DOI: 10.5061/dryad.j0zpc86t3
title: Survey of the hooded skunk in the Trans-Pecos Ecoregion

description: The hooded skunk (Mephitis macroura) is recognized as a species of
 greatest conservation need in Texas and is one of the rarest carnivores in
 Texas. It is one of five species of skunks in Texas, and documentation of
 this mammal has been difficult in part because of its variable pelage
 patterns, all like those of the ubiquitous striped skunk (Mephitis
 mephitis). We studied this species to meet three objectives: 1) determine
 hooded skunk historical and recent occurrence records in the state, 2)
 conduct a field-based study of the lower elevations of the Big Bend region
 of Texas to inform local presence, and 3) model the distribution of the
 species with an emphasis on Chihuahuan Desert populations.  This
 report details the results of our studies and how those research
 objectives were met.
description: # Survey of the hooded skunk in the Trans-Pecos Ecoregion Dataset DOI:
 [10.5061/dryad.j0zpc86t3](10.5061/dryad.j0zpc86t3) ## Description of the
 data and file structure Species distribution modeling was conducted in the
 program R using the Wallace package (Kass et al. 2018, 2022) and followed
 the workflow guidelines of Kass et al. (2024), which recommend additional
 packages to enhance analytical utility. Wallace is built on the *shiny*
 web application framework, providing a graphical user interface (GUI) for
 species distribution modeling (Kass et al. 2022). Many of the
 supplementary packages outlined by Kass et al. (2024) are already
 incorporated as GUI options within Wallace, while others can be added as
 user-specified inputs. For this study, we implemented maximum entropy
 modeling (Phillips et al. 2006) within the Wallace *shiny* application.
 Files denoted as "Mephits_macroura" are products from use of the
 Wallace package.  Files denoted as "Camera" are downloads from
 our camera trap survey on Wildlife Insights (Below). Any other file will
 have additional information.  
 
 ### Files and variables #### File:
 Mephitis_macroura_fc.LQH_rm.1.5_cloglog_(1).tif.aux.xml
 **Description:** Predicted probability of occurrence. #### File:
 Mephitis_macroura_maxnet_evalTbl.csv **Description:** Model evaluation
 table - Global #### File: Mephitis_macroura_maxnet_evalTblBins_(1).csv
 **Description:** Model evaluation table - Across Folds #### File:
 Mephitis_macroura_fc.LQH_rm.1.5_cloglog.tif **Description:** Predicted
 probability of occurrence.  ## **Camera Trap Survey** Between January 2024
 and September 2025, we operated camera traps within Big Bend National
 Park, Black Gap Wildlife Management Area, and El Carmen Land and
 Conservation Co., LLC, CEMEX INC., Texas - all adjacent properties within
 southern Brewster County, TX. At both Black Gap and El Carmen, cameras
 were placed in part at guzzlers, water catchment devices designed to
 provide water to wildlife, and at random locations. Within Big Bend
 National Park, cameras were deployed at random locations only.  Images
 from the camera trap survey were uploaded, identified, and catalogued on
 Wildlife Insights (Perkins et al. 2024). There are 4 csv files downloaded
 from Wildlife Insights. Additionally, there is a pdf
 (Camera_Trap_-_Data-Dictionary-for-Data-Download.pdf) that defines every
 column within these 4 csv files.  **Camera_Trap_Deployments.csv** *
 See Camera_Trap_-_Data-Dictionary-for-Data-Download.pdf. * Additional
 pertinent information provided below.  * Column Information: *
 project_ID: Unique Wildlife Insights Project ID * deployment_ID: Unique
 identifier of site, camera #, and deployment date * placename: Identifier
 of site and camera # * longitude, latitude: Camera deployment location *
 start_date, end date: Date of camera deployment. Date of deployment end
 either due to camera removal or camera failure.  * bait_type: Whether bait
 was used. None used. * feature_type: Whether the camera was placed on an
 anthropogenic or physical feature and what type.  *
 feature_type_methodology: If feature type was other, cells are filled with
 either "Drainage" or "Desert Wash". All empty cells
 are NA.  * camera_id: Unique numerical camera identifier - applied by WI. 
