Using cost‐effectiveness analysis to compare density‐estimation methods for large‐scale wildlife management

Abstract

AbstractDensity estimates for animal populations often inform conservation and management decisions. Many methods to estimate animal density exist but deciding between competing alternatives traditionally has depended upon assessing multiple factors (e.g., precision, total cost, area sampled) independently and often in an ad hoc manner. Cost‐effectiveness analysis is a tool that economists use to decide objectively between competing alternatives. We extend cost‐effectiveness analysis to simultaneously integrate precision and per‐area cost of sampling when selecting between competing techniques used to estimate animal density both after a single application of a method and across several applications of capital equipment. Our extension allows for weighting of factors that may vary with the objectives and constraints of decision makers. We apply our extension of cost‐effectiveness analysis to a case study in which population density of white‐tailed deer (Odocoileus virginianus) was estimated in 3 large management units in Indiana, USA, using 3 competing distance‐sampling methods: fecal‐pellet, camera‐trap, and aerial sampling. The unweighted cost effectiveness of aerial sampling with color and infrared sensors was usually superior after a single application of each method and was always superior across several applications in differing landscapes. Pellet sampling was the most cost effective after a single application of each method in an agriculturally‐dominated management unit. Although camera sampling has increased in popularity, the cost effectiveness of camera sampling was poorer than the other 2 methods, even when allowing for potential future innovations to streamline data processing. Cost‐effectiveness analysis can be useful when selecting among competing methods for monitoring animal populations of conservation and management importance. The same principles used in our cost‐effectiveness analysis can be used to decide between competing alternatives related to any ecological monitoring in addition to density estimation.