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277 results for “occurrence records”
Occurrence Record Dataset from "Annotated checklist of the bees of Bonaire, with a focus on host plants"
<p>This is the occurrence dataset created for the publication "Annotated checklist of the bees of Bonaire, with a focus on host plants" (<a href="https://natuurtijdschriften.nl/pub/1026875" target="_blank" rel="noopener">https://natuurtijdschriften.nl/pub/1026875</a>).</p> <p>Observation and specimen data were assembled for this dataset, with the majority of records obtained during the Bonaire Estafette Expeditie (BEE). All citizen science records from Observation.org and iNaturalist.org up to December 2023 have been critically reviewed.<br>A project was created (<a href="https://www.inaturalist.org/projects/flower-visitors-and-pollinators-of-the-caribbean" target="_blank" rel="noopener">Flower visitors and pollinators of the Caribbean</a>) to improve standardized data collecting of plant-pollinator interactions and on <a href="https://observation.org/">observation.org</a> the standardized fields for interactions were used.<br>Records from passive trapping methods are not included. All bees were either observed or collected by hand or insect net. The majority of specimens will be accessible in the collection of Naturalis Biodiversity Center (RMNH), Leiden (the Netherlands). A synoptic collection is retained at the University of Tartu Zoological Collections in Tartu, Estonia (TUZ).</p> <p>The occurrence dataset (Version 1.4 and later) is:</p> <ul> <li>conform Darwin Core (DwC): <a href="https://dwc.tdwg.org/terms/">https://dwc.tdwg.org/terms</a></li> <li>in the data format CSV (tab delimited values) and UTF-8 encoded</li> </ul> <p> </p> <p><strong>DwC terms (Column labels) used in the dataset with their description:</strong></p> <table> <tbody> <tr> <td><strong>Column label</strong></td> <td><strong>Column description</strong></td> </tr> <tr> <td>occurrenceID</td> <td>Unique identifier or URI (GUID) for each record, mainly unique URLs generated by the web-based data holder.</td> </tr> <tr> <td>catalogNumber</td> <td>Unique code derived from URI in occurrenceID. Each specimen bears a label with this identifier and multimedia are tagged with this identifier.</td> </tr> <tr> <td>recordNumber</td> <td>Sample field ID used to manage data of preserved specimen occurrence records.</td> </tr> <tr> <td>otherCatalogNumbers</td> <td>Other unique identifiers used on specimen labels, but not derived from an URI.</td> </tr> <tr> <td>scientificName</td> <td>The scientific name of the lowest taxonomic rank to which the individual(s) was identified.</td> </tr> <tr> <td>scientificNameAuthorship</td> <td>The author name and year of publication in accordance with ICZN rules.</td> </tr> <tr> <td>verbatimIdentification</td> <td>The original identification, including qualifiers if needed.</td> </tr> <tr> <td>individualCount</td> <td>The number of individuals present at the time of the occurrence.</td> </tr> <tr> <td>sex</td> <td>The sex of the individual(s). The values female, male or unknown are used, if a mixed group is observed multiple values are listed.</td> </tr> <tr> <td>lifeStage</td> <td>The life stage of the individual(s).</td> </tr> <tr> <td>basisOfRecord</td> <td>The specific nature of the data record at the time of the identification (e.g. PreservedSpecimen).</td> </tr> <tr> <td>identifiedBy</td> <td>The name of the person who made the identification in the field or based on collected evidence (e.g. specimen or photo).</td> </tr> <tr> <td>identificationQualifier</td> <td>In case the identification could be given only to a species group 'cf.' is recorded.</td> </tr> <tr> <td>dateIdentified</td> <td>The year when the identification was made.</td> </tr> <tr> <td>previousIdentifications</td> <td>The scientific name originally given to the observed or collected individual(s).</td> </tr> <tr> <td>order</td> <td>The name of the order (e.g. Hymenoptera).</td> </tr> <tr> <td>family</td> <td>The name of the family (e.g. Apidae).</td> </tr> <tr> <td>genus</td> <td>The name of the genus (e.g. Apis).</td> </tr> <tr> <td>subgenus</td> <td>The name of the subgenus (e.g. Apis).</td> </tr> <tr> <td>specificEpithet</td> <td>The name of the species, epithet as given in dwc:scientificName.</td> </tr> <tr> <td>taxonRank</td> <td>The taxonomic rank of the most specific name in dwc:scientificName.</td> </tr> <tr> <td>eventDate</td> <td>The date-time when the event was observed and recorded. The event date uses the ISO 8601-1:2019 standard, with the following formatting being used: format YYYY-MM-DD, or YYYY if only the year is known. If time of capture is known, then format is YYYY-MM-DDTHH:MM, with HH:MM the local time.</td> </tr> <tr> <td>year</td> <td>The year in which the event was observed and recorded.</td> </tr> <tr> <td>month</td> <td>The month in which the event was observed and recorded.