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.
7,081
datasets available to search
ShareScore release 0.7.1
Dataset results
7,081 results for “Habitats”
Fig. 4 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia
Fig. 4. Mean Relative Abundance Indices (± SEM) for 12 most frequently encountered mammal species in PPWS at camera trap locations in DDF (black bars) and SEGF (open bars). RM red muntjac; EWP Eurasian wild pig; B banteng; E Asian elephant; LIC large Indian civet; EAP east Asian porcupine; L leopard; CPC common palm civet; D dhole; LC leopard cat; G gaur; and PTM pig-tailed macaque.
Fig.6 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia
Fig.6. Activity patterns, % of all encounters within each hour, of red muntjacs and Eurasian wild pigs from camera-traps in PPWS.
Fig. 2 in Habitat Preferences And Activity Patterns Of The Larger Mammal Community In Phnom Prich Wildlife Sanctuary, Cambodia
Fig. 2. Increase in species richness (species recorded) with total cumulative number of camera trap nights within Phnom Prich Wildlife Sanctuary (Dec 08–Aug 09).
Fig. 1 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 1. Location maps of Deramakot Forest Reserve in Sabah, Malaysian Borneo (D1 to D4: natural-licks).
Fig. 1 in Flies of the family Dolichopodidae (Diptera: Brachycera), excluding the Microphorinae and Parathalassinae, from the Maltese Islands with notes on their habitats and phenology
Fig. 1. Map of the Maltese Islands indicating the main localities sampled (for the names of localities, see Table 1).
Data for: Pollinator and habitat-mediated selection as potential contributors to ecological speciation in two closely related species
<p>In ecological speciation, incipient species diverge due to natural selection that is ecologically based. In flowering plants, different pollinators could mediate that selection (pollinator-mediated divergent selection) or other features of the environment that differ between habitats of two species could do so (environment-mediated divergent selection). Although these mechanisms are well understood, they have received little rigorous testing, as few studies of divergent selection across sites of closely related species include both floral traits that influence pollination and vegetative traits that influence survival. This study employed common gardens in sites of the two parental species and a hybrid site, each containing advanced generation hybrids along with the parental species, to test these forms of ecological speciation in plants of the genus <em>Ipomopsis</em>. Three vegetative traits (specific leaf area, leaf trichomes, and photosynthetic water-use efficiency) and five floral traits (corolla length and width, anther insertion, petal color, nectar production) were analyzed for impacts on fitness components (survival to flowering and seeds per flower, respectively). These traits exhibited strong clines across the elevational gradient in the hybrid zone, with narrower clines in theory reflecting stronger selection or higher genetic variance. Plants with long corollas and inserted anthers had higher seeds per flower at the <em>I. tenuituba </em>site, whereas selection favored the reverse condition at the <em>I. aggregata</em> site, a signature of divergent selection. In contrast, no divergent selection due to variation in survival was detected on any vegetative trait. Selection within the hybrid zone most closely resembled selection within the <em>I. aggregata</em> site. Across traits, the strength of divergent selection was not significantly correlated with width of the cline, which was better predicted by evolvability (standardized genetic variance). These results support the role of pollinator-mediated divergent selection in ecological speciation and illustrate the importance of genetic variance in determining divergence across hybrid zones.</p>
Fig. 3a-j in Physico-chemical characteristics of habitats colonized by the pond snail Radix labiata (Gastropoda, Basommatophora, Lymnaeidae): a model approach
Fig. 3a-j: Graphical presentation of essential parameters associated with logistic regression: white vertical line: position of the maximum probability of occurrence (xmax), black bar: optimum range of the given variable, grey-shaded area: range of the given variable that is still tolerated by the species; a) water temperature, b) pH, c) electric conductivity, d) oxygen content in the water, e) nitrate concentration in the water, f) water depth, g) biological oxygen demand within five days, h) content of ammonium nitrogen, i) geographic altitude, j) current velocity.
Fig. 1 in Physico-chemical characteristics of habitats colonized by the pond snail Radix labiata (Gastropoda, Basommatophora, Lymnaeidae): a model approach
Fig. 1: General habitus of the shell of R. labiata as well as the living animal: a) Front view of the shell (height: 1.4 cm, width: 0.75 cm), b) back view of the shell, c) living animal with its typical triangular tentacles.
Fig. 2a-j in Physico-chemical characteristics of habitats colonized by the pond snail Radix labiata (Gastropoda, Basommatophora, Lymnaeidae): a model approach
Fig. 2a-j: Results of the logistic regression procedure carried out for ten environmental variables: a) water temperature, b) pH, c) electric conductivity, d) oxygen content in the water, e) nitrate concentration in the water, f) water depth, g) biological oxygen demand within five days, h) content of ammonium nitrogen, i) geographic altitude, j) current velocity.
