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162 results for “environmental heterogeneity”
Data from: Does genetic variation maintained by environmental heterogeneity facilitate adaptation to novel selection?
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Trait-based and multi-scale approach provides insight on responses of freshwater mussels to environmental heterogeneity
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Data from: Environmental heterogeneity and population differences in blue tits personality traits
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Seedling traits from root to shoot exhibit genetic diversity and distinct responses to environmental heterogeneity within a tree population
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Data from: Tree diversity across multiple scales and environmental heterogeneity promote ecosystem multifunctionality in a large temperate forest region
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Data from: On the roles of landscape heterogeneity and environmental variation in determining population genomic structure in a dendritic system
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Data from: Diversity patterns from sequentially restored grasslands support the ‘environmental heterogeneity hypothesis'
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The relative role of rivers, environmental heterogeneity and species traits in driving compositional changes in Southeastern Amazonian bird assemblages
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Fig. 1 in Fish beta diversity responses to environmental heterogeneity and flood pulses are different according to reproductive guild
Fig. 1. Map of the Upper Paraná River floodplain. The triangles represent the sampling stations of the Paraná River sub-basin, the circles represent the sampling stations of the Baía River sub-basin, and the squares represent the sampling stations of the Ivinhema River sub-basin.
Fig. 3 in Fish beta diversity responses to environmental heterogeneity and flood pulses are different according to reproductive guild
Fig. 3. Data analysis procedure for environmental heterogeneity and beta diversity for the different matrices of the trophic and reproductive guilds.
Data from: Quantitative genetic variance in experimental fly populations evolving with or without environmental heterogeneity
Heterogeneous environments are typically expected to maintain more genetic variation in fitness within populations than homogeneous environments. However, the accuracy of this claim depends on the form of heterogeneity as well as the genetic basis of fitness traits and how similar the assay environment is to the environment of past selection. Here we measure quantitative genetic variance for three traits important for fitness using replicated experimental populations of Drosophila melanogaster evolving under four selective regimes: constant salt-enriched medium (Salt), constant cadmium-enriched medium (Cad), and two heterogeneous regimes that vary either temporally (Temp) or spatially (Spatial). As theory predicts, we found that Spatial populations tend to harbor more genetic variation than Temp populations or those maintained in a constant environment that is the same as the assay environment. Contrary to expectation, Salt populations tend to have more genetic variation than Cad populations in both assay environments. We discuss the patterns for quantitative genetic (QG) variances across regimes in relation to previously reported data on genome-wide sequence diversity. For some traits, the QG patterns are similar to the diversity patterns of ecological selected SNPs whereas the QG patterns for some other traits resembled that of neutral SNPs.
Data from: Should I change or should I go? phenotypic plasticity and matching habitat choice in the adaptation to environmental heterogeneity
It can be challenging for organisms to achieve a good match between their phenotypic characteristics and environmental requirements that vary in space and time. The evolution of adaptive phenotypes can result from genetic differentiation at the population level. Individuals, however, could also change their phenotype (adaptive plasticity) or select an environment because it matches with their phenotype (matching habitat choice). It is poorly known under which conditions these different solutions to environmental heterogeneity evolve and whether they operate together. Using an individual-based simulation model, we assessed which solutions evolved depending on degree of temporal variation, costs of multiple underlying traits, and order of dispersal and development. Population genetic divergence was superseded by plasticity or matching habitat choice as temporal variation increased. Plasticity and matching habitat choice were limited by their trait costs, even when this involved only a part of the underlying traits. Independent of the order of dispersal and development, plasticity evolved more commonly than matching habitat choice, in part because the match a phenotype can achieve by matching habitat choice is limited by the types of environments available. Our results explain the apparent relative rarity of matching habitat choice in nature. At the same time, our results can be used to look for matching habitat choice in those biological systems where the conditions for other solutions seem unfavorable.
