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3,339 results for “heterogeneities”
Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data
<p>This upload contains data and all the scripts required to reproduce the results of the artice entitled "Quantifying transmission dynamics of acute hepatitis C virus infections in a heterogeneous population using sequence data".</p> <p><strong>Code is located within Code.zip</strong> . It contains scripts in R and Bash and launchers. Some of the scripts require data files contained within Data.zip.</p> <p><strong>Data is located within Data.zip</strong> , such as the sequences, the inferred phylogeny and the Beast XML file.</p>
Heterogeneous agroecosystems support high diversity and abundance of trap nesting bees and wasps amongst tropical crops
<p>Land-use intensification for agricultural purposes modifies the structure of natural environments in various ways and at different spatial scales. These modifications can affect ecological processes and the community structure of multi-environment users such as solitary bees and wasps. Understanding the role of distinct habitat descriptors in promoting such changes is one of the major challenges of empirical studies. In this study, we use a multi-scale approach to evaluate how landscape compositional and configurational heterogeneity, vegetation structural complexity, and the proportion of agricultural landscape composition affect communities of bees and wasps that nest in pre-existing cavities in remnants of native vegetation bordering agroecosystems. We selected 25 sampling points along a gradient of amount of surrounding agriculture and landscape diversity within natural physiognomies located in Chapada Diamantina, Bahia, Brazil. Through model selection using Akaike's information criterion, we verified the complementary roles of landscape heterogeneity and local vegetation in structuring these hymenopteran communities. Abundance in the groups showed different tendencies depending on the descriptors employed, pointing to the importance of evaluating within-group specificity. Furthermore, bees and wasps presented differential responses to landscape composition, but they did not differ in relation to configurational complexity. In more heterogeneous landscapes or sites with more complex local vegetation, the proportion of agriculture had a positive influence on the response evaluated. Efficient management of agricultural landscapes therefore requires increased landscape heterogeneity and conservation or restoration of native vegetation remnants at the local scale.</p>
Data for "CryoDRGN: Reconstruction of heterogeneous cryo-EM structures using neural networks"
<p>Trained models and reconstructed density maps for:</p> <ul> <li>EMPIAR-10028: "Cryo-EM structure of a <em>Plasmodium falciparum</em> 80S ribosome bound to the anti-protozoan drug emetine" from Wong et al. (2014)</li> <li>EMPIAR-10049: "Molecular Mechanism of V(D)J Recombination from Synaptic RAG1-RAG2 Complex Structures" from Ru et al. (2015)</li> <li>EMPIAR-10076: "Modular assembly of the large bacterial ribosome" from Davis et al. (2016)</li> <li>EMPIAR-10180: "Structure of a pre-catalytic spliceosome" from Plaschka et al. (2017)</li> </ul> <p>Synthetic datasets with simulated heterogeneity and their ground truth density maps, poses, and labels:</p> <ul> <li>Uniform: 50k particle images (128x128, 6A/pix) uniformly sampled from 50 models along a 1-dimensional reaction coordinate</li> <li>Cooperative: 50k particle images (128x128, 6A/pix) sampled along the above reaction coordinate according to a 3-component Gaussian mixture model with overlapping components </li> <li>Noncontiguous: 50k particle images (128x128, 6A/pix) sampled along the above reaction coordinate according to a 3-component Gaussian mixture model without overlapping components</li> <li>Ribosomes: 50k particle images (128x128, 3A/pix) containing a mixture of 30S, 50S, 70S ribosomes simulating compositional heterogeneity</li> </ul>
Metabolomics dataset to identify plasma biomarkers in mice with metabolically heterogeneous melanoma xenografts
<p>Tumor xenografts were generated in mice using BRAF mutant A375 and WM47, NRAS mutant WM3000, and WM3311 (BRAF, NRAS, NF-1 wildtype) human melanoma cells. Xenograft tumor and plasma samples obtained from melanoma-bearing and non-tumor mice were analyzed using the MxP® Quant 500 kit in combination with the inhouse UHPLC-MS/MS-based acylcarnitine assay from Biocrates Life Sciences AG, Innsbruck, Austria. The data were used to characterize the metabolomes of human melanoma cell lines with different genetic background transplanted into mice in order to identify potential new biomarkers and targets for melanoma therapy.</p>
Environmental heterogeneity predicts global species richness patterns better than area
