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1,454 results for “large scale”
Data from: Genetic diversity is largely unpredictable but scales with museum occurrences in a species-rich clade of Australian lizards
Genetic diversity is a fundamental characteristic of species and is affected by many factors, including mutation rate, population size, life history and demography. To better understand the processes that influence levels of genetic diversity across taxa, we collected genome-wide restriction-associated DNA data from more than 500 individuals spanning 76 nominal species of Australian scincid lizards in the genus Ctenotus. To avoid potential biases associated with variation in taxonomic practice across the group, we used coalescent-based species delimitation to delineate 83 species-level lineages within the genus for downstream analyses. We then used these genetic data to infer levels of within-population genetic diversity. Using a phylogenetically informed approach, we tested whether variation in genetic diversity could be explained by population size, environmental heterogeneity or historical demography. We find that the strongest predictor of genetic diversity is a novel proxy for census population size: the number of vouchered occurrences in museum databases. However, museum occurrences only explain a limited proportion of the variance in genetic diversity, suggesting that genetic diversity might be difficult to predict at shallower phylogenetic scales.
Data from: Rapid adaptation in large populations with very rare sex: scalings and spontaneous oscillations
Genetic exchange in microbes and other facultative sexuals can be rare enough that evolution is almost entirely asexual and populations almost clonal. But the benefits of genetic exchange depend crucially on the diversity of genotypes in a population. How very rare recombination together with the accumulation of new mutations shapes the diversity of large populations and gives rise to faster adaptation is still poorly understood. This paper analyzes a particularly simple model: organisms with two asexual chromosomes that can reassort during rare matings that occur at a rate r. The speed of adaptation for large population sizes, N, is found to depend on the ratio ∼ log(Nr)/log(N). For larger populations, the r needed to yield the same speed deceases as a power of N. Remarkably, the population undergoes spontaneous oscillations alternating between phases when the fittest individuals are created by mutation and when they are created by reassortment, which—in contrast to conventional regimes—decreases the diversity. Between the two phases, the mean fitness jumps rapidly. The oscillatory dynamics and the strong fluctuations this induces have implications for the diversity and coalescent statistics. The results are potentially applicable to large microbial populations, especially viruses that have a small number of chromosomes. Some of the key features may be more broadly applicable for large populations with other types of rare genetic exchange.
Data from: Novel bird responses to successive large-scale, landscape transformations
Transformation of intact vegetation into new kinds and configurations of human-modified habitats is a well established driver of biodiversity loss. Following initial conversion, many human-dominated landscapes are then subject to further large-scale changes in land use. The impacts on biodiversity of repeated changes in land use remain poorly known, particularly how changes in the matrix interact with initial patterns of vegetation clearing. We used an 18-year study of birds in remnant patches of endangered temperate woodland in south-eastern Australia to quantify the spatial and temporal effects of successive land use transformation in the surrounding landscape. We examined bird response to: (1) initial patterns of landscape modification (creating semi-cleared grazing land dominated by pastures that surrounded remnant woodland patches), (2) subsequent establishment and maturation of exotic tree plantations on the pastures surrounding woodland patches, and (3) additive and interactive effects of both types of landscape transformation. The majority of the 57 bird species modelled responded to conversion of grazing land to exotic plantations, either independently from initial patterns of landscape transformation (20 species), or interactively (18 species) or additively (15 species) with initial landscape transformation. The occurrence of only one species (the Common Bronzewing) was related to patterns of initial transformation but not subsequent transformation due to plantation establishment. Thus, despite many characteristics of the woodland patches within the plantation remaining largely unaltered throughout our 18 year investigation, the matrix had a profound effect on the kinds of species inhabiting them, with such impacts often magnified over time as the matrix continued to change. Plantation establishment triggered new regional-level spatial processes with effects on birds detected in woodland patches up to 2 km away from the plantation. Matrix conversion selected for species with different traits (size, diet and movement patterns) compared to the initial transformation, suggesting it is acting as a different filter on the bird community. New kinds of landscape transformation (such as plantation establishment on previously cleared land) can radically affect the species that have persisted for many decades in previously modified landscapes. This highlights the challenges, but also opportunities, for conserving taxa in ever changing human-dominated environments.
