Assessing conservation lands for forest birds in an exurban landscape

Abstract

ABSTRACTExurban development is the fastest growing type of land use in the United States and is prominent in the southern Appalachian region. A potential consequence of exurban development is the loss and fragmentation of wildlife habitat. We used a Bayesian model that accounts for false positive and false negative detections to make inferences about how the occupancy of 6 forest‐dwelling, Neotropical migrant birds is related to multi‐scale attributes of exurban development on land managed under 3 different conservation frameworks: national forest, land trust, or unprotected property in Macon County, North Carolina, USA during 2 breeding seasons. We performed Bayesian model selection and model averaging with a Bayesian Information Criterion weights approximation, and we evaluated models’ predictive ability. We compared results from our occupancy model to those from a traditional model assuming data had no false positives. Results indicated that landscape‐ and local‐scale covariates were more strongly related to posterior occupancy probabilities than site‐scale covariates and that landscape composition and elevation were more strongly associated with occupancy probabilities than configuration. In particular, occupancy had a positive relationship with elevation and percent forest and a negative relationship with percent development. The black‐throated blue warbler (Setophaga caerulescens) and wood thrush (Hylocichla mustelina) had the lowest posterior occupancy probabilities of the focal species, suggesting that these species may need particular conservation attention. National forest sites had high occupancy, but land trust sites exhibited patterns similar to unprotected sites. Our findings can provide guidance to county land use planners and land trusts as they respond to exurban development. Also, our study demonstrates the application of an improved occupancy model that can generate more accurate inference by accounting for both types of imperfect detection while describing heterogeneity across sites and survey occasions. © 2017 The Wildlife Society.