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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>
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.
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.
Data from: Depletion of heterogeneous source species pools predicts future invasion rates
Predicting how increasing rates of global trade will result in new establishments of potentially damaging invasive species is a question of critical importance to the development of national and international policies aimed at minimizing future invasions. Centuries of historical movement and establishment of invading species may have depleted the supply of species available for future invasions, and it has been suggested that the problem of invasions will diminish as a result of this. However, the extent to which source pool depletion affects future invasions remains unclear. Here we describe a mechanistic model that captures the simultaneous effects of depletion of source species pools along with increases in pathway rates (e.g. imports) to predict future numbers of new invasions. We assume that the distribution of species abundance within invasion pathways is positively skewed, which is modelled using a log-normal distribution. Given their high propagule pressure, the most abundant species are likely to invade first, while the many rare species are likely to invade only under high pathway volumes. We apply this model to the case study of bark beetle, Scolytinae, invasions in the USA. Source species pools in Europe and Asia (225 and 655 species of Scolytinae, respectively) are much larger than numbers that have historically established (16 and 32). Parameterization of the model indicates a highly skewed species abundance distribution in the pathway and this is confirmed by species frequencies in port inspection records, thus explaining why only a small fraction of species has historically invaded. Forecasts from the model indicate that with increasing rates of imports, more species from these regions are likely to invade in the future despite the depletion of the most abundant species from source species pools. Previous statistical models tend to underestimate future establishments in the presence of increasing import rates due to their failure to account for key underlying mechanisms. Policy implications. The mechanistic model developed here is widely applicable for predicting future invasions of all taxa and provides insights into how increases in rates of imports counteract the species pool depletion effect, resulting in the continued establishment of new species.
Data from: Geographical isolation and environmental heterogeneity contribute to the spatial genetic patterns of Quercus kerrii (Fagaceae)
Southwest China is one of the major global biodiversity hotspots. The Tanaka line, extending within southwestern China from its northwest to its southeast, is an important biogeographical boundary between the Sino-Japanese and Sino-Himalayan floristic regions. Understanding the evolutionary history of the regional keystone species would assist with both reconstructing historical vegetation dynamics and ongoing biodiversity management. In this research, we combined phylogeographic methodologies and species distribution models (SDMs) to investigate the spatial genetic patterns and distribution dynamics of Quercus kerrii, a dominant evergreen oak inhabiting southwest China lowland evergreen broadleaved forests (EBLFs). A total of 403 individuals were sampled from 44 populations throughout southwest China. SDMs and mismatch distribution analysis indicated that Q. kerrii has undergone northward expansion since the Last Glacial Maximum (LGM). Quantitative analysis revealed that the range expansion of Q. kerrii since the LGM exceeded that of the sympatric mid-elevation species Quercus schottkyana, likely owing to their contrasting distribution elevations and habitat availabilities. The historical climate change since the LGM and the latitude gradient of the region played an important role in shaping the genetic diversity of Q. kerrii. The genetic differentiation index and genetic distance surface of Q. kerrii populations east of the Tanaka line exceeded those to its west. The long-term geographic isolation and environmental heterogeneity between the two sides of the Tanaka line might increase species divergence patterns and local adaptation. This study provides new insights into the historical dynamics of subtropical EBLFs and the changing biota of southwest China.
Data from: Modelling the dispersal of the two main hosts of the raccoon rabies variant in heterogeneous environments with landscape genetics
Predicting the geographic spread of wildlife epidemics requires knowledge about the movement patterns of disease hosts or vectors. The field of landscape genetics provides valuable approaches to study dispersal indirectly, which in turn may be used to understand patterns of disease spread. Here, we applied landscape genetic analyses and spatially explicit models to identify the potential path of raccoon rabies spread in a mesocarnivore community. We used relatedness estimates derived from microsatellite genotypes of raccoons and striped skunks to investigate their dispersal patterns in a heterogeneous landscape composed predominantly of agricultural, forested and residential areas. Samples were collected in an area covering 22 000 km2 in southern Québec, where the raccoon rabies variant (RRV) was first detected in 2006. Multiple regressions on distance matrices revealed that genetic distance among male raccoons was strictly a function of geographic distance, while dispersal in female raccoons was significantly reduced by the presence of agricultural fields. In skunks, our results suggested that dispersal is increased in edge habitats between fields and forest fragments in both males and females. Resistance modelling allowed us to identify likely dispersal corridors used by these two rabies hosts, which may prove especially helpful for surveillance and control (e.g. oral vaccination) activities.
