the variation of beta diversity was explained by a combination of environmental and PCNM variables. Most of this variation (12%) corresponded to pure environmental and spatially environmental structure. The data indicated that (1) spatial legacy was not important in explaining the web-spider beta diversity; (2) environmental predictors explained a significant portion of the variation in web-spider composition; (3) one-third of environmental variation was due to a spatial structure that jointly explains variation in species distributions. We were able to detect important factors related to matrix management influencing the web-spider beta-diversity patterns, which are probably linked to historical deforestation events.
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Zald, Harold S.J.; Spies, Thomas A.; Seidl, Rupert; Pabst, Robert J.; Olsen, Keith A.; Steel, E. Ashley
2016-01-01
Forest carbon (C) density varies tremendously across space due to the inherent heterogeneity of forest ecosystems. Variation of forest C density is especially pronounced in mountainous terrain, where environmental gradients are compressed and vary at multiple spatial scales. Additionally, the influence of environmental gradients may vary with forest age and developmental stage, an important consideration as forest landscapes often have a diversity of stand ages from past management and other disturbance agents. Quantifying forest C density and its underlying environmental determinants in mountain terrain has remained challenging because many available data sources lack the spatial grain and ecological resolution needed at both stand and landscape scales. The objective of this study was to determine if environmental factors influencing aboveground live carbon (ALC) density differed between young versus old forests. We integrated aerial light detection and ranging (lidar) data with 702 field plots to map forest ALC density at a grain of 25 m across the H.J. Andrews Experimental Forest, a 6369 ha watershed in the Cascade Mountains of Oregon, USA. We used linear regressions, random forest ensemble learning (RF) and sequential autoregressive modeling (SAR) to reveal how mapped forest ALC density was related to climate, topography, soils, and past disturbance history (timber harvesting and wildfires). ALC increased with stand age in young managed forests, with much greater variation of ALC in relation to years since wildfire in old unmanaged forests. Timber harvesting was the most important driver of ALC across the entire watershed, despite occurring on only 23% of the landscape. More variation in forest ALC density was explained in models of young managed forests than in models of old unmanaged forests. Besides stand age, ALC density in young managed forests was driven by factors influencing site productivity, whereas variation in ALC density in old unmanaged forests was also affected by finer scale topographic conditions associated with sheltered sites. Past wildfires only had a small influence on current ALC density, which may be a result of long times since fire and/or prevalence of non-stand replacing fire. Our results indicate that forest ALC density depends on a suite of multi-scale environmental drivers mediated by complex mountain topography, and that these relationships are dependent on stand age. The high and context-dependent spatial variability of forest ALC density has implications for quantifying forest carbon stores, establishing upper bounds of potential carbon sequestration, and scaling field data to landscape and regional scales. PMID:27041818
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Importance of spatial autocorrelation in modeling bird distributions at a continental scale
Bahn, V.; O'Connor, R.J.; Krohn, W.B.
2006-01-01
Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.
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Bodbyl-Roels, Sarah; Peterson, A Townsend; Xiao, Xiangming
2011-03-28
Ecological niche modeling integrates known sites of occurrence of species or phenomena with data on environmental variation across landscapes to infer environmental spaces potentially inhabited (i.e., the ecological niche) to generate predictive maps of potential distributions in geographic space. Key inputs to this process include raster data layers characterizing spatial variation in environmental parameters, such as vegetation indices from remotely sensed satellite imagery. The extent to which ecological niche models reflect real-world distributions depends on a number of factors, but an obvious concern is the quality and content of the environmental data layers. We assessed ecological niche model predictions of H5N1 avian flu presence quantitatively within and among four geographic regions, based on models incorporating two means of summarizing three vegetation indices derived from the MODIS satellite. We evaluated our models for predictive ability using partial ROC analysis and GLM ANOVA to compare performance among indices and regions. We found correlations between vegetation indices to be high, such that they contain information that overlaps broadly. Neither the type of vegetation index used nor method of summary affected model performance significantly. However, the degree to which model predictions had to be transferred (i.e., projected onto landscapes and conditions not represented on the landscape of training) impacted predictive strength greatly (within-region model predictions far out-performed models projected among regions). Our results provide the first quantitative tests of most appropriate uses of different remotely sensed data sets in ecological niche modeling applications. While our testing did not result in a decisive "best" index product or means of summarizing indices, it emphasizes the need for careful evaluation of products used in modeling (e.g. matching temporal dimensions and spatial resolution) for optimum performance, instead of simple reliance on large numbers of data layers.
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Yang, Ye; Chui, Ting Fong May; Shen, Ping Ping; Yang, Yang; Gu, Ji Dong
2018-03-15
Anthropogenic activities such as land reclamation are threatening tidal marshes worldwide. This study's hypothesis is that land reclamation in a semi-enclosed bay alters the seasonal dynamics of intertidal benthic infauna, which is a key component in the tidal marsh ecosystem. Mai Po Tidal Marsh, Deep Bay, Pearl River Estuary, China was used as a case study to evaluate the hypothesis. Ecological models that simulate benthic biomass dynamics with governing environmental factors were developed, and various scenario experiments were conducted to evaluate the impact of reclamations. Environmental variables, selected from the areas of hydrodynamics, meteorology, and water quality based on correlation analysis, were used to generate Bayesian regression models for biomass prediction. The best-performing model, which considered average water age (i.e., a hydrodynamic indicator of estuarine circulation) in the previous month, salinity variation (i.e., standard deviation of salinity), and the total sunny period in the current month, captured well both seasonal and yearly trends in the benthic infauna observations from 2002 to 2008. This model was then used to simulate biomass dynamics with varying inputs of water age and salinity variation from coastal numerical models of different reclamation scenarios. The simulation results suggest that the reclamation in 2007 decreased the spatial and annual average benthic infauna biomass in the tidal marsh by 20%, which agreed with the 28% biomass decrease recorded by field survey. The range of biomass seasonal variation also decreased significantly from 2.1 to 230.5g/m 2 (without any reclamation) to 1.2 to 131.1g/m 2 (after the 2007 reclamation), which further demonstrates the substantial ecological impact of reclamation. The ecological model developed in this study could simulate seasonal biomass dynamics and evaluate the ecological impact of reclamation projects. It can therefore be applied to evaluate the ecological impact of coastal engineering projects for tidal marsh management, conservation, and restoration. Copyright © 2017 Elsevier B.V. All rights reserved.
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NASA Astrophysics Data System (ADS)
Still, C. J.; Griffith, D.; Edwards, E.; Forrestel, E.; Lehmann, C.; Anderson, M.; Craine, J.; Pau, S.; Osborne, C.
2014-12-01
Variation in plant species traits, such as photosynthetic and hydraulic properties, can indicate vulnerability or resilience to climate change, and feed back to broad-scale spatial and temporal patterns in biogeochemistry, demographics, and biogeography. Yet, predicting how vegetation will respond to future environmental changes is severely limited by the inability of our models to represent species-level trait variation in processes and properties, as current generation process-based models are mostly based on the generalized and abstracted concept of plant functional types (PFTs) which were originally developed for hydrological modeling. For example, there are close to 11,000 grass species, but most vegetation models have only a single C4 grass and one or two C3 grass PFTs. However, while species trait databases are expanding rapidly, they have been produced mostly from unstructured research, with a focus on easily researched traits that are not necessarily the most important for determining plant function. Additionally, implementing realistic species-level trait variation in models is challenging. Combining related and ecologically similar species in these models might ameliorate this limitation. Here we argue for an intermediate, lineage-based approach to PFTs, which draws upon recent advances in gene sequencing and phylogenetic modeling, and where trait complex variations and anatomical features are constrained by a shared evolutionary history. We provide an example of this approach with grass lineages that vary in photosynthetic pathway (C3 or C4) and other functional and structural traits. We use machine learning approaches and geospatial databases to infer the most important environmental controls and climate niche variation for the distribution of grass lineages, and utilize a rapidly expanding grass trait database to demonstrate examples of lineage-based grass PFTs. For example, grasses in the Andropogoneae are typically tall species that dominate wet and seasonally burned ecosystems, whereas Chloridoideae grasses are associated with semi-arid regions. These two C4 lineages are expected to respond quite differently to climate change, but are often modelled as a single PFT.
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Margiotta, M; Bella, S; Buffa, F; Caleca, V; Floris, I; Giorno, V; Lo Verde, G; Rapisarda, C; Sasso, R; Suma, P; Tortorici, F; Laudonia, S
2017-04-01
Glycaspis brimblecombei Moore (Hemiptera: Aphalaridae) is an invasive psyllid introduced into the Mediterranean area, where it affects several species of Eucalyptus. Psyllaephagus bliteus Riek (Hymenoptera: Encyrtidae) is a specialized parasitoid of this psyllid that was accidentally introduced into Italy in 2011. We developed a model of this host-parasitoid system that accounts for the influence of environmental conditions on the G. brimblecombei population dynamics and P. bliteus parasitism rates in the natural ecosystem. The Lotka-Volterra-based model predicts non-constant host growth and parasitoid mortality rates in association with variation in environmental conditions. The model was tested by analyzing sampling data collected in Naples in 2011 (before the parasitoid was present) and defining several environmental patterns, termed Temperature-Rain or T-R patterns, which correspond to the host growth rate. A mean value of the host growth rate was assigned to each T-R pattern, as well as a variation of the parasitoid mortality rate based on temperature thresholds. The proposed model was applied in simulation tests related to T-R patterns carried out with a data series sampled between June 2014 and July 2015 in five Italian sites located in Campania, Lazio, Sicily, and Sardinia regions. The simulation results showed that the proposed model provides an accurate approximation of population trends, although oscillation details may not be apparent. Results predict a 64% reduction in G. brimblecombei population density owing to P. bliteus parasitoid activity. Our results are discussed with respect to features of the host-parasitoid interaction that could be exploited in future biological control programs. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Genetic and Environmental Factors Associated with Cannabis Involvement
Bogdan, Ryan; Winstone, Jonathan MA; Agrawal, Arpana
2016-01-01
Approximately 50-70% of the variation in cannabis use and use disorders can be attributed to heritable factors. For cannabis use, the remaining variance can be parsed in to familial and person-specific environmental factors while for use disorders, only the latter contribute. While numerous candidate gene studies have identified the role of common variation influencing liability to cannabis involvement, replication has been elusive. To date, no genomewide association study has been sufficiently powered to identify significant loci. Despite this, studies adopting polygenic techniques and integrating genetic variation with neural phenotypes and measures of environmental risk, such as childhood adversity, are providing promising new leads. It is likely that the small effect sizes associated with variants related to cannabis involvement will only be robustly identified in substantially larger samples. Results of such large-scale efforts will provide valuable single variant targets for translational research in neurogenetic, pharmacogenetic and non-human animal models as well as polygenic risk indices that can be used to explore a host of other genetic hypotheses related to cannabis use and misuse. PMID:27642547
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Leaf nitrogen from first principles: field evidence for adaptive variation with climate
NASA Astrophysics Data System (ADS)
Dong, Ning; Prentice, Iain Colin; Evans, Bradley J.; Caddy-Retalic, Stefan; Lowe, Andrew J.; Wright, Ian J.
2017-01-01
Nitrogen content per unit leaf area (Narea) is a key variable in plant functional ecology and biogeochemistry. Narea comprises a structural component, which scales with leaf mass per area (LMA), and a metabolic component, which scales with Rubisco capacity. The co-ordination hypothesis, as implemented in LPJ and related global vegetation models, predicts that Rubisco capacity should be directly proportional to irradiance but should decrease with increases in ci : ca and temperature because the amount of Rubisco required to achieve a given assimilation rate declines with increases in both. We tested these predictions using LMA, leaf δ13C, and leaf N measurements on complete species assemblages sampled at sites on a north-south transect from tropical to temperate Australia. Partial effects of mean canopy irradiance, mean annual temperature, and ci : ca (from δ13C) on Narea were all significant and their directions and magnitudes were in line with predictions. Over 80 % of the variance in community-mean (ln) Narea was accounted for by these predictors plus LMA. Moreover, Narea could be decomposed into two components, one proportional to LMA (slightly steeper in N-fixers), and the other to Rubisco capacity as predicted by the co-ordination hypothesis. Trait gradient analysis revealed ci : ca to be perfectly plastic, while species turnover contributed about half the variation in LMA and Narea. Interest has surged in methods to predict continuous leaf-trait variation from environmental factors, in order to improve ecosystem models. Coupled carbon-nitrogen models require a method to predict Narea that is more realistic than the widespread assumptions that Narea is proportional to photosynthetic capacity, and/or that Narea (and photosynthetic capacity) are determined by N supply from the soil. Our results indicate that Narea has a useful degree of predictability, from a combination of LMA and ci : ca - themselves in part environmentally determined - with Rubisco activity, as predicted from local growing conditions. This finding is consistent with a
plant-centred
approach to modelling, emphasizing the adaptive regulation of traits. Models that account for biodiversity will also need to partition community-level trait variation into components due to phenotypic plasticity and/or genotypic differentiation within species vs. progressive species replacement, along environmental gradients. Our analysis suggests that variation in Narea is about evenly split between these two modes. -
Environmental quality and evolutionary potential: lessons from wild populations
Charmantier, Anne; Garant, Dany
2005-01-01
An essential requirement to determine a population's potential for evolutionary change is to quantify the amount of genetic variability expressed for traits under selection. Early investigations in laboratory conditions showed that the magnitude of the genetic and environmental components of phenotypic variation can change with environmental conditions. However, there is no consensus as to how the expression of genetic variation is sensitive to different environmental conditions. Recently, the study of quantitative genetics in the wild has been revitalized by new pedigree analyses based on restricted maximum likelihood, resulting in a number of studies investigating these questions in wild populations. Experimental manipulation of environmental quality in the wild, as well as the use of naturally occurring favourable or stressful environments, has broadened the treatment of different taxa and traits. Here, we conduct a meta-analysis on recent studies comparing heritability in favourable versus unfavourable conditions in non-domestic and non-laboratory animals. The results provide evidence for increased heritability in more favourable conditions, significantly so for morphometric traits but not for traits more closely related to fitness. We discuss how these results are explained by underlying changes in variance components, and how they represent a major step in our understanding of evolutionary processes in wild populations. We also show how these trends contrast with the prevailing view resulting mainly from laboratory experiments on Drosophila. Finally, we underline the importance of taking into account the environmental variation in models predicting quantitative trait evolution. PMID:16011915
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Interacting coastal based ecosystem services: recreation and water quality in Puget Sound, WA
Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William
2013-01-01
Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments.
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Interacting Coastal Based Ecosystem Services: Recreation and Water Quality in Puget Sound, WA
Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William
2013-01-01
Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments. PMID:23451067
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Yao, Y; Lian, Z; Liu, W; Jiang, C; Liu, Y; Lu, H
2009-04-01
Human thermal comfort researches mainly focus on the relation between the environmental factors (e.g. ambient temperature, air humidity, and air velocity, etc.) and the thermal comfort sensation based on a large amount of subjective field investigations. Although some physiological factors, such as skin temperature and metabolism were used in many thermal comfort models,they are not enough to establish a perfect thermal comfort model. In this paper,another two physiological factors, i.e. heart rate variation (HRV) and electroencephalograph (EEG), are explored for the thermal comfort study. Experiments were performed to investigate how these physiological factors respond to the environmental temperatures, and what is the relationship between HRV and EEG and thermal comfort. The experimental results indicate that HRV and EEG may be related to thermal comfort, and they may be useful to understand the mechanism of thermal comfort.
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Uncertainty, learning, and the optimal management of wildlife
Williams, B.K.
2001-01-01
Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.
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Schistosomiasis Breeding Environment Situation Analysis in Dongting Lake Area
NASA Astrophysics Data System (ADS)
Li, Chuanrong; Jia, Yuanyuan; Ma, Lingling; Liu, Zhaoyan; Qian, Yonggang
2013-01-01
Monitoring environmental characteristics, such as vegetation, soil moisture et al., of Oncomelania hupensis (O. hupensis)’ spatial/temporal distribution is of vital importance to the schistosomiasis prevention and control. In this study, the relationship between environmental factors derived from remotely sensed data and the density of O. hupensis was analyzed by a multiple linear regression model. Secondly, spatial analysis of the regression residual was investigated by the semi-variogram method. Thirdly, spatial analysis of the regression residual and the multiple linear regression model were both employed to estimate the spatial variation of O. hupensis density. Finally, the approach was used to monitor and predict the spatial and temporal variations of oncomelania of Dongting Lake region, China. And the areas of potential O. hupensis habitats were predicted and the influence of Three Gorges Dam (TGB)project on the density of O. hupensis was analyzed.
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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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Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Mike D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot
2006-01-01
The relative importance of variables in determining area burned is an important management consideration although gaining insights from existing empirical data has proven difficult. The purpose of this study was to compare the sensitivity of modeled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The...
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Feuillet, Thierry; Charreire, Hélène; Menai, Mehdi; Salze, Paul; Simon, Chantal; Dugas, Julien; Hercberg, Serge; Andreeva, Valentina A; Enaux, Christophe; Weber, Christiane; Oppert, Jean-Michel
2015-03-25
According to the social ecological model of health-related behaviors, it is now well accepted that environmental factors influence habitual physical activity. Most previous studies on physical activity determinants have assumed spatial homogeneity across the study area, i.e. that the association between the environment and physical activity is the same whatever the location. The main novelty of our study was to explore geographical variation in the relationships between active commuting (walking and cycling to/from work) and residential environmental characteristics. 4,164 adults from the ongoing Nutrinet-Santé web-cohort, residing in and around Paris, France, were studied using a geographically weighted Poisson regression (GWPR) model. Objective environmental variables, including both the built and the socio-economic characteristics around the place of residence of individuals, were assessed by GIS-based measures. Perceived environmental factors (index including safety, aesthetics, and pollution) were reported by questionnaires. Our results show that the influence of the overall neighborhood environment appeared to be more pronounced in the suburban southern part of the study area (Val-de-Marne) compared to Paris inner city, whereas more complex patterns were found elsewhere. Active commuting was positively associated with the built environment only in the southern and northeastern parts of the study area, whereas positive associations with the socio-economic environment were found only in some specific locations in the southern and northern parts of the study area. Similar local variations were observed for the perceived environmental variables. These results suggest that: (i) when applied to active commuting, the social ecological conceptual framework should be locally nuanced, and (ii) local rather than global targeting of public health policies might be more efficient in promoting active commuting.
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Jelenkovic, Aline; Ortega-Alonso, Alfredo; Rose, Richard J; Kaprio, Jaakko; Rebato, Esther; Silventoinen, Karri
2011-01-01
Human growth is a complex process that remains insufficiently understood. We aimed to analyze genetic and environmental influences on growth from late childhood to early adulthood. Two cohorts of monozygotic and dizygotic (same sex and opposite sex) Finnish twin pairs were studied longitudinally using self-reported height at 11-12, 14, and 17 years and adult age (FinnTwin12) and at 16, 17, and 18 years and adult age (FinnTwin16). Univariate and multivariate variance component models for twin data were used. From childhood to adulthood, genetic differences explained 72-81% of the variation of height in boys and 65-86% in girls. Environmental factors common to co-twins explained 5-23% of the variation of height, with the residual variation explained by environmental factors unique to each twin individual. Common environmental factors affecting height were highly correlated between the analyzed ages (0.72-0.99 and 0.91-1.00 for boys and girls, respectively). Genetic (0.58-0.99 and 0.70-0.99, respectively) and unique environmental factors (0.32-0.78 and 0.54-0.82, respectively) affecting height at different ages were more weakly, but still substantially, correlated. The genetic contribution to height is strong during adolescence. The high genetic correlations detected across the ages encourage further efforts to identify genes affecting growth. Common and unique environmental factors affecting height during adolescence are also important, and further studies are necessary to identify their nature and test whether they interact with genetic factors. Copyright © 2011 Wiley-Liss, Inc.
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Herrera, Carlos M; Medrano, Mónica; Bazaga, Pilar
2017-08-16
Epigenetic variation can play a role in local adaptation; thus, there should be associations among epigenetic variation, environmental variation, and functional trait variation across populations. This study examines these relationships in the perennial herb Helleborus foetidus (Ranunculaceae). Plants from 10 subpopulations were characterized genetically (AFLP, SSR markers), epigenetically (MSAP markers), and phenotypically (20 functional traits). Habitats were characterized using six environmental variables. Isolation-by-distance (IBD) and isolation-by-environment (IBE) patterns of genetic and epigenetic divergence were assessed, as was the comparative explanatory value of geographical and environmental distance as predictors of epigenetic, genetic, and functional differentiation. Subpopulations were differentiated genetically, epigenetically, and phenotypically. Genetic differentiation was best explained by geographical distance, while epigenetic differentiation was best explained by environmental distance. Divergence in functional traits was correlated with environmental and epigenetic distances, but not with geographical and genetic distances. Results are compatible with the hypothesis that epigenetic IBE and functional divergence reflected responses to environmental variation. Spatial analyses simultaneously considering epigenetic, genetic, phenotypic and environmental information provide a useful tool to evaluate the role of environmental features as drivers of natural epigenetic variation between populations. © 2017 Botanical Society of America.
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García-Roger, Eduardo Moisés; Franch, Belen; Carmona, María José; Serra, Manuel
2017-01-01
Fluctuations in environmental parameters are increasingly being recognized as essential features of any habitat. The quantification of whether environmental fluctuations are prevalently predictable or unpredictable is remarkably relevant to understanding the evolutionary responses of organisms. However, when characterizing the relevant features of natural habitats, ecologists typically face two problems: (1) gathering long-term data and (2) handling the hard-won data. This paper takes advantage of the free access to long-term recordings of remote sensing data (27 years, Landsat TM/ETM+) to assess a set of environmental models for estimating environmental predictability. The case study included 20 Mediterranean saline ponds and lakes, and the focal variable was the water-surface area. This study first aimed to produce a method for accurately estimating the water-surface area from satellite images. Saline ponds can develop salt-crusted areas that make it difficult to distinguish between soil and water. This challenge was addressed using a novel pipeline that combines band ratio water indices and the short near-infrared band as a salt filter. The study then extracted the predictable and unpredictable components of variation in the water-surface area. Two different approaches, each showing variations in the parameters, were used to obtain the stochastic variation around a regular pattern with the objective of dissecting the effect of assumptions on predictability estimations. The first approach, which is based on Colwell’s predictability metrics, transforms the focal variable into a nominal one. The resulting discrete categories define the relevant variations in the water-surface area. In the second approach, we introduced General Additive Model (GAM) fitting as a new metric for quantifying predictability. Both approaches produced a wide range of predictability for the studied ponds. Some model assumptions–which are considered very different a priori–had minor effects, whereas others produced predictability estimations that showed some degree of divergence. We hypothesize that these diverging estimations of predictability reflect the effect of fluctuations on different types of organisms. The fluctuation analysis described in this manuscript is applicable to a wide variety of systems, including both aquatic and non-aquatic systems, and will be valuable for quantifying and characterizing predictability, which is essential within the expected global increase in the unpredictability of environmental fluctuations. We advocate that a priori information for organisms of interest should be used to select the most suitable metrics for estimating predictability, and we provide some guidelines for this approach. PMID:29121667
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Validated predictive modelling of the environmental resistome
Amos, Gregory CA; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H
2015-01-01
Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome. PMID:25679532
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Linking 1D coastal ocean modelling to environmental management: an ensemble approach
NASA Astrophysics Data System (ADS)
Mussap, Giulia; Zavatarelli, Marco; Pinardi, Nadia
2017-12-01
The use of a one-dimensional interdisciplinary numerical model of the coastal ocean as a tool contributing to the formulation of ecosystem-based management (EBM) is explored. The focus is on the definition of an experimental design based on ensemble simulations, integrating variability linked to scenarios (characterised by changes in the system forcing) and to the concurrent variation of selected, and poorly constrained, model parameters. The modelling system used was previously specifically designed for the use in "data-rich" areas, so that horizontal dynamics can be resolved by a diagnostic approach and external inputs can be parameterised by nudging schemes properly calibrated. Ensembles determined by changes in the simulated environmental (physical and biogeochemical) dynamics, under joint forcing and parameterisation variations, highlight the uncertainties associated to the application of specific scenarios that are relevant to EBM, providing an assessment of the reliability of the predicted changes. The work has been carried out by implementing the coupled modelling system BFM-POM1D in an area of Gulf of Trieste (northern Adriatic Sea), considered homogeneous from the point of view of hydrological properties, and forcing it by changing climatic (warming) and anthropogenic (reduction of the land-based nutrient input) pressure. Model parameters affected by considerable uncertainties (due to the lack of relevant observations) were varied jointly with the scenarios of change. The resulting large set of ensemble simulations provided a general estimation of the model uncertainties related to the joint variation of pressures and model parameters. The information of the model result variability aimed at conveying efficiently and comprehensibly the information on the uncertainties/reliability of the model results to non-technical EBM planners and stakeholders, in order to have the model-based information effectively contributing to EBM.
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Validated predictive modelling of the environmental resistome.
Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H
2015-06-01
Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.
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Individual variation affects departure rate from the natal pond in an ephemeral pond-breeding anuran
Chelgren, N.D.; Rosenberg, D.K.; Heppell, S.S.; Gitelman, A.I.
2008-01-01
Frogs exhibit extreme plasticity and individual variation in growth and behavior during metamorphosis, driven by interactions of intrinsic state factors and extrinsic environmental factors. In northern red-legged frogs (Rana aurora Baird and Girard, 1852), we studied the timing of departure from the natal pond as it relates to date and size of individuals at metamorphosis in the context of environmental uncertainty. To affect body size at metamorphosis, we manipulated food availability during the larval stage for a sample (317) of 1045 uniquely marked individuals and released them at their natal ponds as newly metamorphosed frogs. We recaptured 34% of marked frogs in pitfall traps as they departed and related the timing of their initial terrestrial movements to individual properties using a time-to-event model. Median age at first capture was 4 and 9 days postmetamorphosis at two sites. The rate of departure was positively related to body size and to date of metamorphosis. Departure rate was strongly negatively related to time elapsed since rainfall, and this effect was diminished for smaller and later metamorphosing frogs. Individual variation in metamorphic traits thus affects individuals' responses to environmental variability, supporting a behavioral link with variation in survival associated with these same metamorphic traits. ?? 2008 NRC.
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Strategies for preventing invasive plant outbreaks after prescribed fire in ponderosa pine forest
Symstad, Amy J.; Newton, Wesley E.; Swanson, Daniel J.
2014-01-01
Land managers use prescribed fire to return a vital process to fire-adapted ecosystems, restore forest structure from a state altered by long-term fire suppression, and reduce wildfire intensity. However, fire often produces favorable conditions for invasive plant species, particularly if it is intense enough to reveal bare mineral soil and open previously closed canopies. Understanding the environmental or fire characteristics that explain post-fire invasive plant abundance would aid managers in efficiently finding and quickly responding to fire-caused infestations. To that end, we used an information-theoretic model-selection approach to assess the relative importance of abiotic environmental characteristics (topoedaphic position, distance from roads), pre-and post-fire biotic environmental characteristics (forest structure, understory vegetation, fuel load), and prescribed fire severity (measured in four different ways) in explaining invasive plant cover in ponderosa pine forest in South Dakota’s Black Hills. Environmental characteristics (distance from roads and post-fire forest structure) alone provided the most explanation of variation (26%) in post-fire cover of Verbascum thapsus (common mullein), but a combination of surface fire severity and environmental characteristics (pre-fire forest structure and distance from roads) explained 36–39% of the variation in post-fire cover of Cirsium arvense (Canada thistle) and all invasives together. For four species and all invasives together, their pre-fire cover explained more variation (26–82%) in post-fire cover than environmental and fire characteristics did, suggesting one strategy for reducing post-fire invasive outbreaks may be to find and control invasives before the fire. Finding them may be difficult, however, since pre-fire environmental characteristics explained only 20% of variation in pre-fire total invasive cover, and less for individual species. Thus, moderating fire intensity or targeting areas of high severity for post-fire invasive control may be the most efficient means for reducing the chances of post-fire invasive plant outbreaks when conducting prescribed fires in this region.
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Fluid dynamics in flexible tubes: An application to the study of the pulmonary circulation
NASA Technical Reports Server (NTRS)
Kuchar, N. R.
1971-01-01
Based on an analysis of unsteady, viscous flow through distensible tubes, a lumped-parameter model for the dynamics of blood flow through the pulmonary vascular bed was developed. The model is nonlinear, incorporating the variation of flow resistance with transmural pressure. Solved using a hybrid computer, the model yields information concerning the time-dependent behavior of blood pressures, flow rates, and volumes in each important class of vessels in each lobe of each lung in terms of the important physical and environmental parameters. Simulations of twenty abnormal or pathological situations of interest in environmental physiology and clinical medicine were performed. The model predictions agree well with physiological data.
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Steiner, Christopher F.
2012-01-01
The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934
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NASA Astrophysics Data System (ADS)
Pang, Aiping; Sun, Tao; Yang, Zhifeng
2013-03-01
SummaryAgriculture and ecosystems are increasingly competing for water. We propose an approach to assess the economic compensation standard required to release water from agricultural use to ecosystems while taking into account seasonal variability in river flow. First, we defined agricultural water shortage as the difference in water volume between agricultural demands and actual supply after maintaining environmental flows for ecosystems. Second, we developed a production loss model to establish the relationship between production losses and agricultural water shortages in view of seasonal variation in river discharge. Finally, we estimated the appropriate economic compensation for different irrigation stakeholders based on crop prices and production losses. A case study in the Yellow River Estuary, China, demonstrated that relatively stable economic compensation for irrigation processes can be defined based on the developed model, taking into account seasonal variations in river discharge and different levels of environmental flow. Annual economic compensation is not directly related to annual water shortage because of the temporal variability in river flow rate and environmental flow. Crops that have stable planting areas to guarantee food security should be selected as indicator crops in economic compensation assessments in the important grain production zone. Economic compensation may be implemented by creating funds to update water-saving measures in agricultural facilities.
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Vogt, Günter
2017-01-01
Abstract There is increasing evidence, particularly from plants, that epigenetic mechanisms can contribute to environmental adaptation and evolution. The present article provides an overview on this topic for animals and highlights the special suitability of clonal, invasive, hybrid, polyploid, and domesticated species for environmental and evolutionary epigenetics. Laboratory and field studies with asexually reproducing animals have shown that epigenetically diverse phenotypes can be produced from the same genome either by developmental stochasticity or environmental induction. The analysis of invasions revealed that epigenetic phenotype variation may help to overcome genetic barriers typically associated with invasions such as bottlenecks and inbreeding. Research with hybrids and polyploids established that epigenetic mechanisms are involved in consolidation of speciation by contributing to reproductive isolation and restructuring of the genome in the neo-species. Epigenetic mechanisms may even have the potential to trigger speciation but evidence is still meager. The comparison of domesticated animals and their wild ancestors demonstrated heritability and selectability of phenotype modulating DNA methylation patterns. Hypotheses, model predictions, and empirical results are presented to explain how epigenetic phenotype variation could facilitate adaptation and speciation. Clonal laboratory lineages, monoclonal invaders, and adaptive radiations of different evolutionary age seem particularly suitable to empirically test the proposed ideas. A respective research agenda is presented. PMID:29492304
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Carbon Assimilation Pathways, Water Relationships and Plant Ecology.
ERIC Educational Resources Information Center
Etherington, John R.
1988-01-01
Discusses between-species variation in adaptation of the photosynthetic mechanism to cope with wide fluctuations of environmental water regime. Describes models for water conservation in plants and the role of photorespiration in the evolution of the different pathways. (CW)
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Tredennick, Andrew T; de Mazancourt, Claire; Loreau, Michel; Adler, Peter B
2017-04-01
Temporal asynchrony among species helps diversity to stabilize ecosystem functioning, but identifying the mechanisms that determine synchrony remains a challenge. Here, we refine and test theory showing that synchrony depends on three factors: species responses to environmental variation, interspecific interactions, and demographic stochasticity. We then conduct simulation experiments with empirical population models to quantify the relative influence of these factors on the synchrony of dominant species in five semiarid grasslands. We found that the average synchrony of per capita growth rates, which can range from 0 (perfect asynchrony) to 1 (perfect synchrony), was higher when environmental variation was present (0.62) rather than absent (0.43). Removing interspecific interactions and demographic stochasticity had small effects on synchrony. For the dominant species in these plant communities, where species interactions and demographic stochasticity have little influence, synchrony reflects the covariance in species' responses to the environment. © 2017 by the Ecological Society of America.
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NASA Astrophysics Data System (ADS)
Grigorie, Teodor Lucian; Corcau, Ileana Jenica; Tudosie, Alexandru Nicolae
2017-06-01
The paper presents a way to obtain an intelligent miniaturized three-axial accelerometric sensor, based on the on-line estimation and compensation of the sensor errors generated by the environmental temperature variation. Taking into account that this error's value is a strongly nonlinear complex function of the values of environmental temperature and of the acceleration exciting the sensor, its correction may not be done off-line and it requires the presence of an additional temperature sensor. The proposed identification methodology for the error model is based on the least square method which process off-line the numerical values obtained from the accelerometer experimental testing for different values of acceleration applied to its axes of sensitivity and for different values of operating temperature. A final analysis of the error level after the compensation highlights the best variant for the matrix in the error model. In the sections of the paper are shown the results of the experimental testing of the accelerometer on all the three sensitivity axes, the identification of the error models on each axis by using the least square method, and the validation of the obtained models with experimental values. For all of the three detection channels was obtained a reduction by almost two orders of magnitude of the acceleration absolute maximum error due to environmental temperature variation.
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Dynamic Evaluation of Two Decades of CMAQ Simulations ...
This presentation focuses on the dynamic evaluation of the CMAQ model over the continental United States using multi-decadal simulations for the period from 1990 to 2010 to examine how well the changes in observed ozone air quality induced by variations in meteorology and/or emissions are simulated by the model. We applied spectral decomposition of the ozone time-series using the KZ filter to assess the variations in the strengths of synoptic (weather-induced variations) and baseline (long-term variation) forcings, embedded in the simulated and observed concentrations. The results reveal that CMAQ captured the year-to-year variability (more so in the later years than the earlier years) and the synoptic forcing in accordance with what the observations are showing. The National Exposure Research Laboratory (NERL) Computational Exposure Division (CED) develops and evaluates data, decision-support tools, and models to be applied to media-specific or receptor-specific problem areas. CED uses modeling-based approaches to characterize exposures, evaluate fate and transport, and support environmental diagnostics/forensics with input from multiple data sources. It also develops media- and receptor-specific models, process models, and decision support tools for use both within and outside of EPA.
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Agricultural Management Practices Explain Variation in Global Yield Gaps of Major Crops
NASA Astrophysics Data System (ADS)
Mueller, N. D.; Gerber, J. S.; Ray, D. K.; Ramankutty, N.; Foley, J. A.
2010-12-01
The continued expansion and intensification of agriculture are key drivers of global environmental change. Meeting a doubling of food demand in the next half-century will further induce environmental change, requiring either large cropland expansion into carbon- and biodiversity-rich tropical forests or increasing yields on existing croplands. Closing the “yield gaps” between the most and least productive farmers on current agricultural lands is a necessary and major step towards preserving natural ecosystems and meeting future food demand. Here we use global climate, soils, and cropland datasets to quantify yield gaps for major crops using equal-area climate analogs. Consistent with previous studies, we find large yield gaps for many crops in Eastern Europe, tropical Africa, and parts of Mexico. To analyze the drivers of yield gaps, we collected sub-national agricultural management data and built a global dataset of fertilizer application rates for over 160 crops. We constructed empirical crop yield models for each climate analog using the global management information for 17 major crops. We find that our climate-specific models explain a substantial amount of the global variation in yields. These models could be widely applied to identify management changes needed to close yield gaps, analyze the environmental impacts of agricultural intensification, and identify climate change adaptation techniques.
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Suryan, Robert M.; Saba, Vincent S.; Wallace, Bryan P.; Hatch, Scott A.; Frederiksen, Morten; Wanless, Sarah
2009-01-01
Variation in life history traits of organisms is thought to reflect adaptations to environmental forcing occurring from bottom-up and top-down processes. Such variation occurs not only among, but also within species, indicating demographic plasticity in response to environmental conditions. From a broad literature review, we present evidence for ocean basin- and large marine ecosystem-scale variation in intra-specific life history traits, with similar responses occurring among trophic levels from relatively short-lived secondary producers to very long-lived apex predators. Between North Atlantic and North Pacific Ocean basins, for example, species in the Eastern Pacific exhibited either later maturation, lower fecundity, and/or greater annual survival than conspecifics in the Western Atlantic. Parallel variations in life histories among trophic levels also occur in adjacent seas and between eastern vs. western ocean boundaries. For example, zooplankton and seabird species in cooler Barents Sea waters exhibit lower fecundity or greater annual survival than conspecifics in the Northeast Atlantic. Sea turtles exhibit a larger size and a greater reproductive output in the Western Pacific vs. Eastern Pacific. These examples provide evidence for food-web-wide modifications in life history strategies in response to environmental forcing. We hypothesize that such dichotomies result from frequency and amplitude shifts in resource availability over varying temporal and spatial scales. We review data that supports three primary mechanisms by which environmental forcing affects life history strategies: (1) food-web structure; (2) climate variability affecting the quantity and seasonality of primary productivity; (3) bottom-up vs. top-down forcing. These proposed mechanisms provide a framework for comparisons of ecosystem function among oceanic regions (or regimes) and are essential in modeling ecosystem response to climate change, as well as for creating dynamic ecosystem-based marine conservation strategies.
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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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Spatio-temporal models to determine association between Campylobacter cases and environment
Sanderson, Roy A; Maas, James A; Blain, Alasdair P; Gorton, Russell; Ward, Jessica; O’Brien, Sarah J; Hunter, Paul R; Rushton, Stephen P
2018-01-01
Abstract Background Campylobacteriosis is a major cause of gastroenteritis in the UK, and although 70% of cases are associated with food sources, the remainder are probably associated with wider environmental exposure. Methods In order to investigate wider environmental transmission, we conducted a spatio-temporal analysis of the association of human cases of Campylobacter in the Tyne catchment with weather, climate, hydrology and land use. A hydrological model was used to predict surface-water flow in the Tyne catchment over 5 years. We analysed associations between population-adjusted Campylobacter case rate and environmental factors hypothesized to be important in disease using a two-stage modelling framework. First, we investigated associations between temporal variation in case rate in relation to surface-water flow, temperature, evapotranspiration and rainfall, using linear mixed-effects models. Second, we used the random effects for the first model to quantify how spatial variation in static landscape features of soil and land use impacted on the likely differences between subcatchment associations of case rate with the temporal variables. Results Population-adjusted Campylobacter case rates were associated with periods of high predicted surface-water flow, and during above average temperatures. Subcatchments with cattle on stagnogley soils, and to a lesser extent sheep plus cattle grazing, had higher Campylobacter case rates. Conclusions Areas of stagnogley soils with mixed livestock grazing may be more vulnerable to both Campylobacter spread and exposure during periods of high rainfall, with resultant increased risk of human cases of the disease. PMID:29069406
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Mapping the unknown: Modeling future scenarios of riverine fish communities
Riverscapes can be defined by spatial and temporal variation in a suite of environmental conditions that influence the distribution and persistence of riverine fish populations. Fish in riverscapes can exhibit extensive movements, require seasonally-distinct habitats for spawnin...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Lehman, P.W.
Long-term changes in chlorophyll concentration were predicted from environmental variables using Box-Jenkins transfer function models for the Sacramento and San Joaquin rivers and Suisun Bay. The indication that oceanic phytoplankton biomass for the California regions is associated with climatic phenomena produced by El Nino and the Southern Oscillation (ENSO) was one of several factors used to standardize the dataset. Data used for the analyses were collected continuously on a semimonthly or monthly basis over the 17-yr period between 1971 and 1987. Groups of highly correlated environmental variables were summarized along three environmental axes using principal component analysis. The first environmentalmore » axis summarized river flow and specific conductance. The second environmental axis summarized water transparency and the third environmental axis summarized air and water temperature. Chlorophyll concentration was significantly cross-correlated with environmental axes and individual environmental variables. Transfer function models developed to describe changes in chlorophyll concentration over time were characterized by lag responses and described between 41% and 51% of the data variation. Significant cross-correlations between environmental axes and the California climate index (CA SLP) were used to develop a conceptual model of the link between regional climate and estuarine production. 50 refs., 5 figs.« less
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Neurobehavioral foundation of environmental reactivity.
Moore, Sarah R; Depue, Richard A
2016-02-01
Sensitivity to environmental context has been of interest for many years, but the nature of individual differences in environmental sensitivity has become of particular focus over the past 2 decades. What is particularly uncertain are the neural variables and processes that mediate the effects of environment on developmental outcomes. Accordingly, we provide a neurobehavioral foundation of reactivity to the environment in several steps. First, the different patterns of environmental sensitivity are defined to identify the significant factors involved in the manifestation of these patterns. Second, we focus on neurobiological reactivity as the construct underlying variation in sensitivity to the environment by (a) providing an organizing threshold model of elicitation of neurobiology by environmental context; and (b) integrating the literature on 2 sets of neuromodulators in terms of each modulator's (a) contribution to neural and behavioral reactivity to stimulation, and (b) relation to emotional-motivational systems (dopamine, opiates and oxytocin, corticotropin-releasing hormone) or the general modulation of those systems (serotonin, norepinephrine, and GABA). Discussion concludes with (a) a comprehensive neurobehavioral framework of environmental reactivity based on a combinatorial model of a supertrait, (b) methodological implications of the model, and (c) a developmental perspective on environmental reactivity. (c) 2016 APA, all rights reserved).
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Ezenwa, V.O.; Milheim, L.E.; Coffey, M.F.; Godsey, M.S.; King, R.J.; Guptill, S.C.
2007-01-01
Identifying links between environmental variables and infectious disease risk is essential to understanding how human-induced environmental changes will effect the dynamics of human and wildlife diseases. Although land cover change has often been tied to spatial variation in disease occurrence, the underlying factors driving the correlations are often unknown, limiting the applicability of these results for disease prevention and control. In this study, we described associations between land cover composition and West Nile virus (WNV) infection prevalence, and investigated three potential processes accounting for observed patterns: (1) variation in vector density; (2) variation in amplification host abundance; and (3) variation in host community composition. Interestingly, we found that WNV infection rates among Culex mosquitoes declined with increasing wetland cover, but wetland area was not significantly associated with either vector density or amplification host abundance. By contrast, wetland area was strongly correlated with host community composition, and model comparisons suggested that this factor accounted, at least partially, for the observed effect of wetland area on WNV infection risk. Our results suggest that preserving large wetland areas, and by extension, intact wetland bird communities, may represent a valuable ecosystem-based approach for controlling WNV outbreaks. ?? Mary Ann Liebert, Inc.
