Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
9,882
datasets available to search
ShareScore release 0.9.0
Dataset results
9,882 results for “Scale”
Data from: Cross-scale dynamics in community and disease ecology: relative timescales shape the community ecology of pathogens
Communities of free-living organisms are shaped by processes operating within and among patches of habitat, while pathogen communities are shaped by analogous processes operating within and among hosts. Resource competition (R) theory can describe dynamics within patches or hosts, while metacommunity dynamics describe competition-colonization tradeoffs, extinction debts, and superinfection. However, models at this broader scale often assume instantaneous competitive exclusion in co-inhabited patches or coinfected hosts. Impacts of more gradual competitive exclusion on the abundance, distribution, and diversity of species are less clear. Here, we nest a general resource competition model within a metacommunity framework and manipulate the relative timescales for processes operating within and among patches/hosts. We focus on superinfection in pathogen communities. We compare cases where transmission depends on infection prevalence versus the abundance of pathogens within hosts. Surprisingly, slowing the relative pace of competitive exclusion within hosts can decrease infection prevalence of the inferior competitor and increase prevalence of the superior competitor, depending on transmission and virulence. Slower dynamics reduce the abundance of both pathogens within hosts and promote diversity at multiple scales: coinfections within individual hosts and co-occurrence in the host population. These results highlight surprising feedbacks that can emerge across scales and reinforce the rich cross-scale connections between community and disease ecology.
Data from: Which landscape size best predicts the influence of forest cover on restoration success? – A global meta-analysis on the scale of effect
Landscape context is a strong predictor of species persistence, abundance and distribution, yet its influence on the success of ecological restoration remains unclear. Thus, a primary question arises: which landscape size best predicts the effects of forest cover on restoration success? To answer this question, we conducted a global meta-analysis for biodiversity (mammals, birds, invertebrates, herpetofauna and plants) and measures of vegetation structure (cover, density, height, biomass and litter). Response ratios were calculated for comparisons between reference (e.g. old-growth forest) and disturbed sites (degraded or restored). Using an information-theoretic approach, mean response ratio (restoration success) and response ratio variance (restoration predictability) within each study landscape were regressed against the percentage of overall (summed forest cover) and contiguous (summed pixels of ≥60% forest cover) forest within eight different buffer sizes of radius 5–200 km (at 1-km resolution). We included 247 studies encompassing 196 study landscapes and 4360 quantitative comparisons. The best buffer (landscape) size varied for the following: (i) overall and contiguous forest cover, (ii) biodiversity and vegetation structure and (iii) mean response ratio and response ratio variance. Only plant biodiversity was influenced by overall forest cover (buffer size of 5, 10 and 200 km radii), while plants (10 and 200 km radii), mammals (5, 10 and 50–200 km radii), invertebrates (5 and 10 km radii), cover (5 km radii), height (5 km radii) and litter (100 km radii) were influenced by contiguous forest cover. Overall, mean response ratio and response ratio variance were positively and negatively nonlinearly related with both overall and contiguous forest cover, respectively. We reveal for the first time a clear pattern of increasing restoration success and decreasing uncertainty as contiguous forest cover increases. We also indicate preliminary recommended buffer sizes for investigating landscape restoration effects on biodiversity and vegetation structure. However, the coarse grain and variability in the data mean the optimal landscape size may not have been detected; thus, further research is needed. Synthesis and applications. When setting targets for ecological restoration, policymakers and restoration practitioners should account for the following: (i) the landscape context, particularly the amount of contiguous habitat up to 10 km around a disturbed site, and (ii) the uncertainty in restoration success, as it increases when contiguous forest cover falls below about 50%.
Data from: Reproductive isolation between phylogeographic lineages scales with divergence
Phylogeographic studies frequently reveal multiple morphologically cryptic lineages within species. What is not yet clear is whether such lineages represent nascent species or evolutionary ephemera. To address this question, we compare five contact zones, each of which occurs between ecomorphologically cryptic lineages of skinks from the rainforests of the Australian Wet Tropics. Although the contacts probably formed concurrently in response to Holocene expansion from glacial refugia, we estimate that the divergence times (τ) of the lineage pairs range from 3.1 to 11.5 Ma. Multi-locus analyses of the contact zones yielded estimates of reproductive isolation that are tightly correlated with divergence time and, for lineages with older divergence times (τ > 5 Myr), substantial. These results show that phylogeographic splits of increasing depth represent stages along the speciation continuum, even in the absence of overt change in ecologically relevant morphology.
