NEAFWA 2018

AUTHORS: Elias Rosenblatt, Vermont Cooperative Fish and Wildlife Unit, Rubenstein School of Environment and Natural Resources, University of Vermont; Dr. Therese Donovan, U.S. Geological Survey, Vermont Cooperative Fish and Wildlife Unit, Rubenstein School of Environment and Natural Resources, University of Vermont; Dr. James Murdoch, Rubenstein School of Environment and Natural Resources, University of Vermont.

ABSTRACT. Accurate and precise population estimates for wildlife is an important tool in conserving and managing wildlife populations. However, this task remains difficult and expensive, often producing estimates with low levels of precision that make tracking population trends difficult. Moose (Alces alces) are a prime example of this challenge, as this species is wide-ranging in usually challenging terrain, and population estimates are either made with expensive and intensive methods or with cheaper but less precise methods. Population estimates from genetic material have become an increasingly important tool, but methods often require multiple samples from individuals to estimate population size. This presentation will focus on a novel method of population estimation using genetic material to reconstruct a population’s pedigree and infer the existence of individuals that were not sampled. This method shows promise with previous work on large carnivores, and could be an alternative method for estimating population size for other wildlife species. This presentation will explore the extension of this method to a simulated moose population in Vermont, identifying the intensity of sampling required to estimate a population and the spatial considerations of applying this method to a wide ranging, important wildlife species. This presented research lays the groundwork for assessing the application of this method on moose populations in the Northeast.