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Data from: A basin-scale application of environmental DNA assessment for rare endemic species and closely related exotic species in rivers: a case study of giant salamanders in Japan
1. To prevent the invasion of exotic species causing a decline in an endangered endemic species, it is important to determine the distribution of both species at an early stage, when the density of the exotic species is still low, and to manage the invasion immediately. However, distinguishing between closely related species is difficult because they share similar characteristics. 2. The identification of DNA fragments sampled from a body of water (environmental DNA) has become a popular technique for rapidly determining the distribution of a target species. In this study, we analysed environmental DNA in water samples from 37 sites across the Katsura River basin in Japan. We used TaqMan real-time PCR to distinguish the Japanese giant salamander Andrias japonicus from the closely related Chinese giant salamander Andrias davidianus, which is known to invade Japanese rivers and hybridize with the Japanese species. 3. In environmental samples, we detected mtDNA of the endemic species at 25 sites and mtDNA of the exotic species at nine sites. The DNA detection sites were concentrated in the upstream region. The exotic species DNA was found beyond the limits of an earlier capturing survey. 4. Synthesis and applications. Using environmental DNA to monitor the two salamander species requires less time and effort than traditional surveys, so a wide-ranging survey can be conducted rapidly. Our results showed that performing three environmental DNA surveys for each site between autumn and winter is desirable for giant salamanders. Further collection of environmental DNA, in combination with conventional population surveys, will provide valuable information that can help protect rare endemic species in a variety of aquatic ecosystems and can help monitor the invasion of exotic species.
Data from: Applications of random forest feature selection for fine-scale genetic population assignment
Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest, and guided regularized random forest) compared with FST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP dataset for Atlantic salmon (Salmo salar) and a published SNP data set for Alaskan Chinook salmon (Oncorhynchus tshawytscha). In each species, we identified the minimum panel size required to obtain a self-assignment accuracy of at least 90% using each method to create panels of 50-700 markers Panels of SNPs identified using random forest-based methods performed up to 7.8 and 11.2 percentage points better than FST-selected panels of similar size for the Atlantic salmon and Chinook salmon data, respectively. Self-assignment accuracy ≥90% was obtained with panels of 670 and 384 SNPs for each dataset, respectively, a level of accuracy never reached for these species using FST-selected panels. Our results demonstrate a role for machine-learning approaches in marker selection across large genomic datasets to improve assignment for management and conservation of exploited populations.
Evolutionary constraints and adaptation shape the size and colour of rain forest fruits and flowers at continental scale
<p><span><b>Aim:</b> Large-scale patterns in flower and fruit traits provide critical insights into selection processes and the evolutionary history of plant lineages. To isolate and identify the role of selective pressures including different plant-animal interactions, and the factors driving trait evolution, we investigate convergence and divergence between flower and fruit traits in shared environments.</span></p> <p><span><b>Location:</b> Australia to Southeast Asia.</span></p> <p><span><b>Time period: </b>Eocene (~45 My) to Present.</span></p> <p><span><b>Major taxa studied:</b> Woody angiosperm rainforest species (2248 species, 133 families).</span></p> <p><span><b>Methods: </b>Using a continental scale data set for all woody angiosperm species in the Australian rainforest (1816 free-standing and 432 climbing species) we compare the colour and size of fleshy fruits and flowers in relation to life form (trees/shrubs and vines), species biogeographic histories and origins (Sunda vs<i>.</i> Sahul), and bio-regional distributions.</span></p> <p><span><b>Results</b><b>:</b> Fleshy fruits in the Australian rainforest are mostly small, with a diversity of colours (<30mm; 81%), while flowers are mostly small (<10mm; 65%) and whitish (~80%). Compared to trees and shrubs, climbing species showed a higher proportion of red fleshy fruits, and large coloured flowers. Small whitish flowers were dominant across lineages from different biogeographic origins (Sunda-Sahul) and geographical regions, while both small and large fleshy fruits retained a range of disperser attractant colours.</span></p> <p><span><b>Main conclusions:</b> Continental scale size and colour characteristics of flowers and fleshy fruits differed despite sharing environments with similar abiotic selective pressures through time. Plant-animal interactions including pollination and dispersal likely mediate different evolutionary outcomes for plant traits, and reflect both adaptation and evolutionary constraints.</span></p>
Data from: Fire-regime complacency and sensitivity to centennial- through millennial-scale climate change in Rocky Mountain subalpine forests, Colorado, U.S.A.
