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277 results for “regional scale”
Weak population genetic structure in Eurasian spruce bark beetle over large regional scales in Sweden
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Tree diversity across multiple scales and environmental heterogeneity promote ecosystem multifunctionality in a large temperate forest region
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Global factors constrain body size trends across the Great Ordovician Biodiversification Event at a regional scale: a case study from the Arbuckle Mountains of Oklahoma
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Modelling connectivity at a regional scale during seasonal movements of the greater horseshoe bat
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Regional and fine-scale local adaptation in salinity tolerance in Daphnia inhabiting contrasting clusters of inland saline waters
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Data from: Repeatability of adaptive radiation depends on spatial scale: regional versus global replicates of stickleback in lake versus stream habitats
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Data from: Lineage diversity within a widespread endemic Australian skink to better inform conservation in response to regional-scale disturbance
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A model for regional-scale oak savanna management: the roles of fire, canopy, and soils for understory plant diversity
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Large-scale exploration of nitrogen utilization efficiency in Asia region for rice crop: variation patterns and determinants
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Data used in "Evaluation of topography and vegetation coverage impacts on watershed-scale active layer freeze-thaw processes with a simple algorithm in permafrost region on the Qinghai-Tibet Plateau"
<p>This is the data used in the manuscript "Evaluation of topography and vegetation coverage impacts on watershed-scale active layer freeze-thaw processes with a simple algorithm in permafrost region on the Qinghai-Tibet Plateau" (JGR earth surface 2020JF005564 ).</p>
Soil organic carbon distribution for 0-3 m soils at 1 km2 scale of the frozen ground in the Third Pole Regions
<p>Soil organic carbon (SOC) is very important in the vulnerable ecological environment of the Third Pole; however, data regarding the spatial distribution of SOC are still scarce and uncertain. Based on multiple environmental variables and soil profile data from 458 pits (depth of 0–1 m) and 114 cores (depth of 0–3 m), this study uses a machine-learning approach to evaluate the SOC storage and spatial distribution at different soil depths (0–30 cm, 0–50 cm, 0–100 cm, 0–200 cm, and 0–300 cm) in the frozen ground area of the Third Pole region. Our results provide information on the storage, patterns, and environmental controls of SOCSs at a 1 km<sup>2</sup> scale for areas of frozen ground in the Third Pole region, thus providing a scientific basis for future studies pertaining to Earth system models.</p> <p>Soil organic carbon data is stored in grids format, and the file name is "TP-SOC-d.tif", where d represents soil depth, for example, "TP-SOC-30.tif" represents the spatial distribution of soil organic carbon stocks in the Third Pole regions of the upper 30 cm depth interval.</p> <p> </p>
FIGURES 10–12. Dorsal scales. 10–11 in Taxonomic revision of the genus Rhopalapion Schilsky, 1906 (Coleoptera Apionidae) with description of Rhopalapion celatum n. sp. from the Turanian Region
FIGURES 10–12. Dorsal scales. 10–11: Rhopalapion longirostre, 10: ♁, from Turkey: Istanbul; 11: ♁, from Afghanistan: Goudgé Konti—12: Rhopalapion celatum n. sp., ♁ paratype, from Iran: vic. tomb of Cyrus.
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: Evolutionary dynamics of quantitative variation in an adaptive trait at the regional scale: the case of zinc hyperaccumulation in Arabidopsis halleri
Metal hyperaccumulation in plants is an ecological trait whose biological significance remains debated, in particular because the selective pressures that govern its evolutionary dynamics are complex. One of the possible causes of quantitative variation in hyperaccumulation may be local adaptation to metalliferous soils. Here we explored the population genetic structure of Arabidopsis halleri at fourteen metalliferous and non-metalliferous sampling sites in Southern Poland. The results were integrated with a quantitative assessment of variation in zinc hyperaccumulation to trace local adaptation. We identified a clear hierarchical structure with two distinct genetic groups at the upper level of clustering. Interestingly, these groups corresponded to different geographic sub-regions, rather than to ecological types (i.e. metallicolous vs non-metallicolous). Also, approximate Bayesian computation analyses suggested that the current distribution of A. halleri in Southern Poland could be relictual as a result of habitat fragmentation caused by climatic shifts during the Holocene, rather than due to recent colonization of industrially polluted sites. In addition, we find evidence that some non-metallicolous lowland populations may have actually derived from metallicolous populations. Meanwhile, the distribution of quantitative variation in zinc hyperaccumulation did separate metallicolous and non-metallicolous accessions, indicating more recent adaptive evolution and diversifying selection between metalliferous and non-metalliferous habitats. This suggests that zinc hyperaccumulation evolves both ways – towards higher levels at non-metalliferous sites and lower levels at metalliferous sites. Our results open a new perspective on possible evolutionary relationships between A. halleri edaphic types that may inspire future genetic studies of quantitative variation in metal hyperaccumulation.
