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.
67
datasets available to search
ShareScore release 0.9.0
Dataset results
67 results for “stopover”
A map selection of wigeon stopover sites (core areas) based on wetland expert knowledge
<p>Stopover areas (core areas only) along the migration route of wigeons tracked with GPS transmitters were selected when they exhibited forests on more than 50% of their total surface or had less than 50% cover by water and/or wetland on the ESA’s global land cover map. We created a sample of 5,630 regions of interest (3,403 for training and 2,227 for validation), delineated with polygons assigned to land classes listed in the Table 1. We used archives of Google Earth, ESRI, and BING satellites for the photointerpretation of the land classes as described in Table 1. The classification was performed with a Sentinel-2 MultiSpectral Instrument, Level-2A image collection in Google Earth Engine (GEE) through the R-package Rgee to create a batch process applying the GEE Random forest classifier to each selected core home range. The cloudless (maximum 3%) images were selected within the period from 01/06/2021 to 30/09/2021. The optimal number of trees was estimated at 100 for an out of bag error of 14%. The overall accuracy on the validation sample was 82 %. </p>
Inclement weather forces stopovers and prevents migratory progress for obligate soaring migrants
<p>Data from: Mallon, JM, KL Bildstein, and WF Fagan. 2021. Inclement weather forces stopovers and prevents migratory progress for obligate soaring migrants. Movement Ecology</p> <p>These data include only migrations and are annotated with stopovers. See metadata for full information.</p> <p>Data modified from Bildstein KL and Barber D. 2021. Movebank Data Repository. https://doi.org/10.5441/001/1.f3qt46r2.</p> <p> </p>
Fig. 1 in Studen Kladenets Reservoir (CS Bulgaria), a stopover of the migratory Great White Pelicans (Pelecanus onocrotalus Linnaeus, 1758) through the Balkan Peninsula
Fig. 1. Flock of 30 Great White Pelicans, Studen Kladenets Reservoir, 26 August 2020. Photo: Z. Boev.
Data from: Effects of immune status on stopover departure decisions are subordinate to those of condition, cloud cover and tailwind in autumn-migrating common blackbirds (Turdus merula)
Open the record for dataset details and reuse information.
Euphagus carolinus (Rusty Blackbird) from two different breeding populations in northeastern North America exhibit chain migration yet use the same region for stopover
Open the record for dataset details and reuse information.
Data from: Stopover refueling, movement, and departure decisions in the White-throated Sparrow: the influence of intrinsic and extrinsic factors during spring migration
<p>1. Differential migration timing between sex or age classes are examples of how migratory movement strategies can differ among sub-groups within a population. However, in songbirds, evidence for intrinsic differences in en route migratory behavior is often mixed, suggesting that the local environmental context may play a role in accentuating or diminishing patterns. 2. We evaluated how multiple intrinsic and extrinsic variables influenced refueling rates, local movement behavior, and departure decisions in the White-throated Sparrow (Zonotrichia albicollis) during spring migration. This species exhibits a unique genetically-based plumage dimorphism, providing a unique class of individual in which to evaluate patterns and processes of differential migration, in addition to sex, age, and migration distance. 3. At a migratory stopover site, plasma metabolite analysis was used to quantify individual variation in stopover refueling rate. In after second year adults, automated and manual radio telemetry was used to quantify daily activity timing, daily movement distances, stopover duration, and departure time. Arrival timing to the stopover site was determined using capture data. Non-breeding and previous breeding/natal latitude were determined using analysis of hydrogen isotopes in claws and feathers. 4. Males arrived at the stopover site 11 days on average before females, but no difference in migration timing was observed between plumage morph or age classes. After second year adults with more southern previous breeding latitudes arrived at stopover earlier whereas second year birds making their first return migration arrived at stopover in an inverse relationship to non-breeding latitude. Stopover refueling rate did not differ between ages, sexes, or plumage morphs, and daily departure probability of adults was higher under warmer temperatures and favorable tailwinds. White-striped morphs moved greater distances during stopover, initiated daily activity earlier in the morning, and departed for migration earlier in the evening than tan-striped morphs. 5. Our results show that while individual phenotype can influence some aspects of local stopover-scale movement behavior, evidence for differential stopover behavior was weak. Differential migration timing is unlikely to result from intrinsic differences in en route refueling rate and departure decisions, especially because the latter is strongly influenced by meteorological conditions. </p>
Data from: Connecting the dots: Stopover strategies of an intercontinental migratory songbird in the context of the annual cycle
