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470 results for “Spatial Patterns”
Data from: Helianthus maximiliani and species fine-scale spatial pattern affect diversity interactions in reconstructed tallgrass prairies
1. Biodiversity and Ecosystem Function analyses aim to explain how individual species and their interactions affect ecosystem function. With this study we asked in what ways do species interact, are these interactions affected by species planting pattern, and are initial (planted) proportions or previous year (realized) proportions a better reference point for characterizing grassland diversity effects? 2. We addressed these questions with experimental communities compiled from a pool of 16 tallgrass prairie species. We planted all species in monocultures and mixtures that varied in their species richness, evenness, and spatial pattern. We recorded species-specific biomass production over three growing seasons and fitted Diversity-Interactions (DI) models to annual plot biomass yields. 3. In the establishment season, all species interacted equally to form the diversity effect. In years 2 and 3, each species contributed a unique additive coefficient to its interaction with every other species to form the diversity effect. These interactions were affected by H. maximiliani and the species planting pattern. Models based on species planted proportions better-fit annual plot yields than models based on species previous contributions to plot biomass. 4. Outcomes suggest that efforts to plant tallgrass prairies to maximize diversity effects should focus on the specific species present and in what arrangement they are planted. Furthermore, for particularly diverse grasslands, the effort of collecting annual species biomass data may not be necessary when quantifying diversity effects with Diversity-Interactions models.
Flow through a submerged canopy partially covering the bed: spatial flow pattern, multi-dimensional vortices and junction momentum exchange
<p>The dataset (including videos) are uploaded to support the research study <strong>Flow through a submerged canopy partially covering the bed: spatial flow pattern, multi-dimensional vortices and junction momentum exchange (submitted to Water Resources Research) </strong></p>
Data from: The influence of landscape, climate, and history on spatial genetic patterns in keystone plants (Azorella) on sub-Antarctic islands
The distribution of genetic variation in species is governed by factors that act differently across spatial scales. To tease apart the contribution of different processes, especially at intermediate spatial scales, it is useful to study simpler ecosystems such as those on sub-Antarctic oceanic islands. In this study, we characterize spatial genetic patterns of two keystone plant species, Azorella selago on sub-Antarctic Marion Island and Azorella macquariensis on sub-Antarctic Macquarie Island. Although both islands experience a similar climate and vegetation structure, they differ significantly in topography and geological history. We genotyped six microsatellites for 1149 individuals from 123 sites across Marion Island and 372 individuals from 42 sites across Macquarie Island. We tested for spatial patterns in genetic diversity, including correlation with elevation and vegetation type, and clines in different directional bearings. We also examined genetic differentiation within islands, isolation-by-distance with and without accounting for direction, and signals of demographic change. Marion Island was found to have a distinct northwest-southeast divide, with lower genetic diversity and more sites with signal of population expansion in the northwest. We attribute this to asymmetric seed dispersal by the dominant northwesterly winds, and to population persistence in a southwestern refugium during the last Glacial Maximum. No apparent spatial pattern, but greater genetic diversity and differentiation between sites, was found on Macquarie Island, which may be due to the narrow length of the island in the direction of the dominant winds and longer population persistence permitted by the lack of extensive glaciation on the island.
Data from: Geographic isolation and larval dispersal shape seascape genetic patterns differently according to spatial scale
Genetic variation, as a basis of evolutionary change, allows species to adapt and persist in different climates and environments. Yet, a comprehensive assessment of the drivers of genetic variation at different spatial scales is still missing in marine ecosystems. Here, we investigated the influence of environment, geographic isolation, and larval dispersal on the variation in allele frequencies, using an extensive spatial sampling (47 locations) of the striped red mullet (Mullus surmuletus) in the Mediterranean Sea. Univariate multiple regressions were used to test the influence of environment (salinity and temperature), geographic isolation, and larval dispersal on Single Nucleotide Polymorphisms (SNPs) allele frequencies. We used Moran's Eigenvector Maps (db-MEMs) and Asymmetric Eigenvector Maps (AEMs) to decompose geographic and dispersal distances in predictors representing different spatial scales. We found that salinity and temperature had only a weak effect on the variation in allele frequencies. Our results revealed the predominance of geographic isolation to explain variation in allele frequencies at large spatial scale (> 1,000km) while larval dispersal was the major predictor at smaller spatial scale (< 1,000km). Our findings stress the importance of including spatial scales to understand the drivers of spatial genetic variation. We suggest that larval dispersal allows to maintain gene flows at small to intermediate scale, while at broad scale, genetic variation may be mostly shaped by adult mobility, demographic history or multi-generational stepping stone dispersal. These findings bring out important spatial scale considerations to account for in the design of a protected areas network that would efficiently enhance protection and persistence capacity of marine species.
