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.
134
datasets available to search
ShareScore release 0.7.1
Dataset results
134 results for “range dynamics”
Supplementary material for "High turn-over rates at the upper range limit and elevational source-sink dynamics in a widespread songbird"
<p><strong>Abstract</strong></p> <p>The formation of an upper distributional range limit for species breeding along mountain slopes is often based on environmental gradients resulting in changing demographic rates towards high elevations. However, we still lack an empirical understanding of how the interplay of demographic parameters forms the upper range limit in highly mobile species. Here, we study apparent survival and within-study area dispersal over a 700 m elevational gradient in barn swallows (<em>Hirundo rustica</em>) by using 15 years of capture-mark-recapture data. Annual apparent survival of adult breeding birds decreased while breeding dispersal probability of adult females, but not males increased towards the upper range limit. Individuals at high elevations dispersed to farms situated at elevations lower than would be expected by random dispersal. These results suggest higher turn-over rates of breeding individuals at high elevations, an elevational increase in immigration and thus, within-population source-sink dynamics between low and high elevations. The formation of the upper range limit therefore is based on preference for low-elevation breeding sites and immigration to high elevations. Thus, shifts of the upper range limit are not only affected by changes in the quality of high-elevation habitats but also by factors affecting the number of immigrants produced at low elevations.</p>
Population dynamics across latitudes of black spruce at its northern limit in the Brooks Range, Alaska
Although black spruce is the dominant treeline species in the eastern boreal forest, its distribution stops several kilometers short of treeline in the Brooks Range in Alaska, and white spruce is the dominant treeline species. The explanation for this distribution is not known, but two hypotheses are plausible. First, black spruce may be less tolerant of climatic conditions near treeline than white spruce. Second, black spruce may be unable to regenerate successfully near treeline due to long intervals between fires. We are establishing permanently marked study plots along a transect from the Yukon River basin, where black spruce is the dominant species, to the foothills of the Brooks Range, where it reaches its distributional limit. We are reconstructing recruitment history of both black and white spruce at our study sites, and are reconstructing recent fire history from analysis of fire scars and stand age structures. These data are being used to parameterize matrix population models, with which we are describing patterns of population stability.
DEVILS: a tool for the visualization of large datasets with a high dynamic range
<p>This repository accompanying the article “DEVILS: a tool for the visualization of large datasets with a high dynamic range” contains the following:</p> <ul> <li>Extended Material of the article</li> <li>An example raw dataset corresponding to the images shown in Fig. 3</li> <li>A workflow description that demonstrates the use of the DEVILS workflow with BigStitcher.</li> <li>Two scripts (“CLAHE_Parameters_test.ijm” and a “DEVILS_Parallel_tests.groovy”) used for Figure S2, S3 and S4.</li> </ul>
The role of tropical rainfall in driving range dynamics for a long-distance migratory bird
<p>Predicting how the range dynamics of migratory species will respond to climate change requires a mechanistic understanding of the factors that operate across the annual cycle to control the distribution and abundance of a species. Here we use multiple lines of evidence to reveal that environmental conditions during the nonbreeding season influence range dynamics across the lifecycle of a migratory songbird, the American redstart (<em>Setophaga ruticilla</em>). Using long-term data from the nonbreeding grounds and breeding origin estimated from stable hydrogen isotopes in tail feathers, we found that the relationship between nonbreeding season survival and migration distance is mediated by precipitation, but only during dry years. A long-term drying trend throughout the Caribbean is associated with higher mortality for individuals from the northern portion of the species' breeding range, resulting in an approximate 500 km southward shift in breeding origins of this Jamaican population over the past 30 years. This shift in connectivity is mirrored by changes in the redstarts breeding distribution of abundance. These results demonstrate that the climatic effects on demographic processes originating during the tropical nonbreeding season is actively shaping range dynamics in a migratory bird.</p>
Raw data to "Quantum-critical and dynamical properties of the XXZ bilayer with long-range interactions"