<p><strong>Aim:</strong> <span>It is widely accepted that biodiversity can be determined by niche-relate processes and by pure area effects from local to global scales. Their relative importance, however, is still disputed, and empirical tests are still surprisingly scarce at the global scale. We compare the explanatory power of area and environmental heterogeneity as a proxy for niche-related processes as drivers of native mammal species richnessworldwide and with biogeographical regions. </span></p> <p><span><strong>Location:</strong> Global</span></p> <p><span><strong>Time Period: </strong>Data was collated form the IUCN (2013)</span></p> <p><span><strong>Major Taxa Studied:</strong> All mammal species, including possibly extinct species and species with uncertain presence.</span></p> <p><strong>Methods:</strong><strong> </strong>We developed a random walk algorithm to compare the explanatory power of area and environmental heterogeneity on native mammal species richness. As measures for environmental heterogeneity, we used elevation and precipitation ranges, which are well known correlates of species richness.</p> <div> <p><strong>Results:</strong> We find that environmental heterogeneity explains species richness relationships better than area does, suggesting that niche-related processes are more prevalent than pure area effects at broad scales.</p> <p><strong>Main Conclusions:</strong> Our results imply that niche-related processes are essential to understand broad-scale species-area relationships and that habitat diversity is more important than area alone for the protection of global biodiverstiy.</p> </div>
Semi-analytical modeling of rate-dependent relative permeability in heterogeneous formations
<p>Numerical codes and results for MS: Semi-analytical modeling of rate-dependent relative permeability in heterogeneous formations</p>
Data from: Heterogeneity in individual quality in birds: overall patterns and insights from a study on common terns
While life-history theory predicts a trade-off between reproduction and survival, positive covariance, indicative of heterogeneity in individual quality, is often reported among individuals from natural populations. We review longitudinal studies of wild bird populations that test the relationship between annual reproductive success and lifespan and find the majority to report a positive correlation, while none reports a negative correlation. Heterogeneity in individual quality in resource acquisition, masking resource-based trade-offs, therefore appears to be common in birds. Considering that there is little evidence for heritable variation in fitness, heterogeneity in individual quality among adults may be due to life-long effects of developmental conditions. In a 20-year case study on common terns (Sterna hirundo), we test for life-long effects of cohort quality and within-cohort nest quality, but find no significant effects on long-term proxies of quality. Since other studies do find strong life-long effects of developmental conditions, we suggest that the brood reduction strategy adopted by common terns, causing the majority of offspring to die rapidly after hatching, efficiently reduces variation in offspring quality at independence. As such, a brood reduction strategy may contribute to reduced heterogeneity in adult survival in stochastic environments, both suggested to be more common and adaptive in long-lived species. Further study is required to assess heterogeneity in individual reproduction, especially in relation to environmental stochasticity and species' life-history strategies, in order to assess whether the relative strength of selection in early and late life may indeed affect the magnitude of heterogeneity in individual quality over life, and how this is mediated by parent-offspring conflict.
Data from: Occupancy models for data with false positive and false negative errors and heterogeneity across sites and surveys
False positive detections, such as species misidentifications, occur in ecological data, although many models do not account for them. Consequently, these models are expected to generate biased inference. The main challenge in an analysis of data with false positives is to distinguish false positive and false negative processes while modeling realistic levels of heterogeneity in occupancy and detection probabilities without restrictive assumptions about parameter spaces. Building on previous attempts to account for false positive and false negative detections in occupancy models, we present hierarchical Bayesian models that utilize a subset of data with either confirmed detections of a species' presence (CP model) or both confirmed presences and confirmed absences (CACP model). We demonstrate that our models overcome the challenges associated with false positive data by evaluating model performance in Monte Carlo simulations of a variety of scenarios. Our models also have the ability to improve inference by incorporating previous knowledge through informative priors. We describe an example application of the CP model to quantify the relationship between songbird occupancy and residential development, plus we provide instructions for ecologists to use the CACP and CP models in their own research. Monte Carlo simulation results indicated that, when data contained false positive detections, the CACP and CP models generated more accurate and precise posterior probability distributions than a model that assumed data did not have false positive errors. For the scenarios we expect to be most generally applicable, those with heterogeneity in occupancy and detection, the CACP and CP models generated essentially unbiased posterior occupancy probabilities. The CACP model with vague priors generated unbiased posterior distributions for covariate coefficients. The CP model generated unbiased posterior distributions for covariate coefficients with vague or informative priors, depending on the function relating covariates to occupancy probabilities. We conclude that the CACP and CP models generate accurate inference in situations with false positive data for which previous models were not suitable.