Data from: Intraspecific trait variation across multiple scales: the leaf economics spectrum in coffee
Understanding species differences in plant functional traits has been critical in developing a mechanistic understanding of terrestrial ecological processes. Greater attention is now being placed on understanding the extent, causes and consequences of intraspecific trait variation (ITV). ITV is especially important in governing ecological processes in cropping systems, where only a small number of species or genotypes exist in high abundances. However, it remains unclear if key principles of trait-based ecology – namely the leaf economics spectrum (LES) – also describe intraspecific variation in crop functional biology. There also remains a need to understand whether ITV within crops is random, or structured across environmental, management-related or biological levels of organization in agroecosystems. We employed a nested design field survey to evaluate ITV in leaf traits in coffee (Coffea arabica), one of the world's most widespread tropical crops. We evaluated ITV in eight physiological, morphological and chemical leaf traits, across five nested categorical levels (sites, management systems, spatial location, plant identity, branch identity). We compared patterns of LES trait covariation in coffee, to interspecific patterns observed across over 700 wild plant species. Patterns of bivariate and multivariate ITV in coffee were broadly consistent with, but considerably weaker than, interspecific patterns associated with the LES, indicating that crops may systematically diverge from global patterns of trait trade-offs observed in wild plants. Physiological traits varied most widely (coefficient of variation (cv) 42–107%), followed by morphological traits (cv = 15–38%) and chemical traits (cv = 3–11%). Physiological ITV was best explained by the site in which a coffee plant was growing (17–55% explained), while ITV for chemical traits was best explained by management treatments within sites (25–36%); morphological ITV was higher even at the individual tree level or branch level and remained largely unexplained. Our results support the hypothesis that artificial selection and high-resource agricultural environments lead crops to systematically deviate from patterns of leaf trait covariation observed across wild plants species. Coupled with an understanding of how different traits vary systematically across multiple levels of biological organization, these findings help integrate ITV into future analyses of agroecosystem structure and function.
Data from: Fine-scale population dynamics in a marine fish species inferred from dynamic state-space models
Identifying the spatial scale of population structuring is critical for the conservation of natural populations and for drawing accurate ecological inferences. However, population studies often use spatially aggregated data to draw inferences about population trends and drivers, potentially masking ecologically relevant population sub-structure and dynamics. The goals of this study were to investigate how population dynamics models with and without spatial structure affect inferences on population trends and the identification of intrinsic drivers of population dynamics (e.g. density dependence). Specifically, we developed dynamic, age-structured, state-space models to test different hypotheses regarding the spatial structure of a population complex of coastal Atlantic cod (Gadus morhua). Data were from a 93-year survey of juvenile (age 0 and 1) cod sampled along >200 km of the Norwegian Skagerrak coast. We compared two models: one which assumes all sampled cod belong to one larger population, and a second which assumes that each fjord contains a unique population with locally determined dynamics. Using the best supported model, we then reconstructed the historical spatial and temporal dynamics of Skagerrak coastal cod. Cross-validation showed that the spatially structured model with local dynamics had better predictive ability. Furthermore, posterior predictive checks showed that a model which assumes one homogeneous population failed to capture the spatial correlation pattern present in the survey data. The spatially structured model indicated that population trends differed markedly among fjords, as did estimates of population parameters including density-dependent survival. Recent biomass was estimated to be at a near-record low all along the coast, but the finer scale model indicated that the decline occurred at different times in different regions. Warm temperatures were associated with poor recruitment, but local changes in habitat and fishing pressure may have played a role in driving local dynamics. More generally, we demonstrated how state-space models can be used to test evidence for population spatial structure based on survey time-series data. Our study shows the importance of considering spatially structured dynamics, as the inferences from such an approach can lead to a different ecological understanding of the drivers of population declines, and fundamentally different management actions to restore populations.
