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.
355
datasets available to search
ShareScore release 0.9.0
Dataset results
355 results for “mammal species”
Figure 4 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 4. Response graphs of habitat suitability (ordinate axis) according to the explanatory variables that intervened in the adjustment of the model for brown brocket deer (A, B, C). The temperature is expressed in degrees Celsius.Source of bioclimatic variables (bio), site https://www.worldclim.org/data/bioclim.html.
Figure 8 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 8. Species richness maps obtained using three algorithms, (A) "fuzzy union″, (B) "species richness″ and (C) "total beta″.
Figure 7 in Conservation gaps identification through patterns of species richness established from species niche models of mammals in a sector of Chaco Seco ecoregion
Figure 7. Response graphs of habitat suitability (ordinate axis) according to the explanatory variables that intervened in theadjustment of themodel for collared peccary (A,B, C).Temperature is expressed in degrees Celsius and altitude in meters.Source of bioclimatic variables (bio), site https://www.worldclim.org/data/bioclim.html.
Rapid morphological change in a small mammal species after habitat fragmentation over the past half-century
<p><b>Study Aim:</b> To compare the rapid shifts in body size of mainland and island populations of a native rodent and examine the mechanisms underlying these changes.</p> <p><b>Location:</b> Thousand Island Lake, China, which was created in 1959 when the Xin'anjiang Dam was constructed for generating hydroelectricity.</p> <p><b>Taxon:</b> The Chinese white-bellied rat, <i>Niviventer confucianus</i>.</p> <p><b>Methods</b>: Field surveys were conducted from 2015 to 2018 to collect data on body size of the rodents from a set of islands and nearby mainland sites. We constructed multiple linear models to examine the relationships between body size (length and mass) of rodents and biological variables (predators, interspecific and intraspecific competitors, and food availability). We also conducted structural equation modeling (SEM) by constructing models via confirmatory path analysis.</p> <p><b>Results: </b>All island populations of <i>N. confucianus</i> had significantly larger body size (both body mass and body length) than their mainland counterparts. Moreover, populations on small and more isolated islands had larger body size than their relatives on big islands. The relative absence of predators (large-bodied mammals, snakes, and raptors) on islands was most strongly associated with shifts in the body size of rodents. The documented changes occurred after only a half-century of fragmentation.</p> <p><b>Main conclusions: </b>The observed rapid body enlargement of rodents after habitat fragmentation is consistent with a release from predation pressure. SEM indicated that island area, rather than island isolation, had positive effects on the richness of predators, interspecific competitors and food resources, which then had an indirect impact on body size of the rodents. In this study, we report a remarkably rapid case of mammal morphological shifts in a small mammal in response to habitat fragmentation. Given the omnipresence of dams and other anthropogenic disturbances, our findings suggest that a wave of rapid phenotypic shifts in terrestrial vertebrates is taking place in the Anthropocene.</p>
Analysis of biodiversity data suggests that mammal species are hidden in predictable places
<p>Research in the biological sciences is hampered by the Linnean shortfall, which describes the number of hidden species that are suspected of existing without formal species description. Using machine learning and species delimitation methods, we built a predictive model that incorporates some 5.0 × 10<sup>5</sup> data points for 117 species traits, 3.3 × 10<sup>6</sup> occurrence records, and 9.1 × 10<sup>5</sup> gene sequences from 4,310 recognized species of mammals. Delimitation results suggest that there are hundreds of undescribed species in class Mammalia. Predictive modeling indicates that most of these hid- den species will be found in small-bodied taxa with large ranges characterized by high variability in temperature and precipitation. As demonstrated by a quantitative analysis of the literature, such taxa have long been the focus of taxonomic research. This analysis supports taxonomic hypotheses regarding where undescribed diversity is likely to be found and highlights the need for investment in taxonomic research to overcome the Linnean shortfall.</p>
