Publications
2016 |
Cunniffe, Nik J; Cobb, Richard C; Meentemeyer, Ross K; Rizzo, David M; Gilligan, Christopher A Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California Journal Article Proceedings of the National Academy of Sciences, 113 (20), pp. 5640-5645, 2016. Abstract | Links | BibTeX | Tags: constrained budget, landscape-scale stochastic epidemiological model, optimizing disease control, Phytophthora ramorum, risk aversion @article{Cunniffe2016, title = {Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California}, author = {Nik J. Cunniffe and Richard C. Cobb and Ross K. Meentemeyer and David M. Rizzo and Christopher A. Gilligan}, url = {http://www.pnas.org/content/113/20/5640 http://www.pnas.org/content/suppl/2016/04/27/1602153113.DCSupplemental}, doi = {10.1073/pnas.1602153113}, year = {2016}, date = {2016-05-17}, journal = {Proceedings of the National Academy of Sciences}, volume = {113}, number = {20}, pages = {5640-5645}, abstract = {Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that “front loading” the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide.}, keywords = {constrained budget, landscape-scale stochastic epidemiological model, optimizing disease control, Phytophthora ramorum, risk aversion}, pubstate = {published}, tppubtype = {article} } Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that “front loading” the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide. |
Cobb, Richard C; Meentemeyer, Ross K; Rizzo, David M Wildfire and Forest Disease Interaction Lead to Greater Loss of Soil Nutrients and Carbon Journal Article Oecologia, pp. 1-12, 2016. Abstract | Links | BibTeX | Tags: ecosystem disease impacts, invasive pathogens, nitrogen, Phytophthora ramorum, sudden oak death, tanoak @article{Cobb2016, title = {Wildfire and Forest Disease Interaction Lead to Greater Loss of Soil Nutrients and Carbon}, author = {Richard C. Cobb and Ross K. Meentemeyer and David M. Rizzo}, url = {http://link.springer.com/article/10.1007%2Fs00442-016-3649-7}, doi = {10.1007/s00442-016-3649-7}, year = {2016}, date = {2016-05-10}, journal = {Oecologia}, pages = {1-12}, abstract = {Fire and forest disease have significant ecological impacts, but the interactions of these two disturbances are rarely studied. We measured soil C, N, Ca, P, and pH in forests of the Big Sur region of California impacted by the exotic pathogen Phytophthora ramorum, cause of sudden oak death, and the 2008 Basin wildfire complex. In Big Sur, overstory tree mortality following P. ramorum invasion has been extensive in redwood and mixed evergreen forests, where the pathogen kills true oaks and tanoak (Notholithocarpus densiflorus). Sampling was conducted across a full-factorial combination of disease/no disease and burned/unburned conditions in both forest types. Forest floor organic matter and associated nutrients were greater in unburned redwood compared to unburned mixed evergreen forests. Post-fire element pools were similar between forest types, but lower in burned-invaded compared to burned-uninvaded plots. We found evidence disease-generated fuels led to increased loss of forest floor C, N, Ca, and P. The same effects were associated with lower %C and higher PO4-P in the mineral soil. Fire-disease interactions were linear functions of pre-fire host mortality which was similar between the forest types. Our analysis suggests that these effects increased forest floor C loss by as much as 24.4 and 21.3 % in redwood and mixed evergreen forests, respectively, with similar maximum losses for the other forest floor elements. Accumulation of sudden oak death generated fuels has potential to increase fire-related loss of soil nutrients at the region-scale of this disease and similar patterns are likely in other forests, where fire and disease overlap.}, keywords = {ecosystem disease impacts, invasive pathogens, nitrogen, Phytophthora ramorum, sudden oak death, tanoak}, pubstate = {published}, tppubtype = {article} } Fire and forest disease have significant ecological impacts, but the interactions of these two disturbances are rarely studied. We measured soil C, N, Ca, P, and pH in forests of the Big Sur region of California impacted by the exotic pathogen Phytophthora ramorum, cause of sudden oak death, and the 2008 Basin wildfire complex. In Big Sur, overstory tree mortality following P. ramorum invasion has been extensive in redwood and mixed evergreen forests, where the pathogen kills true oaks and tanoak (Notholithocarpus densiflorus). Sampling was conducted across a full-factorial combination of disease/no disease and burned/unburned conditions in both forest types. Forest floor organic matter and associated nutrients were greater in unburned redwood compared to unburned mixed evergreen forests. Post-fire element pools were similar between forest types, but lower in burned-invaded compared to burned-uninvaded plots. We found evidence disease-generated fuels led to increased loss of forest floor C, N, Ca, and P. The same effects were associated with lower %C and higher PO4-P in the mineral soil. Fire-disease interactions were linear functions of pre-fire host mortality which was similar between the forest types. Our analysis suggests that these effects increased forest floor C loss by as much as 24.4 and 21.3 % in redwood and mixed evergreen forests, respectively, with similar maximum losses for the other forest floor elements. Accumulation of sudden oak death generated fuels has potential to increase fire-related loss of soil nutrients at the region-scale of this disease and similar patterns are likely in other forests, where fire and disease overlap. |
Haas, Sarah E; Cushman, Hall J; Dillon, Whalen W; Rank, Nathan E; Rizzo, David M; Meentemeyer, Ross K Effects of individual, community and landscape drivers on the dynamics of a wildland forest epidemic Journal Article Ecology, 97 (3), pp. 649-660, 2016. Abstract | Links | BibTeX | Tags: diversity-disease risk, emerging infectious disease, landscape epidemiology, pathogen spillover, Phytophthora ramorum, seasonality, sudden oak death, survival analysis, time-varying covariate @article{Haas2016, title = {Effects of individual, community and landscape drivers on the dynamics of a wildland forest epidemic}, author = {Sarah E. Haas and J. Hall Cushman and Whalen W. Dillon and Nathan E. Rank and David M. Rizzo and Ross K. Meentemeyer}, url = {http://onlinelibrary.wiley.com/doi/10.1890/15-0767.1/epdf}, doi = {10.1890/15-0767.1}, year = {2016}, date = {2016-03-28}, journal = {Ecology}, volume = {97}, number = {3}, pages = {649-660}, abstract = {The challenges posed by observing host–pathogen–environment interactions across large geographic extents and over meaningful time scales limit our ability to understand and manage wildland epidemics. We conducted a landscape-scale, longitudinal study designed to analyze the dynamics of sudden oak death (an emerging forest disease caused by Phytophthora ramorum) across hierarchical levels of ecological interactions, from individual hosts up to the community and across the broader landscape. From 2004 to 2011, we annually assessed disease status of 732 coast live oak, 271 black oak, and 122 canyon live oak trees in 202 plots across a 275-km2 landscape in central California. The number of infected oak stems steadily increased during the eight-year study period. A survival analysis modeling framework was used to examine which level of ecological heterogeneity best predicted infection risk of susceptible oak species, considering variability at the level of individuals (species identity, stem size), the community (host density, inoculum load, and species richness), and the landscape (seasonal climate variability, habitat connectivity, and topographic gradients). After accounting for unobserved risk shared among oaks in the same plot, survival models incorporating heterogeneity across all three levels better predicted oak infection than did models focusing on only one level. We show that larger oak trees (especially coast live oak) were more susceptible, and that interannual variability in inoculum production by the highly infectious reservoir host, California bay laurel, more strongly influenced disease risk than simply the density of this important host. Concurrently, warmer and wetter rainy-season conditions in consecutive years intensified infection risk, presumably by creating a longer period of inoculum build-up and increased probability of pathogen spillover from bay laurel to oaks. Despite the presence of many alternate host species, we found evidence of pathogen dilution, where less competent hosts in species-rich communities reduce pathogen transmission and overall risk of oak infection. These results identify key parameters driving the dynamics of emerging infectious disease in California woodlands, while demonstrating how multiple levels of ecological heterogeneity jointly determine epidemic trajectories in wildland settings.