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.
21
datasets available to search
ShareScore release 0.9.0
Dataset results
21 results for “mammal occurrence”
Mammal occurrence data derived from camera traps in grassland-shrubland ecotones at 24 sites in the Jornada Basin, southern New Mexico, USA, 2014-ongoing
The objective of this ongoing study is to investigate how abundance, distribution, and activity of mammals (>= 1 kg) vary across grassland to shrubland ecotones in the northern Chihuahuan Desert. This dataset includes animal occurrence data derived from camera trap images captured in 24 grassland-to-shrubland ecotone sites in the Jornada Basin, Dona Ana County, New Mexico, USA. The data set contains occurrence records from 14 mammal species with the date and time a species was detected. Also included are the number of individuals in a photo, operational dates and number of functional camera days for cameras, total number of trap nights a camera was active, and geographical coordinates of camera trap locations. Sampling is ongoing and occurs during the monsoon season from July-November. Sampling has occurred annually since 2014.
Mammal occurrence records (2024) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India
<p>This dataset contains Mammal occurrence records (November 2023 - October 2024) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. It includes a few occurrence records from other parts of southern India. Occurrence records were gathered in the field by researchers of the Nature Conservation Foundation, India, using a mobile data collection application (EpiCollect5). Suggested citation is:<br>Nature Conservation Foundation (2024). Mammal occurrence records (2024) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. Nature Conservation Foundation, India. Dataset, Zenodo. DOI: 10.5281/zenodo.13910696<br> <br><strong>CONTACT #1</strong><br>1. Name: T. R. Shankar Raman <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: trsr@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0002-1347-3953</p> <p><strong>CONTACT #2</strong><br>1. Name: Divya Mudappa <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: divya@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0001-9708-4826</p> <p><strong>Keywords: </strong>tropical rainforest, plantations, Anamalai Hills, Western Ghats, animal distribution, mammals </p> <p><br><strong>Geographic Coverage:</strong><br>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br>2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p><strong>Temporal Coverage:</strong><br>1. Begins: 2023-11-01 (Year, Month, Day)<br>2. Ends: 2024-10-01 (Year, Month, Day)</p> <p>Besides the 00_readMe.txt file containing this information, the dataset includes 23 images (photographs) and two comma-delimited text (csv) files as explained below:<br><strong>1) 01_anamalai-mammals-2024.csv </strong>-- This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded csv file from the EpiCollect5 application website.</p> <p><strong>2) 02_nameMatch.csv</strong> -- This file matches the vernacular name as originally recorded with the correct common name and scientific name</p> <p>+23 image files (with ".jpg" file extension)</p> <p><strong>FILES INCLUDED IN DATASET</strong></p> <p><strong>01_anamalai-mammals-2024.csv</strong><br>This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded csv file from the EpiCollect5 application website.<br>ec5_uuid: Unique ID for each observation<br>created_at: Automatic time stamp of date and time when record was created on the mobile app<br>uploaded_at: Automatic time stamp of date and time when record was uploaded using the mobile app<br>recordedBy: Name of observer<br>title: Title assigned to each record (composite of date, species, and type of observation)<br>lat_gps: Latitude in decimal degrees N<br>long_gps: Longitude in decimal degrees E<br>accuracy_gps: Horizontal accuracy of GPS location in metres<br>UTM_Northing_gps: Latitude in UTM<br>UTM_Easting_gps: Longitude in UTM<br>UTM_Zone_gps: UTM Zone<br>eventDate: Date in ISO format (yyyy-mm-dd)<br>verbatimEventDate: Date in format originally recorded (dd/mm/yyyy)<br>eventTime: Time of observation<br>vernacularName: Species common name as initially recorded<br>individualCount: Number of individuals observed<br>occurrenceRemarks: type of observation<br>habitat: Habitat type<br>photo: Filename of photo if available (NA otherwise)<br>eventRemarks: Notes or remarks about the observation</p> <p><strong>02_nameMatch.csv</strong><br>This file matches the name as originally recorded with the correct common name and scientific name.<br>vernacularName: Common or English name as initially recorded <br>scientificName: Scientific name of the species</p> <p>+23 image files (.jpg extension)</p>
Plate 1. Crocidura nicobarica Microscopic structure a in Observation on the re-occurrence of Nicobar spiny shrew (Crocidura nicobarica Miller, 1902): A critically endangered mammal of Great Nicobar Island, India
Plate 1. Crocidura nicobarica Microscopic structure a) Fore limb, b) Hind limb, c) Tip of tail, d) Dorsal fur, e) Long black hairs in snout, f) Long white hairs in tail and g) White tooth.