1. Key uncertainties in anticipating future fire regimes are their sensitivity to climate change, and the degree to which climate will impact fire regimes directly, through increasing the probability of fire, versus indirectly, through changes in vegetation and landscape flammability. 2. We studied the sensitivity of subalpine forest fire regimes (i.e., fire frequency, fire severity) to previously documented climate variability over the past 6000 years, utilizing pollen and macroscopic charcoal from high-resolution lake-sediment records in Rocky Mountain National Park, Colorado. We combined data from the four lakes to provide composite records of vegetation and fire history within a 200 km2 study area. 3. Rates of forest burning were relatively complacent to millennial-scale summer cooling and decreased effective moisture. Mean return intervals between fire episodes, defined over 500-year periods, generally varied between 150-250 years, consistent with tree-ring-based estimates spanning recent centuries. Variability around these long-term means, however, was significantly correlated with variability in summer moisture (i.e., more burning with drier summers), inferred from existing lake-level and supporting paleoenvironmental records. 4. The most pronounced change in fire regimes was in response to decreased subalpine forest density ca. 2400 cal. year BP, itself a response to regional cooling. This indirect impact of climate was followed by a decrease in charcoal production per fire, a proxy for crown-fire severity, while the long-term rate of burning remained unchanged. Over the last 1500 years, increased summer evaporation and drought frequency were associated with increased fire severity, highlighting a direct link between fire and climate. 5. Synthesis: Subalpine forest fire history reveals complacency and sensitivity of fire regimes to changing vegetation and hydroclimate over the past 6000 years. Complacency is highlighted by non-varying fire frequency over millennia. Sensitivity is evident through changes in biomass burned per fire (and inferred fire severity), in response to climate-induced changes in forest density and, more recently, increased summer drought. Overall, the paleo record suggests that (i) fire severity may be more responsive to climate change than fire frequency in Rocky Mountain subalpine forests, and (ii) the indirect impacts of climate on vegetation and fuels are important mechanisms determining fire-regime response to climate change.
Data from: The large-scale drivers of population declines in a long-distance migratory shorebird
Migratory species can travel tens of thousands of kilometers each year, spending different parts of their annual cycle in geographically distinct locations. Understanding the drivers of population change is vital for conserving migratory species, yet the challenge of collecting data over entire geographic ranges has hindered attempts to identify the processes leading to observed population changes. Here, we use remotely sensed environmental data and count data to investigate the factors driving variability in abundance in two subspecies of a long-distance migratory shorebird, the bar-tailed godwit (Limosa lapponica). We compiled a spatially and temporally explicit dataset of three environmental variables to identify the conditions experienced by each subspecies in each stage of their annual cycle (breeding, non-breeding and staging). We used a Bayesian N-mixture model to analyze 18 years of monthly count data from 21 sites across Australia and New Zealand in relation to the remote sensing datasets. We found that the abundance of one subspecies (L. l. menzbieri) in their non-breeding range was related to climate conditions in breeding grounds, and detected sustained population declines between 1995 and 2012 in both subspecies (L. l. menzbieri, -6.7% and L. l. baueri, -2.1% year-1). To investigate the possible causes of the declines, we quantified changes in habitat extent at 22 migratory staging sites in the Yellow Sea, East Asia, over a 25-year period and found -1.7% and -1.2% year-1 loss of habitat at staging sites used by L. l. menzbieri and L. l baueri, respectively. Our results highlight the need to identify environmental and anthropogenic drivers of population change across all stages of migration to allow the formulation of effective conservation strategies across entire migratory ranges.
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: Detecting small-scale genotype-environment interactions in apomictic dandelion (Taraxacum officinale) populations
Studies of genotype × environment interactions (G×E) and local adaptation provide critical tests of natural selection's ability to counter opposing forces such as gene flow. Such studies may be greatly facilitated in asexual species, given the possibility for experimental replication at the level of true genotypes (rather than populations) and the possibility of using molecular markers to assess genotype-environment associations in the field (neither of which is possible for most sexual species). Here we tested for G×E in asexual dandelions (Taraxacum officinale) by subjecting six genotypes to experimental drought, mown, and benign (control) conditions, and subsequently using microsatellites to assess genotype-environment associations in the field. We found strong G×E, with genotypes that performed poorly under benign conditions showing the highest performance under stressful conditions (drought or mown). Our six focal genotypes comprise >80% of plants in local populations. The most common genotype in the field showed its highest relative performance under mown conditions (the most common habitat in our study area), and almost all plants of this genotype in the field were found growing in mowed lawns. Genotypes performing best under benign experimental conditions were found most frequently in unmown conditions in the field. These results are strongly indicative of local adaptation at a very small scale, with unmown microsites of only a few square meters typically embedded within larger mown lawns. By studying an asexual species we were able to map genotypes with known ecological characteristics to environments with high spatial precision.