}, keywords = {diversity-disease risk, emerging infectious disease, landscape epidemiology, pathogen spillover, Phytophthora ramorum, seasonality, sudden oak death, survival analysis, time-varying covariate}, pubstate = {published}, tppubtype = {article} } The challenges posed by observing host–pathogen–environment interactions across large geographic extents and over meaningful time scales limit our ability to understand and manage wildland epidemics. We conducted a landscape-scale, longitudinal study designed to analyze the dynamics of sudden oak death (an emerging forest disease caused by Phytophthora ramorum) across hierarchical levels of ecological interactions, from individual hosts up to the community and across the broader landscape. From 2004 to 2011, we annually assessed disease status of 732 coast live oak, 271 black oak, and 122 canyon live oak trees in 202 plots across a 275-km2 landscape in central California. The number of infected oak stems steadily increased during the eight-year study period. A survival analysis modeling framework was used to examine which level of ecological heterogeneity best predicted infection risk of susceptible oak species, considering variability at the level of individuals (species identity, stem size), the community (host density, inoculum load, and species richness), and the landscape (seasonal climate variability, habitat connectivity, and topographic gradients). After accounting for unobserved risk shared among oaks in the same plot, survival models incorporating heterogeneity across all three levels better predicted oak infection than did models focusing on only one level. We show that larger oak trees (especially coast live oak) were more susceptible, and that interannual variability in inoculum production by the highly infectious reservoir host, California bay laurel, more strongly influenced disease risk than simply the density of this important host. Concurrently, warmer and wetter rainy-season conditions in consecutive years intensified infection risk, presumably by creating a longer period of inoculum build-up and increased probability of pathogen spillover from bay laurel to oaks. Despite the presence of many alternate host species, we found evidence of pathogen dilution, where less competent hosts in species-rich communities reduce pathogen transmission and overall risk of oak infection. These results identify key parameters driving the dynamics of emerging infectious disease in California woodlands, while demonstrating how multiple levels of ecological heterogeneity jointly determine epidemic trajectories in wildland settings. |
Johnston, Steven F; Cohen, Michael F; Torok, Tamas; Meentemeyer, Ross K; Rank, Nathan E Host phenology and leaf effects on susceptibility of California bay laurel to Phytophthora ramorum Journal Article Phytopathology, 106 (1), pp. 47-55, 2016. Abstract | Links | BibTeX | Tags: California Bay Laurel, host phenology, leaf effects, Phytophthora ramorum, susceptibility, Umbellularia californica @article{Johnston2016, title = {Host phenology and leaf effects on susceptibility of California bay laurel to Phytophthora ramorum}, author = {Steven F. Johnston and Michael F. Cohen and Tamas Torok and Ross K. Meentemeyer and Nathan E. Rank}, url = {http://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-01-15-0016-R}, doi = {10.1094/PHYTO-01-15-0016-R}, year = {2016}, date = {2016-01-01}, journal = {Phytopathology}, volume = {106}, number = {1}, pages = {47-55}, abstract = {Spread of the plant pathogen Phytophthora ramorum, causal agent of the forest disease sudden oak death, is driven by a few competent hosts that support spore production from foliar lesions. The relationship between traits of a principal foliar host, California bay laurel (Umbellularia californica), and susceptibility to P. ramorum infection were investigated with multiple P. ramorum isolates and leaves collected from multiple trees in leaf-droplet assays. We examined whether susceptibility varies with season, leaf age, or inoculum position. Bay laurel susceptibility was highest during spring and summer and lowest in winter. Older leaves (>1 year) were more susceptible than younger ones (8 to 11 months). Susceptibility was greater at leaf tips and edges than the middle of the leaf. Leaf surfaces wiped with 70% ethanol were more susceptible to P. ramorum infection than untreated leaf surfaces. Our results indicate that seasonal changes in susceptibility of U. californica significantly influence P. ramorum infection levels. Thus, in addition to environmental variables such as temperature and moisture, variability in host plant susceptibility contributes to disease establishment of P. ramorum.}, keywords = {California Bay Laurel, host phenology, leaf effects, Phytophthora ramorum, susceptibility, Umbellularia californica}, pubstate = {published}, tppubtype = {article} } Spread of the plant pathogen Phytophthora ramorum, causal agent of the forest disease sudden oak death, is driven by a few competent hosts that support spore production from foliar lesions. The relationship between traits of a principal foliar host, California bay laurel (Umbellularia californica), and susceptibility to P. ramorum infection were investigated with multiple P. ramorum isolates and leaves collected from multiple trees in leaf-droplet assays. We examined whether susceptibility varies with season, leaf age, or inoculum position. Bay laurel susceptibility was highest during spring and summer and lowest in winter. Older leaves (>1 year) were more susceptible than younger ones (8 to 11 months). Susceptibility was greater at leaf tips and edges than the middle of the leaf. Leaf surfaces wiped with 70% ethanol were more susceptible to P. ramorum infection than untreated leaf surfaces. Our results indicate that seasonal changes in susceptibility of U. californica significantly influence P. ramorum infection levels. Thus, in addition to environmental variables such as temperature and moisture, variability in host plant susceptibility contributes to disease establishment of P. ramorum. |
2014 |