The phases of the annual cycle for migratory species are inextricably linked. Yet, less than five percent of ecological studies examine seasonal interactions. In this study, we utilized stable hydrogen isotopes to geographically link individual black-and-white warblers (Mniotilta varia) captured during spring migration with breeding destinations to understand a migrant's stopover strategy in the context of other phases of the annual cycle. We found that stopover strategy is not only a function of a bird's current energetic state, but also the distance remaining to breeding destination and a bird's time-schedule, which has previously been linked to habitat conditions experienced in the preceding phase of the annual cycle. Birds in close proximity to their breeding destination accumulate additional energy reserves prior to arrival on the breeding grounds, as reflected by higher migratory condition upon arrival, higher refueling rates measured via blood plasma metabolites, and longer stopover durations compared to birds migrating to breeding destinations farther from the stopover site. However, late birds near their breeding destination were more likely to depart on the day of arrival (i.e., transients), and among birds that stopped over at the site, the average duration of stopover was almost half the time of early conspecifics, suggesting late birds are trying to catch-up with the overall time-schedule of migration for optimal arrival time on the breeding grounds. In contrast, birds with long distances remaining to breeding destinations were more likely to depart on the day of arrival and primarily used stopover to rest before quickly resuming migration, adopting similar strategies regardless of a bird's time-schedule. Our study demonstrates that migrants adjust their en route strategies in relation to their time-schedule and distance remaining to their breeding destination, highlighting that strategies of migration should be examined in the context of other phases of the annual cycle.
Data from: Associations with landscape and local-scale wetland habitat conditions vary among migratory shorebird species during stopovers
<p>Wetlands provide many ecosystem services and functions, including critical stopover habitat for numberous migratory shorbirds species. We conducted shorebird surveys at >14,000 wetlands and associated observed abundance with wetland variables for 16 species. We found that the scale at which observed abundance was associated with wetland extent varied among speceis, and that for most species abundance was positively associated with higher wetland density, presence of shallow water, more usable area, and limited vegetation. There was considerable variation in the strength and sometimes direction of responses. Our study helps inform optimal habitat requirementes for shorebirds.</p>
Depleted lean body mass after crossing an ecological barrier differentially affects stopover duration and refueling rate among species of long-distance migratory birds
<p>During the long-distance migratory flights of birds, lean mass breakdown occurs in concert with fat catabolism and is expected to have repercussions on total stopover duration because birds require time to rebuild lean tissue before accumulating fat reserves. Despite this, little is known about the role of in-flight lean mass breakdown on stopover duration because direct measurements are restricted by the destructive nature of traditional body composition analysis and the technological limitations of tracking small birds over large expanses. We used non-lethal, non-invasive Quantitative Magnetic Resonance technology and plasma metabolite profiling to measure the body composition and physiological state of free-living birds captured at a migratory stopover site after flight across the Gulf of Mexico, and an automated radiotelemetry array covering ~5000 km<sup>2</sup> to track stopover duration and regional movements. We tested whether stopover duration is prolonged in individuals arriving with lower lean mass and investigated how lean mass affects regional movements. Stopover duration decreased by 22% for each additional gram of lean mass in Northern Waterthrush (Parkesia noveboracensis), but this relationship was not apparent in Swainson's Thrush (Catharus ustulatus), Gray-cheeked Thrush (Catharus minimus), or Yellow-billed Cuckoo (Coccyzus americanus), even though these species also arrived with depleted lean mass. Stopover duration increased for Swainson's Thrush with higher plasma uric acid, a marker of protein catabolism. Northern Waterthrush with higher plasma triglycerides had longer stopovers. Our findings suggest that migratory birds may compensate for substantial lean mass losses by increasing refueling rate or relocating habitat, and highlights species-level differences in lean mass breakdown and the associated impacts on physiological function. Our results highlight the strategies used by different species to recover from a trans-Gulf of Mexico flight and resume migration, which improves our understanding of the annual cycle of migratory birds.</p>
Fig. 2. A in Studen Kladenets Reservoir (CS Bulgaria), a stopover of the migratory Great White Pelicans (Pelecanus onocrotalus Linnaeus, 1758) through the Balkan Peninsula
Fig. 2. A Great White Pelican, Studen Kladenets Reservoir, 26 August 2020. Photo: Zlatozar Z. Boev.