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: Large-scale parentage analysis reveals reproductive patterns and heritability of spawn timing in a hatchery population of steelhead (Oncorhynchus mykiss)
Understanding life history traits is an important first step in formulating effective conservation and management strategies. The use of artificial propagation and supplementation as such a strategy can have numerous effects on the supplemented natural populations and minimizing life history divergence is crucial in minimizing these effects. Here, we use single nucleotide polymorphism (SNP) genotypes for large-scale parentage analysis and pedigree reconstruction in a hatchery population of steelhead, the anadromous form of rainbow trout. Nearly complete sampling of the broodstock for several consecutive years in two hatchery programmes allowed inference about multiple aspects of life history. Reconstruction of cohort age distribution revealed a strong component of fish that spawn at 2 years of age, in contrast to programme goals and distinct from naturally spawning steelhead in the region, which raises a significant conservation concern. The first estimates of variance in family size for steelhead in this region can be used to calculate effective population size and probabilities of inbreeding, and estimation of iteroparity rate indicates that it is reduced by hatchery production. Finally, correlations between family members in the day of spawning revealed for the first time a strongly heritable component to this important life history trait in steelhead and demonstrated the potential for selection to alter life history traits rapidly in response to changes in environmental conditions. Taken together, these results demonstrate the extraordinary promise of SNP-based pedigree reconstruction for providing biological inference in high-fecundity organisms that is not easily achievable with traditional physical tags.
Data from: Community- weighted mean plant traits predict small scale distribution of insect root herbivore abundance
Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive- and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity.
Data from: Fine-scale refuges can buffer demographic and genetic processes against short-term climatic variation and disturbance: a 22 year case study of an arboreal marsupial
Ecological disturbance and climate are key drivers of temporal dynamics in the demography and genetic diversity of natural populations. Microscale refuges are known to buffer species' persistence against environmental change, but the effects of such refuges on demographic and genetic patterns in response to short-term environmental variation are poorly understood. We quantified demographic and genetic responses of mountain brushtail possums (Trichosurus cunninghami) to rainfall variability (1992–2013) and to a major wildfire. We hypothesized that there would be underlying differences in demographic and genetic processes between an unburnt mesic refuge and a topographically exposed zone that was burnt in 2009. Fire caused a 2-year decrease in survival in the burnt zone, but the population grew after the fire due to immigration, leading to increased expected heterozygosity. We documented a fire-related behavioural shift, where the rate of movement by individuals in the unburnt refuge to the burnt zone decreased after fire. Irrespective of the fire, there were long-term differences in demographic and genetic parameters between the mesic/unburnt refuge and the nonmesic/burnt zone. Survival was high and unaffected by rainfall in the refuge, but lower and rainfall-dependent in the nonmesic zone. Net movement of individuals was directional, from the mesic refuge to the nonmesic zone, suggesting fine-scale source–sink dynamics. There were higher expected heterozygosity (HE) and temporal genetic stability in the refuge, but lower HE and marked temporal genetic structure in the exposed habitat, consistent with reduced generational overlap caused by elevated mortality and immigration. Thus, fine-scale refuges can mediate the short-term demographic and genetic effects of climate and ecological disturbance.