Data from: An optimized protocol for large-scale in situ sampling and analysis of volatile organic compounds
Chemical ecology is an ever‐expanding field with a growing interest in population‐ and community‐level studies. Many such studies are hindered due to lack of an efficient and accelerated protocol for large‐scale sampling and analysis of chemical compounds. Here, we present an optimized protocol for such large‐scale study of volatiles. A large‐scale in situ study to understand role of semiochemicals in variation in mating success of lekking blackbuck was conducted. Suitable methods for sampling and statistical analysis were identified by testing and comparing the efficiencies of available techniques to reduce analysis time while retaining sensitivity and comprehensiveness. Solid‐phase extraction using polydimethylsiloxane, analysis using a semiautomated detection of retention time and base peak, and statistical analysis using random forest algorithm were identified as the most efficient methods for large‐scale in situ sampling and analysis of volatiles. The protocol for large‐scale volatile analysis can facilitate evolutionary and metaecological studies of volatiles in situ from all types of biological samples. The protocol has potential for wider application with the analysis and interpretation methods being suitable for all kinds of semiochemicals, including nonvolatile chemicals.
Data from: Large-scale genetic panmixia in the blue shark (Prionace glauca): a single worldwide population, or a genetic lag-time effect of the "grey zone" of differentiation?
The blue shark Prionace glauca, among the most common and widely studied pelagic sharks, is a top predator, exhibiting the widest distribution range. However, little is known about its population structure and spatial dynamics. With an estimated removal of 10 to 20 million individuals per year by fisheries, the species is classified as "Near Threatened" by International Union for Conservation of Nature. We lack the knowledge to forecast the long-term consequences of such a huge removal on this top predator itself and on its trophic network. The genetic analysis of more than 200 samples collected at broad scale (from Mediterranean Sea, North Atlantic and Pacific Oceans) using mtDNA and nine microsatellite markers allowed to detect signatures of genetic bottlenecks but a nearly complete genetic homogeneity across the entire studied range. This apparent panmixia could be explained by a genetic lag-time effect illustrated by simulations of demographic changes that were not detectable through standard genetic analysis before a long transitional phase here introduced as the "population grey zone". The results presented here can thus encompass distinct explanatory scenarios spanning from a single demographic population to several independent populations. This limitation prevents the genetic-based delineation of stocks and thus the ability to anticipate the consequences of severe depletions at all scales. More information is required for the conservation of population(s) and managements of stocks, which may be provided by large scale sampling not only of individuals worldwide, but also of loci genome-wide.
Data from: Small beetle, large-scale drivers: how regional and landscape factors affect outbreaks of the European spruce bark beetle
Unprecedented bark beetle outbreaks have been observed for a variety of forest ecosystems recently, and damage is expected to further intensify as a consequence of climate change. In Central Europe, the response of ecosystem management to increasing infestation risk has hitherto focused largely on the stand level, while the contingency of outbreak dynamics on large-scale drivers remains poorly understood. To investigate how factors beyond the local scale contribute to the infestation risk from Ips typographus (Col., Scol.), we analysed drivers across seven orders of magnitude in scale (from 103 to 1010 m²) over a 23-year period, focusing on the Bavarian Forest National Park. Time-discrete hazard modelling was used to account for local factors and temporal dependencies. Subsequently, beta regression was applied to determine the influence of regional and landscape factors, the latter characterized by means of graph theory. We found that in addition to stand variables, large-scale drivers also strongly influenced bark beetle infestation risk. Outbreak waves were closely related to landscape-scale connectedness of both host and beetle populations as well as to regional bark beetle infestation levels. Furthermore, regional summer drought was identified as an important trigger for infestation pulses. Large-scale synchrony and connectivity are thus key drivers of the recently observed bark beetle outbreak in the area. Synthesis and applications. Our multiscale analysis provides evidence that the risk for biotic disturbances is highly dependent on drivers beyond the control of traditional stand-scale management. This finding highlights the importance of fostering the ability to cope with and recover from disturbance. It furthermore suggests that a stronger consideration of landscape and regional processes is needed to address changing disturbance regimes in ecosystem management.