</td> </tr> <tr> <td>day</td> <td>The day in which the event was observed and recorded.</td> </tr> <tr> <td>eventTime</td> <td>The time or interval during which the event occurred.</td> </tr> <tr> <td>samplingProtocol</td> <td>The name or description of the collecting or recording method used.</td> </tr> <tr> <td>behavior</td> <td>A description of the behavior shown by the individual(s) recorded in this occurrence.</td> </tr> <tr> <td>decimalLatitude</td> <td>The geographic latitude in decimal degrees recorded by a GPS device (WGS84) when observing and recording the occurrence.</td> </tr> <tr> <td>decimalLongitude</td> <td>The geographic longitude in decimal degrees recorded by a GPS device (WGS84) when observing and recording the occurrence.</td> </tr> <tr> <td>geodeticDatum</td> <td>The ellipsoid, geodetic datum, or spatial reference system (SRS) upon which the geographic coordinates given in dwc:decimalLatitude and dwc:decimalLongitude is based.</td> </tr> <tr> <td>verbatimLocality</td> <td>The original textual description of the place.</td> </tr> <tr> <td>island</td> <td>The name of the island.</td> </tr> <tr> <td>countryCode</td> <td>The standard ISO 3166-1 alpha-2 country code for the country.</td> </tr> <tr> <td>coordinateUncertaintyInMeters</td> <td> <p>The horizontal distance (in meters) from the given dwc:decimalLatitude and dwc:decimalLongitude describing the smallest circle containing the actual location, usually the EPE (Estimated Position Error) from the GPS device. The EPE is here measured as the horizontal position error in meters.</p> </td> </tr> <tr> <td>recordedBy</td> <td>A person, group, or organization observing and recording the occurrence.</td> </tr> <tr> <td>associatedTaxa</td> <td>The type of association and the scientific name of the host taxon is recorded that is associated/has relationship with the taxon in dwc:scientificName. The association/relationship is recorded using the format as in the following example: "floral host":"Lantana sp."</td> </tr> <tr> <td>occurrenceRemarks</td> <td>Comments or notes about the dwc:Occurrence.</td> </tr> <tr> <td>associatedSequences</td> <td>A list (concatenated and separated) of identifiers (publication, global unique identifier, URI) of genetic sequence information.</td> </tr> <tr> <td>typeStatus</td> <td>A list (concatenated and separated) of nomenclatural types (type status, typified scientific name, publication) applied to the subject.</td> </tr> <tr> <td>collectionCode</td> <td>The name, acronym, coden, or initialism identifying the collection or data set from which the record was derived.</td> </tr> <tr> <td>identificationRemarks</td> <td>Comments or notes about the identification.</td> </tr> <tr> <td>identificationReferences</td> <td>A reference or list of references (publication, global unique identifier, URI) used for the identification.</td> </tr> <tr> <td>nameAccordingTo</td> <td>A reference to the checklist or publication that was followed to record the name in dwc:scientificName.</td> </tr> <tr> <td>samplingEffort</td> <td>The amount of effort, expressed in minutes or hours, to obtain and record the occurrences.</td> </tr> <tr> <td>occurrenceStatus</td> <td>A statement about the presence or absence of a taxon during the time of an event.</td> </tr> <tr> <td>disposition</td> <td>The current state of a specimen with respect to a collection.</td> </tr> <tr> <td>language</td> <td>The language of the record using ISO 639-1 codes, e.g. en</td> </tr> </tbody> </table>
Occurrences records of Herichthys labridens (Cichliformes: Cichlidae), with associated habitat information, in the Media Luna spring, San Luis Potosí, Mexico
<h2><strong>Introduction</strong></h2> <blockquote> <p>Occurrence records of the endemic cichlid <em>Herichthys labridens</em>, by adult and juvenile life stages, during three summer events (years of 1999, 2009, and 2019), in the Media Luna spring, San Luis Potosí Mexico. </p> </blockquote> <h2><strong>Material and Methods </strong></h2> <blockquote> <p>The occurrence records, ordered by adult and juvenile life stages, were obtained from two sources. For the summer of 1999, data were downloaded from the literature (Palacio-Núñez et al., 2010). For subsequent events, we recorded new data from 66 underwater transects distributed among 14 sectors (S1 to S14) in the Media Luna spring. We followed the method of Palacio-Núñez (2007), which maintained the transect location and sector boundaries of the summer of 1999 (Fig. 1a). The 20 m² transects were placed transversely to the current, from the edge to the central part of the canal (Fig. 1b). This sampling design was selected to meet two basic assumptions for studies of spatial distribution and habitat suitability: (1) the observations within the area are true and, (2) these observations delimit the initial position of the recorded individuals (Buckland & Elston, 1993). The analysis of the spatial information of the sectors, the underwater transects, and the delimitation of the water surface was performed using the QGIS® software version 3.4.8 (Menke, 2019).