<div> <p>This directory contains the data used to generate the numerical results in the work "Quantum-critical and dynamical properties of the XXZ bilayer with long-range interactions [1]".</p> <p>To get an overview of the organization of the directory and a description of the data we recommend the README.md file.</p> <p>[1]: P. Adelhardt, A. Duft and K. P. Schmidt, Quantum-critical and dynamical properties of the XXZ bilayer with long-range interactions, <a href="https://arxiv.org/abs/2408.13145">arXiv:2408.13145</a></p> <p> </p> </div>
Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations
<p>MD simulations used in the studies of the publication "<strong>Neural relational inference to learn long-range allosteric interactions in proteins from molecular dynamics simulations</strong>"</p>
Spatiotemporal influences of climate and humans on muskox range dynamics over multiple millennia
<p>Processes leading to range contractions and population declines of Arctic megafauna during the late Pleistocene and early-Holocene are uncertain, with intense debate on the roles of human hunting, climatic change, and their synergy. Obstacles to a resolution, have included an over reliance on correlative rather than process-explicit approaches for inferring drivers of distributional and demographic change. Using process-explicit macroecological models that integrate modern and fossil occurrence records, spatiotemporal reconstructions of past climatic change, speciesspecific population ecology and the growth and spread of anatomically modern humans, we disentangle the ecological mechanisms and threats that were integral in the decline and extinction of the muskox (Ovibos moschatus) in Eurasia, and in its expansion in North America. We show that accurately reconstructing inferences of past demographic changes for muskox over the last 21,000 years requires high dispersal abilities, large maximum densities, and a small Allee effect. Climatic change was the primary driver of muskox distribution shifts and demographic changes across its previously extensive (circumpolar) range, with populations responding negatively to rapid warming events. Regional analyses reveal that the range collapse and extinction of the muskox in Europe (~ 13 thousand years ago) was caused by humans operating in synergy with climatic warming. In Canada and Greenland, climatic change and human activities combined to drive recent population sizes. The impact of past climatic change on the range and extinction dynamics of muskox during the Pleistocene-Holocene transition signals a vulnerability of this species to future increased warming. By disentangling the ecological processes that shaped the distribution of the muskox through space and time, process-explicit models have important applications for the future conservation and management of this iconic species in a warming Arctic. </p>
Dataset: Global range dynamics of the Bearded Vulture (Gypaetus barbatus) from the Last Glacial Maxima to climate change scenarios
<p>This dataset consists of Bearded Vulture <em>Gypaetus barbatus </em>occurrence points which were used to develop a distribution model to study its suitable habitat of this species. Using these data, we modelled the current distribution of Bearded Vulture throughout its entire range and projected the Last Glacial Maxima (LGM), Mid-Holocene (MH) and future distribution under 2070s climate change scenarios. We compiled these data from the entire distribution range in Asia, Europe and Africa using different sources: freely accessible online resources including, eBird and GBIF repositories, published reports and grey literature and occurrence data collected by the authors in the field, mostly in Nepal.</p> <p> </p> <p> </p>
Research data supporting "Platinum Nanocatalyst Amplification: Redefining the Gold Standard for Lateral Flow Immunoassays with Ultra-Broad Dynamic Range"
<p>Research data supporting the publication: Loynachan C. N., et al., 2017, ACS Nano, DOI: http://dx.doi.org/10.1021/acsnano.7b06229.</p>
Phylogeography and paleoclimatic range dynamics explain variable outcomes to contact across a species' range
<p>Files required to run analyses related to the journal article:" Phylogeography and paleoclimatic range dynamics explain variable outcomes to contact across a species’ range."<br><br>Code which utilizes these data are found at: https://github.com/k-lamb/Campanula-range-history</p> <p>DOI code link: https://doi.org/10.5281/zenodo.12097775</p>
Figure 5 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 5. Last Interglacial, Last Glacial Maximum, Present (1960–1990), and the Future (2050 and 2070) predictions of the potential distribution of two cacti species (C. hildmannianus and P. machrisii) based on 10% thresholding approaches. The abbreviations are defined as follows: LGM-Last Glacial Maximum, LIG-Last Interglacial.