Mammal occurrence records (2015-18) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India
<p>This dataset contains Mammal occurrence records (2015-18) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. It includes a few occurrence records of other chordates. Occurrence records were gathered in the field by researchers of the Nature Conservation Foundation, India, using a mobile data collection application. Suggested citation is:<br> Nature Conservation Foundation (2022). Mammal occurrence records (2015-18) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. Nature Conservation Foundation, India. Dataset, Zenodo. DOI:<br> <br> CONTACT #1<br> 1. Name: T. R. Shankar Raman<br> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br> 3. Work Phone: +91 821 2515601<br> 4. Email address: trsr@ncf-india.org<br> 5. ORCID: https://orcid.org/0000-0002-1347-3953</p> <p>CONTACT #2<br> 1. Name: Divya Mudappa<br> 2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br> 3. Work Phone: +91 821 2515601<br> 4. Email address: divya@ncf-india.org<br> 5. ORCID: https://orcid.org/0000-0001-9708-4826</p> <p>Keywords: tropical rainforest, plantations, Anamalai Hills, animal distribution, </p> <p>Geographic Coverage:<br> 1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br> 2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p>Temporal Coverage:<br> 1. Begins: 2015-01-01 (Year, Month, Day)<br> 2. Ends: 2018-10-31 (Year, Month, Day)</p> <p>Besides this 000_README.txt file, the dataset includes 326 images (photographs) and three comma-delimited text (csv) files as explained below:</p> <ol> <li>001_valparai_mammals.csv -- raw data file from the mobile app (columns are self-explanatory)</li> <li>002_valparai_mammals.csv -- raw data file of linked images from the mobile app (columns are self-explanatory)</li> <li>003_mammal_occurrence_zenodo_2015-18.csv -- curated and compiled dataset with the following columns:</li> </ol> <ul> <li>observation_id: unique id given to a record (corresponds to fulcrum_id in raw data set) observation</li> <li>latitude: latitude in decimal degrees N (WGS 84 datum)</li> <li>longitude: longitude in decimal degrees E (WGS 84 datum)</li> <li>date_: date of observation</li> <li>time: time of observation</li> <li>place: locality name</li> <li>type_of_observation: type of observation indicating whether it was sighting, sign (based on Vocalisation/call, track/pugmark, scat/dung), death, electrocution, roadkill</li> <li>notes: general notes and remarks including number of individuals where available</li> <li>photo: reference id of corresponding photograph (as in the jpg filename)</li> <li>gps_altitude: altitude in metres estimated by the phone GPS</li> <li>gps_horizontal_accuracy: horizontal accuracy in metres estimated by the phone GPS (set at 500 m in a few cases where GPS location was assigned based on locality name)</li> <li>verbatimIdentification: taxon name as noted originally</li> <li>scientificName: scientific name (or Family in a few cases)</li> <li>vernacularName: common or English name</li> <li>recordedBy: names of observers (separated by | )</li> <li>georeferenceRemarks: remarks on georeference</li> <li>occurrenceID: unique occurrence ID assigned to each taxon (recorded under an observation_id)</li> </ul>
Mammal occurrence records (2020-23) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India
<p>This dataset contains Mammal occurrence records (January 2020 - June 2023) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. It includes a few occurrence records of reptiles. Occurrence records were gathered in the field by researchers of the Nature Conservation Foundation, India, using a mobile data collection application. Suggested citation is:<br>Nature Conservation Foundation (2024). Mammal occurrence records (2020-23) in the Valparai Plateau and Anamalai Tiger Reserve, Western Ghats, India. Nature Conservation Foundation, India. Dataset, Zenodo. DOI: 10.5281/zenodo.11903722<br> <br><strong>CONTACT #1</strong><br>1. Name: T. R. Shankar Raman <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: trsr@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0002-1347-3953</p> <p><strong>CONTACT #2</strong><br>1. Name: Divya Mudappa <br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: divya@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0001-9708-4826</p> <p><strong>Keywords:</strong> tropical rainforest, plantations, Anamalai Hills, Western Ghats, animal distribution, mammals </p> <p><strong>Geographic Coverage:</strong><br>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br>2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p><strong>Temporal Coverage:</strong><br>1. Begins: 2020-01-11 (Year, Month, Day)<br>2. Ends: 2023-06-02 (Year, Month, Day)</p> <p>Besides the 000_readMe.txt file containing this information, the dataset includes 60 images (photographs), three comma-delimited text (csv) files, and one R markdown text file with R code as explained below:<br>1) 001_mammalData.csv -- This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded Excel worksheet file</p> <p>2) 002_placeLocs.csv -- This file lists names places for which the GPS location was unavailable from the mobile phone application, and was manually assigned to coordinates with 500 m accuracy</p> <p>3) 003_nameMatch.csv -- This file matches the name as originally recorded with the correct common name and scientific name</p> <p>4) 004_mammup.Rmd -- R code for processing the files to create a file for upload as an occurrence dataset on the Global Biodiversity Information Facility (GBIF.org)</p> <p>+60 image files (with ".jpg" file extension)</p> <p><strong>FILES INCLUDED IN DATASET</strong></p> <p><strong>001_mammdata.csv</strong><br>This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded Excel worksheet file <br>recordedBy: Observer who recorded/made the observation<br>username: Username of person on whose mobile phone the data were noted<br>timestamp: Automatic time stamp of date and time when app was used<br>date: Date of observation<br>time: Time of observation<br>decimalLatitude: Latitude in decimal degrees N<br>decimalLongitude: Longitude in decimal degrees E<br>GPSaltitude: Altitude in metres<br>GPSaccuracy: Horizontal accuracy of GPS location in metres<br>place: Name of locality<br>habitat: Habitat type<br>species: Species common name<br>count: Number of individuals observed<br>countType: Total (solitary or fully counted groups) or Partial (incompletely counted groups)<br>obsType: Type of observation: sighting, sign (droppings or vocalisation), death, roadkill, electrocution, other<br>notes: Notes or remarks on observation<br>imageID: Image filename if available (NA, if not available)<br>instanceID: Automatically generated unique identifier of observation</p> <p><strong>002_placeLocs.csv</strong><br>This file lists names places for which the GPS location was unavailable from the mobile phone application, and was manually assigned to coordinates with 500 m accuracy<br>place: Name of locality as recorded<br>lat: Assigned latitude in decimal degrees N<br>long: Assigned longitude in decimal degrees E<br>GPSaccuracy: Assigned as 500 m – Horizontal accuracy of GPS location in metres</p> <p><strong>003_nameMatch.csv</strong><br>This file matches the name as originally recorded with the correct common name and scientific name.<br>verbatimIdentification: Identification as originally recorded in the ‘species’ column of the mammdata.csv file<br>vernacularName: Common or engish name<br>scientificName: Scientific name</p> <p><strong>004_mammup.Rmd</strong><br>R code for processing the files to create a file for upload as an occurrence dataset on the Global Biodiversity Information Facility (GBIF.org)</p>
Fig. 1 in Blastocystis occurrence and subtype diversity in wild European terrestrial mammals - The case of Białowieza˙Primeval Forest (NE Poland)
Fig. 1. Study area with localization and number of Blastocystis-positive and Blastocystis-negative animals of particular mammalian species.
Fig. 2 in Blastocystis occurrence and subtype diversity in wild European terrestrial mammals - The case of Białowieza˙Primeval Forest (NE Poland)
Fig. 2. Bayesian inference tree based on fragment of sequences obtained from the small subunit rRNA gene (SSU rDNA) of Blastocystis isolates of the present study, performed using MrBayes 3.2.7a. The Bayesian posterior probabilities are shown adjacent to branch nodes.
Linked collectors and determiners for: Occurrence records of small and medium sized mammal species in Tana River Basin, Kenya.
