Predicting population persistence through space and time: An evaluation of spatially structured population models for identifying critical habitat of endangered aquatic species

Endangered species are rare and difficult to enumerate by their very nature, and as such, provide many practical and statistical difficulties for determining population viability and critical habitat. One of the most prevalent difficulties mangers face when modeling endangered species is how much data is needed to support a management decision. We compare the ability of four approaches for modeling species persistence and habitat suitability, across a spectrum of data requirements, including: 1) habitat suitability models (HSI), 2) incidence function models (IFM), 3) minimum area for population viability (MAVP); and, 4) spatially structured population viability analyses. These approaches were used to model species persistence and habitat suitability using three model organisms, including; the endangered minnow the redside dace (Clinostomus elongatus), the threatened mollusc the northern abalone (Haliotis kamtschatkana), and a species of special concern the sea otter (Enhydra lutris). We present model results for a range of recovery goals, including critical habitat required to secure a 0.1 and 0.05 probability of persistence over 100 years. Model comparisons will be used to highlight how issues in data resolution may aid in developing improved management decisions for endangered aquatic species.