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Few, Lauren R.; Grant, Julia D; Trull, Timothy J.; Statham, Dixie J.; Martin, Nicholas G.; Lynskey, Michael T.; Agrawal, Arpana
2014-01-01
Aims To examine the genetic overlap between borderline personality features (BPF) and substance use disorders (SUDs) and the extent to which variation in personality traits contributes to this covariance. Design Genetic structural equation modelling was used to partition the variance in and covariance between personality traits, BPF, and SUDs into additive genetic, shared, and individual-specific environmental factors. Setting All participants were registered with the Australian Twin Registry. Participants A total of 3,127 Australian adult twins participated in the study. Measurements Diagnoses of DSM-IV alcohol and cannabis abuse/dependence (AAD; CAD), and nicotine dependence (ND) were derived via computer-assisted telephone interview. BPF and five-factor model personality traits were derived via self-report questionnaires. Findings Genetic factors were responsible for 49% (95%CI: 42%–55%) of the variance in BPF, 38–42% (95%CI range: 32%–49%) for personality traits and 47% (95%CI: 17%–77%), 54% (95%CI: 43%–64%), and 78% (67%–86%) for ND, AAD and CAD, respectively. Genetic and individual-specific environmental correlations between BPF and SUDs ranged from .33–.56 (95%CI range: .19–.74) and .19–.32 (95%CI range: .06–.43), respectively. Overall, there was substantial support for genetic influences that were specific to AAD, ND and CAD (31%–69%). Finally, genetic variation in personality traits was responsible for 11% (Extraversion for CAD) to 59% (Neuroticism for AAD) of the correlation between BPF and SUDs. Conclusions Both genetic and individual-specific environmental factors contribute to comorbidity between borderline personality features and substance use disorders. A substantial proportion of this comorbidity can be attributed to variation in normal personality traits, particularly Neuroticism. PMID:25041562
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Few, Lauren R; Grant, Julia D; Trull, Timothy J; Statham, Dixie J; Martin, Nicholas G; Lynskey, Michael T; Agrawal, Arpana
2014-12-01
To examine the genetic overlap between borderline personality features (BPF) and substance use disorders (SUDs) and the extent to which variation in personality traits contributes to this covariance. Genetic structural equation modelling was used to partition the variance in and covariance between personality traits, BPF and SUDs into additive genetic, shared and individual-specific environmental factors. All participants were registered with the Australian Twin Registry. A total of 3127 Australian adult twins participated in the study. Diagnoses of DSM-IV alcohol and cannabis abuse/dependence (AAD; CAD) and nicotine dependence (ND) were derived via computer-assisted telephone interview. BPF and five-factor model personality traits were derived via self-report questionnaires. Personality traits, BPF and substance use disorders were partially influenced by genetic factors with heritability estimates ranging from 0.38 (neuroticism; 95% confidence interval: 0.30-0.45) to 0.78 (CAD; 95% confidence interval: 0.67-0.86). Genetic and individual-specific environmental correlations between BPF and SUDs ranged from 0.33 to 0.56 (95% CI = 0.19-0.74) and 0.19-0.32 (95% CI = 0.06-0.43), respectively. Overall, there was substantial support for genetic influences that were specific to AAD, ND and CAD (30.76-68.60%). Finally, genetic variation in personality traits was responsible for 11.46% (extraversion for CAD) to 59.30% (neuroticism for AAD) of the correlation between BPF and SUDs. Both genetic and individual-specific environmental factors contribute to comorbidity between borderline personality features and substance use disorders. A substantial proportion of this comorbidity can be attributed to variation in normal personality traits, particularly neuroticism. © 2014 Society for the Study of Addiction.
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Carroll, Carlos; Roberts, David R; Michalak, Julia L; Lawler, Joshua J; Nielsen, Scott E; Stralberg, Diana; Hamann, Andreas; Mcrae, Brad H; Wang, Tongli
2017-11-01
As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.
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Welch, Brandi C.; Boal, Clint W.; Skipper, Ben R.
2017-01-01
Identifying sources of annual variation in the reproductive success of a species may provide valuable insights into how the species may be affected by future environmental or climatic conditions. We examined annual variation in the nesting phenology, productivity, and apparent nest success of Mississippi Kites (Ictinia mississippiensis), a species common in urban areas in the southern Great Plains, from May through August. We monitored 498 Mississippi Kite nesting attempts in Lubbock, Texas, USA, between 2004 and 2015, from which we modeled daily survival rate as a function of local weather conditions, drought severity, and the state of the El Niño Southern Oscillation. We observed significant annual variation in median incubation initiation date (range = May 20 to June 5), the probability of nest success (range = 0.31–0.90), and productivity (range = 0.25–1.00 fledglings per nest). Our models of daily survival rate suggested that higher daily temperatures, severe storm events, extreme drought conditions, and La Niña events negatively influenced nest survival. These results suggest that increasing storm frequency and higher temperatures associated with climate change are likely to decrease the nesting success of Mississippi Kites in the southern Great Plains.
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Carr, Tony; Yang, Haishun; Ray, Chittaranjan
2016-01-01
Water Productivity (WP) of a crop defines the relationship between the economic or physical yield of the crop and its water use. With this concept it is possible to identify disproportionate water use or water-limited yield gaps and thereby support improvements in agricultural water management. However, too often important qualitative and quantitative environmental factors are not part of a WP analysis and therefore neglect the aspect of maintaining a sustainable agricultural system. In this study, we examine both the physical and economic WP in perspective with temporally changing environmental conditions. The physical WP analysis was performed by comparing simulated maximum attainable corn yields per unit of water using the crop model Hybrid-Maize with observed data from 2005 through 2013 from 108 farm plots in the Central Platte and the Tri Basin Natural Resource Districts of Nebraska. In order to expand the WP analysis on external factors influencing yields, a second model, Maize-N, was used to estimate optimal nitrogen (N)–fertilizer rate for specific fields in the study area. Finally, a vadose zone flow and transport model, HYDRUS-1D for simulating vertical nutrient transport in the soil, was used to estimate locations of nitrogen pulses in the soil profile. The comparison of simulated and observed data revealed that WP was not on an optimal level, mainly due to large amounts of irrigation used in the study area. The further analysis illustrated year-to-year variations of WP during the nine consecutive years, as well as the need to improve fertilizer management to favor WP and environmental quality. In addition, we addressed the negative influence of groundwater depletion on the economic WP through increasing pumping costs. In summary, this study demonstrated that involving temporal variations of WP as well as associated environmental and economic issues can represent a bigger picture of WP that can help to create incentives to sustainably improve agricultural production. PMID:27575368
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Westberg, Erik; Ohali, Shachar; Shevelevich, Anatoly; Fine, Pinchas; Barazani, Oz
2013-01-01
Abstract In Israel Eruca sativa has a geographically narrow distribution across a steep climatic gradient that ranges from mesic Mediterranean to hot desert environments. These conditions offer an opportunity to study the influence of the environment on intraspecific genetic variation. For this, we combined an analysis of neutral genetic markers with a phenotypic evaluation in common-garden experiments, and environmental characterization of populations that included climatic and edaphic parameters, as well as geographic distribution. A Bayesian clustering of individuals from nine representative populations based on amplified fragment length polymorphism (AFLP) divided the populations into a southern and a northern geographic cluster, with one admixed population at the geographic border between them. Linear mixed models, with cluster added as a grouping factor, revealed no clear effects of environment or geography on genetic distances, but this may be due to a strong association of geography and environment with genetic clusters. However, environmental factors accounted for part of the phenotypic variation observed in the common-garden experiments. In addition, candidate loci for selection were identified by association with environmental parameters and by two outlier methods. One locus, identified by all three methods, also showed an association with trichome density and herbivore damage, in net-house and field experiments, respectively. Accordingly, we propose that because trichomes are directly linked to defense against both herbivores and excess radiation, they could potentially be related to adaptive variation in these populations. These results demonstrate the value of combining environmental and phenotypic data with a detailed genetic survey when studying adaptation in plant populations. This article describes the use of several types of data to estimate the influence of the environment on intraspecific genetic variation in populations originating from a steep climatic gradient. In addition to molecular marker data, we made use of phenotypic evaluation from common garden experiments, and a broad GIS based environmental data with edaphic information gathered in the field. This study, among others, lead to the identification of an outlier locus with an association to trichome formation and herbivore defense, and its ecological adaptive value is discussed. PMID:24567822
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Bell, David M; Ward, Eric J; Oishi, A Christopher; Oren, Ram; Flikkema, Paul G; Clark, James S
2015-07-01
Uncertainties in ecophysiological responses to environment, such as the impact of atmospheric and soil moisture conditions on plant water regulation, limit our ability to estimate key inputs for ecosystem models. Advanced statistical frameworks provide coherent methodologies for relating observed data, such as stem sap flux density, to unobserved processes, such as canopy conductance and transpiration. To address this need, we developed a hierarchical Bayesian State-Space Canopy Conductance (StaCC) model linking canopy conductance and transpiration to tree sap flux density from a 4-year experiment in the North Carolina Piedmont, USA. Our model builds on existing ecophysiological knowledge, but explicitly incorporates uncertainty in canopy conductance, internal tree hydraulics and observation error to improve estimation of canopy conductance responses to atmospheric drought (i.e., vapor pressure deficit), soil drought (i.e., soil moisture) and above canopy light. Our statistical framework not only predicted sap flux observations well, but it also allowed us to simultaneously gap-fill missing data as we made inference on canopy processes, marking a substantial advance over traditional methods. The predicted and observed sap flux data were highly correlated (mean sensor-level Pearson correlation coefficient = 0.88). Variations in canopy conductance and transpiration associated with environmental variation across days to years were many times greater than the variation associated with model uncertainties. Because some variables, such as vapor pressure deficit and soil moisture, were correlated at the scale of days to weeks, canopy conductance responses to individual environmental variables were difficult to interpret in isolation. Still, our results highlight the importance of accounting for uncertainty in models of ecophysiological and ecosystem function where the process of interest, canopy conductance in this case, is not observed directly. The StaCC modeling framework provides a statistically coherent approach to estimating canopy conductance and transpiration and propagating estimation uncertainty into ecosystem models, paving the way for improved prediction of water and carbon uptake responses to environmental change. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Variations and heredity in bacterial colonies
Čepl, Jaroslav; Blahůšková, Anna; Neubauer, Zdeněk; Markoš, Anton
2016-01-01
ABSTRACT Spontaneous variation in appearance was studied in bacterial colonies of Serratia marcescens F morphotype1: (i) A defined array of non-heritable phenotype variations does appear repeatedly; (ii) The presence of colonies of different bacterial species will narrow the variability toward the typical F appearance, as if such an added environmental factor curtailed the capacity of colony morphospace; (iii) Similarly the morphospace becomes reduced by random mutations leading to new, heritable morphotypes—at the same time opening a new array of variations typical for the mutant but not accessible directly from the original F morphospace. Results are discussed in context with biphasic model of early morphogenesis applicable to all multicellular bodies. PMID:28042382
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Mayer, Melanie G.; Sommer, Ralf J.
2011-01-01
Many free-living nematodes, including the laboratory model organisms Caenorhabditis elegans and Pristionchus pacificus, have a choice between direct and indirect development, representing an important case of phenotypic plasticity. Under harsh environmental conditions, these nematodes form dauer larvae, which arrest development, show high resistance to environmental stress and constitute a dispersal stage. Pristionchus pacificus occurs in a strong association with scarab beetles in the wild and remains in the dauer stage on the living beetle. Here, we explored the circumstances under which P. pacificus enters and exits the dauer stage by using a natural variation approach. The analysis of survival, recovery and fitness after dauer exit of eight P. pacificus strains revealed that dauer larvae can survive for up to 1 year under experimental conditions. In a second experiment, we isolated dauer pheromones from 16 P. pacificus strains, and tested for natural variation in pheromone production and sensitivity in cross-reactivity assays. Surprisingly, 13 of the 16 strains produce a pheromone that induces the highest dauer formation in individuals of other genotypes. These results argue against a simple adaptation model for natural variation in dauer formation and suggest that strains may have evolved to induce dauer formation precociously in other strains in order to reduce the fitness of these strains. We therefore discuss intraspecific competition among genotypes as a previously unconsidered aspect of dauer formation. PMID:21307052
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Russ, Tom C.; Gatz, Margaret; Pedersen, Nancy L.; Hannah, Jean; Wyper, Grant; Batty, G. David; Deary, Ian J.; Starr, John M.
2015-01-01
Background This study aimed to estimate the magnitude of geographical variation in dementia rates and suggest explanations for this variation. Small-area studies are scarce, and none has adequately investigated the relative contribution of genetic and environmental factors to the distribution of dementia. Methods We present two complementary small-area hierarchical Bayesian disease mapping studies using the comprehensive Swedish Twin Registry (n=27,680) and the 1932 Scottish Mental Survey cohort (n=37,597). The twin study allowed us to isolate the area in order to examine the effect of unshared environmental factors. The Scottish Mental Survey study allowed us to examine various epochs in the life course – approximately age 11 years and adulthood. Results We found a 2-to 3- fold geographical variation in dementia odds in Sweden, after twin random effects – likely to capture genetic and shared environmental variance – were removed. In Scotland we found no variation in dementia odds in childhood but substantial variation, following a broadly similar pattern to Sweden, by adulthood. Conclusions There is geographical variation in dementia rates. Most of this variation is likely to result from unshared environmental factors that have their effect in adolescence or later. Further work is required to confirm these findings and identify any potentially modifiable socio-environmental risk factors for dementia responsible for this geographical variation in risk. However, if these factors do exist and could be optimized in the whole population, our results suggest that dementia rates could be halved. PMID:25575031
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Same genetic components underlie different measures of sweet taste preference.
Keskitalo, Kaisu; Tuorila, Hely; Spector, Tim D; Cherkas, Lynn F; Knaapila, Antti; Silventoinen, Karri; Perola, Markus
2007-12-01
Sweet taste preferences are measured by several often correlated measures. We examined the relative proportions of genetic and environmental effects on sweet taste preference indicators and their mutual correlations. A total of 663 female twins (324 complete pairs, 149 monozygous and 175 dizygous pairs) aged 17-80 y rated the liking and intensity of a 20% (wt/vol) sucrose solution, reported the liking and the use-frequency of 6 sweet foods (sweet desserts, sweets, sweet pastry, ice cream, hard candy, and chocolate), and completed a questionnaire on cravings of sweet foods. The estimated contributions of genetic factors, environmental factors shared by a twin pair, and environmental factors unique to each twin individual to the variance and covariance of the traits were obtained with the use of linear structural equation modeling. Approximately half of the variation in liking for sweet solution and liking and use-frequency of sweet foods (49-53%) was explained by genetic factors, whereas the rest of the variation was due to environmental factors unique to each twin individual. Sweet taste preference-related traits were correlated. Tetravariate modeling showed that the correlation between liking for the sweet solution and liking for sweet foods was due to genetic factors (genetic r = 0.27). Correlations between liking, use-frequency, and craving for sweet foods were due to both genetic and unshared environmental factors. Detailed information on the associations between preference measures is an important intermediate goal in the determination of the genetic components affecting sweet taste preferences.
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Lallias, Delphine; Hiddink, Jan G; Fonseca, Vera G; Gaspar, John M; Sung, Way; Neill, Simon P; Barnes, Natalie; Ferrero, Tim; Hall, Neil; Lambshead, P John D; Packer, Margaret; Thomas, W Kelley; Creer, Simon
2015-01-01
Assessing how natural environmental drivers affect biodiversity underpins our understanding of the relationships between complex biotic and ecological factors in natural ecosystems. Of all ecosystems, anthropogenically important estuaries represent a ‘melting pot' of environmental stressors, typified by extreme salinity variations and associated biological complexity. Although existing models attempt to predict macroorganismal diversity over estuarine salinity gradients, attempts to model microbial biodiversity are limited for eukaryotes. Although diatoms commonly feature as bioindicator species, additional microbial eukaryotes represent a huge resource for assessing ecosystem health. Of these, meiofaunal communities may represent the optimal compromise between functional diversity that can be assessed using morphology and phenotype–environment interactions as compared with smaller life fractions. Here, using 454 Roche sequencing of the 18S nSSU barcode we investigate which of the local natural drivers are most strongly associated with microbial metazoan and sampled protist diversity across the full salinity gradient of the estuarine ecosystem. In order to investigate potential variation at the ecosystem scale, we compare two geographically proximate estuaries (Thames and Mersey, UK) with contrasting histories of anthropogenic stress. The data show that although community turnover is likely to be predictable, taxa are likely to respond to different environmental drivers and, in particular, hydrodynamics, salinity range and granulometry, according to varied life-history characteristics. At the ecosystem level, communities exhibited patterns of estuary-specific similarity within different salinity range habitats, highlighting the environmental sequencing biomonitoring potential of meiofauna, dispersal effects or both. PMID:25423027
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Isabwe, Alain; Yang, Jun R; Wang, Yongming; Liu, Lemian; Chen, Huihuang; Yang, Jun
2018-07-15
Although the influence of microbial community assembly processes on aquatic ecosystem function and biodiversity is well known, the processes that govern planktonic communities in human-impacted rivers remain largely unstudied. Here, we used multivariate statistics and a null model approach to test the hypothesis that environmental conditions and obstructed dispersal opportunities, dictate a deterministic community assembly for phytoplankton and bacterioplankton across contrasting hydrographic conditions in a subtropical mid-sized river (Jiulong River, southeast China). Variation partitioning analysis showed that the explanatory power of local environmental variables was larger than that of the spatial variables for both plankton communities during the dry season. During the wet season, phytoplankton community variation was mainly explained by local environmental variables, whereas the variance in bacterioplankton was explained by both environmental and spatial predictors. The null model based on Raup-Crick coefficients for both planktonic groups suggested little evidences of the stochastic processes involving dispersal and random distribution. Our results showed that hydrological change and landscape structure act together to cause divergence in communities along the river channel, thereby dictating a deterministic assembly and that selection exceeds dispersal limitation during the dry season. Therefore, to protect the ecological integrity of human-impacted rivers, watershed managers should not only consider local environmental conditions but also dispersal routes to account for the effect of regional species pool on local communities. Copyright © 2018 Elsevier B.V. All rights reserved.
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Dispersal, environmental niches and oceanic-scale turnover in deep-sea bivalves
McClain, Craig R.; Stegen, James C.; Hurlbert, Allen H.
2012-01-01
Patterns of beta-diversity or distance decay at oceanic scales are completely unknown for deep-sea communities. Even when appropriate data exist, methodological problems have made it difficult to discern the relative roles of environmental filtering and dispersal limitation for generating faunal turnover patterns. Here, we combine a spatially extensive dataset on deep-sea bivalves with a model incorporating ecological dynamics and shared evolutionary history to quantify the effects of environmental filtering and dispersal limitation. Both the model and empirical data are used to relate functional, taxonomic and phylogenetic similarity between communities to environmental and spatial distances separating them for 270 sites across the Atlantic Ocean. This study represents the first ocean-wide analysis examining distance decay as a function of a broad suite of explanatory variables. We find that both strong environmental filtering and dispersal limitation drive turnover in taxonomic, functional and phylogenetic composition in deep-sea bivalves, explaining 26 per cent, 34 per cent and 9 per cent of the variation, respectively. This contrasts with previous suggestions that dispersal is not limiting in broad-scale biogeographic and biodiversity patterning in marine systems. However, rates of decay in similarity with environmental distance were eightfold to 44-fold steeper than with spatial distance. Energy availability is the most influential environmental variable evaluated, accounting for 3.9 per cent, 9.4 per cent and 22.3 per cent of the variation in functional, phylogenetic and taxonomic similarity, respectively. Comparing empirical patterns with process-based theoretical predictions provided quantitative estimates of dispersal limitation and niche breadth, indicating that 95 per cent of deep-sea bivalve propagules will be able to persist in environments that deviate from their optimum by up to 2.1 g m−2 yr−1 and typically disperse 749 km from their natal site. PMID:22189399
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Thompson, Corinne N; Zelner, Jonathan L; Nhu, Tran Do Hoang; Phan, My Vt; Hoang Le, Phuc; Nguyen Thanh, Hung; Vu Thuy, Duong; Minh Nguyen, Ngoc; Ha Manh, Tuan; Van Hoang Minh, Tu; Lu Lan, Vi; Nguyen Van Vinh, Chau; Tran Tinh, Hien; von Clemm, Emmiliese; Storch, Harry; Thwaites, Guy; Grenfell, Bryan T; Baker, Stephen
2015-09-01
It is predicted that the integration of climate-based early warning systems into existing action plans will facilitate the timely provision of interventions to diarrheal disease epidemics in resource-poor settings. Diarrhea remains a considerable public health problem in Ho Chi Minh City (HCMC), Vietnam and we aimed to quantify variation in the impact of environmental conditions on diarrheal disease risk across the city. Using all inpatient diarrheal admissions data from three large hospitals within HCMC, we developed a mixed effects regression model to differentiate district-level variation in risk due to environmental conditions from the overarching seasonality of diarrheal disease hospitalization in HCMC. We identified considerable spatial heterogeneity in the risk of all-cause diarrhea across districts of HCMC with low elevation and differential responses to flooding, air temperature, and humidity driving further spatial heterogeneity in diarrheal disease risk. The incorporation of these results into predictive forecasting algorithms will provide a powerful resource to aid diarrheal disease prevention and control practices in HCMC and other similar settings. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
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Intraspecific variation shapes community-level behavioral responses to urbanization in spiders.
Dahirel, Maxime; Dierick, Jasper; De Cock, Maarten; Bonte, Dries
2017-09-01
Urban areas are an extreme example of human-changed environments, exposing organisms to multiple and strong selection pressures. Adaptive behavioral responses are thought to play a major role in animals' success or failure in such new environments. Approaches based on functional traits have proven especially valuable to understand how species communities respond to environmental gradients. Until recently, they have, however, often ignored the potential consequences of intraspecific trait variation (ITV). When ITV is prevalent, it may highly impact ecological processes and resilience against stressors. This may be especially relevant in animals, in which behavioral traits can be altered very flexibly at the individual level to track environmental changes. We investigated how species turnover and ITV influenced community-level behavioral responses in a set of 62 sites of varying levels of urbanization, using orb web spiders and their webs as models of foraging behavior. ITV alone explained around one-third of the total trait variation observed among communities. Spider web structure changed according to urbanization, in ways that increase the capture efficiency of webs in a context of smaller urban prey. These trait shifts were partly mediated by species turnover, but ITV increased their magnitude, potentially helping to buffer the effects of environmental changes on communities. The importance of ITV varied depending on traits and on the spatial scale at which urbanization was considered. Despite being neglected from community-level analyses in animals, our results highlight the importance of accounting for intraspecific trait variation to fully understand trait responses to (human-induced) environmental changes and their impact on ecosystem functioning. © 2017 by the Ecological Society of America.
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A genetic perspective on the proposed inclusion of cannabis withdrawal in DSM-5.
Verweij, K J H; Agrawal, A; Nat, N O; Creemers, H E; Huizink, A C; Martin, N G; Lynskey, M T
2013-08-01
Various studies support the inclusion of cannabis withdrawal in the diagnosis of cannabis use disorder (CUD) in the upcoming DSM-5. The aims of the current study were to (1) estimate the prevalence of DSM-5 cannabis withdrawal (criterion B), (2) estimate the role of genetic and environmental influences on individual differences in cannabis withdrawal and (3) determine the extent to which genetic and environmental influences on cannabis withdrawal overlap with those on DSM-IV-defined abuse/dependence. The sample included 2276 lifetime cannabis-using adult Australian twins. Cannabis withdrawal was defined in accordance with criterion B of the proposed DSM-5 revisions. Cannabis abuse/dependence was defined as endorsing one or more DSM-IV criteria of abuse or three or more dependence criteria. The classical twin model was used to estimate the genetic and environmental influences on variation in cannabis withdrawal, along with its covariation with abuse/dependence. Of all the cannabis users, 11.9% met criteria for cannabis withdrawal. Around 50% of between-individual variation in withdrawal could be attributed to additive genetic variation, and the rest of the variation was mostly due to non-shared environmental influences. Importantly, the genetic influences on cannabis withdrawal almost completely (99%) overlapped with those on abuse/dependence. We have shown that cannabis withdrawal symptoms exist among cannabis users, and that cannabis withdrawal is moderately heritable. Genetic influences on cannabis withdrawal are the same as those affecting abuse/dependence. These results add to the wealth of literature that recommends the addition of cannabis withdrawal to the diagnosis of DSM-5 CUD.
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A genetic perspective on the proposed inclusion of cannabis withdrawal in the DSM-5
Verweij, K.J.H.; Agrawal, A.; Nat, N.O.; Creemers, H.E.; Huizink, A.C.; Martin, N.G.; Lynskey, M.T.
2013-01-01
Background Various studies support the inclusion of cannabis withdrawal to the diagnosis of cannabis use disorders in the upcoming DSM-5. The aims of the current study were to (1) estimate the prevalence of DSM-5 cannabis withdrawal (Criterion B), (2) estimate the role of genetic and environmental influences on individual differences in cannabis withdrawal, and (3) determine the extent to which genetic and environmental influences on cannabis withdrawal overlap with those on DSM-IV defined abuse/dependence. Methods The sample included 2276 lifetime cannabis-using adult Australian twins. Cannabis withdrawal was defined in accordance with Criterion B of the proposed DSM-5 revisions. Cannabis abuse/dependence was defined as endorsing one or more DSM-IV criteria of abuse or three or more dependence criteria. The classical twin model was used to estimate the genetic and environmental influences on variation in cannabis withdrawal, as well as its covariation with abuse/dependence. Results Of all cannabis users 11.9% met criteria for cannabis withdrawal. Around 50% of between-individual variation in withdrawal could be attributed to additive genetic variation, and the rest of the variation was mostly due to non-shared environmental influences. Importantly, the genetic influences on cannabis withdrawal almost completely (99%) overlapped with those on abuse/dependence. Conclusions We showed that cannabis withdrawal symptoms exist among cannabis users, and that cannabis withdrawal is moderately heritable. Genetic influences on cannabis withdrawal are the same as those influencing abuse/dependence. These results add to the wealth of literature that recommends the addition of cannabis withdrawal to the diagnosis of DSM-5 cannabis use disorders. PMID:23194657
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Modelling food-web mediated effects of hydrological variability and environmental flows.
Robson, Barbara J; Lester, Rebecca E; Baldwin, Darren S; Bond, Nicholas R; Drouart, Romain; Rolls, Robert J; Ryder, Darren S; Thompson, Ross M
2017-11-01
Environmental flows are designed to enhance aquatic ecosystems through a variety of mechanisms; however, to date most attention has been paid to the effects on habitat quality and life-history triggers, especially for fish and vegetation. The effects of environmental flows on food webs have so far received little attention, despite food-web thinking being fundamental to understanding of river ecosystems. Understanding environmental flows in a food-web context can help scientists and policy-makers better understand and manage outcomes of flow alteration and restoration. In this paper, we consider mechanisms by which flow variability can influence and alter food webs, and place these within a conceptual and numerical modelling framework. We also review the strengths and weaknesses of various approaches to modelling the effects of hydrological management on food webs. Although classic bioenergetic models such as Ecopath with Ecosim capture many of the key features required, other approaches, such as biogeochemical ecosystem modelling, end-to-end modelling, population dynamic models, individual-based models, graph theory models, and stock assessment models are also relevant. In many cases, a combination of approaches will be useful. We identify current challenges and new directions in modelling food-web responses to hydrological variability and environmental flow management. These include better integration of food-web and hydraulic models, taking physiologically-based approaches to food quality effects, and better representation of variations in space and time that may create ecosystem control points. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
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A Test of Carbon and Oxygen Stable Isotope Ratio Process Models in Tree Rings.
NASA Astrophysics Data System (ADS)
Roden, J. S.; Farquhar, G. D.
2008-12-01
Stable isotopes ratios of carbon and oxygen in tree ring cellulose have been used to infer environmental change. Process-based models have been developed to clarify the potential of historic tree ring records for meaningful paleoclimatic reconstructions. However, isotopic variation can be influenced by multiple environmental factors making simplistic interpretations problematic. Recently, the dual isotope approach, where the variation in one stable isotope ratio (e.g. oxygen) is used to constrain the interpretation of variation in another (e.g. carbon), has been shown to have the potential to de-convolute isotopic analysis. However, this approach requires further testing to determine its applicability for paleo-reconstructions using tree-ring time series. We present a study where the information needed to parameterize mechanistic models for both carbon and oxygen stable isotope ratios were collected in controlled environment chambers for two species (Pinus radiata and Eucalyptus globulus). The seedlings were exposed to treatments designed to modify leaf temperature, transpiration rates, stomatal conductance and photosynthetic capacity. Both species were grown for over 100 days under two humidity regimes that differed by 20%. Stomatal conductance was significantly different between species and for seedlings under drought conditions but not between other treatments or humidity regimes. The treatments produced large differences in transpiration rate and photosynthesis. Treatments that effected photosynthetic rates but not stomatal conductance influenced carbon isotope discrimination more than those that influenced primarily conductance. The various treatments produced a range in oxygen isotope ratios of 7 ‰. Process models predicted greater oxygen isotope enrichment in tree ring cellulose than observed. The oxygen isotope ratios of bulk leaf water were reasonably well predicted by current steady-state models. However, the fractional difference between models that predict bulk leaf water versus the site of evaporation did not increase with transpiration rates. In conclusion, although the dual isotope approach may better constrain interpretation of isotopic variation, more work is required before its predictive power can be applied to tree-ring archives.
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Learning, climate and the evolution of cultural capacity.
Whitehead, Hal
2007-03-21
Patterns of environmental variation influence the utility, and thus evolution, of different learning strategies. I use stochastic, individual-based evolutionary models to assess the relative advantages of 15 different learning strategies (genetic determination, individual learning, vertical social learning, horizontal/oblique social learning, and contingent combinations of these) when competing in variable environments described by 1/f noise. When environmental variation has little effect on fitness, then genetic determinism persists. When environmental variation is large and equal over all time-scales ("white noise") then individual learning is adaptive. Social learning is advantageous in "red noise" environments when variation over long time-scales is large. Climatic variability increases with time-scale, so that short-lived organisms should be able to rely largely on genetic determination. Thermal climates usually are insufficiently red for social learning to be advantageous for species whose fitness is very determined by temperature. In contrast, population trajectories of many species, especially large mammals and aquatic carnivores, are sufficiently red to promote social learning in their predators. The ocean environment is generally redder than that on land. Thus, while individual learning should be adaptive for many longer-lived organisms, social learning will often be found in those dependent on the populations of other species, especially if they are marine. This provides a potential explanation for the evolution of a prevalence of social learning, and culture, in humans and cetaceans.
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González-Moreno, A; Bordera, S; Leirana-Alcocer, J; Delfín-González, H
2012-06-01
The biology and behavior of insects are strongly influenced by environmental conditions such as temperature and precipitation. Because some of these factors present a within day variation, they may be causing variations on insect diurnal flight activity, but scant information exists on the issue. The aim of this work was to describe the patterns on diurnal variation of the abundance of Ichneumonoidea and their relation with relative humidity, temperature, light intensity, and wind speed. The study site was a tropical dry forest at Ría Lagartos Biosphere Reserve, Mexico; where correlations between environmental factors (relative humidity, temperature, light, and wind speed) and abundance of Ichneumonidae and Braconidae (Hymenoptera: Ichneumonoidea) were estimated. The best regression model for explaining abundance variation was selected using the second order Akaike Information Criterion. The optimum values of temperature, humidity, and light for flight activity of both families were also estimated. Ichneumonid and braconid abundances were significantly correlated to relative humidity, temperature, and light intensity; ichneumonid also showed significant correlations to wind speed. The second order Akaike Information Criterion suggests that in tropical dry conditions, relative humidity is more important that temperature for Ichneumonoidea diurnal activity. Ichneumonid wasps selected toward intermediate values of relative humidity, temperature and the lowest wind speeds; while Braconidae selected for low values of relative humidity. For light intensity, braconids presented a positive selection for moderately high values.
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Langlois, C; Simon, L; Lécuyer, Ch
2003-12-01
A time-dependent box model is developed to calculate oxygen isotope compositions of bone phosphate as a function of environmental and physiological parameters. Input and output oxygen fluxes related to body water and bone reservoirs are scaled to the body mass. The oxygen fluxes are evaluated by stoichiometric scaling to the calcium accretion and resorption rates, assuming a pure hydroxylapatite composition for the bone and tooth mineral. The model shows how the diet composition, body mass, ambient relative humidity and temperature may control the oxygen isotope composition of bone phosphate. The model also computes how bones and teeth record short-term variations in relative humidity, air temperature and delta18O of drinking water, depending on body mass. The documented diversity of oxygen isotope fractionation equations for vertebrates is accounted for by our model when for each specimen the physiological and diet parameters are adjusted in the living range of environmental conditions.
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Joost, Stéphane; Kalbermatten, Michael; Bezault, Etienne; Seehausen, Ole
2012-01-01
When searching for loci possibly under selection in the genome, an alternative to population genetics theoretical models is to establish allele distribution models (ADM) for each locus to directly correlate allelic frequencies and environmental variables such as precipitation, temperature, or sun radiation. Such an approach implementing multiple logistic regression models in parallel was implemented within a computing program named MATSAM: . Recently, this application was improved in order to support qualitative environmental predictors as well as to permit the identification of associations between genomic variation and individual phenotypes, allowing the detection of loci involved in the genetic architecture of polymorphic characters. Here, we present the corresponding methodological developments and compare the results produced by software implementing population genetics theoretical models (DFDIST: and BAYESCAN: ) and ADM (MATSAM: ) in an empirical context to detect signatures of genomic divergence associated with speciation in Lake Victoria cichlid fishes.
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Advances in modeling trait-based plant community assembly.
Laughlin, Daniel C; Laughlin, David E
2013-10-01
In this review, we examine two new trait-based models of community assembly that predict the relative abundance of species from a regional species pool. The models use fundamentally different mathematical approaches and the predictions can differ considerably. Maxent obtains the most even probability distribution subject to community-weighted mean trait constraints. Traitspace predicts low probabilities for any species whose trait distribution does not pass through the environmental filter. Neither model maximizes functional diversity because of the emphasis on environmental filtering over limiting similarity. Traitspace can test for the effects of limiting similarity by explicitly incorporating intraspecific trait variation. The range of solutions in both models could be used to define the range of natural variability of community composition in restoration projects. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K
2015-04-01
Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.
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Belley, Rénald; Snelgrove, Paul V R; Archambault, Philippe; Juniper, S Kim
2016-01-01
The upwelling of deep waters from the oxygen minimum zone in the Northeast Pacific from the continental slope to the shelf and into the Salish Sea during spring and summer offers a unique opportunity to study ecosystem functioning in the form of benthic fluxes along natural gradients. Using the ROV ROPOS we collected sediment cores from 10 sites in May and July 2011, and September 2013 to perform shipboard incubations and flux measurements. Specifically, we measured benthic fluxes of oxygen and nutrients to evaluate potential environmental drivers of benthic flux variation and ecosystem functioning along natural gradients of temperature and bottom water dissolved oxygen concentrations. The range of temperature and dissolved oxygen encountered across our study sites allowed us to apply a suite of multivariate analyses rarely used in flux studies to identify bottom water temperature as the primary environmental driver of benthic flux variation and organic matter remineralization. Redundancy analysis revealed that bottom water characteristics (temperature and dissolved oxygen), quality of organic matter (chl a:phaeo and C:N ratios) and sediment characteristics (mean grain size and porosity) explained 51.5% of benthic flux variation. Multivariate analyses identified significant spatial and temporal variation in benthic fluxes, demonstrating key differences between the Northeast Pacific and Salish Sea. Moreover, Northeast Pacific slope fluxes were generally lower than shelf fluxes. Spatial and temporal variation in benthic fluxes in the Salish Sea were driven primarily by differences in temperature and quality of organic matter on the seafloor following phytoplankton blooms. These results demonstrate the utility of multivariate approaches in differentiating among potential drivers of seafloor ecosystem functioning, and indicate that current and future predictive models of organic matter remineralization and ecosystem functioning of soft-muddy shelf and slope seafloor habitats should consider bottom water temperature variation. Bottom temperature has important implications for estimates of seasonal and spatial benthic flux variation, benthic-pelagic coupling, and impacts of predicted ocean warming at high latitudes.
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Huber, John H; Childs, Marissa L; Caldwell, Jamie M; Mordecai, Erin A
2018-05-01
Dengue, chikungunya, and Zika virus epidemics transmitted by Aedes aegypti mosquitoes have recently (re)emerged and spread throughout the Americas, Southeast Asia, the Pacific Islands, and elsewhere. Understanding how environmental conditions affect epidemic dynamics is critical for predicting and responding to the geographic and seasonal spread of disease. Specifically, we lack a mechanistic understanding of how seasonal variation in temperature affects epidemic magnitude and duration. Here, we develop a dynamic disease transmission model for dengue virus and Aedes aegypti mosquitoes that integrates mechanistic, empirically parameterized, and independently validated mosquito and virus trait thermal responses under seasonally varying temperatures. We examine the influence of seasonal temperature mean, variation, and temperature at the start of the epidemic on disease dynamics. We find that at both constant and seasonally varying temperatures, warmer temperatures at the start of epidemics promote more rapid epidemics due to faster burnout of the susceptible population. By contrast, intermediate temperatures (24-25°C) at epidemic onset produced the largest epidemics in both constant and seasonally varying temperature regimes. When seasonal temperature variation was low, 25-35°C annual average temperatures produced the largest epidemics, but this range shifted to cooler temperatures as seasonal temperature variation increased (analogous to previous results for diurnal temperature variation). Tropical and sub-tropical cities such as Rio de Janeiro, Fortaleza, and Salvador, Brazil; Cali, Cartagena, and Barranquilla, Colombia; Delhi, India; Guangzhou, China; and Manila, Philippines have mean annual temperatures and seasonal temperature ranges that produced the largest epidemics. However, more temperate cities like Shanghai, China had high epidemic suitability because large seasonal variation offset moderate annual average temperatures. By accounting for seasonal variation in temperature, the model provides a baseline for mechanistically understanding environmental suitability for virus transmission by Aedes aegypti. Overlaying the impact of human activities and socioeconomic factors onto this mechanistic temperature-dependent framework is critical for understanding likelihood and magnitude of outbreaks.
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Temporally variable environments maintain more beta-diversity in Mediterranean landscapes
NASA Astrophysics Data System (ADS)
Martin, Beatriz; Ferrer, Miguel
2015-10-01
We examined the relationships between different environmental factors and the alpha and beta-diversity of terrestrial vertebrates (birds, mammals, amphibians and reptiles) in a Mediterranean region at the landscape level. We investigated whether the mechanisms underlying alpha and beta-diversity patterns are influenced by energy availability, habitat heterogeneity and temporal variability and if the drivers of the diversity patterns differed between both components of diversity. We defined alpha-diversity as synonym of species richness whereas beta-diversity was measured as distinctiveness. We evaluated a total of 13 different predictors using generalized linear mixed model (GLMM) analysis. Habitat spatial heterogeneity increased alpha-diversity, but contrastingly, it did not significantly affect beta-diversity among sites. Disturbed landscapes may show higher habitat spatial variation and higher alpha-diversity due to the contribution of highly generalist species that are wide-distributed and do not differ in composition (beta-diversity) among different sites within the region. Contrastingly, higher beta-diversity levels were negatively related to more stable sites in terms of temporal environmental variation. This negative relationship between environmental stability and beta-diversity levels is explained in terms of species adaptation to the local environmental conditions. Our study highlights the importance of temporal environmental variability in maintaining beta-diversity patterns under highly variable environmental conditions.
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NASA Astrophysics Data System (ADS)
Hyer, E. J.; Xian, P.; Campbell, J. R.
2016-12-01
Aerosol sources, sinks, and transport processes have important variations over the diurnal cycle. Advances in geostationary satellite observation have made it possible to retrieve aerosol properties over a larger fraction of the diurnal cycle in many areas. However, the conditions for retrieval of aerosol from space also have systematic diurnal variation, which must be considered when interpreting satellite data. We used surface PM2.5 observations from the Korean National Institute for Environmental Research, together with the dense network of AERONET sun photometers deployed in Korea for the KORUS-AQ mission in spring 2016, to examine diurnal variations in aerosol conditions and quantify the effect of systematic diurnal processes on daily integrated aerosol quantities of forcing and PM2.5 24-hour exposure. Time-resolved observations of aerosols from in situ data were compared to polar and geostationary satellite observations to evaluate these questions: 1) How well is diurnal variation observed in situ captured by satellite products? 2) Do the satellite products show evidence of systematic biases related to diurnally varying observing conditions? 3) What is the implication of diurnal variation for aerosol forcing estimates based on observations near solar noon? The diurnal variation diagnosed from observations was also compared to the output of the Navy Aerosol Analysis and Prediction System (NAAPS), to examine the ability of this model to capture aerosol diurnal variation. Finally, we discuss the implications of the observed diurnal variation for assimilation of aerosol observations into forecast models.
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Identifying Factors that Influence Expression of Eutrophication in a Central California Estuary
Coastal eutrophication models have proposed that various environmental conditions can serve as filters mediating the effects of nutrient loading on coastal ecosystems. Variation in such filters due to natural or anthropogenic causes can potentially lead to varied responses in ove...
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Analysis of ecological quality of the environment and influencing factors in China during 2005-2010.
Wang, Shi-Xin; Yao, Yao; Zhou, Yi
2014-01-30
Since the twentieth century, China has been facing various kinds of environmental problems. It is necessary to evaluate and analyze the ecological status of the environment over China, which is of great importance for environmental protection measures. In this article, an Eco-environmental Quality Index (EQI) model is established using national remote sensing land-use data, NDVI data from MODIS and other statistical data. The model is used to evaluate the ecological status over China during 2005, 2008 and 2010, and spatial and temporal variations in EQI are analyzed during the period 2005-2010. We also discuss important factors affecting ecological quality, with special emphasis on meteorological conditions (including rainfall and sunshine duration) and anthropogenic factors (including normalized population and gross domestic product densities). The results show that, EQIs in northwestern China are generally lower than those in the southeast of the country, presenting a ladder-like distribution. There is significant correlation between EQI, rainfall and sunshine duration. Population density and GDP also have some relation to EQI. On the whole, the environmental quality results showed little variation during 2005-2010, with national average EQIs of 54.86, 55.07 and 54.43 in 2005, 2008 and 2010, respectively. During 2005-2010, differences in EQI were observed at the local level, but those at the provincial level were small.
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Cruz-Motta, Juan José; Miloslavich, Patricia; Palomo, Gabriela; Iken, Katrin; Konar, Brenda; Pohle, Gerhard; Trott, Tom; Benedetti-Cecchi, Lisandro; Herrera, César; Hernández, Alejandra; Sardi, Adriana; Bueno, Andrea; Castillo, Julio; Klein, Eduardo; Guerra-Castro, Edlin; Gobin, Judith; Gómez, Diana Isabel; Riosmena-Rodríguez, Rafael; Mead, Angela; Bigatti, Gregorio; Knowlton, Ann; Shirayama, Yoshihisa
2010-01-01
Assemblages associated with intertidal rocky shores were examined for large scale distribution patterns with specific emphasis on identifying latitudinal trends of species richness and taxonomic distinctiveness. Seventy-two sites distributed around the globe were evaluated following the standardized sampling protocol of the Census of Marine Life NaGISA project (www.nagisa.coml.org). There were no clear patterns of standardized estimators of species richness along latitudinal gradients or among Large Marine Ecosystems (LMEs); however, a strong latitudinal gradient in taxonomic composition (i.e., proportion of different taxonomic groups in a given sample) was observed. Environmental variables related to natural influences were strongly related to the distribution patterns of the assemblages on the LME scale, particularly photoperiod, sea surface temperature (SST) and rainfall. In contrast, no environmental variables directly associated with human influences (with the exception of the inorganic pollution index) were related to assemblage patterns among LMEs. Correlations of the natural assemblages with either latitudinal gradients or environmental variables were equally strong suggesting that neither neutral models nor models based solely on environmental variables sufficiently explain spatial variation of these assemblages at a global scale. Despite the data shortcomings in this study (e.g., unbalanced sample distribution), we show the importance of generating biological global databases for the use in large-scale diversity comparisons of rocky intertidal assemblages to stimulate continued sampling and analyses. PMID:21179546
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Bi-Annual Report 2010-2011: Shaping pulse flows to meet environmental and energy objectives
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jager, Yetta
2010-10-01
This report describes a bioenergetic model developed to allocate seasonal pulse flows to benefit salmon growth. The model links flow with floodplain inundation and production of invertebrate prey eaten by juvenile Chinook salmon. A unique quantile modeling approach is used to describe temporal variation among juvenile salmon spawned at different times. Preliminary model outputs are presented and future plans to optimize flows both to maximize salmon growth and hydropower production are outlined.