Dillon, Whalen W; Haas, Sarah E; Rizzo, David M; Meentemeyer, Ross K Perspectives of spatial scale in a wildland forest epidemic Journal Article European Journal of Plant Pathology, 138 (3), pp. 449-465, 2014, ISSN: 1573-8469. Abstract | Links | BibTeX | Tags: host density, landscape epidemiology, Phytophthora ramorum, sudden oak death @article{Dillon2014, title = {Perspectives of spatial scale in a wildland forest epidemic}, author = {Whalen W. Dillon and Sarah E. Haas and David M. Rizzo and Ross K. Meentemeyer}, url = {http://link.springer.com/article/10.1007%2Fs10658-013-0376-3}, doi = {10.1007/s10658-013-0376-3}, issn = {1573-8469}, year = {2014}, date = {2014-03-01}, journal = {European Journal of Plant Pathology}, volume = {138}, number = {3}, pages = {449-465}, abstract = {The challenge of observing interactions between plant pathogens, their hosts, and environmental heterogeneity across multiple spatial scales commonly limits our ability to understand and manage wildland forest epidemics. Using the forest pathogen Phytopthora ramorum as a case study, we established 20 multiscale field sites to analyze how host-pathogen-environment relationships vary across spatial scales of observation in a wildland pathosystem. We developed statistical models of disease intensity across five nested levels of spatial aggregation, from an individual host through four broader spatial extents of observation. Analyses were conducted from two spatial perspectives: a focal view, where disease intensity at one scale was examined as a function of broader-scale landscape conditions, and an aggregate view, where disease intensity and landscape conditions was observed at the same scale of spatial aggregation. For each perspective, separate models were developed to compare direct field measurements of host density versus less expensive remotely sensed estimates of host habitat as predictors of disease in landscape-scale studies. From both perspectives, models using direct measurements of host density performed better than models using remotely sensed estimates of host habitat across all four spatial extents. We found no significant difference in model performance at the individual level. From the focal view, the performance of host density models declined with increasing spatial extent, whereas the performance of host habitat models improved with spatial extent. These results illustrate how the scale of observation – both spatial extent and measurement detail – can influence conclusions drawn from epidemiological models of wildland pathosystems.}, keywords = {host density, landscape epidemiology, Phytophthora ramorum, sudden oak death}, pubstate = {published}, tppubtype = {article} } The challenge of observing interactions between plant pathogens, their hosts, and environmental heterogeneity across multiple spatial scales commonly limits our ability to understand and manage wildland forest epidemics. Using the forest pathogen Phytopthora ramorum as a case study, we established 20 multiscale field sites to analyze how host-pathogen-environment relationships vary across spatial scales of observation in a wildland pathosystem. We developed statistical models of disease intensity across five nested levels of spatial aggregation, from an individual host through four broader spatial extents of observation. Analyses were conducted from two spatial perspectives: a focal view, where disease intensity at one scale was examined as a function of broader-scale landscape conditions, and an aggregate view, where disease intensity and landscape conditions was observed at the same scale of spatial aggregation. For each perspective, separate models were developed to compare direct field measurements of host density versus less expensive remotely sensed estimates of host habitat as predictors of disease in landscape-scale studies. From both perspectives, models using direct measurements of host density performed better than models using remotely sensed estimates of host habitat across all four spatial extents. We found no significant difference in model performance at the individual level. From the focal view, the performance of host density models declined with increasing spatial extent, whereas the performance of host habitat models improved with spatial extent. These results illustrate how the scale of observation – both spatial extent and measurement detail – can influence conclusions drawn from epidemiological models of wildland pathosystems. |
2013 |
Metz, Margaret R; Varner, Morgan J; Frangioso, Kerri M; Meentemeyer, Ross K; Rizzo, David M Unexpected redwood mortality from synergies between wildfire and an emerging infectious disease Journal Article Ecology, 94 (10), pp. 2152-2159, 2013. Abstract | Links | BibTeX | Tags: biological invasions, global change, interacting disturbances, Phytophthora ramorum, Sequoia sempervirens, sudden oak death, synergy @article{Metz2013, title = {Unexpected redwood mortality from synergies between wildfire and an emerging infectious disease }, author = {Margaret R. Metz and J. Morgan Varner and Kerri M. Frangioso and Ross K. Meentemeyer and David M. Rizzo}, url = {http://dx.doi.org/10.1890/13-0915.1}, doi = {10.1890/13-0915.1}, year = {2013}, date = {2013-10-01}, journal = {Ecology}, volume = {94}, number = {10}, pages = {2152-2159}, abstract = {An under-examined component of global change is the alteration of disturbance regimes due to warming climates, continued species invasions, and accelerated land-use change. These drivers of global change are themselves novel ecosystem disturbances that may interact with historically occurring disturbances in complex ways. Here we use the natural experiment presented by wildfires in redwood forests impacted by an emerging infectious disease to demonstrate unexpected synergies of novel disturbance interactions. The dominant tree, coast redwood (fire resistant without negative disease impacts), experienced unexpected synergistic increases in mortality when fire and disease co-occurred. The increased mortality risk, more than fourfold at the peak of the effect, was not predictable from impacts of either disturbance alone. Changes in fire behavior associated with changes to forest fuels that occurred through disease progression overwhelmed redwood's usual resilience to wildfire. Our results demonstrate the potential for interacting disturbances to initiate novel successional trajectories and compromise ecosystem resilience.}, keywords = {biological invasions, global change, interacting disturbances, Phytophthora ramorum, Sequoia sempervirens, sudden oak death, synergy}, pubstate = {published}, tppubtype = {article} } An under-examined component of global change is the alteration of disturbance regimes due to warming climates, continued species invasions, and accelerated land-use change. These drivers of global change are themselves novel ecosystem disturbances that may interact with historically occurring disturbances in complex ways. Here we use the natural experiment presented by wildfires in redwood forests impacted by an emerging infectious disease to demonstrate unexpected synergies of novel disturbance interactions. The dominant tree, coast redwood (fire resistant without negative disease impacts), experienced unexpected synergistic increases in mortality when fire and disease co-occurred. The increased mortality risk, more than fourfold at the peak of the effect, was not predictable from impacts of either disturbance alone. Changes in fire behavior associated with changes to forest fuels that occurred through disease progression overwhelmed redwood's usual resilience to wildfire. Our results demonstrate the potential for interacting disturbances to initiate novel successional trajectories and compromise ecosystem resilience. |