The magnitude of large-scale tree mortality caused by the invasive pathogen Phytophthora ramorum
<p>Forest pathogens are important drivers of tree mortality across the globe but it is exceptionally challenging to gather and build unbiased quantitative models of their impacts, which has resulted in few estimates matching the scale of disease. Here we harness the rare dataset matching the spatial scale of pathogen invasion, host, and disease heterogeneity to estimate infection and mortality for the four most susceptible host species of <em>Phytophthora ramorum</em>, an invasive pathogen that drives the most important biological cause of tree mortality in a broad geographic region of coastal California and southwest Oregon. As of 2012, the most current field survey year, we estimate 17.5 (± 4.6 95% CI) million tanoak (<em>Notholithocarpus densiflorus)</em> stems were pathogen-killed with an additional 71 (± 21.5) million infected. We estimated 9.0 million (± 2.2) coast live oak (<em>Quercus agrifolia)</em> and 1.7 million (± 0.5) California black oak (<em>Quercus kelloggii</em>) stems are disease impacted (mortality and infection combined). Lastly, our estimates showed 95.23 million (± 8.6) million infected California bay laurel (<em>Umbellularia californica</em>), which does not suffer mortality from infection and represents a critical source of continued spread. Using an extensive dataset on mortality rates of infected individuals we estimate that cumulative mortality likely increased from 20.8 to 42.8 million individual stems between 2012 and 2019 for all species. While these impacts are substantial, the majority of host populations occur in a yet to be invaded region of northern California indicating that the disease will intensify in the coming decades.</p>
Data from: Whole-genome patterns of linkage disequilibrium across flycatcher populations clarify the causes and consequences of fine-scale recombination rate variation in birds
Recombination rate is heterogeneous across the genome of various species, and so are genetic diversity and differentiation as a consequence of linked selection. However, we still lack a clear picture of the underlying mechanisms for regulating recombination. Here we estimated fine-scale population recombination rate based on the patterns of linkage disequilibrium (LD) across the genomes of multiple populations of two closely related flycatcher species (Ficedula albicollis and F. hypoleuca). This revealed an overall conservation of the recombination landscape between these species at the scale of 200-kb, but we also identified differences in the local rate of recombination despite their recent divergence (<1 million years). Genetic diversity and differentiation were associated with recombination rate in a lineage-specific manner, indicating differences in the extent of linked selection between species. We detected 400-3,085 recombination hotspots per population. Location of hotspots was conserved between species, but the intensity of hotspot activity varied between species. Recombination hotspots were primarily associated with CpG islands (CGIs), regardless of whether CGIs were at promoter regions or away from genes. Recombination hotspots were also associated with specific transposable elements (TEs), but this association appears indirect due to shared preferences of the transposition machinery and the recombination machinery for accessible open chromatin regions. Our results suggest that CGIs are a major determinant of the localization of recombination hotspots, and we propose that both the distribution of TEs and fine-scale variation in recombination rate may be associated with the evolution of the epigenetic landscape.
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: Body-size scaling of metabolic rate in the trilobite Eldredgeops rana
We infer the body-size scaling slope of metabolic rate in a trilobite by applying a cell-size model that has been proposed to explain metabolic scaling in living organisms. This application is especially tractable in fossil arthropods with well-preserved compound eyes because the number and size of eye facets appear to be useful proxies for the relative number and size of cells in the body. As a case study, we examined the ontogenetic scaling of facet size and number in a ∼390-Myr-old local assemblage of the trilobite Eldredgeops rana, which has well-preserved compound eyes and a wide body-size range. Growth in total eye lens area resulted from increases in both facet area and number in relatively small (presumably young) specimens, but only from increases in facet area in large (presumably more mature) specimens. These results suggest that early growth in E. rana involved both cell multiplication and enlargement, whereas later growth involved only cell enlargement. If the cell-size model is correct, then metabolic rate scaled allometrically in E. rana, and the scaling slope of log metabolic rate versus log body mass decreased from ∼0.85 to 0.63 as these animals grew. This inferred age-specific change in metabolic scaling is consistent with similar changes frequently observed in living animals. Additional preliminary analyses of literature data on other trilobites also suggest that the metabolic scaling slope was <1 in benthic species, but ∼1 in pelagic species, as has also been observed in living invertebrates. The eye-facet size (EFS) method featured here opens up new possibilities for examining the bioenergetic allometry of extinct arthropods.
