Skip to main content
Powered by ShareScore

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.

2,445

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

2,445 results for “Genetics: population”

Learn how ShareScore rates datasets ↗
zenodo32/100

FIGURE 2 in Plastid DNA fingerprinting of the rare Fritillaria moggridgei (Liliaceae) reveals population differentiation and genetic isolation within the Fritillaria tubiformis complex

FIGURE 2. Strict consensus tree of more than 2600 most parsimonious trees from analysis of the combined plastid matK and rpl16 intron sequences. Tree length = 451 steps, CI = 0.89 and RI = 0.85. Bootstrap percentages (> 50%) are indicated above branches. Cardiocrinum giganteum and Notholirion thomsonianum are the outgroups. See also Table 2.

opennotspecifiedApr 2013View details →
zenodo32/100

FIGURE 4 in Plastid DNA fingerprinting of the rare Fritillaria moggridgei (Liliaceae) reveals population differentiation and genetic isolation within the Fritillaria tubiformis complex

FIGURE 4. Principal coordinate analysis (PCO) of eleven populations of Fritillaria tubiformis s.l. analyzed for ten microsatellite loci. The first (PCO1) and the second (PCO2) axes explain 50.4% and 20.9% of total variation, respectively. Acronyms correspond to populations (see Table 1). The two genetic groups corresponding to the two subspecific taxa are circled.

opennotspecifiedApr 2013View details →
zenodo32/100

FIGURE 1 in Plastid DNA fingerprinting of the rare Fritillaria moggridgei (Liliaceae) reveals population differentiation and genetic isolation within the Fritillaria tubiformis complex

FIGURE 1. Map of the Italian populations of F. tubiformis s.l. Populations belonging to var. burnatii are labelled with a star and those belonging to subsp. moggridgei with a solid circle. Most sampled populations are located at the boundary between Piedmont (P) and Liguria (L) (Italy). Insets show, top left, sampling sites numbered as for populations (see Table 1) and, top right, the position of the sampled area within the Alps.

opennotspecifiedApr 2013View details →
dryad32/100

Urbanization reduces genetic connectivity in bobcats (Lynx rufus) at both intra- and inter-population spatial scales

<p>Urbanization is a major factor driving habitat fragmentation and connectivity loss in wildlife. However, the impacts of urbanization on connectivity can vary among species and even populations due to differences in local landscape characteristics, and our ability to detect these relationships may depend on the spatial scale at which they are measured. Bobcats (<i>Lynx rufus</i>) are relatively sensitive to urbanization and the status of bobcat populations is an important indicator of connectivity in urban coastal southern California. We genotyped 271 bobcats at 13,520 SNP loci to conduct a replicated landscape resistance analysis in five genetically distinct populations. We tested urban and natural factors potentially influencing individual connectivity in each population separately, as well as study-wide. Overall, landscape genomic effects were most frequently detected at the study-wide spatial scale, with urban land cover (measured as impervious surface) having negative effects and topographic roughness having positive effects on gene flow. The negative effect of urban land cover on connectivity was also evident when populations were analyzed separately despite varying substantially in spatial area and the proportion of urban development, confirming a pervasive impact of urbanization largely independent of spatial scale. The effect of urban development was strongest in one population where stream habitat had been lost to development, suggesting that riparian corridors may help mitigate reduced connectivity in urbanizing areas. Our results demonstrate the importance of replicating landscape genetic analyses across populations and considering how landscape genetic effects may vary with spatial scale and local landscape structure.</p>

opencc-zeroOct 2019View details →
dryad32/100

Oceanographic features and limited dispersal shape the population genetic structure of the vase sponge Ircinia campana in the Greater Caribbean

<p>Understanding population genetic structure can help us to infer dispersal patterns, predict population resilience and design effective management strategies. For sessile species with limited dispersal, this is especially pertinent because genetic diversity and connectivity are key aspects of their resilience to environmental stressors. Here, we describe the population structure of <i>Ircinia campana</i>, a common Caribbean sponge subject to mass mortalities and disease. Microsatellites were used to genotype 440 individuals from 19 sites throughout the Greater Caribbean. We found strong genetic structure across the region, and significant isolation by distance across the Lesser Antilles, highlighting the influence of limited larval dispersal. We also observed spatial genetic structure patterns congruent with oceanography. This includes evidence of connectivity between sponges in the Florida Keys and the southeast coast of the United States (&gt;700 km away) where the oceanographic environment is dominated by the strong Florida Current. Conversely, the population in southern Belize was strongly differentiated from all other sites, consistent with the presence of dispersal-limiting oceanographic features, including the Gulf of Honduras gyre. At smaller spatial scales (&lt;100 km), sites showed heterogeneous patterns of low-level but significant genetic differentiation (chaotic genetic patchiness), indicative of temporal variability in recruitment or local selective pressures. Genetic diversity was similar across sites, but there was evidence of a genetic bottleneck at one site in Florida where past mass mortalities have occurred. These findings underscore the relationship between regional oceanography and weak larval dispersal in explaining population genetic patterns, and could inform conservation management of the species.</p>

opencc-zeroJul 2021View details →
dryad32/100

Context-dependent dispersal determines relatedness and genetic structure in a patchy amphibian population

