Climate change and tree harvest interact to affect future tree species distribution changes
Abstract
Tree harvest and climate change can interact to have synergistic effects on tree species distribution changes. However, few studies have investigated the interactive effects of tree harvest and climate change on tree species distributions.
We assessed the interactive effects of tree harvest and climate change on the distribution of 29 dominant tree species at 270 m resolution in the southern United States, while accounting for species demography, competition, urban growth and natural fire. We simulated tree species distribution changes to year 2100 using a coupled forest dynamic model (LANDIS PRO), ecosystem process model (LINKAGES) and urban growth model (SLEUTH).
The distributions of 20 tree species contracted and nine species expanded within the region under climate change by end of 21st century. Distribution changes for all tree species were very slow and lagged behind the changes in potential distributions that were in equilibrium with new climatic conditions.
Tree harvest and climate change interacted to affect species occurrences and colonization but not extinction. Occurrence and colonization were mainly affected by tree harvest and its interaction with climate change while extinctions were mainly affected by tree harvest and climate change.
Synthesis and applications. Interactive effects of climate and tree harvest acted in the same direction as climate change effects on species occurrences, thereby accelerating climate change induced contraction or expansion of distributions. The overall interactive effects on species colonization were negative, specifically with positive interactive effects at leading edges of species ranges and negative interactive effects at trailing edges. Tree harvest generally did not interact with climate change to greatly facilitate or ameliorate species extinction. Our modelling results highlight the importance of considering disturbances and species demography (e.g. post-harvest regeneration dynamics) when predicting changes in tree distributions.