Data from: Fine scale waterbody data improve prediction of waterbird occurrence despite coarse species data
While modelling habitat suitability and species distribution, ecologists must deal with issues related to the spatial resolution of species occurrence and environmental data. Indeed, given that the spatial resolution of species and environmental datasets range from centimeters to hundreds of kilometers, it underlines the importance of choosing the optimal combination of resolutions to achieve the highest possible modelling prediction accuracy. We evaluated how the spatial resolution of land cover/waterbody datasets (meters to 1 km) affect waterbird habitat suitability models based on atlas data (grid cell of 12×11 km). We hypothesized that the area, perimeter and number of waterbodies computed from high resolution datasets would explain distributions of waterbirds better because coarse resolution datasets omit small waterbodies affecting species occurrence. Specifically, we investigated which spatial resolution of waterbodies better explain the distribution of seven waterbirds nesting on ponds/lakes with areas ranging from 0.1 ha to hundreds of hectares. Our results show that the area and perimeter of waterbodies derived from high resolution datasets (raster data with 30 m resolution, vector data corresponding with map scale 1:10,000) explain the distribution of the waterbirds better than those calculated using less accurate datasets despite the coarse grain of the species data. Taking into account the spatial extent (global vs regional) of the datasets, we found the Global Inland Waterbody Dataset to be the most suitable for modelling distribution of waterbirds. In general, we recommend using land cover data of a resolution sufficient to capture the smallest patches of the habitat suitable for a given species' presence for both fine and coarse grain habitat suitability and distribution modelling.
Data from: Nitrogen deposition and multi-dimensional plant diversity at the landscape scale
Estimating effects of nitrogen (N) deposition is essential for understanding human impacts on biodiversity. However, studies relating atmospheric N deposition to plant diversity are usually restricted to small plots of high conservation value. Here, we used data on 381 randomly selected 1 km2 plots covering most habitat types of Central Europe and an elevational range of 2900 m. We found that high atmospheric N deposition was associated with low values of six measures of plant diversity. The weakest negative relation to N deposition was found in the traditionally measured total species richness. The strongest relation to N deposition was in phylogenetic diversity, with an estimated loss of 19% due to atmospheric N deposition as compared with a homogeneously distributed historic N deposition without human influence, or of 11% as compared with a spatially varying N deposition for the year 1880, during industrialization in Europe. Because phylogenetic plant diversity is often related to ecosystem functioning, we suggest that atmospheric N deposition threatens functioning of ecosystems at the landscape scale.
Data from: Environmental filtering improves ecological niche models across multiple scales
1. A clear challenge for ecological niche modeling is determining how to best mitigate the effects of sampling bias from commonly collected biodiversity data. Recent approaches have focused on filtering occurrences in overrepresented regions based on geographic or environmental proximity. 2. We tested the efficacy of filtering in geographic and environmental space using occurrence data from four species. Our evaluation strategies examined 14 distance measures in geographic and environmental spaces and eight combinations of environmental variables and their ordinations. This resulted in 78 datasets for each species, which we evaluated using area under the curve (AUC), the difference between training and testing AUC, omission rate, the true skill statistic, and Schoener's D to examine the effects of different filtering schemes. 3. The degree of change produced by filtering on predicted suitability and evaluation statistics increased with increasing range size. Environmental filtering resulted in higher model fit at larger extents and retained more occurrences than geographic filtering. 4. Our results indicate that models should be evaluated using multiple evaluation statistics at multiple thresholds. The use of bin sizes when filtering in environmental space allows for simple comparison between species and filter types and makes for an easily reportable and repeatable distance metric. We specifically recommend that ecological niche models using natural history collection data filter in environmental space with variables derived from permutation importance or the first few axes of a principal components ordination.
Data from: Effects of fire regime on the population genetics of natural pine stands, in Genetic structure of forest trees in biodiversity hotspots at different spatial scales (Ph.D. thesis).
The recurrence of wildfires is predicted to increase worldwide due to climate change, resulting in severe impacts on biodiversity and ecosystem functioning. We used simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) markers to examine the effects of fire regime on genetic diversity, demographic history and fine-scale spatial genetic structure (SGS) of Pinus pinaster and P. halepensis, two conifers with similar adaptations to fire in the eastern Iberian Peninsula. Stands growing under high (HiFi) or low (LoFi) frequency of crown fires had similar levels of genetic diversity and similar demographic history, with bottlenecks detected in all stands in both species. HiFi populations were not genetically depleted, suggesting that adaptations such as a diverse canopy seed bank due to serotinous cones, an early age of first flowering and high gene flow buffer against possible reductions of genetic diversity. Significantly stronger SGS at SNPs in HiFi than LoFi stands of P. halepensis suggested fire-related altered dispersal possibly combined with microenvironmental selection in this fire-sensitive "seeder" species. In contrast, SGS at SNP markers was unrelated to fire regime in P. pinaster. This could be a consequence of more pronounced fire-resistance in this species enabling some adults to survive fire, hence causing a lower dependence on post-fire regeneration. Our results highlight that the impact of fire differs in species with similar life-history traits. Therefore, species-specific studies are needed to understand the role of wildfires for the evolution of future forests
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.