Data from: Pyric herbivory, scales of heterogeneity, and drought
1. Understanding how extreme drought alters spatial patterns and temporal stability in grassland biomass will become increasingly important by the end of the century when climate model forecasts suggest drought events will occur more frequently. In grassland landscapes where grazing is driven by fire (termed pyric herbivory), temporal stability in aboveground plant biomass at landscape scales typically coincides with greater spatial variability across local communities (time-since fire patches), whereas variability within local communities is associated with lower temporal stability. 2. We assess the robustness of this relationship during one of the most severe droughts on modern record in the southern Great Plains. We use a long-term pyric herbivory experiment to test whether extreme drought: 1) changes patterns of spatial variability in aboveground plant biomass among or within local communities, 2) changes the temporal stability in aboveground plant biomass and the relationship between spatial variability and temporal variability, and 3) changes the underlying feedback mechanisms associated with pyric herbivory. Ordination revealed a shift from spatially distinct patches before drought to a convergence of patches during drought in terms of aboveground plant biomass and crude protein. 3. Permutation tests revealed that within-patch variability in aboveground plant biomass significantly increased during drought compared to pre-drought levels. Temporal stability in aboveground plant biomass decreased during drought and indeed corresponded with reduced variability in biomass among local communities and increased variability within local communities compared to pre-drought levels. 4. The results from this study strongly suggest that both positive and negative feedback loops responsible for pyric herbivory were maintained by scale-switching during periods of extreme drought and further reinforce the importance of scale in the study of pattern-process relationships.
Data from: Performance of forest bryophytes with different geographical distributions transplanted across a topographically heterogeneous landscape
Most species distribution models assume a close link between climatic conditions and species distributions. Yet, we know little about the link between species' geographical distributions and the sensitivity of performance to local environmental factors. We studied the performance of three bryophyte species transplanted at south- and north-facing slopes in a boreal forest landscape in Sweden. At the same sites, we measured both air and ground temperature. We hypothesized that the two southerly distributed species Eurhynchium angustirete andHerzogiella seligeri perform better on south-facing slopes and in warm conditions, and that the northerly distributed species Barbilophozia lycopodioides perform better on north-facing slopes and in relatively cool conditions. The northern, but not the two southern species, showed the predicted relationship with slope aspect. However, the performance of one of the two southern species was still enhanced by warm temperatures. An important reason for the inconsistent results can be that microclimatic gradients across landscapes are complex and influenced by many climate-forcing factors. Therefore, comparing only north- and south-facing slopes might not capture the complexity of microclimatic gradients. Population growth rates and potential distributions are the integrated results of all vital rates. Still, the study of selected vital rates constitutes an important first step to understand the relationship between population growth rates and geographical distributions and is essential to better predict how climate change influences species distributions.
Data from: Spatial soil heterogeneity has a greater effect on symbiotic arbuscular mycorrhizal fungal communities and plant growth than genetic modification with Bacillus thuringiensis toxin genes
Maize, genetically modified with the insect toxin genes of Bacillus thuringiensis (Bt), is widely cultivated, yet its impacts on soil organisms are poorly understood. Arbuscular mycorrhizal fungi (AMF) form symbiotic associations with plant roots and may be uniquely sensitive to genetic changes within a plant host. In this field study, the effects of nine different lines of Bt maize and their corresponding non-Bt parental isolines were evaluated on AMF colonization and community diversity in plant roots. Plants were harvested 60 days after sowing, and data were collected on plant growth and per cent AMF colonization of roots. AMF community composition in roots was assessed using 454 pyrosequencing of the 28S rRNA genes, and spatial variation in mycorrhizal communities within replicated experimental field plots was examined. Growth responses, per cent AMF colonization of roots and AMF community diversity in roots did not differ between Bt and non-Bt maize, but root and shoot biomass and per cent colonization by arbuscules varied by maize cultivar. Plot identity had the most significant effect on plant growth, AMF colonization and AMF community composition in roots, indicating spatial heterogeneity in the field. Mycorrhizal fungal communities in maize roots were autocorrelated within approximately 1 m, but at greater distances, AMF community composition of roots differed between plants. Our findings indicate that spatial variation and heterogeneity in the field has a greater effect on the structure of AMF communities than host plant cultivar or modification by Bt toxin genes.
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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.