Post-Disturbance Assessment of Bat Communities in the Southern Coastal Plain of New Jersey

Abstract

The Southern Coastal Plain of New Jersey (SCPNJ) is being rapidly altered by human development, altered forestry practices, and climate change. Understanding the influence of such effects on species in decline may provide insights into management efforts and conservation actions. White-nose syndrome (WNS), caused by the fungal pathogen Pseudogymnoascus destructans, was discovered in New York during winter 2006. Since then, several species of cave-hibernating bats have experienced range-wide population declines. The SCPNJ provides habitat for several bat species, including the endangered northern long-eared bat (Myotis septentrionalis). Despite this endangered status, remnant populations persist in coastal regions such as nearby Long Island, New York and on the offshore islands of Massachusetts. Additionally, the species appears to persist year-round in the coastal Carolinas and locally in portions of the Deep South, where shorter and milder winters allow individuals to avoid mortality from WNS. Although the SCPNJ experiences milder winters than nearby inland areas, the region contains a unique dynamic of increasing urbanization and habitat loss within a fire-adapted ecosystem. Prior to European settlement, the Pine Barrens within the SCPNJ were frequently burned and maintained by indigenous populations for hunting and forest management practices. After European settlement and subsequent forest harvesting, disturbance patterns shifted in response to fire suppression campaigns and land use change. To assess whether the SCPNJ functions as a refugium for the northern long-eared bat, I collected acoustic data from 2024–2026 using a spatially balanced sampling design. I processed calls using an automated call classification software and manually vetted files identified as potential northern long-eared bat calls. I used landscape and weather variables to fit a priori frequentist occupancy models. I used the top-performing model to parameterize a Bayesian occupancy model and then compared performance and predictions of these approaches. My results indicated a positive relationship between northern long-eared bat occupancy and the proportion of area burned within the past 10 years. Notably, fitting the top frequentist model within a Bayesian analysis using informative priors provided more stable and informative coefficient estimates likely due to limited detections. Based on the positive association between northern long-eared bat occupancy and fire, combined with recent wildfire events in the New Jersey Pine Barrens, I investigated the short-term effects of fire on total bat activity. Specifically, I collected acoustic data in two recent (< 1 year) wildfire areas and constructed Bayesian activity models. From April to November 2025, I deployed detectors along transects in burned interior, forest edge, and unburned sites. I processed data using automated call classification software, filtered by MLE, and aggregated total bat activity for each detector at the weekly scale. I then modeled activity within a Bayesian framework using normalized difference vegetation index (NDVI) as a proxy for fire disturbance effects on bat activity. I selected the most parsimonious model from three competing candidates. This model revealed a negative relationship between bat activity and NDVI, indicating higher activity in recently burned areas or along fire breaks. This suggests that fire reduces clutter that would otherwise obstruct flight paths whereby also likely promoting habitat diversity for both roosting and foraging. Results from this research indicate that periodic fire disturbance may benefit the bat community as a whole and a forest-dwelling endangered species such as northern long-eared bat, specifically. Land managers may use prescribed fire to promote a mosaic of productive roosting and foraging habitat to support bat populations on conserved lands that are otherwise facing increasing anthropogenic pressures elsewhere in the SCPNJ.