Data from: Contrasting global patterns of spatially periodic fairy circles and regular insect nests in drylands
<p>Numerical analysis of spatial pattern is widely used in ecology to describe the characteristics of floral and faunal distributions. These methods allow attribution of pattern to causal mechanisms by uncovering the specific signatures of patterns and causal agents. For example, grassland‐gap patterns called fairy circles (FCs) in Namibia and Australia are characterized by highly regular and homogenous distributions across landscapes that show spatially periodic ordering. These FCs have been suggested to be caused by both social insects and competitive plant interactions. We compared eight Namibian and Australian FC patterns and also modeled FCs to 16 patterns of social insect nests in Africa, Australia, and America that include the most regular termite mound patterns known. For pattern‐process inference, we used spatial statistics based on both nearest‐neighbor analysis and neighborhood‐density functions. None of the analyzed insect‐nest distributions attain the spatially periodic ordering that is typical of FCs. The inherently more variable patterns of termite and ant nests are commonly attributable to well documented aspects of the faunal life‐history. Our quantitative evidence from drylands shows that the more variable insect‐nest distributions in water‐limited environments cannot explain the characteristic spatial signature of FCs. The analysis demonstrates the interpretation of scale‐dependent neighborhood‐density functions and that it is the identification of unique spatial signatures in regular patterns that need to be linked to process. While our results cannot verify a specific hypothesis, they support the hypothesis that FCs in these drylands are more likely an emergent vegetation pattern caused by strong plant competition for water.</p>
Data from: Ecological and spatial patterns associated with diversification of the shrub genus Tetraglochin along Southern-Central Andes (Rosaceae)
In addition to the degree of geographical isolation (sympatry, parapatry, allopatry and peripatry), ecology can be an important factor promoting diversification of lineages, both by niche divergence as well as niche conservatism. Tetraglochin is a genus of shrubs with six species distributed along the Southern and Central Andes, from Peru to southern Argentina and central Chile. Although monophyly of the genus as the identity of its species are well established, spatiotemporal framework for its diversification and the potential role of the ecology and geography in the speciation process remain unknown. In the present study we analyzed diversification times and historical biogeography of the genus, and conducted different climatic niche and geographical range comparisons among its species to determine possible patterns associated with speciation. Results support the Pleistocene diversification, early along the Southern Andes and the Patagonian Steppe and subsequently in the Central Andes. Climatic niche divergence did not prove to be a major factor promoting speciation, but rather the phylogenetic niche conservatism. Our analyses also favored the sympatric model of speciation, although patterns from geographical range evolution are difficult to interpret due to the lability on the ancestral distributions, and therefore micro-allopatric or parapatric divergence associated with the glacial-interglacial cycles and climatic oscillations throughout the Quaternary should not be discarded. Other potential factors associated with diversification of Tetraglochin are also discussed.
Data from: Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches
PLEASE NOTE, THESE DATA ARE ALSO REFERRED TO IN TWO OTHER PUBLICATIONS. PLEASE SEE http://dx.doi.org/10.1111/j.1365-2486.2008.01766.x AND http://dx.doi.org/10.1111/2041-210X.12222 FOR MORE INFORMATION. Aim: This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location: Two study areas in the Alps of Switzerland. Methods: We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results: The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient. Main conclusions: Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.