Cobb, Richard C; Rizzo, David M; Hayden, Katherine J; Garbelotto, Matteo; Filipe, Joao; Gilligan, Christopher A; Dillon, Whalen W; Meentemeyer, Ross K; Valachovic, Yana S; Goheen, Ellen; Swiecki, Tedmund J; Hansen, Everett M; Frankel, Susan J Madrono, 60 (2), pp. 151-164, 2013. Abstract | Links | BibTeX | Tags: California Floristic Provence, disease ecology, genetic diversity, pathogen management, pathogen-caused extinction, Phytophthora ramorum, restoration, tanoak population decline @article{Cobb2013, title = {Biodiversity Conservation in the Face of Dramatic Forest Disease: An Integrated Conservation Strategy for Tanoak (Notholithocarpus densiflorus) Threatened by Sudden Oak Death}, author = {Richard C. Cobb and David M. Rizzo and Katherine J. Hayden and Matteo Garbelotto and Joao Filipe and Christopher A. Gilligan and Whalen W. Dillon and Ross K. Meentemeyer and Yana S. Valachovic and Ellen Goheen and Tedmund J. Swiecki and Everett M. Hansen and Susan J. Frankel}, url = {http://dx.doi.org/10.3120/0024-9637-60.2.151}, doi = {10.3120/0024-9637-60.2.151}, year = {2013}, date = {2013-04-01}, journal = {Madrono}, volume = {60}, number = {2}, pages = {151-164}, abstract = {Non-native diseases of dominant tree species have diminished North American forest biodiversity, structure, and ecosystem function over the last 150 years. Since the mid-1990s, coastal California forests have suffered extensive decline of the endemic overstory tree tanoak, Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon & S. H. Oh (Fagaceae), following the emergence of the exotic pathogen Phythophthora ramorum and the resulting disease sudden oak death. There are two central challenges to protecting tanoak: 1) the pathogen P. ramorum has multiple pathways of spread and is thus very difficult to eradicate, and 2) the low economic valuation of tanoak obscures the cultural and ecological importance of this species. However, both modeling and field studies have shown that pathogen-centric management and host-centric preventative treatments are effective methods to reduce rates of spread, local pathogen prevalence, and to increase protection of individual trees. These management strategies are not mutually exclusive, but we lack precise understanding of the timing and extent to apply each strategy in order to minimize disease and the subsequent accumulation of fuels, loss of obligate flora and fauna, or destruction of culturally important stands. Recent work identifying heritable disease resistance traits, ameliorative treatments that reduce pathogen populations, and silvicultural treatments that shift stand composition hold promise for increasing the resiliency of tanoak populations. We suggest distinct strategies for pathogen invaded and uninvaded areas, place these in the context of local management goals, and suggest a management strategy and associated research priorities to retain the biodiversity and cultural values associated with tanoak.}, keywords = {California Floristic Provence, disease ecology, genetic diversity, pathogen management, pathogen-caused extinction, Phytophthora ramorum, restoration, tanoak population decline}, pubstate = {published}, tppubtype = {article} } Non-native diseases of dominant tree species have diminished North American forest biodiversity, structure, and ecosystem function over the last 150 years. Since the mid-1990s, coastal California forests have suffered extensive decline of the endemic overstory tree tanoak, Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon & S. H. Oh (Fagaceae), following the emergence of the exotic pathogen Phythophthora ramorum and the resulting disease sudden oak death. There are two central challenges to protecting tanoak: 1) the pathogen P. ramorum has multiple pathways of spread and is thus very difficult to eradicate, and 2) the low economic valuation of tanoak obscures the cultural and ecological importance of this species. However, both modeling and field studies have shown that pathogen-centric management and host-centric preventative treatments are effective methods to reduce rates of spread, local pathogen prevalence, and to increase protection of individual trees. These management strategies are not mutually exclusive, but we lack precise understanding of the timing and extent to apply each strategy in order to minimize disease and the subsequent accumulation of fuels, loss of obligate flora and fauna, or destruction of culturally important stands. Recent work identifying heritable disease resistance traits, ameliorative treatments that reduce pathogen populations, and silvicultural treatments that shift stand composition hold promise for increasing the resiliency of tanoak populations. We suggest distinct strategies for pathogen invaded and uninvaded areas, place these in the context of local management goals, and suggest a management strategy and associated research priorities to retain the biodiversity and cultural values associated with tanoak. |
2011 |
Meentemeyer, Ross K; Cunniffe, Nik J; Cook, Alex R; Filipe, Joao A; Hunter, Richard D; Rizzo, David M; Gilligan, Christopher A Epidemiological modeling of invasion in heterogeneous landscapes: Spread of sudden oak death in California (1990-2030) Journal Article Ecosphere, 2 (art17), 2011. Abstract | Links | BibTeX | Tags: computational biology, emerging infectious disease, GIS, landscape epidemiology, Phytophthora ramorum, spatial heterogeneity, species distribution model @article{Meentemeyer2011, title = {Epidemiological modeling of invasion in heterogeneous landscapes: Spread of sudden oak death in California (1990-2030)}, author = {Ross K. Meentemeyer and Nik J. Cunniffe and Alex R. Cook and Joao A. Filipe and Richard D. Hunter and David M. Rizzo and Christopher A. Gilligan }, url = {http://dx.doi.org/10.1890/ES10-00192.1}, year = {2011}, date = {2011-02-16}, journal = {Ecosphere}, volume = {2}, number = {art17}, abstract = {The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-temporal, stochastic epidemiological modeling in combination with realistic geographical modeling to predict the spread of the sudden oak death pathogen (Phytophthora ramorum) through heterogeneous host populations in wildland forests, subject to fluctuating weather conditions. The model considers three stochastic processes: (1) the production of inoculum at a given site; (2) the chance that inoculum is dispersed within and among sites; and (3) the probability of infection following transmission to susceptible host vegetation. We parameterized the model using Markov chain Monte Carlo (MCMC) estimation from snapshots of local- and regional-scale data on disease spread, taking account of landscape heterogeneity and the principal scales of spread. Our application of the model to Californian landscapes over a 40-year period (1990–2030), since the approximate time of pathogen introduction, revealed key parameters driving the spatial spread of disease and the magnitude of stochastic variability in epidemic outcomes. Results show that most disease spread occurs via local dispersal (<250 m) but infrequent long-distance dispersal events can substantially accelerate epidemic spread in regions with high host availability and suitable weather conditions. In the absence of extensive control, we predict a ten-fold increase in disease spread between 2010 and 2030 with most infection concentrated along the north coast between San Francisco and Oregon. Long-range dispersal of inoculum to susceptible host communities in the Sierra Nevada foothills and coastal southern California leads to little secondary infection due to lower host availability and less suitable weather conditions. However, a shift to wetter and milder conditions in future years would double the amount of disease spread in California through 2030. This research illustrates how stochastic epidemiological models can be applied to realistic geographies and used to increase predictive understanding of disease dynamics in large, heterogeneous regions.