Data from: The effects of selective history and environmental heterogeneity on inbreeding depression in experimental populations of Drosophila melanogaster
Inbreeding depression varies considerably among populations, but only some aspects of this variation have been thoroughly studied. Because inbreeding depression requires genetic variation, factors that influence the amount of standing variation can affect the magnitude of inbreeding depression. Environmental heterogeneity has long been considered an important contributor to the maintenance of genetic variation, but its effects on inbreeding depression have been largely ignored by empiricists. Here we compare inbreeding depression, measured in two environments, for 20 experimental populations of Drosophila melanogaster that have been maintained under four different selection regimes, including two types of environmentally homogeneous selection and two types environmentally heterogeneous selection. In line with theory, we find considerably higher inbreeding depression in populations from heterogeneous selection regimes. We also use our data set to test whether inbreeding depression is correlated with either stress or the phenotypic coefficient of variation (CV), as suggested by some recent studies. Though both of these factors are significant predictors of inbreeding depression in our study, there is an effect of assay environment on inbreeding depression that cannot be explained by either stress or CV.
Data from: Environmental heterogeneity does not affect levels of phenotypic plasticity in natural populations of three Drosophila species
Adaptation of natural populations to variable environmental conditions may occur by changes in trait means and/or in the levels of plasticity. Theory predicts that environmental heterogeneity favors plasticity of adaptive traits. Here we investigated the performance in several traits of three sympatric Drosophila species freshly collected in two environments that differ in the heterogeneity of environmental conditions. Differences in trait means within species were found in several traits, indicating that populations differed in their evolutionary response to the environmental conditions of their origin. Different species showed distinct adaptation with a very different role of plasticity across species for coping with environmental changes. However, geographically distinct populations of the same species generally displayed the same levels of plasticity as induced by fluctuating thermal regimes. This indicates a weak and trait-specific effect of environmental heterogeneity on plasticity. Furthermore, similar levels of plasticity were found in a laboratory-adapted population of Drosophila melanogaster with a common geographic origin but adapted to the laboratory conditions for more than 100 generations. Thus, this study does not confirm theoretical predictions on the degree of adaptive plasticity among populations in relation to environmental heterogeneity but shows a very distinct role of species-specific plasticity.
Data from: Environmental heterogeneity generates opposite gene-by-environment interactions for two fitness-related traits within a population
Theory predicts that environmental heterogeneity offers a potential solution to the maintenance of genetic variation within populations, but empirical evidence remains sparse. The livebearing fish Xiphophorus variatus exhibits polymorphism at a single locus, with different alleles resulting in up to five distinct melanistic "tailspot" patterns within populations. We investigated the effects of heterogeneity in two ubiquitous environmental variables (temperature and food availability) on two fitness-related traits (upper thermal limits and body condition) in two different tailspot types (wildtype and upper cut crescent). We found gene-by-environment (GxE) interactions between tailspot type and food level affecting upper thermal limits (UTL), as well as between tailspot type and thermal environment affecting body condition. Exploring mechanistic bases underlying these GxE patterns, we found no differences between tailspot types in hsp70 gene expression despite significant overall increases in expression under both thermal and food stress. Similarly, there was no difference in routine metabolic rates between the tailspot types. The reversal of relative performance of the two tailspot types under different environmental conditions revealed a mechanism by which environmental heterogeneity can balance polymorphism within populations through selection on different fitness-related traits.
Is shallow convection sensitive to environmental heterogeneities?
This dataset contains the data files that underlie the four figures that are included in the paper entitled "Is shallow convection sensitive to environmental heterogeneities?" (please see the "Related Links" section to access the paper). The data represents analysis of 3D large eddy simulation. These are either profiles (e.g., the cloud fraction) or evolutions (e.g., the mean liquid water path) of various model-predicted quantities. These typically include several dozen levels each. One figure includes 2D cross sections of predicted cloud water mixing ratio. The abstract of the paper is included as follows: "The key assumption underlying convection parameterizations is that rising plumes develop in a horizontally-homogeneous environment. With this in mind, we investigate the impact of environmental cloud-layer heterogeneities on shallow convection using large-eddy simulation that applies a master-slave methodology. In the master-slave approach, two independent sets of thermodynamic variables (master and slave) are driven by one dynamics (coupled with the master) to remove the impact of internal variability of the dynamical system considered. The two thermodynamic sets include either a realistic heterogeneous environment or an environment that is homogenized outside clouds. It is important that homogenization also excludes subsiding shells surrounding cumulus clouds. The results show a small impact of the homogenization since the cloud field properties differ little between the master and slave thermodynamic sets. The physical explanation highlights the role of the subsiding shell shielding a shallow cumulus cloud from its environment."