Data from: Seascape continuity plays an important role in determining patterns of spatial genetic structure in a coral reef fish
Detecting patterns of spatial genetic structure (SGS) can help identify intrinsic and extrinsic barriers to gene flow within metapopulations. For marine organisms such as coral reef fishes, identifying these barriers is critical to predicting evolutionary dynamics and demarcating evolutionarily significant units for conservation. In this study, we adopted an alternative hypothesis-testing framework to identify the patterns and predictors of SGS in the Caribbean reef fish Elacatinus lori. First, genetic structure was estimated using nuclear microsatellites and mitochondrial cytochrome b sequences. Next, clustering and network analyses were applied to visualize patterns of SGS. Finally, logistic regressions and linear mixed models were used to identify the predictors of SGS. Both sets of markers revealed low global structure: mitochondrial ΦST = 0.12, microsatellite FST = 0.0056. However, there was high variability among pairwise estimates, ranging from no differentiation between sites on contiguous reef (ΦST = 0) to strong differentiation between sites separated by ocean expanses ≥ 20 km (maximum ΦST = 0.65). Genetic clustering and statistical analyses provided additional support for the hypothesis that seascape discontinuity, represented by oceanic breaks between patches of reef habitat, is a key predictor of SGS in E. lori. Notably, the estimated patterns and predictors of SGS were consistent between both sets of markers. Combined with previous studies of dispersal in E. lori, these results suggest that the interaction between seascape continuity and the dispersal kernel plays an important role in determining genetic connectivity within metapopulations.
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: Spatial and temporal patterns of frugivorous Hornbill movements in Central Africa and their implications for rain forest conservation
Tropical forest conservation and restoration require an understanding of the movements and habitat preferences of important seed dispersers. With forests now being altered at an unprecedented rate, avian frugivores are becoming increasingly vital for forest regeneration. Seed movement, however, is highly dependent on the behavioral characteristics of their dispersers. Here, we examined the movements, habitat preferences, and range sizes of two African frugivores: the Black-casqued (Ceratogymna atrata) and the White-thighed (Bycanistes albotibialis) Hornbill, in the lowland rain forests of southern Cameroon. Using satellite transmitters, we tracked eight hornbills for 3 yr to characterize their movements and relate them to environmental landscape features. Hornbill movements differed significantly, with B. albotibialis ranging over larger areas (mean = 20,274 ha) than C. atrata (mean = 5604 ha), and females of both species covering over 15 times the area of males. Evidence suggests that movements are irruptive during particular periods, perhaps driven by low resource availability. In addition, hornbills often returned to the same localities within a year, although movements were not characterized as migratory. Both species displayed significant differences in habitat preference, with B. albotibialis utilizing disturbed habitat more frequently than C. atrata (t = −22.04, P = 2.2 × 10−16). Major roads were found to act as barriers for C. atrata, but not for B. albotibialis. The ability of both hornbill species to move large distances suggests hornbills will play a vital role in the maintenance and regeneration of rain forests in Central Africa as forest fragmentation increases and terrestrial vertebrates decline in numbers.
Data from: Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus)
Deciphering patterns of genetic variation within a species is essential for understanding population structure, local adaptation and differences in diversity between populations. Whilst neutrally evolving genetic markers can be used to elucidate demographic processes and genetic structure, they are not subject to selection and therefore are not informative about patterns of adaptive variation. As such, assessments of pertinent adaptive loci, such as the immunity genes of the Major Histocompatibility Complex (MHC), are increasingly being incorporated into genetic studies. In this study we combined neutral (microsatellite, mtDNA) and adaptive (MHC class II DLA-DRB1 locus) markers to elucidate the factors influencing patterns of genetic variation in the African wild dog (Lycaon pictus); an endangered canid that has suffered extensive declines in distribution and abundance. Our genetic analyses found all extant wild dog populations to be relatively small (Ne < 30). Furthermore, through coalescent modelling, we detected a genetic signature of a recent and substantial demographic decline, which correlates with human expansion, but contrasts with findings in some other African mammals. We found strong structure of wild dog populations, indicating the negative influence of extensive habitat fragmentation and loss of gene flow between habitat patches. Across populations we found that the spatial and temporal structure of microsatellite and MHC diversity were correlated, and strongly influenced by demographic stability and population size, indicating the effects of genetic drift in these small populations. Despite this correlation, we detected signatures of selection at the MHC, implying that selection has not been completely overwhelmed by genetic drift.