Data from: Sun skink landscape genomics: assessing how microevolutionary processes shape genetic and phenotypic diversity across a heterogeneous and fragmented landscape
Incorporating genomic data sets into landscape genetic analyses allows for powerful insights into population genetics, explicitly geographical correlates of selection, and morphological diversification of organisms across the geographical template. Here, we utilize an integrative approach to examine gene flow and detect selection, and we relate these processes to genetic and phenotypic population differentiation across South-East Asia in the common sun skink, Eutropis multifasciata. We quantify the relative effects of geographic and ecological isolation in this system and find elevated genetic differentiation between populations from island archipelagos compared to those on the adjacent South-East Asian continent, which is consistent with expectations concerning landscape fragmentation in island archipelagos. We also identify a pattern of isolation by distance, but find no substantial effect of ecological/environmental variables on genetic differentiation. To assess whether morphological conservatism in skinks may result from stabilizing selection on morphological traits, we perform FST–PST comparisons, but observe that results are highly dependent on the method of comparison. Taken together, this work provides novel insights into the manner by which micro-evolutionary processes may impact macro-evolutionary scale biodiversity patterns across diverse landscapes, and provide genomewide confirmation of classic predictions from biogeographical and landscape ecological theory.
Data from: Landscape heterogeneity strengthens the relationship between β-diversity and ecosystem function
Consensus has emerged in the literature that increased biodiversity enhances the capacity of ecosystems to perform multiple functions. However, most biodiversity/ecosystem function studies focus on a single ecosystem, or on landscapes of homogenous ecosystems. Here we investigate how increased landscape-level environmental dissimilarity may affect the relationship between different metrics of diversity (α, β, or γ) and ecosystem function. We produced a suite of simulated landscapes, each of which contained four experimental outdoor aquatic mesocosms. Differences in temperature and nutrient conditions of the mesocosms allowed us to simulate landscapes containing a range of within-landscape environmental heterogeneities. We found that the variation in ecosystem functions was primarily controlled by environmental conditions, with diversity metrics accounting for a smaller (but significant) amount of variation in function. When landscapes were more homogeneous, α, β, and γ diversity was not associated with differences in primary production, and only γ was associated with changes in decomposition. In these homogeneous landscapes, differences in these two ecosystem functions were most strongly related to nutrient and temperature conditions in the ecosystems. However, as landscape-level environmental dissimilarity increased, the relationship between α, β, or γ and ecosystem functions strengthened, with β being a greater predictor of variation in decomposition at the highest levels of environmental dissimilarity than α or γ. We propose that when all ecosystems in a landscape have similar environmental conditions, species sorting is likely to generate a single community composition that is well suited to those environmental conditions, β is low, and the efficiency of diversity-ecosystem function couplings is similar across communities. Under this low β, the effect of abiotic conditions on ecosystem function will be most apparent. However, when environmental conditions vary among ecosystems, species sorting pressures is different among ecosystems, producing different communities among locations in a landscape. These conditions lead to stronger relationships between β and the magnitude of ecosystem functions. Our results illustrate that abiotic conditions and the homogeneity of communities influence ecosystem function expressed at the landscape-scale.
