Climate-smart restoration and sustainable ecosystem management requires understanding which plant species will survive and thrive under both current and future climate conditions. Changing climate conditions are expected to place new environmental stresses on plants across biomes, potentially shifting the climate envelope, with unexpected consequences for ecological communities. Here, we train machine learning models on the global distribution of Earth's biomes, demonstrating that soil and climate can accurately capture contemporary biome-climate envelopes (BCEs) with 90% accuracy. We then predict how changes in climate might alter BCEs under different climate change scenarios (RCP 4.5 and 8.5). We find that 11–17% of the terrestrial surface is likely to experience a change in BCE by 2080 and 16–19% has a highly uncertain BCE trajectory over the coming decades. BCE boundaries generally shift poleward, with the tundra BCE shrinking by up to 47% under RCP 8.5, and various dryland BCEs overall increasing under RCP 8.5. These models do not necessarily reflect changes in vegetation characteristics under future climate conditions, as uncertainty about ecological feedbacks and migration rates preclude our capacity to predict how climate variation would impact these vegetation dynamics. However, we identify regions where changing climate conditions might make the local environments stressful for the vegetation that presently exists in those regions.
Runge et al. (Fri,) studied this question.