Data from: Demographic history influences spatial patterns of genetic diversity in recently expanded coyote (Canis latrans) populations
Human-mediated range expansions have increased in recent decades and represent unique opportunities to evaluate genetic outcomes of establishing peripheral populations across broad expansion fronts. Over the past century, coyotes (Canis latrans) have undergone a pervasive range expansion and now inhabit every state in the continental United States. Coyote expansion into eastern North America was facilitated by anthropogenic landscape changes and followed two broad expansion fronts. The northern expansion extended through the Great Lakes region and southern Canada, where hybridization with remnant wolf populations was common. The southern and more recent expansion front occurred approximately 40 years later and across territory where gray wolves have been historically absent and remnant red wolves were extirpated in the 1970s. We conducted a genetic survey at 10 microsatellite loci of 482 coyotes originating from 11 eastern U.S. states to address how divergent demographic histories influence geographic patterns of genetic diversity. We found that population structure corresponded to a north-south divide, which is consistent with the two known expansion routes. Additionally, we observed extremely high genetic diversity, which is atypical of recently expanded populations and is likely the result of multiple complex demographic processes, in addition to hybridization with other Canis species. Finally, we considered the transition of allele frequencies across geographic space and suggest the mid-Atlantic states of North Carolina and Virginia as an emerging contact zone between these two distinct coyote expansion fronts.
Data from: Spatial patterns of the frog Oophaga pumilio in a plantation system are consistent with conspecific attraction
The conspecific attraction hypothesis predicts that individuals are attracted to conspecifics because conspecifics may be cues to quality habitat and/or colonists may benefit from living in aggregations. Poison frogs (Dendrobatidae) are aposematic, territorial, and visually oriented – three characteristics which make dendrobatids an appropriate model to test for conspecific attraction. In this study, we tested this hypothesis using an extensive mark-recapture dataset of the strawberry poison frog (Oophaga pumilio) from La Selva Biological Station, Costa Rica. Data were collected from replicate populations in a relatively homogenous Theobroma cacao plantation, which provided a unique opportunity to test how conspecifics influence spatial ecology of migrants in a controlled habitat with homogeneous structure. We predicted that (1) individuals entering a population would aggregate with resident adults, (2) migrants would share sites with residents at greater frequency than expected by chance, and (3) migrant home-ranges would have shorter nearest-neighbor distances (NND) to residents than expected by chance. The results were consistent with these three predictions: relative to random simulations, we observed significant aggregation, home-range overlap, and NND distribution functions in four, five, and six, respectively, of the six migrant-resident groups analyzed. Conspecific attraction may benefit migrant O. pumilio by providing cues to suitable home sites and/or increasing potential for social interactions with conspecifics; if true, these benefits should outweigh the negative effects of other factors associated with aggregation. The observed aggregation between migrant and resident O. pumilio is consistent with conspecific attraction in dendrobatid frogs, and our study provides rare support from a field setting that conspecific attraction may be a relevant mechanism for models of anuran spatial ecology.
Macroimmunology: the drivers and consequences of spatial patterns in wildlife immune defense
<p>1. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immune phenotypes across spatial scales. Identifying the most important spatial drivers of immunity could help preempt infectious disease risks, especially in the context of how large-scale factors such as urbanization affect defense by changing environmental conditions. 2. We provide a synthesis of how to apply macroecological approaches to the study of ecoimmunology (i.e., macroimmunology). We first review spatial factors that could generate spatial variation in defense, highlighting the need for large-scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favored over small-scale experimental studies. We next conduct a systematic review of the literature to assess the frequency of spatial studies and to classify them according to taxa, immune measures, spatial replication and extent, and statistical methods. 3. We review 210 ecoimmunology studies sampling multiple host populations. We show that whereas spatial approaches are relatively common, spatial replication is generally low and unlikely to provide sufficient environmental variation or power to differentiate competing spatial hypotheses. We also highlight statistical biases in macroimmunology, in that few studies characterize and account for spatial dependence statistically, potentially affecting inferences for the relationships between environmental conditions and immune defense. 4. We use these findings to describe tools from geostatistics and spatial modeling that can improve inference about the associations between environmental and immunological variation. In particular, we emphasize exploratory tools that can guide spatial sampling and highlight the need for greater use of mixed-effects models that account for spatial variability while also allowing researchers to account for both individual- and habitat-level covariates. 5. We lastly discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions, and urbanization as being especially amenable to spatial approaches. We highlight opportunities posed by assessing spatial variation in host tolerance, coupling large-scale field studies with small-scale field experiments and longitudinal approaches, and applying statistical tools from macroecology and meta-analysis to identify generalizable spatial patterns.</p>