 * camera_name: Unique camera name that combines site and camera number -
 internal. Redundant between deployment ID and placename.  * quiet_period:
 Time, in seconds, between successive detections.  * camera_functioning:
 Binary. Camera functioning indicates the camera was operational the entire
 period. All others indicate the loss of function during the deployment
 period and cause. * sensor_height: Height the sensor was deployed at. All
 are "knee height". * sensor_orientation: Angle the camera sensor
 was deployed at. All are parallel to the ground.  * detection_distance:
 Estimate of distance camera can detect wildlife in meters.  *
 recorded_remarks: Any additional notes on the camera deployment
 **Camera_Trap_Images.csv** * All detections from camera trap project that
 were catalogued within Wildlife Insights.  * Blank cells are present in
 this spreadsheet. They are present in the taxonomic columns when species
 identification could not be resolved at a lower level and in the bounding
 boxes column when a detection box was not generated per image. These cells
 are intentionally left blank.  * Future users should note that our cameras
 produced 3 images per detection event and all 3 images may not be
 categorized as the same species based upon how we reviewed and curated the
 images on Wildlife Insights. For example, image one may incompletely
 capture information capable of identifying the species (and in this
 instance be categorized as Canidae) while the next two images capture this
 information and are categorized as gray fox. Subsequent assessment of the
 dataset within an r package such as camtrapR (Niedballa et al. 2016) to
 identify species categorization errors (e.g., 3 images within ~ 5 seconds)
 will flag this as a potential error. Future users should use the Wildlife
 Insights project (Perkins et al. 2024) to resolve these issues.  * Project
 personnel have mammal expertise with a carnivore concentration. Any user
 of this dataset outside of mammalian carnivores should consider using the
 Wildlife Insights project (Perkins et al. 2024) to confirm species
 identification.  * Of note, avian species were primarily categorized as
 "avian" outside of turkey vulture and scaled quail. Detections
 included both black vulture and Montezuma quail, but these were less than
 1% compared to the former species.  * Of note, mule and white-tailed deer
 occur within the study area. White-tailed deer were only definitively
 identified from El Carmen. Generally, deer on El Carmen were categorized
 as *Odocoileus sp.* while deer at Black Gap and Big Bend were categorized
 as mule deer.  * Of note, up to 3 cottontail rabbit species are
 hypothesized to occur within the study region. We are unaware of any
 reliable way to differentiate among these species from image only. Future
 users should elevate this consideration above any categorizations within
 the dataset.  * Of note, collared peccary were frequently and abundantly
 detected. These images were reviewed a bit more closely as we have
 collaborative interest of this species (as of fall 2025). Feral pigs were
 present, but seemingly extremely rare (e.g., 1 known large boar moving
 among 2 of the properties). American black bear were present and detected
 relatively frequent. Efforts were made to resolve the Wildlife Insights AI
 initial identification across these 3 species. Broadly, temporal use of
 this dataset for collared peccary with a temporal designation of
 independence of 1 hour or less, may benefit from review of the Wildlife
 Insights project.  * Of note, up to 4 currently extant canine species may
 occur within the study area (as of fall 2025). Recent survey of the
 general area failed to detect kit fox (Hewitt et al. 2022) and to our
 knowledge, red fox have never been located as far south in Brewster County
 as our survey area (Schmidly and Bradley 2016). While the Wildlife
 Insights AI flagged some detections as red fox or Vulpes species, we
 categorized all of these as grey fox. Across all canine images, there were
 none identified as kit fox or red fox that closely resembled these
 species. **Camera_Trap_Identifiers.csv** * Camera trap identifiers
 including Wildlife Insights designated camera trap ID (camera_id) and
 internal camera trap ID (camera name). 
 **Camera_Trap_Projects_Metadata.csv** * Project metadata associated with
 the Wildlife Insights project.  
