Better Model Transfers Require Knowledge of Mechanisms
Model transferability is an emerging and important branch of predictive science that has grown primarily from a need to produce ecological forecasts in the face of widespread data deficiency and escalating environmental novelty. In our recent article in Trends in Ecology and Evolution , we outlined some of the major roadblocks that currently undermine the practice of model transfers in ecology. The response of Radchuk et al.  to our work stresses the value of considering ‘first principles’ in projections of ecosystem change  and offers insights into outstanding challenges specific to mechanistic (synonym: process-based) models .