}, keywords = {computational biology, emerging infectious disease, GIS, landscape epidemiology, Phytophthora ramorum, spatial heterogeneity, species distribution model}, pubstate = {published}, tppubtype = {article} } The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-temporal, stochastic epidemiological modeling in combination with realistic geographical modeling to predict the spread of the sudden oak death pathogen (Phytophthora ramorum) through heterogeneous host populations in wildland forests, subject to fluctuating weather conditions. The model considers three stochastic processes: (1) the production of inoculum at a given site; (2) the chance that inoculum is dispersed within and among sites; and (3) the probability of infection following transmission to susceptible host vegetation. We parameterized the model using Markov chain Monte Carlo (MCMC) estimation from snapshots of local- and regional-scale data on disease spread, taking account of landscape heterogeneity and the principal scales of spread. Our application of the model to Californian landscapes over a 40-year period (1990–2030), since the approximate time of pathogen introduction, revealed key parameters driving the spatial spread of disease and the magnitude of stochastic variability in epidemic outcomes. Results show that most disease spread occurs via local dispersal (<250 m) but infrequent long-distance dispersal events can substantially accelerate epidemic spread in regions with high host availability and suitable weather conditions. In the absence of extensive control, we predict a ten-fold increase in disease spread between 2010 and 2030 with most infection concentrated along the north coast between San Francisco and Oregon. Long-range dispersal of inoculum to susceptible host communities in the Sierra Nevada foothills and coastal southern California leads to little secondary infection due to lower host availability and less suitable weather conditions. However, a shift to wetter and milder conditions in future years would double the amount of disease spread in California through 2030. This research illustrates how stochastic epidemiological models can be applied to realistic geographies and used to increase predictive understanding of disease dynamics in large, heterogeneous regions. |
1. | Cunniffe, Nik J; Cobb, Richard C; Meentemeyer, Ross K; Rizzo, David M; Gilligan, Christopher A: Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California. In: Proceedings of the National Academy of Sciences, 113 (20), pp. 5640-5645, 2016. (Type: Journal Article | Abstract | Links | BibTeX) @article{Cunniffe2016, title = {Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California}, author = {Nik J. Cunniffe and Richard C. Cobb and Ross K. Meentemeyer and David M. Rizzo and Christopher A. Gilligan}, url = {http://www.pnas.org/content/113/20/5640 http://www.pnas.org/content/suppl/2016/04/27/1602153113.DCSupplemental}, doi = {10.1073/pnas.1602153113}, year = {2016}, date = {2016-05-17}, journal = {Proceedings of the National Academy of Sciences}, volume = {113}, number = {20}, pages = {5640-5645}, abstract = {Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that “front loading” the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that “front loading” the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide. |
2. | Cobb, Richard C; Meentemeyer, Ross K; Rizzo, David M: Wildfire and Forest Disease Interaction Lead to Greater Loss of Soil Nutrients and Carbon. In: Oecologia, pp. 1-12, 2016. (Type: Journal Article | Abstract | Links | BibTeX) @article{Cobb2016, title = {Wildfire and Forest Disease Interaction Lead to Greater Loss of Soil Nutrients and Carbon}, author = {Richard C. Cobb and Ross K. Meentemeyer and David M. Rizzo}, url = {http://link.springer.com/article/10.1007%2Fs00442-016-3649-7}, doi = {10.1007/s00442-016-3649-7}, year = {2016}, date = {2016-05-10}, journal = {Oecologia}, pages = {1-12}, abstract = {Fire and forest disease have significant ecological impacts, but the interactions of these two disturbances are rarely studied. We measured soil C, N, Ca, P, and pH in forests of the Big Sur region of California impacted by the exotic pathogen Phytophthora ramorum, cause of sudden oak death, and the 2008 Basin wildfire complex. In Big Sur, overstory tree mortality following P. ramorum invasion has been extensive in redwood and mixed evergreen forests, where the pathogen kills true oaks and tanoak (Notholithocarpus densiflorus). Sampling was conducted across a full-factorial combination of disease/no disease and burned/unburned conditions in both forest types. Forest floor organic matter and associated nutrients were greater in unburned redwood compared to unburned mixed evergreen forests. Post-fire element pools were similar between forest types, but lower in burned-invaded compared to burned-uninvaded plots. We found evidence disease-generated fuels led to increased loss of forest floor C, N, Ca, and P. The same effects were associated with lower %C and higher PO4-P in the mineral soil. Fire-disease interactions were linear functions of pre-fire host mortality which was similar between the forest types. Our analysis suggests that these effects increased forest floor C loss by as much as 24.4 and 21.3 % in redwood and mixed evergreen forests, respectively, with similar maximum losses for the other forest floor elements. Accumulation of sudden oak death generated fuels has potential to increase fire-related loss of soil nutrients at the region-scale of this disease and similar patterns are likely in other forests, where fire and disease overlap.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Fire and forest disease have significant ecological impacts, but the interactions of these two disturbances are rarely studied. We measured soil C, N, Ca, P, and pH in forests of the Big Sur region of California impacted by the exotic pathogen Phytophthora ramorum, cause of sudden oak death, and the 2008 Basin wildfire complex. In Big Sur, overstory tree mortality following P. ramorum invasion has been extensive in redwood and mixed evergreen forests, where the pathogen kills true oaks and tanoak (Notholithocarpus densiflorus). Sampling was conducted across a full-factorial combination of disease/no disease and burned/unburned conditions in both forest types. Forest floor organic matter and associated nutrients were greater in unburned redwood compared to unburned mixed evergreen forests. Post-fire element pools were similar between forest types, but lower in burned-invaded compared to burned-uninvaded plots. We found evidence disease-generated fuels led to increased loss of forest floor C, N, Ca, and P. The same effects were associated with lower %C and higher PO4-P in the mineral soil. Fire-disease interactions were linear functions of pre-fire host mortality which was similar between the forest types. Our analysis suggests that these effects increased forest floor C loss by as much as 24.4 and 21.3 % in redwood and mixed evergreen forests, respectively, with similar maximum losses for the other forest floor elements. Accumulation of sudden oak death generated fuels has potential to increase fire-related loss of soil nutrients at the region-scale of this disease and similar patterns are likely in other forests, where fire and disease overlap. |
3. | Haas, Sarah E; Cushman, Hall J; Dillon, Whalen W; Rank, Nathan E; Rizzo, David M; Meentemeyer, Ross K: Effects of individual, community and landscape drivers on the dynamics of a wildland forest epidemic. In: Ecology, 97 (3), pp. 649-660, 2016. (Type: Journal Article | Abstract | Links | BibTeX) @article{Haas2016, title = {Effects of individual, community and landscape drivers on the dynamics of a wildland forest epidemic}, author = {Sarah E. Haas and J. Hall Cushman and Whalen W. Dillon and Nathan E. Rank and David M. Rizzo and Ross K. Meentemeyer}, url = {http://onlinelibrary.wiley.com/doi/10.1890/15-0767.1/epdf}, doi = {10.1890/15-0767.1}, year = {2016}, date = {2016-03-28}, journal = {Ecology}, volume = {97}, number = {3}, pages = {649-660}, abstract = {The challenges posed by observing host–pathogen–environment interactions across large geographic extents and over meaningful time scales limit our ability to understand and manage wildland epidemics. We conducted a landscape-scale, longitudinal study designed to analyze the dynamics of sudden oak death (an emerging forest disease caused by Phytophthora ramorum) across hierarchical levels of ecological interactions, from individual hosts up to the community and across the broader landscape. From 2004 to 2011, we annually assessed disease status of 732 coast live oak, 271 black oak, and 122 canyon live oak trees in 202 plots across a 275-km2 landscape in central California. The number of infected oak stems steadily increased