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University of California Santa Cruz Responding to An UNIVERSITY OF CALIFORNIA SANTA CRUZ RESPONDING TO AN EMERGENT PLANT PEST-PATHOGEN COMPLEX ACROSS SOCIAL-ECOLOGICAL SCALES A dissertation submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in ENVIRONMENTAL STUDIES with an emphasis in ECOLOGY AND EVOLUTIONARY BIOLOGY by Shannon Colleen Lynch December 2020 The Dissertation of Shannon Colleen Lynch is approved: Professor Gregory S. Gilbert, chair Professor Stacy M. Philpott Professor Andrew Szasz Professor Ingrid M. Parker Quentin Williams Acting Vice Provost and Dean of Graduate Studies Copyright © by Shannon Colleen Lynch 2020 TABLE OF CONTENTS List of Tables iv List of Figures vii Abstract x Dedication xiii Acknowledgements xiv Chapter 1 – Introduction 1 References 10 Chapter 2 – Host Evolutionary Relationships Explain 12 Tree Mortality Caused by a Generalist Pest– Pathogen Complex References 38 Chapter 3 – Microbiome Variation Across a 66 Phylogeographic Range of Tree Hosts Affected by an Emergent Pest–Pathogen Complex References 110 Chapter 4 – On Collaborative Governance: Building Consensus on 180 Priorities to Manage Invasive Species Through Collective Action References 243 iii LIST OF TABLES Chapter 2 Table I Insect vectors and corresponding fungal pathogens causing 47 Fusarium dieback on tree hosts in California, Israel, and South Africa. Table II Phylogenetic signal for each host type measured by D statistic. 48 Table SI Native range and infested distribution of tree and shrub FD- 49 ISHB host species. Chapter 3 Table I Study site attributes. 124 Table II Mean and median richness of microbiota in wood samples 128 collected from FD-ISHB host trees. Table III Fungal endophyte-Fusarium in vitro interaction outcomes. 129 Table IV Bacterial endophyte-Fusarium in vitro interaction outcomes. 132 Table V Neutral bacterial endophyte-Fusarium in vitro interaction 133 outcomes. Table VI Linear discriminant functions of microbial communities in FD- 134 ISHB infested and non-infested Salix, Platanus, and Persea. Table VII Test classification accuracies for each predictive linear 136 discriminant analysis on testing samples. Table VIII Linear discriminant functions given by predictive discriminant 137 analyses of microbial communities in host species (Salix, Platanus, Quercus, and Persea). Table IX Linear discriminant functions given by predictive discriminant 138 analyses of microbial communities in FD-ISHB attacked and not-attacked trees. iv Table X Linear discriminant function given by predictive discriminant 138 analysis of microbial communities in Quercus in FD-ISHB infested and non-infested plots. Table SI Reference species from GenBank used for phylogenetic 139 analysis-based endophyte species identification. Table SII Counts of microbial taxa isolated across hosts. 152 Table SIII Linear discriminant functions of microbial communities in host 157 species (using rare or abundant taxa). Table SIV Linear discriminant functions given by predictive discriminant 158 analyses of microbial communities in samples collected from FD-ISHB attacked and not-attacked trees (using rare or abundant taxa). Table SV Linear discriminant function given by predictive discriminant 159 analysis of microbial communities isolated from Quercus in FD-ISHB infested and non-infested plots (using rare or abundant taxa). Table SVI Confusion matrices of host classification (using rare or 160 abundant taxa) Table SVII Confusion matrices of status classification for each host 161 species (using rare or abundant taxa). Table SVIII Studies that characterized wood-inhabiting fungal communities 162 in different tree host species. Table SIX Wood-inhabiting fungal taxa isolated from host species in 163 previous studies. Table SMI Fungal species used for the biological mock community 179 (BioMOck) DNA standard. Chapter 4 Table I Stakeholders that participated in this study. 251 Table II Executive and sub-committee chairs who facilitated 253 collaborative decision making in the present study. v Table III Collaborative actions that emerged from sub-committee 255 collaborations. vi LIST OF FIGURES Chapter 2 Figure 1 Representation of the expected phylogenetic effects on different 16 host types impacted by Fusarium dieback-invasive shot hole borers. Figure 2 Phylogenetic tree of families representing all examined tree 27 species. Figure 3 Phylogenetic distances for all species pairs of each host type. 28 Figure S1 Distribution of pairwise phylogenetic distances (PD) for 63 different subsets of host types. Figure S2 Empirical Cumulative Distribution Function (ECDF) of the 64 phylogenetic distance data for each host type from 0-800 Myr. Figure S3 Cumulative distribution of phylogenetic distances (CDPD) for 65 all species pairs of each host type from quantiles 