Data for: Hunting mode and habitat selection mediate the success of human hunters
<p class="MsoNormal"><span>As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems<span>. </span>Yet compared to non-human predators<span>, little is known about the </span>drivers and consequences of<span> </span>human<span> hunt</span>ing behavior<span>.<strong> </strong>Here, we characterized the hunting modes, habi</span>tat selection,<span> and harvest success of 483 rifle hunters in California</span> using<span> high-resolu</span>tion <span>GPS </span>data<span>. We used Hidden Markov Models to characterize fine-scale behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with stalking as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with </span>important<span> differences in habitat use of successful and unsuccessful hunters across modes. Our study indicates that hunters can successfully employ a diversity of harvest strategies, and </span>that<span> hunting success </span>is <span>mediated by the </span>interacting effects of<span> hunting mod</span>e and <span>landscape features. Such results high</span>light the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.</span></p>
Canopy Height Map of Los Angeles County Native Habitat Areas
<p>Using LARIAC4 (2016) LIDAR imagery this Canopy Height Model was derived using the lidR, terra and sf packages in R at a resolution of 1 meter. Native habitat areas were selected based on occurence of native flora taxa from iNaturalist in each LARIAC tile. Tiles with no or very few native plants were not included. Additionally, LA County north of the Santa Clara river and San Gabriel mountains was not included, please contact me if you need additional areas. Non-organic features such as power lines, houses, and some high altitude LIDAR noise are still present in the data, future efforts are needed to remove these. Processing took place on the Occidental College computing cluster using a machine with 192GB RAM and 32 cores and took approximately 3 days. The code used to generate this CHM is available here: https://gist.github.com/max-mapper/d52ad9df2f9ed4d191e67955f950e044. The CHM is available as Cloud Optimized Geotiff, which can be viewed in QGIS dynamically over HTTPS without requiring a full download.</p>
FIGURE 4 in Specific damage recognised on land snail shells as a tool for studying predation intensity: differences related to habitat and predator types
FIGURE 4 Variation in the minimal rate of predation recorded in six samples collected in each of five habitat types. Different letters refer to significant differences (p <0.05) among habitat types, based on a generalised linear model. The central line of each box refers to the median value, box height to the interquartile range, whiskers to the non-outlier range (i.e., 1.5 times the interquartile range at each side), and small circles to outliers.
FIGURE 5 in Specific damage recognised on land snail shells as a tool for studying predation intensity: differences related to habitat and predator types
FIGURE 5 Relative representation of individual predation types recognised in six samples collected at each of five habitat types. The height of the column represents the average value, while the lines indicate the standard deviation.
FIGURE 2 in Specific damage recognised on land snail shells as a tool for studying predation intensity: differences related to habitat and predator types
FIGURE 2 Examples of the recorded evidence of predation caused by various predators. a) shell of Cochlicopa lubrica predated on by a snail; b) characteristic damage caused by a carabid beetle, here on a shell of Discus rotundatus; c) puparium of the parasitoid dipteran fly Pherbellia limbata within a Granaria frumentum shell (the shell was crushed manually); d) external damage to a Xerolenta obvia shell caused by bird predation; e) Drilus beetle larval exuviae within an Alinda biplicata shell (the shell was crushed manually).
Distance functions of carabids in crop fields depend on functional traits, crop type and adjacent habitat: a synthesis
<p>Natural pest and weed regulation are essential for agricultural production, but the spatial distribution of natural enemies within crop fields and its drivers are mostly unknown. Using 28 datasets comprising 1,204 study sites across eight Western and Central European countries, we performed a quantitative synthesis of carabid richness, activity densities and functional traits in relation to field edges (i.e. distance functions). We show for the first time that distance functions of carabids strongly depend on carabid functional traits, crop type and, to a lesser extent, adjacent non-crop habitats. Richness of both predators and granivores and activity densities of small and granivorous species decreased towards field interiors, whereas the densities of large species increased. We found strong distance decays in maize and vegetables whereas richness and densities remained more stable in cereals, oilseed crops and legumes. We conclude that carabid assemblages in agricultural landscapes are driven by the complex interplay of crop types, adjacent non-crop habitats and further landscape parameters with great potential for targeted agroecological management. In particular, our synthesis indicates that a higher edge-interior ratio can counter the distance decay of carabid richness per field and thus likely benefits natural pest and weed regulation, hence contributing to agricultural sustainability.</p>
Reclaiming urban vacant land to manage stormwater and support insect habitat