Data from: Patterns of local community composition are linked to large-scale diversification and dispersal of clades
At any location, a group of organisms may be represented by several clades. What determines which clades will dominate local communities in terms of their species richness? Here, this relatively neglected question is addressed by analyzing 166 local assemblages of snakes distributed globally. For most regions, local assemblages are dominated by clades with higher global-scale diversification rates and more frequent dispersal into each region, and not by clades that have been present in that region longer. This result contrasts with many other studies of local richness (in other organisms), which show strong impacts of regional colonization time on overall local species richness of clades. Furthermore, even though local assemblages are assembled independently on different continents, most regions have converged on similar patterns of proportional richness. Specifically, a few rapidly diversifying clades dominate most communities around the world. The high diversification rates of these clades are then linked to their high dispersal rates. Similar patterns may occur in many groups, such as plants, frogs, salamanders, birds, and mammals.
Data from: Template for using biological trait groupings when exploring large-scale variation in seafloor multifunctionality
Understanding large-scale spatial variation in ecosystem properties and associated functionality is key for successful conservation of ecosystems. This study provides a template for how to estimate differences in ecosystem functionality over large spatial scales by using groupings of biological traits. We focus on trait groupings that describe three important benthic ecosystem properties, namely bioturbation, community stability and juvenile dispersal. Recognizing that groups of traits interact and are constrained within an organism, we statistically define important functional trait subgroups that describe each ecosystem property. The sub-groups are scored according to their weighted ecological impact to gain an overall estimation of the cumulative expression of each ecosystem property at individual sites. Furthermore, by assigning each property a value relative to its observed maximum, and by summing up the individual property values, we offer an estimate of benthic ecosystem multifunctionality. Based on a spatially extensive benthic data set, we were able to identify coastal areas with high and low potential for the considered benthic ecosystem properties and the measure of ecosystem multifunctionality. Importantly, we show that a large part of the spatial variation in functional trait sub-groups and in benthic ecosystem multifunctionality was explained by environmental change. Our results indicate that through this simplification it is possible to estimate the functionality of the seafloor. Such information is vital in marine spatial planning efforts striving to balance the utilization with the preservation of natural resources.
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: 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.
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: 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.
Data from: A new integrative framework for large-scale assessments of biodiversity and community dynamics, using littoral gastropods and crabs of British Columbia, Canada
Improving our understanding of species responses to environmental changes is an important contribution ecologists can make to facilitate effective management decisions. Novel synthetic approaches to assessing biodiversity and ecosystem integrity are needed, ideally including all species living in a community and the dynamics defining their ecological relationships. Here we present and apply an integrative approach that links high-throughput, multi-character taxonomy with community ecology. The overall purpose is to enable the coupling of biodiversity assessments with investigations into the nature of ecological interactions in a community-level data set. We collected 1,195 gastropods and crabs in British Columbia. First, the General mixed Yule-coalescent (GMYC) and the Poisson Tree Processes (PTP) methods for proposing primary species-hypotheses based on cox1 sequences were evaluated against an integrative taxonomic framework. We then used data on the geographic distribution of delineated species to test species co-occurrence patterns for non-randomness using community-wide and pairwise approaches. Results showed that PTP generally outperformed GMYC and thus constitutes a more effective option for producing species-hypotheses in community-level datasets. Non-random species co-occurrence patterns indicative of ecological relationships or habitat preferences were observed for grazer gastropods, whereas assemblages of opportunistic omnivorous gastropods and crabs appeared influenced by random processes. Species-pair associations were consistent with current ecological knowledge, thus suggesting that applying community assembly within a large taxonomical framework constitutes a valuable tool for assessing ecological interactions. Combining phylogenetic, morphological and co-occurrence data enabled an integrated view of communities, providing both a conceptual and pragmatic framework for biodiversity assessments and investigations into community dynamics.
