Optimizing ecological surveys for conservation.
Abstract
Conservation decisions must be made with limited funding and incomplete information. Ecological surveys can help reduce uncertainty and, in turn, potentially lead to better management decisions. However, conducting surveys can reduce funds available for implementing management actions and, in turn, can potentially lead to worse conservation outcomes. Here we develop a value of information framework to evaluate and optimize survey plans. Our framework evaluates survey plans based on their ability to improve how likely resulting protected area systems are to secure species of interest, and accounts for survey and land acquisition costs. Using an example of eight imperilled plant species in Middlesex County (Ontario, Canada), we assessed our framework against conventional approaches for designing survey plans that involve selecting places with (i) maximal geographic coverage, (ii) diverse environmental conditions, (iii) highly uncertain information, (iv) high imperilled species richness and (v) low protected area establishment costs. We found that optimized survey plans could improve the protected area system by, on average, 57.52% (0.21 SD) (up to 105.25%) over conventional survey approaches. These optimized plans could also improve the protected area system by, on average, 19.91% (up to 32.37%) over simply prioritizing based on existing information. Survey plans designed using conventional approaches, in many cases, led to a worse protected area system than simply using existing information. Such conventional approaches performed the worst when they allocated a large percentage of the available budget to data collection. Synthesis and applications. Our findings demonstrate that conventional approaches for designing ecological surveys can impede conservation efforts by squandering funds on data that have little chance of improving decision making. Indeed, conventional approaches for designing surveys had the poorest performance under limited budgets, which are typical in real world planning exercises. We recommend that conservation practitioners carefully consider how data collection efforts can potentially improve conservation decisions, and also the costs associated with data collection. By applying the principles of value of information, our framework enables conservation practitioners to cost-effectively collect data in places that will maximize conservation outcomes.