Optimal trade-offs between learning and doing in habitat conservation

Background/Question/Methods

Species’ habitats should be identified as accurately as possible to maximize the benefit to conservation and minimize the opportunity costs of habitat protection. However, delaying habitat protection in favor of improving accuracy could result in additional habitat loss in the interim. Determining how much time to invest on learning about species’ habitat use and requirements is therefore important to maximize the accuracy of habitat identification while still allowing for timely protection. To address this question, we developed a general approach to determining the optimal amount of time to spend on learning before protecting habitats. We assumed that the accuracy of habitat identification improves over time as learning occurs, resulting in a greater proportion of habitats correctly identified and protected. We also assumed that habitat loss is ongoing, resulting in a decrease in the area of available habitats that can be protected over time. We then expressed the total area of habitats that are correctly identified as a function of both habitat loss and improved accuracy over time. Using this relationship, we optimized the trade-off between learning and doing by determining the amount of time spent on research that maximizes the area of habitat that is correctly identified and protected.

Results/Conclusions

We used one linear, two hyperbolic, and two sigmoid functions to simulate learning over time, and the loss of between 1% and 10% of available habitat area per year to simulate ongoing habitat loss. Simulations revealed that the optimal time to spend learning decreased with increasing rates of habitat loss. When only 1% of habitats are lost per year, the optimal time is determined by the learning rate. For example, given a false positive identification rate of 0.5, the optimal time varied from 15 or 17 years using sigmoid curves, to 3 or 6 years using hyperbolic curves. However, when habitat loss is 5% per year or greater, the optimal number of years becomes 4 years or less, regardless of the learning rate. This approach to determining the optimal time for learning highlights the need for timely protection when the threat of habitat loss is high, and the need for greater accuracy in identification when habitat loss occurs slowly. It can therefore serve as a useful tool for guiding the allocation of conservation resources towards research or habitat protection, for instance, in determining the amount of time to spend on research before designating critical habitats for threatened and endangered species.