Precision ecology for targeted conservation action

Abstract

Addressing the coupled threats of catastrophic climate change and biodiversity loss requires implementation of conservation and restoration actions globally. However, on-the-ground action is hindered by context dependency: the ubiquitous challenge that implementation outcomes vary from place to place due to complex dependencies among social and ecological drivers. Policymakers and practitioners recognize the need to tailor solutions to contexts, and target actions to places where they will work effectively. To provide information for decision-making, applied ecologists can learn from medicine and marketing, which aim to provide healthcare tailored to individual patients, and advertisements targeting individual tastes. These disciplines exploit big data and rapidly developing computational advances to predict treatment effects for individual units. Here we argue why and how ecological disciplines can begin to capitalize on these rich advances, to equip ecologists with a potentially powerful toolkit for applying big data to site-specific interventions, allowing effective conservation over large extents. We review approaches that hold promise for applied ecology, identify hurdles that must be overcome and propose a roadmap for establishing the conditions that will permit adoption of precision ecology.