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495 results for “spatial scale”
Data from: Ant diversity in Neotropical savannas: hierarchical processes acting at multiple spatial scales
1. Understanding what creates and maintains macroscale biodiversity gradients is a central focus of ecological and evolutionary research. Spatial patterns in diversity are driven by a hierarchy of factors operating at multiple scales. Historical and climatic factors drive large-scale patterns of diversity by affecting the size of regional species pools, while habitat heterogeneity or microhabitat characteristics further influence species coexistence at small scales. 2. We tested the degree to which the species-energy, historical factors, habitat heterogeneity and local environment hypotheses explain observed patterns of ant diversity across hierarchical spatial scales. 3. We sampled ground-dwelling ants at 29 sites within a Neotropical savanna region, the Brazilian Cerrado. We measured species density – an abundance-dependent diversity metric – and rarefied species richness – an abundance-independent metric – at spatial scales with varying grain sizes. For each hypothesis, two correlates were used to predict ant diversity patterns: i) species-energy: rainfall and productivity; ii) historical factors: historical variation in rainfall and refugial areas; iii) habitat heterogeneity: heterogeneity in greenness and diversity of land cover; iv) local factors: contents of sand and coarse fragments in the soil. 4. Ant diversity patterns correlated to net primary productivity and to the proportion of coarse fragments in the soil, corroborating the species-energy and local environment hypotheses, respectively. Soil negatively influenced species density, but not rarefied species richness, which was positively influenced by productivity. We found scale dependencies in the effects of soil/productivity on species density; productivity best predicted species density patterns at large scales, since sampling completeness offset the abundance-driven effects of soil. 5. Considering abundance differences may help to discern the mechanisms underlying the relationship between macroscale diversity patterns and its ecological drivers. Plant productivity affected ant diversity independently of abundance, possibly by limiting the size of regional species pools. On the other hand, soil properties had an abundance-dependent effect on ant diversity, indicating a sampling mechanism. Our findings are consistent with predictions of the hierarchical theory of diversity. Large-scale patterns of productivity limit regional diversity, an effect that cascades down to finer spatial scales, where soil properties influence the number of coexisting species.
Data from: Small-scale spatial variation in infection risk shapes the evolution of a Borrelia resistance gene in wild rodents
Spatial variation in pathogen-mediated selection is predicted to influence the evolutionary trajectory of host populations and lead to spatial variation in their immunogenetic composition. However, to date few studies have been able to directly link small-scale spatial variation in infection risk to host immune gene evolution in natural, non-human populations. Here we use a natural rodent-Borrelia system to test for associations between landscape-level spatial variation in Borrelia infection risk along replicated elevational gradients in the Swiss Alps and Toll-like receptor 2 (TLR2) evolution, a candidate gene for Borrelia resistance, across bank vole (Myodes glareolus) populations. We found that Borrelia infection risk (i.e. the product of Borrelia prevalence in questing ticks and the average tick load of voles at a sampling site) was spatially variable and significantly negatively associated with elevation. Across sampling sites, Borrelia prevalence in bank voles was significantly positively associated with Borrelia infection risk along the elevational clines. We observed a significant association between naturally occurring TLR2 polymorphisms in hosts and their Borrelia infection status. The TLR2 variant associated with a reduced likelihood of Borrelia infection was most common in rodent populations at lower elevations that face a high Borrelia infection risk, and its frequency changed in accordance with the change in Borrelia infection risk along the elevational clines. These results suggest that small-scale spatial variation in parasite-mediated selection affects the immunogenetic composition of natural host populations, providing a striking example that the microbial environment shapes the evolution of the host's immune system in the wild.
Data from: Speciation has a spatial scale that depends on levels of gene flow
Area is generally assumed to affect speciation rates, but work on the spatial context of speciation has focused mostly on patterns of range overlap between emerging species rather than on questions of geographical scale. A variety of geographical theories of speciation predict that the probability of speciation occurring within a given region should (1) increase with the size of the region and (2) increase as the spatial extent of intraspecific gene flow becomes smaller. Using a survey of speciation events on isolated oceanic islands for a broad range of taxa, we find evidence for both predictions. The probability of in situ speciation scales with island area in bats, carnivorous mammals, birds, flowering plants, lizards, butterflies and moths, and snails. Ferns are an exception to these findings, but they exhibit high frequencies of polyploid and hybrid speciation, which are expected to be scale independent. Furthermore, the minimum island size for speciation correlates across groups with the strength of intraspecific gene flow, as is estimated from a meta‐analysis of published population genetic studies. These results indicate a general geographical model of speciation rates that are dependent on both area and gene flow. The spatial scale of population divergence is an important but neglected determinant of broad‐scale diversity patterns.
