Assessing local population vulnerability with branching process models: an application to wind energy development

Authored by Richard A Erickson, Eric A Eager, Jessica C Stanton, Julie A Beston, Jay E Diffendorfer, Wayne E Thogmartin

Date Published: 2015

DOI: 10.1890/es15-00103.1

Sponsors: United States National Science Foundation (NSF)

Platforms: R

Model Documentation: Other Narrative Mathematical description

Model Code URLs: https://figshare.com/articles/Supplement_1_R_code_used_to_generate_the_model_output_and_figures_for_Assessing_local_population_vulnerability_with_branching_process_models_An_application_to_wind_energy_development_/3564498

Abstract

Quantifying the impact of anthropogenic development on local populations is important for conservation biology and wildlife management. However, these local populations are often subject to demographic stochasticity because of their small population size. Traditional modeling efforts such as population projection matrices do not consider this source of variation whereas individual-based models, which include demographic stochasticity, are computationally intense and lack analytical tractability. One compromise between approaches is branching process models because they accommodate demographic stochasticity and are easily calculated. These models are known within some sub-fields of probability and mathematical ecology but are not often applied in conservation biology and applied ecology. We applied branching process models to quantitatively compare and prioritize species locally vulnerable to the development of wind energy facilities. Specifically, we examined species vulnerability using branching process models for four representative species: A cave bat (a long-lived, low fecundity species), a tree bat (short-lived, moderate fecundity species), a grassland songbird (a short-lived, high fecundity species), and an eagle (a long-lived, slow maturation species). Wind turbine-induced mortality has been observed for all of these species types, raising conservation concerns. We simulated different mortality rates from wind farms while calculating local extinction probabilities. The longer-lived species types (e.g., cave bats and eagles) had much more pronounced transitions from low extinction risk to high extinction risk than short-lived species types (e.g., tree bats and grassland songbirds). High-offspring-producing species types had a much greater variability in baseline risk of extinction than the lower-offspring-producing species types. Long-lived species types may appear stable until a critical level of incidental mortality occurs. After this threshold, the risk of extirpation for a local population may rapidly increase with only minimal increases in wind mortality. Conservation biologists and wildlife managers may need to consider this mortality pattern when issuing take permits and developing monitoring protocols for wind facilities. We also describe how our branching process models may be generalized across a wider range of species for a larger assessment project and then describe how our methods may be applied to other stressors in addition to wind.

Tags

bird United-states Impact Fatalities Predictions Endangered indiana bat Ranging domestic cats White-nose syndrome Avian mortality Hypotheses