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White-nose Syndrome Surveillance And Bat Monitoring Activities In North Coast And Cascades Network Parks, 2016–2024

Department of the Interior

@usgov.doi_gov_white_nose_syndrome_surveillance_and_bat_monit_ec1301e5

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About this Dataset

White-nose Syndrome Surveillance And Bat Monitoring Activities In North Coast And Cascades Network Parks, 2016–2024

This data package contains National Park Service (NPS) and United States Geological Survey (USGS) white-nose syndrome disease surveillance tabular data collected during 2016-2024 at Ebey's Landing National Historical Reserve (EBLA), Lewis and Clark National Historical Park (LEWI), Mount Rainier National Park (MORA), North Cascades National Park (NOCA), Olympic National Park (OLYM), and San Juan Island National Historical Park (SAJH).

Associated publications can be found in the project reference at: NCCN Bat Population Monitoring and White-Nose Syndrome Surveillance (https://irma.nps.gov/DataStore/Reference/Profile/2315014).

Pseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome (WNS) in bats, has caused serious declines in bat populations across North America. In March 2016, the first case of WNS west of the Rocky Mountains was reported from a little brown bat (Myotis lucifugus) near North Bend, WA (King County), approximately 30 miles north of Mount Rainier National Park. In response, the NPS Pacific West Region (PWR) formed a working group of subject matter experts with experience in bat biology, disease ecology, veterinary medicine, WNS epidemiology, park management, and communications. This working group drafted a bat monitoring and WNS response plan for PWR parks which included five priority areas: communication, training and resources, WNS surveillance, bat monitoring, and collaboration and coordination.

In 2016, we began studying the current distribution of WNS disease in the National Parks of the North Coast and Cascades Network (NCCN) and its causative agent Pd, as well as the bat species most likely to be affected by the disease. The goal of disease monitoring was to detect Pd and WNS in bat colonies across the NCCN to provide information to park units on the status of their bat populations and inform potential management decisions, and to contribute to state and national efforts to document the geographic spread, species impacted, and how the disease progresses in bat populations over time.

We conducted WNS surveillance in five different park units in the NCCN from 2016 to 2024. We captured and swabbed bats, swabbed roost materials, and collected guano and tested these samples using quantitative real-time polymerase chain reaction (qPCR), which detects the presence of Pd DNA by measuring target nucleic acid sequences in each sample. When possible, we confirmed clinical signs of WNS through histopathology of tissue samples and carcasses.

Data within this package include bat species sampled, species identification method, number and types of samples collected, outcomes of qPCR for Pd DNA detection for all samples and histopathology for tissue and carcass samples, and sampling locations at the township level to protect sensitive bat roost locations.
Organization: Department of the Interior
Last updated: 2025-09-14T20:45:08.427113
Tags: bats, big-brown-bat, corynorhinus-townsendii, disease, disease-surveillance, ebeys-landing-national-historical-reserve, ebla, ecological-framework-biological-integrity-at-risk-biota-te-species-and-communities, ecological-framework-biological-integrity-focal-species-or-communities-mammals, ecological-framework-biological-integrity-infestations-and-disease-animal-diseases, ecology, eptesicus-fuscus, lasionycteris-noctivagans, lewi, lewis-and-clark-national-historical-park, little-brown-bat, little-brown-myotis, long-eared-myotis, long-legged-myotis, monitoring, mora, mount-rainier-national-park, mule-eared-bat, myotis, myotis-ciliolabrum, myotis-evotis, myotis-lucifugus, myotis-volans, myotis-yumanensis, nccn, noca, north-cascades-national-park, north-coast-and-cascades-network, nps-gov-subject-site-at-risk-species, nps-gov-subject-site-bats, nps-gov-subject-site-diseases-pests, nps-gov-subject-site-mammals, olym, olympic-national-park, pacific-townsends-big-eared-bat, pseudogymnoascus-destructans, sajh, san-juan-island-national-historical-park, silver-haired-bat, small-footed-myotis, townsends-big-eared-bat, western-big-eared-bat, western-long-eared-bat, western-lump-nosed-bat, western-small-footed-bat, western-small-footed-myotis, white-nose-syndrome, yuma-myotis

Tables

NPS USGS BatDiseaseSurveillance 2016-2024

@usgov.doi_gov_white_nose_syndrome_surveillance_and_bat_monit_ec1301e5.nps_usgs_batdiseasesurveillance_2016_2024
  • 41.65 kB
  • 94 rows
  • 47 columns
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CREATE TABLE nps_usgs_batdiseasesurveillance_2016_2024 (
  "year" BIGINT,
  "park_unit" VARCHAR,
  "site_name" VARCHAR,
  "county" VARCHAR,
  "structure_type" VARCHAR,
  "township" VARCHAR,
  "centroid_latitude" DOUBLE,
  "centroid_longitude" DOUBLE,
  "species_sampled_1_scientific" VARCHAR,
  "species_sampled_1_common" VARCHAR,
  "species_sampled_2_scientific" VARCHAR,
  "species_sampled_2_common" VARCHAR,
  "species_sampled_3_scientific" VARCHAR,
  "species_sampled_3_common" VARCHAR,
  "species_sampled_4_scientific" VARCHAR,
  "species_sampled_4_common" VARCHAR,
  "species_sampled_5_scientific" VARCHAR,
  "species_sampled_5_common" VARCHAR,
  "species_identification_acoustic" VARCHAR,
  "species_identification_genetic" VARCHAR,
  "species_identification_morphology" VARCHAR,
  "total_tissue_samples" BIGINT,
  "tissue_sample_type" VARCHAR,
  "tissue_species_1_scientific" VARCHAR,
  "tissue_species_1_common" VARCHAR,
  "tissue_species_1_num_individuals" BIGINT,
  "tissue_species_2_scientific" VARCHAR,
  "tissue_species_2_common" VARCHAR,
  "tissue_species_2_num_individuals" BIGINT,
  "tissue_qpcr_result" VARCHAR,
  "tissue_histopathology_result" VARCHAR,
  "total_swab_samples" BIGINT,
  "positive_swabs_samples" BIGINT,
  "inconclusive_swabs_samples" BIGINT,
  "negative_swabs_samples" BIGINT,
  "total_guano_samples" BIGINT,
  "positive_guano_samples" BIGINT,
  "inconclusive_guano_samples" BIGINT,
  "negative_guano_samples" BIGINT,
  "total_environmental_samples" BIGINT,
  "positive_environmental_samples" BIGINT,
  "inconclusive_environmental_samples" BIGINT,
  "negative_environmental_samples" BIGINT,
  "total_samples" BIGINT,
  "total_positive_samples" BIGINT,
  "total_inconclusive_samples" BIGINT,
  "total_negative_samples" BIGINT
);

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