Data from: Genetic rescue by distant trees mitigates qualitative pollen limitation imposed by fine-scale spatial genetic structure
Restricted seed dispersal frequently leads to fine-scale spatial genetic structure (i.e., FSGS) within plant populations. Depending on its spatial extent and the mobility of pollinators, this inflated kinship at the immediate neighbourhood can critically impoverish pollen quality. Despite the common occurrence of positive FSGS within plant populations, our knowledge regarding the role of long-distance pollination preventing reproductive failure is still limited. Using microsatellite markers, we examined the existence of positive FSGS in two low-density populations of the tree Pyrus bourgaeana. We also designed controlled crosses among trees differing in their kinship to investigate the effects of increased local kinship on plant reproduction. We used six pollination treatments and fully monitored fruit production, fruit and seed weight, proportion of mature seeds per fruit, and seed germination. Our results revealed positive FSGS in both study populations and lower fruit initiation in flowers pollinated with pollen from highly-genetically related individuals within the neighbourhood, with this trend intensifying as the fruit development progressed. Besides, open-pollinated flowers exhibited lower performance of compared to those pollinated by distant pollen donors, suggesting intense qualitative pollen limitation in natural populations. We found positive fine-scale spatial genetic structure is translated into impoverished pollen quality from nearby pollen donors which negatively impacts the reproductive success of trees in low-density populations. Under this scenario of intrapopulation genetic rescue by distant pollen donors, the relevance of highly-mobile pollinators for connecting spatially and genetically distant patches of trees may be crucial to safeguarding population recruitment.
Data from: Spatial and temporal aridity gradients provide poor proxies for plant-plant interactions under climate change: a large-scale experiment
1. Plant-plant interactions may critically modify the impact of climate change on plant communities. However, the magnitude and even direction of potential future interactions remains highly debated, especially for water limited ecosystems. Predictions range from increasing facilitation to increasing competition with future aridification. 2. The different methodologies used for assessing plant-plant interactions under changing environmental conditions may affect the outcome but they are not equally represented in the literature. Mechanistic experimental manipulations are rare compared to correlative approaches that infer future patterns from current observations along spatial climatic gradients. 3. Here, we utilize a unique climatic gradient in combination with a large-scale, long-term experiment to test whether predictions about plant-plant interactions yield similar results when using experimental manipulations, spatial gradients or temporal variation. We assessed shrub-annual interactions in three different sites along a natural rainfall gradient (spatial) during 9 years of varying rainfall (temporal) and 8 years of dry and wet manipulations of ambient rainfall (experimental) that closely mimicked regional climate scenarios. 4. The results were fundamentally different among all three approaches. Experimental water manipulations hardly altered shrub effects on annual plant communities for the assessed fitness parameters biomass and survival. Along the spatial gradient, shrub effects shifted from clearly negative to mildly facilitative towards drier sites, whereas temporal variation showed the opposite trend: more negative shrub effects in drier years. 5. Based on our experimental approach, we conclude that shrub-annual interaction will remain similar under climate change. In contrast, the commonly applied space-for time approach based on spatial gradients would have suggested increasing facilitative effects with climate change. We discuss potential mechanisms governing the differences among the three approaches. 6. Our study highlights the critical importance of long-term experimental manipulations for evaluating climate change impacts. Correlative approaches, e.g. along spatial or temporal gradients, may be misleading and overestimate the response of plant-plant interactions to climate change.
Data from: Fine scale spatial variability in the influence of environmental cycles on the occurrence of dolphins at coastal sites
Environmental cycles often influence the presence of animals, creating patterns at different temporal scales, which may mean that their effects overlap and/or interact. Interactions between diel and seasonal cycles have been reported to influence fish behaviour but little is known about such interactions in marine top predators. Here, we studied the combined effect of seasonal, tidal and diel cycles on the occurrence of bottlenose dolphins (Tursiops truncatus) within a Marine Protected Area in Scotland. Our analyses were based on echolocation detections from passive acoustic devices (CPODs) deployed at three coastal sites between 2010 and 2016. We described patterns of dolphins' occurrence using circular statistics and then used generalised additive mixed models to explore the relative importance of each cycle and any interactions between them. We found site-specific cyclical patterns of presence that remained constant across years. There was a highly significant interaction between seasonal and diel cycles at two sites around deep channels, where occurrence was diurnal in summer but became nocturnal in autumn. The study demonstrates the highly plastic behaviour of bottlenose dolphins and shows a previously unreported behaviour that has management implications for this and other marine protected areas.
