Predicting the impact of climate change-induced resource loss on the endangered Golden-cheeked Warbler (Setophaga chrysoparia)

Abstract

Although human land use has been the leading driver of endangerment, climate change continues to compound global biodiversity loss and poses a major risk to threatened and endangered species (Thomas et al. 2004, Chapin et al. Wilkening et al. 2019). For habitat specialists, such as the Golden-cheeked Warbler (Setophaga chrysoparia), climate change will have lasting consequences on habitat configuration, resource availability, phenology, and population densities (Wilkening et al. 2019, Maxwell et al. 2019). The Golden-cheeked Warbler, an endangered migratory songbird, breeds exclusively in the Ashe juniper (Juniperus ashei)-oak (Quercus sp.) woodlands of central Texas and depends on the shedding bark of mature juniper for nesting (Kroll 1980, Ladd and Gass 1999, Pulich 1976). Understanding how climate change will alter Golden-cheeked Warbler habitat is essential to the conservation of this at-risk species. In this study, I explore how modeling approaches can be used to project the potential impacts of climate change on at-risk species, with the focus of informing landscape-level management decisions for the conservation of both the Golden-cheeked Warbler and Ashe juniper. In Chapter 1, I describe how I developed an ensembled species distribution model for Ashe juniper using edaphic, topographic and climatic predictor variables. I then used the best-performing model to project the potential future distributions of juniper through 2100 using the outputs from two generalized circulation models (GCMs) run for two shared socio-economic pathways (SSPs). Across all models, I observed a contraction of the distribution of juniper within Texas. The juniper projections were then overlayed with a model of warbler densities to determine the potential loss of optimal and marginal warbler habitat through 2100 due to resource loss (Mueller et al. 2022). Under the most extreme climate scenario, the models predicted an almost complete loss of optimal and marginal warbler habitat, nearly 1,027 km2 and 9,485 km2, respectively. This approach detected areas where warbler habitat would persist even in the most extreme scenarios of climate-driven resource loss, allowing us to inform managers of areas of highest conservation priority. In Chapter 2, with the support of my collaborators, I built a population model to simulate the effects of climate change-driven resource loss on the population responses of Golden-cheeked Warblers within Texas. Using the modeling platform HexSim, we leveraged literature and expert knowledge on the life history of the endangered warbler to parameterize a spatially explicit, individual-based model. I created a time series of habitat maps based on the work from Chapter 1. I then simulated warbler responses to a changing habitat under the same four climate scenarios. The model outcomes allowed me to determine the importance of selected protected areas to the persistence of warbler populations and confirm which of the areas could strategically be prioritized in conservation management. Results indicate that climate-induced resource loss has the potential to reduce warbler abundance by up to 94% in the most extreme climate scenarios (UKESM1-0-LL), with 10% and 51% reduction in the MPI-ESM1-2-HR SSP2-4.5 and SSP3-7.0 scenarios, respectively. At 4 out of 14 protected sites, our simulation forecasted complete loss of occupancy with the MPI-ESM1-2-HR SSP3-7.0 scenario but forecasted complete loss at 11 out of the 14 sites with the UKESM1-0-LL SSP2-4.5 scenario. Through this analysis, our model identified the Balcones Canyonlands Preserve, Balcones Canyonlands National Wildlife Refuge, and Fort Cavazos as containing important climate refugia. Our study presents the immense impact climate change will potentially have on the persistence of the endangered Golden-cheeked Warbler and its habitat. This work contributes to the scientific understanding of how complex modeling can be leveraged to inform landscape-level conservation efforts of at-risk species threatened by climate change.