Seedling traits from root to shoot exhibit genetic diversity and distinct responses to environmental heterogeneity within a tree population
<p>Phenotypic diversity within plant species is crucial to shaping evolutionary responses of populations and interactions among species, yet intraspecific genetic variability notably in roots has attracted little attention. Further, evidence for the root−shoot trait synchronisation remains inconclusive, narrowing our understanding of the role that belowground traits play in local adaptation. We applied broad 'top-to-toe' phenotyping to a model system whose native environmental conditions were simulated in experimental settings. Fifteen maternal families of Norway spruce <i>Picea abies </i>from southern Finland grew in six combinations of two simulated growing seasons and three soil treatments. We scored variation in 25 functional traits, including size, architecture and morphology of intact root systems, and shoot growth and phenology. Careful phenotyping of roots uncovered five trait dimensions, with root size, architecture and morphology forming the three largest axes of variation. Dimensions varied in their treatment responses. We observed among-family differences in all trait dimensions, marking substantial within-population genetic diversity. For example, average total root length varied almost twofold among families, but family × soil interactions indicated treatment-specific estimates of genetic variance. Mirroring root traits, phenotypic plasticity and genetic variation characterised shoot growth and phenology. In all, the complete phenotypic dataset yielded six trait dimensions, with assorted measures of root system and shoot size composing the main axis of variation. Although plastic and genetically variable, root architecture and morphology were not associated with shoot growth in any treatment. Also phenology and root-to-shoot ratio were detached from the primary axis of trait variability. Our results demonstrate that complex within-species patterns of trait covariation can be observed even locally and that phenotypic variation in independent trait dimensions reflecting divergent growth strategies is under genetic control. More accurate predictions of population and species responses to changes in the environment can be achieved when such intraspecific diversity is taken into account.</p>
Data from: Root heterogeneity along an arctic elevational gradient: the importance of resolution
Spatial heterogeneity affects plant performance and is influenced by plants, but the scale at which fine roots react to or generate spatial heterogeneity has received little attention. Fine roots might be expected to respond to heterogeneity at a scale comparable to their diameter (mm), but studies to date have been conducted at much coarser resolutions (cm – m). Here we quantify root heterogeneity in contrasting habitats with special attention to the influence of resolution. We measured fine root length heterogeneity at resolutions ranging from 1 to 300 mm2, at four elevations along an arctic alpine gradient from 500 m a.s.l. (forest) to 1100 m (tundra). We calculated the magnitude of heterogeneity as the coefficient of variation of root length, and the scale of heterogeneity using semivariance analysis. The magnitude of heterogeneity was about twofold greater at fine than coarse resolution. Further, the magnitude of heterogeneity was generally greatest at the highest elevation, suggesting that soil at 1100 m was less evenly occupied by plant roots than soils at lower elevations. The exception to this was at the 1 mm2 resolution, for which the magnitude of heterogeneity did not vary with elevation, possibly because heterogeneity at this scale is related to ecophysiological processes common to all vegetation types. The scale of root length heterogeneity increased significantly with resolution coarseness, suggesting that roots respond to or generate patchiness at small scales that have not previously been examined. In contrast, the scale of heterogeneity did not vary significantly with elevation and the accompanying turnover in growth form. Our results suggest that roots in four vegetation types respond to or generate very fine scales of spatial heterogeneity, including scales much smaller than those that have previously been examined. Both the magnitude and scale of heterogeneity varied with sampling resolution, suggesting resolutions as small as a few millimetres are relevant to studies of spatial root interactions and below-ground processes.
Data from: Landscape determinants of fine-scale genetic structure of a small rodent in a heterogeneous landscape (Hluhluwe-iMfolozi Park, South Africa)
Small mammals provide ecosystem services, acting, for example, as pollinators and seed dispersers. In addition, they are also disease reservoirs that can be detrimental to human health and they can also act as crop pests. Knowledge of their dispersal preferences is therefore useful for population management and landscape planning. Genetic data were used alongside landscape data to examine the influence of the landscape on the demographic connectedness of the Natal multimammate mouse (Mastomys natalensis) and to identify landscape characteristics that influence the genetic structure of this species across a spatially and temporally varying environment. The most significant landscape features shaping gene flow were aspect, vegetation cover, topographic complexity (TC) and rivers, with western facing slopes, topographic complexity and rivers restricting gene flow. In general, thicket vegetation was correlated with increased gene flow. Identifying features of the landscape that facilitate movement/dispersal in M. natalensis potentially has application for other small mammals in similar ecosystems. As the primary reservoir host of the zoonotic Lassa virus, a landscape genetics approach may have applications in determining areas of high disease risk to humans. Identifying these landscape features may also be important in crop management due to damage by rodent pests.