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Luo, Ya-Huang; Liu, Jie; Tan, Shao-Lin; Cadotte, Marc William; Wang, Yue-Hua; Xu, Kun; Li, De-Zhu; Gao, Lian-Ming
2016-01-01
Understanding how communities respond to environmental variation is a central goal in ecology. Plant communities respond to environmental gradients via intraspecific and/or interspecific variation in plant functional traits. However, the relative contribution of these two responses to environmental factors remains poorly tested. We measured six functional traits (height, leaf thickness, specific leaf area (SLA), leaf carbon concentration (LCC), leaf nitrogen concentration (LNC) and leaf phosphorus concentration (LPC)) for 55 tree species occurring at five elevations across a 1200 m elevational gradient of subalpine forests in Yulong Mountain, Southwest China. We examined the relative contribution of interspecific and intraspecific traits variability based on community weighted mean trait values and functional diversity, and tested how different components of trait variation respond to different environmental axes (climate and soil variables). Species turnover explained the largest amount of variation in leaf morphological traits (leaf thickness and SLA) across the elevational gradient. However, intraspecific variability explained a large amount of variation (49.3%-76.3%) in three other traits (height, LNC and LPC) despite high levels of species turnover. The detection of limiting similarity in community assembly was improved when accounting for both intraspecific and interspecific variability. Different components of trait variation respond to different environmental axes, especially soil water content and climatic variables. Our results indicate that intraspecific variation is critical for understanding community assembly and evaluating community response to environmental change.
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Luo, Ya-Huang; Liu, Jie; Tan, Shao-Lin; Cadotte, Marc William; Wang, Yue-Hua; Xu, Kun; Li, De-Zhu; Gao, Lian-Ming
2016-01-01
Understanding how communities respond to environmental variation is a central goal in ecology. Plant communities respond to environmental gradients via intraspecific and/or interspecific variation in plant functional traits. However, the relative contribution of these two responses to environmental factors remains poorly tested. We measured six functional traits (height, leaf thickness, specific leaf area (SLA), leaf carbon concentration (LCC), leaf nitrogen concentration (LNC) and leaf phosphorus concentration (LPC)) for 55 tree species occurring at five elevations across a 1200 m elevational gradient of subalpine forests in Yulong Mountain, Southwest China. We examined the relative contribution of interspecific and intraspecific traits variability based on community weighted mean trait values and functional diversity, and tested how different components of trait variation respond to different environmental axes (climate and soil variables). Species turnover explained the largest amount of variation in leaf morphological traits (leaf thickness and SLA) across the elevational gradient. However, intraspecific variability explained a large amount of variation (49.3%–76.3%) in three other traits (height, LNC and LPC) despite high levels of species turnover. The detection of limiting similarity in community assembly was improved when accounting for both intraspecific and interspecific variability. Different components of trait variation respond to different environmental axes, especially soil water content and climatic variables. Our results indicate that intraspecific variation is critical for understanding community assembly and evaluating community response to environmental change. PMID:27191402
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Adu, Michael O; Chatot, Antoine; Wiesel, Lea; Bennett, Malcolm J; Broadley, Martin R; White, Philip J; Dupuy, Lionel X
2014-05-01
The potential exists to breed for root system architectures that optimize resource acquisition. However, this requires the ability to screen root system development quantitatively, with high resolution, in as natural an environment as possible, with high throughput. This paper describes the construction of a low-cost, high-resolution root phenotyping platform, requiring no sophisticated equipment and adaptable to most laboratory and glasshouse environments, and its application to quantify environmental and temporal variation in root traits between genotypes of Brassica rapa L. Plants were supplied with a complete nutrient solution through the wick of a germination paper. Images of root systems were acquired without manual intervention, over extended periods, using multiple scanners controlled by customized software. Mixed-effects models were used to describe the sources of variation in root traits contributing to root system architecture estimated from digital images. It was calculated that between one and 43 replicates would be required to detect a significant difference (95% CI 50% difference between traits). Broad-sense heritability was highest for shoot biomass traits (>0.60), intermediate (0.25-0.60) for the length and diameter of primary roots and lateral root branching density on the primary root, and lower (<0.25) for other root traits. Models demonstrate that root traits show temporal variations of various types. The phenotyping platform described here can be used to quantify environmental and temporal variation in traits contributing to root system architecture in B. rapa and can be extended to screen the large populations required for breeding for efficient resource acquisition.
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Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa.
Redding, David W; Tiedt, Sonia; Lo Iacono, Gianni; Bett, Bernard; Jones, Kate E
2017-07-19
Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.
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Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa
2017-01-01
Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources. This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’. PMID:28584173
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Zas, R; Sampedro, L
2015-01-01
Quantitative seed provisioning is an important life-history trait with strong effects on offspring phenotype and fitness. As for any other trait, heritability estimates are vital for understanding its evolutionary dynamics. However, being a trait in between two generations, estimating additive genetic variation of seed provisioning requires complex quantitative genetic approaches for distinguishing between true genetic and environmental maternal effects. Here, using Maritime pine as a long-lived plant model, we quantified additive genetic variation of cone and seed weight (SW) mean and SW within-individual variation. We used a powerful approach combining both half-sib analysis and parent–offspring regression using several common garden tests established in contrasting environments to separate G, E and G × E effects. Both cone weight and SW mean showed significant genetic variation but were also influenced by the maternal environment. Most of the large variation in SW mean was attributable to additive genetic effects (h2=0.55–0.74). SW showed no apparent G × E interaction, particularly when accounting for cone weight covariation, suggesting that the maternal genotypes actively control the SW mean irrespective of the amount of resources allocated to cones. Within-individual variation in SW was low (12%) relative to between-individual variation (88%), and showed no genetic variation but was largely affected by the maternal environment, with greater variation in the less favourable sites for pine growth. In summary, results were very consistent between the parental and the offspring common garden tests, and clearly indicated heritable genetic variation for SW mean but not for within-individual variation in SW. PMID:25160045
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NASA Astrophysics Data System (ADS)
Pecháček, Pavel; Stella, David; Keil, Petr; Kleisner, Karel
2014-12-01
The males of the Brimstone butterfly ( Gonepteryx rhamni) have ultraviolet pattern on the dorsal surfaces of their wings. Using geometric morphometrics, we have analysed correlations between environmental variables (climate, productivity) and shape variability of the ultraviolet pattern and the forewing in 110 male specimens of G. rhamni collected in the Palaearctic zone. To start with, we subjected the environmental variables to principal component analysis (PCA). The first PCA axis (precipitation, temperature, latitude) significantly correlated with shape variation of the ultraviolet patterns across the Palaearctic. Additionally, we have performed two-block partial least squares (PLS) analysis to assess co-variation between intraspecific shape variation and the variation of 11 environmental variables. The first PLS axis explained 93 % of variability and represented the effect of precipitation, temperature and latitude. Along this axis, we observed a systematic increase in the relative area of ultraviolet colouration with increasing temperature and precipitation and decreasing latitude. We conclude that the shape variation of ultraviolet patterns on the forewings of male Brimstones is correlated with large-scale environmental factors.
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Pelosse, Perrine; Kribs-Zaleta, Christopher M; Ginoux, Marine; Rabinovich, Jorge E; Gourbière, Sébastien; Menu, Frédéric
2013-01-01
Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas' disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control.
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Pelosse, Perrine; Kribs-Zaleta, Christopher M.; Ginoux, Marine; Rabinovich, Jorge E.; Gourbière, Sébastien; Menu, Frédéric
2013-01-01
Insects are known to display strategies that spread the risk of encountering unfavorable conditions, thereby decreasing the extinction probability of genetic lineages in unpredictable environments. To what extent these strategies influence the epidemiology and evolution of vector-borne diseases in stochastic environments is largely unknown. In triatomines, the vectors of the parasite Trypanosoma cruzi, the etiological agent of Chagas’ disease, juvenile development time varies between individuals and such variation most likely decreases the extinction risk of vector populations in stochastic environments. We developed a simplified multi-stage vector-borne SI epidemiological model to investigate how vector risk-spreading strategies and environmental stochasticity influence the prevalence and evolution of a parasite. This model is based on available knowledge on triatomine biodemography, but its conceptual outcomes apply, to a certain extent, to other vector-borne diseases. Model comparisons between deterministic and stochastic settings led to the conclusion that environmental stochasticity, vector risk-spreading strategies (in particular an increase in the length and variability of development time) and their interaction have drastic consequences on vector population dynamics, disease prevalence, and the relative short-term evolution of parasite virulence. Our work shows that stochastic environments and associated risk-spreading strategies can increase the prevalence of vector-borne diseases and favor the invasion of more virulent parasite strains on relatively short evolutionary timescales. This study raises new questions and challenges in a context of increasingly unpredictable environmental variations as a result of global climate change and human interventions such as habitat destruction or vector control. PMID:23951018
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Moreno-Pino, Mario; De la Iglesia, Rodrigo; Valdivia, Nelson; Henríquez-Castilo, Carlos; Galán, Alexander; Díez, Beatriz; Trefault, Nicole
2016-07-01
Spatial environmental heterogeneity influences diversity of organisms at different scales. Environmental filtering suggests that local environmental conditions provide habitat-specific scenarios for niche requirements, ultimately determining the composition of local communities. In this work, we analyze the spatial variation of microbial communities across environmental gradients of sea surface temperature, salinity and photosynthetically active radiation and spatial distance in Fildes Bay, King George Island, Antarctica. We hypothesize that environmental filters are the main control of the spatial variation of these communities. Thus, strong relationships between community composition and environmental variation and weak relationships between community composition and spatial distance are expected. Combining physical characterization of the water column, cell counts by flow cytometry, small ribosomal subunit genes fingerprinting and next generation sequencing, we contrast the abundance and composition of photosynthetic eukaryotes and heterotrophic bacterial local communities at a submesoscale. Our results indicate that the strength of the environmental controls differed markedly between eukaryotes and bacterial communities. Whereas eukaryotic photosynthetic assemblages responded weakly to environmental variability, bacteria respond promptly to fine-scale environmental changes in this polar marine system. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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NASA Astrophysics Data System (ADS)
Penenko, Vladimir; Tsvetova, Elena; Penenko, Aleksey
2014-05-01
A modeling technology based on coupled models of atmospheric dynamics and chemistry are presented [1-3]. It is the result of application of variational methods in combination with the methods of decomposition and splitting. The idea of Euler's integrating factors combined with technique of adjoint problems is also used. In online technologies, a significant part of algorithmic and computational work consist in solving the problems like convection-diffusion-reaction and in organizing data assimilation techniques based on them. For equations of convection-diffusion, the methodology gives us the unconditionally stable and monotone discrete-analytical schemes in the frames of methods of decomposition and splitting. These schemes are exact for locally one-dimensional problems respect to the spatial variables. For stiff systems of equations describing transformation of gas and aerosol substances, the monotone and stable schemes are also obtained. They are implemented by non- iterative algorithms. By construction, all schemes for different components of state functions are structurally uniform. They are coordinated among themselves in the sense of forward and inverse modeling. Variational principles are constructed taking into account the fact that the behavior of the different dynamic and chemical components of the state function is characterized by high variability and uncertainty. Information on the parameters of models, sources and emission impacts is also not determined precisely. Therefore, to obtain the consistent solutions, we construct methods of the sensitivity theory taking into account the influence of uncertainty. For this purpose, new methods of data assimilation of hydrodynamic fields and gas-aerosol substances measured by different observing systems are proposed. Optimization criteria for data assimilation problems are defined so that they include a set of functionals evaluating the total measure of uncertainties. The latter are explicitly introduced into the equations of the model of processes as desired deterministic control functions. This method of data assimilation with control functions is implemented by direct algorithms. The modeling technology presented here focuses on various scientific and applied problems of environmental prediction and design, including risk assessment in relation to existing and potential sources of natural and anthropogenic influences. The work is partially supported by the Programs No 4 of Presidium RAS and No 3 of Mathematical Department of RAS; by RFBR projects NN 11-01-00187 and 14-01-31482; by Integrating projects of SD RAS No 8 and 35. Our studies are in the line with the goals of COST Action ES1004. References 1. V. Penenko, A.Baklanov, E. Tsvetova and A. Mahura. Direct and Inverse Problems in a Variational Concept of Environmental Modeling, Pure and Applied Geoph. 2012.V.169:447-465. 2. A.V. Penenko, Discrete-analytic schemes for solving an inverse coefficient heat conduction problem in a layered medium with gradient methods, Numerical Analysis and Applications, 2012. V. 5:326-341. 3. V. Penenko, E. Tsvetova. Variational methods for constructing the monotone approximations for atmospheric chemistry models, Numerical analysis and applications, 2013. V. 6: 210-220.
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Cosmic Ray Modulation and Radiation Dose of Aircrews During Possible Grand Minimum
NASA Astrophysics Data System (ADS)
Miyake, S.; Kataoka, R.; Sato, T.; Imada, S.; Miyahara, H.; Shiota, D.; Matsumoto, T.; Ueno, H.
2017-12-01
The Sun is exhibiting low solar activity levels since the descending phase of the last solar cycle, and it is likely to be continued as well as in the case of the past grand solar minima. The cosmic-ray modulation, which is the variation of the galactic cosmic ray (GCR) spectrum caused by the heliospheric environmental change, is basically anti-correlated with the solar activity. In the recent weak solar cycle, we thus expect that the flux of GCRs is getting higher than that in the previous solar cycles, leading to the increase in the radiation exposure in the space and atmosphere. In order to quantitatively evaluate the possible solar modulation of GCRs and resultant radiation exposure at flight altitude, we have developed the time-dependent and three-dimensional model of the cosmic-ray modulation. Our model can give the flux of GCRs anywhere in the heliosphere by assuming the variation of the solar wind speed, the strength of the heliospheric magnetic field (HMF), and its tilt angle. We solve the gradient-curvature drift motion of GCRs in the HMF, and therefore reproduce the 22-year variation of the cosmic-ray modulation. We also calculate the neutron monitor counting rate and the radiation dose of aircrews at flight altitude, by the air-shower simulation performed by PHITS (Particle and Heavy Ion Transport code System). In our previous study [1], we calculated the radiation dose at a flight altitude during the coming solar cycle by assuming the variation of the solar wind speed and the strength of the HMF expressed by sinusoidal curve, and obtained that an annual radiation dose of aircrews in 5 years around the next solar minimum will be up to 19% higher than that at the last cycle. In this study, we predict the new model of the heliospheric environmental change on the basis of a prediction model for the sunspot number. The quantitative predictions of the cosmic-ray modulation and the radiation dose at a flight altitude during possible Grand Minimum considering the new model for the heliospheric environmental change will be presented at the meeting. [1] S. Miyake, R. Kataoka, and T. Sato, Space Weather, 15, 589-605, 2017.
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Astorga, Anna; Death, Russell; Death, Fiona; Paavola, Riku; Chakraborty, Manas; Muotka, Timo
2014-07-01
To define whether the beta diversity of stream invertebrate communities in New Zealand exhibits geographical variation unexplained by variation in gamma diversity and, if so, what mechanisms (productivity, habitat heterogeneity, dispersal limitation, disturbance) best explain the observed broad-scale beta diversity patterns. We sampled 120 streams across eight regions (stream catchments), spanning a north-south gradient of 12° of latitude, and calculated beta diversity (with both species richness and abundance data) for each region. We explored through a null model if beta diversity deviates from the expectation of stochastic assembly processes and whether the magnitude of the deviation varies geographically. We then performed multimodel inference analysis on the key environmental drivers of beta diversity, using Akaike's information criterion and model and predictor weights to select the best model(s) explaining beta diversity. Beta diversity was, unexpectedly, highest in the South Island. The null model analysis revealed that beta diversity was greater than expected by chance in all eight regions, but the magnitude of beta deviation was higher in the South Island, suggesting differences in environmental filtering and/or dispersal limitation between North and South Island. Habitat heterogeneity was the predominant driver of beta diversity of stream macroinvertebrates, with productivity having a secondary, and negative, contribution. This is one of the first studies accounting for stochastic effects while examining the ecological drivers of beta diversity. Our results suggest that local environmental heterogeneity may be the strongest determinant of beta diversity of stream invertebrates, more so than regional- or landscape-scale variables.
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Romano, Valéria; MacIntosh, Andrew J. J.
2016-01-01
Different hypotheses explain variation in the occurrence of self-directed behaviour such as scratching and self-grooming: a parasite hypothesis linked with ectoparasite load, an environmental hypothesis linked with seasonal conditions and a social hypothesis linked with social factors. These hypotheses are not mutually exclusive but are often considered separately. Here, we revisited these hypotheses together in female Japanese macaques (Macaca fuscata fuscata) of Kōjima islet, Japan. We input occurrences of scratching and self-grooming during focal observations in models combining parasitological (lice load), social (dominance rank, social grooming, aggression received and proximity), and environmental (rainfall, temperature and season) variables. Using an information-theory approach, we simultaneously compared the explanatory value of models against each other using variation in Akaike's information criterion and Akaike's weights. We found that evidence for models with lice load, with or without environmental–social parameters, was stronger than that for other models. In these models, scratching was positively associated with lice load and social grooming whereas self-grooming was negatively associated with lice load and positively associated with social grooming, dominance rank and number of female neighbours. This study indicates that the study animals scratch primarily because of an immune/stimulus itch, possibly triggered by ectoparasite bites/movements. It also confirms that self-grooming could act as a displacement activity in the case of social uncertainty. We advocate that biological hypotheses be more broadly considered even when investigating social processes, as one does not exclude the other. PMID:28018646
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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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Helble, Tyler A; D'Spain, Gerald L; Campbell, Greg S; Hildebrand, John A
2013-11-01
This paper demonstrates the importance of accounting for environmental effects on passive underwater acoustic monitoring results. The situation considered is the reduction in shipping off the California coast between 2008-2010 due to the recession and environmental legislation. The resulting variations in ocean noise change the probability of detecting marine mammal vocalizations. An acoustic model was used to calculate the time-varying probability of detecting humpback whale vocalizations under best-guess environmental conditions and varying noise. The uncorrected call counts suggest a diel pattern and an increase in calling over a two-year period; the corrected call counts show minimal evidence of these features.
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Invited review: A position on the Global Livestock Environmental Assessment Model (GLEAM).
MacLeod, M J; Vellinga, T; Opio, C; Falcucci, A; Tempio, G; Henderson, B; Makkar, H; Mottet, A; Robinson, T; Steinfeld, H; Gerber, P J
2018-02-01
The livestock sector is one of the fastest growing subsectors of the agricultural economy and, while it makes a major contribution to global food supply and economic development, it also consumes significant amounts of natural resources and alters the environment. In order to improve our understanding of the global environmental impact of livestock supply chains, the Food and Agriculture Organization of the United Nations has developed the Global Livestock Environmental Assessment Model (GLEAM). The purpose of this paper is to provide a review of GLEAM. Specifically, it explains the model architecture, methods and functionality, that is the types of analysis that the model can perform. The model focuses primarily on the quantification of greenhouse gases emissions arising from the production of the 11 main livestock commodities. The model inputs and outputs are managed and produced as raster data sets, with spatial resolution of 0.05 decimal degrees. The Global Livestock Environmental Assessment Model v1.0 consists of five distinct modules: (a) the Herd Module; (b) the Manure Module; (c) the Feed Module; (d) the System Module; (e) the Allocation Module. In terms of the modelling approach, GLEAM has several advantages. For example spatial information on livestock distributions and crops yields enables rations to be derived that reflect the local availability of feed resources in developing countries. The Global Livestock Environmental Assessment Model also contains a herd model that enables livestock statistics to be disaggregated and variation in livestock performance and management to be captured. Priorities for future development of GLEAM include: improving data quality and the methods used to perform emissions calculations; extending the scope of the model to include selected additional environmental impacts and to enable predictive modelling; and improving the utility of GLEAM output.
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Modeling Stream Temperatures with the Inclusion of Irradiance Change due to Forest Biomass Shifts.
Changes in stream temperature are directly and indirectly due to solar energy loading levels. Solar radiation is a significant environmental driver that impacts the quality and resilience of terrestrial and aquatic habitats, yet its spatiotemporal variations are complicated to mo...
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Farias, Ariel A; Jaksic, Fabian M
2007-03-01
1. Within mainstream ecological literature, functional structure has been viewed as resulting from the interplay of species interactions, resource levels and environmental variability. Classical models state that interspecific competition generates species segregation and guild formation in stable saturated environments, whereas opportunism causes species aggregation on abundant resources in variable unsaturated situations. 2. Nevertheless, intrinsic functional constraints may result in species-specific differences in resource-use capabilities. This could force some degree of functional structure without assuming other putative causes. However, the influence of such constraints has rarely been tested, and their relative contribution to observed patterns has not been quantified. 3. We used a multiple null-model approach to quantify the magnitude and direction (non-random aggregation or divergence) of the functional structure of a vertebrate predator assemblage exposed to variable prey abundance over an 18-year period. Observed trends were contrasted with predictions from null-models designed in an orthogonal fashion to account independently for the effects of functional constraints and opportunism. Subsequently, the unexplained variation was regressed against environmental variables to search for evidence of interspecific competition. 4. Overall, null-models accounting for functional constraints showed the best fit to the observed data, and suggested an effect of this factor in modulating predator opportunistic responses. However, regression models on residual variation indicated that such an effect was dependent on both total and relative abundance of principal (small mammals) and alternative (arthropods, birds, reptiles) prey categories. 5. In addition, no clear evidence for interspecific competition was found, but differential delays in predator functional responses could explain some of the unaccounted variation. Thus, we call for caution when interpreting empirical data in the context of classical models assuming synchronous responses of consumers to resource levels.
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NASA Astrophysics Data System (ADS)
Johnson, D. J.; Needham, J.; Xu, C.; Davies, S. J.; Bunyavejchewin, S.; Giardina, C. P.; Condit, R.; Cordell, S.; Litton, C. M.; Hubbell, S.; Kassim, A. R. B.; Shawn, L. K. Y.; Nasardin, M. B.; Ong, P.; Ostertag, R.; Sack, L.; Tan, S. K. S.; Yap, S.; McDowell, N. G.; McMahon, S.
2016-12-01
Terrestrial carbon cycling is a function of the growth and survival of trees. Current model representations of tree growth and survival at a global scale rely on coarse plant functional traits that are parameterized very generally. In view of the large biodiversity in the tropical forests, it is important that we account for the functional diversity in order to better predict tropical forest responses to future climate changes. Several next generation Earth System Models are moving towards a size-structured, trait-based approach to modelling vegetation globally, but the challenge of which and how many traits are necessary to capture forest complexity remains. Additionally, the challenge of collecting sufficient trait data to describe the vast species richness of tropical forests is enormous. We propose a more fundamental approach to these problems by characterizing forests by their patterns of survival. We expect our approach to distill real-world tree survival into a reasonable number of functional types. Using 10 large-area tropical forest plots that span geographic, edaphic and climatic gradients, we model tree survival as a function of tree size for hundreds of species. We found surprisingly few categories of size-survival functions emerge. This indicates some fundamental strategies at play across diverse forests to constrain the range of possible size-survival functions. Initial cluster analysis indicates that four to eight functional forms are necessary to describe variation in size-survival relations. Temporal variation in size-survival functions can be related to local environmental variation, allowing us to parameterize how demographically similar groups of species respond to perturbations in the ecosystem. We believe this methodology will yield a synthetic approach to classifying forest systems that will greatly reduce uncertainty and complexity in global vegetation models.
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Thomson, Madeleine C; Obsomer, Valérie; Kamgno, Joseph; Gardon, Jacques; Wanji, Samuel; Takougang, Innocent; Enyong, Peter; Remme, Jan H; Molyneux, David H; Boussinesq, Michel
2004-01-01
Background Loa loa has recently emerged as a filarial worm of significant public health importance as a consequence of its impact on the African Programme for Onchocerciasis Control (APOC). Severe, sometimes fatal, encephalopathic reactions to ivermectin (the drug of choice for onchocerciasis control) have occurred in some individuals with high Loa loa microfilarial counts. Since high density of Loa loa microfilariae is known to be associated with high prevalence rates, a distribution map of the latter may determine areas where severe reactions might occur. The aim of the study was to identify variables which were significantly associated with the presence of a Loa microfilaraemia in the subjects examined, and to develop a spatial model predicting the prevalence of the Loa microfilaraemia. Methods Epidemiological data were collected from 14,225 individuals living in 94 villages in Cameroon, and analysed in conjunction with environmental data. A series of logistic regression models (multivariate analysis) was developed to describe variation in the prevalence of Loa loa microfilaraemia using individual level co-variates (age, sex, μl of blood taken for examination) and village level environmental co-variates (including altitude and satellite-derived vegetation indices). Results A spatial model of Loa loa prevalence was created within a geographical information system. The model was then validated using an independent data set on Loa loa distribution. When considering both data sets as a whole, and a prevalence threshold of 20%, the sensitivity and the specificity of the model were 81.7 and 69.4%, respectively. Conclusions The model developed has proven very useful in defining the areas at risk of post-ivermectin Loa-related severe adverse events. It is now routinely used by APOC when projects of community-directed treatment with ivermectin are examined. PMID:15298709
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Thomson, Madeleine C; Obsomer, Valérie; Kamgno, Joseph; Gardon, Jacques; Wanji, Samuel; Takougang, Innocent; Enyong, Peter; Remme, Jan H; Molyneux, David H; Boussinesq, Michel
2004-08-06
BACKGROUND: Loa loa has recently emerged as a filarial worm of significant public health importance as a consequence of its impact on the African Programme for Onchocerciasis Control (APOC). Severe, sometimes fatal, encephalopathic reactions to ivermectin (the drug of choice for onchocerciasis control) have occurred in some individuals with high Loa loa microfilarial counts. Since high density of Loa loa microfilariae is known to be associated with high prevalence rates, a distribution map of the latter may determine areas where severe reactions might occur. The aim of the study was to identify variables which were significantly associated with the presence of a Loa microfilaraemia in the subjects examined, and to develop a spatial model predicting the prevalence of the Loa microfilaraemia. METHODS: Epidemiological data were collected from 14,225 individuals living in 94 villages in Cameroon, and analysed in conjunction with environmental data. A series of logistic regression models (multivariate analysis) was developed to describe variation in the prevalence of Loa loa microfilaraemia using individual level co-variates (age, sex, microl of blood taken for examination) and village level environmental co-variates (including altitude and satellite-derived vegetation indices). RESULTS: A spatial model of Loa loa prevalence was created within a geographical information system. The model was then validated using an independent data set on Loa loa distribution. When considering both data sets as a whole, and a prevalence threshold of 20%, the sensitivity and the specificity of the model were 81.7 and 69.4%, respectively. CONCLUSIONS: The model developed has proven very useful in defining the areas at risk of post-ivermectin Loa-related severe adverse events. It is now routinely used by APOC when projects of community-directed treatment with ivermectin are examined.
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The Evolution of Phenotypic Switching in Subdivided Populations
Carja, Oana; Liberman, Uri; Feldman, Marcus W.
2014-01-01
Stochastic switching is an example of phenotypic bet hedging, where offspring can express a phenotype different from that of their parents. Phenotypic switching is well documented in viruses, yeast, and bacteria and has been extensively studied when the selection pressures vary through time. However, there has been little work on the evolution of phenotypic switching under both spatially and temporally fluctuating selection pressures. Here we use a population genetic model to explore the interaction of temporal and spatial variation in determining the evolutionary dynamics of phenotypic switching. We find that the stable switching rate is mainly determined by the rate of environmental change and the migration rate. This stable rate is also a decreasing function of the recombination rate, although this is a weaker effect than those of either the period of environmental change or the migration rate. This study highlights the interplay of spatial and temporal environmental variability, offering new insights into how migration can influence the evolution of phenotypic switching rates, mutation rates, or other sources of phenotypic variation. PMID:24496012
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ERIC Educational Resources Information Center
Mustanski, Brian S.; Viken, Richard J.; Kaprio, Jaakko; Pulkkinen, Lea; Rose, Richard J.
2004-01-01
To study sources of individual differences in pubertal development, the authors fit a sex-limitation common factor model to data reported, at ages 11 and 14 years, by 1,891 twin pairs on items that comprise the Pubertal Development Scale (PDS; A. C. Petersen, L. Crockett, M. Richards, & A. Boxer, 1988). The model divides variation into a general…
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Little, Keriann; Olsson, Craig A; Youssef, George J; Whittle, Sarah; Simmons, Julian G; Yücel, Murat; Sheeber, Lisa B; Foley, Debra L; Allen, Nicholas B
2015-11-01
A single imaging gene-environment (IGxE) framework that is able to simultaneously model genetic, neurobiological, and environmental influences on psychopathology outcomes is needed to improve understanding of how complex interrelationships between allelic variation, differences in neuroanatomy or neuroactivity, and environmental experience affect risk for psychiatric disorder. In a longitudinal study of adolescent development we demonstrate the utility of such an IGxE framework by testing whether variation in parental behavior at age 12 altered the strength of an imaging genetics pathway, involving an indirect association between allelic variation in the serotonin transporter gene to variation in hippocampal volume and consequent onset of major depressive disorder by age 18. Results were consistent with the presence of an indirect effect of the serotonin transporter S-allele on depression onset via smaller left and right hippocampal volumes that was significant only in family environments involving either higher levels of parental aggression or lower levels of positive parenting. The previously reported finding of S-allele carriers' increased risk of depression in adverse environments may, therefore, be partly because of the effects of these environments on a neurobiological pathway from the serotonin transporter gene to depression onset that proceeds through variation in hippocampal volume. (c) 2015 APA, all rights reserved).
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A simple estimate of ecosystem respiration across biomes based on MODIS products
NASA Astrophysics Data System (ADS)
Jaegermeyr, J.; Hostert, P.; Lucht, W.
2010-12-01
Beside carbon sequestration by terrestrial photosynthesis, in particular the subsequent carbon release by ecosystem respiration (Reco) is a crucial flux for estimating carbon budgets. Heterotrophic soil decomposition rates (Rh) and autotrophic respiration rates (Ra), which add up to Reco, are highly sensitive to environmental conditions and in some cases they determine net ecosystem productivity. Prior respiration modeling approaches revealed that a precise process-based and bottom-up modeling is important for realistic estimates. On a short timescale, as in the case of satellite environmental monitoring, simplified empirical models are not necessarily less accurate, though. For most major biomes, ecosystem carbon efflux is predominantly driven by air temperature. It can further be limited by water stress, plant activity and substrate quality. Developing simple, empirical and wall-to-wall respiration models from continuous Moderate Resolution Imaging Spectroradiometer (MODIS) land products on a continental scale can enhance our understanding of spatially explicit respiration patterns. We therefore accept model uncertainties by simplifying decay and respiratory processes in that we account for a single static carbon pool and do not include any feedback mechanisms. Preliminary results suggest that the 8-day MODIS 1km land surface temperature product (LST) and the vegetation-water index (NDWI) derived from the 8-day MODIS 500m surface reflectance product are sufficient to largely explain the variability of Reco. Spatial flux variations can be attributed to plant activity variation. We therefore introduce a site-specific, maximum leaf area index (LAI) from the MODIS 1km LAI product as a proxy. A biome-specific model parameterization and validation is performed, based on 8-day composite FLUXNET tower data representing major global biomes. We found that the frequently used temperature model by Loyd and Taylor (1994) does not show superior performance on 8-day ecosystem respiration data. The model by Del Grosso et al. (2005) is more flexible to account for lower Q10 values at high temperatures and thus it is used to describe the temperature dependency here. Although we cannot explain flux variations arising from overall carbon pool variations, results suggest that our approach may contribute to simplified Reco estimates.
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Global scale environmental control of plant photosynthetic capacity
Ali, Ashehad; Xu, Chonggang; Rogers, Alistair; ...
2015-12-01
Photosynthetic capacity, determined by light harvesting and carboxylation reactions, is a key plant trait that determines the rate of photosynthesis; however, in Earth System Models (ESMs) at a reference temperature, it is either a fixed value for a given plant functional type or derived from a linear function of leaf nitrogen content. In this study, we conducted a comprehensive analysis that considered correlations of environmental factors with photosynthetic capacity as determined by maximum carboxylation (V c,m) rate scaled to 25°C (i.e., V c,25; μmol CO 2·m –2·s –1) and maximum electron transport rate (Jmax) scaled to 25°C (i.e., J 25;more » μmol electron·m –2·s –1) at the global scale. Our results showed that the percentage of variation in observed Vc,25 and J25 explained jointly by the environmental factors (i.e., day length, radiation, temperature, and humidity) were 2–2.5 times and 6–9 times of that explained by area-based leaf nitrogen content, respectively. Environmental factors influenced photosynthetic capacity mainly through photosynthetic nitrogen use efficiency, rather than through leaf nitrogen content. The combination of leaf nitrogen content and environmental factors was able to explain ~56% and ~66% of the variation in V c,25 and J 25 at the global scale, respectively. As a result, our analyses suggest that model projections of plant photosynthetic capacity and hence land–atmosphere exchange under changing climatic conditions could be substantially improved if environmental factors are incorporated into algorithms used to parameterize photosynthetic capacity in ESMs.« less
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NASA Astrophysics Data System (ADS)
Yokozawa, M.
2017-12-01
Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.
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2012-01-01
Objective Odor exposure is an environmental stressor that is responsible of many citizens complains about air pollution in non-urban areas. However, information about the exposure-response relation is scarce. One of the main challenges is to identify a measurable compound that can be related with odor annoyance responses. We investigated the association between regional and temporal variation of ammonia (NH3) concentrations in five Danish non-urban regions and environmental odor annoyance as perceived by the local residents. Methods A cross-sectional study where NH3 concentration was obtained from the national air quality monitoring program and from emission-dispersion modelling, and odor pollution perception from questionnaires. The exposure-response model was a sigmoid model. Linear regression analyses were used to estimate the model constants after equation transformations. The model was validated using leave-one-out cross validation (LOOCV) statistical method. Results About 45% of the respondents were annoyed by odor pollution at their residential areas. The perceived odor was characterized by all respondents as animal waste odor. The exposure-annoyance sigmoid model showed that the prevalence of odor annoyance was significantly associated with NH3 concentrations (measured and estimated) at the local air quality monitoring stations (p < 0.01,R2 = 0.99; and p < 0.05,R2 = 0.93; respectively). Prediction errors were below 5.1% and 20% respectively. The seasonal pattern of odor perception was associated with the seasonal variation in NH3 concentrations (p < 0.001, adjusted R2 = 0.68). Conclusion The results suggest that atmospheric NH3 levels at local air quality stations could be used as indicators of prevalence of odor annoyance in non-urban residential communities. PMID:22513250
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Yin, Xinyou
2012-01-01
To understand the physiological basis of genetic variation and resulting quantitative trait loci (QTLs) for photosynthesis in a rice (Oryza sativa L.) introgression line population, 13 lines were studied under drought and well-watered conditions, at flowering and grain filling. Simultaneous gas exchange and chlorophyll fluorescence measurements were conducted at various levels of incident irradiance and ambient CO2 to estimate parameters of a model that dissects photosynthesis into stomatal conductance (g s), mesophyll conductance (g m), electron transport capacity (J max), and Rubisco carboxylation capacity (V cmax). Significant genetic variation in these parameters was found, although drought and leaf age accounted for larger proportions of the total variation. Genetic variation in light-saturated photosynthesis and transpiration efficiency (TE) were mainly associated with variation in g s and g m. One previously mapped major QTL of photosynthesis was associated with variation in g s and g m, but also in J max and V cmax at flowering. Thus, g s and g m, which were demonstrated in the literature to be responsible for environmental variation in photosynthesis, were found also to be associated with genetic variation in photosynthesis. Furthermore, relationships between these parameters and leaf nitrogen or dry matter per unit area, which were previously found across environmental treatments, were shown to be valid for variation across genotypes. Finally, the extent to which photosynthesis rate and TE can be improved was evaluated. Virtual ideotypes were estimated to have 17.0% higher photosynthesis and 25.1% higher TE compared with the best genotype investigated. This analysis using introgression lines highlights possibilities of improving both photosynthesis and TE within the same genetic background. PMID:22888131
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
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Limited potential for adaptation to climate change in a broadly distributed marine crustacean.
Kelly, Morgan W; Sanford, Eric; Grosberg, Richard K
2012-01-22
The extent to which acclimation and genetic adaptation might buffer natural populations against climate change is largely unknown. Most models predicting biological responses to environmental change assume that species' climatic envelopes are homogeneous both in space and time. Although recent discussions have questioned this assumption, few empirical studies have characterized intraspecific patterns of genetic variation in traits directly related to environmental tolerance limits. We test the extent of such variation in the broadly distributed tidepool copepod Tigriopus californicus using laboratory rearing and selection experiments to quantify thermal tolerance and scope for adaptation in eight populations spanning more than 17° of latitude. Tigriopus californicus exhibit striking local adaptation to temperature, with less than 1 per cent of the total quantitative variance for thermal tolerance partitioned within populations. Moreover, heat-tolerant phenotypes observed in low-latitude populations cannot be achieved in high-latitude populations, either through acclimation or 10 generations of strong selection. Finally, in four populations there was no increase in thermal tolerance between generations 5 and 10 of selection, suggesting that standing variation had already been depleted. Thus, plasticity and adaptation appear to have limited capacity to buffer these isolated populations against further increases in temperature. Our results suggest that models assuming a uniform climatic envelope may greatly underestimate extinction risk in species with strong local adaptation.
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Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa
2015-03-01
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 pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Toward an Integrative Understanding of Social Behavior: New Models and New Opportunities
Blumstein, Daniel T.; Ebensperger, Luis A.; Hayes, Loren D.; Vásquez, Rodrigo A.; Ahern, Todd H.; Burger, Joseph Robert; Dolezal, Adam G.; Dosmann, Andy; González-Mariscal, Gabriela; Harris, Breanna N.; Herrera, Emilio A.; Lacey, Eileen A.; Mateo, Jill; McGraw, Lisa A.; Olazábal, Daniel; Ramenofsky, Marilyn; Rubenstein, Dustin R.; Sakhai, Samuel A.; Saltzman, Wendy; Sainz-Borgo, Cristina; Soto-Gamboa, Mauricio; Stewart, Monica L.; Wey, Tina W.; Wingfield, John C.; Young, Larry J.
2010-01-01
Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur. PMID:20661457
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Cover of coastal vegetation as an indicator of eutrophication along environmental gradients.
Wikström, Sofia A; Carstensen, Jacob; Blomqvist, Mats; Krause-Jensen, Dorte
2016-01-01
Coastal vegetation communities are important for primary production, biodiversity, coastal protection, carbon and nutrient cycling which, in combination with their sensitivity to eutrophication, render them potential indicators of environmental status for environmental policies like the EU Water and Marine Strategy Framework Directives. We evaluated one potential indicator for coastal vegetation, the cumulative cover at depths where the vegetation is light limited, by investigating its response to eutrophication along gradients in natural conditions. We used a large data set covering the Swedish coastline, spanning broad gradients in nutrient level, water clarity, seabed substrate, physical exposure and climate in addition to a salinity gradient from 0.5 to 30.5. Macroalgal cover increased significantly along gradients of declining nutrient concentration and increasing water clarity when we had accounted for diver effects, spatio-temporal sampling variability, salinity gradients, wave exposure and latitude. The developed empirical model explained 79% of the variation in algal cover across 130 areas. Based on this, we identified macroalgal cover as a promising indicator across the Baltic Sea, Kattegat and Skagerrak. A parallel analysis of soft-substrate macrophytes similarly identified significant increases in cover with decreasing concentrations of total nitrogen and increasing salinity, but the resulting empirical model explained only 52% of the variation in cover, probably due to the spatially more variable nature of soft-substrate vegetation. The identified general responses of vegetation cover to gradients of eutrophication across wide ranges in environmental settings may be useful for monitoring and management of marine vegetation in areas with strong environmental gradients.
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NASA Astrophysics Data System (ADS)
Clément, A.; Laurens, S.
2011-07-01
The Structural Health Monitoring of civil structures subjected to ambient vibrations is very challenging. Indeed, the variations of environmental conditions and the difficulty to characterize the excitation make the damage detection a hard task. Auto-regressive (AR) models coefficients are often used as damage sensitive feature. The presented work proposes a comparison of the AR approach with a state-space feature formed by the Jacobian matrix of the dynamical process. Since the detection of damage can be formulated as a novelty detection problem, Mahalanobis distance is applied to track new points from an undamaged reference collection of feature vectors. Data from a concrete beam subjected to temperature variations and damaged by several static loading are analyzed. It is observed that the damage sensitive features are effectively sensitive to temperature variations. However, the use of the Mahalanobis distance makes possible the detection of cracking with both of them. Early damage (before cracking) is only revealed by the AR coefficients with a good sensibility.
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Quantifying variation in speciation and extinction rates with clade data.
Paradis, Emmanuel; Tedesco, Pablo A; Hugueny, Bernard
2013-12-01
High-level phylogenies are very common in evolutionary analyses, although they are often treated as incomplete data. Here, we provide statistical tools to analyze what we name "clade data," which are the ages of clades together with their numbers of species. We develop a general approach for the statistical modeling of variation in speciation and extinction rates, including temporal variation, unknown variation, and linear and nonlinear modeling. We show how this approach can be generalized to a wide range of situations, including testing the effects of life-history traits and environmental variables on diversification rates. We report the results of an extensive simulation study to assess the performance of some statistical tests presented here as well as of the estimators of speciation and extinction rates. These latter results suggest the possibility to estimate correctly extinction rate in the absence of fossils. An example with data on fish is presented. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
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Mayer, Melanie G; Sommer, Ralf J
2011-09-22
Many free-living nematodes, including the laboratory model organisms Caenorhabditis elegans and Pristionchus pacificus, have a choice between direct and indirect development, representing an important case of phenotypic plasticity. Under harsh environmental conditions, these nematodes form dauer larvae, which arrest development, show high resistance to environmental stress and constitute a dispersal stage. Pristionchus pacificus occurs in a strong association with scarab beetles in the wild and remains in the dauer stage on the living beetle. Here, we explored the circumstances under which P. pacificus enters and exits the dauer stage by using a natural variation approach. The analysis of survival, recovery and fitness after dauer exit of eight P. pacificus strains revealed that dauer larvae can survive for up to 1 year under experimental conditions. In a second experiment, we isolated dauer pheromones from 16 P. pacificus strains, and tested for natural variation in pheromone production and sensitivity in cross-reactivity assays. Surprisingly, 13 of the 16 strains produce a pheromone that induces the highest dauer formation in individuals of other genotypes. These results argue against a simple adaptation model for natural variation in dauer formation and suggest that strains may have evolved to induce dauer formation precociously in other strains in order to reduce the fitness of these strains. We therefore discuss intraspecific competition among genotypes as a previously unconsidered aspect of dauer formation. This journal is © 2011 The Royal Society
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Encarnación-Luévano, Alondra; Rojas-Soto, Octavio R; Sigala-Rodríguez, J Jesús
2013-01-01
The importance of climatic conditions in shaping the geographic distribution of amphibian species is mainly associated to their high sensitivity to environmental conditions. How they cope with climate gradients through behavioral adaptations throughout their distribution is an important issue due to the ecological and evolutionary implications for population viability. Given their low dispersal abilities, the response to seasonal climate changes may not be migration, but behavioral and physiological adaptations. Here we tested whether shifts in climatic seasonality can predict the temporal variation of surface activity of the fossorial Lowland Burrowing Treefrog (Smilisca fodiens) across its geographical distribution. We employed Ecological Niche Modeling (ENM) to perform a monthly analysis of spatial variation of suitable climatic conditions (defined by the July conditions, the month of greatest activity), and then evaluated the geographical correspondence of monthly projections with the occurrence data per month. We found that the species activity, based on the species' occurrence data, corresponds with the latitudinal variation of suitable climatic conditions. Due to the behavioral response of this fossorial frog to seasonal climate variation, we suggest that precipitation and temperature have played a major role in the definition of geographical and temporal distribution patterns, as well as in shaping behavioral adaptations to local climatic conditions. This highlights the influence of macroclimate on shaping activity patterns and the important role of fossorials habits to meet the environmental requirements necessary for survival.