Data from: From animal tracks to fine-scale movement modes: a straightforward approach for identifying multiple, spatial movement patterns
1. Thanks to developments in animal tracking technology, detailed data on the movement tracks of individual animals are now attainable for many species. However, straightforward methods to decompose individual tracks into high-resolution, spatial modes are lacking but are essential to understand what an animal is doing. 2. We developed an analytical approach that combines separately-validated methods into a straightforward tool for converting animal GPS tracks to short-range movement modes. Our three-step analytical process comprises: (1) decomposing data into separate movement segments using behavioural change point analysis; (2) defining candidate movement modes and translating them into non-linear or linear equations between net squared displacement (NSD) and time; and (3) fitting each candidate equation to NSD segments and determining the best-fitting modes using Concordance Criteria, Akaike's Information Criteria and other fine-scale segment characteristics. We illustrate our approach for three sub-adults, male wild boar Sus scrofa tracked at 15 min intervals over 4 months using GPS collars. We defined five candidate movement modes based on previously published studies of short-term movements: encamped, ranging, round trips (complete and partial), and wandering. 3. Our approach successfully classified over 80% of the tracks into these movement modes lasting between 5 and 54 hours and covering between 300 m to 20 km. Repeated analyses of GPS data resampled at different rates indicated that one positional fix every 3-4 h was sufficient for >70% classification success. Classified modes were consistent with published observations of wild boar movement, further validating our method. 4. The proposed approach advances the status quo by permitting classification into multiple movement modes (where these are adequately discernable from spatial fixes) facilitating analyses at high temporal and spatial resolutions, and is straightforward, largely objective, and without restrictive assumptions, necessary parameterizations or visual interpretation. Thus, it should capture the complexity and variability of tracked animal movement mode for a variety of taxa across a wide range of spatial and temporal scales.
Data from: Local interactions and self-organized spatial patterns stabilize microbial cross-feeding against cheaters
Mutualisms are ubiquitous, but models predict they should be susceptible to cheating. Resolving this paradox has become relevant to synthetic ecology: cooperative cross-feeding, a nutrient exchange mutualism, has been proposed to stabilize microbial consortia. Previous attempts to understand how cross-feeders remain robust to non-producing cheaters have relied on complex behavior (e.g., cheater punishment) or group selection. Using a stochastic spatial model, we demonstrate two novel mechanisms that can allow cross-feeders to outcompete cheaters, rather than just escape from them. Both mechanisms work through the spatial segregation of the resources, which prevents individual cheaters from acquiring the resources they need to reproduce. First, if microbe dispersal is low but resources are shared widely, then the cross-feeders self-organize into stable spatial patterns. Here the cross-feeders can build up where the resource they need is abundant, and send their resource to where their partner is, separating resources at regular intervals in space. Second, if dispersal is high but resource sharing is local, then random variation in population density creates small-scale variation in resource density, separating the resources from each other by chance. These results suggest that cross-feeding may be more robust than previously expected and offer strategies to engineer stable consortia.
Data from: Spatial patterns of self-recruitment of a coral reef fish in relation to island-scale retention mechanisms
Oceanographic features influence the transport and delivery of marine larvae, and physical retention mechanisms, such as eddies, can enhance self-recruitment (i.e. the return of larvae to their natal population). Knowledge of exact locations of hatching (origin) and settlement (arrival) of larvae of reef animals provides a means to compare observed patterns of self-recruitment 'connectivity' with those expected from water circulation patterns. Using parentage inference based on multiple sampling years in Moorea, French Polynesia, we describe spatial and temporal variation in self-recruitment of the anemonefish Amphiprion chrysopterus, evaluate the consistency of net dispersal distances of self-recruits against the null expectation of passive particle dispersal and test the hypothesis that larvae originating in certain reef habitats (lagoons and passes) would be retained and thus more likely to self-recruit than those originating on the outer (fore) reef. Estimates of known self-recruitment were consistent across the sampling years (~25–27% of sampled recruits). For most (88%) of these self-recruits, the net distance between hatching and settlement locations was within the maximum dispersal distance expected for a neutrally buoyant passive particle based on the longest duration of the larval dispersive phase and the average direction and speed of current flow around Moorea. Furthermore, a parent of a given body size on the outer (fore) reef of Moorea was less likely to produce self-recruits than those in passes. Our findings show that even a simple dispersal model based on net average flow and direction of alongshore currents can provide insight into landscape-scale retention patterns of reef fishes.