The counteracting effects of human-driven speciation and extinction on mammal species richness and phylogenetic diversity
<p><span>Human activities are causing massive increases in extinction rates, but may also lead to drastic increases in speciation rates – for example following the human-mediated spread of species to otherwise unreachable landmasses. The long-term net anthropogenic effects on biodiversity, therefore, remain uncertain. The aim of this paper is to assess the combined anthropogenic effects of extinctions and speciations on biodiversity over geological time scales. </span><span>We estimate known anthropogenic and predicted future extinctions based on Red List categories from the International Union for Conservation of Nature. We infer potential anthropogenic speciations assuming that all introductions to isolated landmasses will over time evolve into distinct species. We then estimate changes in regional and global species richness and phylogenetic diversity due to these extinctions and speciations. </span><span>We show that if all species introduced into new landmasses develop into new species, the number of anthropogenic speciation and extinctions eventually become similar</span><span>. However, even after accounting for an anthropogenic increase in speciation, our estimates suggest recovery times for phylogenetic diversity of several million years</span><span>. </span><span>Our results highlight that while humans are causing drastic biodiversity losses, human-driven speciation could eventually counterbalance these losses in species numbers, while phylogenetic diversity at least within our simulation scenarios would remain permanently reduced. This conclusion, however, requires our pressures on biodiversity to cease soon and requires us to consider geological timescales rather than changes over this century.</span></p>
Species richness, composition and microhabitat characteristics of non-volant terrestrial mammals in disturbed habitats
<b>Description: </b><p>A study on the small mammals communities was carried out in disturbed habitats aroundsabah, namely university malaysia sabah (ums), klias peat swamp forest reserve(klias), kawang forest reserve (kawang), kalabakan forest reserve (safe) and maliaubasin conservation area (maliau). the objectives were (1) to determine the speciesrichness and composition of non-volant small mammal communities in disturbedhabitats; (2) to characterize the microhabitat-use patterns of the non-volant smallmammal communities in disturbed habitats; and (3) to determine the microhabitatpreferences of the non-volant small mammal communities in disturbed habitats. the aimof this study was to investigate how the habitat disturbance affects the species richness,community compositions and microhabitat-use pattern of the small mammals. this studywas conducted from october 2014 to march 2015 with a total sampling effort of 540trap-nights. overall, 71 individuals representing 14 species were successfully caughtduring this study. the species richness peaked at safe, and then declined at the rest ofthe study sites. habitat variables analysis showed that all study sites were divided intothree distinctive groups in terms of habitat types. canonical discriminant functionanalysis were used to analyze the microhabitat preferences and use-pattern of smallmammals and results showed the preferences of small mammals towards shrub cover(rattus rattus and callosciurus notatus), litter cover (callosciurus prevostii and echinorexgymnurus) and herbs limber (tupaia gracilis). The locations of the traps have not been given longitute and latitute as there were set on animal trails approximately 20metres from one another. </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/150"><b>Species richness, composition and microhabitat characteristics of non-volant terrestrial mammals in disturbed habitats</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Universiti Malaysia Sabah (Grant)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiverstiy Council (Research licence NA)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3265704">here</a></p><p><b>Files: </b>This consists of 1 file: Veg_Volent_mammals.xlsx</p><p><b>Veg_Volent_mammals.