Data from: Predicted effects of climate factors on mountain species are not uniform over different spatial scales
The selection of relevant factors and appropriate spatial scale(s) is fundamental when modelling species response to climate change. We evaluated whether the effects of climate factors on species distribution/occurrence are consistently modelled over different spatial scales in birds, and used a two-scale approach to identify species-climate correlations unlikely to represent causal effects. We used passerine birds inhabiting mountain grassland in the Apennines (Italy) as a model. We surveyed four grassland species at 400 sampling points, and built habitat selection models (territory scale) and distribution models (7 algorithms, landscape scale). We compared the effect of climatic predictors on occurrence/distribution highlighted by models over to the two spatial scales, and with the effects supposed a priori based on the climatic niche of each species. Models at the territory level included at least one climatic predictor for three species; the observed effect of climatic predictors was seldom consistent with supposed effects. At the broadest scale, distribution models for all species included climatic predictors, with varying consistence with supposed effects and findings at the finer scale. Despite the importance of climate for species distribution, occurrence could be more directly related to other factors, with important implications for understanding/predicting the impacts of climate/environmental changes. Our approach revealed key variables for grassland birds, and highlighted the scale-dependent perceived importance of climate. At the local scale, climate effects were weak or hard to interpret. We found a general lack of consistence between supposed and observed effects at the territory level, and between landscape and territory models. Our results show the importance of predicting the potential effect of climatic factors prior to the analyses, carefully selecting ecologically meaningful variables and scales, and evaluating the nature and scale of climate-species links. We call for caution when predicting under future climates, especially when mechanistic effects and consistency across scales lack.
Data from: Do spatial scale and life history affect fish-habitat relationships?
1. Understanding how animals interact with their environment is a fundamental ecological question with important implications for conservation and management. The relationships between animals and their habitat, however, can be scale dependent. If ecologists work at suboptimal spatial scales, they will gain an incomplete picture of how animals respond to the landscape. Identifying the scale at which animal-landscape relationships are strongest (the 'scale of effect') will improve our ability to better plan management and conservation activities. 2. Several recent studies have greatly enhanced our knowledge about the scale of effect, and the potential drivers of inter-specific variability, in particular life-history traits. However, while many marine systems are inherently multi-scalar, research into the scale of effect has been mainly focussed on terrestrial taxa. As the scales of observation in fish-habitat association studies are often selected based on convention rather than biological reasoning, they may provide an incomplete picture of the scales where these associations are strongest. 3. We examined fish-habitat associations across four nested spatial scales in a temperate reef system to ask: (1.) at what scale are fish-habitat associations the strongest, (2.) are habitat elements consistently important across scales, and (3.) do scale-dependent fish-habitat associations vary in relation to either body size, geographic range size or trophic level? 4. We found that: (1.) the strongest fish-habitat associations were observed when these relationships were examined at considerably larger spatial scales than usually investigated; (2.) the importance of environmental predictors varied across spatial scales, indicating that conclusions about the importance of habitat elements will depend on the scales at which studies are undertaken; and (3.) scale-dependent fish-habitat associations were consistent across all life-history traits. 5. Our results highlight the importance of considering how animals relate to their environment and suggest the small scales often chosen to examine fish-habitat associations are likely to be suboptimal. Developing a more mechanistic understanding of animal-habitat associations will greatly aid in predicting and managing responses to future anthropogenic disturbances.