 
 ## **Mephitis macroura "habitat ranking"** We used information
 from the 10 m resolution Texas Parks and Wildlife Department Ecological
 Mapping System (Elliot et al. 2014) to assess and rank potential *M.
 macroura* habitat associated with 11 occurrence records. This ranking
 classification was used solely to inform randomly stratified camera-trap
 survey locations. To identify the vegetative communities associated with
 *M. macroura*, we first applied a 1-kilometer buffer around each location
 and then conducted a summary analysis of the proportion of vegetation
 types within each buffer. To check for consistency across the Chisos
 Mountains, this procedure was repeated on a subset of nine lower-elevation
 locations and again on all 11 locations, but with vegetation types found
 only in the Chisos Mountains removed. In each instance, the ranking of the
 top three vegetation types remained the same: succulent desert scrub,
 mixed desert shrubland, and hill and foothill grassland vegetation types
 ranked the highest and together accounted for 52% of the land-cover at 10
 m resolution in the global assessment.
 **Environmental_1-km_Buffers_from_BIBE_MEMA_Observations.xlsx** Workbooks:
 * All Data: All data exported from the 1-km buffers surrounding each of
 the 11 hooded skunk occurrence records. Data is from the Texas Parks and
 Wildlife Department Ecological Mapping System (Elliot et al. 2014). *
 Location: Name of individual camera trap associated with occurrence
 record.  * Lat/Long. Latitude or Longitude. * Veg Community: Vegetation
 community classifier.  * Hectares: Size, in hectares, of each polygon. *
 Truncated Data. Same dataset as "All Data", but truncated to
 only the 5 columns previous identified.  * Individual Locations %: * Pivot
 Tables summing the hectares of vegetative community per class.  * Station:
 Camera Trap Station. * Total HA: Total Hectares per Veg Class.  * %:
 Decimal value for the percentage each veg class contributes to the overall
 1-km buffer.  * Global % * Pivot table with all vegetation classes summed
 across the 11 buffers * Cumulative: Total Hectares of each vegetation
 class.  * Overall %: Percentage each vegetation class contributed to the
 11 buffers * Green: Vegetation Classes representing more than 5% of the
 global total and found throughout the study area. * Red: Vegetation
 Classes representing more than 5% of the global total but primarily found
 in the Chisos Mountains, with secondary presence in the Northern Rosillos
 and Sierra del Carmens (e.g., higher elevation vegetation types).  * High
 Elevation: * Subset of locations (~2/3 of total) that were relatively
 higher in location compared to all occurrence locations or were "in
 between" higher and lower.  * The only new column is Rank. Of these
 cameras and vegetation classes, numerical rankings were applied based upon
 overall percentage. Vegetation classes less than 5% were not considered. 
 * Lower Elevation:  * Same as the higher elevation workbook except these
 are the lower elevation occurrence locations and those "in
 between". ## Big Bend National Park (BIBE) Camera Trap Survey Between
 2021 and 2021, National Park Service Personnel operated a camera trap
 survey comprised of 12 cameras arrayed in a grid across the Chisos
 Mountain range within the boundaries of Big Bend National Park. Under
 permit, images previously categorized as "skunk" were provided
 by the NPS, categorized, and results presented. Image metadata was tagged
 with a camera station identifier and species. Next, the camtrapR package
 (Niedballa et al. 2016) was used to define temporal independence as one
 visitation per species per camera trap per 12 hours. 
 **BIBE_Camera_Trap_Survey.csv** * Images are of 4 skunk species from
 camera deployed within Big Bend National Park.  * Note some images contain
 multiple species including Urocyon cinereoargenteus and Canis latrans.  *
 Station: Station identifier based on station names provided by BIBE
 personnel.  * Species: Scientific name of species identified in image. *
 DateTimeOriginal: Month/Day/Year; Hour:Minute * Date: Month/Day/Year *
 Time: Hour:Minute:Second * delta.time.secs; delta.time.minute.;
 delta.time.hour: * Per species, the first visit per camera trap is
 designated as 0, 0, 0 in these columns. After this visit, all successive
 visits that occurred 12 hours after the previous, are categorized as
 temporally independent and given a unique row with these columns
 representing the time (hours, minutes, and seconds) since the previous
 unique visit.  * metadata_Site: All are BIBE - Big Bend National Park.  *
 metadata_Species: Scientific name.  * metadata_Camera: Camera station
 identifier.  * n_images: Total number of images associated with each
 unique visit (e.g., all images of the species per camera per 12 hours).