</p> <p> </p> <p><strong>Figure 1</strong>. <a href="https://zenodo.org/api/records/14231104/draft/files/Sector%20boundary_Transect%20location%20and%20sampling_Media%20Luna%20spring.jpeg/content" target="_blank" rel="noopener noreferrer">Sector boundary_Transect location and sampling_Media Luna spring.jpeg</a>. (a) Location of the transects in the Media Luna spring, Mexico. (b) Design scheme of the sampling transect; a CPVC pipe was used to give width to the edges of the transect and a nylon rope was attached to each side of the pipes to demarcate the length of the transect. Floating rubber buoys were added to the transects (at the edge towards the center of the canal) to prevent them from sinking into the sediment and to locate them among the vegetation. Transect scheme: Jorge Palacio-Núñez.</p> <p><br>In the summer events where we worked in field, we recorded the spatial location (i.e., GPS coordinates) of each individual and its life stage by direct observation with snorkel equipment and using a Garmin etrex device. The recorded information included the data of water depth and related underwater coverage. It is important to mention that, to prevent a repeat observation of the same organism or to ommit any individual, the transect was swaped slowly and in one direction only (i.e., from the center of the canal to the shore). We also used underwater cameras to validate the information. In adittion, the characterization of <em>H. labridens</em> individuals by life stage was performed by approximate size. For this purpose, previous studies on the life history and biology of the species were reviewed (Miller et al., 2005; De La Maza-Benignos & Lozano-Vilano, 2013). It is worth mentioning that, during fieldwork, we avoided manipulation, damage, or unnecessary capture of the fish (e.g., Prchalová et al., 2009).</p> <p><br>The databases by life stage were organized for each summer event, where, each observation record was included along with the associated habitat conditions. Subsequently, we depurated each database to remove atypical spatial data, data without information, incomplete data, or data with duplicate coordinates (García-Roselló et al., 2014). Then, we performed spatial filtering of the remaining records to validate those that were within the study area, and to prevent that two or more points were within 0.1 m of each other. These steps of our analysis were performed using the software Qgis® version 3.28.4 and Rstudio® (Rstudio team, 2020). Subsequently, with the data set that included fish records, water depth, and underwater coverage variables, we performed a final environmental filter to rule out atypical records. This exploration was performed in Rstudio ® using the outliers function, starting from the lowest and highest quantiles.</p> </blockquote> <h2><strong>Results</strong></h2> <blockquote> <p>The final filtered databases were organized by life stage and summer event:</p> <p><strong>Adult: </strong></p> <table> <tbody> <tr> <td>Summer event</td> <td>Database</td> </tr> <tr> <td>1999</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Adult_1999_Palacio-N%C3%BA%C3%B1ez%20et%20al.,%202010.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Adult_1999_Palacio-Núñez et al., 2010.csv</a></td> </tr> <tr> <td>2009</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Adult_2009_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Adult_2009_Field work.csv</a></td> </tr> <tr> <td>2019</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Adult_2019_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Adult_2019_Field work.csv</a></td> </tr> </tbody> </table> <p><strong> Juvenile:</strong></p> <table> <tbody> <tr> <td>Summer event</td> <td>Database</td> </tr> <tr> <td>1999</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Juvenile_1999_Palacio-N%C3%BA%C3%B1ez%20et%20al.,%202010.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Juvenile_1999_Palacio-Núñez et al., 2010.csv</a></td> </tr> <tr> <td>2009</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Juvenile_2009_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Juvenile_2009_Field work.csv</a></td> </tr> <tr> <td>2019</td> <td><a href="https://zenodo.org/api/records/14231104/draft/files/Occurrences_records_H_labridens_Juvenile_2019_Field%20work.csv/content" target="_blank" rel="noopener noreferrer">Occurrences_records_H_labridens_Juvenile_2019_Field work.csv</a></td> </tr> </tbody> </table> </blockquote> <p> </p> <blockquote> <p>These occurrence records for <em>H. labridens </em>are ready to be used in ecological niche modeling and spatial distribution studies. Also, these records can be used for other ecological and spatial studies, because each record (i.e., individual) included geoespatial coordinates, sector, location, and transect number. Also, we recorded information about the conditions of underwater coverage and water depth, which were asociated to each ocurrence record.</p> <p>For more information about several R codes where the previous databases can be used, visit the following repository URL: <a href="https://doi.org/10.5281/zenodo.7603557">https://doi.org/10.5281/zenodo.7603557</a>.</p> <p>Also, to download the UC and WDp variables to run the spatial and ecological modeling, visit the following repository URL: <a href="https://doi.org/10.5281/zenodo.7603890">https://doi.org/10.5281/zenodo.7603890</a>.</p> </blockquote>