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: Density dependence and population regulation in marine fish: a large-scale, long-term field manipulation
Do small-scale experiments showing spatial density dependence in marine fishes scale-up to temporal density dependence and regulation of relatively large local populations? If so, what are the causative mechanisms and their implications? We conducted an 8-year multi-generation study of population dynamics of bicolor damselfish (Stegastes partitus) inhabiting four large coral reefs in the Bahamas. After a 4-year baseline period, it was clear that two populations naturally received very few settlement-stage larvae, so recruitment of recently settled fish was artificially enhanced at one low-settlement reef and reduced at one high-settlement reef to ensure a broad range of population sizes over which to test for regulation. Over all 8 years, populations on the two naturally high-settlement reefs experienced temporal density dependence in multiple per capita demographic rates mortality, survival to adulthood, and fecundity. These local populations also displayed components of regulation persistence, boundedness, and return tendency. Reefs supporting regulated populations were structurally complex, providing sufficient prey refuges that ensured high survival at low densities. In contrast, populations at low-settlement reefs experienced either density-independent or slightly inversely density-dependent demographic rates, even though recruitment was artificially augmented to high levels at one reef. There was no evidence of regulation at these reefs, and indeed, one local population suffered temporary extirpation. Here, habitat complexity was relatively low, increasing the risk of predation, especially at low population densities when fish would have to travel longer distances when finding mates or home sites inhabited by conspecifics. Among all demographic parameters, density dependence in individual growth (an indicator of within-species competition for food) was least correlated with the presence or absence of local population regulation. We conclude that, for systems like these, the environmental context of a local population -- especially predation risk and the distribution and abundance of spatial refuges -- is more important than the magnitude of larval supply alone in determining the existence of regulating density dependence. At the broader metapopulation scale, density dependence in both survival and fecundity exogenously caused by predation may provide regulation for the entire stock, even when endogenous within-species competition (assumed to be important in most fisheries models) is weak.
Multi-scale landscape genetics of American marten at their southern range periphery
<p>American marten (<i>Martes americana</i>) are a conservation priority in many forested regions of North America. Populations are fragmented at the southern edge of their distribution due to suboptimal habitat conditions. Facilitating gene flow may improve population resilience through genetic and demographic rescue. We used a multi-scale approach to estimate the relationship between genetic connectivity and landscape characteristics among individuals at three scales in the northeastern United States: regional, subregional, and local. We integrated multiple modeling techniques and identified top models based on consensus. Top models were used to parameterize resistance surfaces at each scale, and circuit theory was used to identify potential movement corridors.</p> <p>Regional gene flow was affected by forest cover, climate, developed land cover, and slope. At subregional and local scales, effects were site-specific and included subsets of climate, developed land cover, and slope. Developed land cover significantly affected gene flow in all sites examined at each scale. The effect of slope on gene flow was positive or negative depending on the site examined. At finer scales, reduced variance in forest cover may have limited the ability to detect a relationship with gene flow. Occupancy probability was a relatively poor predictor and we caution its use as a proxy for landscape resistance. Our results underscore the importance of replication and multi-scale approaches in landscape genetics. Climate warming and landscape conversion may reduce the genetic connectivity of marten populations in the northeastern United States and represent the primary challenges to marten conservation at the southern periphery of their range.</p>
Resolving fine-scale population structure and fishery exploitation using sequenced microsatellites in a northern fish
<p>The resiliency of populations and species to environmental change is dependent on the maintenance of genetic diversity, and as such quantifying diversity is central to combatting ongoing wide spread reductions in biodiversity. With the advent of next-generation sequencing, several methods now exist for resolving fine-scale population structure, but the comparative performance of these methods for genetic assignment has rarely been tested. Here we evaluate the performance of sequenced microsatellites and a single nucleotide polymorphism (SNP) array to resolve fine-scale population structure in a critically important salmonid in northeastern Canada, Arctic charr (<i>Salvelinus alpinus</i>). We also assess the utility of sequenced microsatellites for fisheries applications by quantifying the spatial scales of movement and exploitation through genetic assignment of fishery samples to rivers of origin and comparing these results with a 29-year tagging dataset. Self-assignment and simulation-based analyses of 111 genome-wide microsatellite loci and 500 informative SNPs from 28 populations of Arctic charr in northeastern Canada identified largely river-specific genetic structure. Despite large differences (~4X) in the number of loci surveyed between panels, mean self-assignment accuracy was similar with the SNP panel and with the microsatellite loci (>90%). Subsequent analysis of 996 fishery-collected samples using the microsatellite panel revealed that larger rivers contribute greater numbers of individuals to the fishery, and that coastal fisheries largely exploit individuals originating from nearby rivers, corroborating results from traditional tagging experiments. Our results demonstrate the efficacy of sequence-based microsatellite genotyping to advance understanding of fine-scale population structure and harvest composition in northern and understudied species.</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.