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Lefebvre, Valérie; Kiani, Seifollah Poormohammad; Durand-Tardif, Mylène
2009-08-13
Plants are particularly subject to environmental stress, as they cannot move from unfavourable surroundings. As a consequence they have to react in situ. In any case, plants have to sense the stress, then the signal has to be transduced to engage the appropriate response. Stress response is effected by regulating genes, by turning on molecular mechanisms to protect the whole organism and its components and/or to repair damage. Reactions vary depending on the type of stress and its intensity, but some are commonly turned on because some responses to different abiotic stresses are shared. In addition, there are multiple ways for plants to respond to environmental stress, depending on the species and life strategy, but also multiple ways within a species depending on plant variety or ecotype. It is regularly accepted that populations of a single species originating from diverse geographic origins and/or that have been subjected to different selective pressure, have evolved retaining the best alleles for completing their life cycle. Therefore, the study of natural variation in response to abiotic stress, can help unravel key genes and alleles for plants to cope with their unfavourable physical and chemical surroundings. This review is focusing on Arabidopsis thaliana which has been largely adopted by the global scientific community as a model organism. Also, tools and data that facilitate investigation of natural variation and abiotic stress encountered in the wild are set out. Characterization of accessions, QTLs detection and cloning of alleles responsible for variation are presented.
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Sanabria, Eduardo Alfredo; Quiroga, Lorena Beatriz; Martino, Adolfo Ludovico
2012-03-01
We studied the variation of thermal parameters of Odontophrynus occidentalis between season (wet and dry) in the Monte desert (Argentina). We measured body temperatures, microhabitat temperatures, and operative temperatures; while in the laboratory, we measured the selected body temperatures. Our results show a change in the thermal parameters of O. occidentalis that is related to environmental constraints of their thermal niche. Environmental thermal constraints are present in both seasons (dry and wet), showing variations in thermal parameters studied. Apparently imposed environmental restrictions, the toads in nature always show body temperatures below the set point. Acclimatization is an advantage for toads because it allows them to bring more frequent body temperatures to the set point. The selected body temperature has seasonal intraindividual variability. These variations can be due to thermo-sensitivity of toads and life histories of individuals that limits their allocation and acquisition of resources. Possibly the range of variation found in selected body temperature is a consequence of the thermal environmental variation along the year. These variations of thermal parameters are commonly found in deserts and thermal bodies of nocturnal ectotherms. The plasticity of selected body temperature allows O. occidentales to have longer periods of activity for foraging and reproduction, while maintaining reasonable high performance at different temperatures. The plasticity in seasonal variation of the thermal parameters has been poorly studied, and is greatly advantageous to desert species during changes in both seasonal and daily temperature, as these environments are known for their high environmental variability. © 2012 WILEY PERIODICALS, INC.
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Kevin M. Potter; Douglas J. Shinneman; Robert E. Means; Valerie D. Hipkins; Mary Frances Mahalovich
2017-01-01
Geological, climatological and ecological processes partially or entirely isolate evolutionary lineages within tree species. These lineages may develop adaptations to different local environmental conditions, and may eventually evolve into distinct forms or species. Isolation also can reduce adaptive genetic variation within populations of a species, potentially...
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Jacobs, Rianne; Meesters, Johannes A J; Ter Braak, Cajo J F; van de Meent, Dik; van der Voet, Hilko
2016-12-01
There is a growing need for good environmental risk assessment of engineered nanoparticles (ENPs). Environmental risk assessment of ENPs has been hampered by lack of data and knowledge about ENPs, their environmental fate, and their toxicity. This leads to uncertainty in the risk assessment. To deal with uncertainty in the risk assessment effectively, probabilistic methods are advantageous. In the present study, the authors developed a method to model both the variability and the uncertainty in environmental risk assessment of ENPs. This method is based on the concentration ratio and the ratio of the exposure concentration to the critical effect concentration, both considered to be random. In this method, variability and uncertainty are modeled separately so as to allow the user to see which part of the total variation in the concentration ratio is attributable to uncertainty and which part is attributable to variability. The authors illustrate the use of the method with a simplified aquatic risk assessment of nano-titanium dioxide. The authors' method allows a more transparent risk assessment and can also direct further environmental and toxicological research to the areas in which it is most needed. Environ Toxicol Chem 2016;35:2958-2967. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC. © 2016 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.
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NASA Astrophysics Data System (ADS)
Bowen, Gabriel J.; Kennedy, Casey D.; Liu, Zhongfang; Stalker, Jeremy
2011-12-01
The stable H and O isotope composition of river and stream water records information on runoff sources and land-atmosphere water fluxes within the catchment and is a potentially powerful tool for network-based monitoring of ecohydrological systems. Process-based hydrological models, however, have thus far shown limited power to replicate observed large-scale variation in U.S. surface water isotope ratios. Here we develop a geographic information system-based model to predict long-term annual average surface water isotope ratios across the contiguous United States. We use elevation-explicit, gridded precipitation isotope maps as model input and data from a U.S. Geological Survey monitoring program for validation. We find that models incorporating monthly variation in precipitation-evapotranspiration (P-E) amounts account for the majority (>89%) of isotopic variation and have reduced regional bias relative to models that do not consider intra-annual P-E effects on catchment water balance. Residuals from the water balance model exhibit strong spatial patterning and correlations that suggest model residuals isolate additional hydrological signal. We use interpolated model residuals to generate optimized prediction maps for U.S. surface water δ2H and δ18O values. We show that the modeled surface water values represent a relatively accurate and unbiased proxy for drinking water isotope ratios across the United States, making these data products useful in ecological and criminal forensics applications that require estimates of the local environmental water isotope variation across large geographic regions.
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Diamond, Sarah E
2017-02-01
How will organisms respond to climate change? The rapid changes in global climate are expected to impose strong directional selection on fitness-related traits. A major open question then is the potential for adaptive evolutionary change under these shifting climates. At the most basic level, evolutionary change requires the presence of heritable variation and natural selection. Because organismal tolerances of high temperature place an upper bound on responding to temperature change, there has been a surge of research effort on the evolutionary potential of upper thermal tolerance traits. Here, I review the available evidence on heritable variation in upper thermal tolerance traits, adopting a biogeographic perspective to understand how heritability of tolerance varies across space. Specifically, I use meta-analytical models to explore the relationship between upper thermal tolerance heritability and environmental variability in temperature. I also explore how variation in the methods used to obtain these thermal tolerance heritabilities influences the estimation of heritable variation in tolerance. I conclude by discussing the implications of a positive relationship between thermal tolerance heritability and environmental variability in temperature and how this might influence responses to future changes in climate. © 2016 New York Academy of Sciences.
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NASA Astrophysics Data System (ADS)
Greene, Casey S.; Hill, Douglas P.; Moore, Jason H.
The relationship between interindividual variation in our genomes and variation in our susceptibility to common diseases is expected to be complex with multiple interacting genetic factors. A central goal of human genetics is to identify which DNA sequence variations predict disease risk in human populations. Our success in this endeavour will depend critically on the development and implementation of computational intelligence methods that are able to embrace, rather than ignore, the complexity of the genotype to phenotype relationship. To this end, we have developed a computational evolution system (CES) to discover genetic models of disease susceptibility involving complex relationships between DNA sequence variations. The CES approach is hierarchically organized and is capable of evolving operators of any arbitrary complexity. The ability to evolve operators distinguishes this approach from artificial evolution approaches using fixed operators such as mutation and recombination. Our previous studies have shown that a CES that can utilize expert knowledge about the problem in evolved operators significantly outperforms a CES unable to use this knowledge. This environmental sensing of external sources of biological or statistical knowledge is important when the search space is both rugged and large as in the genetic analysis of complex diseases. We show here that the CES is also capable of evolving operators which exploit one of several sources of expert knowledge to solve the problem. This is important for both the discovery of highly fit genetic models and because the particular source of expert knowledge used by evolved operators may provide additional information about the problem itself. This study brings us a step closer to a CES that can solve complex problems in human genetics in addition to discovering genetic models of disease.
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Temporal patterns in the foraging behavior of sea otters in Alaska
Esslinger, George G.; Bodkin, James L.; Breton, André R.; Burns, Jennifer M.; Monson, Daniel H.
2014-01-01
Activity time budgets in apex predators have been proposed as indicators of population status relative to resource limitation or carrying capacity. We used archival time-depth recorders implanted in 15 adult female and 4 male sea otters (Enhydra lutris) from the northernmost population of the species, Prince William Sound, Alaska, USA, to examine temporal patterns in their foraging behavior. Sea otters that we sampled spent less time foraging during summer (females 8.8 hr/day, males 7.9 hr/day) than other seasons (females 10.1–10.5 hr/day, males 9.2–9.5 hr/day). Both sexes showed strong preferences for diurnal foraging and adjusted their foraging effort in response to the amount of available daylight. One exception to this diurnal foraging mode occurred after females gave birth. For approximately 3 weeks post-partum, females switched to nocturnal foraging, possibly in an effort to reduce the risk of predation by eagles on newborn pups. We used multilevel mixed regression models to assess the contribution of several biological and environmental covariates to variation in the daily foraging effort of parous females. In the random effects only model, 87% of the total variation in foraging effort was within-otter variation. The relatively small among-otter variance component (13%) indicates substantial consistency in the foraging effort of sea otters in this northern population. In the top 3 models, 17% of the within-otter variation was explained by reproductive stage, day length, wind speed, air temperature and a wind speed × air temperature interaction. This study demonstrates the potential importance of environmental and reproductive effects when using activity budgets to assess population status relative to carrying capacity.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Nelson, Kurt; James, Scott C.; Roberts, Jesse D.
A modelling framework identifies deployment locations for current-energy-capture devices that maximise power output while minimising potential environmental impacts. The framework, based on the Environmental Fluid Dynamics Code, can incorporate site-specific environmental constraints. Over a 29-day period, energy outputs from three array layouts were estimated for: (1) the preliminary configuration (baseline), (2) an updated configuration that accounted for environmental constraints, (3) and an improved configuration subject to no environmental constraints. Of these layouts, array placement that did not consider environmental constraints extracted the most energy from flow (4.38 MW-hr/day), 19% higher than output from the baseline configuration (3.69 MW-hr/day). Array placementmore » that considered environmental constraints removed 4.27 MW-hr/day of energy (16% more than baseline). In conclusion, this analysis framework accounts for bathymetry and flow-pattern variations that typical experimental studies cannot, demonstrating that it is a valuable tool for identifying improved array layouts for field deployments.« less
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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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Identifying environmental correlates of intraspecific genetic variation.
Harrisson, K A; Yen, J D L; Pavlova, A; Rourke, M L; Gilligan, D; Ingram, B A; Lyon, J; Tonkin, Z; Sunnucks, P
2016-09-01
Genetic variation is critical to the persistence of populations and their capacity to adapt to environmental change. The distribution of genetic variation across a species' range can reveal critical information that is not necessarily represented in species occurrence or abundance patterns. We identified environmental factors associated with the amount of intraspecific, individual-based genetic variation across the range of a widespread freshwater fish species, the Murray cod Maccullochella peelii. We used two different approaches to statistically quantify the relative importance of predictor variables, allowing for nonlinear relationships: a random forest model and a Bayesian approach. The latter also accounted for population history. Both approaches identified associations between homozygosity by locus and both disturbance to the natural flow regime and mean annual flow. Homozygosity by locus was negatively associated with disturbance to the natural flow regime, suggesting that river reaches with more disturbed flow regimes may support larger, more genetically diverse populations. Our findings are consistent with the hypothesis that artificially induced perennial flows in regulated channels may provide greater and more consistent habitat and reduce the frequency of population bottlenecks that can occur frequently under the highly variable and unpredictable natural flow regime of the system. Although extensive river regulation across eastern Australia has not had an overall positive effect on Murray cod numbers over the past century, regulation may not represent the primary threat to Murray cod survival. Instead, pressures other than flow regulation may be more critical to the persistence of Murray cod (for example, reduced frequency of large floods, overfishing and chemical pollution).
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Endocrine mechanisms, behavioral phenotypes and plasticity: known relationships and open questions.
Hau, Michaela; Goymann, Wolfgang
2015-01-01
Behavior of wild vertebrate individuals can vary in response to environmental or social factors. Such within-individual behavioral variation is often mediated by hormonal mechanisms. Hormones also serve as a basis for among-individual variations in behavior including animal personalities and the degree of responsiveness to environmental and social stimuli. How do relationships between hormones and behavioral traits evolve to produce such behavioral diversity within and among individuals? Answering questions about evolutionary processes generating among-individual variation requires characterizing how specific hormones are related to variation in specific behavioral traits, whether observed hormonal variation is related to individual fitness and, whether hormonal traits are consistent (repeatable) aspects of an individual's phenotype. With respect to within-individual variation, we need to improve our insight into the nature of the quantitative relationships between hormones and the traits they regulate, which in turn will determine how they may mediate behavioral plasticity of individuals. To address these questions, we review the actions of two steroid hormones, corticosterone and testosterone, in mediating changes in vertebrate behavior, focusing primarily on birds. In the first part, we concentrate on among-individual variation and present examples for how variation in corticosterone concentrations can relate to behaviors such as exploration of novel environments and parental care. We then review studies on correlations between corticosterone variation and fitness, and on the repeatability over time of corticosterone concentrations. At the end of this section, we suggest that further progress in our understanding of evolutionary patterns in the hormonal regulation of behavior may require, as one major tool, reaction norm approaches to characterize hormonal phenotypes as well as their responses to environments. In the second part, we discuss types of quantitative relationships between hormones and behavioral traits within individuals, using testosterone as an example. We review conceptual models for testosterone-behavior relationships and discuss the relevance of these models for within-individual plasticity in behavior. Next, we discuss approaches for testing the nature of quantitative relationships between testosterone and behavior, concluding that again reaction norm approaches might be a fruitful way forward. We propose that an integration of new tools, especially of reaction norm approaches into the field of behavioral endocrinology will allow us to make significant progress in our understanding of the mechanisms, the functional implications and the evolution of hormone-behavior relationships that mediate variation both within and among individuals. This knowledge will be crucial in light of already ongoing habitat alterations due to global change, as it will allow us to evaluate the mechanisms as well as the capacity of wild populations to adjust hormonally-mediated behaviors to altered environmental conditions.
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Hubbard, Joanna K; Jenkins, Brittany R; Safran, Rebecca J
2015-01-01
Phenotypic differences among individuals are often linked to differential survival and mating success. Quantifying the relative influence of genetic and environmental variation on phenotype allows evolutionary biologists to make predictions about the potential for a given trait to respond to selection and various aspects of environmental variation. In particular, the environment individuals experience during early development can have lasting effects on phenotype later in life. Here, we used a natural full-sib/half-sib design as well as within-individual longitudinal analyses to examine genetic and various environmental influences on plumage color. We find that variation in melanin-based plumage color – a trait known to influence mating success in adult North American barn swallows (Hirundo rustica erythrogaster) – is influenced by both genetics and aspects of the developmental environment, including variation due to the maternal phenotype and the nest environment. Within individuals, nestling color is predictive of adult color. Accordingly, these early environmental influences are relevant to the sexually selected plumage color variation in adults. Early environmental conditions appear to have important lifelong implications for individual reproductive performance through sexual signal development in barn swallows. Our results indicate that feather color variation conveys information about developmental conditions and maternal care alleles to potential mates in North American barn swallows. Melanin-based colors are used for sexual signaling in many organisms, and our study suggests that these signals may be more sensitive to environmental variation than previously thought. PMID:26380676
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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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Oliveira, João M.; Segurado, Pedro; Santos, José M.; Teixeira, Amílcar; Ferreira, Maria T.; Cortes, Rui V.
2012-01-01
Identifying the environmental gradients that control the functional structure of biological assemblages in reference conditions is fundamental to help river management and predict the consequences of anthropogenic stressors. Fish metrics (density of ecological guilds, and species richness) from 117 least disturbed stream reaches in several western Iberia river basins were modelled with generalized linear models in order to investigate the importance of regional- and local-scale abiotic gradients to variation in functional structure of fish assemblages. Functional patterns were primarily associated with regional features, such as catchment elevation and slope, rainfall, and drainage area. Spatial variations of fish guilds were thus associated with broad geographic gradients, showing (1) pronounced latitudinal patterns, affected mainly by climatic factors and topography, or (2) at the basin level, strong upstream-downstream patterns related to stream position in the longitudinal gradient. Maximum native species richness was observed in midsize streams in accordance with the river continuum concept. The findings of our study emphasized the need to use a multi-scale approach in order to fully assess the factors that govern the functional organization of biotic assemblages in ‘natural’ streams, as well as to improve biomonitoring and restoration of fluvial ecosystems. PMID:23029242
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Patrick, Christopher J; Yuan, Lester L
2017-07-01
Flow alteration is widespread in streams, but current understanding of the effects of differences in flow characteristics on stream biological communities is incomplete. We tested hypotheses about the effect of variation in hydrology on stream communities by using generalized additive models to relate watershed information to the values of different flow metrics at gauged sites. Flow models accounted for 54-80% of the spatial variation in flow metric values among gauged sites. We then used these models to predict flow metrics in 842 ungauged stream sites in the mid-Atlantic United States that were sampled for fish, macroinvertebrates, and environmental covariates. Fish and macroinvertebrate assemblages were characterized in terms of a suite of metrics that quantified aspects of community composition, diversity, and functional traits that were expected to be associated with differences in flow characteristics. We related modeled flow metrics to biological metrics in a series of stressor-response models. Our analyses identified both drying and base flow instability as explaining 30-50% of the observed variability in fish and invertebrate community composition. Variations in community composition were related to variations in the prevalence of dispersal traits in invertebrates and trophic guilds in fish. The results demonstrate that we can use statistical models to predict hydrologic conditions at bioassessment sites, which, in turn, we can use to estimate relationships between flow conditions and biological characteristics. This analysis provides an approach to quantify the effects of spatial variation in flow metrics using readily available biomonitoring data. © 2017 by the Ecological Society of America.
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Hjort, Jan; Hugg, Timo T; Antikainen, Harri; Rusanen, Jarmo; Sofiev, Mikhail; Kukkonen, Jaakko; Jaakkola, Maritta S; Jaakkola, Jouni J K
2016-05-01
Despite the recent developments in physically and chemically based analysis of atmospheric particles, no models exist for resolving the spatial variability of pollen concentration at urban scale. We developed a land use regression (LUR) approach for predicting spatial fine-scale allergenic pollen concentrations in the Helsinki metropolitan area, Finland, and evaluated the performance of the models against available empirical data. We used grass pollen data monitored at 16 sites in an urban area during the peak pollen season and geospatial environmental data. The main statistical method was generalized linear model (GLM). GLM-based LURs explained 79% of the spatial variation in the grass pollen data based on all samples, and 47% of the variation when samples from two sites with very high concentrations were excluded. In model evaluation, prediction errors ranged from 6% to 26% of the observed range of grass pollen concentrations. Our findings support the use of geospatial data-based statistical models to predict the spatial variation of allergenic grass pollen concentrations at intra-urban scales. A remote sensing-based vegetation index was the strongest predictor of pollen concentrations for exposure assessments at local scales. The LUR approach provides new opportunities to estimate the relations between environmental determinants and allergenic pollen concentration in human-modified environments at fine spatial scales. This approach could potentially be applied to estimate retrospectively pollen concentrations to be used for long-term exposure assessments. Hjort J, Hugg TT, Antikainen H, Rusanen J, Sofiev M, Kukkonen J, Jaakkola MS, Jaakkola JJ. 2016. Fine-scale exposure to allergenic pollen in the urban environment: evaluation of land use regression approach. Environ Health Perspect 124:619-626; http://dx.doi.org/10.1289/ehp.1509761.
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Neutral dynamics with environmental noise: Age-size statistics and species lifetimes
NASA Astrophysics Data System (ADS)
Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M.
2015-08-01
Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O (√{N }) ] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Lu; Hejazi, Mohamad; Li, Hongyi
This study explores the interactions between climate and thermoelectric generation in the U.S. by coupling an Earth System Model with a thermoelectric power generation model. We validated model simulations of power production for selected power plants (~44% of existing thermoelectric capacity) against reported values. In addition, we projected future usable capacity for existing power plants under two different climate change scenarios. Results indicate that climate change alone may reduce average thermoelectric generating capacity by 2%-3% by the 2060s. Reductions up to 12% are expected if environmental requirements are enforced without waivers for thermal variation. This study concludes that the impactmore » of climate change on the U.S. thermoelectric power system is less than previous estimates due to an inclusion of a spatially-disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. This work highlights the significance of accounting for legal constructs in which the operation of power plants are managed, and underscores the effects of provisional variances in addition to environmental requirements.« less
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Temporal and Spatial Variations in the Twinning Rate in Norway.
Fellman, Johan
2016-08-01
Strong geographical variations have been noted in the twinning rate (TWR). In general, the rate is high among people of African origin, intermediate among Europeans, and low among most Asiatic populations. In Europe, there tends to be a south-north cline, with a progressive increase in the TWR from south to north and a minimum around the Basque provinces. The highest TWRs in Europe have been found among the Nordic populations. Furthermore, within larger populations, small isolated subpopulations have been identified to have extreme, mainly high, TWRs. In the study of the temporal variation of the TWR in Norway, we consider the period from 1900 to 2014. The regional variation of the TWR in Norway is analyzed for the different counties for two periods, 1916-1926 and 1960-1988. Heterogeneity between the regional TWRs in Norway during 1916-1926 was found, but the goodness of fit for the alternative spatial models was only slight. The optimal regression model for the TWR in Norway has the longitude and its square as regressors. According to this model, the spatial variation is distributed in a west-east direction. For 1960-1988, no significant regional variation was observed. One may expect that the environmental and genetic differences between the counties in Norway have disappeared and that the regional TWRs have converged towards a common low level.
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Evolutionary response when selection and genetic variation covary across environments.
Wood, Corlett W; Brodie, Edmund D
2016-10-01
Although models of evolution usually assume that the strength of selection on a trait and the expression of genetic variation in that trait are independent, whenever the same ecological factor impacts both parameters, a correlation between the two may arise that accelerates trait evolution in some environments and slows it in others. Here, we address the evolutionary consequences and ecological causes of a correlation between selection and expressed genetic variation. Using a simple analytical model, we show that the correlation has a modest effect on the mean evolutionary response and a large effect on its variance, increasing among-population or among-generation variation in the response when positive, and diminishing variation when negative. We performed a literature review to identify the ecological factors that influence selection and expressed genetic variation across traits. We found that some factors - temperature and competition - are unlikely to generate the correlation because they affected one parameter more than the other, and identified others - most notably, environmental novelty - that merit further investigation because little is known about their impact on one of the two parameters. We argue that the correlation between selection and genetic variation deserves attention alongside other factors that promote or constrain evolution in heterogeneous landscapes. © 2016 John Wiley & Sons Ltd/CNRS.
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Air-mediated pollen flow from genetically modified to conventional crops.
Kuparinen, Anna; Schurr, Frank; Tackenberg, Oliver; O'Hara, Robert B
2007-03-01
Tools for estimating pollen dispersal and the resulting gene flow are necessary to assess the risk of gene flow from genetically modified (GM) to conventional fields, and to quantify the effectiveness of measures that may prevent such gene flow. A mechanistic simulation model is presented and used to simulate pollen dispersal by wind in different agricultural scenarios over realistic pollination periods. The relative importance of landscape-related variables such as isolation distance, topography, spatial configuration of the fields, GM field size and barrier, and environmental variation are examined in order to find ways to minimize gene flow and to detect possible risk factors. The simulations demonstrated a large variation in pollen dispersal and in the predicted amount of contamination between different pollination periods. This was largely due to variation in vertical wind. As this variation in wind conditions is difficult to control through management measures, it should be carefully considered when estimating the risk of gene flow from GM crops. On average, the predicted level of gene flow decreased with increasing isolation distance and with increasing depth of the conventional field, and increased with increasing GM field size. Therefore, at a national scale and over the long term these landscape properties should be accounted for when setting regulations for controlling gene flow. However, at the level of an individual field the level of gene flow may be dominated by uncontrollable variation. Due to the sensitivity of pollen dispersal to the wind, we conclude that gene flow cannot be summarized only by the mean contamination; information about the frequency of extreme events should also be considered. The modeling approach described in this paper offers a way to predict and compare pollen dispersal and gene flow in varying environmental conditions, and to assess the effectiveness of different management measures.
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Xia, Charley; Amador, Carmen; Huffman, Jennifer; Trochet, Holly; Campbell, Archie; Porteous, David; Hastie, Nicholas D; Hayward, Caroline; Vitart, Veronique; Navarro, Pau; Haley, Chris S
2016-02-01
Genome-wide association studies have successfully identified thousands of loci for a range of human complex traits and diseases. The proportion of phenotypic variance explained by significant associations is, however, limited. Given the same dense SNP panels, mixed model analyses capture a greater proportion of phenotypic variance than single SNP analyses but the total is generally still less than the genetic variance estimated from pedigree studies. Combining information from pedigree relationships and SNPs, we examined 16 complex anthropometric and cardiometabolic traits in a Scottish family-based cohort comprising up to 20,000 individuals genotyped for ~520,000 common autosomal SNPs. The inclusion of related individuals provides the opportunity to also estimate the genetic variance associated with pedigree as well as the effects of common family environment. Trait variation was partitioned into SNP-associated and pedigree-associated genetic variation, shared nuclear family environment, shared couple (partner) environment and shared full-sibling environment. Results demonstrate that trait heritabilities vary widely but, on average across traits, SNP-associated and pedigree-associated genetic effects each explain around half the genetic variance. For most traits the recently-shared environment of couples is also significant, accounting for ~11% of the phenotypic variance on average. On the other hand, the environment shared largely in the past by members of a nuclear family or by full-siblings, has a more limited impact. Our findings point to appropriate models to use in future studies as pedigree-associated genetic effects and couple environmental effects have seldom been taken into account in genotype-based analyses. Appropriate description of the trait variation could help understand causes of intra-individual variation and in the detection of contributing loci and environmental factors.
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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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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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Sawaya, Gina M; Goldberg, Adam S; Steele, Michael A; Dalgleish, Harmony J
2018-05-01
The conditional mutualism between scatterhoarders and trees varies on a continuum from mutualism to antagonism and can change across time and space, and among species. We examined 4 tree species (red oak [Quercus rubra], white oak [Quercus alba], American chestnut [Castanea dentata] and hybrid chestnut [C. dentata × Castanea mollissima) across 5 sites and 3 years to quantify the variability in this conditional mutualism. We used a published model to compare the rates of seed emergence with and without burial to the probability that seeds will be cached and left uneaten by scatterhoarders to quantify variation in the conditional mutualism that can be explained by environmental variation among sites, years, species, and seed provenance within species. All species tested had increased emergence when buried. However, comparing benefits of burial to the probability of caching by scatterhoarders indicated a mutualism in red oak, while white oak was nearly always antagonistic. Chestnut was variable around the boundary between mutualism and antagonism, indicating a high degree of context dependence in the relationship with scatterhoarders. We found that different seed provenances did not vary in their potential for mutualism. Temperature did not explain microsite differences in seed emergence in any of the species tested. In hybrid chestnut only, emergence on the surface declined with soil moisture in the fall. By quantifying the variation in the conditional mutualism that was not caused by changes in scatterhoarder behavior, we show that environmental conditions and seed traits are an important and underappreciated component of the variation in the relationship between trees and scatterhoarders. © 2018 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.
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Food web dynamics in a seasonally varying wetland
DeAngelis, D.L.; Trexler, J.C.; Donalson, D.D.
2008-01-01
A spatially explicit model is developed to simulate the small fish community and its underlying food web, in the freshwater marshes of the Everglades. The community is simplified to a few small fish species feeding on periphyton and invertebrates. Other compartments are detritus, crayfish, and a piscivorous fish species. This unit food web model is applied to each of the 10,000 spatial cells on a 100 x 100 pixel landscape. Seasonal variation in water level is assumed and rules are assigned for fish movement in response to rising and falling water levels, which can cause many spatial cells to alternate between flooded and dry conditions. It is shown that temporal variations of water level on a spatially heterogeneous landscape can maintain at least three competing fish species. In addition, these environmental factors can strongly affect the temporal variation of the food web caused by top-down control from the piscivorous fish.
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NASA Astrophysics Data System (ADS)
Chisholm, Rebecca H.; Lorenzi, Tommaso; Desvillettes, Laurent; Hughes, Barry D.
2016-08-01
Epigenetic mechanisms are increasingly recognised as integral to the adaptation of species that face environmental changes. In particular, empirical work has provided important insights into the contribution of epigenetic mechanisms to the persistence of clonal species, from which a number of verbal explanations have emerged that are suited to logical testing by proof-of-concept mathematical models. Here, we present a stochastic agent-based model and a related deterministic integrodifferential equation model for the evolution of a phenotype-structured population composed of asexually-reproducing and competing organisms which are exposed to novel environmental conditions. This setting has relevance to the study of biological systems where colonising asexual populations must survive and rapidly adapt to hostile environments, like pathogenesis, invasion and tumour metastasis. We explore how evolution might proceed when epigenetic variation in gene expression can change the reproductive capacity of individuals within the population in the new environment. Simulations and analyses of our models clarify the conditions under which certain evolutionary paths are possible and illustrate that while epigenetic mechanisms may facilitate adaptation in asexual species faced with environmental change, they can also lead to a type of "epigenetic load" and contribute to extinction. Moreover, our results offer a formal basis for the claim that constant environments favour individuals with low rates of stochastic phenotypic variation. Finally, our model provides a "proof of concept" of the verbal hypothesis that phenotypic stability is a key driver in rescuing the adaptive potential of an asexual lineage and supports the notion that intense selection pressure can, to an extent, offset the deleterious effects of high phenotypic instability and biased epimutations, and steer an asexual population back from the brink of an evolutionary dead end.
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Personality and Sociodemographic Variables as Sources of Variation in Environmental Perception.
ERIC Educational Resources Information Center
Feimer, Nickolaus R.
This research paper examines the relationship between individual differences in environmental perception, and variables which may be important in predicting, if not explaining those variations. The analyses reported were based upon an environmental perception research study previously conducted at the University of California at Berkeley during…
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Modelling the multidimensional niche by linking functional traits to competitive performance
Maynard, Daniel S.; Leonard, Kenneth E.; Drake, John M.; Hall, David W.; Crowther, Thomas W.; Bradford, Mark A.
2015-01-01
Linking competitive outcomes to environmental conditions is necessary for understanding species' distributions and responses to environmental change. Despite this importance, generalizable approaches for predicting competitive outcomes across abiotic gradients are lacking, driven largely by the highly complex and context-dependent nature of biotic interactions. Here, we present and empirically test a novel niche model that uses functional traits to model the niche space of organisms and predict competitive outcomes of co-occurring populations across multiple resource gradients. The model makes no assumptions about the underlying mode of competition and instead applies to those settings where relative competitive ability across environments correlates with a quantifiable performance metric. To test the model, a series of controlled microcosm experiments were conducted using genetically related strains of a widespread microbe. The model identified trait microevolution and performance differences among strains, with the predicted competitive ability of each organism mapped across a two-dimensional carbon and nitrogen resource space. Areas of coexistence and competitive dominance between strains were identified, and the predicted competitive outcomes were validated in approximately 95% of the pairings. By linking trait variation to competitive ability, our work demonstrates a generalizable approach for predicting and modelling competitive outcomes across changing environmental contexts. PMID:26136444
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Lin, Maozi; Wang, Zhiwei; He, Lingchao; Xu, Kang; Cheng, Dongliang; Wang, Genxuan
2015-01-01
Photosynthesis-irradiance (PI) curves are extensively used in field and laboratory research to evaluate the photon-use efficiency of plants. However, most existing models for PI curves focus on the relationship between the photosynthetic rate (Pn) and photosynthetically active radiation (PAR), and do not take account of the influence of environmental factors on the curve. In the present study, we used a new non-competitive inhibited Michaelis-Menten model (NIMM) to predict the co-variation of Pn, PAR, and the relative pollution index (I). We then evaluated the model with published data and our own experimental data. The results indicate that the Pn of plants decreased with increasing I in the environment and, as predicted, were all fitted well by the NIMM model. Therefore, our model provides a robust basis to evaluate and understand the influence of environmental pollution on plant photosynthesis. PMID:26561863
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Architecture and functional ecology of the human gastrocnemius muscle-tendon unit.
Butler, Erin E; Dominy, Nathaniel J
2016-04-01
The gastrocnemius muscle-tendon unit (MTU) is central to human locomotion. Structural variation in the human gastrocnemius MTU is predicted to affect the efficiency of locomotion, a concept most often explored in the context of performance activities. For example, stiffness of the Achilles tendon varies among individuals with different histories of competitive running. Such a finding highlights the functional variation of individuals and raises the possibility of similar variation between populations, perhaps in response to specific ecological or environmental demands. Researchers often assume minimal variation in human populations, or that industrialized populations represent the human species as well as any other. Yet rainforest hunter-gatherers, which often express the human pygmy phenotype, contradict such assumptions. Indeed, the human pygmy phenotype is a potential model system for exploring the range of ecomorphological variation in the architecture of human hindlimb muscles, a concept we review here. © 2015 Anatomical Society.
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Modeling elm growth and Dutch elm disease susceptibility
Alberto Santini; Luisa Ghelardini
2012-01-01
Elm susceptibility to Dutch elm disease (DED) displays strong seasonal variation. The period during which elms can become infected and express DED symptoms is generally restricted to several weeks after growth resumption in spring, although it can vary among species, provenances, and environmental conditions. The reason for this phenomenon is not understood, but the...
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Repeatability of circadian behavioural variation revealed in free-ranging marine fish.
Alós, Josep; Martorell-Barceló, Martina; Campos-Candela, Andrea
2017-02-01
Repeatable between-individual differences in the behavioural manifestation of underlying circadian rhythms determine chronotypes in humans and terrestrial animals. Here, we have repeatedly measured three circadian behaviours, awakening time, rest onset and rest duration, in the free-ranging pearly razorfish, Xyrithchys novacula , facilitated by acoustic tracking technology and hidden Markov models. In addition, daily travelled distance, a standard measure of daily activity as fish personality trait, was repeatedly assessed using a State-Space Model. We have decomposed the variance of these four behavioural traits using linear mixed models and estimated repeatability scores ( R ) while controlling for environmental co-variates: year of experimentation, spatial location of the activity, fish size and gender and their interactions. Between- and within-individual variance decomposition revealed significant R s in all traits suggesting high predictability of individual circadian behavioural variation and the existence of chronotypes. The decomposition of the correlations among chronotypes and the personality trait studied here into between- and within-individual correlations did not reveal any significant correlation at between-individual level. We therefore propose circadian behavioural variation as an independent axis of the fish personality, and the study of chronotypes and their consequences as a novel dimension in understanding within-species fish behavioural diversity.
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Fire, humans, and climate: modeling distribution dynamics of boreal forest waterbirds.
Börger, Luca; Nudds, Thomas D
2014-01-01
Understanding the effects of landscape change and environmental variability on ecological processes is important for evaluating resource management policies, such as the emulation of natural forest disturbances. We analyzed time series of detection/nondetection data using hierarchical models in a Bayesian multi-model inference framework to decompose the dynamics of species distributions into responses to environmental variability, spatial variation in habitat conditions, and population dynamics and interspecific interactions, while correcting for observation errors and variation in sampling regimes. We modeled distribution dynamics of 14 waterbird species (broadly defined, including wetland and riparian species) using data from two different breeding bird surveys collected in the Boreal Shield ecozone within Ontario, Canada. Temporal variation in species occupancy (2000-2006) was primarily driven by climatic variability. Only two species showed evidence of consistent temporal trends in distribution: Ring-necked Duck (Aythya collaris) decreased, and Red-winged Blackbird (Agelaius phoeniceus) increased. The models had good predictive ability on independent data over time (1997-1999). Spatial variation in species occupancy was strongly related to the distribution of specific land cover types and habitat disturbance: Fire and forest harvesting influenced occupancy more than did roads, settlements, or mines. Bioclimatic and habitat heterogeneity indices and geographic coordinates exerted negligible influence on most species distributions. Estimated habitat suitability indices had good predictive ability on spatially independent data (Hudson Bay Lowlands ecozone). Additionally, we detected effects of interspecific interactions. Species responses to fire and forest harvesting were similar for 13 of 14 species; thus, forest-harvesting practices in Ontario generally appeared to emulate the effects of fire for waterbirds over timescales of 10-20 years. Extrapolating to all 84 waterbird species breeding on the Ontario Boreal Shield, however, suggested that up to 30 species may instead have altered (short-term) distribution dynamics due to forestry practices. Hence, natural disturbances are critical components of the ecology of the boreal forest and forest practices which aim to approximate them may succeed in allowing the maintenance of the associated species, but improved monitoring and modeling of large-scale boreal forest bird distribution dynamics will be necessary to resolve existing uncertainties, especially on less-common species.
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Törnwall, Outi; Silventoinen, Karri; Kaprio, Jaakko; Tuorila, Hely
2012-10-10
Although potential environmental influences on hedonic responses to oral pungency have been identified, little is known of the possible role of genetics underlying these responses. We explored the contribution of genetic and environmental influences on the pleasantness of oral pungency and spicy foods. Respondents were young adult Finnish twins (n=331, 21-25 years), including 47 complete monozygotic and 93 dizygotic twin pairs and 51 twin individuals without their co-twin. Pleasantness and intensity of strawberry jelly spiked with capsaicin (0.0001% w/v) relative to untainted strawberry jelly were rated. Furthermore, pleasantness of spicy foods and oral pungency caused by spices were rated based on food names in a questionnaire. Respondents were grouped as non-likers, medium-likers, and likers by their pleasantness responses to capsaicin spiked jelly. The contribution of genetic and environmental factors to variation and co-variation of the pleasantness traits was analyzed using quantitative genetic modeling. The non-likers perceived oral pungency as more intense (sensory) and rated pleasantness of spicy foods and pungent sensations caused by spices (questionnaire) as less pleasant than the likers. Genetic factors accounted for 18-58% of the variation in the pleasantness of oral pungency, spicy foods and pungent sensations. The rest was due to environmental factors. All pleasantness traits (sensory and questionnaire based) were shown to share a common genetic variance. This indicates that an underlying genetic aptitude to like oral pungency, and spicy foods exists and it is expressed in these measures. The findings broaden the understanding of the diverse nature of individual food preferences and motivate further search for the underlying genetic components of oral pungency. Copyright © 2012. Published by Elsevier Inc.
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Alvarenga, Júlio Miguel; Vieira, Cecília Rodrigues; Godinho, Leandro Braga; Campelo, Pedro Henrique; Pitts, James Purser; Colli, Guarino Rinaldi
2017-01-01
Understanding how and why biological communities are organized over space and time is a major challenge and can aid biodiversity conservation in times of global changes. Herein, spatial-temporal variation in the structure of velvet ant communities was examined along a forest-savanna gradient in the Brazilian Cerrado to assess the roles of environmental filters and interspecific interactions upon community assembly. Velvet ants were sampled using 25 arrays of Y-shaped pitfall traps with drift fences for one year along an environmental gradient from cerrado sensu stricto (open canopy, warmer, drier) to cerradão (closed canopy, cooler, moister). Dataloggers installed on each trap recorded microclimate parameters throughout the study period. The effects of spatial distances, microclimate parameters and shared ancestry on species abundances and turnover were assessed with canonical correspondence analysis, generalized dissimilarity modelling and variance components analysis. Velvet ant diversity and abundance were higher in the cerrado sensu stricto and early in the wet season. There was pronounced compositional turnover along the environmental gradient, and temporal variation in richness and abundance was stronger than spatial variation. The dry season blooming of woody plant species fosters host abundance and, subsequently, velvet ant captures. Species were taxonomically clustered along the gradient with Sphaeropthalmina (especially Traumatomutilla spp.) and Pseudomethocina more associated, respectively, with cerrado sensu stricto and cerradão. This suggests a predominant role of environmental filters on community assemble, with physiological tolerances and host preferences being shared among members of the same lineages. Induced environmental changes in Cerrado can impact communities of wasps and their hosts with unpredictable consequences upon ecosystem functioning and services.
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Godinho, Leandro Braga; Campelo, Pedro Henrique; Pitts, James Purser; Colli, Guarino Rinaldi
2017-01-01
Understanding how and why biological communities are organized over space and time is a major challenge and can aid biodiversity conservation in times of global changes. Herein, spatial-temporal variation in the structure of velvet ant communities was examined along a forest-savanna gradient in the Brazilian Cerrado to assess the roles of environmental filters and interspecific interactions upon community assembly. Velvet ants were sampled using 25 arrays of Y-shaped pitfall traps with drift fences for one year along an environmental gradient from cerrado sensu stricto (open canopy, warmer, drier) to cerradão (closed canopy, cooler, moister). Dataloggers installed on each trap recorded microclimate parameters throughout the study period. The effects of spatial distances, microclimate parameters and shared ancestry on species abundances and turnover were assessed with canonical correspondence analysis, generalized dissimilarity modelling and variance components analysis. Velvet ant diversity and abundance were higher in the cerrado sensu stricto and early in the wet season. There was pronounced compositional turnover along the environmental gradient, and temporal variation in richness and abundance was stronger than spatial variation. The dry season blooming of woody plant species fosters host abundance and, subsequently, velvet ant captures. Species were taxonomically clustered along the gradient with Sphaeropthalmina (especially Traumatomutilla spp.) and Pseudomethocina more associated, respectively, with cerrado sensu stricto and cerradão. This suggests a predominant role of environmental filters on community assemble, with physiological tolerances and host preferences being shared among members of the same lineages. Induced environmental changes in Cerrado can impact communities of wasps and their hosts with unpredictable consequences upon ecosystem functioning and services. PMID:29077763
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Environmental and genetic determinants of innovativeness in a natural population of birds
Quinn, John L.; Cole, Ella F.; Reed, Thomas E.
2016-01-01
Much of the evidence for the idea that individuals differ in their propensity to innovate and solve new problems has come from studies on captive primates. Increasingly, behavioural ecologists are studying innovativeness in wild populations, and uncovering links with functional behaviour and fitness-related traits. The relative importance of genetic and environmental factors in driving this variation, however, remains unknown. Here, we present the results of the first large-scale study to examine a range of causal factors underlying innovative problem-solving performance (PSP) among 831 great tits (Parus major) temporarily taken into captivity. Analyses show that PSP in this population: (i) was linked to a variety of individual factors, including age, personality and natal origin (immigrant or local-born); (ii) was influenced by natal environment, because individuals had a lower PSP when born in poor-quality habitat, or where local population density was high, leading to cohort effects. Links with many of the individual and environmental factors were present only in some years. In addition, PSP (iii) had little or no measurable heritability, as estimated by a Bayesian animal model; and (iv) was not influenced by maternal effects. Despite previous reports of links between PSP and a range of functional traits in this population, the analyses here suggest that innovativeness had weak if any evolutionary potential. Instead most individual variation was caused by phenotypic plasticity driven by links with other behavioural traits and by environmentally mediated developmental stress. Heritability estimates are population, time and context specific, however, and more studies are needed to determine the generality of these effects. Our results shed light on the causes of innovativeness within populations, and add to the debate on the relative importance of genetic and environmental factors in driving phenotypic variation within populations. PMID:26926275
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NASA Astrophysics Data System (ADS)
Silva, Claudio; Yáñez, Eleuterio; Barbieri, María Angela; Bernal, Claudio; Aranis, Antonio
2015-05-01
Recent studies have demonstrated the effects of climate change on both oceanographic conditions and the relative abundance and distribution of fisheries resources. In this study, we investigated the impacts of climate change on swordfish (Xiphias gladius) and common sardine (Strangomera bentincki) fisheries using predictions of changes from global models (according to the NCAR model and IPCC emissions scenario A2), bioclimate envelope models and satellite-based sea surface temperature (SST) estimates from high-resolution regional models for the simulation period 2015-2065. Predictions of SST from global climate models were regionalised using the Delta statistical downscaling technique. The results show an SST trend of 0.0196 °C per year in the study area, equivalent to 0.98 °C for the simulation horizon and for a high CO2 emission scenario (A2). The bioclimate envelope models were developed using historical (2001-2011) monthly environmental and fisheries data. These data included the local relative abundance index of fish catch per unit effort (CPUE), corresponding to the total catch (kg) by 1000 hooks in a 1° latitude × 1° longitude fishing grid for swordfish and to the total catch (ton) by hold capacity (100 m3) in a 10‧ latitude × 10‧ longitude grid for common sardine. The environmental data included temporal (month), spatial (latitude) and thermal conditions (SST). In the first step of the bioclimate modelling performed in this study, generalised additive models (GAMs) were used as an exploratory tool to identify the functional relationships between the environmental variables and CPUE. These relationships were then parameterised using general linear models (GLMs) to provide a robust forecasting tool. With this modelling approach, environmental variables explained 58.7% of the variation in the CPUE of swordfish and 60.6% of the variation in the CPUE of common sardine in the final GLMs. Using IDRISI GIS, these GLMs simulated monthly changes in the relative abundance and distribution of the studied species forced by changes in the regionalised SST projected by the NCAR model under the A2 emission scenario. The simulations predicted a slight decline of 6% (17 kg/1000 hooks) and 7% (3.8 ton/100 m3) for swordfish and common sardine, respectively, in the spatial mean of the potential relative abundance (CPUE) by 2065.
