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Common Factors Drive Disease and Coarse Woody Debris Dynamics in Forests Impacted by Sudden Oak Death
Authors:Richard C Cobb  Maggie N Chan  Ross K Meentemeyer  David M Rizzo
Institution:(1) Graduate Group in Ecology, University of California, One Shields Ave., Davis, California 95616, USA;(2) Department of Plant Pathology, University of California, One Shields Ave., Davis, California 95616, USA;(3) Department of Geography and Earth Sciences, University of North Carolina, 9201 University City Boulevard, Charlotte, North Carolina 28223, USA
Abstract:Disease ecology has made important steps in describing how epidemiological processes control the impact of pathogens on populations and communities but fewer field or theoretical studies address disease effects at the ecosystem level. We demonstrate that the same epidemiological mechanisms drive disease intensity and coarse woody debris (CWD) dynamics in natural forest ecosystems impacted by an emerging disease. Sudden oak death (causal agent, Phytophthora ramorum) has caused mortality of tanoak (Notholithocarpus densiflorus) on a spatial scale and rate comparable to other major North American forest diseases caused by invasive pathogens. In pathogen invaded stands, mean CWD masses were 22.4 Mg ha−1 of standing dead tanoak (snags) and 11.5 Mg ha−1 in logs compared to 0.27 and 1.16 Mg ha−1 of snags and logs in an uninvaded stand. Within invaded stands variation in CWD mass and accumulation rates were largely driven by the distribution of pre-disease tanoak biomass and the densities of infected tanoak and California bay laurel (Umbellularia californica) which jointly determine P. ramorum sporulation and disease emergence rates. In a narrow range of community and host characteristics sudden oak death can result in woody debris dynamics similar to discrete disturbances such as fire and forest harvest but it is more common to have lower maximum amounts with slower rates of accumulation than these better studied disturbances. Our results indicate that models of CWD dynamics need to integrate epidemiological processes to predict realistic ecosystem impacts and lead to management applications for forest pathogens.
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