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Climatic changes, Forest management, Ecological disturbances, Forest dynamics


Interactions among disturbances are seldom quantified, and how they will be affected by climate change is even more uncertain. In this study, we sought to better understand how interactions among disturbances shift under climate change by applying a process-based landscape disturbance and succession model (LANDIS-II) to project disturbance regimes under climate change in north-central Minnesota, USA. Specifically, we (1) contrasted mortality rates and the extent of disturbance for four individual (single) disturbance regimes (fire, insects, wind, or forest management) vs. all four disturbance regimes operating simultaneously (concurrent) under multiple climate change scenarios and (2) determined how climate change interacts with single and concurrent disturbance regimes to affect carbon stocks and forest composition. Under single disturbance regimes, we found that climate change amplifies mortality, but did not substantially change the overall extent of disturbances. Tree mortality under the concurrent disturbance regime scenario was less than the sum of all single disturbance regimes, providing evidence of significant negative feedbacks among disturbances, particularly under climate change. Finally, we found that climate change was the most critical driver of area harvested (via shifts in species composition), soil carbon, species composition, and diversity, while the disturbance regime (i.e., single or concurrent) had a larger influence on aboveground carbon and the relative dominance of conifers vs. hardwoods. In conclusion, our simulations suggest that disturbance interactions will be strongly mediated by climate change and will produce increasingly negative feedbacks, preventing worst-case disturbance outcomes. Our results underscore the importance of running simulations with multiple disturbances on the landscape concurrently rather than focusing on any one or two disturbances.


Copyright: © 2018 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.



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