Records of Sargassum horneri occurrence in the eastern Pacific
Presented here are records of the occurrence of Sargassum horneri in California, USA, and Baja California, Mexico, since 2003, the year it was first discovered in the eastern Pacific. These data and their sources were published as supplementary tables in: Marks LM, Salinas-Ruiz P, Reed DC, Holbrook SJ, Culver CS, Engle JM, Kushner DJ, Caselle JE, Freiwald J, Williams JP, Smith JR, Aguilar-Rosas LE, Kaplanis NJ (2015) Range expansion of a non-native, invasive, macroalga Sargassum horneri (Turner) C. Agardh, 1820 in the eastern Pacific. BioInvasions Records 4, DOI: 10.3391/bir.2015.4.4.02
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>
Global Biodiversity Information Facility (GBIF): an exhaustive list of gbif record ids, dataset keys, and their associated Occurrence IDs, Institution Code, Collection Codes and Catalog Numbers. hash://sha256/ea88f03a7bfd1ba853fdbea3203d54ab81ac3cdc8e8da7c96bbbba9c4b05d933 hash://md5/c49fe34785354847b37ea4509261e130
<p>The Global Biodiversity Information Facility (GBIF) indexes thousands of biodiversity datasets from Natural History Collections, citizen science initiatives (e.g., iNaturalist, eBird), and other sources. As part of the index process, GBIF associates at least two identifiers with indexed records: a record id (aka gbifID) and a dataset id (aka dataset key). These ids are central to do lookup, reference data, and package interpreted data products.</p> <p>This publication contains an exhaustive list of GBIF IDs and ids associated by their data providers as derived from:</p> <p>GBIF.org (01 March 2023) GBIF Occurrence Download https://doi.org/10.15468/dl.pk3trq</p> <p>The resource (size: ~260GB) provided by GBIF had content id hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97 and was used to generate the resource included in this publication using</p> <pre><code class="language-bash">preston cat 'zip:hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97!/0015281-230224095556074.csv'\ | cut -f 1,2,3,37,38,39\ | gzip\ > gbifid.tsv.gz </code></pre> <p>with the content id of gbifid.tsv.gz (size: ~35GB) being hash://sha256/a339e32e10edaad585f61f2ded06cbb23e0618c65a6360db18d7d729054940a8 .</p> <p>the first 10 lines of gbifid.tsv.gz as extracted via</p> <pre><code>preston cat --remote https://zenodo.org/record/7789866/files,https://linker.bio hash://sha256/a339e32e10edaad585f61f2ded06cbb23e0618c65a6360db18d7d729054940a8\ | gunzip\ | head</code></pre> <p>are:</p> <pre><code>gbifID datasetKey occurrenceID institutionCode collectionCode catalogNumber 2997162320 c71c8000-9fc7-422c-804a-ce6abe751771 3399442 CEPEC CEPEC CEPEC00109669 2997162309 c71c8000-9fc7-422c-804a-ce6abe751771 2733085 CEPEC CEPEC CEPEC00000818 2997162317 c71c8000-9fc7-422c-804a-ce6abe751771 2733086 CEPEC CEPEC CEPEC00000888 2997162313 c71c8000-9fc7-422c-804a-ce6abe751771 3399443 CEPEC CEPEC CEPEC00109744 2997162306 c71c8000-9fc7-422c-804a-ce6abe751771 2733087 CEPEC CEPEC CEPEC00000889 2997162316 c71c8000-9fc7-422c-804a-ce6abe751771 3399440 CEPEC CEPEC CEPEC00109605 2997162324 c71c8000-9fc7-422c-804a-ce6abe751771 2733088 CEPEC CEPEC CEPEC00000890 2997162308 c71c8000-9fc7-422c-804a-ce6abe751771 3399441 CEPEC CEPEC CEPEC00109615 2997162303 c71c8000-9fc7-422c-804a-ce6abe751771 2733089 CEPEC CEPEC CEPEC00000891</code></pre> <p>Note that at time of writing, the html resource associated with the occurrence id 2997162320, and data set key c71c8000-9fc7-422c-804a-ce6abe751771 (extracted from of the first data row example above) are available via:</p> <p>https://gbif.org/occurrence/2997162320</p> <p>and</p> <p>https://gbif.org/dataset/c71c8000-9fc7-422c-804a-ce6abe751771</p> <p>respectively.</p> <p>This resource was initially created to help integrate with Bionomia (https://bionomia.net) to help associate people identifiers provided by bionomia to their original records via their GBIF ids. Bionomia re-uses GBIF records ids as a way to define links between records and the people (e.g., curators, collectors, identifiers) that worked on them. </p> <p>In other words, this resource provides a versioned translation table from the GBIF data universe (as defined by GBIF record ids, and dataset keys) to the data collections that exist (and evolve) independent of it. </p> <p>Note that the resource identified by hash://sha256/c8bac8acb28c8524c53589b3a40e322dbbbdadf5689fef2e20266fbf6ddf6b97 was not included in this publication it was too big (260GB) to fit. You may be able to retrieve the resource from its original location at https://api.gbif.org/v1/occurrence/download/request/0015281-230224095556074.zip .</p>