Data from: Spatial analyses of two color polymorphisms in an alpine grasshopper reveal a role of small‐scale heterogeneity
Discrete color polymorphisms represent a fascinating aspect of intraspecific diversity. Color morph ratios often vary clinally, but in some cases, there are no marked clines and mixes of different morphs occur at appreciable frequencies in most populations. This poses the questions of how polymorphisms are maintained. We here study the spatial and temporal distribution of a very conspicuous color polymorphism in the club‐legged grasshopper Gomphocerus sibiricus. The species occurs in a green and a nongreen (predominately brown) morph, a green–brown polymorphism that is common among Orthopteran insects. We sampled color morph ratios at 42 sites across the alpine range of the species and related color morph ratios to local habitat parameters and climatic conditions. Green morphs occurred in both sexes, and their morph ratios were highly correlated among sites, suggesting shared control of the polymorphism in females and males. We found that in at least 40 of 42 sites green and brown morphs co‐occurred with proportions of green ranging from 0% to 70% with significant spatial heterogeneity. The proportion of green individuals tended to increase with decreasing summer and winter precipitations. Nongreen individuals can be further distinguished into brown and pied individuals, and again, this polymorphism is shared with other grasshopper species. We found pied individuals at all sites with proportions ranging from 3% to 75%, with slight, but significant variation between years. Pied morphs show a clinal increase in frequency from east to west and decreased with altitude and lower temperatures and were more common on grazed sites. The results suggest that both small‐scale and large‐scale spatial heterogeneity affects color morph ratios. The almost universal co‐occurrence of all three color morphs argues against strong effects of genetic drift. Instead, the data suggest that small‐scale migration–selection balance and/or local balancing selection maintain populations polymorphic.
Data from: Landscape heterogeneity and local adaptation define the spatial genetic structure of Pacific salmon in a pristine environment
Identifying the spatial distribution of genetic variation across the landscape is an essential step in informing species conservation. Comparison of closely related and geographically overlapping species can be particularly useful in cases where landscape may similarly influence genetic structure. Congruent patterns among species highlight the importance that landscape heterogeneity plays in determining genetic structure whereas contrasting patterns emphasize differences in species-specific ecology and life-history or the importance of species-specific adaptation to local environments. We examined the interacting roles of demography and adaptation in determining spatial genetic structure in two closely related and geographically overlapping species in a pristine environment. Using single nucleotide polymorphism (SNP) loci exhibiting both neutral and putative adaptive variation, we evaluated the genetic structure of sockeye salmon in the Copper River, Alaska; these data were compared to existing data for Chinook salmon from the same region. Overall, both species exhibited patterns of isolation by distance; the spatial distribution of populations largely determined the distribution of genetic variation across the landscape. Further, both species exhibited largely congruent patterns of within- and among-population genetic diversity, highlighting the role that landscape heterogeneity and historical processes play in determining spatial genetic structure. Potential adaptive differences among geographically proximate sockeye salmon populations were observed when high FST outlier SNPs were evaluated in a landscape genetics context. Results were evaluated in the context of conservation efforts with an emphasis on reproductive isolation, historical processes, and local adaptation.
Data from: Does genetic variation maintained by environmental heterogeneity facilitate adaptation to novel selection?
Environmental heterogeneity helps maintain genetic variation in fitness. Therefore, one might predict that populations living in heterogeneous environments have higher adaptive potential than populations living in homogeneous environments. Such a prediction could be useful in guiding conservation priorities without requiring detailed genetic studies. However, this prediction will be true only if the additional genetic variation maintained by environmental heterogeneity can be used to respond to novel selection. Here we examine the effect of environmental heterogeneity on future adaptability using replicated experimental Drosophila melanogaster populations that had previously evolved for ∼100 generations under one of four selective regimes: constant salt-enriched larvae medium, constant cadmium-enriched larvae medium, and two heterogeneous regimes that vary either temporally or spatially between the two media. Replicates of these experimental populations were subjected to a novel heat stress while being maintained in their original larval diet selection regimes. Adaptation to increased temperature was measured with respect to female productivity and male siring success after ∼20 generations. For female productivity, there was evidence of adaptation overall and heterogeneous populations had a larger adaptive response than homogeneous populations. There was less evidence of adaptation overall for male siring success and no support for faster adaptation in heterogeneous populations.
