Integrating Genetic Data and Demographic Modeling to Facilitate Conservation of Small, Isolated Mountain Goat Populations

Acquisition of field data and analytical methods needed for conservation and management of wildlife populations represent significant challenges, particularly for species that inhabit landscapes that are difficult to access or species that persist in small, isolated populations. In such instances, integrating diverse and complementary data streams, such as genetic and non-genetic data, can advance our understanding of population dynamics and associated management implications. We examined how genetic and morphologic data can be used to articulate population structure of a low-density, peninsular population of mountain goats (Oreamnos americanus) on the Cleveland Peninsula, Alaska, USA, and surrounding areas, 2005-2018. We then use a population demographic modeling approach to examine how the use of population structure information influences sustainable harvest quotas, as compared to a panmictic, null model. Specifically, we conducted extensive field sampling of genetic (n = 446) and morphologic (i.e., horn length, n = 371) data to characterize population structure. We conducted demographic analyses and examined harvest modeling scenarios using a sex- and age-specific matrix population modeling approach. Genetic and morphologic data analyses suggested peninsular subpopulations were demographically isolated, relative to surrounding mainland populations. Specifically, genetic structuring was evident and followed an isolation-by-distance, stepping-stone pattern indicating limited interchange, low effective population sizes, and reduced genetic diversity along a peninsular extremity to mainland gradient. Harvest modeling indicated that overharvest would likely occur if the panmictic, null model was used to guide harvest because the smallest genetically defined population at the peninsular extremity was too small to permit any level of sustainable harvest. Our analyses illustrate the importance of using genetic and morphologic data, in combination with demographic modeling, to quantitatively delineate population boundaries and dynamics for ensuring viability of small, isolated populations. (c) 2020 The Wildlife Society.

Automated summary

Obtaining field data and analytical methods for wildlife population conservation and management are significant challenges, especially for species in difficult-to-reach landscapes or small, isolated populations. Integrating genetic and non-genetic data can enhance understanding of population dynamics. Studying a low-density mountain goat population, genetic and morphologic data indicated demographically isolated peninsular subpopulations and influenced sustainable harvest quotas. The importance of using genetic and morphologic data, along with demographic modeling, in delineating population boundaries and dynamics for small, isolated populations was highlighted.