Four conservation challenges and a synthesis - Williams, Byron K.; Brown, Eleanor D. (Ecology and evolution, 2023)
Conservation and management of biological systems involves decision‐making over time, with a generic goal of sustaining systems and their capacity to function in the future. We address four persistent and difficult conservation challenges: (1) prediction of future consequences of management, (2) uncertainty about the system's structure, (3) inability to observe ecological systems fully, and (4) nonstationary system dynamics. We describe these challenges in terms of dynamic systems subject to different sources of uncertainty, and we present a basic Markovian framework that can encompass approaches to all four challenges. Finding optimal conservation strategies for each challenge requires issue‐specific structural features, including adaptations of state transition models, uncertainty metrics, valuation of accumulated returns, and solution methods. Strategy valuation exhibits not only some remarkable similarities among approaches but also some important operational differences. Technical linkages among the models highlight synergies in solution approaches, as well as possibilities for combining them in particular conservation problems. As methodology and computing software advance, such an integrated conservation framework offers the potential to improve conservation outcomes with strategies to allocate management resources efficiently and avoid negative consequences. Four ubiquitous challenges to effective conservation are as follows: prediction of the future impacts of decisions; inability to observe biological systems fully; uncertainty about system structure; and nonstationary system dynamics. We present a basic Markovian framework, encompassing approaches to all four challenges, which features technical linkages among the challenges and thus allows synergies in solution approaches for particular conservation problems. The framework offers the potential to improve conservation outcomes with strategies that allocate management resources more efficiently and avoid negative consequences.