Occurrence records used to develop a climatic suitability model for emerald ash borer in DDRP
<p>Presence records used to calibrate and validate a climatic suitability model for emerald ash borer in the DDRP platform (Degree-Days, Risk, and Phenological event mapping) (Barker et al. 2023). The first sheet ("Records") of the Excel file provides the range (native or invaded), continent, country, state or province, locality, latitude, and longitude of origin for each record. The "Coords_est" column indicates whether the coordinates were estimated from city- or county-level information (1 = yes, 0 = no). The year in which the record was collected is provided if known. The second sheet of the Excel file ("References") provides a list of references for each record source.</p>
Occurrence Record Dataset from "Depth Matters for Marine Biodiversity"
<p>This is the final occurrence record dataset produced for the manuscript "Depth Matters for Marine Biodiversity". Detailed methods for the creation of the dataset, below, have been excerpted from Appendix I: Extended Methods. Detailed citations for the occurrence datasets from which these data were derived can also be foud in Appedix I of the manuscript.</p> <p><span>We first assembled a list of all recognized species of fishes from the orders Scombiformes</span><span> (Betancur-R et al., 2017)</span><span>, Gadiformes, and Beloniformes by accessing FishBase</span><span> (Boettiger et al., 2012; Froese & Pauly, 2017)</span><span> and the Ocean Biodiversity Information System (OBIS; </span><span>OBIS, 2022; Provoost & Bosch, 2019)</span><span> through queries in R</span><span> (R Core Team, 2021)</span><span>. Species were considered Atlantic if their FishBase distribution or occurrence records on OBIS included any area within the Atlantic or Mediterranean major fishing regions as defined by the Food and Agriculture Organization of the United Nations (FAO Regions 21, 27, 31, 34, 37, 41, 47, and 48;</span><span> FAO, 2020)</span><span>. The database query script can be found on the project code repository (</span><a href="https://github.com/hannahlowens/3DFishRichness/blob/main/1_OccurrenceSearch.R"><span>https://github.com/hannahlowens/3DFishRichness/blob/main/1_OccurrenceSearch.R</span></a><span>). We then curated the list of names to resolve discrepancies in taxonomy and known distributions through comparison with the Eschmeyer Catalog of Fishes</span><span> (Eschmeyer & Fricke, 2015)</span><span> , accessed in September of 2020, as our ultimate taxonomic authority. The resulting list of species was then mapped onto the Global Biodiversity Information Facility’s backbone taxonomy</span><span> (Chamberlain et al., 2021; GBIF.org, 2020a)</span><span> to ensure taxonomic concurrence across databases (Supplementary Table 1). The final taxonomic list was used to download occurrence records from OBIS</span><span> (OBIS, 2022)</span><span> and GBIF</span><span> (GBIF.org, 2020b)</span><span> in R through <em>robis</em></span><span> (Provoost & Bosch, 2019)</span><span> and <em>occCite</em></span><span> (Owens et al., 2021)</span><span>. </span></p> <p><span><span> </span>For each species, duplicate points were removed from two- and three-dimensional species occurrence datasets separately, and inaccurate depth records were removed from 3D datasets (all records with and without depth information were retained for the 2D dataset). Depth records were based on the “depth” field in both the GBIF and OBIS datasets, which define the field as “depth below the surface in meters”. We chose this value over incorporating information from “minimumDepthInMeters” and “maximumDepthInMeters” because more records contained information from the “depth” field than either of the two other fields (although when these fields were both supplied, “depth” appears to have been often, but not always, derived by calculated the mean between minimum and maximum depth). We also initially included the “depthAccuracy” field from both datasets but did not ultimately use this field as it was not complete enough to be useful. Instead, we determined depth inaccuracy based on extreme statistical outliers (values greater than 2 or less than -2 when occurrence depths were centered and scaled), depths that exceeded bathymetry at occurrence coordinates, and occurrence depths far outside known depth ranges obtained from FishBase, Eschmeyer’s Catalog of Fishes, and/or congeneric depth ranges in the dataset. Once the resulting data were mapped and curated to remove records with putatively spurious coordinates, under-sampled regions and species were augmented with data from publicly available digital museum collection databases not served through OBIS or GBIF, as well as a literature search. Finally, for datasets with more than 20 points