Species distribution models (SDMs) have been widely used to project terrestrial species’ responses to climate change and are increasingly being used for similar objectives in the marine realm. These projections are critically needed to develop strategies for resource management and the conservation of marine ecosystems. SDMs are a powerful and necessary tool; however, they are subject to many sources of uncertainty. To ensure that SDM projections are informative for management and conservation decisions, sources of uncertainty must be considered and properly addressed. Here we provide ten overarching guidelines that will aid researchers to identify, minimize, and account for uncertainty through the entire model development process, from the formation of a study question to the presentation of results. These guidelines were developed at an international workshop attended by over 50 researchers and practitioners. Although our guidelines are broadly applicable across biological realms, we provide particular focus to the challenges and uncertainties associated with projecting the impacts of climate change on marine species and ecosystems.

While species interactions are fundamental for linking biodiversity to ecosystem functioning and for conservation, large-scale empirical data are lacking for most species and ecosystems. Accumulating evidence suggests that trophic interactions are predictable from available functional trait information, but we have yet to understand how well we can predict interactions across large spatial scales and food webs. Here, we built a model predicting predator-prey interactions based on functional traits for European vertebrates. We found that even models calibrated with very few known interactions (100 out of 71k) estimated the entire food web reasonably well. However, predators were easier to predict than prey, with prey in some clades being particularly difficult to predict (e.g., fowls and storks). Local food web connectance was also consistently over-estimated. Our results demonstrate the potential for filling gaps in sparse food webs, an important step towards a better description of biodiversity with strong implications for conservation planning.