Data from: The impact of spatial scale and habitat configuration on patterns of trait variation and local adaptation in a wild plant parasite
Theory indicates that spatial scale and habitat configuration are fundamental for coevolutionary dynamics and how diversity is maintained in host–pathogen interactions. Yet, we lack empirical data to translate the theory to natural host–parasite systems. In this study, we conduct a multiscale cross-inoculation study using the specialist wild plant pathogen Podosphaera plantaginis on its host plant Plantago lanceolata. We apply the same sampling scheme to a region with highly fragmented (Åland) and continuous (Saaremaa) host populations. Although theory predicts higher parasite virulence in continuous regions, we did not detect differences in traits conferring virulence among the regions. Patterns of adaptation were highly scale dependent. We detected parasite maladaptation among regions, and among populations separated by intermediate distances (6.0–40.0 km) within the fragmented region. In contrast, parasite performance did not vary significantly according to host origin in the continuous landscape. For both regions, differentiation among populations was much larger for genetic variation than for phenotypic variation, indicating balancing selection maintaining phenotypic variation within populations. Our findings illustrate the critical role of spatial scale and habitat configuration in driving host–parasite coevolution. The absence of more aggressive strains in the continuous landscape, in contrast to theoretical predictions, has major implications for long-term decision making in conservation, agriculture, and public health.
Data from: The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales
Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.
Data from: Species richness-productivity relationships of tropical terrestrial ferns at regional and local scales
1. The species richness-productivity relationship (SRPR), by which the species richness of habitats or ecosystems is related to the productivity of the ecosystem or the taxon, has been documented both on regional and local scales, but its generality, biological meaning, and underlying mechanisms remain debated. 2. We evaluated the SRPR and 3 mechanistic hypotheses using terrestrial ferns in 18 study plots along an elevational gradient (500-4000 m) in Ecuador. We measured annual increases in above-ground biomass of 6175 fern individuals from 91 species over 2 years, and estimated plot-level tree productivity from increases in above-ground woody biomass of 560 trees. Analyses were conducted by (a) comparing plots along the elevational gradient (regional scale) and (b) comparing plots within each elevational belt (local scale). 3. Fern diversity was related to the productivity of the fern assemblages, but not to above-ground productivity of the trees. At the regional scale, we found a positive relationship of fern species richness to fern productivity that appeared to be determined by an increase in the number of fern individuals and niche availability. In contrast, at the local scale this relationship was negative and likely driven by interspecific competition. 4. Synthesis: Plot diversity of ferns appears to be limited by the number of available niches and competition to occupy these niches. At the local scale, this is reflected in a negative SRPR probably driven by competition, whereas with increasing scale the positive influence of productivity emerges. This represents the first evidence that productivity and competition affect the diversity of tropical herb assemblages at the plot scale.
Data from: Comparison of coded-wire tagging with parentage-based tagging and genetic stock identification in a large-scale coho salmon fisheries application in British Columbia, Canada
Wild Pacific salmon, including Coho salmon Onchorynchus kisutch, have been supplemented with hatchery propagation for over 50 years in support of increased ocean harvest and conservation of threatened populations. In Canada, the Wild Salmon Policy for Pacific salmon was established with the goal of maintaining and restoring healthy and diverse Pacific salmon populations, making conservation of wild salmon and their habitats the highest priority for resource management decision-making. A new approach to the assessment and management of wild coho salmon, and the associated hatchery production and fishery management is needed. Implementation of parentage-based tagging (PBT) may overcome problems associated with coded-wire tag-based (CWT) assessment and management of coho salmon fisheries, providing at a minimum information equivalent to that derived from the CWT program. PBT and genetic stock identification (GSI) were used to identify coho salmon sampled in fisheries (8,006 individuals) and escapements (1,692 individuals) in British Columbia to specific conservation units (CU), populations, and broodyears. Individuals were genotyped at 304 single nucleotide polymorphisms (SNPs) via direct sequencing of amplicons. Very high accuracy of assignment to population (100%) via PBT for 543 jack (age 2) assigned to correct age and collection location and 265 coded-wire tag (CWT, age 3) coho salmon assigned to correct age and release location was observed, with a 40,774–individual, 267–population baseline available for assignment. Coho salmon from un-CWTed enhanced populations contributed 65% of the catch in southern recreational fisheries in 2017. Application of a PBT-GSI system of identification to individuals in 2017 fisheries and escapements provided high-resolution estimates of stock composition, catch, and exploitation rate by CU or population, providing an alternate and more effective method in the assessment and management of Canadian-origin coho salmon relative to CWTs, and an opportunity for a genetic-based system to replace the current CWT system for coho salmon assessment.