remaining after data curation, occurrence data were downsampled to the resolution of the environmental data; that is, to 1 point per 1 degree grid cell in the 2D dataset, and to one point per depth slice per 1 degree grid cell in the 3D dataset. </span></p> <p> </p> <p>References:</p> <p>Betancur-R, R., Wiley, E. O., Arratia, G., Acero, A., Bailly, N., Miya, M., Lecointre, G., & Ortí, G. (2017). Phylogenetic classification of bony fishes. <em>BMC Evolutionary Biology</em>, <em>17</em>(1), 162. <a href="https://doi.org/10.1186/s12862-017-0958-3">https://doi.org/10.1186/s12862-017-0958-3</a></p> <p>Boettiger, C., Lang, D. T., & Wainwright, P. C. (2012). rfishbase: exploring, manipulating and visualizing FishBase data from R. <em>Journal of Fish Biology</em>, <em>81</em>(6), 2030–2039. <a href="https://doi.org/10.1111/j.1095-8649.2012.03464.x">https://doi.org/10.1111/j.1095-8649.2012.03464.x</a></p> <p>Chamberlain, S., Barve, V., McGlinn, D., Oldoni, D., Desmet, P., Geffert, L., & Ram, K. (2021). <em>rgbif: Interface to the Global Biodiversity Information Facility API</em>. <a href="https://CRAN.R-project.org/package=rgbif">https://CRAN.R-project.org/package=rgbif</a></p> <p>Eschmeyer, & Fricke, W. N. &. (2015). Taxonomic checklist of fish species listed in the CITES Appendices and EC Regulation 338/97 (Elasmobranchii, Actinopteri, Coelacanthi, and Dipneusti, except the genus Hippocampus). <em>Catalog of Fishes, Electronic Version</em>. Accessed September, 2020. <a href="https://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes">https://www.calacademy.org/scientists/projects/eschmeyers-catalog-of-fishes</a></p> <p>FAO. (2020). <em>FAO Major Fishing Areas</em>. United Nations Fisheries and Aquaculture Division. <a href="https://www.fao.org/fishery/en/collection/area">https://www.fao.org/fishery/en/collection/area</a></p> <p>Froese, R., & Pauly, D. (2017). <em>FishBase</em>. Accessed September, 2022. www.fishbase.org</p> <p>GBIF.org. (2020a). <em>GBIF Backbone Taxonomy</em>. Accessed September, 2020. GBIF.org</p> <p>GBIF.org. (2020b). <em>GBIF Occurrence Download</em>. Accessed November, 2020. <a href="https://doi.org/10.15468">https://doi.org/10.15468</a></p> <p>OBIS. (2020). <em>Ocean Biodiversity Information System. Intergovernmental Oceanographic Commission of UNESCO</em>. Accessed November, 2020. www.obis.org</p> <p>Owens, H. L., Merow, C., Maitner, B. S., Kass, J. M., Barve, V., & Guralnick, R. P. (2021). occCite: Tools for querying and managing large biodiversity occurrence datasets. <em>Ecography</em>, <em>44</em>(8), 1228–1235. <a href="https://doi.org/10.1111/ecog.05618">https://doi.org/10.1111/ecog.05618</a></p> <p>Provoost, P., & Bosch, S. (2019). <em>robis: R Client to access data from the OBIS API</em>. <a href="https://cran.r-project.org/package=robis">https://cran.r-project.org/package=robis</a></p> <p>R Core Team. (2021). <em>R: A Language and Environment for Statistical Computing</em>. <a href="https://www.R-project.org/">https://www.R-project.org/</a></p>
Species occurrence records of special area of conservation Montesinho/Nogueira.
<p>The dataset contains biodiversity data for significant taxonomic groups (flora - vascular plants, amphibians, reptiles, birds, and mammals) in special area of conservation Montesinho/Nogueira (Portugal). It covers the period from 2000 to 2022 and has a high spatial resolution (e.g., georeferenced and aggregated (1 km) records. Additionally, the dataset offers details on the conservation status of each species at both regional (Portugal) and European levels, as well as the sources of the records and their corresponding spatial resolution. The dataset was developed in response to the absence of standardized species occurrence records in the region and to facilitate modeling (e.g., development of ecological niche models).</p>
Fig. 4 in Ephemeral Occurrence of the Echiuran Listriolobus brevirostris (Annelida: Echiura) in Osaka Bay between 1995 and 2002; a New Record for Japan, Probably Resulting from Human-mediated Introduction
Fig. 4. Relationship between trunk length and proboscis length in 52 fixed specimens of Listriolobus brevirostris, collected from Osaka Bay in 1999 (NSMT-Ec 164 to 183).
Fig. 3 in Ephemeral Occurrence of the Echiuran Listriolobus brevirostris (Annelida: Echiura) in Osaka Bay between 1995 and 2002; a New Record for Japan, Probably Resulting from Human-mediated Introduction
Fig. 3. Internal morphology (dorsal view) of Listriolobus brevirostris from Osaka Bay, collected off Kobe on 26 November 2001 (NSMT-Ec 186). A, anterior end of trunk; B, posterior end of trunk (ventral vessel undetectable due to deterioration). Abbreviations: al, alimentary canal; av, anal vesicle; dv, dorsal vessel; gd, gonoduct; gl, gonostomal lip; im, interbasal muscle; nv, neurointestinal vessel; rc, rectal caecum; re, rectum; rv, ring vessel; tb, terminal bulb; vn, ventral nerve cord: vs, ventral seta; vv, ventral vessel. Scale bars: 1 mm.