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Vegetation cover</b> (described in worksheet Vegetation_cover)</p><p>Description: The estimated canopy cover and percentage of ground cover of traps across disturbed habitats</p><p>Number of fields: 19</p><p>Number of data rows: 180</p><p>Fields: </p><ul><li><b>Date</b>: Date the vegetation cover was collected (Field type: Date)</li><li><b>Location</b>: Where data was collected (Field type: Location)</li><li><b>Habitat_type</b>: Habitat type (Field type: Categorical)</li><li><b>Trap_station</b>: Transect and trap number (Field type: ID)</li><li><b>Canopy_cover</b>: Percentage of canopy cover (Field type: Numeric)</li><li><b>Canopy_height</b>: Canopy height (Field type: Numeric)</li><li><b>Herbs_Climber</b>: Any climbers seen on trees for example vines and lianas (Field type: Numeric)</li><li><b>Tree_GBH_>10CM</b>: Tree girth at breast height of 10 cm (Field type: Numeric)</li><li><b>Tree_GBH_>30CM</b>: Tree girth at breast height of 30 cm (Field type: Numeric)</li><li><b>Tree_GBH_>60CM</b>: Tree girth at breast height of 60 cm (Field type: Numeric)</li><li><b>Tree_GBH_>90CM</b>: Tree girth at breast height of 90 cm (Field type: Numeric)</li><li><b>Fallen_trees_bran</b>: Percentage cover (Field type: Numeric)</li><li><b>Bareground</b>: Percentage cover (Field type: Numeric)</li><li><b>Shrub</b>: Percentage cover (Field type: Numeric)</li><li><b>grass</b>: Percentage cover (Field type: Numeric)</li><li><b>Rock</b>: Percentage cover (Field type: Numeric)</li><li><b>Litter</b>: Percentage cover (Field type: Numeric)</li><li><b>Water</b>: Percentage cover (Field type: Numeric)</li><li><b>Twig</b>: Percentage cover (Field type: Numeric)</li></ul></li><li><p><b>Non volent mammal abundance</b> (described in worksheet Non_volent_mammals)</p><p>Description: The abundance of non-volant terrestrails mammals caught across disturbed habitats. Growth and sex measurements takens</p><p>Number of fields: 17</p><p>Number of data rows: 490</p><p>Fields: </p><ul><li><b>Date</b>: Date the vegetation cover was collected (Field type: Date)</li><li><b>Location</b>: Where data was collected (Field type: Location)</li><li><b>Transect</b>: Transect number (Field type: ID)</li><li><b>Habitat</b>: Habitat type (Field type: Categorical)</li><li><b>Trap_station</b>: Transect and trap number (Field type: ID)</li><li><b>Species</b>: Species of non volent mammals caught in trap (Field type: Taxa)</li><li><b>Weight</b>: Weight of caught non volent mammal (Field type: Numeric)</li><li><b>Ear</b>: Ear measurment of caught non volent mammal (Field type: Numeric)</li><li><b>Hind_leg</b>: Hind leg measurement of caught non-volent mammal (Field type: Numeric)</li><li><b>Head_body</b>: Head to body measurement of caught non volent mammal (Field type: Numeric)</li><li><b>Tail</b>: Tail length of caught non volent mammal (Field type: Numeric)</li><li><b>Sex</b>: Sex of caught non volent mammal (Field type: Categorical)</li><li><b>Sexual_activity</b>: Sexual maturity of caught non volent mammal (Field type: Categorical)</li><li><b>Age</b>: Age class of caught non volent mammal (Field type: Categorical)</li><li><b>Trap_condition</b>: Trap condition (Field type: Categorical)</li><li><b>Trap_open_closed</b>: Trap open or closed (Field type: Categorical)</li><li><b>Bait</b>: Bait taken or intact (Field type: Categorical)</li></ul></li></ol><p><b>Date range: </b>2014-10-22 to 2015-03-30</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Chordata<br> -  - Mammalia<br> -  -  - Erinaceomorpha<br> -  -  -  - Erinaceidae<br> -  -  -  -  - <i>Echinosorex</i><br> -  -  -  -  -  - <i>Echinosorex gymnura</i><br> -  -  - Rodentia<br> -  -  -  - Muridae<br> -  -  -  -  - <i>Lenothrix</i><br> -  -  -  -  -  - <i>Lenothrix canus</i><br> -  -  -  -  - <i>Leopoldamys</i><br> -  -  -  -  -  - <i>Leopoldamys sabanus</i><br> -  -  -  -  - <i>Maxomys</i><br> -  -  -  -  -  - <i>Maxomys rajah</i><br> -  -  -  -  -  - <i>Maxomys surifer</i><br> -  -  -  -  - <i>Niviventer</i><br> -  -  -  -  -  - <i>Niviventer cremoriventer</i><br> -  -  -  -  - <i>Rattus</i><br> -  -  -  -  -  - <i>Rattus rattus</i><br> -  -  -  - Sciuridae<br> -  -  -  -  - <i>Callosciurus</i><br> -  -  -  -  -  - <i>Callosciurus adamsi</i><br> -  -  -  -  -  - <i>Callosciurus notatus</i><br> -  -  -  -  -  - <i>Callosciurus prevostii</i><br> -  -  -  -  - <i>Sundasciurus</i><br> -  -  -  -  -  - <i>Sundasciurus lowii</i><br> -  -  - Scandentia<br> -  -  -  - Tupaiidae<br> -  -  -  -  - <i>Tupaia</i><br> -  -  -  -  -  - <i>Tupaia dorsalis</i><br> -  -  -  -  -  - <i>Tupaia glis</i><br> -  -  -  -  -  - <i>Tupaia gracilis</i><br></div><p></p>