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Cisneros, Laura M; Fagan, Matthew E; Willig, Michael R
2016-01-01
Assembly of species into communities following human disturbance (e.g., deforestation, fragmentation) may be governed by spatial (e.g., dispersal) or environmental (e.g., niche partitioning) mechanisms. Variation partitioning has been used to broadly disentangle spatial and environmental mechanisms, and approaches utilizing functional and phylogenetic characteristics of communities have been implemented to determine the relative importance of particular environmental (or niche-based) mechanisms. Nonetheless, few studies have integrated these quantitative approaches to comprehensively assess the relative importance of particular structuring processes. We employed a novel variation partitioning approach to evaluate the relative importance of particular spatial and environmental drivers of taxonomic, functional, and phylogenetic aspects of bat communities in a human-modified landscape in Costa Rica. Specifically, we estimated the amount of variation in species composition (taxonomic structure) and in two aspects of functional and phylogenetic structure (i.e., composition and dispersion) along a forest loss and fragmentation gradient that are uniquely explained by landscape characteristics (i.e., environment) or space to assess the importance of competing mechanisms. The unique effects of space on taxonomic, functional and phylogenetic structure were consistently small. In contrast, landscape characteristics (i.e., environment) played an appreciable role in structuring bat communities. Spatially-structured landscape characteristics explained 84% of the variation in functional or phylogenetic dispersion, and the unique effects of landscape characteristics significantly explained 14% of the variation in species composition. Furthermore, variation in bat community structure was primarily due to differences in dispersion of species within functional or phylogenetic space along the gradient, rather than due to differences in functional or phylogenetic composition. Variation among bat communities was related to environmental mechanisms, especially niche-based (i.e., environmental) processes, rather than spatial mechanisms. High variation in functional or phylogenetic dispersion, as opposed to functional or phylogenetic composition, suggests that loss or gain of niche space is driving the progressive loss or gain of species with particular traits from communities along the human-modified gradient. Thus, environmental characteristics associated with landscape structure influence functional or phylogenetic aspects of bat communities by effectively altering the ways in which species partition niche space.
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Fagan, Matthew E.; Willig, Michael R.
2016-01-01
Background Assembly of species into communities following human disturbance (e.g., deforestation, fragmentation) may be governed by spatial (e.g., dispersal) or environmental (e.g., niche partitioning) mechanisms. Variation partitioning has been used to broadly disentangle spatial and environmental mechanisms, and approaches utilizing functional and phylogenetic characteristics of communities have been implemented to determine the relative importance of particular environmental (or niche-based) mechanisms. Nonetheless, few studies have integrated these quantitative approaches to comprehensively assess the relative importance of particular structuring processes. Methods We employed a novel variation partitioning approach to evaluate the relative importance of particular spatial and environmental drivers of taxonomic, functional, and phylogenetic aspects of bat communities in a human-modified landscape in Costa Rica. Specifically, we estimated the amount of variation in species composition (taxonomic structure) and in two aspects of functional and phylogenetic structure (i.e., composition and dispersion) along a forest loss and fragmentation gradient that are uniquely explained by landscape characteristics (i.e., environment) or space to assess the importance of competing mechanisms. Results The unique effects of space on taxonomic, functional and phylogenetic structure were consistently small. In contrast, landscape characteristics (i.e., environment) played an appreciable role in structuring bat communities. Spatially-structured landscape characteristics explained 84% of the variation in functional or phylogenetic dispersion, and the unique effects of landscape characteristics significantly explained 14% of the variation in species composition. Furthermore, variation in bat community structure was primarily due to differences in dispersion of species within functional or phylogenetic space along the gradient, rather than due to differences in functional or phylogenetic composition. Discussion Variation among bat communities was related to environmental mechanisms, especially niche-based (i.e., environmental) processes, rather than spatial mechanisms. High variation in functional or phylogenetic dispersion, as opposed to functional or phylogenetic composition, suggests that loss or gain of niche space is driving the progressive loss or gain of species with particular traits from communities along the human-modified gradient. Thus, environmental characteristics associated with landscape structure influence functional or phylogenetic aspects of bat communities by effectively altering the ways in which species partition niche space. PMID:27761338
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Sheth, Seema N; Angert, Amy L
2014-10-01
The geographic ranges of closely related species can vary dramatically, yet we do not fully grasp the mechanisms underlying such variation. The niche breadth hypothesis posits that species that have evolved broad environmental tolerances can achieve larger geographic ranges than species with narrow environmental tolerances. In turn, plasticity and genetic variation in ecologically important traits and adaptation to environmentally variable areas can facilitate the evolution of broad environmental tolerance. We used five pairs of western North American monkeyflowers to experimentally test these ideas by quantifying performance across eight temperature regimes. In four species pairs, species with broader thermal tolerances had larger geographic ranges, supporting the niche breadth hypothesis. As predicted, species with broader thermal tolerances also had more within-population genetic variation in thermal reaction norms and experienced greater thermal variation across their geographic ranges than species with narrow thermal tolerances. Species with narrow thermal tolerance may be particularly vulnerable to changing climatic conditions due to lack of plasticity and insufficient genetic variation to respond to novel selection pressures. Conversely, species experiencing high variation in temperature across their ranges may be buffered against extinction due to climatic changes because they have evolved tolerance to a broad range of temperatures. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
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Brauer, Chris J; Unmack, Peter J; Beheregaray, Luciano B
2017-12-01
Understanding whether small populations with low genetic diversity can respond to rapid environmental change via phenotypic plasticity is an outstanding research question in biology. RNA sequencing (RNA-seq) has recently provided the opportunity to examine variation in gene expression, a surrogate for phenotypic variation, in nonmodel species. We used a comparative RNA-seq approach to assess expression variation within and among adaptively divergent populations of a threatened freshwater fish, Nannoperca australis, found across a steep hydroclimatic gradient in the Murray-Darling Basin, Australia. These populations evolved under contrasting selective environments (e.g., dry/hot lowland; wet/cold upland) and represent opposite ends of the species' spectrum of genetic diversity and population size. We tested the hypothesis that environmental variation among isolated populations has driven the evolution of divergent expression at ecologically important genes using differential expression (DE) analysis and an anova-based comparative phylogenetic expression variance and evolution model framework based on 27,425 de novo assembled transcripts. Additionally, we tested whether gene expression variance within populations was correlated with levels of standing genetic diversity. We identified 290 DE candidate transcripts, 33 transcripts with evidence for high expression plasticity, and 50 candidates for divergent selection on gene expression after accounting for phylogenetic structure. Variance in gene expression appeared unrelated to levels of genetic diversity. Functional annotation of the candidate transcripts revealed that variation in water quality is an important factor influencing expression variation for N. australis. Our findings suggest that gene expression variation can contribute to the evolutionary potential of small populations. © 2017 John Wiley & Sons Ltd.
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Yu, Xiao-Dong; Lü, Liang; Wang, Feng-Yan; Luo, Tian-Hong; Zou, Si-Si; Wang, Cheng-Bin; Song, Ting-Ting; Zhou, Hong-Zhang
2016-01-01
The aim of this paper is to increase understanding of the relative importance of the input of geographic and local environmental factors on richness and composition of epigaeic steppe beetles (Coleoptera: Carabidae and Tenebrionidae) along a geographic (longitudinal/precipitation) gradient in the Inner Mongolia grassland. Specifically, we evaluate the associations of environmental variables representing climate and environmental heterogeneity with beetle assemblages. Beetles were sampled using pitfall traps at 25 sites scattered across the full geographic extent of the study biome in 2011-2012. We used variance partitioning techniques and multi-model selection based on the Akaike information criterion to assess the relative importance of the spatial and environmental variables on beetle assemblages. Species richness and abundance showed unimodal patterns along the geographic gradient. Together with space, climate variables associated with precipitation, water-energy balance and harshness of climate had strong explanatory power in richness pattern. Abundance pattern showed strongest association with variation in temperature and environmental heterogeneity. Climatic factors associated with temperature and precipitation variables and the interaction between climate with space were able to explain a substantial amount of variation in community structure. In addition, the turnover of species increased significantly as geographic distances increased. We confirmed that spatial and local environmental factors worked together to shape epigaeic beetle communities along the geographic gradient in the Inner Mongolia grassland. Moreover, the climate features, especially precipitation, water-energy balance and temperature, and the interaction between climate with space and environmental heterogeneity appeared to play important roles on controlling richness and abundance, and species compositions of epigaeic beetles.
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Fadda, Daniela; Scalas, L Francesca; Meleddu, Mauro
2015-08-01
This study examined self-esteem as mediator in the relations of personal (extraversion, neuroticism) and environmental (maternal, paternal, peer-relationships) variables with domains of positive psychological functioning (PPF) in adolescence (Satisfaction with life, Mastery, Vigor, Social Interest, Social Cheerfulness). We compared one-sided and multidimensional models using a sample of 1193 high school students (592 males and 601 females). We examined variations in adolescent PPF as a function of parenting styles via independent examination of maternal and paternal bonding. Results supported the multidimensional models, which indicated direct effects of personality traits, maternal care and peer relationships, as well as indirect effects, mediated by self-esteem, of all predictors on most PPF dimensions. Overall, our study provided a broader picture of personal and environmental predictors on different dimensions of PPF, which supported the mediating role of self-esteem and emphasized the importance of considering multidimensional models to characterize PPF in adolescents. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
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Nelson, Kurt; James, Scott C.; Roberts, Jesse D.; ...
2017-06-05
A modelling framework identifies deployment locations for current-energy-capture devices that maximise power output while minimising potential environmental impacts. The framework, based on the Environmental Fluid Dynamics Code, can incorporate site-specific environmental constraints. Over a 29-day period, energy outputs from three array layouts were estimated for: (1) the preliminary configuration (baseline), (2) an updated configuration that accounted for environmental constraints, (3) and an improved configuration subject to no environmental constraints. Of these layouts, array placement that did not consider environmental constraints extracted the most energy from flow (4.38 MW-hr/day), 19% higher than output from the baseline configuration (3.69 MW-hr/day). Array placementmore » that considered environmental constraints removed 4.27 MW-hr/day of energy (16% more than baseline). In conclusion, this analysis framework accounts for bathymetry and flow-pattern variations that typical experimental studies cannot, demonstrating that it is a valuable tool for identifying improved array layouts for field deployments.« less
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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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Skinner, Michael K
2015-04-26
Environment has a critical role in the natural selection process for Darwinian evolution. The primary molecular component currently considered for neo-Darwinian evolution involves genetic alterations and random mutations that generate the phenotypic variation required for natural selection to act. The vast majority of environmental factors cannot directly alter DNA sequence. Epigenetic mechanisms directly regulate genetic processes and can be dramatically altered by environmental factors. Therefore, environmental epigenetics provides a molecular mechanism to directly alter phenotypic variation generationally. Lamarck proposed in 1802 the concept that environment can directly alter phenotype in a heritable manner. Environmental epigenetics and epigenetic transgenerational inheritance provide molecular mechanisms for this process. Therefore, environment can on a molecular level influence the phenotypic variation directly. The ability of environmental epigenetics to alter phenotypic and genotypic variation directly can significantly impact natural selection. Neo-Lamarckian concept can facilitate neo-Darwinian evolution. A unified theory of evolution is presented to describe the integration of environmental epigenetic and genetic aspects of evolution. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
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Zhang, Dan; Zhang, Qi; Qiu, Jiaming; Bai, Peng; Liang, Kang; Li, Xianghu
2018-10-01
Hydrological extremes are changing under the impacts of environmental change, i.e., climate variation and human activity, which can substantially influence ecosystems and the living environment of humans in affected region. This study investigates the impacts of environmental change on hydrological drought in the middle reaches of the Yangtze River in China based on hydrological modelling. Change points for streamflow into two major lakes and a reservoir in the study area were detected in the late 1980s using the Mann-Kendall test. Streamflow simulation by a water balance model was performed, and the resulting Kling-Gupta efficiency value was >0.90. Hydrological drought events were identified based on the simulated streamflow under different scenarios. The results show that the hydrological drought occurrence was increased by precipitation, whereas the drought peak value was increased by potential evapotranspiration. The impacts of precipitation and potential evapotranspiration on drought severity and duration varied in the study area. However, hydrological drought was intensified by the influence of human activity, which increased the severity, duration and peak value of droughts. The dominant factor for hydrological drought severity is precipitation, followed by potential evapotranspiration and human activity. The impacts of climate variation and human activity on drought severity are larger than on drought duration. In addition, environmental change is shown to have an "accumulation effect" on hydrological drought, demonstrating that the indirect impacts of environmental change on hydrological drought are much larger than the direct impacts on streamflow. This study improves our understanding of the responses of hydrological extremes to environmental change, which is useful for the management of water resources and the prediction of hydrological disasters. Copyright © 2018 Elsevier B.V. All rights reserved.
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Kevin R. Ford; Constance A. Harrington; J. Bradley St. Clair
2017-01-01
The phenology of diameter-growth cessation in trees will likely play a key role in mediating species and ecosystem responses to climate change. A common expectation is that warming will delay cessation, but the environmental and genetic influences on this process are poorly understood. We modeled the effects of temperature, photoperiod, and seed-source climate on...
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Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition
NASA Technical Reports Server (NTRS)
Lau, William K. M.; Waliser, Duane E.
2011-01-01
Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.
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NASA Astrophysics Data System (ADS)
Sabrekov, Aleksandr F.; Runkle, Benjamin R. K.; Glagolev, Mikhail V.; Terentieva, Irina E.; Stepanenko, Victor M.; Kotsyurbenko, Oleg R.; Maksyutov, Shamil S.; Pokrovsky, Oleg S.
2017-08-01
Small lakes represent an important source of atmospheric CH4 from northern wetlands. However, spatiotemporal variations in flux magnitudes and the lack of knowledge about their main environmental controls contribute large uncertainty into the global CH4 budget. In this study, we measured methane fluxes from small lakes using chambers and bubble traps. Field investigations were carried out in July-August 2014 within the West Siberian middle and southern taiga zones. The average and median of measured methane chamber fluxes were 0.32 and 0.30 mgCH4 m-2 h-1 for middle taiga lakes and 8.6 and 4.1 mgCH4 m-2 h-1 for southern taiga lakes, respectively. Pronounced flux variability was found during measurements on individual lakes, between individual lakes and between zones. To analyze these differences and the influences of environmental controls, we developed a new dynamic process-based model. It shows good performance with emission rates from the southern taiga lakes and poor performance for individual lakes in the middle taiga region. The model shows that, in addition to well-known controls such as temperature, pH and lake depth, there are significant variations in the maximal methane production potential between these climatic zones. In addition, the model shows that variations in gas-filled pore space in lake sediments are capable of controlling the total methane emissions from individual lakes. The CH4 emissions exhibited distinct zonal differences not only in absolute values but also in their probability density functions: the middle taiga lake fluxes were best described by a lognormal distribution while the southern taiga lakes followed a power-law distribution. The latter suggests applicability of self-organized criticality theory for methane emissions from the southern taiga zone, which could help to explain the strong variability within individual lakes.
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Pezaro, Nadav; Doody, J Sean; Thompson, Michael B
2017-08-01
Sex-determining mechanisms are broadly categorised as being based on either genetic or environmental factors. Vertebrate sex determination exhibits remarkable diversity but displays distinct phylogenetic patterns. While all eutherian mammals possess XY male heterogamety and female heterogamety (ZW) is ubiquitous in birds, poikilothermic vertebrates (fish, amphibians and reptiles) exhibit multiple genetic sex-determination (GSD) systems as well as environmental sex determination (ESD). Temperature is the factor controlling ESD in reptiles and temperature-dependent sex determination (TSD) in reptiles has become a focal point in the study of this phenomenon. Current patterns of climate change may cause detrimental skews in the population sex ratios of reptiles exhibiting TSD. Understanding the patterns of variation, both within and among populations and linking such patterns with the selection processes they are associated with, is the central challenge of research aimed at predicting the capacity of populations to adapt to novel conditions. Here we present a conceptual model that innovates by defining an individual reaction norm for sex determination as a range of incubation temperatures. By deconstructing individual reaction norms for TSD and revealing their underlying interacting elements, we offer a conceptual solution that explains how variation among individual reaction norms can be inferred from the pattern of population reaction norms. The model also links environmental variation with the different patterns of TSD and describes the processes from which they may arise. Specific climate scenarios are singled out as eco-evolutionary traps that may lead to demographic extinction or a transition to either male or female heterogametic GSD. We describe how the conceptual principles can be applied to interpret TSD data and to explain the adaptive capacity of TSD to climate change as well as its limits and the potential applications for conservation and management programs. © 2016 Cambridge Philosophical Society.
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Fowler, Mike S; Ruokolainen, Lasse
2013-01-01
The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.
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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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Doi, Hideyuki; Chang, Kwang-Hyeon; Nishibe, Yuichiro; Imai, Hiroyuki; Nakano, Shin-ichi
2013-01-01
The importance of analyzing the determinants of biodiversity and community composition by using multiple trophic levels is well recognized; however, relevant data are lacking. In the present study, we investigated variations in species diversity indices and community structures of the plankton taxonomic groups-zooplankton, rotifers, ciliates, and phytoplankton-under a range of local environmental factors in pond ecosystems. For each planktonic group, we estimated the species diversity index by using linear models and analyzed the community structure by using canonical correspondence analysis. We showed that the species diversity indices and community structures varied among the planktonic groups and according to local environmental factors. The observed lack of congruence among the planktonic groups may have been caused by niche competition between groups with similar trophic guilds or by weak trophic interactions. Our findings highlight the difficulty of predicting total biodiversity within a system, based upon a single taxonomic group. Thus, to conserve the biodiversity of an ecosystem, it is crucial to consider variations in species diversity indices and community structures of different taxonomic groups, under a range of local conditions.
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Natural and Unanticipated Modifiers of RNAi Activity in Caenorhabditis elegans
Asad, Nadeem; Aw, Wen Yih; Timmons, Lisa
2012-01-01
Organisms used as model genomics systems are maintained as isogenic strains, yet evidence of sequence differences between independently maintained wild-type stocks has been substantiated by whole-genome resequencing data and strain-specific phenotypes. Sequence differences may arise from replication errors, transposon mobilization, meiotic gene conversion, or environmental or chemical assault on the genome. Low frequency alleles or mutations with modest effects on phenotypes can contribute to natural variation, and it has proven possible for such sequences to become fixed by adapted evolutionary enrichment and identified by resequencing. Our objective was to identify and analyze single locus genetic defects leading to RNAi resistance in isogenic strains of Caenorhabditis elegans. In so doing, we uncovered a mutation that arose de novo in an existing strain, which initially frustrated our phenotypic analysis. We also report experimental, environmental, and genetic conditions that can complicate phenotypic analysis of RNAi pathway defects. These observations highlight the potential for unanticipated mutations, coupled with genetic and environmental phenomena, to enhance or suppress the effects of known mutations and cause variation between wild-type strains. PMID:23209671
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Epigenetic Influence of Stress and the Social Environment
Gudsnuk, Kathryn; Champagne, Frances A.
2012-01-01
Animal models of early-life stress and variation in social experience across the lifespan have contributed significantly to our understanding of the environmental regulation of the developing brain. Plasticity in neurobiological pathways regulating stress responsivity, cognition, and reproductive behavior is apparent during the prenatal period and continues into adulthood, suggesting a lifelong sensitivity to environmental cues. Recent evidence suggests that dynamic epigenetic changes—molecular modifications that alter gene expression without altering the underlying DNA sequence—account for this plasticity. In this review, we highlight studies of laboratory rodents that illustrate the association between the experience of prenatal stress, maternal separation, maternal care, abusive caregiving in infancy, juvenile social housing, and adult social stress and variation in DNA methylation and histone modification. Moreover, we discuss emerging evidence for the transgenerational impact of these experiences. These experimental paradigms have yielded insights into the potential role of epigenetic mechanisms in mediating the effects of the environment on human development and also indicate that consideration of the sensitivity of laboratory animals to environmental cues may be an important factor in predicting long-term health and welfare. PMID:23744967
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Random regression models using different functions to model milk flow in dairy cows.
Laureano, M M M; Bignardi, A B; El Faro, L; Cardoso, V L; Tonhati, H; Albuquerque, L G
2014-09-12
We analyzed 75,555 test-day milk flow records from 2175 primiparous Holstein cows that calved between 1997 and 2005. Milk flow was obtained by dividing the mean milk yield (kg) of the 3 daily milking by the total milking time (min) and was expressed as kg/min. Milk flow was grouped into 43 weekly classes. The analyses were performed using a single-trait Random Regression Models that included direct additive genetic, permanent environmental, and residual random effects. In addition, the contemporary group and linear and quadratic effects of cow age at calving were included as fixed effects. Fourth-order orthogonal Legendre polynomial of days in milk was used to model the mean trend in milk flow. The additive genetic and permanent environmental covariance functions were estimated using random regression Legendre polynomials and B-spline functions of days in milk. The model using a third-order Legendre polynomial for additive genetic effects and a sixth-order polynomial for permanent environmental effects, which contained 7 residual classes, proved to be the most adequate to describe variations in milk flow, and was also the most parsimonious. The heritability in milk flow estimated by the most parsimonious model was of moderate to high magnitude.
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Walker, Anthony P; Quaife, Tristan; van Bodegom, Peter M; De Kauwe, Martin G; Keenan, Trevor F; Joiner, Joanna; Lomas, Mark R; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan; Woodward, F Ian
2017-09-01
The maximum photosynthetic carboxylation rate (V cmax ) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr -1 , 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.
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NASA Technical Reports Server (NTRS)
Walker, Anthony P.; Quaife, Tristan; Van Bodegom, Peter M.; De Kauwe, Martin G.; Keenan, Trevor F.; Joiner, Joanna; Lomas, Mark R.; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan;
2017-01-01
The maximum photosynthetic carboxylation rate (V (sub cmax)) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V(sub cmax) distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 petagrams of Carbon (PgC) per year, 65 percent of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27percent coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r equals 0.85-0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V(sub cmax) variation in the field, particularly in northern latitudes.
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Robinson, Joshua R
2017-05-01
Our knowledge of the Pleistocene environments of Africa consists primarily of data at a scale too coarse to capture the full habitat variation important to hominins 'on the ground.' These environments are complex, highly variable, and poorly understood. As such, data from individual sites are a needed addition to our current paleoenvironmental reconstructions. This study offers a site-based approach focusing on stable isotope analyses of fossil faunal tooth enamel from three archaeological sites in tropical Africa. Carbon and oxygen stable isotope data are reported from the sites of Porc Epic, Ethiopia, Lukenya Hill, Kenya, and Kalemba Rockshelter, Zambia. Stable isotope data from tooth enamel are used to measure two environmental variables: (1) aridity based on oxygen isotope composition and (2) dietary reconstructions of fossil ungulates based on the relative proportions of C 3 browse and C 4 graze in the diet. These data allow for a preliminary assessment of existing models that attempt to explain the behavioral and technological variation characteristic of the transition between the Middle and Later Stone Ages. Results indicate spatial and temporal variation in aridity and phytogeography in tropical Africa during the Pleistocene, suggesting that no single model is likely to provide an explanation for the transition at all sites across Africa. Copyright © 2017 Elsevier Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Feng, Maoyuan; Liu, Pan; Guo, Shenglian; Shi, Liangsheng; Deng, Chao; Ming, Bo
2017-08-01
Operating rules have been used widely to decide reservoir operations because of their capacity for coping with uncertain inflow. However, stationary operating rules lack adaptability; thus, under changing environmental conditions, they cause inefficient reservoir operation. This paper derives adaptive operating rules based on time-varying parameters generated using the ensemble Kalman filter (EnKF). A deterministic optimization model is established to obtain optimal water releases, which are further taken as observations of the reservoir simulation model. The EnKF is formulated to update the operating rules sequentially, providing a series of time-varying parameters. To identify the index that dominates the variations of the operating rules, three hydrologic factors are selected: the reservoir inflow, ratio of future inflow to current available water, and available water. Finally, adaptive operating rules are derived by fitting the time-varying parameters with the identified dominant hydrologic factor. China's Three Gorges Reservoir was selected as a case study. Results show that (1) the EnKF has the capability of capturing the variations of the operating rules, (2) reservoir inflow is the factor that dominates the variations of the operating rules, and (3) the derived adaptive operating rules are effective in improving hydropower benefits compared with stationary operating rules. The insightful findings of this study could be used to help adapt reservoir operations to mitigate the effects of changing environmental conditions.
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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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Linear mixed model for heritability estimation that explicitly addresses environmental variation.
Heckerman, David; Gurdasani, Deepti; Kadie, Carl; Pomilla, Cristina; Carstensen, Tommy; Martin, Hilary; Ekoru, Kenneth; Nsubuga, Rebecca N; Ssenyomo, Gerald; Kamali, Anatoli; Kaleebu, Pontiano; Widmer, Christian; Sandhu, Manjinder S
2016-07-05
The linear mixed model (LMM) is now routinely used to estimate heritability. Unfortunately, as we demonstrate, LMM estimates of heritability can be inflated when using a standard model. To help reduce this inflation, we used a more general LMM with two random effects-one based on genomic variants and one based on easily measured spatial location as a proxy for environmental effects. We investigated this approach with simulated data and with data from a Uganda cohort of 4,778 individuals for 34 phenotypes including anthropometric indices, blood factors, glycemic control, blood pressure, lipid tests, and liver function tests. For the genomic random effect, we used identity-by-descent estimates from accurately phased genome-wide data. For the environmental random effect, we constructed a covariance matrix based on a Gaussian radial basis function. Across the simulated and Ugandan data, narrow-sense heritability estimates were lower using the more general model. Thus, our approach addresses, in part, the issue of "missing heritability" in the sense that much of the heritability previously thought to be missing was fictional. Software is available at https://github.com/MicrosoftGenomics/FaST-LMM.
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Scribner, Kim T.; Lowe, Winsor H.; Landguth, Erin L.; Luikart, Gordon; Infante, Dana M.; Whelan, Gary; Muhlfeld, Clint C.
2015-01-01
Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management-relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance–response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.
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Interpreting estimates of heritability--a note on the twin decomposition.
Stenberg, Anders
2013-03-01
While most outcomes may in part be genetically mediated, quantifying genetic heritability is a different matter. To explore data on twins and decompose the variation is a classical method to determine whether variation in outcomes, e.g. IQ or schooling, originate from genetic endowments or environmental factors. Despite some criticism, the model is still widely used. The critique is generally related to how estimates of heritability may encompass environmental mediation. This aspect is sometimes left implicit by authors even though its relevance for the interpretation is potentially profound. This short note is an appeal for clarity from authors when interpreting the magnitude of heritability estimates. It is demonstrated how disregarding existing theoretical contributions can easily lead to unnecessary misinterpretations and/or controversies. The key arguments are relevant also for estimates based on data of adopted children or from modern molecular genetics research. Copyright © 2012 Elsevier B.V. All rights reserved.
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General-Purpose Genotype or How Epigenetics Extend the Flexibility of a Genotype
Massicotte, Rachel; Angers, Bernard
2012-01-01
This project aims at investigating the link between individual epigenetic variability (not related to genetic variability) and the variation of natural environmental conditions. We studied DNA methylation polymorphisms of individuals belonging to a single genetic lineage of the clonal diploid fish Chrosomus eos-neogaeus sampled in seven geographically distant lakes. In spite of a low number of informative fragments obtained from an MSAP analysis, individuals of a given lake are epigenetically similar, and methylation profiles allow the clustering of individuals in two distinct groups of populations among lakes. More importantly, we observed a significant pH variation that is consistent with the two epigenetic groups. It thus seems that the genotype studied has the potential to respond differentially via epigenetic modifications under variable environmental conditions, making epigenetic processes a relevant molecular mechanism contributing to phenotypic plasticity over variable environments in accordance with the GPG model. PMID:22567383
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NASA Astrophysics Data System (ADS)
Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio
2018-02-01
Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.
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Massatti, Rob; Knowles, L Lacey
2016-08-01
Deterministic processes may uniquely affect codistributed species' phylogeographic patterns such that discordant genetic variation among taxa is predicted. Yet, explicitly testing expectations of genomic discordance in a statistical framework remains challenging. Here, we construct spatially and temporally dynamic models to investigate the hypothesized effect of microhabitat preferences on the permeability of glaciated regions to gene flow in two closely related montane species. Utilizing environmental niche models from the Last Glacial Maximum and the present to inform demographic models of changes in habitat suitability over time, we evaluate the relative probabilities of two alternative models using approximate Bayesian computation (ABC) in which glaciated regions are either (i) permeable or (ii) a barrier to gene flow. Results based on the fit of the empirical data to data sets simulated using a spatially explicit coalescent under alternative models indicate that genomic data are consistent with predictions about the hypothesized role of microhabitat in generating discordant patterns of genetic variation among the taxa. Specifically, a model in which glaciated areas acted as a barrier was much more probable based on patterns of genomic variation in Carex nova, a wet-adapted species. However, in the dry-adapted Carex chalciolepis, the permeable model was more probable, although the difference in the support of the models was small. This work highlights how statistical inferences can be used to distinguish deterministic processes that are expected to result in discordant genomic patterns among species, including species-specific responses to climate change. © 2016 John Wiley & Sons Ltd.
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Briley, Daniel A.; Tucker-Drob, Elliot M.
2017-01-01
The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681
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Rethinking "normal": The role of stochasticity in the phenology of a synchronously breeding seabird.
Youngflesh, Casey; Jenouvrier, Stephanie; Hinke, Jefferson T; DuBois, Lauren; St Leger, Judy; Trivelpiece, Wayne Z; Trivelpiece, Susan G; Lynch, Heather J
2018-05-01
Phenological changes have been observed in a variety of systems over the past century. There is concern that, as a consequence, ecological interactions are becoming increasingly mismatched in time, with negative consequences for ecological function. Significant spatial heterogeneity (inter-site) and temporal variability (inter-annual) can make it difficult to separate intrinsic, extrinsic and stochastic drivers of phenological variability. The goal of this study was to understand the timing and variability in breeding phenology of Adélie penguins under fixed environmental conditions and to use those data to identify a "null model" appropriate for disentangling the sources of variation in wild populations. Data on clutch initiation were collected from both wild and captive populations of Adélie penguins. Clutch initiation in the captive population was modelled as a function of year, individual and age to better understand phenological patterns observed in the wild population. Captive populations displayed as much inter-annual variability in breeding phenology as wild populations, suggesting that variability in breeding phenology is the norm and thus may be an unreliable indicator of environmental forcing. The distribution of clutch initiation dates was found to be moderately asymmetric (right skewed) both in the wild and in captivity, consistent with the pattern expected under social facilitation. The role of stochasticity in phenological processes has heretofore been largely ignored. However, these results suggest that inter-annual variability in breeding phenology can arise independent of any environmental or demographic drivers and that synchronous breeding can enhance inherent stochasticity. This complicates efforts to relate phenological variation to environmental variability in the wild. Accordingly, we must be careful to consider random forcing in phenological processes, lest we fit models to data dominated by random noise. This is particularly true for colonial species where breeding synchrony may outweigh each individual's effort to time breeding with optimal environmental conditions. Our study highlights the importance of identifying appropriate null models for studying phenology. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
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Caribbean coral growth influenced by anthropogenic aerosol emissions
NASA Astrophysics Data System (ADS)
Kwiatkowski, Lester; Cox, Peter M.; Economou, Theo; Halloran, Paul R.; Mumby, Peter J.; Booth, Ben B. B.; Carilli, Jessica; Guzman, Hector M.
2013-05-01
Coral growth rates are highly dependent on environmental variables such as sea surface temperature and solar irradiance. Multi-decadal variability in coral growth rates has been documented throughout the Caribbean over the past 150-200 years, and linked to variations in Atlantic sea surface temperatures. Multi-decadal variability in sea surface temperatures in the North Atlantic, in turn, has been linked to volcanic and anthropogenic aerosol forcing. Here, we examine the drivers of changes in coral growth rates in the western Caribbean between 1880 and 2000, using previously published coral growth chronologies from two sites in the region, and a numerical model. Changes in coral growth rates over this period coincided with variations in sea surface temperature and incoming short-wave radiation. Our model simulations show that variations in the concentration of anthropogenic aerosols caused variations in sea surface temperature and incoming radiation in the second half of the twentieth century. Before this, variations in volcanic aerosols may have played a more important role. With the exception of extreme mass bleaching events, we suggest that neither climate change from greenhouse-gas emissions nor ocean acidification is necessarily the driver of multi-decadal variations in growth rates at some Caribbean locations. Rather, the cause may be regional climate change due to volcanic and anthropogenic aerosol emissions.
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NASA Technical Reports Server (NTRS)
Patel, Bhogila M.; Hoge, Peter A.; Nagpal, Vinod K.; Hojnicki, Jeffrey S.; Rusick, Jeffrey J.
2004-01-01
This paper describes the methods employed to apply probabilistic modeling techniques to the International Space Station (ISS) power system. These techniques were used to quantify the probabilistic variation in the power output, also called the response variable, due to variations (uncertainties) associated with knowledge of the influencing factors called the random variables. These uncertainties can be due to unknown environmental conditions, variation in the performance of electrical power system components or sensor tolerances. Uncertainties in these variables, cause corresponding variations in the power output, but the magnitude of that effect varies with the ISS operating conditions, e.g. whether or not the solar panels are actively tracking the sun. Therefore, it is important to quantify the influence of these uncertainties on the power output for optimizing the power available for experiments.
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de Mendoza, Guillermo; Ventura, Marc; Catalan, Jordi
2015-07-01
Aiming to elucidate whether large-scale dispersal factors or environmental species sorting prevail in determining patterns of Trichoptera species composition in mountain lakes, we analyzed the distribution and assembly of the most common Trichoptera (Plectrocnemia laetabilis, Polycentropus flavomaculatus, Drusus rectus, Annitella pyrenaea, and Mystacides azurea) in the mountain lakes of the Pyrenees (Spain, France, Andorra) based on a survey of 82 lakes covering the geographical and environmental extremes of the lake district. Spatial autocorrelation in species composition was determined using Moran's eigenvector maps (MEM). Redundancy analysis (RDA) was applied to explore the influence of MEM variables and in-lake, and catchment environmental variables on Trichoptera assemblages. Variance partitioning analysis (partial RDA) revealed the fraction of species composition variation that could be attributed uniquely to either environmental variability or MEM variables. Finally, the distribution of individual species was analyzed in relation to specific environmental factors using binomial generalized linear models (GLM). Trichoptera assemblages showed spatial structure. However, the most relevant environmental variables in the RDA (i.e., temperature and woody vegetation in-lake catchments) were also related with spatial variables (i.e., altitude and longitude). Partial RDA revealed that the fraction of variation in species composition that was uniquely explained by environmental variability was larger than that uniquely explained by MEM variables. GLM results showed that the distribution of species with longitudinal bias is related to specific environmental factors with geographical trend. The environmental dependence found agrees with the particular traits of each species. We conclude that Trichoptera species distribution and composition in the lakes of the Pyrenees are governed predominantly by local environmental factors, rather than by dispersal constraints. For boreal lakes, with similar environmental conditions, a strong role of dispersal capacity has been suggested. Further investigation should address the role of spatial scaling, namely absolute geographical distances constraining dispersal and steepness of environmental gradients at short distances.
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de Mendoza, Guillermo; Ventura, Marc; Catalan, Jordi
2015-01-01
Aiming to elucidate whether large-scale dispersal factors or environmental species sorting prevail in determining patterns of Trichoptera species composition in mountain lakes, we analyzed the distribution and assembly of the most common Trichoptera (Plectrocnemia laetabilis, Polycentropus flavomaculatus, Drusus rectus, Annitella pyrenaea, and Mystacides azurea) in the mountain lakes of the Pyrenees (Spain, France, Andorra) based on a survey of 82 lakes covering the geographical and environmental extremes of the lake district. Spatial autocorrelation in species composition was determined using Moran’s eigenvector maps (MEM). Redundancy analysis (RDA) was applied to explore the influence of MEM variables and in-lake, and catchment environmental variables on Trichoptera assemblages. Variance partitioning analysis (partial RDA) revealed the fraction of species composition variation that could be attributed uniquely to either environmental variability or MEM variables. Finally, the distribution of individual species was analyzed in relation to specific environmental factors using binomial generalized linear models (GLM). Trichoptera assemblages showed spatial structure. However, the most relevant environmental variables in the RDA (i.e., temperature and woody vegetation in-lake catchments) were also related with spatial variables (i.e., altitude and longitude). Partial RDA revealed that the fraction of variation in species composition that was uniquely explained by environmental variability was larger than that uniquely explained by MEM variables. GLM results showed that the distribution of species with longitudinal bias is related to specific environmental factors with geographical trend. The environmental dependence found agrees with the particular traits of each species. We conclude that Trichoptera species distribution and composition in the lakes of the Pyrenees are governed predominantly by local environmental factors, rather than by dispersal constraints. For boreal lakes, with similar environmental conditions, a strong role of dispersal capacity has been suggested. Further investigation should address the role of spatial scaling, namely absolute geographical distances constraining dispersal and steepness of environmental gradients at short distances. PMID:26257867
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Inheritance of Vertebral Number in the Three-Spined Stickleback (Gasterosteus aculeatus)
Alho, Jussi S.; Leinonen, Tuomas; Merilä, Juha
2011-01-01
Intraspecific variation in the number of vertebrae is taxonomically widespread, and both genetic and environmental factors are known to contribute to this variation. However, the relative importance of genetic versus environmental influences on variation in vertebral number has seldom been investigated with study designs that minimize bias due to non-additive genetic and maternal influences. We used a paternal half-sib design and animal model analysis to estimate heritability and causal components of variance in vertebral number in three-spined sticklebacks (Gasterosteus aculeatus). We found that both the number of vertebrae (h2 = 0.36) and body size (h2 = 0.42) were moderately heritable, whereas the influence of maternal effects was estimated to be negligible. While the number of vertebrae had a positive effect on body size, no evidence for a genetic correlation between body size and vertebral number was detected. However, there was a significant positive environmental correlation between these two traits. Our results support the generalization-in accordance with results from a review of heritability estimates for vertebral number in fish, reptiles and mammals-that the number of vertebrae appears to be moderately to highly heritable in a wide array of species. In the case of the three-spined stickleback, independent evolution of body size and number of vertebrae should be possible given the low genetic correlation between the two traits. PMID:21603609
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Scharsack, Jörn P; Franke, Frederik; Erin, Noémi I; Kuske, Andra; Büscher, Janine; Stolz, Hendrik; Samonte, Irene E; Kurtz, Joachim; Kalbe, Martin
2016-08-01
Recent research provides accumulating evidence that the evolutionary dynamics of host-parasite adaptations strongly depend on environmental variation. In this context, the three-spined stickleback (Gasterosteus aculeatus) has become an important research model since it is distributed all over the northern hemisphere and lives in very different habitat types, ranging from marine to freshwater, were it is exposed to a huge diversity of parasites. While a majority of studies start from explorations of sticklebacks in the wild, only relatively few investigations have continued under laboratory conditions. Accordingly, it has often been described that sticklebacks differ in parasite burden between habitats, but the underlying co-evolutionary trajectories are often not well understood. With the present review, we give an overview of the most striking examples of stickleback-parasite-environment interactions discovered in the wild and discuss two model parasites which have received some attention in laboratory studies: the eye fluke Diplostomum pseudospathacaeum, for which host fish show habitat-specific levels of resistance, and the tapeworm Schistocephalus solidus, which manipulates immunity and behavior of its stickleback host to its advantage. Finally, we will concentrate on an important environmental variable, namely temperature, which has prominent effects on the activity of the immune system of ectothermic hosts and on parasite growth rates. Copyright © 2016 The Authors. Published by Elsevier GmbH.. All rights reserved.
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Galloway, Aaron W. E.; Winder, Monika
2015-01-01
Essential fatty acids (EFA), which are primarily generated by phytoplankton, limit growth and reproduction in diverse heterotrophs. The biochemical composition of phytoplankton is well-known to be governed both by phylogeny and environmental conditions. Nutrients, light, salinity, and temperature all affect both phytoplankton growth and fatty acid composition. However, the relative importance of taxonomy and environment on algal fatty acid content has yet to be comparatively quantified, thus inhibiting predictions of changes to phytoplankton food quality in response to global environmental change. We compiled 1145 published marine and freshwater phytoplankton fatty acid profiles, consisting of 208 species from six major taxonomic groups, cultured in a wide range of environmental conditions, and used a multivariate distance-based linear model to quantify the total variation explained by each variable. Our results show that taxonomic group accounts for 3-4 times more variation in phytoplankton fatty acids than the most important growth condition variables. The results underscore that environmental conditions clearly affect phytoplankton fatty acid profiles, but also show that conditions account for relatively low variation compared to phylogeny. This suggests that the underlying mechanism determining basal food quality in aquatic habitats is primarily phytoplankton community composition, and allows for prediction of environmental-scale EFA dynamics based on phytoplankton community data. We used the compiled dataset to calculate seasonal dynamics of long-chain EFA (LCEFA; ≥C20 ɷ-3 and ɷ-6 polyunsaturated fatty acid) concentrations and ɷ-3:ɷ-6 EFA ratios in Lake Washington using a multi-decadal phytoplankton community time series. These analyses quantify temporal dynamics of algal-derived LCEFA and food quality in a freshwater ecosystem that has undergone large community changes as a result of shifting resource management practices, highlighting diatoms, cryptophytes and dinoflagellates as key sources of LCEFA. Moreover, the analyses indicate that future shifts towards cyanobacteria-dominated communities will result in lower LCEFA content in aquatic ecosystems. PMID:26076015
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2011-09-30
energy metabolism, suppression of immune and inflammatory reactions and inhibition of bone and muscle growth. Studies of both captive and free- ranging...Anemia, hypothyroidism and immune suppression associated with polychlorinated biphenyl exposure in bottlenose dolphins (Tursiops truncatus). Proc R
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Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors
Atul Jain; Xiaojuan Yang; Haroon Kheshgi; A. David McGuire; Wilfred Post; David Kicklighter
2009-01-01
Nitrogen cycle dynamics have the capacity to attenuate the magnitude of global terrestrial carbon sinks and sources driven by CO2 fertilization and changes in climate. In this study, two versions of the terrestrial carbon and nitrogen cycle components of the Integrated Science Assessment Model (ISAM) are used to evaluate how variation in nitrogen...
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On the variability of alligator sex ratios
Nichols, J.D.; Chabreck, R.H.