 Cameras were set to record 3 images per trigger.  * HierarchicalSubject:
 Hierarchical column that contains site, species, and camera using both
 commas and magritte pipes.  
 
 ## Code/software Wallace (Kass et al. 2018, 2022) via program r.  ##
 References Kass, J. M., Vilela B., Aiello-Lammens M. E., Muscarella R.,
 Merow C., Anderson R. P. 2018. Wallace: A flexible platform for
 reproducible modeling of species niches and distributions built for
 community expansion. Methods in Ecology and Evolution, 9:1151-1156. Kass,
 J.M., Pinilla-Buitrago, G.E, Paz, A., Johnson, B.A., Grisales-Betancur,
 V., Meenan, S.I., Attali, D., Broennimann, O., Galante, P.J., Maitner,
 B.S., Owens, H.L., Varela, S., Aiello-Lammens, M.E., Merow, C., Blair,
 M.E., Anderson R.P. 2022. wallace 2: a shiny app for modeling species
 niches and distributions redesigned to facilitate expansion via module
 contributions. Ecography, 2023: e06547. DOI: 10.1111/ecog.06547.
 Niedballa, J., R. Sollmann, A. Courtiol, and A. Wilting. 2016. camtrapR:
 an R package for efficient camera trap data management. Methods in Ecology
 and Evolution 7:1457-1462. doi: 10.1111/2041-210X.12600. Phillips, S. J.,
 R. P. Anderson, and R. E. Schapire. 2006. Maximum entropy modeling of
 species geographic distributions. Ecological Modeling 190:231-259. ##
 Access information Other publicly accessible locations of the data: *
 Perkins, J. C., R. C. Dowler, and R. D. Stevens. 2024. Last updated August
 2025. Survey of the carnivore community of southern Brewster County.
 [http://n2t.net/ark:/63614/w12008605](http://n2t.net/ark:/63614/w12008605). Accessed via wildlifeinsights.org on 2025-08-25. Data was derived from the following sources: * GBIF: Global Biodiversity Information Facility (GBIF). 2025. *Mephitis macroura* Occurrence Download. Accessed 25 April 2025. DOI: 10.15468/dl.rw3qjb. * WorldClim: Fick, S. E., and R. J. Hijmans. 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. *International Journal of Climatology* 37(12): 4302–4315. [https://doi.org/10.1002/joc.5086.](https://doi.org/10.1002/joc.5086) * iNaturalist: iNaturalist. 2025. Hooded Skunk Project. [https://www.inaturalist.org/projects/hooded-skunk](https://www.inaturalist.org/projects/hooded-skunk). Project created December 2024. * Perkins, J. C., R. C. Dowler, and R. D. Stevens. 2024. Last updated October 2025. Survey of the carnivore community of southern Brewster County. [http://n2t.net/ark:/63614/w12008605](http://n2t.net/ark:/63614/w12008605). Accessed via wildlifeinsights.org on 2025-10-17.  * Elliott, L. F., A. Treuer-Kuehn, C. F. Blodgett, C. D. True, D. German, and D. D. Diamond. 2009-2014. Ecological Systems of Texas: 391 Mapped Types. Phase 1 – 6, 10-meter resolution Geodatabase, Interpretive Guides, and Technical Type Descriptions. Texas Parks & Wildlife Department and Texas Water Development Board, Austin, Texas. Documents and Data Available at: [https://tpwd.texas.gov/gis/programs/landscape-ecology/by-ecoregion-vector](https://tpwd.texas.gov/gis/programs/landscape-ecology/by-ecoregion-vector).