Data from: Genetic relatedness does not retain spatial pattern across multiple spatial scales: dispersal and colonization in the coral, Pocillopora damicornis
Patterns of isolation-by-distance are uncommon in coral populations. Here, we depart from historical trends of large-scale, geographic genetic analyses by scaling down to a single patch reef in Kāne'ohe Bay, Hawai'i, and map and genotype all colonies of the coral, Pocillopora damicornis. Six polymorphic microsatellite loci were used to assess population genetic and clonal structure and to calculate individual colony pairwise relatedness values. Our results point to an inbred, highly clonal reef (between 53 and 116 clonal lineages out of 2352 genotyped colonies) with a very skewed genet frequency distribution (over 70% of the reef was composed of just seven genotypes). Spatial autocorrelation analyses revealed that corals found close together on the reef were more genetically related than corals further apart. Spatial genetic structure disappears, however, as spatial scale increases and then becomes negative at the largest distances. Stratified, random sampling of three neighbouring reefs confirms that reefs are demographically open and inter-reef genetic structuring was not detected. Attributing process to pattern in corals is complicated by their mixed reproductive strategies. Separate autocorrelation analyses, however, show that the spatial distribution of both clones and non-clones contribute to spatial genetic structure. Overall, we demonstrate genetic structure on an intra-reef scale and genetic panmixia on an inter-reef scale indicating that, for P. damicornis, small- and large-scale dispersal processes are likely not the same. By starting from an inter-individual, intra-reef level before scaling up to an inter-reef level, this study demonstrates that isolation-by-distance patterns for the coral P. damicornis are limited to small scales and highlights the importance of investigating genetic patterns and ecological processes at multiple scales.
Data from: Fine-scale spatial genetic dynamics over the life-cycle of the tropical tree Prunus africana
Studying fine-scale spatial genetic patterns across life stages is a powerful approach to identify ecological processes acting within tree populations. We investigated spatial genetic dynamics across five life stages in the insect-pollinated and vertebrate-dispersed tropical tree Prunus africana in Kakamega Forest, Kenya. Using six highly polymorphic microsatellite loci, we assessed genetic diversity and spatial genetic structure (SGS) from seed rain and seedlings, and different sapling stages to adult trees. We found significant SGS in all stages, potentially caused by limited seed dispersal and high recruitment rates in areas with high light availability. SGS decreased from seed and early seedling stages to older juvenile stages. Interestingly, SGS was stronger in adults than in late juveniles. The initial decrease in SGS was probably driven by both random and non-random thinning of offspring clusters during recruitment. Intergenerational variation in SGS could have been driven by variation in gene flow processes, overlapping generations in the adult stage or local selection. Our study shows that complex sequential processes during recruitment contribute to SGS of tree populations.
Data from: Termite mounds differ in their importance for herbivores across savanna types, seasons and spatial scales
Herbivores do not forage uniformly across landscapes, but select for patches of higher nutrition and lower predation risk. Macrotermes mounds contain higher concentrations of soil nutrients and support grasses of higher nutritional value than the surrounding savanna matrix, attracting mammalian grazers that preferentially forage on termite mound vegetation. However, little is known about the spatial extent of such termite influence on grazing patterns and how it might differ in time and space. We measured grazing intensity in three African savanna types differing in rainfall and foliar nutrients and predicted that the functional importance of mounds for grazing herbivores would increase as the difference in foliar nutrient levels between mound and savanna matrix grasses increases and the mounds become more attractive. We expected this to occur in nutrient-poor areas and during the dry season when savanna matrix grass nutrient levels are lower. Tuft use and grass N and P content were measured along transects away from termite mounds, enabling calculation of the spatial extent of termite influence on mammalian grazing. Using termite mound densities estimated from airborne light detection and ranging (LiDAR), we further upscaled field-based results to determine the percentage of the landscape influenced by termite activity. Grasses in close proximity to termite mounds were preferentially grazed at all sites and in both seasons, but the strength of mound influence varied between savanna types and seasons. In the wet season, mounds had a relatively larger effect on grazers at the landscape scale in the nutrient-poor, wetter savanna, whereas in the dry season the pattern was reversed with more of the landscape influenced at the nutrient-rich, driest site. Our results reveal that termite mounds enhance the value of savanna landscapes for herbivores, but that their functional importance varies across savanna types and seasons.
Data from: Ecological segregation in a small mammal hybrid zone: habitat-specific mating opportunities and selection against hybrids restrict gene flow on a fine spatial scale
The degree to which closely related species interbreed is determined by a complex interaction of ecological, behavioral, and genetic factors. We examine the degree of interbreeding between two woodrat species, Neotoma bryanti and N. lepida, at a sharp ecological transition. We identify the ecological association of each genotypic class, assess the opportunity for mating between these groups, and test whether they have similar patterns of year-to-year persistence on our study site. We find that 13% of individuals have a hybrid signature but that the two parental populations and backcrosses are highly segregated by habitat type and use. Also, we find that adult hybrids are comparable to parental types in terms of year-to-year persistence on our site but that, among juveniles, significantly fewer hybrids reach adulthood on site compared to their purebred counterparts. Our analyses show that this hybrid zone is maintained by occasional nonassortative mating coupled with hybrid fertility, but that these factors are balanced by lower apparent survival of juvenile hybrids and habitat-based preference or selection that limits heterospecific mating while promoting backcrossing to habitat-specific genotypes. This system presents a novel example of the role that sharp resource gradients play in reproductive isolation and the potential for genetic introgression.
