Spatial estimation of the density and carbon content of host populations for Phytophthora ramorum in California and Oregon

Outbreak of the emerging infectious disease sudden oak death continues to threaten California and Oregon forests following introduction of the exotic plant pathogen Phytophthora ramorum. Identifying areas at risk and forecasting changes in forest carbon following disease outbreak requires an understanding of the geographical distribution of host populations, which is unknown. In this study, we quantify and map the population density and carbon contents of five key host species for P. ramorum in California and Oregon, including four hosts killed by the pathogen (Notholithocarpus densiflorus, Quercus agrifolia, Quercus kelloggii and Quercus chrysolepis) and the foliar host Umbellularia californica which supports high sporulation rates. We integrate multiple sources of vegetation data, assembled from sparsely distributed (regional-scale) forest inventory and analysis (FIA) plots and more densely distributed (landscape-scale) plots for monitoring sudden oak death, and develop spatial prediction models based on correlation with environmental variables and spatial dependencies in host abundance. We estimate that 1.8 billion N. densiflorus trees (68 Tg C) and 2.6 billion Quercus host trees (227 Tg C) occur across 3.9 and 17.7 million ha of their respective habitat. A total of 436 million U. californica trees (14 Tg C) occur across 4.2 million ha which frequently overlap with Quercus and N. densiflorus host populations. Combination of landscape-scale data with FIA data resulted in more accurate estimation of host populations and their carbon contents. Forests of northern California and southwest Oregon have the highest concentration of the most susceptible hosts along with climatic conditions that favor pathogen spread. This study represents the first spatially-explicit estimate of P. ramorum host populations and their carbon contents which exceed previously published estimates. Our results will inform landscape- to regional-scale models of disease dynamics and guide management decisions regarding ecosystem impacts including risk of C release following widespread tree mortality. (C) 2011 Elsevier B.V. All rights reserved.