DOI: 10.5281/zenodo.7901045
title: Occurrence dataset for the subspecies of the American badger (Taxidea taxus berlandieri) in the north-central region of Mexico

description: The subspecies of American badger (Taxidea taxus berlandieri Baird, 1858), also called tlalcoyote (Figure 1), is distributed in north-central Mexico. However, its occurrence records are scarce and the few that exist are uncertain due to incorrect georeferencing or identification of the taxonomic unit. In view of this, we disgned a spatial sampling in part of the states of Coahuila de Zaragoza, Durango, Nuevo León, San Luis Potosí and Zacatecas. In this north-central protion of Mexico, we generated a grid of squares measuring 5 × 5 km over the entire study area using QGIS® 3.10 software.  Subsequently, we excluded squares that included urban settlements, agricultural land, or water bodies in more than 30% of their extension; we also descarted squares located at an altitude over 2,250 meters above sea level.  To perform this filtering, we used both the land use and vegetation chart of the INEGI [Instituto Nacional de Estadística, Geografía e Informática] (2018) and the Digital Elevation Model (DEM) downloaded from the USGS page [United States Geological Survey] (2019) as a basis.  As result, we obtained 3,471 squares separated by at least 5 km.  Then, through simple random sampling, 177 (≈5%) squares were selected, where we generated centroids to be used as sampling sites.   

In field work, between 2009 and 2015, at these 177 sites we traced a 10 × 100 m transect, where we searched for T. t. berlandieri signs (i.e., burrows and scratching posts). In this case, their burrows and scratching posts are easily observed and quantified, and there is no chance of mistaking them for burrows of other species (Long 1973; Merlin 1999). Also, we recorded possible sightings, as other studies (e.g., Merlin 1999; Elbroch 2003).  As result, we only found 33 with signs of occurrence.  

Figure 1. Individual of tlalcoyote (Taxidea taxus Berlandieri). Photo obtained from Naturalista (2023) and uploaded by David Molina©. All rights reserved (CC BY-NC-ND).

To increase the number of records, we included occurrence data from GBIF [Global Biodiversity Information Facility portal] (2022). We downloaded only the records that included coordinates and that their basis of registration was "preserved specimen". This, because they are correctly identified as specimens from biological collections (Maldonado et al. 2015). In addition, we only selected records for Mexico. Subsequently, we filtered the downloaded database, discarding records that were incorrectly georeferenced, with atypical and duplicate coordinates, as well as with low geospatial accuracy (e.g., less than three decimals of precision).

We loaded the remaining data into the QGIS® software and performed a spatial filtering, where we excluded data that were outside the study area, located in unlikely areas (e.g., human settlements, bodies of water, agricultural areas) and with a distance of less than 5 km from the records obtained in the field. This gave a total of 10 records from the GBIF portal. Finally, we loaded the raster layers of elevation (Elev; INEGI 2007), normalized difference vegetation index (NDVI, USGS 2019) and the slope of the terrain into the software to extract the pixel values based on the GBIF records and those obtained in the field. With this, we generated a new global dataset to which we performed environmental filtering to find environmental outliers. We plotted the normality distribution of the data for each variable and the dispersion of the data among the variables.  In this filtering, we conserve all records. Figure 2 shows the normality distribution of the records as a function of Elev. Figure 3 shows the dispersion of the data between Elev and NDVI.

Figure 2. Normality distribution of T. t. berlandieri occurrence records as a function of the elevation variable (Elev).

Figure 3. Scatter plot of T. t. berlandieri occurrence records as a function of elevation (Elev) and normalized difference vegetation index (NDVI).

For the north-central region of Mexico, we present the global database (i.e., Tatabe_joint.csv), as well as the database that contains only the field evidence records (i.e., Tatabe_first_order.csv) and another one with the filtered GBIF records (i.e., Tatabe_GBIF.csv).