Data from: Spatial pattern and scale influence invader demographic response to simulated precipitation change in an annual grassland community
It is important to predict which invasive species will benefit from future changes in climate, and thereby identify those invaders that need particular attention and prioritization of management efforts. Because establishment, persistence, and spread determine invasion success, this prediction requires detailed demographic information. Explicit study of the impact of pattern on demographic response is particularly important for species that are naturally patchy, such as the invasive grass, Aegilops triuncialis. In the northern California Coast Range, where climate change may increase or decrease mean annual rainfall, we conducted a field experiment to understand the interaction of climate change and local-scale patterning on the demography of A. triuncialis. We manipulated precipitation (reduced, ambient, or augmented), seed density, and seeding pattern. Demographic and environmental data were collected for three years following initial seeding. Pattern and scale figure prominently in the demographic response of A. triuncialis to precipitation manipulation. Pattern interacts with precipitation and seeding density in its influence on per-plant seed output. Although per-plot seed production was highest when seeds were not aggregated, per-plant seed output was higher in aggregated patches. Results suggest aggregation of invasive A. triuncialis reduces the detrimental impact of interspecific competition in its invaded community, and that interspecific competition per se has a stronger impact than intraspecific competition
Data from: Spatial structure of above-ground biomass limits accuracy of carbon mapping in rainforest but large scale forest inventories can help to overcome
Precise mapping of above-ground biomass (AGB) is a major challenge for the success of REDD+ processes in tropical rainforest. The usual mapping methods are based on two hypotheses: a large and long-ranged spatial autocorrelation and a strong environment influence at the regional scale. However, there are no studies of the spatial structure of AGB at the landscapes scale to support these assumptions. We studied spatial variation in AGB at various scales using two large forest inventories conducted in French Guiana. The dataset comprised 2507 plots (0.4 to 0.5 ha) of undisturbed rainforest distributed over the whole region. After checking the uncertainties of estimates obtained from these data, we used half of the dataset to develop explicit predictive models including spatial and environmental effects and tested the accuracy of the resulting maps according to their resolution using the rest of the data. Forest inventories provided accurate AGB estimates at the plot scale, for a mean of 325 Mg.ha-1. They revealed high local variability combined with a weak autocorrelation up to distances of no more than10 km. Environmental variables accounted for a minor part of spatial variation. Accuracy of the best model including spatial effects was 90 Mg.ha-1 at plot scale but coarse graining up to 2-km resolution allowed mapping AGB with accuracy lower than 50 Mg.ha-1. Whatever the resolution, no agreement was found with available pan-tropical reference maps at all resolutions. We concluded that the combined weak autocorrelation and weak environmental effect limit AGB maps accuracy in rainforest, and that a trade-off has to be found between spatial resolution and effective accuracy until adequate "wall-to-wall" remote sensing signals provide reliable AGB predictions. Waiting for this, using large forest inventories with low sampling rate (<0.5%) may be an efficient way to increase the global coverage of AGB maps with acceptable accuracy at kilometric resolution.