Data from: Continental-scale patterns of pathogen prevalence: a case study on the corncrake
Pathogen infections can represent a substantial threat to wild populations, especially those already limited in size. To determine how much variation in the pathogens observed among fragmented populations is caused by ecological factors, one needs to examine systems where host genetic diversity is consistent among the populations, thus controlling for any potentially confounding genetic effects. Here, we report geographic variation in haemosporidian infection among European populations of corncrake. This species now occurs in fragmented populations, but there is little genetic structure and equally high levels of genetic diversity among these populations. We observed a longitudinal gradient of prevalence from western to Eastern Europe negatively correlated with national agricultural yield, but positively correlated with corncrake census population sizes when only the most widespread lineage is considered. This likely reveals a possible impact of local agriculture intensity, which reduced host population densities in Western Europe and, potentially, insect vector abundance, thus reducing the transmission of pathogens. We conclude that in the corncrake system, where metapopulation dynamics resulted in variations in local census population sizes, but not in the genetic impoverishment of these populations, anthropogenic activity has led to a reduction in host populations and pathogen prevalence.
Data from: Fine-scale landscape genetics of the American badger (Taxidea taxus): disentangling landscape effects and sampling artifacts in a poorly understood species
Landscape genetics is a powerful tool for conservation because it identifies landscape features that are important for maintaining genetic connectivity between populations within heterogeneous landscapes. However, using landscape genetics in poorly understood species presents a number of challenges, namely, limited life history information for the focal population and spatially biased sampling. Both obstacles can reduce power in statistics, particularly in individual-based studies. In this study, we genotyped 233 American badgers in Wisconsin at 12 microsatellite loci to identify alternative statistical approaches that can be applied to poorly understood species in an individual-based framework. Badgers are protected in Wisconsin owing to an overall lack in life history information, so our study utilized partial redundancy analysis (RDA) and spatially lagged regressions to quantify how three landscape factors (Wisconsin River, Ecoregions and land cover) impacted gene flow. We also performed simulations to quantify errors created by spatially biased sampling. Statistical analyses first found that geographic distance was an important influence on gene flow, mainly driven by fine-scale positive spatial autocorrelations. After controlling for geographic distance, both RDA and regressions found that Wisconsin River and Agriculture were correlated with genetic differentiation. However, only Agriculture had an acceptable type I error rate (3–5%) to be considered biologically relevant. Collectively, this study highlights the benefits of combining robust statistics and error assessment via simulations and provides a method for hypothesis testing in individual-based landscape genetics.
Data from: Nest fidelity is driven by multi-scale information in a long-lived seabird
Although the reproductive success of most organisms depends on factors acting at several spatial scales, little is known about how organisms are able to synthesize multi-scale information to optimize reproduction. Using longitudinal data from a long-lived seabird, Monteiro's storm-petrel, we show that average breeding success is strongly related to oceanic conditions at the population level, and we postulate that (i) individuals use proximal information (their own reproduction outcome in year t) to assess the qualities of their mate and nest and to decide to retain them or not in year t + 1; (ii) the intensity of these responses depends on the quality of the oceanic environment in year t, which affects the predictability of reproduction outcome in year t + 1. Our results confirm that mate and nest fidelities are higher following successful reproduction and that the relationship between the success of a given pair and subsequent nest fidelity is stronger in years with unfavourable oceanic conditions, suggesting that individuals rely on distant information to modulate their use of proximal information and adjust their breeding strategy.