<p>Dispersal is a central process in ecology and evolution with far reaching consequences for the dynamics and genetics of spatially structured populations (SSPs). Individuals can adjust their decisions to disperse according to local fitness prospects, resulting in context-dependent dispersal. By determining dispersal rate, distance, and direction, these individual-level decisions further modulate the demography, relatedness, and genetic structure of SSPs. Here, we examined how context-dependent dispersal influences the dynamics and genetics of a Great Crested Newt (<i>Triturus cristatus</i>) SSP. We collected capture-recapture data of 5564 individuals and genetic data of 950 individuals across a SSP in northern Germany. We added genetic data from six sites outside this SSP to assess genetic structure and gene flow at a regional level. Dispersal rates within the SSP were high but dispersal distances were short. Dispersal was context-dependent: individuals preferentially immigrated into high-quality ponds where breeding probabilities were higher. The studied SSP behaved like a patchy population, where subpopulations at each pond were demographically interdependent. High context-dependent dispersal led to weak but significant spatial genetic structure and relatedness within the SSP. At the regional level, a strong hierarchical genetic structure with very few first-generation migrants as well as low effective dispersal rates suggest the presence of independent demographic units. Overall, our study highlights the importance of habitat quality for driving context-dependent dispersal and therefore demography and genetic structure in SSPs. Limited capacity for long-distance dispersal seems to increase genetic structure within a population and leads to demographic isolation in anthropogenic landscapes.</p>

opencc-zeroJul 2021View details →
zenodo32/100

Figure 2 in Effects of fragmentation on genetic variation in populations of the terrestrial earthworm Drawida japonica Michaelsen, 1892 (Oligochaeta, Moniligastridae) in Shandong and Liaodong peninsulas, China

Figure 2. Maximum-parsimony (MP) tree of the unique haplotypes. Numbers at nodes represent bootstrap values (&gt; 50) as a measure of support.

opennotspecifiedJun 2012View details →
zenodo32/100

Figure 4 in Effects of fragmentation on genetic variation in populations of the terrestrial earthworm Drawida japonica Michaelsen, 1892 (Oligochaeta, Moniligastridae) in Shandong and Liaodong peninsulas, China

Figure 4. Mismatch curve of nucleotide pairwise based on 16S sequences. Exp, expected value; Obs, observed value.

opennotspecifiedJun 2012View details →
zenodo32/100

Figure 3 in Effects of fragmentation on genetic variation in populations of the terrestrial earthworm Drawida japonica Michaelsen, 1892 (Oligochaeta, Moniligastridae) in Shandong and Liaodong peninsulas, China

Figure 3. Maximum-likelihood (ML) tree of the unique haplotypes. Bootstrap values (&gt; 50) are shown on the nodes; Bayesian inference (BI) tree based on the analysis of the unique haplotypes. Posterior probability values (&gt; 0.5) are shown.

opennotspecifiedJun 2012View details →
zenodo32/100

Figure 5 in Effects of fragmentation on genetic variation in populations of the terrestrial earthworm Drawida japonica Michaelsen, 1892 (Oligochaeta, Moniligastridae) in Shandong and Liaodong peninsulas, China

Figure 5. Mismatch curve of nucleotide pairwise based on 28S sequences. Exp, expected value; Obs, observed value.

opennotspecifiedJun 2012View details →
dryad32/100

Agriculture creates subtle genetic structure among migratory and non-migratory populations of burrowing owls throughout North America