Data from: Taxonomic and functional diversity of the co-flowering community differentially affect Cakile edentula pollination at different spatial scales
1. The number of co-flowering species, floral density and floral trait diversity can be major determinants of pollinator-mediated plant-plant interactions in a community. However, evaluation of how each one of these co-flowering components affects the pollination success of a single focal plant species, and how these effects vary at different spatial scales, is lacking. 2. Here we evaluated the effects of functional diversity (flower morphology and colour), taxonomic diversity (reflecting potential sampling effects) and flower density (conspecific and heterospecific), on the pollinator environment (i.e. visitation rate and pollinator diversity), and pollination success (i.e. pollen load size and number of pollen tubes per style) of Cakile edentula (Brassicaceae). We applied structural equation models (SEM's) at the floral-neighbourhood (plot level) and community-wide scales to uncover the factors that mediate co-flowering community effects on C. edentula pollination success. 3. We found that co-flowering community effects at the community level are more important than fine-scale floral-neighbourhood differences in mediating plant pollination success in our study species. Increasing plant functional diversity decreased pollinator visitation rate but increased the diversity of pollinator functional groups visiting C. edentula flowers. Taxonomic diversity negatively affected pollinator diversity suggesting that other unmeasured floral traits may be relevant or that single-species effects (sampling effects) may be important. Overall, our results suggest that functional floral trait diversity in a community may be the most important factor influencing pollination success of species in a community. We also found evidence for intra- and interspecific pollinator competition mediated by flower density but none of these effects seemed to have a significant impact on pollination success. 4. This study is an important step towards understanding the complexity of co-flowering community effects on the pollination success of individual plant species at multiple spatial scales. This study further reveals the potential importance of plant functional diversity in a community in helping predict competitive and facilitative interactions in co-flowering communities. 5. Synthesis. Floral density, taxonomic and functional co-flowering diversity are important drivers of pollination success in flowering plants. The effects of the co-flowering diversity on the pollination success of plant species can largely depend on the spatial scale being studied. Only evaluating the outcomes of pollinator-mediated plant-plant interactions at multiple stages of the pollination process can lead to a complete understanding of their ecological consequences in nature.
Data from: On the spatial scale of dispersal in coral reef fishes
Marine biologists have gone through a paradigm shift, from the assumption that marine populations are largely 'open' due to extensive larval dispersal to the realization that marine dispersal is 'more restricted than previously thought'. Yet, population genetic studies often reveal low levels of genetic structure across large geographic areas. On the other side, more direct approaches such as mark-recapture provide evidence of localized dispersal. To what extent can direct and indirect studies of marine dispersal be reconciled? One approach consists in applying genetic methods that have been validated with direct estimates of dispersal. Here, we use such an approach - genetic isolation-by-distance between individuals in continuous populations - to estimate the spatial scale of dispersal in five species of coral reef fish presenting low levels of genetic structure across the Caribbean. Individuals were sampled continuously along a 220 km transect following the Mesoamerican Barrier Reef, population densities were estimated from surveys covering 17 200 m2 of reef, and samples were genotyped at a total of 58 microsatellite loci. A small but positive isolation-by-distance slope was observed in the five species, providing mean parent-offspring dispersal estimates ranging between 7 and 42 km (CI 1-113 km), and suggesting that there might be a correlation between minimum/maximum PLD and dispersal in coral reef fishes. Coalescent-based simulations indicate that these results are robust to a variety of dispersal distributions and sampling designs. We conclude that low levels of genetic structure across large geographic areas are not necessarily indicative of extensive dispersal at ecological timescales.
Data from: Network-scale effects of invasive species on spatially-structured amphibian populations
<p>Understanding the factors affecting the dynamics of spatially-structured populations (SSP) is a central topic of conservation and landscape ecology. Invasive alien species are increasingly important drivers of the dynamics of native species. However, the impacts of invasives are often assessed at the patch scale, while their effects on SSP dynamics are rarely considered. We used long-term abundance data to test whether the impact of invasive crayfish on subpopulations can also affect the whole SSP dynamics, through their influence on source populations. From 2010 to 2018, we surveyed a network of 58 ponds and recorded the abundance of Italian agile frog clutches, the occurrence of an invasive crayfish, and environmental features. Using Bayesian hierarchical models, we assessed relationships between frog abundance in ponds and a) environmental features; b) connectivity within the SSP; c) occurrence of invasive species at both the patch- and the SSP-levels. If spatial relationships between ponds were overlooked, we did not detect effects of crayfish presence on frog abundance or trends. When we jointly considered habitat, subpopulation, and SSP features, processes acting at all these levels affected frog abundance. At the subpopulation scale, frog abundance in a year was related to habitat features, but was unrelated to crayfish occurrence at that site during the previous year. However, when we considered the SSP level, we found a strong negative relationship between frog abundance in a given site and crayfish frequency in surrounding wetlands during the previous year. Hence, SSP-level analyses can identify effects that would remain unnoticed when focussing on single patches. Invasive species can affect population dynamics even in not invaded patches, through the degradation of subpopulation networks. Patch-scale assessments of the impact of invasive species can thus be insufficient: predicting the long-term interplay between invasive and native populations requires landscape-level approaches accounting for the complexity of spatial interactions.</p>