Figure 7 in Two new genera and two new species of the mite family Neopygmephoridae (Acari: Heterostigmata) associated with small mammals from USA
Figure 7 Theriadania venusta sp. nov., female: A – gnathosoma in dorsal view, B – gnathosoma
FIGURE 10 in A second endemic land mammal for the Hawaiian Islands: a new genus and species of fossil bat (Chiroptera: Vespertilionidae)
FIGURE 10. Skeleton of Synemporion keana in situ on the floor near the lower end of Māhiehie Cave.
Fig. 74 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 74. Dorsal and ventral views of the skin of AMNH 266566, neotype of Cavia acouchy Erxleben,
Fig. 33 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 33. Limits of 12 rodent craniodental measurements defined in the text.
Fig. 30 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 30. Dorsal, ventral, and lateral cranial views of FMNH 21720, neotype of Viverra touan Shaw
Fig. 39 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 39. Left maxillary toothrows (A, B) and right mandibular toothrows (C, D) of Neacomys dubosti
Fig. 65 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 65. Dorsal and ventral views of the skin of NMW 42010, lectotype of Coendou melanurus
Fig. 69 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 69. Left lateral cranial views of Coendou melanurus (top, AMNH 94174) and C. insidiosus
Fig. 64 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species
Fig. 64. Dorsal, ventral, and lateral cranial views of NMW 42010, lectotype of Coendou melanurus
Rapid morphological change in a small mammal species after habitat fragmentation over the past half-century
<p><span><b>Study Aim:</b> To compare the rapid shifts in body size of mainland and island populations of a native rodent and examine the mechanisms underlying these changes.</span></p> <p><span><b>Location:</b> Thousand Island Lake, China, which was created in 1959 when the Xin'anjiang Dam was constructed for generating hydroelectricity.</span></p> <p><b>Taxon:</b> The Chinese white-bellied rat, <i>Niviventer confucianus</i>.</p> <p><span><b>Methods</b>: Field surveys were conducted from 2015 to 2018 to collect data on body size of the rodents from a set of islands and nearby mainland sites. We constructed multiple linear models to examine the relationships between body size (length and mass) of rodents and biological variables (predators, interspecific and intraspecific competitors, and food availability). We also conducted structural equation modeling (SEM) by constructing models via confirmatory path analysis.</span></p> <p><span><b>Results: </b>All island populations of <i>N. confucianus</i> had significantly larger body size (both body mass and body length) than their mainland counterparts. Moreover, populations on small and more isolated islands had larger body size than their relatives on big islands. The relative absence of predators (large-bodied mammals, snakes, and raptors) on islands was most strongly associated with shifts in the body size of rodents. The documented changes occurred after only a half-century of fragmentation.</span></p> <p><span><b>Main conclusions: </b>The observed rapid body enlargement of rodents after habitat fragmentation is consistent with a release from predation pressure. SEM indicated that island area, rather than island isolation, had positive effects on the richness of predators, interspecific competitors and food resources, which then had an indirect impact on body size of the rodents. In this study, we report a remarkably rapid case of mammal morphological shifts in a small mammal in response to habitat fragmentation. Given the omnipresence of dams and other anthropogenic disturbances, our findings suggest that a wave of rapid phenotypic shifts in terrestrial vertebrates is taking place in the Anthropocene.</span></p>
Northern Nevada wildlife and topography: Camera trapping data set for 14 mammal species collected from 100 sampling sites in northwestern Nevada