Natural history specimen data linked to collectors and determiners held within, "Occurrence records of small and medium sized mammal species in Tana River Basin, Kenya". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d">https://bionomia.net/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d">https://gbif.org/dataset/2d0a21e0-0330-4c83-8be3-7234482f138d</a>. Formatted as a Frictionless Data package.
Text-fig. 6. Distribution of Oligocene continental sediments of Africa, revealing the patchy and incomplete coverage of the occurrences. The Tunisian sedimentary outcrops represent an important resource for the north-western part of the continent. in Arsinoitherium (Embrithopoda) And Other Large Mammals And Plants From The Oligocene Of Tunisia
Text-fig. 6. Distribution of Oligocene continental sediments of Africa, revealing the patchy and incomplete coverage of the occurrences. The Tunisian sedimentary outcrops represent an important resource for the north-western part of the continent.
Literature review of occurrence and transmission dynamics of SARS-CoV2 in mammal animals
<p>A literature review has been conducted, focusing on susceptibility of wild and domestic animal species reported under field and laboratory conditions, considering different diagnostic tests (e.g., virus isolation, RNA and antibody detection), infection dynamic, pathogenesis, immunity and further transmission of the virus. Review protocol and data extraction tables are available.</p> <p>The following review questions were considered:</p> <ul> <li>Which mammal species have been reported positive to SARS CoV 2 in the field (either at RNA, isolated virus, antibodies), and their geographical distribution?</li> </ul> <ul> <li>Which wild and domestic mammal species are susceptible to SARS CoV 2 in laboratory conditions</li> <li><em>Dynamic of infection and pathogenesis</em>: <ul> <li>What are confirmed infection routes for these species?</li> <li>What is the length of the incubation period in these species</li> <li>What are the clinical signs, if any, their severity, duration, etc.</li> <li>Which species are able to shed the virus (even in absence of clinical signs)</li> <li>Do these species develop protective immunity</li> </ul> </li> <li>Which of these species can further transmit the disease to same/other species ?</li> <li>What are the genetic virus variants in each species where it is isolated?</li> <li>In which animals vaccines against SARS CoV 2 have been tested, and what are the results in terms of immunogenicity, protection to challenge, or safety?</li> </ul> <ul> <li>Which diagnostic tests are used in animals to detect SARS CoV <ul> <li>Type of test</li> <li>Test performance (Se, Sp)</li> <li>Sample matrix used</li> </ul> </li> </ul>
Data from: Environmental variables influence patterns of mammal co-occurrence following introduced predator control
<p>Co-occurring species often overlap in resource use and can interact in complex ways. However, shifts in environmental conditions or resource availability can lead to changes in patterns of species co-occurrence, which may be exacerbated by global escalation of human disturbances to ecosystems, including conservation directed alterations. We investigated the relative abundance and co-occurrence of two naturally sympatric mammal species following two forms of environmental disturbance: wildfire and introduced predator control. Using 14 years of abundance data from repeat surveys at long-term monitoring sites in south-eastern Australia, we examined the association between a marsupial, the common brushtail possum Trichosurus vulpecula, and a co-occurring native rodent, the bush rat <em>Rattus fuscipes</em>. We asked: Is the increase in abundance of common brushtail possums following control of an introduced predator associated with a decline in abundance of the bush rats?</p> <p>Using Bayesian regression models, we tested hypotheses that the abundance of each species would vary with changes in environmental and disturbance variables, and that the negative association between bush rats and common brushtail possums was stronger than the association between bush rats and disturbance. Our analyses revealed that bush rat abundance varied greatly in relation to environmental and disturbance variables, whereas common brushtail possums showed relatively limited variation in response to the same variables. There was a negative association between common brushtail possums and bush rats, but this association was weaker than the initial decline and subsequent recovery of bush rats in response to wildfires.</p> <p>Using co-occurrence analysis, we can readily infer negative relationships in abundance between co-occurring species, but to understand the impacts of such associations, and plan appropriate conservation measures, we require more information on interactions between the species and environmental variables. Co-occurrence can be a powerful and novel method to diagnose threats to communities and understand changes in ecosystem dynamics.</p>
Data from: Environmental variables influence patterns of mammal co-occurrence following introduced predator control
Open the record for dataset details and reuse information.
Different mammals, same structure: Co-occurrence structure across the Plio-Pleistocene transition
Open the record for dataset details and reuse information.