during the eight-year study period. A survival analysis modeling framework was used to examine which level of ecological heterogeneity best predicted infection risk of susceptible oak species, considering variability at the level of individuals (species identity, stem size), the community (host density, inoculum load, and species richness), and the landscape (seasonal climate variability, habitat connectivity, and topographic gradients). After accounting for unobserved risk shared among oaks in the same plot, survival models incorporating heterogeneity across all three levels better predicted oak infection than did models focusing on only one level. We show that larger oak trees (especially coast live oak) were more susceptible, and that interannual variability in inoculum production by the highly infectious reservoir host, California bay laurel, more strongly influenced disease risk than simply the density of this important host. Concurrently, warmer and wetter rainy-season conditions in consecutive years intensified infection risk, presumably by creating a longer period of inoculum build-up and increased probability of pathogen spillover from bay laurel to oaks. Despite the presence of many alternate host species, we found evidence of pathogen dilution, where less competent hosts in species-rich communities reduce pathogen transmission and overall risk of oak infection. These results identify key parameters driving the dynamics of emerging infectious disease in California woodlands, while demonstrating how multiple levels of ecological heterogeneity jointly determine epidemic trajectories in wildland settings.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The challenges posed by observing host–pathogen–environment interactions across large geographic extents and over meaningful time scales limit our ability to understand and manage wildland epidemics. We conducted a landscape-scale, longitudinal study designed to analyze the dynamics of sudden oak death (an emerging forest disease caused by Phytophthora ramorum) across hierarchical levels of ecological interactions, from individual hosts up to the community and across the broader landscape. From 2004 to 2011, we annually assessed disease status of 732 coast live oak, 271 black oak, and 122 canyon live oak trees in 202 plots across a 275-km2 landscape in central California. The number of infected oak stems steadily increased during the eight-year study period. A survival analysis modeling framework was used to examine which level of ecological heterogeneity best predicted infection risk of susceptible oak species, considering variability at the level of individuals (species identity, stem size), the community (host density, inoculum load, and species richness), and the landscape (seasonal climate variability, habitat connectivity, and topographic gradients). After accounting for unobserved risk shared among oaks in the same plot, survival models incorporating heterogeneity across all three levels better predicted oak infection than did models focusing on only one level. We show that larger oak trees (especially coast live oak) were more susceptible, and that interannual variability in inoculum production by the highly infectious reservoir host, California bay laurel, more strongly influenced disease risk than simply the density of this important host. Concurrently, warmer and wetter rainy-season conditions in consecutive years intensified infection risk, presumably by creating a longer period of inoculum build-up and increased probability of pathogen spillover from bay laurel to oaks. Despite the presence of many alternate host species, we found evidence of pathogen dilution, where less competent hosts in species-rich communities reduce pathogen transmission and overall risk of oak infection. These results identify key parameters driving the dynamics of emerging infectious disease in California woodlands, while demonstrating how multiple levels of ecological heterogeneity jointly determine epidemic trajectories in wildland settings. |
4. | Johnston, Steven F; Cohen, Michael F; Torok, Tamas; Meentemeyer, Ross K; Rank, Nathan E: Host phenology and leaf effects on susceptibility of California bay laurel to Phytophthora ramorum. In: Phytopathology, 106 (1), pp. 47-55, 2016. (Type: Journal Article | Abstract | Links | BibTeX) @article{Johnston2016, title = {Host phenology and leaf effects on susceptibility of California bay laurel to Phytophthora ramorum}, author = {Steven F. Johnston and Michael F. Cohen and Tamas Torok and Ross K. Meentemeyer and Nathan E. Rank}, url = {http://apsjournals.apsnet.org/doi/pdf/10.1094/PHYTO-01-15-0016-R}, doi = {10.1094/PHYTO-01-15-0016-R}, year = {2016}, date = {2016-01-01}, journal = {Phytopathology}, volume = {106}, number = {1}, pages = {47-55}, abstract = {Spread of the plant pathogen Phytophthora ramorum, causal agent of the forest disease sudden oak death, is driven by a few competent hosts that support spore production from foliar lesions. The relationship between traits of a principal foliar host, California bay laurel (Umbellularia californica), and susceptibility to P. ramorum infection were investigated with multiple P. ramorum isolates and leaves collected from multiple trees in leaf-droplet assays. We examined whether susceptibility varies with season, leaf age, or inoculum position. Bay laurel susceptibility was highest during spring and summer and lowest in winter. Older leaves (>1 year) were more susceptible than younger ones (8 to 11 months). Susceptibility was greater at leaf tips and edges than the middle of the leaf. Leaf surfaces wiped with 70% ethanol were more susceptible to P. ramorum infection than untreated leaf surfaces. Our results indicate that seasonal changes in susceptibility of U. californica significantly influence P. ramorum infection levels. Thus, in addition to environmental variables such as temperature and moisture, variability in host plant susceptibility contributes to disease establishment of P. ramorum.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Spread of the plant pathogen Phytophthora ramorum, causal agent of the forest disease sudden oak death, is driven by a few competent hosts that support spore production from foliar lesions. The relationship between traits of a principal foliar host, California bay laurel (Umbellularia californica), and susceptibility to P. ramorum infection were investigated with multiple P. ramorum isolates and leaves collected from multiple trees in leaf-droplet assays. We examined whether susceptibility varies with season, leaf age, or inoculum position. Bay laurel susceptibility was highest during spring and summer and lowest in winter. Older leaves (>1 year) were more susceptible than younger ones (8 to 11 months). Susceptibility was greater at leaf tips and edges than the middle of the leaf. Leaf surfaces wiped with 70% ethanol were more susceptible to P. ramorum infection than untreated leaf surfaces. Our results indicate that seasonal changes in susceptibility of U. californica significantly influence P. ramorum infection levels. Thus, in addition to environmental variables such as temperature and moisture, variability in host plant susceptibility contributes to disease establishment of P. ramorum. |