Fig. 1 in Evaluating the correlation between area, environmental heterogeneity, and species richness using terrestrial isopods (Oniscidea) from the Pontine Islands (West Mediterranean)
Fig. 1 Pontine archipelago. The geographic distance between Ventotene- Santo Stefano and the remaining islands is not in scale. 1, Scoglio Ravia; 2, Scoglio di Pilato; 3, Faraglioni della Madonna; 4, Scogli della Cantina; 5, Scoglio Cappello; 6, Faraglione di Mezzogiorno; 7, Le Galere
Data from: Contrasting effects of spatial heterogeneity and environmental stochasticity on population dynamics of a perennial wildflower
Understanding how variation in growth, survival and reproduction affect population dynamics is a fundamental question in ecology. Although the effects of among-year variation (environmental stochasticity) are well understood, the effects of among-site variation (spatial heterogeneity) are less clearly defined. I evaluated the effects of spatial and temporal variation on the population dynamics of Pulsatilla patens, pasqueflower, a perennial prairie forb. I conducted a 10-year demographic monitoring study, and quantified vital rate variation among sites and years using generalized linear models. I incorporated vital rate functions using this variation into integral projection models for stochastic and spatially heterogeneous environments. I also explored the effects of temporal and spatial autocorrelation, by exploring model predictions over the range of possible values for temporal autocorrelation and local seed dispersal. Vital rates varied more among years than among sites. However, environmental stochasticity and spatial heterogeneity had similar magnitude effects on population dynamics. These effects were also qualitatively different: environmental stochasticity reduced population growth rates relative to the average, whereas spatial heterogeneity increased population growth rates. Spatial autocorrelation and negative temporal autocorrelation led to higher population growth rates, although environmental stochasticity still reduced growth rates for all autocorrelation values, and spatial heterogeneity increased growth rates for all autocorrelation values. Some form of autocorrelation would be necessary for model projections to match observed population trends. Synthesis. Spatial heterogeneity is as important as environmental stochasticity for population dynamics, but it is much less often incorporated into population projection models. This study points to a number of interesting avenues for future research into the roles of spatial heterogeneity and spatiotemporal variation for long-term population dynamics.
Data from: Elements of metacommunity structure of diatoms and macroinvertebrates within stream networks differing in environmental heterogeneity
<p><strong>Aim:</strong> Idealized metacommunity structures (i.e. checkerboard, random, quasi-structures, nested, Clementsian, Gleasonian, and evenly spaced) have recently gained increasing attention, but their relationships with environmental heterogeneity and how they vary with organism groups remain poorly understood. Here we tested two main hypotheses: (1) gradient-driven patterns (Clementsian and Gleasonian) occur frequently in heterogeneous environments, and (2) small organisms (here, diatoms) are more likely to exhibit gradient-driven patterns than large organisms (here, macroinvertebrates).</p> <p><strong>Location:</strong> Streams in three regions in China.</p> <p><strong>Taxon:</strong> Diatoms and macroinvertebrates.</p> <p><strong>Methods:</strong> The stream diatom and macroinvertebrate data, as well as the environmental data collected from the same set of sites were used to examine the idealized metacommunity structures via the elements of the metacommunity structure (EMS; coherence, turnover, and boundary clumping) analysis in three regions. We extended the traditional EMS approach by ordering sites along known environmental gradients.</p> <p><strong>Results: </strong>We found that Clementsian structure with high degrees of coherence and turnover, and significantly positive clumping was typically observed in the high-heterogeneity regions, whereas randomness was prevalent in the low-heterogeneity region. Macroinvertebrates exhibited clearer Clementsian structures compared with diatoms, while diatoms showed more randomness compared with macroinvertebrates, indicating a stronger role of environmental filtering for macroinvertebrates than diatoms. In most cases, the results of the more novel EMS approach differed from the results of the traditional EMS technique.</p> <p><strong>Main Conclusions:</strong> Our results suggested that the occurrence of different metacommunity structures may be related with the degree of regional environmental heterogeneity. However, diatom metacommunities were more random than those of macroinvertebrate, and such an unexpected result may result from different dispersal abilities between the two organism groups. In addition, we found that the novel EMS approach increased power in discerning metacommunity structure in comparison to the traditional EMS technique.</p>
Data from: No effect of environmental heterogeneity on the maintenance of genetic variation in wing shape in Drosophila melanogaster
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.