Data from: Bat communities respond positively to large-scale thinning of forest regrowth
Over half of the world's forests are secondary regrowth and support considerable biodiversity. Thinning of these forests is a widespread management practice that can affect forest species, including echolocating bats and their prey. We compared total activity of 11 bat taxa, foraging activity of six bat guilds and biomass of 11 insect orders across four forest thinning categories in managed remnant eucalypt forests in south-eastern Australia: unthinned regrowth, forest thinned recently (0–4 years) and in the medium term (5–10 years) and reference (mature open forest). Thinning had been carried out at large (˜350 ha) spatial scales. Total bat activity was 60% less and foraging activity was 80% less in unthinned regrowth, compared to reference sites, but activity levels were similar among thinned and reference sites. Insect biomass was greatest in unthinned sites, and while bat activity was related to prey biomass, this relationship was weak in unthinned sites. Together, this suggests that forest structure was more important than prey availability or time since thinning in influencing bat activity patterns. Synthesizing our findings with the broader literature on bats and thinning, we found support for a clutter threshold of 1100 stems ha−1, above which bat activity was markedly lower, across two continents (the USA and Australia) and four broad vegetation types (eucalypt, conifer, deciduous and mixed forests). While elsewhere bats with adaptive traits for open habitats generally respond positively to thinning, in our study, species with traits consistent with clutter tolerance (high call frequency and low wing aspect ratio) had lowest activity levels (up to 22 times) in unthinned regrowth compared to all other forest types. Synthesis and applications. Widespread dense regrowth forest can restrict movement and foraging of bats, even those adapted to clutter. We recommend thinning dense regrowth or plantations to below 1100 stems ha−1 when targeting bat foraging habitat, but effects of thinning on roost habitat and other forest biota require further investigation.
Data from: Restriction to large-scale gene flow versus regional panmixia among cold seep Escarpia spp. (Polychaeta, Siboglinidae)
The history of colonization and dispersal in fauna distributed among deep-sea chemosynthetic ecosystems remains enigmatic and poorly understood because of an inability to mark and track individuals. A combination of molecular, morphological and environmental data improves understanding of spatial and temporal scales at which panmixia, disruption of gene flow or even speciation may occur. Vestimentiferan tubeworms of the genus Escarpia are important components of deep -sea cold seep ecosystems, as they provide long-term habitat for many other taxa. Three species of Escarpia, Escarpia spicata [Gulf of California (GoC)], Escarpia laminata [Gulf of Mexico (GoM)] and Escarpia southwardae (West African Cold Seeps), have been described based on morphology, but are not discriminated through the use of mitochondrial markers (cytochrome oxidase subunit 1; large ribosomal subunit rDNA, 16S; cytochrome b). Here, we also sequenced the exon-primed intron-crossing Haemoglobin subunit B2 intron and genotyped 28 microsatellites to (i) determine the level of genetic differentiation, if any, among the three geographically separated entities and (ii) identify possible population structure at the regional scale within the GoM and West Africa. Results at the global scale support the occurrence of three genetically distinct groups. At the regional scale among eight sampling sites of E. laminata (n = 129) and among three sampling sites of E. southwardae (n = 80), no population structure was detected. These findings suggest that despite the patchiness and isolation of seep habitats, connectivity is high on regional scales.