1980-01-01
Samples of alligators from wild and 'farm' populations exhibited disproportionate sex ratios. Males predominated among young alligators from wild populations, whereas females were much more abundant than males in the farm population, where resources were superabundant. These results and other considerations lead us to hypothesize that environmental factors influence sex determination in alligators. During favorable environmental conditions natural selection is expected to favor a preponderance of the sex whose individuals exhibit the greater environmentally associated variation in relative fitness. We hypothesize that environmentally associated variation in age at sexual maturity of females produces sufficient variation in relative fitness of females to result in selection for low sex ratios during periods of resource abundance.
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Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J
2011-07-01
Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.
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Global patterns and predictors of fish species richness in estuaries.
Vasconcelos, Rita P; Henriques, Sofia; França, Susana; Pasquaud, Stéphanie; Cardoso, Inês; Laborde, Marina; Cabral, Henrique N
2015-09-01
1. Knowledge of global patterns of biodiversity and regulating variables is indispensable to develop predictive models. 2. The present study used predictive modelling approaches to investigate hypotheses that explain the variation in fish species richness between estuaries over a worldwide spatial extent. Ultimately, such models will allow assessment of future changes in ecosystem structure and function as a result of environmental changes. 3. A comprehensive worldwide data base was compiled of the fish assemblage composition and environmental characteristics of estuaries. Generalized Linear Models were used to quantify how variation in species richness among estuaries is related to historical events, energy dynamics and ecosystem characteristics, while controlling for sampling effects. 4. At the global extent, species richness differed among marine biogeographic realms and continents and increased with mean sea surface temperature, terrestrial net primary productivity and the stability of connectivity with a marine ecosystem (open vs. temporarily open estuaries). At a smaller extent (within a marine biogeographic realm or continent), other characteristics were also important in predicting variation in species richness, with species richness increasing with estuary area and continental shelf width. 5. The results suggest that species richness in an estuary is defined by predictors that are spatially hierarchical. Over the largest spatial extents, species richness is influenced by the broader distributions and habitat use patterns of marine and freshwater species that can colonize estuaries, which are in turn governed by history contingency, energy dynamics and productivity variables. Species richness is also influenced by more regional and local parameters that can further affect the process of community colonization in an estuary including the connectivity of the estuary with the adjacent marine habitat, and, over smaller spatial extents, the size of these habitats. In summary, patterns of species richness in estuaries across large spatial extents seem to reflect from global to local processes acting on community colonization. The importance of considering spatial extent, sampling effects and of combining history and contemporary environmental characteristics when exploring biodiversity is highlighted. © 2015 The Authors. Journal of Animal Ecology published by John Wiley & Sons on behalf of the British Ecological Society.
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Neeman, Noga; Spotila, James R; O'Connor, Michael P
2015-09-07
Variation in the yearly number of sea turtles nesting at rookeries can interfere with population estimates and obscure real population dynamics. Previous theoretical models suggested that this variation in nesting numbers may be driven by changes in resources at the foraging grounds. We developed a physiologically-based model that uses temperatures at foraging sites to predict foraging conditions, resource accumulation, remigration probabilities, and, ultimately, nesting numbers for a stable population of sea turtles. We used this model to explore several scenarios of temperature variation at the foraging grounds, including one-year perturbations and cyclical temperature oscillations. We found that thermally driven resource variation can indeed synchronize nesting in groups of turtles, creating cohorts, but that these cohorts tend to break down over 5-10 years unless regenerated by environmental conditions. Cohorts were broken down faster at lower temperatures. One-year perturbations of low temperature had a synchronizing effect on nesting the following year, while high temperature perturbations tended to delay nesting in a less synchronized way. Cyclical temperatures lead to cyclical responses both in nesting numbers and remigration intervals, with the amplitude and lag of the response depending on the duration of the cycle. Overall, model behavior is consistent with observations at nesting beaches. Future work should focus on refining the model to fit particular nesting populations and testing further whether or not it may be used to predict observed nesting numbers and remigration intervals. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Tenailleau, Quentin M; Bernard, Nadine; Pujol, Sophie; Houot, Hélène; Joly, Daniel; Mauny, Frédéric
2015-01-01
Environmental epidemiological studies rely on the quantification of the exposure level in a surface defined as the subject's exposure area. For residential exposure, this area is often the subject's neighborhood. However, the variability of the size and nature of the neighborhoods makes comparison of the findings across studies difficult. This article examines the impact of the neighborhood's definition on environmental noise exposure levels obtained from four commonly used sampling techniques: address point, façade, buffers, and official zoning. A high-definition noise model, built on a middle-sized French city, has been used to estimate LAeq,24 h exposure in the vicinity of 10,825 residential buildings. Twelve noise exposure indicators have been used to assess inhabitants' exposure. Influence of urban environmental factors was analyzed using multilevel modeling. When the sampled area increases, the average exposure increases (+3.9 dB), whereas the SD decreases (-1.6 dB) (P<0.01). Most of the indicators differ statistically. When comparing indicators from the 50-m and 400-m radius buffers, the assigned LAeq,24 h level varies across buildings from -9.4 to +22.3 dB. This variation is influenced by urban environmental characteristics (P<0.01). On the basis of this study's findings, sampling technique, neighborhood size, and environmental composition should be carefully considered in further exposure studies.
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Field heritability of a plant adaptation to fire in heterogeneous landscapes.
Castellanos, M C; González-Martínez, S C; Pausas, J G
2015-11-01
The strong association observed between fire regimes and variation in plant adaptations to fire suggests a rapid response to fire as an agent of selection. It also suggests that fire-related traits are heritable, a precondition for evolutionary change. One example is serotiny, the accumulation of seeds in unopened fruits or cones until the next fire, an important strategy for plant population persistence in fire-prone ecosystems. Here, we evaluate the potential of this trait to respond to natural selection in its natural setting. For this, we use a SNP marker approach to estimate genetic variance and heritability of serotiny directly in the field for two Mediterranean pine species. Study populations were large and heterogeneous in climatic conditions and fire regime. We first estimated the realized relatedness among trees from genotypes, and then partitioned the phenotypic variance in serotiny using Bayesian animal models that incorporated environmental predictors. As expected, field heritability was smaller (around 0.10 for both species) than previous estimates under common garden conditions (0.20). An estimate on a subset of stands with more homogeneous environmental conditions was not different from that in the complete set of stands, suggesting that our models correctly captured the environmental variation at the spatial scale of the study. Our results highlight the importance of measuring quantitative genetic parameters in natural populations, where environmental heterogeneity is a critical aspect. The heritability of serotiny, although not high, combined with high phenotypic variance within populations, confirms the potential of this fire-related trait for evolutionary change in the wild. © 2015 John Wiley & Sons Ltd.
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Human metabolic profiles are stably controlled by genetic and environmental variation
Nicholson, George; Rantalainen, Mattias; Maher, Anthony D; Li, Jia V; Malmodin, Daniel; Ahmadi, Kourosh R; Faber, Johan H; Hallgrímsdóttir, Ingileif B; Barrett, Amy; Toft, Henrik; Krestyaninova, Maria; Viksna, Juris; Neogi, Sudeshna Guha; Dumas, Marc-Emmanuel; Sarkans, Ugis; The MolPAGE Consortium; Silverman, Bernard W; Donnelly, Peter; Nicholson, Jeremy K; Allen, Maxine; Zondervan, Krina T; Lindon, John C; Spector, Tim D; McCarthy, Mark I; Holmes, Elaine; Baunsgaard, Dorrit; Holmes, Chris C
2011-01-01
1H Nuclear Magnetic Resonance spectroscopy (1H NMR) is increasingly used to measure metabolite concentrations in sets of biological samples for top-down systems biology and molecular epidemiology. For such purposes, knowledge of the sources of human variation in metabolite concentrations is valuable, but currently sparse. We conducted and analysed a study to create such a resource. In our unique design, identical and non-identical twin pairs donated plasma and urine samples longitudinally. We acquired 1H NMR spectra on the samples, and statistically decomposed variation in metabolite concentration into familial (genetic and common-environmental), individual-environmental, and longitudinally unstable components. We estimate that stable variation, comprising familial and individual-environmental factors, accounts on average for 60% (plasma) and 47% (urine) of biological variation in 1H NMR-detectable metabolite concentrations. Clinically predictive metabolic variation is likely nested within this stable component, so our results have implications for the effective design of biomarker-discovery studies. We provide a power-calculation method which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect 1H NMR-based biomarkers quantifying predisposition to disease. PMID:21878913
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Heino, Jani; Soininen, Janne; Alahuhta, Janne; Lappalainen, Jyrki; Virtanen, Risto
2017-01-01
Metacommunity patterns and underlying processes in aquatic organisms have typically been studied within a drainage basin. We examined variation in the composition of six freshwater organismal groups across various drainage basins in Finland. We first modelled spatial structures within each drainage basin using Moran eigenvector maps. Second, we partitioned variation in community structure among three groups of predictors using constrained ordination: (1) local environmental variables, (2) spatial variables, and (3) dummy variable drainage basin identity. Third, we examined turnover and nestedness components of multiple-site beta diversity, and tested the best fit patterns of our datasets using the "elements of metacommunity structure" analysis. Our results showed that basin identity and local environmental variables were significant predictors of community structure, whereas within-basin spatial effects were typically negligible. In half of the organismal groups (diatoms, bryophytes, zooplankton), basin identity was a slightly better predictor of community structure than local environmental variables, whereas the opposite was true for the remaining three organismal groups (insects, macrophytes, fish). Both pure basin and local environmental fractions were, however, significant after accounting for the effects of the other predictor variable sets. All organismal groups exhibited high levels of beta diversity, which was mostly attributable to the turnover component. Our results showed consistent Clementsian-type metacommunity structures, suggesting that subgroups of species responded similarly to environmental factors or drainage basin limits. We conclude that aquatic communities across large scales are mostly determined by environmental and basin effects, which leads to high beta diversity and prevalence of Clementsian community types.
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Sources of Variation in Sweat Chloride Measurements in Cystic Fibrosis.
Collaco, Joseph M; Blackman, Scott M; Raraigh, Karen S; Corvol, Harriet; Rommens, Johanna M; Pace, Rhonda G; Boelle, Pierre-Yves; McGready, John; Sosnay, Patrick R; Strug, Lisa J; Knowles, Michael R; Cutting, Garry R
2016-12-01
Expanding the use of cystic fibrosis transmembrane conductance regulator (CFTR) potentiators and correctors for the treatment of cystic fibrosis (CF) requires precise and accurate biomarkers. Sweat chloride concentration provides an in vivo assessment of CFTR function, but it is unknown the degree to which CFTR mutations account for sweat chloride variation. To estimate potential sources of variation for sweat chloride measurements, including demographic factors, testing variability, recording biases, and CFTR genotype itself. A total of 2,639 sweat chloride measurements were obtained in 1,761 twins/siblings from the CF Twin-Sibling Study, French CF Modifier Gene Study, and Canadian Consortium for Genetic Studies. Variance component estimation was performed by nested mixed modeling. Across the tested CF population as a whole, CFTR gene mutations were found to be the primary determinant of sweat chloride variability (56.1% of variation) with contributions from variation over time (e.g., factors related to testing on different days; 13.8%), environmental factors (e.g., climate, family diet; 13.5%), other residual factors (e.g., test variability; 9.9%), and unique individual factors (e.g., modifier genes, unique exposures; 6.8%) (likelihood ratio test, P < 0.001). Twin analysis suggested that modifier genes did not play a significant role because the heritability estimate was negligible (H 2 = 0; 95% confidence interval, 0.0-0.35). For an individual with CF, variation in sweat chloride was primarily caused by variation over time (58.1%) with the remainder attributable to residual/random factors (41.9%). Variation in the CFTR gene is the predominant cause of sweat chloride variation; most of the non-CFTR variation is caused by testing variability and unique environmental factors. If test precision and accuracy can be improved, sweat chloride measurement could be a valuable biomarker for assessing response to therapies directed at mutant CFTR.
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Sources of Variation in Sweat Chloride Measurements in Cystic Fibrosis
Blackman, Scott M.; Raraigh, Karen S.; Corvol, Harriet; Rommens, Johanna M.; Pace, Rhonda G.; Boelle, Pierre-Yves; McGready, John; Sosnay, Patrick R.; Strug, Lisa J.; Knowles, Michael R.; Cutting, Garry R.
2016-01-01
Rationale: Expanding the use of cystic fibrosis transmembrane conductance regulator (CFTR) potentiators and correctors for the treatment of cystic fibrosis (CF) requires precise and accurate biomarkers. Sweat chloride concentration provides an in vivo assessment of CFTR function, but it is unknown the degree to which CFTR mutations account for sweat chloride variation. Objectives: To estimate potential sources of variation for sweat chloride measurements, including demographic factors, testing variability, recording biases, and CFTR genotype itself. Methods: A total of 2,639 sweat chloride measurements were obtained in 1,761 twins/siblings from the CF Twin-Sibling Study, French CF Modifier Gene Study, and Canadian Consortium for Genetic Studies. Variance component estimation was performed by nested mixed modeling. Measurements and Main Results: Across the tested CF population as a whole, CFTR gene mutations were found to be the primary determinant of sweat chloride variability (56.1% of variation) with contributions from variation over time (e.g., factors related to testing on different days; 13.8%), environmental factors (e.g., climate, family diet; 13.5%), other residual factors (e.g., test variability; 9.9%), and unique individual factors (e.g., modifier genes, unique exposures; 6.8%) (likelihood ratio test, P < 0.001). Twin analysis suggested that modifier genes did not play a significant role because the heritability estimate was negligible (H2 = 0; 95% confidence interval, 0.0–0.35). For an individual with CF, variation in sweat chloride was primarily caused by variation over time (58.1%) with the remainder attributable to residual/random factors (41.9%). Conclusions: Variation in the CFTR gene is the predominant cause of sweat chloride variation; most of the non-CFTR variation is caused by testing variability and unique environmental factors. If test precision and accuracy can be improved, sweat chloride measurement could be a valuable biomarker for assessing response to therapies directed at mutant CFTR. PMID:27258095
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Solar Cycle Variation and Application to the Space Radiation Environment
NASA Technical Reports Server (NTRS)
Wilson, John W.; Kim, Myung-Hee Y.; Shinn, Judy L.; Tai, Hsiang; Cucinotta, Francis A.; Badhwar, Gautam D.; Badavi, Francis F.; Atwell, William
1999-01-01
The interplanetary plasma and fields are affected by the degree of disturbance that is related to the number and types of sunspots in the solar surface. Sunspot observations were improved with the introduction of the telescope in the seventeenth century, allowing observations which cover many centuries. A single quantity (sunspot number) was defined by Wolf in 1848 that is now known to be well correlated with many space observable quantities and is used herein to represent variations caused in the space radiation environment. The resultant environmental models are intended for future aircraft and space-travel-related exposure estimates.
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Fu, Guifang; Dai, Xiaotian; Symanzik, Jürgen; Bushman, Shaun
2017-01-01
Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
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Coupled hydraulic and photosynthetic feedbacks on forest transpiration throughout the growing season
NASA Astrophysics Data System (ADS)
Mackay, D. S.; Ewers, B. E.
2007-12-01
Ecosystem models account for vegetative controls on water fluxes using environmental drivers and hydraulic and/or biochemical limits on canopy stomatal conductance (Gs), variations in space and time of leaf area index (L), and species or biome specific parameters. However, some parameters, such as maximum stomatal conductance or its reference proxy at vapor pressure deficit of 1 kPa (Gsref), may not be strictly time-independent suggesting as yet undefined mechanisms in the models. We developed a model of coupled canopy water and carbon exchange, which allowed us to examine photosynthetic and hydraulic feedbacks on Gsref spanning the whole growing season for several dominant tree species in wetland and upland positions that collectively account for most a 1600 square km region centered on the WLEF AmeriFlux tower in Wisconsin, USA. The model assimilated half-hourly sap flux and micrometeorological data to quantify and explain temporal variations in Gsref for trembling aspen, sugar maple, and red pine in upland sites, and speckled alder and white cedar in wetland sites. Results show (1) phenological effects on photosynthetic activity with feedback on Gsref in all species, and (2) lags of up to two months between maximum per unit leaf area photosynthetic rates for conifer versus deciduous species. These results show that for given environmental conditions canopy transpiration depends on both L and timing of biochemical activation, both of which have implications for regional ecosystem water cycling.
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Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model
NASA Technical Reports Server (NTRS)
Barata, Raquel A.; Drewry, Darren
2012-01-01
The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.
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Bernatchez, L
2016-12-01
The first goal of this paper was to overview modern approaches to local adaptation, with a focus on the use of population genomics data to detect signals of natural selection in fishes. Several mechanisms are discussed that may enhance the maintenance of genetic variation and evolutionary potential, which have been overlooked and should be considered in future theoretical development and predictive models: the prevalence of soft sweeps, polygenic basis of adaptation, balancing selection and transient polymorphisms, parallel evolution, as well as epigenetic variation. Research on fish population genomics has provided ample evidence for local adaptation at the genome level. Pervasive adaptive evolution, however, seems to almost never involve the fixation of beneficial alleles. Instead, adaptation apparently proceeds most commonly by soft sweeps entailing shifts in frequencies of alleles being shared between differentially adapted populations. One obvious factor contributing to the maintenance of standing genetic variation in the face of selective pressures is that adaptive phenotypic traits are most often highly polygenic, and consequently the response to selection should derive mostly from allelic co-variances among causative loci rather than pronounced allele frequency changes. Balancing selection in its various forms may also play an important role in maintaining adaptive genetic variation and the evolutionary potential of species to cope with environmental change. A large body of literature on fishes also shows that repeated evolution of adaptive phenotypes is a ubiquitous evolutionary phenomenon that seems to occur most often via different genetic solutions, further adding to the potential options of species to cope with a changing environment. Moreover, a paradox is emerging from recent fish studies whereby populations of highly reduced effective population sizes and impoverished genetic diversity can apparently retain their adaptive potential in some circumstances. Although more empirical support is needed, several recent studies suggest that epigenetic variation could account for this apparent paradox. Therefore, epigenetic variation should be fully integrated with considerations pertaining to role of soft sweeps, polygenic and balancing selection, as well as repeated adaptation involving different genetic basis towards improving models predicting the evolutionary potential of species to cope with a changing world. © 2016 The Fisheries Society of the British Isles.
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Temporal and spatial variation in pharmaceutical concentrations in an urban river system
Burns, Emily E.; Carter, Laura J.; Kolpin, Dana W.; Thomas-Oates, Jane; Boxall, Alistair B.A.
2018-01-01
Many studies have quantified pharmaceuticals in the environment, few however, have incorporated detailed temporal and spatial variability due to associated costs in terms of time and materials. Here, we target 33 physico-chemically diverse pharmaceuticals in a spatiotemporal exposure study into the occurrence of pharmaceuticals in the wastewater system and the Rivers Ouse and Foss (two diverse river systems) in the city of York, UK. Removal rates in two of the WWTPs sampled (a conventional activated sludge (CAS) and trickling filter plant) ranged from not eliminated (carbamazepine) to >99% (paracetamol). Data comparisons indicate that pharmaceutical exposures in river systems are highly variable regionally, in part due to variability in prescribing practices, hydrology, wastewater management, and urbanisation and that select annual median pharmaceutical concentrations observed in this study were higher than those previously observed in the European Union and Asia thus far. Significant spatial variability was found between all sites in both river systems, while seasonal variability was significant for 86% and 50% of compounds in the River Foss and Ouse, respectively. Seasonal variations in flow, in-stream attenuation, usage and septic effluent releases are suspected drivers behind some of the observed temporal exposure variability. When the data were used to evaluate a simple environmental exposure model for pharmaceuticals, mean ratios of predicted environmental concentrations (PECs), obtained using the model, to measured environmental concentrations (MECs) were 0.51 and 0.04 for the River Foss and River Ouse, respectively. Such PEC/MEC ratios indicate that the model underestimates actual concentrations in both river systems, but to a much greater extent in the larger River Ouse.
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NASA Astrophysics Data System (ADS)
Baracchini, Theo; King, Aaron A.; Bouma, Menno J.; Rodó, Xavier; Bertuzzo, Enrico; Pascual, Mercedes
2017-10-01
Seasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera's seasonality observed worldwide, provides a unique opportunity to gain insights on underlying environmental drivers. Here, we propose a mechanistic, rainfall-temperature driven, stochastic epidemiological model which explicitly accounts for the fluctuations of the aquatic reservoir, and analyze with this model the historical dataset of cholera mortality in the Bengal region. Parameters are inferred with a recently developed sequential Monte Carlo method for likelihood maximization in partially observed Markov processes. Results indicate that the hydrological regime is a major driver of the seasonal dynamics of cholera. Rainfall tends to buffer the propagation of the disease in wet regions due to the longer residence times of water in the environment and an associated dilution effect, whereas it enhances cholera resurgence in dry regions. Moreover, the dynamics of the environmental water reservoir determine whether the seasonality is unimodal or bimodal, as well as its phase relative to the monsoon. Thus, the full range of seasonal patterns can be explained based solely on the local variation of rainfall and temperature. Given the close connection between cholera seasonality and environmental conditions, a deeper understanding of the underlying mechanisms would allow the better management and planning of public health policies with respect to climate variability and climate change.
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Capra, Hervé; Plichard, Laura; Bergé, Julien; Pella, Hervé; Ovidio, Michaël; McNeil, Eric; Lamouroux, Nicolas
2017-02-01
Modeling individual fish habitat selection in highly variable environments such as hydropeaking rivers is required for guiding efficient management decisions. We analyzed fish microhabitat selection in the heterogeneous hydraulic and thermal conditions (modeled in two-dimensions) of a reach of the large hydropeaking Rhône River locally warmed by the cooling system of a nuclear power plant. We used modern fixed acoustic telemetry techniques to survey 18 fish individuals (five barbels, six catfishes, seven chubs) signaling their position every 3s over a three-month period. Fish habitat selection depended on combinations of current microhabitat hydraulics (e.g. velocity, depth), past microhabitat hydraulics (e.g. dewatering risk or maximum velocities during the past 15days) and to a lesser extent substrate and temperature. Mixed-effects habitat selection models indicated that individual effects were often stronger than specific effects. In the Rhône, fish individuals appear to memorize spatial and temporal environmental changes and to adopt a "least constraining" habitat selection. Avoiding fast-flowing midstream habitats, fish generally live along the banks in areas where the dewatering risk is high. When discharge decreases, however, they select higher velocities but avoid both dewatering areas and very fast-flowing midstream habitats. Although consistent with the available knowledge on static fish habitat selection, our quantitative results demonstrate temporal variations in habitat selection, depending on individual behavior and environmental history. Their generality could be further tested using comparative experiments in different environmental configurations. Copyright © 2016 Elsevier B.V. All rights reserved.
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Grace, J.B.; Guntenspergen, G.R.
1999-01-01
Here we propose that an important cause of variation in species density may be prior environmental conditions that continue to influence current patterns. In this paper we investigated the degree to which species density varies with location within the landscape, independent of contemporaneous environmental conditions. The area studied was a coastal marsh landscape subject to periodic storm events. To evaluate the impact of historical effects, it was assumed that the landscape position of a plot relative to the river's mouth ('distance from sea') and to the edge of a stream channel ('distance from shore') would correlate with the impact of prior storm events, an assumption supported by previous studies. To evaluate the importance of spatial location on species density, data were collected from five sites located at increasing distances from the river's mouth along the Middle Pearl River in Louisiana. At each site, plots were established systematically along transects perpendicular to the shoreline. For each of the 175 Plots, we measured elevation, soil salinity, percent of plot recently disturbed, percent of sunlight captured by the plant canopy (as a measure of plant abundance), and plant species density. Structural equation analysis ascertained the degree to which landscape position variables explained variation in species density that could not be explained by current environmental indicators. Without considering landscape variables, 54% of the variation in species density could be explained by the effects of salinity, flooding, and plant abundance. When landscape variables were included, distance from shore was unimportant but distance from sea explained an additional 12% of the variance in species density (R2 of final model = 66%). Based on these results it appears that at least some of the otherwise unexplained variation in species density can be attributed to landscape position, and presumably previous storm events. We suggest that future studies may gain additional insight into the factors controlling current patterns of species density by examining the effects of position within the landscape.
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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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Otárola, Mauricio Fernández; Avalos, Gerardo
2014-06-01
• Premise of the study: Environmental heterogeneity is a strong selective force shaping adaptation and population dynamics across temporal and spatial scales. Natural and anthropogenic gradients influence the variation of environmental and biotic factors, which determine population demography and dynamics. Successional gradients are expected to influence demographic parameters, but the relationship between these gradients and the species life history, habitat requirements, and degree of variation in demographic traits remains elusive.• Methods: We used the palm Euterpe precatoria to test the effect of successional stage on plant demography within a continuous population. We calculated demographic parameters for size stages and performed matrix analyses to investigate the demographic variation within primary and secondary forests of La Selva, Costa Rica.• Key results: We observed differences in mortality and recruitment of small juveniles between primary and secondary forests. Matrix models described satisfactorily the chronosequence of population changes, which were characterized by high population growth rate in disturbed areas, and decreased growth rate in old successional forests until reaching stability.• Conclusions: Different demographic parameters can be expressed in contiguous subpopulations along a gradient of successional stages with important consequences for population dynamics. Demographic variation superimposed on these gradients contributes to generate subpopulations with different demographic composition, density, and ecological properties. Therefore, the effects of spatial variation must be reconsidered in the design of demographic analyses of tropical palms, which are prime examples of subtle local adaptation. These considerations are crucial in the implementation of management plans for palm species within spatially complex and heterogeneous tropical landscapes. © 2014 Botanical Society of America, Inc.
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Pomara, Lars Y; LeDee, Olivia E; Martin, Karl J; Zuckerberg, Benjamin
2014-07-01
Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range-wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back-cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long-term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long-term demographic decline and range contraction for a species of high-conservation concern. Range-wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal-limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management. © 2013 John Wiley & Sons Ltd.
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Zhang, Lihua; Zhang, Jiachao; Zeng, Guangming; Dong, Haoran; Chen, Yaoning; Huang, Chao; Zhu, Yuan; Xu, Rui; Cheng, Yujun; Hou, Kunjie; Cao, Weicheng; Fang, Wei
2018-08-01
This study evaluated the contributions of environmental variables to the variations in bacterial 16S rDNA, nitrifying and denitrifying genes abundances during composting in the presence of polyvinylpyrrolidone coated silver nanoparticles (PVP-AgNPs). Manual forward selection in redundancy analysis (RDA) indicated that the variation in 16S rDNA was significantly explained by NO 3 - -N, while nitrifying genes were significantly related with pH, and denitrifying genes were driven by NO 3 - -N and TN. Partial RDA further revealed that NO 3 - -N solely explained 28.8% of the variation in 16S rDNA abundance, and pH accounted for 61.8% of the variation in nitrifying genes. NO 3 - -N and TN accounted for 34.2% and 9.2% of denitrifying genes variation, respectively. The RDA triplots showed that different genes shared different relationships with environmental parameters. Based on these findings, a composting with high efficiency and quality may be conducted in the future work by adjusting the significant environmental variables. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Zheng, Yi; Lin, Zhongrong; Li, Hao; Ge, Yan; Zhang, Wei; Ye, Youbin; Wang, Xuejun
2014-05-15
Urban stormwater runoff delivers a significant amount of polycyclic aromatic hydrocarbons (PAHs), mostly of atmospheric origin, to receiving water bodies. The PAH pollution of urban stormwater runoff poses serious risk to aquatic life and human health, but has been overlooked by environmental modeling and management. This study proposed a dynamic modeling approach for assessing the PAH pollution and its associated environmental risk. A variable time-step model was developed to simulate the continuous cycles of pollutant buildup and washoff. To reflect the complex interaction among different environmental media (i.e. atmosphere, dust and stormwater), the dependence of the pollution level on antecedent weather conditions was investigated and embodied in the model. Long-term simulations of the model can be efficiently performed, and probabilistic features of the pollution level and its risk can be easily determined. The applicability of this approach and its value to environmental management was demonstrated by a case study in Beijing, China. The results showed that Beijing's PAH pollution of road runoff is relatively severe, and its associated risk exhibits notable seasonal variation. The current sweeping practice is effective in mitigating the pollution, but the effectiveness is both weather-dependent and compound-dependent. The proposed modeling approach can help identify critical timing and major pollutants for monitoring, assessing and controlling efforts to be focused on. The approach is extendable to other urban areas, as well as to other contaminants with similar fate and transport as PAHs. Copyright © 2014 Elsevier B.V. All rights reserved.
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Random forests as cumulative effects models: A case study of lakes and rivers in Muskoka, Canada.
Jones, F Chris; Plewes, Rachel; Murison, Lorna; MacDougall, Mark J; Sinclair, Sarah; Davies, Christie; Bailey, John L; Richardson, Murray; Gunn, John
2017-10-01
Cumulative effects assessment (CEA) - a type of environmental appraisal - lacks effective methods for modeling cumulative effects, evaluating indicators of ecosystem condition, and exploring the likely outcomes of development scenarios. Random forests are an extension of classification and regression trees, which model response variables by recursive partitioning. Random forests were used to model a series of candidate ecological indicators that described lakes and rivers from a case study watershed (The Muskoka River Watershed, Canada). Suitability of the candidate indicators for use in cumulative effects assessment and watershed monitoring was assessed according to how well they could be predicted from natural habitat features and how sensitive they were to human land-use. The best models explained 75% of the variation in a multivariate descriptor of lake benthic-macroinvertebrate community structure, and 76% of the variation in the conductivity of river water. Similar results were obtained by cross-validation. Several candidate indicators detected a simulated doubling of urban land-use in their catchments, and a few were able to detect a simulated doubling of agricultural land-use. The paper demonstrates that random forests can be used to describe the combined and singular effects of multiple stressors and natural environmental factors, and furthermore, that random forests can be used to evaluate the performance of monitoring indicators. The numerical methods presented are applicable to any ecosystem and indicator type, and therefore represent a step forward for CEA. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.
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Restrepo-Coupe, Natalia; Levine, Naomi M.; Christoffersen, Bradley O.; ...
2016-08-29
To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of othermore » fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Restrepo-Coupe, Natalia; Levine, Naomi M.; Christoffersen, Bradley O.
To predict forest response to long-term climate change with high confidence requires that dynamic global vegetation models (DGVMs) be successfully tested against ecosystem response to short-term variations in environmental drivers, including regular seasonal patterns. Here, we used an integrated dataset from four forests in the Brasil flux network, spanning a range of dry-season intensities and lengths, to determine how well four state-of-the-art models (IBIS, ED2, JULES, and CLM3.5) simulated the seasonality of carbon exchanges in Amazonian tropical forests. We found that most DGVMs poorly represented the annual cycle of gross primary productivity (GPP), of photosynthetic capacity (Pc), and of othermore » fluxes and pools. Models simulated consistent dry-season declines in GPP in the equatorial Amazon (Manaus K34, Santarem K67, and Caxiuanã CAX); a contrast to observed GPP increases. Model simulated dry-season GPP reductions were driven by an external environmental factor, ‘soil water stress’ and consequently by a constant or decreasing photosynthetic infrastructure (Pc), while observed dry-season GPP resulted from a combination of internal biological (leaf-flush and abscission and increased Pc) and environmental (incoming radiation) causes. Moreover, we found models generally overestimated observed seasonal net ecosystem exchange (NEE) and respiration (Re) at equatorial locations. In contrast, a southern Amazon forest (Jarú RJA) exhibited dry-season declines in GPP and Re consistent with most DGVMs simulations. While water limitation was represented in models and the primary driver of seasonal photosynthesis in southern Amazonia, changes in internal biophysical processes, light-harvesting adaptations (e.g., variations in leaf area index (LAI) and increasing leaf-level assimilation rate related to leaf demography), and allocation lags between leaf and wood, dominated equatorial Amazon carbon flux dynamics and were deficient or absent from current model formulations. In conclusion, correctly simulating flux seasonality at tropical forests requires a greater understanding and the incorporation of internal biophysical mechanisms in future model developments.« less
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Modeling of coastal water contamination in Fortaleza (Northeastern Brazil).
Pereira, S P; Rosman, P C C; Alvarez, C; Schetini, C A F; Souza, R O; Vieira, R H S F
2015-01-01
An important tool in environmental management projects and studies due to the complexity of environmental systems, environmental modeling makes it possible to integrate many variables and processes, thereby providing a dynamic view of systems. In this study the bacteriological quality of the coastal waters of Fortaleza (a state capital in Northeastern Brazil) was modeled considering multiple contamination sources. Using the software SisBaHiA, the dispersion of thermotolerant coliforms and Escherichia coli from three sources of contamination (local rivers, storm drains and submarine outfall) was analyzed. The models took into account variations in bacterial decay due to solar radiation and other environmental factors. Fecal pollution discharged from rivers and storm drains is transported westward by coastal currents, contaminating strips of beach water to the left of each storm drain or river. Exception to this condition only occurs on beaches protected by the breakwater of the harbor, where counterclockwise vortexes reverse this behavior. The results of the models were consistent with field measurements taken during the dry and the rainy season. Our results show that the submarine outfall plume was over 2 km from the nearest beach. The storm drains and the Maceió stream are the main factors responsible for the poor water quality on the waterfront of Fortaleza. The depollution of these sources would generate considerable social, health and economic gains for the region.
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Mechanisms of increased lifespan in hypoxia
USDA-ARS?s Scientific Manuscript database
Genetic variation accounts for a relatively small amount of the variation in lifespan (generally 15-30%), while environmental stressors are very strong predictors (Finch and Kirkwood 2000). Hypoxia is an environmental stress that increases longevity in some contexts, but the mechanisms remain poorly...
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NASA Astrophysics Data System (ADS)
Iwata, Hiroki; Mano, Masayoshi; Ono, Keisuke; Tokida, Takeshi; Kawazoe, Takahiro; Kosugi, Yoshiko; Sakabe, Ayaka; Takahashi, Kenshi; Miyata, Akira
2018-04-01
Season-long methane (CH4) exchange was observed in a rice paddy field in central Japan (Kanto Region) using the eddy covariance technique to clarify the variations in environmental controls on CH4 exchange in different stages of cultivation. Before heading of rice plant, the CH4 emission depended on wind speed and soil temperature. The soil temperature dependence can be due to an increase in CH4 production, higher molecular diffusion, and higher conductance within rice plant at higher soil temperature. An occurrence of ebullitive emission was also suggested from the wind speed dependence. After heading was completed, relative humidity and water temperature influenced CH4 emission. The amplitude of the diurnal variation in emission increased from 0.03 μmolm-2s-1 in the late pre-heading stage to 0.13 μmolm-2s-1 in the post-heading stage. Induced convective throughflow within the rice aerenchyma after the change in plant structure was attributable to this variation in environmental controls after the heading. After drainage, CH4 emission was confined to short periods after strong rain events. The water level controlled the timing of emission, most likely by influencing the diffusion efficiency from the anoxic soil to the atmosphere and CH4 oxidation in the surface oxic zone. The variation in the dominant transport pathway needs to be accounted for in terrestrial ecosystem models to accurately predict CH4 emission from rice paddies.
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Hopwood, Paul E; Moore, Allen J; Royle, Nick J
2014-06-22
Good early nutritional conditions may confer a lasting fitness advantage over individuals suffering poor early conditions (a 'silver spoon' effect). Alternatively, if early conditions predict the likely adult environment, adaptive plastic responses might maximize individual performance when developmental and adult conditions match (environmental-matching effect). Here, we test for silver spoon and environmental-matching effects by manipulating the early nutritional environment of Nicrophorus vespilloides burying beetles. We manipulated nutrition during two specific early developmental windows: the larval environment and the post-eclosion environment. We then tested contest success in relation to variation in adult social environmental quality experienced (defined according to whether contest opponents were smaller (good environment) or larger (poor environment) than the focal individual). Variation in the larval environment influenced adult body size but not contest success per se for a given adult social environment experienced (an 'indirect' silver spoon effect). Variation in post-eclosion environment affected contest success dependent on the quality of the adult environment experienced (a context-dependent 'direct' silver spoon effect). By contrast, there was no evidence for environmental-matching. The results demonstrate the importance of social environmental context in determining how variation in nutrition in early life affects success as an adult.
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Nath, Cheryl D; Dattaraja, H S; Suresh, H S; Joshi, N V; Sukumar, R
2006-12-01
Tree diameter growth is sensitive to environmental fluctuations and tropical dry forests experience high seasonal and inter-annual environmental variation. Tree growth rates in a large permanent plot at Mudumalai, southern India, were examined for the influences of rainfall and three intrinsic factors (size, species and growth form) during three 4-year intervals over the period 1988-2000. Most trees had lowest growth during the second interval when rainfall was lowest, and skewness and kurtosis of growth distributions were reduced during this interval. Tree diameter generally explained less than 10% of growth variation and had less influence on growth than species identity or time interval. Intraspecific variation was high, yet species identity accounted for up to 16% of growth variation in the community. There were no consistent differences between canopy and understory tree growth rates; however, a few subgroups of species may potentially represent canopy and understory growth guilds. Environmentally-induced temporal variations in growth generally did not reduce the odds of subsequent survival. Growth rates appear to be strongly influenced by species identity and environmental variability in the Mudumalai dry forest. Understanding and predicting vegetation dynamics in the dry tropics thus also requires information on temporal variability in local climate.
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Phenotypic plasticity in the scaling of avian basal metabolic rate
McKechnie, Andrew E; Freckleton, Robert P; Jetz, Walter
2006-01-01
Many birds exhibit short-term, reversible adjustments in basal metabolic rate (BMR), but the overall contribution of phenotypic plasticity to avian metabolic diversity remains unclear. The available BMR data include estimates from birds living in natural environments and captive-raised birds in more homogenous, artificial environments. All previous analyses of interspecific variation in BMR have pooled these data. We hypothesized that phenotypic plasticity is an important contributor to interspecific variation in avian BMR, and that captive-raised populations exhibit general differences in BMR compared to wild-caught populations. We tested this hypothesis by fitting general linear models to BMR data for 231 bird species, using the generalized least-squares approach to correct for phylogenetic relatedness when necessary. The scaling exponent relating BMR to body mass in captive-raised birds (0.670) was significantly shallower than in wild-caught birds (0.744). The differences in metabolic scaling between captive-raised and wild-caught birds persisted when migratory tendency and habitat aridity were controlled for. Our results reveal that phenotypic plasticity is a major contributor to avian interspecific metabolic variation. The finding that metabolic scaling in birds is partly determined by environmental factors provides further support for models that predict variation in scaling exponents, such as the allometric cascade model. PMID:16627278
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Modeling black-footed ferret energetics: Are southern release sites better?
Harrington, Lauren A.; Biggins, Dean E.; Alldredge, A. William
2006-01-01
Several models have been developed to estimate prey requirements and to assess habitat suitability of release sites for the black-footed ferret (Mustela nigripes) (e.g., Stromberg and others, 1983; Powell and others, 1985; Biggins and others, 1993). None of these models, however, addressed possible differences in energetic requirements between sites due to climatic differences within the ferret’s historical range. We used a simplified energetics model to examine the effect of variation in environmental conditions on ferret energetic requirements. The aim of the study was to determine whether the ferret might be more successful in one area than another.
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NASA Astrophysics Data System (ADS)
Finsinger, Walter; Dos Santos, Thibaut; McKey, Doyle
2013-07-01
Variation of stomatal frequency (stomatal density and stomatal index) includes genetically-based, potentially-adaptive variation, and variation due to phenotypic plasticity, the degree of which may be fundamental to the ability to maintain high water-use efficiency and thus to deal with environmental change. We analysed stomatal frequency and morphology (pore length, pore width) in leaves from several individuals from nine populations of four sub-species of the Leonardoxa africana complex. The dataset represents a hierarchical sampling wherein factors are nested within each level (leaves in individuals, individuals in sites, etc.), allowing estimation of the contribution of different levels to overall variation, using variance-component analysis. SI showed significant variation among sites ("site" is largely confounded with "sub-species"), being highest in the sub-species localized in the highest-elevation site. However, most of the observed variance was accounted for at intra-site and intra-individual levels. This variance could reflect great phenotypic plasticity, presumably in response to highly local variation in micro-environmental conditions.
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A practical guide to environmental association analysis in landscape genomics.
Rellstab, Christian; Gugerli, Felix; Eckert, Andrew J; Hancock, Angela M; Holderegger, Rolf
2015-09-01
Landscape genomics is an emerging research field that aims to identify the environmental factors that shape adaptive genetic variation and the gene variants that drive local adaptation. Its development has been facilitated by next-generation sequencing, which allows for screening thousands to millions of single nucleotide polymorphisms in many individuals and populations at reasonable costs. In parallel, data sets describing environmental factors have greatly improved and increasingly become publicly accessible. Accordingly, numerous analytical methods for environmental association studies have been developed. Environmental association analysis identifies genetic variants associated with particular environmental factors and has the potential to uncover adaptive patterns that are not discovered by traditional tests for the detection of outlier loci based on population genetic differentiation. We review methods for conducting environmental association analysis including categorical tests, logistic regressions, matrix correlations, general linear models and mixed effects models. We discuss the advantages and disadvantages of different approaches, provide a list of dedicated software packages and their specific properties, and stress the importance of incorporating neutral genetic structure in the analysis. We also touch on additional important aspects such as sampling design, environmental data preparation, pooled and reduced-representation sequencing, candidate-gene approaches, linearity of allele-environment associations and the combination of environmental association analyses with traditional outlier detection tests. We conclude by summarizing expected future directions in the field, such as the extension of statistical approaches, environmental association analysis for ecological gene annotation, and the need for replication and post hoc validation studies. © 2015 John Wiley & Sons Ltd.
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NASA Technical Reports Server (NTRS)
Salawitch, R. J.; Wofsy, S. C.; Wennberg, P. O.; Cohen, R. C.; Anderson, J. G.; Fahey, D. W.; Gao, R. S.; Keim, E. R.; Woodbridge, E. L.; Stimpfle, R. M.;
1994-01-01
In situ measurements of hydrogen, nitrogen, and chlorine radicals obtained through sunrise and sunset in the lower stratosphere during SPADE are compared to results from a photochemical model constrained by observed concentrations of radical precursors and environmental conditions. Models allowing for heterogeneous hydrolysis of N205 on sulfate aerosols agree with measured concentrations of NO, NO2, and ClO throughout the day, but fail to account for high concentrations of OH and H02 observed near sunrise and sunset. The morning burst of [OH] and [HO2] coincides with the rise of [NO] from photolysis of N02, suggesting a new source of HO, that photolyzes in the near UV (350 to 400 nm) spectral region. A model that allows for the heterogeneous production of HN02 results in an excellent simulation of the diurnal variations of [OH] and [HO2].
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NASA Technical Reports Server (NTRS)
Salawitch, R. J.; Wofsy, S. C.; Wennberg, P. O.; Cohen, R. C.; Anderson, J. G.; Fahey, D. W.; Gao, R. S.; Keim, E. R.; Woodbridge, E. L.; Stimpfle, R. M.
1994-01-01
In situ measurements of hydrogen, nitrogen, and chlorine radicals obtained through sunrise and sunset in the lower statosphere during SPADE are compared to results from a photochemical model constrained by observed concentrations of radical precursors and environmental conditions. Models allowing for heteogeneous hydrolysis of N2O5 on sulfate aerosols agree with measured concentrations of NO, NO2, and ClO throughout the day, but fail to account for high concentrations of OH and HO2 observed near sunrise and sunset. The morning burst of (OH) and (HO2) coincides with the rise of (NO) from photolysis of NO2, suggesting a new source of HO(x) that photolyzes in the near UV (350 to 400 nm) spectral region. A model that allow for the heterogeneous production of HNO2 results in an excellent simulation of the diurnal variations of (OH) and (HO2).
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Open Systems with Error Bounds: Spin-Boson Model with Spectral Density Variations.
