NSF Award Abstract - #0217064

AWSFL008-DS3

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

Abstract

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