<p>Camera traps are one of the most common field techniques for surverying terrestrial mammal communities and thus, much work has gone into understanding how different factors influence species detection at camera trap locations. However, the effect of fine-scale topography, such as terrain slope and position, on wildlife detection has not been explicitly quantified despite strong effects of topography on animal movement in mountainous regions. This data set contains weekly detection non-detection data for 14 mammal species from 100 camera traps sites monitored for 28 months (June 2018 - September 2020) in northwestern Nevada, U.S.A. This sampling extent was split into 3 month sampling seasons, exclusive of winter (Dec, Jan, Feb) and spring 2020, when data were sparse. In addition to species detection data, that dataset includes topographic variables at cameras sites: 1) terrain slope, calculated in R package raster from a 10m digital elevation model and 2) Topographic position index averaged across three buffer sizes around points 270m, 810m, and 2430m. The land cover variables proportion mixed conifer and proportion pinyon-juniper woodland within a 5000m buffer of sites are also included. Both are derived from the USDA/US DOI Landfire 2016 dataset. The luring variable indicates whether attractant was applied at a site during a given week, the effect of which was assumed to last for a month after the last application. </p>
Effects of large mammal exclusion on seedling communities depend on plant species traits and landscape protection in human-modified Costa Rican forests
<ol> <li>Large terrestrial herbivorous mammals (LTH-mammals) influence plant community structure by affecting seedling establishment in mature tropical forests. Many of these LTH-mammals frequent secondary forests, but their effects on seedling establishment in them are understudied, hindering our understanding of how LTH-mammals influence forest regeneration in human-modified landscapes.</li> <li>We tested the hypothesis that the strength of LTH-mammals' effects on seedling establishment depends on landscape protection, forest successional stage, and plant species' traits using a manipulative field experiment in six 1-ha sites with varying successional age and landscape protection. In each site, we established forty seedling plot-pairs, with one plot excluding LTH-mammals and one not, and monitored seedlings of 116 woody species for 26 months.</li> <li>We found significant effects of LTH-mammal exclusion on seedling survival contingent upon the protection of forests at the landscape level and forest stage. After 26 months, survival differences between LTH-mammal exclusion and non-exclusion treatments were greater in protected than unprotected landscapes. Additionally, plant species' traits were related to the LTH-mammals' differential effects, as LTH-mammals reduced the survival of seedlings of larger-seeded species the most. Overall, LTH-mammals' effects translated into significant shifts in community composition as seedling communities inside and outside the exclosures diverged. Moreover, lower density and higher species diversity were found as early as 12 and 18 months outside than inside exclosures.</li> <li> <em>Synthesis and applications</em>. Insight into the interactions between LTH-mammals and seedling communities in forest regeneration can be instrumental in planning effective restoration efforts. We highlight the importance of landscape protection in seedling survival and the role of LTH-mammals in promoting seedling diversity in mature forests but also in secondary successional forests. The findings suggest that conservation efforts and possibly trophic rewilding can be important approaches for preserving diversity and influencing the trajectory of secondary tropical forest succession. However, we also caution that an overabundance of LTH-mammals may adversely impact the pace of forest succession due to their preference for large-seeded species. Therefore, a comprehensive wildlife management plan is indispensable. Additionally, longer-term studies on LTH-mammals are necessary to understand the effects of temporal fluctuations that are undetected in short-term studies.</li> </ol>
Data and scripts from: Most mammals do not wander: few species escape continental endemism
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.