Figure 2 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 2. Occurrence points used for ecological niche modeling are shown in red. Squares equal approximately 2 decimal degrees and the background image on thmap shows the elevational structure of Brazil.
Figure 1 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 1. Approximate distribution of D. gouveai (green area) showed Caatinga and Cerrado domains and the localities sampled for the species (based on Moraes et al., 2009), descriptive statistics (n, number of individuals; H, the number of haplotype; H d, haplotype diversity; pi, nucleotide diversity) and median joining network of 48 individuals of D. gouveai. All statistics based on nucleotide sequences were adopted from Moraes et al. (2009). MIR: Pirapotanga; FOR: Morro do Forno; FUR: Furnas; CEU: Vale do Céu; CRI: Cristalina; FER: Fercal; PIR: Pirenópolis; SER: Serrinha; IBO: Ibotirama; BAX: Baxio.
Figure 4 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 4. Last Interglacial, Last Glacial Maximum, Present (1960–1990), and the Future (2050 and 2070) predictions of the potential distribution of D. gouveai based on two thresholding approaches. Arrows shows very limited potential distribution of D. gouveai in 2050 and 2070. The abbreviations are defined as follows: LGM-Last Glacial Maximum, LIG-Last Interglacial. Additionally, specific climate models include LGM-cc (Community Climate System Model), LGM-me (MPI-ESM-P, General Circulation Models), and LGM-mr (Model for Interdisciplinary Research on Climate, Earth System version 2 for Long-term simulations).
Figure 3 in The range dynamics of a cactophilic Drosophila species under climate change scenarios
Figure 3. Isolation-by-distance of populations of D. gouveai based on mtDNA. Linear regression lines were drawn for all comparisons among populations (full line), and for populations not included MIR (dotted line).
Fig. 2 in Temporal and demographic blood parasite dynamics in two free-ranging neotropical primates
Fig. 2. Individual infection status by parasite by year. Strength and thickness of lines are scaled to the number of individuals that took a given infection trajectory from one year to the next. Two diagonal lines span 2012‾2014 because those individuals were not sampled in 2013. The + symbols represent every infection or non-infection found across all individuals in the study.
Fig. 3 in Temporal and demographic blood parasite dynamics in two free-ranging neotropical primates
Fig. 3. Parasite species richness by species, age class and sex. Colors represent females (black) and males (gray).
Fig. 1 in Temporal and demographic blood parasite dynamics in two free-ranging neotropical primates
Fig. 1. Annual prevalence of single- and co-infections by species. Prevalence indicated for each parasite (dark gray), and each pairwise combination of parasites (light gray). Numbers near the top of each bar show the exact prevalence; black lines indicate 95% confidence intervals; dots indicate expected levels of co-infection (refer to Section 3.2). M-D is co-occurrence of M. mariae and Dipetalonema spp., D-T is Dipetalonema spp. and T. minasense, and M-T is M. mariae and T. minasense.
Figure 2 in Range dynamics of some nemoral species of Lepidoptera in the Russian Far East due to climate change
Figure 2. Some species of Lepidoptera from Amur region (Russia): A – Lobocla bifasciata, 1.07.2021; B, C – Chrysozephyrus brillantinus, 16.07.2021; D – Clanis undulosa, 30.06.2021; E – Acosmeryx naga, 3.07.2021; F – Ambulyx tobii, 1.07.2021; G – Rhagastis mongoliana, 3.07.2021; H, I, J – Siglophora sanguinolenta (H, I –25– 27.07.2021, J – live specimen, 9.09.2021). A, B, D–J – upperside, C – underside. A–H, J – males, I – female. Localities: A – 7 km N Tarmanchukan; B, C – 2 km S Voronezhskoe–1; D, F, H–J – 8 km SE Boitsovo; E – Mokhovaya Pad'; G – 4.5 km NW Rachi.
Figure 1 in Range dynamics of some nemoral species of Lepidoptera in the Russian Far East due to climate change
Figure 1. Distribution records of the some nemoral species of Lepidoptera in the southern part of the Amur region (Russia).
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.