<p>Urban green spaces can provide important wildlife habitat and ecosystem services. In legacy cities, built structures are demolished as populations dwindle, resulting in vacant land. Vacant land constitutes an opportunity to establish green infrastructure that provides multiple ecosystem services. Our objective was to determine whether establishing green infrastructure on vacant land to manage stormwater could provide insect habitat in the legacy city of Cleveland, Ohio, U.S.A. Two green infrastructure treatments were implemented on vacant land in the historic Slavic Village neighborhood in 2014 and 2015: rain gardens (lower cost) and bioswales (higher cost). We hypothesized that rain gardens and bioswales would support more abundant, species rich insect communities compared to unaltered vacant lots. Wild bees (<em>Hymenoptera: Aculeata</em>) and lady beetles (<em>Coleoptera: Coccinellidae</em>), two insect groups of conservation concern, were sampled during the summer (June–August) from 2014 to 2016 using pan traps and yellow sticky card traps. Local vegetation and temporal variables were measured. Generalized linear mixed effects models evaluated whether insect biodiversity varied with treatment, habitat variables, site, and time. We collected 3,004 bees from pan traps and 5,438 lady beetles from yellow sticky card traps during this study. Bee biodiversity was similar among treatments. In 2014, alien <em>Coccinellidae</em> abundance was higher in vacant lots compared to rain gardens. In 2015 and 2016, alien <em>Coccinellidae </em>were marginally more abundant in rain gardens compared to vacant lots and bioswales, while native <em>Coccinellidae</em> abundance was significantly higher in vacant lots. In the short term, establishing green infrastructure on vacant land can improve stormwater management without compromising the quality of vacant land as insect habitat.</p>
Figure 3 in Morphogeometric and genetic variations among North African populations of the Mediterranean killifish Aphanius fasciatus (Valenciennes, 1821) from different habitats
Figure 3. – Projection of Procrustes coordinates and scores of canonical variate on Aphanius fasciatus shape analysis (A) and comparative transformation grids (B). LM: Mellah lagoon, M: Mellah marsh, BZ: Lagoon of Bizerte, LA: Ayata Lake.
Figure 2 in Morphogeometric and genetic variations among North African populations of the Mediterranean killifish Aphanius fasciatus (Valenciennes, 1821) from different habitats
Figure 2. – Landmarks distribution on fish body of Aphanius fasciatus. 1: Eye position, 2: Dorsal opercular limit, 3: Beginning of dorsal fin, 4: End of dorsal fin, 5: Dorsal limit of caudal peduncle, 6: Median limit of caudal peduncle, 7: Ventral limit of caudal peduncle, 8: End of anal fin, 9: Beginning of anal fin, 10: Pelvic fin insertion, 11: Ventral opercula limit, 12: Dorsal limit of pectoral fin, 13: Ventral limit of pectoral fin, 14: Mouth.
Figure 1 in Morphogeometric and genetic variations among North African populations of the Mediterranean killifish Aphanius fasciatus (Valenciennes, 1821) from different habitats
Figure 1. – Map of the west Mediterranean basin with North African sample sites. 1: Mellah lagoon (LM), 2: Mellah marsh (M), 3: Lagoon of Bizerte (BZ), 4: Ayata Lake (LA).
Application of LiDAR to assess the habitat selection of an endangered small mammal in an estuarine wetland environment
<p>Light detection and ranging (lidar) has emerged as a valuable tool for examining the fine-scale characteristics of vegetation. However, lidar is rarely used to examine coastal wetland vegetation or the habitat selection of small mammals. Extensive anthropogenic modification has threatened the endemic species in the estuarine wetlands of the California coast, such as the endangered salt marsh harvest mouse (<em>Reithrodontomys raviventris</em>; SMHM). A better understanding of SMHM habitat selection could help managers better protect this species. We assessed the ability of airborne topographic lidar imagery in measuring the vegetation structure of SMHM habitats in a coastal wetland with a narrow range of vegetation heights. We also aimed to better understand the role of vegetation structure in habitat selection at different spatial scales. Habitat selection was modeled from data compiled from 15 small mammal trapping grids collected in the highly urbanized San Francisco Estuary in California, USA. Analyses were conducted at three spatial scales: microhabitat (25 m<sup>2</sup>), mesohabitat (2,025 m<sup>2</sup>), and macrohabitat (10,000 m<sup>2</sup>). A suite of structural covariates was derived from raw lidar data to examine vegetation complexity. We found that adding structural covariates to conventional habitat selection variables significantly improved our models. At the microhabitat scale in managed wetlands, SMHM preferred areas with denser and shorter vegetation, and selected for proximity to levees and taller vegetation in tidal wetlands. At the mesohabitat scale, SMHM were associated with a lower percentage of bare ground and with pickleweed (<em>Salicornia pacifica</em>) presence. All covariates were insignificant at the macrohabitat scale.<em> </em>Our results suggest that SMHM preferentially selected microhabitats with access to tidal refugia and mesohabitats with consistent food sources. Our findings showed that lidar can contribute to improving our understanding of habitat selection of wildlife in coastal wetlands and help to guide future conservation of an endangered species.</p>
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.