Data and code from Rodkey et al. (2024): "Sod farms drive habitat selection of a migratory grassland shorebird during a critical stopover period"
<p>The data and code in this repository was used to fit the final models for the submitted manuscript "Sod farms drive habitat selection of a migratory grassland shorebird" by Rodkey and coauthors.</p> <p><strong>Abstract:</strong></p> <p>Migratory shorebirds are one of the fastest declining groups of North American avifauna. Yet, relatively little is known about how these species select habitat during migration. We explored the habitat selection of Buff-breasted Sandpipers (<em>Calidris subruficollis</em>) during spring and fall migration through the Texas Coastal Plain, a major stopover region for this species. Using tracking data from 118 birds compiled over 4 years, we found Buff-breasted Sandpipers selected intensively managed crops such as sod and short-stature crop fields, but generally avoided rangeland and areas near trees and shrubs. This work supports prior studies that also indicate the importance of short-stature vegetation for this species. Use of sod and corn varied by season, with birds preferring sod in spring, and avoiding corn when it is tall, but selecting for corn in fall after harvest. This dependence on cropland in the Texas Coastal Plain is contrary to habitat use observed in other parts of their non-breeding range, where rangelands are used extensively. The species' almost complete reliance on a highly specialized crop, sod, at this critical stopover site raises concerns about potential exposure to contaminants as well as questions about whether current management practices are providing suitable conditions for migratory grassland birds.</p> <p> </p> <p><strong>Data and code for model fitting </strong><em>bbsa_sodfarm_selection.zip</em><br>Following files are used to fit final models for the Texas study and the range-wide study.</p> <p><strong>script_tx </strong>is the script used to fit models on Texas dataset. <strong> </strong><em>script_tx.R</em></p> <p><strong>script_rw </strong> is the script used to fit models on range-wide dataset. <em>script_rw.R</em></p> <p><strong>data_tx </strong>is the datafile for containing model input data for the Texas models. data<em>_tx.csv</em></p> <p><strong>data_rw </strong>is the datafile containing model input data for the rangewide models. <em>data_rw.csv</em></p> <p>Columns in the datafiles for both Texas and rangewide models (data_tx and data_rw) are organized as follows:</p> <p>ID - unique identifier for tracked birds</p> <p>year - year in which bird was tracked</p> <p>season - season in which bird was tracked (spring or fall)</p> <p>fromTexas - (rangewide dataset only) whether or not the tracked bird was captured in the study region, the Texas Coastal Plain (T = bird was caught within study region; F = bird was caught outside of study region)</p> <p>night- (Texas dataset only) whether or not the location fell within daytime or nightime hours (y = nightime, n = daytime)</p> <p>droad - distance of location in meters from nearest road</p> <p>dwoody - distance of location in meters from nearest woody cover</p> <p>corn_prop250 - proportion of corn/sorghum landcover type within a 250m buffer around location</p> <p>cotton_prop500 - proportion of cotton/soybean landcover type within a 500m buffer around location</p> <p>herb_prop250 - proportion of herbaceous (i.e., grassy) landcover type within a 250m buffer around location</p> <p>rice_prop1000 - proportion of rice landcover type within a 1000m buffer around location</p> <p>sod_prop250 - proportion of sod landcover type within a 250m buffer around location</p> <p>presence - identifying used versus available locations (1 = used, as in, an actual GPS location of tracked bird; 0 = available, as in, a randomly generated location within the bird's area of use)</p> <p> </p> <p> </p> <p><strong>Tracking data </strong><em>bbsa_txStudy_movebank_20240731.csv</em></p> <p>Tracking data used for Texas study. Lotek PinPoint GPS data were imported and decoded via Movebank and relevant columns were selected. Columns are organized as follows:</p> <p> </p> <p>timestamp - time of GPS location in UTC (format = YYYY-MM-DD HH:MM:SS.SSS)</p> <p>location.long - longitude of GPS location in decimal degrees, projected in the WGS 84 datum</p> <p>location.lat - latitude of GPS location in decimal degrees, projected in the WGS 84 datum</p> <p>lotek.crc.status.text - value of Lotek's cyclical redundancy check (OK = good data, OK(corrected) = message was corrected with Lotek's error correction algorithm, Fail = data has been corrupted on transmission, and therefore cannot be trusted)</p> <p>sensor.type - type of sensor, all rows are "gps"</p> <p>tag.local.identifier - Argos ID of the attached Lotek PinPoint GPS transmitter</p> <p>individual.local.identifier - unique individual identifier, in this case the USGS-issued band number attached to each tracked bird</p> <p>individual.taxon.canonical.name - species taxonomical name, all rows are "Calidris subruficollis"</p> <p>sex - sex of tracked bird (M = male, F = female)</p> <p>age - age of tracke bird (AHY = after-hatch-year, HY = hatch-year)</p> <p> </p> <p> </p> <p><strong>Sod farm layer </strong><em>sodLayer_tgcp.tif</em><br>Raster layer representing sod farms in the Western Gulf Coastal Plain ecoregion of Texas. Resolution of 30m with values from 0 - 1, with 1 representing sod farms. Sod farms were identified via visual inspection, cross-referencing the U.S. Department of Agriculture's Cropland Data Layer with Google Earth high resolution imagery from 2022. This was a modification of preliminary data on sod farm distribution in the region compiled by B. Ortego, S. Gifford and J. Lyons.</p> <p> </p>