Fig. 5 in Ephemeral Occurrence of the Echiuran Listriolobus brevirostris (Annelida: Echiura) in Osaka Bay between 1995 and 2002; a New Record for Japan, Probably Resulting from Human-mediated Introduction
Fig. 5. Seasonal changes in trunk length of Listriolobus brevirostris from Osaka Bay in 1999. Solid bars indicate mature specimen(s), dotted lines, measurements from live specimens, and double-headed arrow of dotted line, the length range in live specimens (see text).
Temporal trends in the spatial bias of species occurrence records
<p>Large-scale biodiversity databases have great potential for quantifying long-term trends of species, but they also bring many methodological challenges. Spatial bias of species occurrence records is well recognized. Yet, the dynamic nature of this spatial bias - how spatial bias has changed over time - has been largely overlooked. We examined the spatial sampling bias of species occurrence records within multiple biodiversity databases in Germany and tested whether spatial bias in relation to land cover or land use (urban and protected areas) has changed over time. We focused our analyses on urban and protected areas as these represent two well-known correlates of sampling bias in biodiversity datasets. We found that the proportion of annual records from urban areas has increased over time while the proportion of annual records within protected areas has not consistently changed. Using simulations, we examined the implications of this changing sampling bias for estimation of long-term trends of species' distributions. When assessing biodiversity change, our findings suggest that the effects of spatial bias depend on how it affects sampling of the underlying land-use change drivers affecting species. Oversampling of regions undergoing the greatest degree of change, for instance near human settlements, might lead to overestimation of the trends of specialist species. For robust estimation of the long-term trends in species' distributions, analyses using species occurrence records may need to consider not only spatial bias, but also changes in the strength of spatial bias through time.</p>
Occurrence records for Craterostigmus tasmanianus Pocock, 1902
<p>The centipedes <em>Craterostigmus tasmanianus</em> Pocock, 1902 and <em>C. crabilli</em> Edgecombe and Giribet, 2008 are the only known species in the order Craterostigmomorpha. <em>C. tasmanianus</em> occurs only in Tasmania (Australia), while <em>C. crabilli </em>occurs in both the North and South Islands of New Zealand.</p> <p><em>C. tasmanianus</em> is widespread in Tasmania and is found in forest and woodland from sea level to at least 1300 m elevation, and in areas with average annual rainfall from 600 to 2500+ mm. It requires moist microhabitats, and in the drier parts of its range it is restricted to riparian forest and scrub and on south-facing hillslopes. It can be locally abundant in rainforest, in mid-elevation wet eucalypt forest, and in high-elevation eucalypt woodland on Tasmania's Central Plateau. For more information on the habits and life history of <em>C. tasmanianus</em>, see Mesibov (1995) (<a href="https://biodiversitylibrary.org/page/57364741">https://biodiversitylibrary.org/page/57364741</a>).</p> <p>In the table "Craterostigmus_tasmanianus_records.txt" I list <em>C. tasmanianus</em> occurrence records in Darwin Core format. Data for my own collecting events are from an authority file (<a href="https://zenodo.org/record/6618279">https://zenodo.org/record/6618279</a>). I excluded three uncertain records:</p> <p>(1) Queen Victoria Museum and Art Gallery (Launceston, Tasmania, Australia), QVM:23:25118 (1 specimen). The only locality information on the specimen label is "Site 4, no. 3 pit"</p> <p>(2) Specimens collected on Mt Wellington by Vernon Hickman (University of Tasmania) and studied by Sidnie Manton (University of Cambridge). Manton thanked "Professor V. V. Hickman for his indefatigable efforts in climbing Mount Wellington, Tasmania, and collecting and packing <em>Craterostigmus tasmanianus</em> for me on a number of occasions, and for the information he has sent me about this animal" (p. 359 in Manton SM (1965) The evolution of arthropodan locomotory mechanisms. Part 8. Functional requirements and body design in Chilopoda, together with a comparative account of their skeleto-muscular systems and an Appendix on a comparison between burrowing forces of annelids and chilopods and its bearing upon the evolution of the arthropodan haemocoel. <em>Zoological Journal of the Linnean Society</em> 46(306-307):251-483; pls 1-7.) Parts of two Hickman specimens of <em>C. tasmanianus</em>, embedded in paraffin, were sent by Manton to Carol Prunescu for anatomical studies (<a href="https://www.biodiversitylibrary.org/page/58835329">https://www.biodiversitylibrary.org/page/58835329</a>).</p> <p>(3) A specimen in the Field Museum of Natural History (FMNHINS 0000 096 000) is said to have been collected by John Kethley "40 km SW of Smithton" on 4 March 1977, field number FMHD#77-190. The date and location are highly unlikely. I assisted Kethley with his collections in northwest Tasmania and on 5 (not 4) March 1977 we sampled along the Savage River Pipeline Road, ca 40 km south<em>east</em> of Smithton. The Field Museum specimen is likely to be from rainforest at the 22-mile peg on the pipeline road, and is probably a partner to the record for Tasmanian Museum and Art Gallery J2340.