Seabird meta-Population Viability Model (mPVA) methods

M Tim Tinker; Kelly M Zilliacus; Diana Ruiz; Bernie R Tershy; Donald A Croll

doi:10.1016/j.mex.2021.101599

Seabird meta-Population Viability Model (mPVA) methods

MethodsX. 2021 Dec 9:9:101599. doi: 10.1016/j.mex.2021.101599. eCollection 2022.

Authors

M Tim Tinker^{1

2}, Kelly M Zilliacus³, Diana Ruiz³, Bernie R Tershy³, Donald A Croll³

Affiliations

¹ EEB Department, University of California Santa Cruz, Santa Cruz, CA USA.
² Nhydra Ecological Consulting, Nova Scotia, Canada.
³ Conservation Action Lab, University of California Santa Cruz, Santa Cruz, CA USA.

Abstract

The seabird meta-population viability model (mPVA) uses a generalized approach to project abundance and quasi-extinction risk for 102 seabird species under various conservation scenarios. The mPVA is a stage-structured projection matrix that tracks abundance of multiple populations linked by dispersal, accounting for breeding island characteristics and spatial distribution. Data are derived from published studies, grey literature, and expert review (with over 500 contributions). Invasive species impacts were generalized to stage-specific vital rates by fitting a Bayesian state-space model to trend data from Islands where invasive removals had occurred, while accounting for characteristics of seabird biology, breeding islands and invasive species. Survival rates were estimated using a competing hazards formulation to account for impacts of multiple threats, while also allowing for environmental and demographic stochasticity, density dependence and parameter uncertainty.•The mPVA provides resource managers with a tool to quantitatively assess potential benefits of alternative management actions, for multiple species•The mPVA compares projected abundance and quasi-extinction risk under current conditions (no intervention) and various conservation scenarios, including removal of invasive species from specified breeding islands, translocation or reintroduction of individuals to an island of specified location and size, and at-sea mortality amelioration via reduction in annual at-sea deaths.

Keywords: AFR, Age of first reproduction; AoO, Area of occupancy; Bayesian hierarchical model; Conservation; Extinction risk; IUCN, International Union for Conservation of Nature; JAGS, Just another Gibbs Sampler; K, Carrying capacity; MCMC, Markov chain Monte Carlo analysis; MLE, Maximum likelihood estimation; Population model; QE, Quasi-extinction threshold; QEP, Quasi-extinction probability; R, R computer language for statistical computing; SSD, Stable stage distribution; mPVA, meta-Population Viability Analysis.