Data from: Phenotype-environment mismatch in metapopulations - implications for the maintenance of maladaptation at the regional scale
Maladaptation is widespread in natural populations. However, maladaptation has most often been associated with absolute population decline in local habitats rather than on a spectrum of relative fitness variation that can assist natural populations in their persistence at larger regional scales. We report results from a field experiment that tested for relative maladaptation between pond habitats with spatial heterogeneity and (a)symmetric selection in pH. In the experiment, we quantified relative maladaptation in a copepod metapopulation as a mismatch between the mean population phenotype and the optimal trait value that would maximize mean population fitness under either stable or fluctuating pH environmental conditions. To complement the field experiment, we constructed a metapopulation model that addressed both relative (distance from the optimum) and absolute (negative population growth) maladaptation, with the aim of forecasting maladaptation to pH at the regional scale in relation to spatial structure (environmental heterogeneity and connectivity) and temporal environmental fluctuations. The results from our experiment indicated that maladaptation to pH at the regional scale depended on the asymmetry of the fitness surface at the local level. The results from our metapopulation model revealed how dispersal and (a)symmetric selection can operate on the fitness surface to maintain maladaptive phenotype-environment mismatch at local and regional scales in a metapopulation. Environmental stochasticity resulted in the maintenance of maladaptation that was robust to dispersal, but also revealed an interaction between the asymmetry in selection and environmental correlation. Our findings emphasize the importance of maladaptation for planning conservation strategies that can support adaptive potential in fragmented and changing landscapes.
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: Variation in the ecstatic display call of the Gentoo Penguin (Pygoscelis papua) across regional geographic scales
Geographic variation in bird vocalizations is common and has been associated with genetic differences and speciation, as well as with short-term changes in response to anthropogenic noise. Because vocalizations are used for individual recognition in many species, geographic variation in these traits may affect mate choice, pair bonding, and territory defense. Anecdotal evidence suggests the existence of geographic variation in vocalizations between isolated populations of Gentoo Penguins (Pygoscelis papua), but there have been no comprehensive studies of Gentoo Penguin vocalizations across a broad geographic range. We used acoustic recordings of ambient colony sound at 22 breeding colonies in the Antarctic Peninsula and South Shetland Islands, South Georgia, the Falkland Islands, and Argentina to address 2 main questions regarding Gentoo Penguin vocalizations: (1) How do ecstatic display calls vary both within and between individuals, colonies, and regions? (2) Can ecstatic display calls be used to distinguish subspecies? We found high levels of variation between individuals and between colonies, but little additional variation between regions or subspecies. We found no trends to suggest a latitudinal gradient in vocal characteristics, although we did find that some measures varied with relative distance between colonies. Although we found significant differences at the colony level, unknown calls could not easily be categorized to colony or region by machine learning. We conclude that the vocal soundscape of each colony is driven by variation between individuals within a colony and, developing independently from neighboring colonies, becomes differentiated from other colonies through a process of drift. Although individual calls could, in most cases, be identified to subspecies by machine learning, our analysis suggests that subspecies differences may be driven by variation among colonies and that subspecies identification may be unreliable using acoustics alone.
Data from: Multi-scale model of regional population decline in little brown bats due to white-nose syndrome
The introduced fungal pathogen Pseudogymnoascus destructans is causing decline of several species of bats in North America, with some even at risk of extinction or extirpation. The severity of the epidemic of white-nose syndrome caused by P. destructans has prompted investigation of the transmission and virulence of infection at multiple scales, but linking these scales is necessary to quantify the mechanisms of transmission and assess population-scale declines. We build a model connecting within-cave disease dynamics of little brown bats to regional scale dispersal, reproduction, and disease spread, including multiple plausible mechanisms of transmission. We parameterize the model using the approach of plausible parameter sets, by comparing stochastic simulation results to statistical probes from empirical data on within-cave prevalence and survival, as well as between-cave spread across a region. Our results are consistent with frequency-dependent transmission between bats, support an important role of environmental transmission, and show very little effect of dispersal among colonies on metapopulation survival. The model also offers a generalizable method to assess hypotheses about cave-to-cave transmission and to identify gaps in knowledge about key processes, and could be expanded to include additional mechanisms or bat species as research on this detrimental fungus progresses.
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.
Codes and data: Community size predicts temporal β-diversity at local but not regional scales
<p>UPDATED VERSION 2025-08-30 (models were updated)</p> <p>This zip file contains the codes demonstrating how I analyzed and selected publicly available and globally extensive data on fish composition and environmental variables to test the hypothesis that random fluctuations caused by demographic stochasticity in small populations might extend to communities and metacommunities, potentially affecting stability propagation across biological levels and spatial scales. The READ_ME file contains additional details about the steps I took to develop this analysis.</p> <p>This study was financed by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior-Brasil (CAPES) - Finance Code 001.</p>
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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.