Vertebrate-habitat relationships: Logistic regression models predict probability of occurrence of bird and small mammal species in western Oregon
Logistic regression models predicting probability of occurrence of bird and of small-mammal species were produced using animal-habitat data sets from throughout western Oregon (Garman and Cole 1999 - Vertebrate Habitat Relationships Data Bank (VHRDB), Report to Coastal Landscape Analysis and Modeling Study). Regression coefficients, variables, and metrics related to model predictions are provided here under Entity 1, and in VHRDB as VERTLOGR.
Dataset for "Cascading effects of mammal host community composition on tick vector occurrence at the urban human-wildlife interface"
<p>Dataset for the following paper:</p> <p><strong>Cascading effects of mammal host community composition on tick vector occurrence at the urban human-wildlife interface</strong></p> <p>Jonathan Bastard *, Nichar Gregory *, Maria Pilar Fernandez, Michaela Mincone, Olivia Card, Sara Kross, Maria Diuk-Wasser</p> <p>* These authors contributed equally.</p>
Plate 2 in Observation on the re-occurrence of Nicobar spiny shrew (Crocidura nicobarica Miller, 1902): A critically endangered mammal of Great Nicobar Island, India
Plate 2. The skull and dentition of Crocidura nicobarica in Dorsal, ventral, microscopic view.
Figure 1 in Observation on the re-occurrence of Nicobar spiny shrew (Crocidura nicobarica Miller, 1902): A critically endangered mammal of Great Nicobar Island, India
Figure 1. Field photograph of Crocidura nicobarica Miller, 1902.
Combining local ecological knowledge with camera traps to assess the link between African mammal life history traits and their occurrence in anthropogenic landscapes
<p>Understanding what influences species and trait composition is critical for predicting changes in communities driven by landscape transformation. </p> <p>We explored how life history traits are associated with the persistence of mammal species in human-dominated habitats within the Garden Route Biosphere Reserve, South Africa. We combined data from a camera trap and a local ecological knowledge-based survey in an integrated occupancy model to analyze species occurrence along a gradient of anthropogenic landscape transformation. </p> <p>Results confirmed that mammal occurrence in human-modified habitats was related to specific life history traits. Species with more specialist diets, as well as larger body mass species were more likely to stay in protected areas. Species with slow reproductive strategies occupied more natural areas. </p> <p>Our study also showed that combining different monitoring methods enabled us to increase spatial coverage and mammal sighting numbers. This approach fostered research participation by various stakeholders, an important step for co-designing wildlife-friendly anthropogenic spaces. </p> <p><strong>Synthesis and applications: </strong>Integrating data from a standard ecological protocol and structured participatory citizen knowledge allowed us to identify the species functional traits associated with mammal species occurrence in anthropogenic landscapes at a local scale. These results advocate for wisely combining methods, and will guide conservation orientated land-use planning towards the protection of natural habitats in the Garden Route Biosphere Reserve. This methodological approach will enable managers and conservationists to use data obtain from diverse protocols. This should catalyze the involvement of citizens in biodiversity monitoring and conservation.</p>
Mammal occurrence records (2022-24) from Sakleshpura, central Western Ghats, India
<p><strong>Mammal occurrence records (2022-24) from Sakleshpura, central Western Ghats, India</strong></p> <p>This dataset contains mammal occurrence records from 2022 to 2024 in the Sakleshpura region of central Western Ghats, India. It includes a few occurrence records of other chordates. Occurrence records were gathered in the field by researchers of the Nature Conservation Foundation, India, using a mobile data collection application. Suggested citation is:<br>Nature Conservation Foundation (2024). Mammal occurrence records (2022-24) from Sakleshpura, central Western Ghats, India. Nature Conservation Foundation, India. Dataset</p> <p><strong>Keywords:</strong> tropical rainforest, plantations, Sakleshpura, animal distribution, Western Ghats</p> <p><strong>CONTACT #1</strong><br>1. Name: Anand M Osuri<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: aosuri@ncf-india.org<br>5. ORCID: https://orcid.org/0000-0001-9909-5633</p> <p><strong>CONTACT #2</strong><br>1. Name: Vijay Karthick<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: vijayk@ncf-india.org <br>5. ORCID: https://orcid.org/0000-0001-6023-3955</p> <p><strong>CONTACT #3</strong><br>1. Name: Vijay Kumar<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: vijaykumar@ncf-india.org <br>5. ORCID: https://orcid.org/0009-0000-4149-0083</p> <p><br><strong>Geographic Coverage:</strong><br>1. Location/Study Area: Sakleshpura, Karnataka, India<br>2. GPS coordinates: Kadamane Village (12.924647, 75.654650)</p> <p><strong>Temporal Coverage:</strong><br>1. Begins: 2022-05-16 (Year, Month, Day)<br>2. Ends: 2024-05-22 (Year, Month, Day)</p> <p>Besides the 000_readMe.txt file containing this information and the 14 images associated with individual observations, the dataset includes three comma-delimited text (csv) files, and one R code file as explained below:<br>1) <strong>001_mammalData.csv</strong> -- This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded Excel worksheet file</p> <p>2) <strong>002_placeLocs.csv</strong> -- This file lists names places for which the GPS location was unavailable from the mobile phone application, and was manually assigned to coordinates with 500 or 1000m accuracy</p> <p>3) <strong>003_nameMatch.csv</strong> -- This file matches the name as originally recorded with the correct common name and scientific name</p> <p>4) <strong>004_GBIF_upload_code.R </strong>-- R code for processing the files to create a file for upload as an occurrence dataset on the Global Biodiversity Information Facility (GBIF.org)</p> <p>5) <strong>005_download_images_from_googledrive.R</strong> - R code to extract image IDs and download images from googledrive</p> <p>6) <strong>006_kadamane_mammal_occurrence.xls</strong>x - An excel file that contains the raw data and used in the codes above</p> <p>FILES INCLUDED IN DATASET</p> <p><strong>001_mammaldata.csv</strong><br>This file has the main mammal occurrence data with relevant and renamed columns derived from the original downloaded Excel worksheet file </p> <p>observers: Observers who made the observation<br>timestamp: Automatic time stamp of date and time when app was used<br>date: Date of observation<br>time: Time of observation<br>decimalLatitude: Latitude in decimal degrees N<br>decimalLongitude: Longitude in decimal degrees E<br>GPSaltitude: Altitude in metres<br>GPSaccuracy: Horizontal accuracy of GPS location in metres<br>place: Name of locality<br>habitat: Habitat type<br>taxa: mammal or reptile/amphibian<br>species: Species common name<br>count: Number of individuals observed<br>countType: Total (solitary or fully counted groups) or Partial (incompletely counted groups)<br>obsType: Type of observation: sighting, sign (droppings or vocalisation), death, roadkill, electrocution, other<br>notes: Notes or remarks on observation<br>imageID: Link to the google drive photo, if photo is available<br>instanceID: Automatically generated unique identifier of observation</p> <p><strong>002_placeLocs.csv</strong><br>This file lists names places for which the GPS location was unavailable from the mobile phone application, and was manually assigned to coordinates with 500 m accuracy</p> <p>place: Name of locality as recorded<br>lat: Assigned latitude in decimal degrees N<br>long: Assigned longitude in decimal degrees E<br>GPSaccuracy: Assigned as 500 or 1000m – Horizontal accuracy of GPS location in metres</p> <p><strong>003_nameMatch.csv</strong><br>This file matches the name as originally recorded with the correct common name and scientific name.</p> <p>verbatimIdentification: Identification as originally recorded in the ‘species’ column of the mammaldata.csv file<br>vernacularName: Common or english name<br>scientificName: Scientific name</p> <p><strong>004_GBIF_upload_code.R</strong><br>R code for processing the files to create a file for upload as an occurrence dataset on the Global Biodiversity Information Facility (GBIF.org)</p> <p><strong>005_download_images_from_googledrive.R</strong><br>R code that extracts imageIDs from the 001_mammalData.csv file and downloads them automatically to a preferred directory</p> <p><strong>006_kadamane_mammal_occurrence.xlsx</strong><br>An excel file that contains the raw data and used in the codes above</p>
Combining local ecological knowledge with camera traps to assess the link between African mammal life history traits and their occurrence in anthropogenic landscapes
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.