Population structure across a species distribution primarily reflects historical, ecological and evolutionary processes. However, large-scale contemporaneous changes in land use have the potential to create changes in habitat quality and thereby cause changes in gene flow, population structure, and distributions. As such, land-use changes in one portion of a species range may explain declines in other portions of their range. For example, many burrowing owl populations have declined or become extirpated near the northern edge of the species' breeding distribution during the second half of the 20th century. In the same period, large extensions of thornscrub were converted to irrigated agriculture in northwestern Mexico. These irrigated areas may now support the highest densities of burrowing owls in North America. We tested the hypothesis that burrowing owls that colonized this recently created owl habitat in northwestern Mexico originated from declining migratory populations from the northern portion of the species' range (migration-driven breeding dispersal whereby long-distance migrants from Canada and the U.S. became year-round residents in the newly created irrigated agriculture areas in Mexico). We used 10 novel microsatellite markers to genotype 1,560 owls from 36 study locations in Canada, Mexico, and the United States. We found that burrowing owl populations are practically panmictic throughout the entire North American breeding range. However, an analysis of molecular variance provided some evidence that burrowing owl populations in northwestern Mexico and Canada together are more genetically differentiated from the rest of the populations in the breeding range, lending some support to our migration-driven breeding dispersal hypothesis. We found evidence of subtle genetic differentiation associated with irrigated agricultural areas in southern Sonora and Sinaloa in northwestern Mexico. Our results suggest that land-use can produce location-specific population dynamics leading to subtle genetic structure even in the absence of dispersal barriers.

opencc-zeroAug 2021View details →
zenodo32/100

Figure 5 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)

Figure 5. Mean number of barricades per burrow in Ilyoplax pusilla at six localities (bar indicates SD). Localities arranged according to latitude. Shared alphabetical letters indicate no significant difference (p.0.05) by Tukey's honestly significant difference test.

opennotspecifiedJan 2009View details →
zenodo32/100

Figure 2 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)

Figure 2. Cheliped path movement in Ilyoplax pusilla: circular type and vertical type. Arrows indicate wave path.

opennotspecifiedJan 2009View details →
zenodo32/100

Figure 6 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)

Figure 6. Parsimony network of mitochondrial DNA cytochrome oxidase subunit I (COI) haplotypes of Ilyoplax pusilla. Haplotypes correspond to Table 5. Single solid line indicates one base. Circle size indicates number of each haplotype. Largest circle, n542; second largest, n514 or 15; third, n58; fourth, n54 or n55; fifth, n52; smallest circle, n51.

opennotspecifiedJan 2009View details →
zenodo32/100

Figure 3 in Genetic, ecological and morphological differences among populations of the cactophilic Drosophila mojavensis from southwestern USA and northwestern Mexico, with descriptions of two new subspecies

Figure 3. Photographs showing lateral views of the aedeagus and aedeagal apodeme in the four subspecies of Drosophila mojavensis. (A) D. m. mojavensis; (B) D. m. baja; (C) D. m. sonorensis; (D) D. m. wrigleyi.

opennotspecifiedApr 2009View details →
zenodo32/100

Figure 1 in Genetic, ecological and morphological differences among populations of the cactophilic Drosophila mojavensis from southwestern USA and northwestern Mexico, with descriptions of two new subspecies

Figure 1. Map showing approximate geographic distribution of the four subspecies of Drosophila mojavensis in southwestern USA and northwestern Mexico.?5unconfirmed subspecies at San Felipe, Baja California. Numbers show localities where flies used for laboratory cultures were collected: (1) Mojave; (2) Baja; (3) Sonora; (4) Catalina (see 'Materials and methods' for details).

opennotspecifiedApr 2009View details →
zenodo32/100

Figure 1 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)

Figure 1. Geographic distribution of Ilyoplax pusilla in Japan (broken line) from Wada et al. (1992), and six localities studied.

opennotspecifiedJan 2009View details →
zenodo32/100

Figure 4 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)

Figure 4. Proportion of extended waves in 30 waving motions of Ilyoplax pusilla at six localities (bar indicates SD). Localities arranged according to latitude. Shared alphabetical letters indicate no significant difference (p.0.05) by Tukey's honestly significant difference test.

opennotspecifiedJan 2009View details →
zenodo32/100

Figure 3 in Geographical variations in waving display and barricade-building behaviour, and genetic population structure in the intertidal brachyuran crab Ilyoplax pusilla (de Haan, 1835)

Figure 3. Maximum cheliped extension during waving movements in Ilyoplax pusilla: extended type and non-extended type.

opennotspecifiedJan 2009View details →
zenodo32/100

Figure 1 in Genetic diversity of Atherina hepsetus (Osteichthyes: Atherinidae) populations as determined by RFLP analysis of three mtDNA regions

Figure 1. Sampling sites: Monastiraki (MON), Panagopoula (PAN), Kiparissi (KIP), Tinos (TIN), Naxos (NAX), Samos (SAM), Nissiros (NIS), Leipsi (LEI), Kos (KOS), Lesvos (MYT) and Evvoia (EVV).

opennotspecifiedFeb 2008View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record