C-RUI: Spatial Modeling of a Biological Invasion: the Spread of Sudden Oak Death and the Importance of Host Genetics, Environmental Forcings, and Community Structyre

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Biological invasions represent a major component of global environmental change.Invasions may lead to reduced biodiversity and often result in permanent alterations toecosystems.Invasive non-native plant pathogens have dramatically affected ecosystems in manyparts of the world.The mechanisms underlying dispersal of these pathogens and their ecologicalconsequences are critical issues for conservation and ecosystem management.Spatial pattern isa fundamental property of disease dynamics because it reflects the genetic heterogeneity andenvironmental forces acting on pathogen dispersal and life history.A multidisciplinary approachis required to solve the challenges of 1)incorporating fine-scale processes of pathogen dispersalinto landscape-level models and 2)integrating spatial variation in environmental factors and hostpopulation genetics with disease incidence.In this proposal,we describe research to analyze spatio-temporal dynamics ofPhytophthora ramorum,an emerging,and probably exotic,pathogen that causes a lethal diseaseof oaks and tanoaks in coastal California.This disease,known as Sudden Oak Death (SOD),hasreached epidemic levels in several counties.The proposal integrates spatial data on hostgenetics,community structure,and environmental variation with investigations of mechanismsunderlying spread of P.ramorum to model changes in the distribution of this plant disease acrossthe landscape.Model predictions will identify critical factors that influence the distribution ofSOD and provide forecasts of habitat loss in oak woodlands as a consequence of SOD.Thisproposal describes a multidisciplinary program to model the spread of a destructive plant diseaseand to predict its ecological consequences.Our objectives are not developed as discreteactivities for individual researchers,but rather a collaborative effort among researchers to attacka single problem.We aim to accomplish the following:1.Develop a statistically based model that predicts spatial patterns of SOD risk on thelandscape,based on relationships among several critical environmental factors.These factorsinclude proximity to previously infected locations,genetic background of host species,plantcommunity structure,landscape structure,abiotic conditions,and anthropogenic activities.2.Develop a mechanistic model that predicts spatial patterns of pathogen activity and hostsusceptibility based on empirical studies of pathogen dispersal between hosts on fine spatialscales and on environmental conditions conducive to pathogen reproduction and dispersal.3.Develop a model of SOD spread that integrates the most predictive components of thestatistical and mechanistic models.4.Foster participation of undergraduates in this cross-disciplinary research and integrate theresearch into the curriculum of core courses in the Departments of Biology and Geography atSonoma State University.Sonoma State University is located within 20 km of the study area,which is easilyaccessible to PI s and their students.Previous analyses of the relationship betweenenvironmental variation and SOD spread have concentrated on the most heavily impactedregions in Marin County where the pathogen has infected trees throughout the study area.Incontrast,the present study focuses on SOD spread into new areas that presently show no sign ofinfection.We believe that this approach will contribute substantially towards a greaterunderstanding of the biology of this pathogen and to our understanding of the ecology andgenetics of plant-pathogen interactions.The timing of this study will also ensure involvement bymotivated undergraduates at Sonoma State University who wish to participate in research thateveryone recognizes is of critical significance to the larger community.