</p> <p>Note that there are duplicate occurrence records in the table if a single collection of specimens was split between institutions or researchers. As of 15 June 2022, there were 345 occurrence records in the table with a unique combination of eventDate, decimal Latitude and decimalLongitude.</p> <p>In the associatedReferences field I have tried to link specimen lots with research articles. In the case of research articles based on sequences, tracing the links between sequences and specimens was made difficult by incomplete documentation. For this reason there is no associatedSequences field in the table, and I am not confident that I have included relevant references for all records.</p> <p>For help in preparing the records table I am very grateful to</p> <p>Adam Baldinger (Museum of Comparative Zoology)<br> Andrew Crowden (Natural Resources and Environment Tasmania)<br> Wolfgang Dohle (Berlin, Germany)<br> Greg Edgecombe (Natural History Museum, UK)<br> Henrik Enghoff (Natural History Museum of Denmark)<br> Gero Hilken (Universität Duisberg-Essen)<br> Eszter Lazanyi (Hungarian Natural History Museum)<br> Megan McCuller (North Carolina Museum of Natural Sciences)<br> Catriona McPhee (Museums Victoria)<br> Kirrily Moore (Tasmanian Museum and Art Gallery)<br> Carsten Müller (Universität Greifswald)<br> Hilke Ruhberg (Universität Hamburg)<br> Arkady Schileyko (Zoological Museum of M.V. Lomonosov Moscow State University)<br> Helen Smith (Australian Museum)<br> Jörg Spelda (Petershausen, Germany)<br> Eivind Undheim (Norwegian University of Science and Technology)<br> Julianne Waldock (Western Australian Museum)</p> <p>Version 2 of the table adds an associated reference to cratas-202.</p>
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>
Figure 1 in New records of the occurrence of Megaleporinus macrocephalus (Garavello & Britski, 1988) (Characiformes, Anostomidae) from the basins of the Itapecuru and Mearim rivers in Maranhão, Northeastern Brazil
Figure 1. Geographic distribution of Megaleporinus macrocephalus in Brazil. The area of the new registrations for the Itapecuru rivers in the municipality of Pé da Serra and Mearim in the locality Laje dos Currais, in São Mateus, and in the city of Pedreiras in the Northeast Region.
Figure 4 in First occurrence of Panthera atrox (Felidae, Pantherinae) in the Mexican state of Hidalgo and a review of the record of felids from the Pleistocene of Mexico
Figure 4. Potential common prey-size range for Panthera atrox from the late Pleistocene of southeastern Hidalgo, including the herbivores that have been reported at the El Barrio locality (HGO-47). Diamond and line indicate the mean and observed range of body mass (from Van Valkenburgh et al., 2016).
Figure 1 in First occurrence of Panthera atrox (Felidae, Pantherinae) in the Mexican state of Hidalgo and a review of the record of felids from the Pleistocene of Mexico
Figure 1. (a) Index map showing the study area in southeastern Hidalgo, central Mexico; the capital of the state (Pachuca) and the late Pleistocene locality El Barrio (HGO-47) are depicted. (b) Stratigraphic section of the El Barrio locality (HGO-47); the arrow indicates the fossil-bearing level.
Figure 3 in First occurrence of Panthera atrox (Felidae, Pantherinae) in the Mexican state of Hidalgo and a review of the record of felids from the Pleistocene of Mexico
Figure 3. Left fifth metacarpal (UAHMP-4222) of Panthera atrox from the late Pleistocene of southeastern Hidalgo, central Mexico. (a) Ventral, (b) dorsal, (c) medial, (d) lateral, (e) proximal, and (f) distal views. Scale bar equals 2 cm.
Figure 5 in First occurrence of Panthera atrox (Felidae, Pantherinae) in the Mexican state of Hidalgo and a review of the record of felids from the Pleistocene of Mexico
Figure 5. Geographic distribution of Panthera atrox in North America during the late Pleistocene (main source: KurtØn and Anderson, 1980). The gray silhouette indicates the record from southeastern Hidalgo, central Mexico.
Figure 7 in First occurrence of Panthera atrox (Felidae, Pantherinae) in the Mexican state of Hidalgo and a review of the record of felids from the Pleistocene of Mexico
Figure 7. Mexican Pleistocene localities with records of felids. The map is regionalized in the morphotectonic provinces of Ferrusquía-Villafranca (1993). Abbreviations of the morphotectonic provinces as in Table 3. Squares indicate the early Pleistocene localities and circles the late Pleistocene localities. The felid record includes the following species: A: Panthera atrox; B: Panthera onca; C: Puma concolor; D: Puma yagouaroundi; E: Lynx rufus; F: Leopardus pardalis; G: Leopardus wiedii; H: Smilodon fatalis; I: Smilodon cf. S. gracilis; J: Felis rexroadensis; K: Miracinonyx inexpectatus.
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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)
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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
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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.