Data from: Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation
Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual-based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real-world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.
Data from: Walking in a heterogeneous landscape: dispersal, gene-flow and conservation implications for the giant panda in the Qinling Mountains
Understanding the interaction between life history, demography and population genetics in threatened species is critical for the conservations of viable populations. In the context of habitat loss and fragmentation, identifying the factors that underpin the structuring of genetic variation within populations can allow conservationists to evaluate habitat quality and connectivity and help to design dispersal corridors effectively. In this study, we carried out a detailed, fine-scale landscape genetic investigation of a giant panda population for the first time, using a large microsatellite data set and examined the role of isolation-by-barriers (IBB), isolation-by-distance (IBD) and isolation-by-resistance (IBR) in shaping the genetic variation pattern of giant pandas in the Qinling Mountains. We found that the Qinling population comprises one continuous genetic cluster, and among the landscape hypotheses tested, gene flow was found to be correlated with resistance gradients for two topographic factors, rather than geographical distance or barriers. Gene-flow was inferred to be facilitated by easterly slope aspect and to be constrained by land surface with high topographic complexity. These factors are related to benign micro-climatic conditions for both the pandas and the food resources they rely on and more accessible topographic conditions for movement, respectively. We identified optimal corridors based on these results, aiming to promote gene flow between human-induced habitat fragments. These findings provide insight into the permeability and affinities of the giant panda habitat and offer important reference for the conservation of the giant panda and its habitat.
Data from: Canopy height variation and environmental heterogeneity in the tropical dry forests of coastal Oaxaca, Mexico
Despite its importance for carbon storage and other ecosystem functions, the variation of vegetation canopy height is not yet well understood. We examined the relationship between this community attribute and environmental heterogeneity in a tropical dry forest of southern Mexico. We sampled vegetation in 15 sites along a 100-km coastal stretch of Oaxaca State, and measured the heights of all woody plants (excluding lianas). The majority of the ca. 4000 individuals recorded concentrated in the 4–8 m height range. We defined three plant sets to describe overall community canopy height at each site: a set including all plants, a set made up by the tallest plants representing 10 percent of all individuals, and a set comprising the 10 tallest plants. For each site we computed maximum height and the mean and median heights of the three sets. Significant collinearity was observed between the seven resulting height variables, but null distributions constructed through bootstrap revealed their different behaviors as functions of species richness and density of individuals. Through linear modeling and a model selection procedure, we identified 21 models that best described the variation of canopy height variables. These models pointed out to soil (measured as PC1 of a principal component analysis performed on 10 soil variables), water stress, and elevation as the main drivers of canopy height variation in the region. In the event of increasing water stress resulting from global climate change, the studied tropical dry forests could become shorter and thus decrease their carbon storage potential.
Data from: Amount or pattern? Grassland responses to the heterogeneity and availability of two key resources
Patterns of resource availability and heterogeneity shape the composition, productivity, and dynamics of plant assemblages in a wide variety of terrestrial ecosystems. Despite this, the responses of plant assemblages to simultaneous changes in the availability and heterogeneity of more than a single resource are virtually unknown. To fill this gap, microcosms consisting of assemblages formed by Lolium perenne, Plantago lanceolata, Anthoxantum odoratum, Holcus lanatus, and Trifolium repens were grown in a factorial experiment with the following treatments: nutrient availability (NA), water availability (WA), spatial nutrient heterogeneity (NH), and temporal water heterogeneity (WH). Assemblages exhibited precise root foraging patterns in response to nutrient heterogeneity, which were modified by NA and WA. A series of two- and three-way interactions involving the four factors evaluated determined biomass production, the belowground : aboveground biomass ratio, the patterns of root biomass allocation with depth, and the relative contribution to aboveground biomass of Lolium and Anthoxanthum. In all cases, these interactions explained significant amounts of the variation found in the data. Our study demonstrates that considering the interactions between resource availability and heterogeneity allows for a refinement of predictions that can detectably reduce the error associated with extrapolating from single factor analyses.
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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.