Winds aloft over three water bodies influence spring stopover distributions of migrating birds along the Gulf of Mexico coast
<p>Migrating birds contend with dynamic wind conditions that ultimately influence most aspects of their migration, from broad-scale movements to individual decisions about where to rest and refuel. We used weather surveillance radar data to measure spring stopover distributions of northward migrating birds along the northern Gulf of Mexico coast and found a strong influence of winds over non-adjacent water bodies, the Caribbean Sea and Atlantic Ocean, along with the contiguous Gulf of Mexico. Specifically, we quantified the relative influence of meridional (north-south) and zonal (west-east) wind components over the three water bodies on weekly spring stopover densities along western, central, and eastern regions of the northern Gulf of Mexico coast. Winds over the Caribbean Sea and Atlantic Ocean were just as, or more, influential than winds over the Gulf of Mexico, with the highest stopover densities in the central and eastern regions of the coast following the fastest winds from the east over the Caribbean Sea. In contrast, stopover density along the western region of the coast was most influenced by winds over the Gulf of Mexico, with the highest densities following winds from the south. Our results elucidate the important role of wind conditions over multiple water bodies on region-wide stopover distributions and complement tracking data showing Nearctic-Neotropical birds flying non-stop from South America to the northern Gulf of Mexico coast. Smaller-bodied birds may be particularly sensitive to prevailing wind conditions during non-stop flights over water, with probable orientation and energetic consequences that shape subsequent terrestrial stopover distributions. In the future, the changing climate is likely to alter wind conditions associated with migration, so birds that employ non-stop over-water flight strategies may face growing challenges. </p>
Data from: Arriving late and lean at a stopover site is selected against in a declining migratory bird population
<p>Loss and/or deterioration of refuelling habitats have caused population declines in many migratory bird species, but whether this results from unequal mortality among individuals varying in migration traits remains to be shown. Based on 13 years of body mass and size data of great knots (<em>Calidris tenuirostris</em>) at a stopover site of the Yellow Sea, combined with resightings of individuals marked at this stopover site along the East Asian-Australasian Flyway, we assessed year to year changes in annual apparent survival rates, and how apparent survival differed between migration phenotypes (their i.e. migration timing and fuel stores). The measurements occurred over a period of habitat loss and/or deterioration in this flyway. We found that the annual apparent survival rates of great knots rapidly declined from 2006 to 2018, late-arriving individuals with small fuel stores exhibiting the lowest apparent survival rate. There was an advancement in mean arrival date and an increase in the mean fuel load of stopping birds over the study period. Our results suggest that late-arriving individuals with small fuel loads were selected against. Thus, habitat loss and/or deterioration at staging sites may cause changes in the composition of migratory phenotypes at the population-level.</p>
Migratory bird stopover patterns linked to urbanization and social landscapes
Open the record for dataset details and reuse information.
Data from: Persistent species relationships characterize migrating bird communities across stopover sites and seasons
Open the record for dataset details and reuse information.
Data from: Arriving late and lean at a stopover site is selected against in a declining migratory bird population
Open the record for dataset details and reuse information.
Data from: Connecting the dots: Stopover strategies of an intercontinental migratory songbird in the context of the annual cycle
Open the record for dataset details and reuse information.
Data from: Associations with landscape and local-scale wetland habitat conditions vary among migratory shorebird species during stopovers
Open the record for dataset details and reuse information.
Depleted lean body mass after crossing an ecological barrier differentially affects stopover duration and refueling rate among species of long-distance migratory birds
Open the record for dataset details and reuse information.
Winds aloft over three water bodies influence spring stopover distributions of migrating birds along the Gulf of Mexico coast
Open the record for dataset details and reuse information.
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.