Mascherpa, F; Smirne, A; Huelga, S F; Plenio, M B
2017-03-10
In the study of open quantum systems, one of the most common ways to describe environmental effects on the reduced dynamics is through the spectral density. However, in many models this object cannot be computed from first principles and needs to be inferred on phenomenological grounds or fitted to experimental data. Consequently, some uncertainty regarding its form and parameters is unavoidable; this in turn calls into question the accuracy of any theoretical predictions based on a given spectral density. Here, we focus on the spin-boson model as a prototypical open quantum system, find two error bounds on predicted expectation values in terms of the spectral density variation considered, and state a sufficient condition for the strongest one to apply. We further demonstrate an application of our result, by bounding the error brought about by the approximations involved in the hierarchical equations of motion resolution method for spin-boson dynamics.
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A New Occurrence Model for National Assessment of Undiscovered Volcanogenic Massive Sulfide Deposits
Shanks, W.C. Pat; Dusel-Bacon, Cynthia; Koski, Randolph; Morgan, Lisa A.; Mosier, Dan; Piatak, Nadine M.; Ridley, Ian; Seal, Robert R.; Schulz, Klaus J.; Slack, John F.; Thurston, Roland
2009-01-01
Volcanogenic massive sulfide (VMS) deposits are very significant current and historical resources of Cu-Pb-Zn-Au-Ag, are active exploration targets in several areas of the United States and potentially have significant environmental effects. This new USGS VMS deposit model provides a comprehensive review of deposit occurrence and ore genesis, and fully integrates recent advances in the understanding of active seafloor VMS-forming environments, and integrates consideration of geoenvironmental consequences of mining VMS deposits. Because VMS deposits exhibit a broad range of geological and geochemical characteristics, a suitable classification system is required to incorporate these variations into the mineral deposit model. We classify VMS deposits based on compositional variations in volcanic and sedimentary host rocks. The advantage of the classification method is that it provides a closer linkage between tectonic setting and lithostratigraphic assemblages, and an increased predictive capability during field-based studies.
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Physics and the canalization of morphogenesis: a grand challenge in organismal biology
von Dassow, Michelangelo; Davidson, Lance A.
2011-01-01
Morphogenesis takes place in a background of organism-to-organism and environmental variation. Therefore, a fundamental question in the study of morphogenesis is how the mechanical processes of tissue movement and deformation are affected by that variability, and in turn, how the mechanics of the system modulates phenotypic variation. We highlight a few key factors, including environmental temperature, embryo size, and environmental chemistry that might perturb the mechanics of morphogenesis in natural populations. Then we discuss several ways in which mechanics – including feedback from mechanical cues – might influence intra-specific variation in morphogenesis. To understand morphogenesis it will be necessary to consider whole-organism, environment, and evolutionary scales because these larger scales present the challenges that developmental mechanisms have evolved to cope with. Studying the variation organisms express and the variation organisms experience will aid in deciphering the causes of birth defects. PMID:21750364
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Predictions of avian Plasmodium expansion under climate change.
Loiseau, Claire; Harrigan, Ryan J; Bichet, Coraline; Julliard, Romain; Garnier, Stéphane; Lendvai, Adám Z; Chastel, Olivier; Sorci, Gabriele
2013-01-01
Vector-borne diseases are particularly responsive to changing environmental conditions. Diurnal temperature variation has been identified as a particularly important factor for the development of malaria parasites within vectors. Here, we conducted a survey across France, screening populations of the house sparrow (Passer domesticus) for malaria (Plasmodium relictum). We investigated whether variation in remotely-sensed environmental variables accounted for the spatial variation observed in prevalence and parasitemia. While prevalence was highly correlated to diurnal temperature range and other measures of temperature variation, environmental conditions could not predict spatial variation in parasitemia. Based on our empirical data, we mapped malaria distribution under climate change scenarios and predicted that Plasmodium occurrence will spread to regions in northern France, and that prevalence levels are likely to increase in locations where transmission already occurs. Our findings, based on remote sensing tools coupled with empirical data suggest that climatic change will significantly alter transmission of malaria parasites.
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2015-01-01
Building behaviours occur in various organisms from bacteria to humans. Social insects build various structures such as large nests and underground galleries, achieved by self-organization. Structures built by social insects have recently been demonstrated to vary widely in size and shape within a species, even under the same environmental conditions. However, little is known about how intraspecific variation in structures emerges from collective behaviours. Here we show that the colony variation of structures can be generated by simply changing two behavioural parameters of group members, even with the same building algorithm. Our laboratory experiment of termite shelter tube construction demonstrated clear intercolonial variation, and a two-dimensional lattice model showed that it can be attributed to the extent of positive feedback and the number of individuals engaged in building. This study contributes to explaining the great diversity of structures emerging from collective building in social insects. PMID:26715997
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Window Area and Development Drive Spatial Variation in Bird-Window Collisions in an Urban Landscape
Hager, Stephen B.; Cosentino, Bradley J.; McKay, Kelly J.; Monson, Cathleen; Zuurdeeg, Walt; Blevins, Brian
2013-01-01
Collisions with windows are an important human-related threat to birds in urban landscapes. However, the proximate drivers of collisions are not well understood, and no study has examined spatial variation in mortality in an urban setting. We hypothesized that the number of fatalities at buildings varies with window area and habitat features that influence avian community structure. In 2010 we documented bird-window collisions (BWCs) and characterized avian community structure at 20 buildings in an urban landscape in northwestern Illinois, USA. For each building and season, we conducted 21 daily surveys for carcasses and nine point count surveys to estimate relative abundance, richness, and diversity. Our sampling design was informed by experimentally estimated carcass persistence times and detection probabilities. We used linear and generalized linear mixed models to evaluate how habitat features influenced community structure and how mortality was affected by window area and factors that correlated with community structure. The most-supported model was consistent for all community indices and included effects of season, development, and distance to vegetated lots. BWCs were related positively to window area and negatively to development. We documented mortalities for 16/72 (22%) species (34 total carcasses) recorded at buildings, and BWCs were greater for juveniles than adults. Based on the most-supported model of BWCs, the median number of annual predicted fatalities at study buildings was 3 (range = 0–52). These results suggest that patchily distributed environmental resources and levels of window area in buildings create spatial variation in BWCs within and among urban areas. Current mortality estimates place little emphasis on spatial variation, which precludes a fundamental understanding of the issue. To focus conservation efforts, we illustrate how knowledge of the structural and environmental factors that influence bird-window collisions can be used to predict fatalities in the broader landscape. PMID:23326420
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Window area and development drive spatial variation in bird-window collisions in an urban landscape.
Hager, Stephen B; Cosentino, Bradley J; McKay, Kelly J; Monson, Cathleen; Zuurdeeg, Walt; Blevins, Brian
2013-01-01
Collisions with windows are an important human-related threat to birds in urban landscapes. However, the proximate drivers of collisions are not well understood, and no study has examined spatial variation in mortality in an urban setting. We hypothesized that the number of fatalities at buildings varies with window area and habitat features that influence avian community structure. In 2010 we documented bird-window collisions (BWCs) and characterized avian community structure at 20 buildings in an urban landscape in northwestern Illinois, USA. For each building and season, we conducted 21 daily surveys for carcasses and nine point count surveys to estimate relative abundance, richness, and diversity. Our sampling design was informed by experimentally estimated carcass persistence times and detection probabilities. We used linear and generalized linear mixed models to evaluate how habitat features influenced community structure and how mortality was affected by window area and factors that correlated with community structure. The most-supported model was consistent for all community indices and included effects of season, development, and distance to vegetated lots. BWCs were related positively to window area and negatively to development. We documented mortalities for 16/72 (22%) species (34 total carcasses) recorded at buildings, and BWCs were greater for juveniles than adults. Based on the most-supported model of BWCs, the median number of annual predicted fatalities at study buildings was 3 (range = 0-52). These results suggest that patchily distributed environmental resources and levels of window area in buildings create spatial variation in BWCs within and among urban areas. Current mortality estimates place little emphasis on spatial variation, which precludes a fundamental understanding of the issue. To focus conservation efforts, we illustrate how knowledge of the structural and environmental factors that influence bird-window collisions can be used to predict fatalities in the broader landscape.
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Huang, Xiaodong; Clements, Archie C A; Williams, Gail; Mengersen, Kerrie; Tong, Shilu; Hu, Wenbiao
2016-04-01
A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7-December 31, 2009, at a postal area level in Queensland, Australia. We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space-time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: -0.341; 95% credible interval (CI): -0.370--0.311) and the socio-economic index for area (SEIFA) (posterior mean: -0.003; 95% CI: -0.004--0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007-0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period. Copyright © 2016 Elsevier Inc. All rights reserved.
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Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross
Ferris, Martin T.; Aylor, David L.; Bottomly, Daniel; Whitmore, Alan C.; Aicher, Lauri D.; Bell, Timothy A.; Bradel-Tretheway, Birgit; Bryan, Janine T.; Buus, Ryan J.; Gralinski, Lisa E.; Haagmans, Bart L.; McMillan, Leonard; Miller, Darla R.; Rosenzweig, Elizabeth; Valdar, William; Wang, Jeremy; Churchill, Gary A.; Threadgill, David W.; McWeeney, Shannon K.; Katze, Michael G.; Pardo-Manuel de Villena, Fernando; Baric, Ralph S.; Heise, Mark T.
2013-01-01
Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss. PMID:23468633
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A species sensitivity distribution (SSD) is a probability model of the variation of species sensitivities to a stressor, in particular chemical exposure. The SSD approach has been used as a decision support tool in environmental protection and management since the 1980s, and the ...
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Nowak, R.S.; Tausch, R.J.
1998-11-01
This report focuses on the following two research projects relating to the biological effects of climate change: Hybridization and genetic diversity populations of Utah (Juniperus osteosperma) and western (Juniperus occidentalis) juniper: Evidence from nuclear ribosomal and chloroplast DNA; and Ecophysiological patterns of pinyon and juniper.
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Genetic, environmental, and epigenetic factors in the development of personality disturbance.
Depue, Richard A
2009-01-01
A dimensional model of personality disturbance is presented that is defined by extreme values on interacting subsets of seven major personality traits. Being at the extreme has marked effects on the threshold for eliciting those traits under stimulus conditions: that is, the extent to which the environment affects the neurobiological functioning underlying the traits. To explore the nature of development of extreme values on these traits, each trait is discussed in terms of three major issues: (a) the neurobiological variables associated with the trait, (b) individual variation in this neurobiology as a function of genetic polymorphisms, and (c) the effects of environmental adversity on these neurobiological variables through the action of epigenetic processes. It is noted that gene-environment interaction appears to be dependent on two main factors: (a) both genetic and environmental variables appear to have the most profound and enduring effects when they exert their effects during early postnatal periods, times when the forebrain is undergoing exuberant experience-expectant dendritic and axonal growth; and (b) environmental effects on neurobiology are strongly modified by individual differences in "traitlike" functioning of neurobiological variables. A model of the nature of the interaction between environmental and neurobiological variables in the development of personality disturbance is presented.
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Mapping spatial patterns of denitrifiers at large scales (Invited)
NASA Astrophysics Data System (ADS)
Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.
2010-12-01
Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.
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Direct and indirect genetic and fine-scale location effects on breeding date in song sparrows.
Germain, Ryan R; Wolak, Matthew E; Arcese, Peter; Losdat, Sylvain; Reid, Jane M
2016-11-01
Quantifying direct and indirect genetic effects of interacting females and males on variation in jointly expressed life-history traits is central to predicting microevolutionary dynamics. However, accurately estimating sex-specific additive genetic variances in such traits remains difficult in wild populations, especially if related individuals inhabit similar fine-scale environments. Breeding date is a key life-history trait that responds to environmental phenology and mediates individual and population responses to environmental change. However, no studies have estimated female (direct) and male (indirect) additive genetic and inbreeding effects on breeding date, and estimated the cross-sex genetic correlation, while simultaneously accounting for fine-scale environmental effects of breeding locations, impeding prediction of microevolutionary dynamics. We fitted animal models to 38 years of song sparrow (Melospiza melodia) phenology and pedigree data to estimate sex-specific additive genetic variances in breeding date, and the cross-sex genetic correlation, thereby estimating the total additive genetic variance while simultaneously estimating sex-specific inbreeding depression. We further fitted three forms of spatial animal model to explicitly estimate variance in breeding date attributable to breeding location, overlap among breeding locations and spatial autocorrelation. We thereby quantified fine-scale location variances in breeding date and quantified the degree to which estimating such variances affected the estimated additive genetic variances. The non-spatial animal model estimated nonzero female and male additive genetic variances in breeding date (sex-specific heritabilities: 0·07 and 0·02, respectively) and a strong, positive cross-sex genetic correlation (0·99), creating substantial total additive genetic variance (0·18). Breeding date varied with female, but not male inbreeding coefficient, revealing direct, but not indirect, inbreeding depression. All three spatial animal models estimated small location variance in breeding date, but because relatedness and breeding location were virtually uncorrelated, modelling location variance did not alter the estimated additive genetic variances. Our results show that sex-specific additive genetic effects on breeding date can be strongly positively correlated, which would affect any predicted rates of microevolutionary change in response to sexually antagonistic or congruent selection. Further, we show that inbreeding effects on breeding date can also be sex specific and that genetic effects can exceed phenotypic variation stemming from fine-scale location-based variation within a wild population. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.
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NASA Astrophysics Data System (ADS)
Wang, Kejing; Zhang, Yuan; An, Youzhi; Jing, Zhuoxin; Wang, Chao
2013-09-01
With the fast urbanization process, how does the vegetation environment change in one of the most economically developed metropolis, Shanghai in East China? To answer this question, there is a pressing demand to explore the non-stationary relationship between socio-economic conditions and vegetation across Shanghai. In this study, environmental data on vegetation cover, the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery in 2003 were integrated with socio-economic data to reflect the city's vegetative conditions at the census block group level. To explore regional variations in the relationship of vegetation and socio-economic conditions, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to characterize mean NDVI against three independent socio-economic variables, an urban land use ratio, Gross Domestic Product (GDP) and population density. The study results show that a considerable distinctive spatial variation exists in the relationship for each model. The GWR model has superior effects and higher precision than the OLS model at the census block group scale. So, it is more suitable to account for local effects and geographical variations. This study also indicates that unreasonable excessive urbanization, together with non-sustainable economic development, has a negative influence of vegetation vigor for some neighborhoods in Shanghai.
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Isaac, Marney E.; Martin, Adam R.; de Melo Virginio Filho, Elias; Rapidel, Bruno; Roupsard, Olivier; Van den Meersche, Karel
2017-01-01
Hypotheses on the existence of a universal “Root Economics Spectrum” (RES) have received arguably the least attention of all trait spectra, despite the key role root trait variation plays in resource acquisition potential. There is growing interest in quantifying intraspecific trait variation (ITV) in plants, but there are few studies evaluating (i) the existence of an intraspecific RES within a plant species, or (ii) how a RES may be coordinated with other trait spectra within species, such as a leaf economics spectrum (LES). Using Coffea arabica (Rubiaceae) as a model species, we measured seven morphological and chemical traits of intact lateral roots, which were paired with information on four key LES traits. Field collections were completed across four nested levels of biological organization. The intraspecific trait coefficient of variation (cv) ranged from 25 to 87% with root diameter and specific root tip density showing the lowest and highest cv, respectively. Between 27 and 68% of root ITV was explained by site identity alone for five of the seven traits measured. A single principal component explained 56.2% of root trait covariation, with plants falling along a RES from resource acquiring to conserving traits. Multiple factor analysis revealed significant orthogonal relationships between root and leaf spectra. RES traits were strongly orthogonal with respect to LES traits, suggesting these traits vary independently from one another in response to environmental cues. This study provides among the first evidence that plants from the same species differentiate from one another along an intraspecific RES. We find that in one of the world’s most widely cultivated crops, an intraspecific RES is orthogonal to an intraspecific LES, indicating that above and belowground responses of plants to managed (or natural) environmental gradients are likely to occur independently from one another. PMID:28747919
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NASA Technical Reports Server (NTRS)
Nilsen, Frances M.; Dorsey, Jonathan E.; Long, Stephen E.; Schock, Tracey B.; Bowden, John A.; Lowers, Russell H.; Guillette, Louis J., Jr.
2016-01-01
Seasonal variation of mercury (Hg) is not well studied in free-ranging wildlife. Atmospheric deposition patterns of Hg have been studied in detail and have been modeled for both global and specific locations with great accuracy and correlates to environment impact. However, monitoring these trends in wildlife is complicated due to local environmental parameters (e.g., rainfall, humidity, pH, bacterial composition) that can affect the transformation of atmospheric Hg to the biologically available forms. Here, we utilized an abundant and healthy population of American alligators (Alligator mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), FL, and assessed Hg burden in whole blood samples over a span of 7 years (2007 2014; n 174) in an effort to assess seasonal variation of total [Hg]. While the majority of this population is assumed healthy, 18 individuals with low body mass indices (BMI, defined in this study) were captured throughout the 7 year sampling period. These individual alligators exhibited [Hg] that were not consistent with the observed overall seasonal [Hg] variation, and were statistically different from the healthy population of alligators. The alligators with low BMI had elevated concentrations of Hg compared to their age/sex/season matched counterparts with normal BMI. Statistically significant differences were found between the winter and spring seasons for animals with normal BMI. The data in this report supports the conclusion that organismal total [Hg] do fluctuate directly with seasonal deposition rates as well as other seasonal environmental parameters, such as average rainfall and prevailing wind direction. This study highlights the unique environment of MINWR to permit annual assessment of apex predators, such as the American alligator, to determine detailed environmental impact of contaminants of concern.
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Isaac, Marney E; Martin, Adam R; de Melo Virginio Filho, Elias; Rapidel, Bruno; Roupsard, Olivier; Van den Meersche, Karel
2017-01-01
Hypotheses on the existence of a universal "Root Economics Spectrum" (RES) have received arguably the least attention of all trait spectra, despite the key role root trait variation plays in resource acquisition potential. There is growing interest in quantifying intraspecific trait variation (ITV) in plants, but there are few studies evaluating (i) the existence of an intraspecific RES within a plant species, or (ii) how a RES may be coordinated with other trait spectra within species, such as a leaf economics spectrum (LES). Using Coffea arabica (Rubiaceae) as a model species, we measured seven morphological and chemical traits of intact lateral roots, which were paired with information on four key LES traits. Field collections were completed across four nested levels of biological organization. The intraspecific trait coefficient of variation (cv) ranged from 25 to 87% with root diameter and specific root tip density showing the lowest and highest cv, respectively. Between 27 and 68% of root ITV was explained by site identity alone for five of the seven traits measured. A single principal component explained 56.2% of root trait covariation, with plants falling along a RES from resource acquiring to conserving traits. Multiple factor analysis revealed significant orthogonal relationships between root and leaf spectra. RES traits were strongly orthogonal with respect to LES traits, suggesting these traits vary independently from one another in response to environmental cues. This study provides among the first evidence that plants from the same species differentiate from one another along an intraspecific RES. We find that in one of the world's most widely cultivated crops, an intraspecific RES is orthogonal to an intraspecific LES, indicating that above and belowground responses of plants to managed (or natural) environmental gradients are likely to occur independently from one another.
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Solar array model corrections from Mars Pathfinder lander data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ewell, R.C.; Burger, D.R.
1997-12-31
The MESUR solar array power model initially assumed values for input variables. After landing early surface variables such as array tilt and azimuth or early environmental variables such as array temperature can be corrected. Correction of later environmental variables such as tau versus time, spectral shift, dust deposition, and UV darkening is dependent upon time, on-board science instruments, and ability to separate effects of variables. Engineering estimates had to be made for additional shadow losses and Voc sensor temperature corrections. Some variations had not been expected such as tau versus time of day, and spectral shift versus time of day.more » Additions needed to the model are thermal mass of lander petal and correction between Voc sensor and temperature sensor. Conclusions are: the model works well; good battery predictions are difficult; inclusion of Isc and Voc sensors was valuable; and the IMP and MAE science experiments greatly assisted the data analysis and model correction.« less
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Barrera-Redondo, Josué; Ramírez-Barahona, Santiago; Eguiarte, Luis E
2018-05-01
Variation in rates of molecular evolution (heterotachy) is a common phenomenon among plants. Although multiple theoretical models have been proposed, fundamental questions remain regarding the combined effects of ecological and morphological traits on rate heterogeneity. Here, we used tree ferns to explore the correlation between rates of molecular evolution in chloroplast DNA sequences and several morphological and environmental factors within a Bayesian framework. We revealed direct and indirect effects of body size, biological productivity, and temperature on substitution rates, where smaller tree ferns living in warmer and less productive environments tend to have faster rates of molecular evolution. In addition, we found that variation in the ratio of nonsynonymous to synonymous substitution rates (dN/dS) in the chloroplast rbcL gene was significantly correlated with ecological and morphological variables. Heterotachy in tree ferns may be influenced by effective population size associated with variation in body size and productivity. Macroevolutionary hypotheses should go beyond explaining heterotachy in terms of mutation rates and instead, should integrate population-level factors to better understand the processes affecting the tempo of evolution at the molecular level. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.
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Kinyoki, Damaris K; Berkley, James A; Moloney, Grainne M; Odundo, Elijah O; Kandala, Ngianga-Bakwin; Noor, Abdisalan M
2016-07-28
Stunting among children under five years old is associated with long-term effects on cognitive development, school achievement, economic productivity in adulthood and maternal reproductive outcomes. Accurate estimation of stunting and tools to forecast risk are key to planning interventions. We estimated the prevalence and distribution of stunting among children under five years in Somalia from 2007 to 2010 and explored the role of environmental covariates in its forecasting. Data from household nutritional surveys in Somalia from 2007 to 2010 with a total of 1,066 clusters covering 73,778 children were included. We developed a Bayesian hierarchical space-time model to forecast stunting by using the relationship between observed stunting and environmental covariates in the preceding years. We then applied the model coefficients to environmental covariates in subsequent years. To determine the accuracy of the forecasting, we compared this model with a model that used data from all the years with the corresponding environmental covariates. Rainfall (OR = 0.994, 95 % Credible interval (CrI): 0.993, 0.995) and vegetation cover (OR = 0.719, 95 % CrI: 0.603, 0.858) were significant in forecasting stunting. The difference in estimates of stunting using the two approaches was less than 3 % in all the regions for all forecast years. Stunting in Somalia is spatially and temporally heterogeneous. Rainfall and vegetation are major drivers of these variations. The use of environmental covariates for forecasting of stunting is a potentially useful and affordable tool for planning interventions to reduce the high burden of malnutrition in Somalia.
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NASA Astrophysics Data System (ADS)
Oh, Ki-Yong; Epureanu, Bogdan I.
2017-10-01
A 1-D phenomenological force model of a Li-ion battery pack is proposed to enhance the control performance of Li-ion battery cells in pack conditions for efficient performance and health management. The force model accounts for multiple swelling sources under the operational environment of electric vehicles to predict swelling-induced forces in pack conditions, i.e. mechanically constrained. The proposed force model not only incorporates structural nonlinearities due to Li-ion intercalation swelling, but also separates the overall range of states of charge into three ranges to account for phase transitions. Moreover, an approach to study cell-to-cell variations in pack conditions is proposed with serial and parallel combinations of linear and nonlinear stiffness, which account for battery cells and other components in the battery pack. The model is shown not only to accurately estimate the reaction force caused by swelling as a function of the state of charge, battery temperature and environmental temperature, but also to account for cell-to-cell variations due to temperature variations, SOC differences, and local degradation in a wide range of operational conditions of electric vehicles. Considering that the force model of Li-ion battery packs can account for many possible situations in actual operation, the proposed approach and model offer potential utility for the enhancement of current battery management systems and power management strategies.
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NASA Astrophysics Data System (ADS)
Bender, Amanda L. D.; Chitwood, Daniel H.; Bradley, Alexander S.
2017-06-01
Leaf wax n-alkanes are broadly used to reconstruct paleoenvironmental information. However, the utility of n-alkanes as a paleoenvironmental proxy may be modulated by the extent to which biological as well as environmental factors influence the structural and isotopic variability of leaf waxes. In paleoclimate applications, there is usually an implicit assumption that most variation of leaf wax traits through a time series can be attributed to environmental change and that biological sources of variability within plant communities are small. For example, changes in hydrology affect the δ2H of waxes via rainwater and the δ13C of leaf waxes by changing plant communities. We measured the degree of genetic control over δ13C variation in leaf waxes within closely related species with an experimental greenhouse growth study. We measured the proportion of variability in structural and isotopic leaf wax traits that is attributable to genetic variation using a set of 76 introgression lines (ILs) between two interfertile Solanum (tomato) species: S. lycopersicum cv M82 (hereafter cv M82) and S. pennellii. Leaves of S. pennellii, a wild desert tomato relative, produced significantly more iso-alkanes than cv M82, a domesticated tomato cultivar adapted to water-replete conditions. We report a methylation index to summarize the ratio of branched (iso- and anteiso-) to total alkanes. Between S. pennellii and cv M82, the iso-alkanes were found to be enriched in 13C by 1.2-1.4‰ over n-alkanes. The broad-sense heritability values (H2) of leaf wax traits describe the degree to which genetic variation contributes to variation of these traits. Variation of individual carbon isotopic compositions of alkanes were of low heritability (H2 = 0.13-0.19), suggesting that most variation in δ13C of leaf waxes in this study can be attributed to environmental variance. This supports the interpretation that variation in the δ13C of wax compounds recorded in sediments reflects paleoenvironmental and vegetation changes. Average chain length (ACL) values of n-alkanes were of intermediate heritability (H2 = 0.30), suggesting that ACL values are more strongly influenced by genetic cues.
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Genetic variation in heat-stress tolerance among South American Drosophila populations.
Fallis, Lindsey C; Fanara, Juan Jose; Morgan, Theodore J
2011-10-01
Spatial or temporal differences in environmental variables, such as temperature, are ubiquitous in nature and impose stress on organisms. This is especially true for organisms that are isothermal with the environment, such as insects. Understanding the means by which insects respond to temperature and how they will react to novel changes in environmental temperature is important for understanding the adaptive capacity of populations and to predict future trajectories of evolutionary change. The organismal response to heat has been identified as an important environmental variable for insects that can dramatically influence life history characters and geographic range. In the current study we surveyed the amount of variation in heat tolerance among Drosophila melanogaster populations collected at diverse sites along a latitudinal gradient in Argentina (24°-38°S). This is the first study to quantify heat tolerance in South American populations and our work demonstrates that most of the populations surveyed have abundant within-population phenotypic variation, while still exhibiting significant variation among populations. The one exception was the most heat tolerant population that comes from a climate exhibiting the warmest annual mean temperature. All together our results suggest there is abundant genetic variation for heat-tolerance phenotypes within and among natural populations of Drosophila and this variation has likely been shaped by environmental temperature.
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Dale, Amy L; Lowry, Gregory V; Casman, Elizabeth A
2015-06-16
Mathematical models are needed to estimate environmental concentrations of engineered nanoparticles (NPs), which enter the environment upon the use and disposal of consumer goods and other products. We present a spatially resolved environmental fate model for the James River Basin, Virginia, that explores the influence of daily variation in streamflow, sediment transport, and stream loads from point and nonpoint sources on water column and sediment concentrations of zinc oxide (ZnO) and silver (Ag) NPs and their reaction byproducts over 20 simulation years. Spatial and temporal variability in sediment transport rates led to high NP transport such that less than 6% of NP-derived metals were retained in the river and sediments. Chemical transformations entirely eliminated ZnO NPs and doubled Zn mobility in the stream relative to Ag. Agricultural runoff accounted for 23% of total metal stream loads from NPs. Average NP-derived metal concentrations in the sediment varied spatially up to 9 orders of magnitude, highlighting the need for high-resolution models. Overall, our results suggest that "first generation" NP risk models have probably misrepresented NP fate in freshwater rivers due to low model resolutions and the simplification of NP chemistry and sediment transport.
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Soil resources and topography shape local tree community structure in tropical forests
Baldeck, Claire A.; Harms, Kyle E.; Yavitt, Joseph B.; John, Robert; Turner, Benjamin L.; Valencia, Renato; Navarrete, Hugo; Davies, Stuart J.; Chuyong, George B.; Kenfack, David; Thomas, Duncan W.; Madawala, Sumedha; Gunatilleke, Nimal; Gunatilleke, Savitri; Bunyavejchewin, Sarayudh; Kiratiprayoon, Somboon; Yaacob, Adzmi; Supardi, Mohd N. Nur; Dalling, James W.
2013-01-01
Both habitat filtering and dispersal limitation influence the compositional structure of forest communities, but previous studies examining the relative contributions of these processes with variation partitioning have primarily used topography to represent the influence of the environment. Here, we bring together data on both topography and soil resource variation within eight large (24–50 ha) tropical forest plots, and use variation partitioning to decompose community compositional variation into fractions explained by spatial, soil resource and topographic variables. Both soil resources and topography account for significant and approximately equal variation in tree community composition (9–34% and 5–29%, respectively), and all environmental variables together explain 13–39% of compositional variation within a plot. A large fraction of variation (19–37%) was spatially structured, yet unexplained by the environment, suggesting an important role for dispersal processes and unmeasured environmental variables. For the majority of sites, adding soil resource variables to topography nearly doubled the inferred role of habitat filtering, accounting for variation in compositional structure that would previously have been attributable to dispersal. Our results, illustrated using a new graphical depiction of community structure within these plots, demonstrate the importance of small-scale environmental variation in shaping local community structure in diverse tropical forests around the globe. PMID:23256196
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Fritts, Andrea K.; Peterson, James T.; Wisniewski, Jason M.; Bringolf, Robert B.
2015-01-01
The development of effective nonlethal biomonitoring techniques is imperative for the preservation of imperiled freshwater mussel populations. Changes in hemolymph chemistry profiles and tissue glycogen are potential biomarkers for nonlethally monitoring stress in mussels. We sampled three species in the Flint River Basin over 2 years to evaluate how these hemolymph and tissue biomarkers responded to environmental changes. We used hierarchical linear models to evaluate the relationships between variation in the biomarkers and environmental factors and found that the responses of the hemolymph and tissue parameters were strongly related to stream discharge. Shifts in alanine aminotransferase and glycogen showed the largest relations with discharge at the time of sampling, while magnesium levels were most explained by the discharge for 5 days prior to sampling. Aspartate aminotransferase, bicarbonate, and calcium showed the strongest relations with mean discharge for 15 days prior to sampling. The modeling results indicated that biomarker responses varied substantially among individuals of different size, sex, and species and illustrated the value of hierarchical modeling techniques to account for the inherent complexity of aquatic ecosystems.
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Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.; ...
2017-06-23
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.
Here, the maximum photosynthetic carboxylation rate (V cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr –1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated throughmore » to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated ( r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V cmax variation in the field, particularly in northern latitudes.« less
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NASA Astrophysics Data System (ADS)
Ren, W. X.; Lin, Y. Q.; Fang, S. E.
2011-11-01
One of the key issues in vibration-based structural health monitoring is to extract the damage-sensitive but environment-insensitive features from sampled dynamic response measurements and to carry out the statistical analysis of these features for structural damage detection. A new damage feature is proposed in this paper by using the system matrices of the forward innovation model based on the covariance-driven stochastic subspace identification of a vibrating system. To overcome the variations of the system matrices, a non-singularity transposition matrix is introduced so that the system matrices are normalized to their standard forms. For reducing the effects of modeling errors, noise and environmental variations on measured structural responses, a statistical pattern recognition paradigm is incorporated into the proposed method. The Mahalanobis and Euclidean distance decision functions of the damage feature vector are adopted by defining a statistics-based damage index. The proposed structural damage detection method is verified against one numerical signal and two numerical beams. It is demonstrated that the proposed statistics-based damage index is sensitive to damage and shows some robustness to the noise and false estimation of the system ranks. The method is capable of locating damage of the beam structures under different types of excitations. The robustness of the proposed damage detection method to the variations in environmental temperature is further validated in a companion paper by a reinforced concrete beam tested in the laboratory and a full-scale arch bridge tested in the field.
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Ben Sadok, Inès; Martinez, Sebastien; Moutier, Nathalie; Garcia, Gilbert; Leon, Lorenzo; Belaj, Angelina; De La Rosa, Raúl; Khadari, Bouchaib; Costes, Evelyne
2015-01-01
Climatic changes impact fruit tree growth and severely limit their production. Investigating the tree ability to cope with environmental variations is thus necessary to adapt breeding and management strategies in order to ensure sustainable production. In this study, we assessed the genetic parameters and genotype by environment interaction (GxE) during the early tree growth. One hundred and twenty olive seedlings derived from the cross 'Olivière' x 'Arbequina' were examined across two sites with contrasted environments, accounting for ontogenetic trends over three years. Models including the year of growth, branching order, environment, genotype effects, and their interactions were built with variance function and covariance structure of residuals when necessary. After selection of a model, broad sense heritabilities were estimated. Despite strong environmental effect on most traits, no GxE was found. Moreover, the internal structure of traits co-variation was similar in both sites. Ontogenetic growth variation, related to (i) the overall tree form and (ii) the growth and branching habit at growth unit scale, was not altered by the environment. Finally, a moderate to strong genetic control was identified for traits at the whole tree scale and at internode scale. Among all studied traits, the maximal internode length exhibited the highest heritability (H2 = 0.74). Considering the determinant role of this trait in tree architecture and its stability across environments, this study consolidates its relevance for breeding.
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Ben Sadok, Inès; Martinez, Sebastien; Moutier, Nathalie; Garcia, Gilbert; Leon, Lorenzo; Belaj, Angelina; De La Rosa, Raúl; Khadari, Bouchaib; Costes, Evelyne
2015-01-01
Climatic changes impact fruit tree growth and severely limit their production. Investigating the tree ability to cope with environmental variations is thus necessary to adapt breeding and management strategies in order to ensure sustainable production. In this study, we assessed the genetic parameters and genotype by environment interaction (GxE) during the early tree growth. One hundred and twenty olive seedlings derived from the cross ‘Olivière’ x ‘Arbequina’ were examined across two sites with contrasted environments, accounting for ontogenetic trends over three years. Models including the year of growth, branching order, environment, genotype effects, and their interactions were built with variance function and covariance structure of residuals when necessary. After selection of a model, broad sense heritabilities were estimated. Despite strong environmental effect on most traits, no GxE was found. Moreover, the internal structure of traits co-variation was similar in both sites. Ontogenetic growth variation, related to (i) the overall tree form and (ii) the growth and branching habit at growth unit scale, was not altered by the environment. Finally, a moderate to strong genetic control was identified for traits at the whole tree scale and at internode scale. Among all studied traits, the maximal internode length exhibited the highest heritability (H2 = 0.74). Considering the determinant role of this trait in tree architecture and its stability across environments, this study consolidates its relevance for breeding. PMID:26062090
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Temporal dynamic of malaria in a suburban area along the Niger River.
Sissoko, Mahamadou Soumana; Sissoko, Kourane; Kamate, Bourama; Samake, Yacouba; Goita, Siaka; Dabo, Abdoulaye; Yena, Mama; Dessay, Nadine; Piarroux, Renaud; Doumbo, Ogobara K; Gaudart, Jean
2017-10-23
Even if rainfall and temperature are factors classically associated to malaria, little is known about other meteorological factors, their variability and combinations related to malaria, in association with river height variations. Furthermore, in suburban area, urbanization and growing population density should be assessed in relation to these environmental factors. The aim of this study was to assess the impact of combined environmental, meteorological and hydrological factors on malaria incidence through time in the context of urbanization. Population observational data were prospectively collected. Clinical malaria was defined as the presence of parasites in addition to clinical symptoms. Meteorological and hydrological factors were measured daily. For each factors variation indices were estimated. Urbanization was yearly estimated assessing satellite imaging and field investigations. Principal component analysis was used for dimension reduction and factors combination. Lags between malaria incidences and the main components were assessed by cross-correlation functions. Generalized additive model was used to assess relative impact of different environmental components, taking into account lags, and modelling non-linear relationships. Change-point analysis was used to determine transmission periods within years. Malaria incidences were dominated by annual periodicity and varied through time without modification of the dynamic, with no impact of the urbanization. The main meteorological factor associated with malaria was a combination of evaporation, humidity and rainfall, with a lag of 3 months. The relationship between combined temperature factors showed a linear impact until reaching high temperatures limiting malaria incidence, with a lag 3.25 months. Height and variation of the river were related to malaria incidence (respectively 6 week lag and no lag). The study emphasizes no decreasing trend of malaria incidence despite accurate access to care and control strategies in accordance to international recommendations. Furthermore, no decreasing trend was showed despite the urbanization of the area. Malaria transmission remain increase 3 months after the beginning of the dry season. Addition to evaporation versus humidity/rainfall, nonlinear relationship for temperature and river height and variations have to be taken into account when implementing malaria control programmes.
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Sánchez-de la Vega, Guillermo; Castellanos-Morales, Gabriela; Gámez, Niza; Hernández-Rosales, Helena S.; Vázquez-Lobo, Alejandra; Aguirre-Planter, Erika; Jaramillo-Correa, Juan P.; Montes-Hernández, Salvador; Lira-Saade, Rafael; Eguiarte, Luis E.
2018-01-01
Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma, known in Mexico as calabaza pipiana, and its wild relative C. argyrosperma ssp. sororia. The main aim of this study was to use molecular data (microsatellites) to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia, and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia, in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs) for sororia to identify changes in this wild subspecies’ distribution from the Holocene (∼6,000 years ago) to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies (HE = 0.428 in sororia, and HE = 0.410 in argyrosperma). Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation (FST) among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango). We detected low levels of gene flow among populations at a regional scale (<0.01), except for the Yucatan Peninsula, and the northern portion of the Pacific Coast. Our analyses suggested that the Isthmus of Tehuantepec is an effective barrier isolating southern populations. Our SDM results indicate that environmental characteristics in the Balsas-Jalisco region, a potential center of domestication, were suitable for the presence of sororia during the Holocene. PMID:29662500
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Sánchez-de la Vega, Guillermo; Castellanos-Morales, Gabriela; Gámez, Niza; Hernández-Rosales, Helena S; Vázquez-Lobo, Alejandra; Aguirre-Planter, Erika; Jaramillo-Correa, Juan P; Montes-Hernández, Salvador; Lira-Saade, Rafael; Eguiarte, Luis E
2018-01-01
Analyses of genetic variation allow understanding the origin, diversification and genetic resources of cultivated plants. Domesticated taxa and their wild relatives are ideal systems for studying genetic processes of plant domestication and their joint is important to evaluate the distribution of their genetic resources. Such is the case of the domesticated subspecies C. argyrosperma ssp. argyrosperma , known in Mexico as calabaza pipiana , and its wild relative C. argyrosperma ssp. sororia . The main aim of this study was to use molecular data (microsatellites) to assess the levels of genetic variation and genetic differentiation within and among populations of domesticated argyrosperma across its distribution in Mexico in comparison to its wild relative, sororia , and to identify environmental suitability in previously proposed centers of domestication. We analyzed nine unlinked nuclear microsatellite loci to assess levels of diversity and distribution of genetic variation within and among populations in 440 individuals from 19 populations of cultivated landraces of argyrosperma and from six wild populations of sororia , in order to conduct a first systematic analysis of their genetic resources. We also used species distribution models (SDMs) for sororia to identify changes in this wild subspecies' distribution from the Holocene (∼6,000 years ago) to the present, and to assess the presence of suitable environmental conditions in previously proposed domestication sites. Genetic variation was similar among subspecies ( H E = 0.428 in sororia , and H E = 0.410 in argyrosperma ). Nine argyrosperma populations showed significant levels of inbreeding. Both subspecies are well differentiated, and genetic differentiation ( F ST ) among populations within each subspecies ranged from 0.152 to 0.652. Within argyrosperma we found three genetic groups (Northern Mexico, Yucatan Peninsula, including Michoacan and Veracruz, and Pacific coast plus Durango). We detected low levels of gene flow among populations at a regional scale (<0.01), except for the Yucatan Peninsula, and the northern portion of the Pacific Coast. Our analyses suggested that the Isthmus of Tehuantepec is an effective barrier isolating southern populations. Our SDM results indicate that environmental characteristics in the Balsas-Jalisco region, a potential center of domestication, were suitable for the presence of sororia during the Holocene.
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Evaluation of redundancy analysis to identify signatures of local adaptation.
Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric
2018-05-26
Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
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Modeled streamflow metrics on small, ungaged stream reaches in the Upper Colorado River Basin
Reynolds, Lindsay V.; Shafroth, Patrick B.
2016-01-20
Modeling streamflow is an important approach for understanding landscape-scale drivers of flow and estimating flows where there are no streamgage records. In this study conducted by the U.S. Geological Survey in cooperation with Colorado State University, the objectives were to model streamflow metrics on small, ungaged streams in the Upper Colorado River Basin and identify streams that are potentially threatened with becoming intermittent under drier climate conditions. The Upper Colorado River Basin is a region that is critical for water resources and also projected to experience large future climate shifts toward a drying climate. A random forest modeling approach was used to model the relationship between streamflow metrics and environmental variables. Flow metrics were then projected to ungaged reaches in the Upper Colorado River Basin using environmental variables for each stream, represented as raster cells, in the basin. Last, the projected random forest models of minimum flow coefficient of variation and specific mean daily flow were used to highlight streams that had greater than 61.84 percent minimum flow coefficient of variation and less than 0.096 specific mean daily flow and suggested that these streams will be most threatened to shift to intermittent flow regimes under drier climate conditions. Map projection products can help scientists, land managers, and policymakers understand current hydrology in the Upper Colorado River Basin and make informed decisions regarding water resources. With knowledge of which streams are likely to undergo significant drying in the future, managers and scientists can plan for stream-dependent ecosystems and human water users.
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Caenorhabditis elegans vulval cell fate patterning
NASA Astrophysics Data System (ADS)
Félix, Marie-Anne
2012-08-01
The spatial patterning of three cell fates in a row of competent cells is exemplified by vulva development in the nematode Caenorhabditis elegans. The intercellular signaling network that underlies fate specification is well understood, yet quantitative aspects remain to be elucidated. Quantitative models of the network allow us to test the effect of parameter variation on the cell fate pattern output. Among the parameter sets that allow us to reach the wild-type pattern, two general developmental patterning mechanisms of the three fates can be found: sequential inductions and morphogen-based induction, the former being more robust to parameter variation. Experimentally, the vulval cell fate pattern is robust to stochastic and environmental challenges, and minor variants can be detected. The exception is the fate of the anterior cell, P3.p, which is sensitive to stochastic variation and spontaneous mutation, and is also evolving the fastest. Other vulval precursor cell fates can be affected by mutation, yet little natural variation can be found, suggesting stabilizing selection. Despite this fate pattern conservation, different Caenorhabditis species respond differently to perturbations of the system. In the quantitative models, different parameter sets can reconstitute their response to perturbation, suggesting that network variation among Caenorhabditis species may be quantitative. Network rewiring likely occurred at longer evolutionary scales.
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Weiner, J; Kinsman, S; Williams, S
1998-11-01
We studied the growth of individual Xanthium strumarium plants growing at four naturally occurring local densities on a beach in Maine: (1) isolated plants, (2) pairs of plants ≤1 cm apart, (3) four plants within 4 cm of each other, and (4) discrete dense clumps of 10-39 plants. A combination of nondestructive measurements every 2 wk and parallel calibration harvests provided very good estimates of the growth in aboveground biomass of over 400 individual plants over 8 wk and afforded the opportunity to fit explicit growth models to 293 of them. There was large individual variation in growth and resultant size within the population and within all densities. Local crowding played a role in determining plant size within the population: there were significant differences in final size between all densities except pairs and quadruples, which were almost identical. Overall, plants growing at higher densities were more variable in growth and final size than plants growing at lower densities, but this was due to increased variation among groups (greater variation in local density and/or greater environmental heterogeneity), not to increased variation within groups. Thus, there was no evidence of size asymmetric competition in this population. The growth of most plants was close to exponential over the study period, but half the plants were slightly better fit by a sigmoidal (logistic) model. The proportion of plants better fit by the logistic model increased with density and with initial plant size. The use of explicit growth models over several growth intervals to describe stand development can provide more biological content and more statistical power than "growth-size" methods that analyze growth intervals separately.
