Aim: Climate change causes shifts in species ranges globally. Terrestrial plant species often lag behind temperature shifts, and it is unclear to what extent animal-dispersed plants can track climate change. Here, we estimate the ability of bird-dispersed plant species to track future temperature change on a tropical mountain.
Location: Tropical elevational gradient (500–3500 m.a.s.l.) in the Manú biosphere reserve, Peru.
Time period: From 1960–1990 to 2061–2080.
Taxa: Fleshy-fruited plants and avian frugivores.
Methods: Using simulations based on the functional traits of avian frugivores and fruiting plants, we quantified the number of long-distance dispersal (LDD) events that woody plant species would require to track projected temperature shifts on a tropical mountain by the year 2070 under different greenhouse gas emission scenarios [representative concentration pathway (RCP) 2.6, 4.5 and 8.5]. We applied this approach to 343 bird-dispersed woody plant species.
Results: Our simulations revealed that bird-dispersed plants differed in their climate-tracking ability, with large-fruited and canopy plants exhibiting a higher climate-tracking ability. Our simulations also suggested that even under scenarios of strong and intermediate mitigation of greenhouse gas emissions (RCP 2.6 and 4.5), sufficient upslope dispersal would require several LDD events by 2070, which is unlikely for the majority of woody plant species. Furthermore, the ability of plant species to track future changes in temperature increased in simulations with a low degree of trait matching between plants and birds, suggesting that plants in generalized seed-dispersal systems might be more resilient to climate change.
Main conclusion: Our study illustrates how the functional traits of plants and animals can inform predictive models of species dispersal and range shifts under climate change and suggests that the biodiversity of tropical mountain ecosystems is highly vulnerable to future warming. The increasing availability of functional trait data for plants and animals globally will allow parameterization of similar models for many other seed-dispersal systems.