Data from: Drivers of the spatial scale that best predict primate responses to landscape structure
Understanding the effect of landscape structure on biodiversity is critically needed to improve management strategies. To accurately evaluate such effect, landscape metrics need to be assessed at the correct scale, i.e. considering the spatial extent at which species‐landscape relationship is strongest (scale of effect, SE). Although SE is highly variable, its drivers are poorly known, but of key relevance to understand the way species use the landscape. In this study, we evaluate whether and how species traits, biological responses, landscape variables and the regional context of the study drive SE in Mexican primates. We estimated the relative abundance and immature‐to‐female ratio (a proxy of reproductive success) of howler monkeys (Alouatta palliata and A. pigra) and spider monkeys (Ateles geoffroyi) in 48 forest patches from four rainforest regions (12 patches per region) with different land‐use intensity. We then assessed the composition (forest cover, matrix functionality) and configuration (forest patch density, connectors' density, forest edge density) of local landscapes considering 13 scales (100 to 1300‐m radius) to identify the spatial extent at which each landscape variable best predict each response variable in each species and region. We found that SE did not differ significantly among the drivers evaluated. However, it tended to be lower for connectors' density than for forest patch density and forest edge density, probably because connectors' density is associated with local‐scale processes such as supplementary dynamics. Surprisingly, SE also tended to be higher in the more disturbed region than in the rest of the regions, probably because primates in the more disturbed region used larger areas of the landscape. Our findings therefore suggest that SE depends more strongly on landscape variables and regional context than on species traits and biological responses, and hence, especial caution should be taken when attempting to generalize SE to different explanatory variables and regions.
Data from: A local evaluation of the individual state-space to scale up Bayesian spatial capture recapture
1. Spatial capture-recapture models (SCR) are used to estimate animal density and to investigate a range of problems in spatial ecology that cannot be addressed with traditional non-spatial methods. Bayesian approaches in particular offer tremendous flexibility for SCR modelling. Increasingly, SCR data are being collected over very large spatial extents making analysis computational intensive, sometimes prohibitively so. 2. To mitigate the computational burden of large-scale SCR models, we developed an improved formulation of the Bayesian SCR model that uses local evaluation of the individual state-space (LESS). Based on prior knowledge about a species' home range size, we created square evaluation windows that restrict the spatial domain in which an individual's detection probability (detector window) and activity center location (AC window) are estimated. We used simulations and empirical data analyses to assess the performance and bias of SCR with LESS. 3. LESS produced unbiased estimates of SCR parameters when the AC window width was ≥5σ (σ: the scale parameter of the half-normal detection function), and when the detector window extended beyond the edge of the AC window by 2σ. Importantly, LESS considerably decreased the computation time needed for fitting SCR models. In our simulations, LESS increased the computation speed of SCR models up to 57 fold. We demonstrate the power of this new approach by mapping the density of an elusive large carnivore – the wolverine (Gulo gulo) – with an unprecedented resolution and across the species' entire range in Norway (more than 200 000 km2). 4. Our approach helps overcome a major computational obstacle to population and landscape-level SCR analyses. The LESS implementation in a Bayesian framework makes the customization and fitting of SCR accessible for practitioners that are working at scales that are relevant for conservation and management.
Data from: Differential divergence in autosomes and sex chromosomes is associated with intra-island diversification at a very small spatial scale in a songbird lineage
<p>Recently diverged taxa showing marked phenotypic and ecological diversity are optimal systems to understand the genetic processes underlying speciation. We used genome-wide markers to investigate the diversification of the Reunion grey white eye (<i>Zosterops borbonicus</i>) on the small volcanic island of Reunion (Mascarene archipelago), where this species complex exhibits four geographic forms that are parapatrically distributed across the island and differ strikingly in plumage colour. One form restricted to the highlands is separated by a steep ecological gradient from three distinct lowland forms which meet at narrow hybrid zones that are not associated with environmental variables. Analyses of genomic variation based on SNP data from genotyping-by-sequencing and pooled RADseq approaches, reveal that signatures of selection associated with elevation can be found at multiple regions across the genome, whereas most loci associated with the lowland forms are located on the Z sex chromosome. We identified <i>TYRP1</i>, a Z-linked colour gene, as a likely candidate locus underlying colour variation among lowland forms. Tests of demographic models revealed that highland and lowland forms diverged in the presence of gene flow, and divergence has progressed as gene flow was restricted by selection at loci across the genome. This system is promising to investigate how natural selection and reproductive isolation shape the genomic landscape of divergence at multiple stages of the speciation process.</p>
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.