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TRY – a global database of plant traits
Kattge, J; Díaz, S; Lavorel, S; Prentice, I C; Leadley, P; Bönisch, G; Garnier, E; Westoby, M; Reich, P B; Wright, I J; Cornelissen, J H C; Violle, C; Harrison, S P; Van Bodegom, P M; Reichstein, M; Enquist, B J; Soudzilovskaia, N A; Ackerly, D D; Anand, M; Atkin, O; Bahn, M; Baker, T R; Baldocchi, D; Bekker, R; Blanco, C C; Blonder, B; Bond, W J; Bradstock, R; Bunker, D E; Casanoves, F; Cavender-Bares, J; Chambers, J Q; Chapin, F S; Chave, J; Coomes, D; Cornwell, W K; Craine, J M; Dobrin, B H; Duarte, L; Durka, W; Elser, J; Esser, G; Estiarte, M; Fagan, W F; Fang, J; Fernández-Méndez, F; Fidelis, A; Finegan, B; Flores, O; Ford, H; Frank, D; Freschet, G T; Fyllas, N M; Gallagher, R V; Green, W A; Gutierrez, A G; Hickler, T; Higgins, S I; Hodgson, J G; Jalili, A; Jansen, S; Joly, C A; Kerkhoff, A J; Kirkup, D; Kitajima, K; Kleyer, M; Klotz, S; Knops, J M H; Kramer, K; Kühn, I; Kurokawa, H; Laughlin, D; Lee, T D; Leishman, M; Lens, F; Lenz, T; Lewis, S L; Lloyd, J; Llusià, J; Louault, F; Ma, S; Mahecha, M D; Manning, P; Massad, T; Medlyn, B E; Messier, J; Moles, A T; Müller, S C; Nadrowski, K; Naeem, S; Niinemets, Ü; Nöllert, S; Nüske, A; Ogaya, R; Oleksyn, J; Onipchenko, V G; Onoda, Y; Ordoñez, J; Overbeck, G; Ozinga, W A; Patiño, S; Paula, S; Pausas, J G; Peñuelas, J; Phillips, O L; Pillar, V; Poorter, H; Poorter, L; Poschlod, P; Prinzing, A; Proulx, R; Rammig, A; Reinsch, S; Reu, B; Sack, L; Salgado-Negret, B; Sardans, J; Shiodera, S; Shipley, B; Siefert, A; Sosinski, E; Soussana, J-F; Swaine, E; Swenson, N; Thompson, K; Thornton, P; Waldram, M; Weiher, E; White, M; White, S; Wright, S J; Yguel, B; Zaehle, S; Zanne, A E; Wirth, C
2011-01-01
Plant traits – the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs – determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation – but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.
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Tarroux, Arnaud; Bêty, Joël; Gauthier, Gilles; Berteaux, Dominique
2012-01-01
Inter-individual variation in diet within generalist animal populations is thought to be a widespread phenomenon but its potential causes are poorly known. Inter-individual variation can be amplified by the availability and use of allochthonous resources, i.e., resources coming from spatially distinct ecosystems. Using a wild population of arctic fox as a study model, we tested hypotheses that could explain variation in both population and individual isotopic niches, used here as proxy for the trophic niche. The arctic fox is an opportunistic forager, dwelling in terrestrial and marine environments characterized by strong spatial (arctic-nesting birds) and temporal (cyclic lemmings) fluctuations in resource abundance. First, we tested the hypothesis that generalist foraging habits, in association with temporal variation in prey accessibility, should induce temporal changes in isotopic niche width and diet. Second, we investigated whether within-population variation in the isotopic niche could be explained by individual characteristics (sex and breeding status) and environmental factors (spatiotemporal variation in prey availability). We addressed these questions using isotopic analysis and bayesian mixing models in conjunction with linear mixed-effects models. We found that: i) arctic fox populations can simultaneously undergo short-term (i.e., within a few months) reduction in both isotopic niche width and inter-individual variability in isotopic ratios, ii) individual isotopic ratios were higher and more representative of a marine-based diet for non-breeding than breeding foxes early in spring, and iii) lemming population cycles did not appear to directly influence the diet of individual foxes after taking their breeding status into account. However, lemming abundance was correlated to proportion of breeding foxes, and could thus indirectly affect the diet at the population scale.
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Tarroux, Arnaud; Bêty, Joël; Gauthier, Gilles; Berteaux, Dominique
2012-01-01
Inter-individual variation in diet within generalist animal populations is thought to be a widespread phenomenon but its potential causes are poorly known. Inter-individual variation can be amplified by the availability and use of allochthonous resources, i.e., resources coming from spatially distinct ecosystems. Using a wild population of arctic fox as a study model, we tested hypotheses that could explain variation in both population and individual isotopic niches, used here as proxy for the trophic niche. The arctic fox is an opportunistic forager, dwelling in terrestrial and marine environments characterized by strong spatial (arctic-nesting birds) and temporal (cyclic lemmings) fluctuations in resource abundance. First, we tested the hypothesis that generalist foraging habits, in association with temporal variation in prey accessibility, should induce temporal changes in isotopic niche width and diet. Second, we investigated whether within-population variation in the isotopic niche could be explained by individual characteristics (sex and breeding status) and environmental factors (spatiotemporal variation in prey availability). We addressed these questions using isotopic analysis and Bayesian mixing models in conjunction with linear mixed-effects models. We found that: i) arctic fox populations can simultaneously undergo short-term (i.e., within a few months) reduction in both isotopic niche width and inter-individual variability in isotopic ratios, ii) individual isotopic ratios were higher and more representative of a marine-based diet for non-breeding than breeding foxes early in spring, and iii) lemming population cycles did not appear to directly influence the diet of individual foxes after taking their breeding status into account. However, lemming abundance was correlated to proportion of breeding foxes, and could thus indirectly affect the diet at the population scale. PMID:22900021
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Forecasting seasonal hydrologic response in major river basins
NASA Astrophysics Data System (ADS)
Bhuiyan, A. M.
2014-05-01
Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts.
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Environmental variability and acoustic signals: a multi-level approach in songbirds.
Medina, Iliana; Francis, Clinton D
2012-12-23
Among songbirds, growing evidence suggests that acoustic adaptation of song traits occurs in response to habitat features. Despite extensive study, most research supporting acoustic adaptation has only considered acoustic traits averaged for species or populations, overlooking intraindividual variation of song traits, which may facilitate effective communication in heterogeneous and variable environments. Fewer studies have explicitly incorporated sexual selection, which, if strong, may favour variation across environments. Here, we evaluate the prevalence of acoustic adaptation among 44 species of songbirds by determining how environmental variability and sexual selection intensity are associated with song variability (intraindividual and intraspecific) and short-term song complexity. We show that variability in precipitation can explain short-term song complexity among taxonomically diverse songbirds, and that precipitation seasonality and the intensity of sexual selection are related to intraindividual song variation. Our results link song complexity to environmental variability, something previously found for mockingbirds (Family Mimidae). Perhaps more importantly, our results illustrate that individual variation in song traits may be shaped by both environmental variability and strength of sexual selection.
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Wu, Naicheng; Qu, Yueming; Guse, Björn; Makarevičiūtė, Kristė; To, Szewing; Riis, Tenna; Fohrer, Nicola
2018-03-01
There has been increasing interest in algae-based bioassessment, particularly, trait-based approaches are increasingly suggested. However, the main drivers, especially the contribution of hydrological variables, of species composition, trait composition, and beta diversity of algae communities are less studied. To link species and trait composition to multiple factors (i.e., hydrological variables, local environmental variables, and spatial factors) that potentially control species occurrence/abundance and to determine their relative roles in shaping species composition, trait composition, and beta diversities of pelagic algae communities, samples were collected from a German lowland catchment, where a well-proven ecohydrological modeling enabled to predict long-term discharges at each sampling site. Both trait and species composition showed significant correlations with hydrological, environmental, and spatial variables, and variation partitioning revealed that the hydrological and local environmental variables outperformed spatial variables. A higher variation of trait composition (57.0%) than species composition (37.5%) could be explained by abiotic factors. Mantel tests showed that both species and trait-based beta diversities were mostly related to hydrological and environmental heterogeneity with hydrological contributing more than environmental variables, while purely spatial impact was less important. Our findings revealed the relative importance of hydrological variables in shaping pelagic algae community and their spatial patterns of beta diversities, emphasizing the need to include hydrological variables in long-term biomonitoring campaigns and biodiversity conservation or restoration. A key implication for biodiversity conservation was that maintaining the instream flow regime and keeping various habitats among rivers are of vital importance. However, further investigations at multispatial and temporal scales are greatly needed.
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Schaub, Michael; Jakober, Hans; Stauber, Wolfgang
2011-10-01
Demographic rates of migratory species passing through several areas during their annual cycle may be affected by environmental conditions at each of these areas. Recent studies provide evidence that their impact is not necessarily immediate, but can be delayed. We studied survival, reproductive success and arrival date at the breeding grounds of red-backed shrikes Lanius collurio, a trans-Saharan migrant, in relation to weather and vegetation on the breeding grounds, the stopover sites during migration and in the wintering areas. These environmental factors are used as proxy of the shrike's food supply. We analysed detailed demographic data of some 4,600 individuals from 25 years with multistate capture-recapture and mixed models. Survival probabilities of juveniles and breeders of both sexes varied in parallel across time, suggesting that all cohorts were sensitive to similar causes of mortality. Reproductive performance increased with temperature and decreased with rainfall on the breeding area. Moreover, it increased with vegetation cover in the Sahelian stopover area used on autumn migration suggesting a carry-over effect. Arrival date was negatively affected by spring temperatures in the breeding area. Hence, demographic rates were affected by environmental factors on the breeding grounds, but also outside and elsewhere. This suggests that the shrike's population dynamics are driven by environmental factors operating at various scales of space and time. However, only a small amount of the temporal variation in demographic rates is explained by the environmental factors considered, suggesting that additional factors, such as those operating during migration, might be important.
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Biological and Environmental Influences on Parturition Date and Birth Mass of a Seasonal Breeder
Wolcott, Daniel M.; Reitz, Ryan L.; Weckerly, Floyd W.
2015-01-01
Natal features (e.g. Julian birth date and birth mass) often have fitness consequences and can be influenced by endogenous responses by the mother to seasonal fluctuations in nutritional quality and photoperiodic cues. We sought to further understand the biological and environmental factors that influence the natal features of a polytocous species in an environment with constant nutritional resources and limited seasonal variation. During a 36-year study we assessed the influence of biological factors (maternal age and litter type [i.e., litter size and sexual composition]) and environmental factors (total precipitation and mean maximum temperature during months encompassing conception, the last trimester of gestation, and the entire length of gestation) on Julian birth date and birth mass using linear-mixed effects models. Linear and quadratic functions of maternal age influenced both natal features with earliest Julian birth dates and heaviest birth masses occurring at prime-age and older individuals, which ranged from 5–9 years of age. Litter type influenced Julian birth date and birth mass. Interestingly, environmental factors affected Julian birth date and birth mass even though mothers were continuously allowed access to a high-quality diet. Random effects revealed considerable variation among mothers and years. This study demonstrates that, in long-lived polytocous species, environmental factors may have a greater influence on natal features than previously supposed and the influence from biological factors is also complex. The documented responses to environmental influences provide unique insights into how mammalian seasonal reproductive dynamics may respond to current changes in climate. PMID:25885545
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Biological and environmental influences on parturition date and birth mass of a seasonal breeder.
Wolcott, Daniel M; Reitz, Ryan L; Weckerly, Floyd W
2015-01-01
Natal features (e.g. Julian birth date and birth mass) often have fitness consequences and can be influenced by endogenous responses by the mother to seasonal fluctuations in nutritional quality and photoperiodic cues. We sought to further understand the biological and environmental factors that influence the natal features of a polytocous species in an environment with constant nutritional resources and limited seasonal variation. During a 36-year study we assessed the influence of biological factors (maternal age and litter type [i.e., litter size and sexual composition]) and environmental factors (total precipitation and mean maximum temperature during months encompassing conception, the last trimester of gestation, and the entire length of gestation) on Julian birth date and birth mass using linear-mixed effects models. Linear and quadratic functions of maternal age influenced both natal features with earliest Julian birth dates and heaviest birth masses occurring at prime-age and older individuals, which ranged from 5-9 years of age. Litter type influenced Julian birth date and birth mass. Interestingly, environmental factors affected Julian birth date and birth mass even though mothers were continuously allowed access to a high-quality diet. Random effects revealed considerable variation among mothers and years. This study demonstrates that, in long-lived polytocous species, environmental factors may have a greater influence on natal features than previously supposed and the influence from biological factors is also complex. The documented responses to environmental influences provide unique insights into how mammalian seasonal reproductive dynamics may respond to current changes in climate.
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Ecogeography, genetics, and the evolution of human body form.
Roseman, Charles C; Auerbach, Benjamin M
2015-01-01
Genetic resemblances among groups are non-randomly distributed in humans. This population structure may influence the correlations between traits and environmental drivers of natural selection thus complicating the interpretation of the fossil record when modern human variation is used as a referential model. In this paper, we examine the effects of population structure and natural selection on postcranial traits that reflect body size and shape with application to the more general issue of how climate - using latitude as a proxy - has influenced hominin morphological variation. We compare models that include terms reflecting population structure, ascertained from globally distributed microsatellite data, and latitude on postcranial phenotypes derived from skeletal dimensions taken from a large global sample of modern humans. We find that models with a population structure term fit better than a model of natural selection along a latitudinal cline in all cases. A model including both latitude and population structure terms is a good fit to distal limb element lengths and bi-iliac breadth, indicating that multiple evolutionary forces shaped these morphologies. In contrast, a model that included only a population structure term best explained femoral head diameter and the crural index. The results demonstrate that population structure is an important part of human postcranial variation, and that clinally distributed natural selection is not sufficient to explain among-group differentiation. The distribution of human body form is strongly influenced by the contingencies of modern human origins, which calls for new ways to approach problems in the evolution of human variation, past and present. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Langseth, Brian J.; Jones, Michael L.; Riley, Stephen C.
2014-01-01
Ecopath with Ecosim (EwE) is a widely used modeling tool in fishery research and management. Ecopath requires a mass-balanced snapshot of a food web at a particular point in time, which Ecosim then uses to simulate changes in biomass over time. Initial inputs to Ecopath, including estimates for biomasses, production to biomass ratios, consumption to biomass ratios, and diets, rarely produce mass balance, and thus ad hoc changes to inputs are required to balance the model. There has been little previous research of whether ad hoc changes to achieve mass balance affect Ecosim simulations. We constructed an EwE model for the offshore community of Lake Huron, and balanced the model using four contrasting but realistic methods. The four balancing methods were based on two contrasting approaches; in the first approach, production of unbalanced groups was increased by increasing either biomass or the production to biomass ratio, while in the second approach, consumption of predators on unbalanced groups was decreased by decreasing either biomass or the consumption to biomass ratio. We compared six simulation scenarios based on three alternative assumptions about the extent to which mortality rates of prey can change in response to changes in predator biomass (i.e., vulnerabilities) under perturbations to either fishing mortality or environmental production. Changes in simulated biomass values over time were used in a principal components analysis to assess the comparative effect of balancing method, vulnerabilities, and perturbation types. Vulnerabilities explained the most variation in biomass, followed by the type of perturbation. Choice of balancing method explained little of the overall variation in biomass. Under scenarios where changes in predator biomass caused large changes in mortality rates of prey (i.e., high vulnerabilities), variation in biomass was greater than when changes in predator biomass caused only small changes in mortality rates of prey (i.e., low vulnerabilities), and was amplified when environmental production was increased. When standardized to mean changes in biomass within each scenario, scenarios when vulnerabilities were low and when fishing mortality was increased explained the most variation in biomass. Our findings suggested that approaches to balancing Ecopath models have relatively little effect on changes in biomass over time, especially when compared to assumptions about how mortality rates of prey change in response to changes in predator biomass. We concluded that when constructing food-web models using EwE, determining the effect of changes in predator biomass on mortality rates of prey should be prioritized over determining the best way to balance the model.
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Nakayama, Madoka; Shoji, Wataru
2017-01-01
As with many living organisms, bacteria often live on the surface of solids, such as foods, organisms, buildings and soil. Compared with dispersive behavior in liquid, bacteria on surface environment exhibit significantly restricted mobility. They have access to only limited resources and cannot be liberated from the changing environment. Accordingly, appropriate collective strategies are necessarily required for long-term growth and survival. However, in spite of our deepening knowledge of the structure and characteristics of individual cells, strategic self-organizing dynamics of their community is poorly understood and therefore not yet predictable. Here, we report a morphological change in Bacillus subtilis biofilms due to environmental pH variations, and present a mathematical model for the macroscopic spatio-temporal dynamics. We show that an environmental pH shift transforms colony morphology on hard agar media from notched ‘volcano-like’ to round and front-elevated ‘crater-like’. We discover that a pH-dependent dose-response relationship between nutritional resource level and quantitative bacterial motility at the population level plays a central role in the mechanism of the spatio-temporal cell population structure design in biofilms. PMID:28253348
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Predicting evolutionary rescue via evolving plasticity in stochastic environments
Baskett, Marissa L.
2016-01-01
Phenotypic plasticity and its evolution may help evolutionary rescue in a novel and stressful environment, especially if environmental novelty reveals cryptic genetic variation that enables the evolution of increased plasticity. However, the environmental stochasticity ubiquitous in natural systems may alter these predictions, because high plasticity may amplify phenotype–environment mismatches. Although previous studies have highlighted this potential detrimental effect of plasticity in stochastic environments, they have not investigated how it affects extinction risk in the context of evolutionary rescue and with evolving plasticity. We investigate this question here by integrating stochastic demography with quantitative genetic theory in a model with simultaneous change in the mean and predictability (temporal autocorrelation) of the environment. We develop an approximate prediction of long-term persistence under the new pattern of environmental fluctuations, and compare it with numerical simulations for short- and long-term extinction risk. We find that reduced predictability increases extinction risk and reduces persistence because it increases stochastic load during rescue. This understanding of how stochastic demography, phenotypic plasticity, and evolution interact when evolution acts on cryptic genetic variation revealed in a novel environment can inform expectations for invasions, extinctions, or the emergence of chemical resistance in pests. PMID:27655762
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Maalouf, Amani; El-Fadel, Mutasem
2017-11-01
In this study, the carbon footprint of introducing a food waste disposer (FWD) policy was examined in the context of its implications on solid waste and wastewater management with economic assessment of environmental externalities emphasizing potential carbon credit and increased sludge generation. For this purpose, a model adopting a life cycle inventory approach was developed to integrate solid waste and wastewater management processes under a single framework and test scenarios for a waste with high organic food content typical of developing economies. For such a waste composition, the results show that a FWD policy can reduce emissions by nearly ∼42% depending on market penetration, fraction of food waste ground, as well as solid waste and wastewater management schemes, including potential energy recovery. In comparison to baseline, equivalent economic gains can reach ∼28% when environmental externalities including sludge management and emissions variations are considered. The sensitivity analyses on processes with a wide range in costs showed an equivalent economic impact thus emphasizing the viability of a FWD policy although the variation in the cost of sludge management exhibited a significant impact on savings. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Tasaki, Sohei; Nakayama, Madoka; Shoji, Wataru
2017-01-01
As with many living organisms, bacteria often live on the surface of solids, such as foods, organisms, buildings and soil. Compared with dispersive behavior in liquid, bacteria on surface environment exhibit significantly restricted mobility. They have access to only limited resources and cannot be liberated from the changing environment. Accordingly, appropriate collective strategies are necessarily required for long-term growth and survival. However, in spite of our deepening knowledge of the structure and characteristics of individual cells, strategic self-organizing dynamics of their community is poorly understood and therefore not yet predictable. Here, we report a morphological change in Bacillus subtilis biofilms due to environmental pH variations, and present a mathematical model for the macroscopic spatio-temporal dynamics. We show that an environmental pH shift transforms colony morphology on hard agar media from notched 'volcano-like' to round and front-elevated 'crater-like'. We discover that a pH-dependent dose-response relationship between nutritional resource level and quantitative bacterial motility at the population level plays a central role in the mechanism of the spatio-temporal cell population structure design in biofilms.
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Ergon, T; Ergon, R
2017-03-01
Genetic assimilation emerges from selection on phenotypic plasticity. Yet, commonly used quantitative genetics models of linear reaction norms considering intercept and slope as traits do not mimic the full process of genetic assimilation. We argue that intercept-slope reaction norm models are insufficient representations of genetic effects on linear reaction norms and that considering reaction norm intercept as a trait is unfortunate because the definition of this trait relates to a specific environmental value (zero) and confounds genetic effects on reaction norm elevation with genetic effects on environmental perception. Instead, we suggest a model with three traits representing genetic effects that, respectively, (i) are independent of the environment, (ii) alter the sensitivity of the phenotype to the environment and (iii) determine how the organism perceives the environment. The model predicts that, given sufficient additive genetic variation in environmental perception, the environmental value at which reaction norms tend to cross will respond rapidly to selection after an abrupt environmental change, and eventually becomes equal to the new mean environment. This readjustment of the zone of canalization becomes completed without changes in genetic correlations, genetic drift or imposing any fitness costs of maintaining plasticity. The asymptotic evolutionary outcome of this three-trait linear reaction norm generally entails a lower degree of phenotypic plasticity than the two-trait model, and maximum expected fitness does not occur at the mean trait values in the population. © 2016 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.
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Arnan, Xavier; Cerdá, Xim; Retana, Javier
2015-01-01
We analyze the relative contribution of environmental and spatial variables to the alpha and beta components of taxonomic (TD), phylogenetic (PD), and functional (FD) diversity in ant communities found along different climate and anthropogenic disturbance gradients across western and central Europe, in order to assess the mechanisms structuring ant biodiversity. To this aim we calculated alpha and beta TD, PD, and FD for 349 ant communities, which included a total of 155 ant species; we examined 10 functional traits and phylogenetic relatedness. Variation partitioning was used to examine how much variation in ant diversity was explained by environmental and spatial variables. Autocorrelation in diversity measures and each trait's phylogenetic signal were also analyzed. We found strong autocorrelation in diversity measures. Both environmental and spatial variables significantly contributed to variation in TD, PD, and FD at both alpha and beta scales; spatial structure had the larger influence. The different facets of diversity showed similar patterns along environmental gradients. Environment explained a much larger percentage of variation in FD than in TD or PD. All traits demonstrated strong phylogenetic signals. Our results indicate that environmental filtering and dispersal limitations structure all types of diversity in ant communities. Strong dispersal limitations appear to have led to clustering of TD, PD, and FD in western and central Europe, probably because different historical and evolutionary processes generated different pools of species. Remarkably, these three facets of diversity showed parallel patterns along environmental gradients. Trait-mediated species sorting and niche conservatism appear to structure ant diversity, as evidenced by the fact that more variation was explained for FD and that all traits had strong phylogenetic signals. Since environmental variables explained much more variation in FD than in PD, functional diversity should be a better indicator of community assembly processes than phylogenetic diversity.
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Spatiotemporal Interpolation for Environmental Modelling
Susanto, Ferry; de Souza, Paulo; He, Jing
2016-01-01
A variation of the reduction-based approach to spatiotemporal interpolation (STI), in which time is treated independently from the spatial dimensions, is proposed in this paper. We reviewed and compared three widely-used spatial interpolation techniques: ordinary kriging, inverse distance weighting and the triangular irregular network. We also proposed a new distribution-based distance weighting (DDW) spatial interpolation method. In this study, we utilised one year of Tasmania’s South Esk Hydrology model developed by CSIRO. Root mean squared error statistical methods were performed for performance evaluations. Our results show that the proposed reduction approach is superior to the extension approach to STI. However, the proposed DDW provides little benefit compared to the conventional inverse distance weighting (IDW) method. We suggest that the improved IDW technique, with the reduction approach used for the temporal dimension, is the optimal combination for large-scale spatiotemporal interpolation within environmental modelling applications. PMID:27509497
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Faris, A M; Wang, H-H; Tarone, A M; Grant, W E
2016-05-31
Estimates of insect age can be informative in death investigations and, when certain assumptions are met, can be useful for estimating the postmortem interval (PMI). Currently, the accuracy and precision of PMI estimates is unknown, as error can arise from sources of variation such as measurement error, environmental variation, or genetic variation. Ecological models are an abstract, mathematical representation of an ecological system that can make predictions about the dynamics of the real system. To quantify the variation associated with the pre-appearance interval (PAI), we developed an ecological model that simulates the colonization of vertebrate remains by Cochliomyia macellaria (Fabricius) (Diptera: Calliphoridae), a primary colonizer in the southern United States. The model is based on a development data set derived from a local population and represents the uncertainty in local temperature variability to address PMI estimates at local sites. After a PMI estimate is calculated for each individual, the model calculates the maximum, minimum, and mean PMI, as well as the range and standard deviation for stadia collected. The model framework presented here is one manner by which errors in PMI estimates can be addressed in court when no empirical data are available for the parameter of interest. We show that PAI is a potential important source of error and that an ecological model is one way to evaluate its impact. Such models can be re-parameterized with any development data set, PAI function, temperature regime, assumption of interest, etc., to estimate PMI and quantify uncertainty that arises from specific prediction systems. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Rakowski, Andrzej Z; Nakamura, Toshio; Pazdur, Anna
2008-10-01
Radiocarbon concentration in the atmosphere is significantly lower in areas where man-made emissions of carbon dioxide occur. This phenomenon is known as Suess effect, and is caused by the contamination of clean air with non-radioactive carbon from fossil fuel combustion. The effect is more strongly observed in industrial and densely populated urban areas. Measurements of carbon isotope concentrations in a study area can be compared to those from areas of clear air in order to estimate the amount of carbon dioxide emission from fossil fuel combustion by using a simple mathematical model. This can be calculated using the simple mathematical model. The result of the mathematical model followed in this study suggests that the use of annual rings of trees to obtain the secular variations of 14C concentration of atmospheric CO2 can be useful and efficient for environmental monitoring and modeling of the carbon distribution in local scale.
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Lü, Xiao-Tao; Reed, Sasha C.; Hou, Shuang-Li; Hu, Yan-Yu; Wei, Hai-Wei; Lü, Fu-Mei; Cui, Qiang; Han, Xing Guo
2017-01-01
Plant nutrient concentrations and stoichiometry drive fundamental ecosystem processes, with important implications for primary production, diversity, and ecosystem sustainability. While a range of evidence exists regarding how plant nutrients vary across spatial scales, our understanding of their temporal variation remains less well understood. Nevertheless, we know nutrients regulate plant function across time, and that important temporal controls could strongly interact with environmental change. Here, we report results from a 3-year assessment of inter-annual changes of foliar nitrogen (N) and phosphorus (P) concentrations and stoichiometry in three dominant grasses in response to N deposition and prescribed fire in a temperate steppe of northern China. Foliar N and P concentrations and their ratios varied greatly among years, with this temporal variation strongly related to inter-annual variation in precipitation. Nitrogen deposition significantly increased foliar N concentrations and N:P ratios in all species, while fire significantly altered foliar N and P concentrations but had no significant impacts on N:P ratios. Generally, N addition enhanced the temporal stability of foliar N and decreased that of foliar P and of N:P ratios. Our results indicate that plant nutrient status and response to environmental change are temporally dynamic and that there are differential effects on the interactions between environmental change drivers and timing for different nutrients. These responses have important implications for consideration of global change effects on plant community structure and function, management strategies, and the modeling of biogeochemical cycles under global change scenarios.
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Lathouri, Maria; Korre, Anna
2015-12-15
Although significant progress has been made in understanding how environmental factors modify the speciation, bioavailability and toxicity of metals such as copper in aquatic environments, the current methods used to establish water quality standards do not necessarily consider the different geological and geochemical characteristics of a given site and the factors that affect copper fate, bioavailability potential and toxicity. In addition, the temporal variation in the concentration and bioavailable metal fraction is also important in freshwater systems. The work presented in this paper illustrates the temporal and seasonal variability of a range of water quality parameters, and Cu speciation, bioavailability and toxicity at four freshwaters sites in the UK. Rivers Coquet, Cree, Lower Clyde and Eden (Kent) were selected to cover a broad range of different geochemical environments and site characteristics. The monitoring data used covered a period of around six years at almost monthly intervals. Chemical equilibrium modelling was used to study temporal variations in Cu speciation and was combined with acute toxicity modelling to assess Cu bioavailability for two aquatic species, Daphnia magna and Daphnia pulex. The estimated copper bioavailability, toxicity levels and the corresponding ecosystem risks were analysed in relation to key water quality parameters (alkalinity, pH and DOC). Although copper concentrations did not vary much during the sampling period or between the seasons at the different sites; copper bioavailability varied markedly. In addition, through the chronic-Cu BLM-based on the voluntary risk assessment approach, the potential environmental risk in terms of the chronic toxicity was assessed. A much higher likelihood of toxicity effects was found during the cold period at all sites. It is suggested that besides the metal (copper) concentration in the surface water environment, the variability and seasonality of other important water quality parameters should be considered in setting appropriately protective environmental quality standards for metals. Copyright © 2015 Elsevier B.V. All rights reserved.
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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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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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Measuring environmental efficiency of agricultural water use: a Luenberger environmental indicator.
Azad, Md A S; Ancev, Tihomir
2014-12-01
Irrigated agriculture creates substantial environmental pressures by withdrawing large quantities of water, leaving rivers and wetlands empty and unable to support the valuable ecosystems that depend on the water resource. The key challenge facing society is that of balancing water extractions for agricultural production and other uses with provision of appropriate environmental flow to maintain healthy rivers and wetlands. Measuring tradeoffs between economic gain of water use in agriculture and its environmental pressures can contribute to constructing policy instruments for improved water resource management. The aim of this paper is to develop a modelling framework to measure these tradeoffs. Using a new approach - Luenberger environmental indicator - the study derives environmental efficiency scores for various types of irrigation enterprises across seventeen natural resource management regions within the Murray-Darling Basin, Australia. Findings show that there is a substantial variation in environmental performance of irrigation enterprises across the regions. Some enterprises were found to be relatively environmentally efficient in some regions, but they were not efficient in others. The environmental efficiency scores could be used as a guideline for formulating regional policy and strategy to achieve sustainable water use in the agricultural sector. Copyright © 2014 Elsevier Ltd. All rights reserved.
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NASA Technical Reports Server (NTRS)
Bubenheim, David L.; Schlick, Greg; Genovese, Vanessa; Wilson, Kenneth D.
2018-01-01
Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta.
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Merkle, Jerod A.; Cross, Paul C.; Scurlock, Brandon M.; Cole, Eric K.; Courtemanch, Alyson B.; Dewey, Sarah R.; Kauffman, Matthew J.
2018-01-01
Disease models typically focus on temporal dynamics of infection, while often neglecting environmental processes that determine host movement. In many systems, however, temporal disease dynamics may be slow compared to the scale at which environmental conditions alter host space-use and accelerate disease transmission.Using a mechanistic movement modelling approach, we made space-use predictions of a mobile host (elk [Cervus Canadensis] carrying the bacterial disease brucellosis) under environmental conditions that change daily and annually (e.g., plant phenology, snow depth), and we used these predictions to infer how spring phenology influences the risk of brucellosis transmission from elk (through aborted foetuses) to livestock in the Greater Yellowstone Ecosystem.Using data from 288 female elk monitored with GPS collars, we fit step selection functions (SSFs) during the spring abortion season and then implemented a master equation approach to translate SSFs into predictions of daily elk distribution for five plausible winter weather scenarios (from a heavy snow, to an extreme winter drought year). We predicted abortion events by combining elk distributions with empirical estimates of daily abortion rates, spatially varying elk seroprevelance and elk population counts.Our results reveal strong spatial variation in disease transmission risk at daily and annual scales that is strongly governed by variation in host movement in response to spring phenology. For example, in comparison with an average snow year, years with early snowmelt are predicted to have 64% of the abortions occurring on feedgrounds shift to occurring on mainly public lands, and to a lesser extent on private lands.Synthesis and applications. Linking mechanistic models of host movement with disease dynamics leads to a novel bridge between movement and disease ecology. Our analysis framework offers new avenues for predicting disease spread, while providing managers tools to proactively mitigate risks posed by mobile disease hosts. More broadly, we demonstrate how mechanistic movement models can provide predictions of ecological conditions that are consistent with climate change but may be more extreme than has been observed historically.
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NASA Astrophysics Data System (ADS)
Jin, Chenhao; Li, Jingcheng; Jang, Shinae; Sun, Xiaorong; Christenson, Richard
2015-03-01
Structural health monitoring has drawn significant attention in the past decades with numerous methodologies and applications for civil structural systems. Although many researchers have developed analytical and experimental damage detection algorithms through vibration-based methods, these methods are not widely accepted for practical structural systems because of their sensitivity to uncertain environmental and operational conditions. The primary environmental factor that influences the structural modal properties is temperature. The goal of this article is to analyze the natural frequency-temperature relationships and detect structural damage in the presence of operational and environmental variations using modal-based method. For this purpose, correlations between natural frequency and temperature are analyzed to select proper independent variables and inputs for the multiple linear regression model and neural network model. In order to capture the changes of natural frequency, confidence intervals to detect the damages for both models are generated. A long-term structural health monitoring system was installed on an in-service highway bridge located in Meriden, Connecticut to obtain vibration and environmental data. Experimental testing results show that the variability of measured natural frequencies due to temperature is captured, and the temperature-induced changes in natural frequencies have been considered prior to the establishment of the threshold in the damage warning system. This novel approach is applicable for structural health monitoring system and helpful to assess the performance of the structure for bridge management and maintenance.
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Timing of breeding in variable environments: tropical birds as model systems.
Hau, M
2001-09-01
Animals need to adjust reproductive decisions to environmental seasonality. In contrast to species from the well-studied temperate zones, little is known for tropical birds about the environmental cues that stimulate reproductive activity and the physiological mechanisms that regulate reproduction. I am investigating the environmental and endocrine mechanisms that underlie the timing of reproduction in spotted antbirds from the near-equatorial Panamanian rainforest and in small ground finches from the equatorial arid Galápagos islands. Spotted antbirds live in a fairly predictable seasonal environment and show regular changes in gonad sizes and some reproductive hormones. Despite the small annual variation in photoperiod close to the equator, these birds can measure slight photoperiodic increases and use it to initiate reproductive activity. Spotted antbirds also respond to seasonal changes in food availability, which allows them to flexibly adjust gonad growth to environmental conditions. Testosterone is involved in regulating song and aggressive behavior in these year-round territorial birds, although it can remain at low plasma levels throughout the year. In contrast, small ground finches exposed to a rather unpredictable climate on Galápagos appear to grow their gonads whenever heavy rains fall and have regressed gonads during other times of the year. The lack of a physiological preparation for the breeding season and their response to short-term cues related to rainfall indicate a striking flexibility in the regulation of breeding in small ground finches. I suggest that tropical birds can serve as model systems to study the physiological adaptations to different environments. Unraveling the neuroendocrine mechanisms behind the flexibility in reproductive timing will clarify whether differences found between temperate and tropical birds represent variations of the same basic mechanism or instead reflect a fundamental divergence in physiological control systems. Copyright 2001 Academic Press.
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Environmental flow assessments for transformed estuaries
NASA Astrophysics Data System (ADS)
Sun, Tao; Zhang, Heyue; Yang, Zhifeng; Yang, Wei
2015-01-01
Here, we propose an approach to environmental flow assessment that considers spatial pattern variations in potential habitats affected by river discharges and tidal currents in estuaries. The approach comprises four steps: identifying and simulating the distributions of critical environmental factors for habitats of typical species in an estuary; mapping of suitable habitats based on spatial distributions of the Habitat Suitability Index (HSI) and adopting the habitat aggregation index to understand fragmentation of potential suitable habitats; defining variations in water requirements for a certain species using trade-off analysis for different protection objectives; and recommending environmental flows in the estuary considering the compatibility and conflict of freshwater requirements for different species. This approach was tested using a case study in the Yellow River Estuary. Recommended environmental flows were determined by incorporating the requirements of four types of species into the assessments. Greater variability in freshwater inflows could be incorporated into the recommended environmental flows considering the adaptation of potential suitable habitats with variations in the flow regime. Environmental flow allocations should be conducted in conjunction with land use conflict management in estuaries. Based on the results presented here, the proposed approach offers flexible assessment of environmental flow for aquatic ecosystems that may be subject to future change.
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NASA Astrophysics Data System (ADS)
Fernandes, Sheryl Oliveira; Gonsalves, Maria-Judith; Michotey, Valérie D.; Bonin, Patricia C.; Loka, A.; Bharathi, P.
2013-10-01
Denitrification activity (DNT) and associated environmental parameters were examined in two mangrove ecosystems of Goa, India - the relatively unimpacted Tuvem and the anthropogenically-influenced Divar. Sampling was carried out at every 2 cm interval within the 0-10 cm depth range to determine (1) seasonal (pre-monsoon, monsoon and post-monsoon) down-core variation in DNT (2) assess the environmental factors influencing the DNT and (3) to build predictive models for benthic DNT. Denitrification generally decreased with depth and showed marked seasonal variation at both the locations. Denitrification peaked during the pre-monsoon occurring at a rate of up to 21.00 ± 12.84 nmol N2O g-1 h-1 within 0-4 cm at both the locations. Further, DNT at pre-monsoon was significantly influenced by Fe content at Tuvem and Divar suggesting Fe-mediated nitrate respiration. The influence of other limiting substrates such as NO3- and NO2- was most important during the monsoon and post-monsoon especially at Divar. The multiple regression models developed could predict 67-98% of the observed variability in DNT through the seasons. About 6-9 environmental variables were required to relatively well-predict DNT in these sediments with the complexity governing DNT decreasing from pre-monsoon to post-monsoon. Our results reveal that seasonal dynamics of DNT in tropical mangrove sediments are closely linked to the total Fe at the prevailing ambient concentration in both the systems.
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Ecosystem effects of environmental flows: Modelling and experimental floods in a dryland river
Shafroth, P.B.; Wilcox, A.C.; Lytle, D.A.; Hickey, J.T.; Andersen, D.C.; Beauchamp, Vanessa B.; Hautzinger, A.; McMullen, L.E.; Warner, A.
2010-01-01
Successful environmental flow prescriptions require an accurate understanding of the linkages among flow events, geomorphic processes and biotic responses. We describe models and results from experimental flow releases associated with an environmental flow program on the Bill Williams River (BWR), Arizona, in arid to semiarid western U.S.A. Two general approaches for improving knowledge and predictions of ecological responses to environmental flows are: (1) coupling physical system models to ecological responses and (2) clarifying empirical relationships between flow and ecological responses through implementation and monitoring of experimental flow releases. We modelled the BWR physical system using: (1) a reservoir operations model to simulate reservoir releases and reservoir water levels and estimate flow through the river system under a range of scenarios, (2) one- and two-dimensional river hydraulics models to estimate stage-discharge relationships at the whole-river and local scales, respectively, and (3) a groundwater model to estimate surface- and groundwater interactions in a large, alluvial valley on the BWR where surface flow is frequently absent. An example of a coupled, hydrology-ecology model is the Ecosystems Function Model, which we used to link a one-dimensional hydraulic model with riparian tree seedling establishment requirements to produce spatially explicit predictions of seedling recruitment locations in a Geographic Information System. We also quantified the effects of small experimental floods on the differential mortality of native and exotic riparian trees, on beaver dam integrity and distribution, and on the dynamics of differentially flow-adapted benthic macroinvertebrate groups. Results of model applications and experimental flow releases are contributing to adaptive flow management on the BWR and to the development of regional environmental flow standards. General themes that emerged from our work include the importance of response thresholds, which are commonly driven by geomorphic thresholds or mediated by geomorphic processes, and the importance of spatial and temporal variation in the effects of flows on ecosystems, which can result from factors such as longitudinal complexity and ecohydrological feedbacks. ?? Published 2009.
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Modeling aeolian dune and dune field evolution
NASA Astrophysics Data System (ADS)
Diniega, Serina
Aeolian sand dune morphologies and sizes are strongly connected to the environmental context and physical processes active since dune formation. As such, the patterns and measurable features found within dunes and dune fields can be interpreted as records of environmental conditions. Using mathematical models of dune and dune field evolution, it should be possible to quantitatively predict dune field dynamics from current conditions or to determine past field conditions based on present-day observations. In this dissertation, we focus on the construction and quantitative analysis of a continuum dune evolution model. We then apply this model towards interpretation of the formative history of terrestrial and martian dunes and dune fields. Our first aim is to identify the controls for the characteristic lengthscales seen in patterned dune fields. Variations in sand flux, binary dune interactions, and topography are evaluated with respect to evolution of individual dunes. Through the use of both quantitative and qualitative multiscale models, these results are then extended to determine the role such processes may play in (de)stabilization of the dune field. We find that sand flux variations and topography generally destabilize dune fields, while dune collisions can yield more similarly-sized dunes. We construct and apply a phenomenological macroscale dune evolution model to then quantitatively demonstrate how dune collisions cause a dune field to evolve into a set of uniformly-sized dunes. Our second goal is to investigate the influence of reversing winds and polar processes in relation to dune slope and morphology. Using numerical experiments, we investigate possible causes of distinctive morphologies seen in Antarctic and martian polar dunes. Finally, we discuss possible model extensions and needed observations that will enable the inclusion of more realistic physical environments in the dune and dune field evolution models. By elucidating the qualitative and quantitative connections between environmental conditions, physical processes, and resultant dune and dune field morphologies, this research furthers our ability to interpret spacecraft images of dune fields, and to use present-day observations to improve our understanding of past terrestrial and martian environments.
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Yang, Wen; Zheng, Zhongming; Zheng, Cheng; Lu, Kaihong; Ding, Dewen; Zhu, Jinyong
2018-01-15
The phytoplankton community structure is potentially influenced by both extrinsic effects originating from the surrounding environment and intrinsic effects relying on interspecific interactions between two species. However, few studies have simultaneously considered both types of effects and assessed the relative importance of these factors. In this study, we used data collected over nine months (August 2012-May 2013) from a typical subtropical reservoir in southeast China to analyze the temporal variation of its phytoplankton community structure and develop a quantitative understanding of the extrinsic and intrinsic effects on phytoplankton community dynamics. Significant temporal variations were observed in environmental variables as well as the phytoplankton and zooplankton communities, whereas their variational trajectories and directions were entirely different. Variance partitioning analysis showed that extrinsic factors significantly explained only 31% of the variation in the phytoplankton community, thus suggesting that these factors were incomplete predictors of the community structure. Random forest-based models showed that 48% of qualified responsible phytoplankton species were more accurately predicted by phytoplankton-only models, which revealed clear effects of interspecific species-to-species interactions. Furthermore, we used association networks to model the interactions among phytoplankton, zooplankton and the environment. Network comparisons indicated that interspecific interactions were widely present in the phytoplankton community and dominated the network rather than those between phytoplankton and extrinsic factors. These findings expand the current understanding of the underlying mechanisms that govern phytoplankton community dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.
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Obesity, hypertension and genetic variation in the TIGER Study
USDA-ARS?s Scientific Manuscript database
Obesity and hypertension are multifactoral conditions in which the onset and severity of the conditions are influenced by the interplay of genetic and environmental factors. We hypothesize that multiple genes and environmental factors account for a significant amount of variation in BMI and blood pr...
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Mechanisms of increased lifespan in hypoxia in the alfalfa leafcutting bee, Megachile rotundata
USDA-ARS?s Scientific Manuscript database
Genetic variation accounts for a small amount of variation in lifespan, while environmental stressors are strong predictors. Hypoxia is an environmental stress that increases longevity in some contexts, but the mechanisms remain poorly understood. In the bee Megachile rotundata, lifespan doubles upo...