Scaling up from greenhouse resistance to fitness in the field for a host of an emerging forest disease

Evolutionary Applications

Katherine J. Hayden¹  Matteo Garbelotto¹  Richard Dodd¹ 

[1] Environmental Science Policy, and Management, University of California, Berkeley, CA, USA

关键词: forest management;    generalized linear mixed models;    host–parasite interactions;    invasive species;    natural selection and contemporary evolution;    quantitative genetics;    sudden oak death;    survival analysis;   

DOI  :  10.1111/eva.12080

来源: Wiley

【 摘 要 】

Abstract

Forest systems are increasingly threatened by emergent, exotic diseases, yet management strategies for forest trees may be hindered by long generation times and scant background knowledge. We tested whether nursery disease resistance and growth traits have predictive value for the conservation of Notholithocarpus densiflorus, the host most susceptible to sudden oak death. We established three experimental populations to assess nursery growth and resistance to Phytophthora ramorum, and correlations between nursery-derived breeding values with seedling survival in a field disease trial. Estimates of nursery traits’ heritability were low to moderate, with lowest estimates for resistance traits. Within the field trial, survival likelihood was increased in larger seedlings and decreased with the development of disease symptoms. The seed-parent family wide likelihood of survival was likewise correlated with family predictors for size and resistance to disease in 2nd year laboratory assays, though not resistance in 1st year leaf assays. We identified traits and seedling families with increased survivorship in planted tanoaks, and a framework to further identify seed parents favored for restoration. The additive genetic variation and seedling disease dynamics we describe hold promise to refine current disease models and expand the understanding of evolutionary dynamics of emergent infectious diseases in highly susceptible hosts.

【 授权许可】

CC BY   
© 2013 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.