1% to 15% after (a) the removal of gymnosperms from the non- competent host data and (b) the removal of South African species data. Chapter 3 Figure 1 A) Phylogeny of competent host species sampled in this study, 77 and B) pairwise phylogenetic distances for each host species. Figure 2 Representative outcomes of interactions between Fusarium spp. 81 and endophytes observed in vitro. Figure 3 Number of fungal families isolated from trees in FD-ISHB 86 infested and non-infested monitoring plots in Southern California. Figure 4 A) Number of genera within each order exhibiting different in 88 vitro interaction outcomes with Fusarium. B) Number of genera within each division. vii Figure 5 Number of bacteria families isolated from trees in FD-ISHB - 89 infested and non-infested monitoring plots. Figure 6 Plots of discriminant scores and confusion matrices for testing 93 samples given by linear discriminant functions for endophyte communities in FD-ISHB attacked and not- attacked Persea, Platanus, and Salix trees. Figure 7 Plots of discriminant scores and confusion matrices for testing 96 and training samples given by linear discriminant functions for endophyte communities among tree hosts. Figure 8 Predicted discriminant scores and confusion matrices for testing 99 samples given by the linear discriminant function for endophyte communities among FD-ISHB attacked and not- attacked Salix, Platanus, and Persea trees within infested plots. Figure 9 A) Predicted discriminant scores for testing samples given by 101 the linear discriminant function for endophyte communities in Quercus among FD-ISHB infested and non-infested plots and B) Confusion matrix. Figure S1a Pairwise comparisons of distance matrices used to calculate 170 NMDS scores in the mean phylogenetic distance (MPD), GUniFrac, and Bray-Curtis community dissimilarity metrics. Figure S1b Diagnostic plots comparing the Euclidean distances of NMDS 171 scores in the mean phylogenetic distance (MPD), GUniFrac, and Bray-Curtis community dissimilarity metrics. Figure S2 Plots of discriminant scores for testing and training samples 172 given by linear discriminant functions for endophyte communities among tree hosts. Figure S3 Predicted discriminant scores for testing samples given by the 173 linear discriminant function for endophyte communities among FD-ISHB attacked and not-attacked Salix, Platanus, and Persea trees within infested plots. Figure S4 Predicted discriminant scores for testing samples given by the 174 linear discriminant function for endophyte communities in Quercus among FD-ISHB infested and non-infested plots. viii Chapter 4 Figure 1 A model of collaborative governance developed by Emmerson 198 et al. (2012). ix Abstract RESPONDING TO AN EMERGENT PLANT PEST-PATHOGEN COMPLEX ACROSS SOCIAL-ECOLOGICAL SCALES by SHANNON COLLEEN LYNCH Responding effectively to accidental introductions of plant pests (e.g., fungi, bacteria, viruses, animals, plants) is complicated because timely and costly decisions must be made across social and ecological scales with limited information. In this dissertation, I provide an interdisciplinary framework that allows responsible institutions to respond quickly and effectively to an emerging, introduced, multi-host pest-pathogen complex using even minimal knowledge available about pest attributes. First, I take an evolutionary ecology approach and examine how the phylogenetic structure of host ranges of different pest-pathogen combinations can be used to predict likelihoods of establishment, spread, and impacts of Fusarium dieback - invasive shot hole borers (FD–ISHB) in the urban-wildland forests and avocado growing regions of Southern California, where the pest-pathogen complex has established after its introduction from Southeast Asia. Phylogenetic dispersion analysis on a comprehensive FD–ISHB host-range data set shows that the strength of the phylogenetic signal is progressively more pronounced for more severely affected host species. As a basis for risk analysis, this understanding helps plant health first responders assess how any polyphagous pest complex might behave when introduced x to novel environments with a new set of possible hosts, which in turn informs more efficient and cost-effective phytosanitary surveillance priorities. Second, I conduct a multivariate analysis of fungi and bacteria cultured from wood in a phylogenetically diverse set of live tree hosts to determine if the structure and composition of tree microbiomes is predictive of the likelihood or outcome of attack by FD–ISHB. I further explore interactions within the microbiome between endophytic microbes and the pathogen to identify potential opportunities and mechanisms to shape disease establishment and spread, and evaluate whether endogenous microbes could
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