Strengthening the contribution of macroecological models to conservation practice
Owing to their large‐scale scope and emphasis on prediction, macroecological models have the potential to provide key contributions to evidence‐based conservation practice. However, examples of macroecological modelling outputs directly influencing conservation practice and decision‐making remain rare. The general barriers to implementation of ecological research into conservation practice have been discussed at length, whereas much less attention has been given to the specific barriers faced by macroecological modelling research. Here, I start to address this gap by discussing how two important barriers could be overcome in a practical manner, because their burden falls primarily on the researcher. The first barrier is the potential perception of macroecological models as “black boxes” by potential end‐users, who may have little time and/or quantitative training to inspect the underlying methods fully. The second barrier is the difficulty in effective translation of the uncertainty inherent to most macroecological models, given the high threshold for weight of evidence required to support most decisions. To overcome these barriers, I put forward a number of solutions, most of which rely on researchers agreeing to and adopting model documentation and communication standards already in existence. I conclude by introducing the bigger challenges ahead for the macroecology–conservation practice interface: transformation of publication incentives and establishment of a two‐way flow of knowledge between macroecologists and conservation practitioners. Macroecologists can contribute much‐needed evidence to support conservation decisions. However, fundamental changes to their research communication standards, their publication incentives and their understanding of regulatory settings will be needed to ensure that macroecological contributions are considered in practice.
Global Ecology and Biogeography 28 (Macroecology 30th Anniversary Issue): 54-60
Keywords: macroecology, science-practice gap, macroecological models, uncertainty, black box, practitioners, policy