Data from: Contrasted invasion processes imprint the genetic structure of an invasive scale insect across southern Europe
Deciphering the colonization processes by which introduced pests invade new areas is essential to limit the risk of further expansion and/or multiple introductions. We here studied the invasion history of the maritime pine bast scale Matsucoccus feytaudi. This host-specific insect does not cause any damage in its native area, but it devastated maritime pine forests of South-Eastern France where it was detected in the 1960s, and since then reached Italy and Corsica. We used population genetic approaches to infer the populations' recent evolutionary history from microsatellite markers and Approximate Bayesian Computation. Consistent with previous mitochondrial data, we showed that the native range is geographically strongly structured, which is probably due to the patchy distribution of the obligate host and the limited dispersal capacity of the scale. Our results show that the invasion history can be described in three successive steps involving different colonization and dispersal processes. During the mid-XXth century, massive introductions occurred from the Landes planted forest to South-Eastern France, probably due to transportation of infested wood material after World War II. Stepping-stone expansion, consistent with natural dispersal, then allowed M. feytaudi to reach the maritime pine forests of Liguria and Tuscany in Italy. The island of Corsica was accidentally colonized in the 1990s, and the most plausible scenario involves the introduction of a limited number of migrants from the forests of South-Eastern France and Liguria, which is consistent with an aerial dispersal due to the dominant winds that blow in spring in this region.
Data from: Predictable food supplies induce plastic shifts in avian scaled body mass
Urbanization constitutes one of the most profound forms of land-use change and strongly affects global biodiversity and ecosystem functioning. Expansion of urban areas typically leads to species loss but may also induce more subtle changes in species dynamics through selection or plasticity. Using a dual correlative (field) and experimental (aviary) approach, we here show that free-ranging urban house sparrows in southern France were smaller and lighter than their rural counterparts after allometric scaling, whereas 2 independent indices of nutritional (feather growth rates) and developmental (feather asymmetry) stress did not vary with urbanization. When subjecting these individuals to urban or rural diets in a highly predictable, controlled setting, rural but not urban sparrows decreased their body mass, independent of diet type, to the extent that initial scaled mass differences between urban and rural birds disappeared by the end of the captive period. By integrating field- and aviary measurements of body size and mass with indices of nutritional and developmental stress, we conclude that the lower scaled body masses of urban birds likely reflect a plastic response to predictable food supplies, possibly mediated through predation. Urban environments therefore do not necessarily constitute nutritionally stressful environments for species that typically cohabit with humans, such as house sparrows.
Data from: Repeatable, continuous and real-time estimates of coupled nitrogenase activity and carbon exchange at the whole-plant scale
1. Symbiotic nitrogen fixation (SNF) by higher plants and their bacterial symbionts is a globally important input of nitrogen. Our understanding of the mechanisms that control SNF and the timescales over which they operate has been constrained by limitations of the existing methods for measuring SNF. One method, Acetylene Reduction Assays by Cavity-ring down laser Absorption Spectroscopy (ARACAS), seems promising, as it is highly sensitive and gives rapid, continuous, repeatable and real-time measurements of nitrogenase activity. ARACAS has been used to study nitrogen fixation in lichens, mosses and asymbiotic bacteria, but adapting it to higher plants poses challenges because acetylene and ethylene can influence plant function. 2. Here we report modifications to ARACAS that allow it to be used on higher plants in an environmentally-controlled incubation chamber. The modifications include lower concentrations of acetylene (2%) and ethylene and concurrent measurements of whole chamber CO2 exchange, H2O exchange and nitrogenase activity, linking nitrogenase activity to whole-plant rates of photosynthesis and respiration. 3. After propagating the error terms from all sources, we establish the following parameters of the method: (A) The detection limit of our method was 2-3 ppbv C2H4 hr-1, although it rose substantially when we used tank-derived acetylene, which has much higher ethylene contamination; (B) Repeated measures at a frequency of 3 days or longer did not diminish nitrogenase activity or photosynthesis, although daily measurements diminished nitrogenase activity; (C) This method can detect changes at timescales as short as seconds; (D) Continuous measurement of nitrogenase activity is maintained above 90% of the maximum rate for 7.0 ± 1.3 (mean ± SD) hours. 4. This method has the potential to improve our understanding of the controls over SNF and therefore how SNF and global nitrogen and carbon cycling are likely to be affected by global change.
ScienceDex guides
Understand access before you commit
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.