Data from: Automated DNA-based plant identification for large-scale biodiversity assessment
Rapid degradation of tropical forests urges to improve our efficiency in large-scale biodiversity assessment. DNA-barcoding can assist greatly in this task, but commonly used phenetic approaches for DNA-based identifications rely on the existence of comprehensive reference databases, which are infeasible for hyperdiverse tropical ecosystems. Alternatively, phylogenetic methods are more robust to sparse taxon sampling but time-consuming, while multiple alignment of species-diagnostic, typically length-variable markers can be problematic across divergent taxa. We advocate the combination of phylogenetic and phenetic methods for taxonomic assignment of DNA-barcode sequences against incomplete reference databases such as GenBank, and we developed a pipeline to implement this approach on large-scale plant diversity projects. The pipeline workflow includes several steps: database construction and curation, query sequence clustering, sequence retrieval, distance calculation, multiple alignment and phylogenetic reconstruction. We describe the strategies used to establish these steps and the optimisation of parameters to fit the selected psbA-trnH marker. We tested the pipeline using infertile plant samples and herbivore diet sequences from the highly threatened Nicaraguan seasonally dry forest and exploiting a valuable purpose-built resource: a partial local reference database of plant psbA-trnH. The selected methodology proved efficient and reliable for high-throughput taxonomic assignment, and our results corroborate the advantage of applying 'strict' tree-based criteria to avoid false positives. The pipeline tools are distributed as the scripts suite 'BAGpipe' (pipeline for Biodiversity Assessment using GenBank data), which can be readily adjusted to the purposes of other projects and applied to sequence-based identification for any marker or taxon.
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: Large-scale phylogeny of chameleons suggests African origins and Eocene diversification
Oceanic dispersal has emerged as an important factor contributing to biogeographic patterns in numerous taxa. Chameleons are a clear example of this, as they are primarily found in Africa and Madagascar, but the age of the family is post-Gondwanan break-up. A Malagasy origin for the family has been suggested, yet this hypothesis has not been tested using modern biogeographic methods with a dated phylogeny. To examine competing hypotheses of African and Malagasy origins, we generated a dated phylogeny using between six and 13 genetic markers, for up to 174 taxa representing greater than 90 per cent of all named species. Using three different ancestral-state reconstruction methods (Bayesian and likelihood approaches), we show that the family most probably originated in Africa, with two separate oceanic dispersals to Madagascar during the Palaeocene and the Oligocene, when prevailing oceanic currents would have favoured eastward dispersal. Diversification of genus-level clades took place in the Eocene, and species-level diversification occurred primarily in the Oligocene. Plio-Pleistocene speciation is rare, resulting in a phylogeny dominated by palaeo-endemic species. We suggest that contraction and fragmentation of the Pan-African forest coupled to an increase in open habitats (savannah, grassland, heathland), since the Oligocene played a key role in diversification of this group through vicariance.
Data from: Asynchronous changes in abundance over large scales are explained by demographic variation rather than environmental stochasticity in an invasive flagellate
Environmental stochasticity is important in explaining the persistence and establishment of invasive species, but the simultaneous effects of environmental and demographic factors are difficult to separate. Understanding how demography and environmental factors affect invasive species abundance over large temporal and spatial scales is essential to anticipate populations at risk of becoming established and setting appropriate management measures. Using a hierarchical mixed modeling approach we analyzed the spatial and interannual dynamics of the invasive raphidophyte Gonyostomum semen, a noxious flagellate which is spreading in northern Europe, in response to demographic and environmental variation. We used data from 76 lakes distributed across two biogeographical regions in Sweden (Central Plains in the south and Fennoscandian region in the north) and sampled during 14 years. We found a strong asynchrony in the density dynamics of G. semen populations between the two regions. G. semen showed positive trends (i.e. increasing frequency of high density peaks) in most southern lakes, forming established populations with recurrent blooms in successive years in some of them. In contrast, G. semen populations were smaller and more stochastic in the north. G. semen previous year's abundance, a proxy for cyst production and recruitment, had a strong control on the dynamics, likely contributing to the stability of high density populations in southern lakes. Conversely, the effects of climate and habitat were weaker and their influence varied across regions. Temperature was the limiting factor in the north whereas local habitat was more important in the south. Synthesis: A full understanding of the mechanisms driving abundance changes across large scales can only be gained if endogenous and environmental factors are analyzed together. For phytoplankton species, and specially, noxious microalgae, this implies that proxies for cyst production and recruitment, which are the inoculum for next year population, should be included in e.g. distribution, bloom formation and climate models, as these may modify establishment and population response to environmental variation. Asynchronous changes in abundance across regions also indicate that management plans should be developed for small regions, as inference at a large scale may obscure the mechanisms driving local population changes.
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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.