Data from: Spatial patterns of neutral and functional genetic variation reveal patterns of local adaptation in raccoon (Procyon lotor) populations exposed to raccoon rabies
Local adaptation is necessary for population survival and depends on the interplay between responses to selective forces and demographic processes that introduce or retain adaptive and maladaptive attributes. Host-parasite systems are dynamic, varying in space and time, where both host and parasites must adapt to their ever-changing environment in order to survive. We investigated patterns of local adaptation in raccoon populations with varying temporal exposure to the raccoon rabies virus (RRV). RRV infects approximately 85% of the population when epizootic and has been presumed to be completely lethal once contracted; however, disease challenge experiments and varying spatial patterns of RRV spread suggest some level of immunity may exist. We first assessed patterns of local adaptation in raccoon populations along the eastern seaboard of North America by contrasting spatial patterns of neutral (microsatellite loci) and functional, major histocompatibility complex (MHC) genetic diversity and structure. We explored variation of MHC allele frequencies in light of temporal population exposure to RRV (0-60 years) and specific RRV strains in infected raccoons. Our results revealed high levels of MHC variation (66 DRB exon 2 alleles) and pronounced genetic structure relative to neutral microsatellite loci, indicative of local adaptation. We found a positive association linking MHC genetic diversity and temporal RRV exposure, but no association with susceptibility and resistance to RRV strains. These results have implications for landscape epidemiology studies seeking to predict the spread of RRV and present an example of how population demographics influence the degree to which populations adapt to local selective pressures.
Data from: Spatial patterns along an elevation gradient in high altitude grasslands, Brazil
The Brazilian high altitude grasslands are important biodiversity centers that contribute to human well being far outside their boundaries. They host many vulnerable species that may go locally extinct as a result of small changes in the environment. Performing studies on local species distribution is important to achieve biodiversity conservation in these areas. This study intended to characterize a high altitude grassland plant community along an elevation gradient in Southeastern Brazil. Simple logistic regression, chi-squared tests and indicator species analysis were performed to investigate respectively whether: (i) the occurrence of botanical families was related to the altitude; (ii) the richness and abundance of life forms varied along the gradient and (iii) there were populations associated with specific altitudinal belts. Rubiaceae and Polygalaceae had higher occurrence probability in higher altitudes. Hemicryptophytes and chamaephytes seem to be the most favored life forms under local extreme conditions such as low temperatures and drought. Vegetation spectra varied significantly along the gradient, highlighting the major role of the turnover of habitats in a local scale in underlying patterns of species distribution. Upper elevations encompassed a high number of indicator species, and further identification of high altitude grasslands' indicator species will provide clues about adaptability of local species, which is important to be considered in ecosystem management and conservation.
Data from: The interplay among acorn abundance and rodent behavior drives the spatial pattern of seedling recruitment in mature Mediterranean oak forests
The patterns of seedling recruitment in animal-dispersed plants result from the interactions among environmental and behavioral variables. However, we know little on the contribution and combined effect of both kinds of variables. We designed a field study to assess the interplay between environment (vegetation structure, seed abundance, rodent abundance) and behavior (seed dispersal and predation by rodents, and rooting by wild boars), and their contribution to the spatial patterns of seedling recruitment in a Mediterranean mixed-oak forest. In a spatially explicit design, we monitored intensively all environmental and behavioral variables in fixed points at a small spatial scale from autumn to spring, as well as seedling emergence and survival. Our results revealed that the spatial patterns of seedling emergence were strongly related to acorn availability on the ground, but not by a facilitationeffect of vegetation cover. Rodents changed seed shadows generated by mother trees by dispersing most seeds from shrubby to open areas, but the spatial patterns of acorn dispersal/predation had no direct effect on recruitment. By contrast, rodents had a strong impact on recruitment as pilferers of cached seeds. Rooting by wild boars also reduced recruitment by reducing seed abundance, but also by changing rodent's behavior towards higher consumption of acorns in situ. Hence, seed abundance and the foraging behavior of scatter-hoarding rodents and wild boars are driving the spatial patterns of seedling recruitment in this mature oak forest, rather than vegetation features. The contribution of vegetation to seedling recruitment (e.g. facilitation by shrubs) may be context dependent, having a little role in closed forests, or being overridden by directed seed dispersal from shrubby to open areas. We warn about the need of using broad approaches that consider the combined action of environment and behavior to improve our knowledge on the dynamics of natural regeneration in forests.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.