5. | Dillon, Whalen W; Haas, Sarah E; Rizzo, David M; Meentemeyer, Ross K: Perspectives of spatial scale in a wildland forest epidemic. In: European Journal of Plant Pathology, 138 (3), pp. 449-465, 2014, ISSN: 1573-8469. (Type: Journal Article | Abstract | Links | BibTeX) @article{Dillon2014, title = {Perspectives of spatial scale in a wildland forest epidemic}, author = {Whalen W. Dillon and Sarah E. Haas and David M. Rizzo and Ross K. Meentemeyer}, url = {http://link.springer.com/article/10.1007%2Fs10658-013-0376-3}, doi = {10.1007/s10658-013-0376-3}, issn = {1573-8469}, year = {2014}, date = {2014-03-01}, journal = {European Journal of Plant Pathology}, volume = {138}, number = {3}, pages = {449-465}, abstract = {The challenge of observing interactions between plant pathogens, their hosts, and environmental heterogeneity across multiple spatial scales commonly limits our ability to understand and manage wildland forest epidemics. Using the forest pathogen Phytopthora ramorum as a case study, we established 20 multiscale field sites to analyze how host-pathogen-environment relationships vary across spatial scales of observation in a wildland pathosystem. We developed statistical models of disease intensity across five nested levels of spatial aggregation, from an individual host through four broader spatial extents of observation. Analyses were conducted from two spatial perspectives: a focal view, where disease intensity at one scale was examined as a function of broader-scale landscape conditions, and an aggregate view, where disease intensity and landscape conditions was observed at the same scale of spatial aggregation. For each perspective, separate models were developed to compare direct field measurements of host density versus less expensive remotely sensed estimates of host habitat as predictors of disease in landscape-scale studies. From both perspectives, models using direct measurements of host density performed better than models using remotely sensed estimates of host habitat across all four spatial extents. We found no significant difference in model performance at the individual level. From the focal view, the performance of host density models declined with increasing spatial extent, whereas the performance of host habitat models improved with spatial extent. These results illustrate how the scale of observation – both spatial extent and measurement detail – can influence conclusions drawn from epidemiological models of wildland pathosystems.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The challenge of observing interactions between plant pathogens, their hosts, and environmental heterogeneity across multiple spatial scales commonly limits our ability to understand and manage wildland forest epidemics. Using the forest pathogen Phytopthora ramorum as a case study, we established 20 multiscale field sites to analyze how host-pathogen-environment relationships vary across spatial scales of observation in a wildland pathosystem. We developed statistical models of disease intensity across five nested levels of spatial aggregation, from an individual host through four broader spatial extents of observation. Analyses were conducted from two spatial perspectives: a focal view, where disease intensity at one scale was examined as a function of broader-scale landscape conditions, and an aggregate view, where disease intensity and landscape conditions was observed at the same scale of spatial aggregation. For each perspective, separate models were developed to compare direct field measurements of host density versus less expensive remotely sensed estimates of host habitat as predictors of disease in landscape-scale studies. From both perspectives, models using direct measurements of host density performed better than models using remotely sensed estimates of host habitat across all four spatial extents. We found no significant difference in model performance at the individual level. From the focal view, the performance of host density models declined with increasing spatial extent, whereas the performance of host habitat models improved with spatial extent. These results illustrate how the scale of observation – both spatial extent and measurement detail – can influence conclusions drawn from epidemiological models of wildland pathosystems. |
6. | Metz, Margaret R; Varner, Morgan J; Frangioso, Kerri M; Meentemeyer, Ross K; Rizzo, David M: Unexpected redwood mortality from synergies between wildfire and an emerging infectious disease . In: Ecology, 94 (10), pp. 2152-2159, 2013. (Type: Journal Article | Abstract | Links | BibTeX) @article{Metz2013, title = {Unexpected redwood mortality from synergies between wildfire and an emerging infectious disease }, author = {Margaret R. Metz and J. Morgan Varner and Kerri M. Frangioso and Ross K. Meentemeyer and David M. Rizzo}, url = {http://dx.doi.org/10.1890/13-0915.1}, doi = {10.1890/13-0915.1}, year = {2013}, date = {2013-10-01}, journal = {Ecology}, volume = {94}, number = {10}, pages = {2152-2159}, abstract = {An under-examined component of global change is the alteration of disturbance regimes due to warming climates, continued species invasions, and accelerated land-use change. These drivers of global change are themselves novel ecosystem disturbances that may interact with historically occurring disturbances in complex ways. Here we use the natural experiment presented by wildfires in redwood forests impacted by an emerging infectious disease to demonstrate unexpected synergies of novel disturbance interactions. The dominant tree, coast redwood (fire resistant without negative disease impacts), experienced unexpected synergistic increases in mortality when fire and disease co-occurred. The increased mortality risk, more than fourfold at the peak of the effect, was not predictable from impacts of either disturbance alone. Changes in fire behavior associated with changes to forest fuels that occurred through disease progression overwhelmed redwood's usual resilience to wildfire. Our results demonstrate the potential for interacting disturbances to initiate novel successional trajectories and compromise ecosystem resilience.}, keywords = {}, pubstate = {published}, tppubtype = {article} } An under-examined component of global change is the alteration of disturbance regimes due to warming climates, continued species invasions, and accelerated land-use change. These drivers of global change are themselves novel ecosystem disturbances that may interact with historically occurring disturbances in complex ways. Here we use the natural experiment presented by wildfires in redwood forests impacted by an emerging infectious disease to demonstrate unexpected synergies of novel disturbance interactions. The dominant tree, coast redwood (fire resistant without negative disease impacts), experienced unexpected synergistic increases in mortality when fire and disease co-occurred. The increased mortality risk, more than fourfold at the peak of the effect, was not predictable from impacts of either disturbance alone. Changes in fire behavior associated with changes to forest fuels that occurred through disease progression overwhelmed redwood's usual resilience to wildfire. Our results demonstrate the potential for interacting disturbances to initiate novel successional trajectories and compromise ecosystem resilience. |
7. | Cobb, Richard C; Rizzo, David M; Hayden, Katherine J; Garbelotto, Matteo; Filipe, Joao; Gilligan, Christopher A; Dillon, Whalen W; Meentemeyer, Ross K; Valachovic, Yana S; Goheen, Ellen; Swiecki, Tedmund J; Hansen, Everett M; Frankel, Susan J: Biodiversity Conservation in the Face of Dramatic Forest Disease: An Integrated Conservation Strategy for Tanoak (Notholithocarpus densiflorus) Threatened by Sudden Oak Death. In: Madrono, 60 (2), pp. 151-164, 2013. (Type: Journal Article | Abstract | Links | BibTeX) @article{Cobb2013, title = {Biodiversity Conservation in the Face of Dramatic Forest Disease: An Integrated Conservation Strategy for Tanoak (Notholithocarpus densiflorus) Threatened by Sudden Oak Death}, author = {Richard C. Cobb and David M. Rizzo and Katherine J. Hayden and Matteo Garbelotto and Joao Filipe and Christopher A. Gilligan and Whalen W. Dillon and Ross K. Meentemeyer and Yana S. Valachovic and Ellen Goheen and Tedmund J. Swiecki and Everett M. Hansen and Susan J. Frankel}, url = {http://dx.doi.org/10.3120/0024-9637-60.2.151}, doi = {10.3120/0024-9637-60.2.151}, year = {2013}, date = {2013-04-01}, journal = {Madrono}, volume = {60}, number = {2}, pages = {151-164}, abstract = {Non-native diseases of dominant tree species have diminished North American forest biodiversity, structure, and ecosystem function over the last 150 years. Since the mid-1990s, coastal California forests have suffered extensive decline of the endemic overstory tree tanoak, Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon & S. H. Oh (Fagaceae), following the emergence of the exotic pathogen Phythophthora ramorum and the resulting disease sudden oak death. There are two central challenges to protecting tanoak: 1) the pathogen P. ramorum has multiple pathways of spread and is thus very difficult to eradicate, and 2) the low economic valuation of tanoak obscures the cultural and ecological importance of this species. However, both modeling and field studies have shown that pathogen-centric management and host-centric preventative treatments are effective methods to reduce rates of spread, local pathogen prevalence, and to increase protection of individual trees. These management strategies are not mutually exclusive, but we lack precise understanding of the timing and extent to apply each strategy in order to minimize disease and the subsequent accumulation of fuels, loss of obligate flora and fauna, or destruction of culturally important stands. Recent work identifying heritable disease resistance traits, ameliorative treatments that reduce pathogen populations, and silvicultural treatments that shift stand composition hold promise for increasing the resiliency of tanoak populations. We suggest distinct strategies for pathogen invaded and uninvaded areas, place these in the context of local management goals, and suggest a management strategy and associated research priorities to retain the biodiversity and cultural values associated with tanoak.}, keywords = {}, pubstate = {published}, tppubtype = {article} } Non-native diseases of dominant tree species have diminished North American forest biodiversity, structure, and ecosystem function over the last 150 years. Since the mid-1990s, coastal California forests have suffered extensive decline of the endemic overstory tree tanoak, Notholithocarpus densiflorus (Hook. & Arn.) Manos, Cannon & S. H. Oh (Fagaceae), following the emergence of the exotic pathogen Phythophthora ramorum and the resulting disease sudden oak death. There are two central challenges to protecting tanoak: 1) the pathogen P. ramorum has multiple pathways of spread and is thus very difficult to eradicate, and 2) the low economic valuation of tanoak obscures the cultural and ecological importance of this species. However, both modeling and field studies have shown that pathogen-centric management and host-centric preventative treatments are effective methods to reduce rates of spread, local pathogen prevalence, and to increase protection of individual trees. These management strategies are not mutually exclusive, but we lack precise understanding of the timing and extent to apply each strategy in order to minimize disease and the subsequent accumulation of fuels, loss of obligate flora and fauna, or destruction of culturally important stands. Recent work identifying heritable disease resistance traits, ameliorative treatments that reduce pathogen populations, and silvicultural treatments that shift stand composition hold promise for increasing the resiliency of tanoak populations. We suggest distinct strategies for pathogen invaded and uninvaded areas, place these in the context of local management goals, and suggest a management strategy and associated research priorities to retain the biodiversity and cultural values associated with tanoak. |
8. | Meentemeyer, Ross K; Cunniffe, Nik J; Cook, Alex R; Filipe, Joao A; Hunter, Richard D; Rizzo, David M; Gilligan, Christopher A: Epidemiological modeling of invasion in heterogeneous landscapes: Spread of sudden oak death in California (1990-2030). In: Ecosphere, 2 (art17), 2011. (Type: Journal Article | Abstract | Links | BibTeX) @article{Meentemeyer2011, title = {Epidemiological modeling of invasion in heterogeneous landscapes: Spread of sudden oak death in California (1990-2030)}, author = {Ross K. Meentemeyer and Nik J. Cunniffe and Alex R. Cook and Joao A. Filipe and Richard D. Hunter and David M. Rizzo and Christopher A. Gilligan }, url = {http://dx.doi.org/10.1890/ES10-00192.1}, year = {2011}, date = {2011-02-16}, journal = {Ecosphere}, volume = {2}, number = {art17}, abstract = {The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-temporal, stochastic epidemiological modeling in combination with realistic geographical modeling to predict the spread of the sudden oak death pathogen (Phytophthora ramorum) through heterogeneous host populations in wildland forests, subject to fluctuating weather conditions. The model considers three stochastic processes: (1) the production of inoculum at a given site; (2) the chance that inoculum is dispersed within and among sites; and (3) the probability of infection following transmission to susceptible host vegetation. We parameterized the model using Markov chain Monte Carlo (MCMC) estimation from snapshots of local- and regional-scale data on disease spread, taking account of landscape heterogeneity and the principal scales of spread. Our application of the model to Californian landscapes over a 40-year period (1990–2030), since the approximate time of pathogen introduction, revealed key parameters driving the spatial spread of disease and the magnitude of stochastic variability in epidemic outcomes. Results show that most disease spread occurs via local dispersal (<250 m) but infrequent long-distance dispersal events can substantially accelerate epidemic spread in regions with high host availability and suitable weather conditions. In the absence of extensive control, we predict a ten-fold increase in disease spread between 2010 and 2030 with most infection concentrated along the north coast between San Francisco and Oregon. Long-range dispersal of inoculum to susceptible host communities in the Sierra Nevada foothills and coastal southern California leads to little secondary infection due to lower host availability and less suitable weather conditions. However, a shift to wetter and milder conditions in future years would double the amount of disease spread in California through 2030. This research illustrates how stochastic epidemiological models can be applied to realistic geographies and used to increase predictive understanding of disease dynamics in large, heterogeneous regions.}, keywords = {}, pubstate = {published}, tppubtype = {article} } The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-temporal, stochastic epidemiological modeling in combination with realistic geographical modeling to predict the spread of the sudden oak death pathogen (Phytophthora ramorum) through heterogeneous host populations in wildland forests, subject to fluctuating weather conditions. The model considers three stochastic processes: (1) the production of inoculum at a given site; (2) the chance that inoculum is dispersed within and among sites; and (3) the probability of infection following transmission to susceptible host vegetation. We parameterized the model using Markov chain Monte Carlo (MCMC) estimation from snapshots of local- and regional-scale data on disease spread, taking account of landscape heterogeneity and the principal scales of spread. Our application of the model to Californian landscapes over a 40-year period (1990–2030), since the approximate time of pathogen introduction, revealed key parameters driving the spatial spread of disease and the magnitude of stochastic variability in epidemic outcomes. Results show that most disease spread occurs via local dispersal (<250 m) but infrequent long-distance dispersal events can substantially accelerate epidemic spread in regions with high host availability and suitable weather conditions. In the absence of extensive control, we predict a ten-fold increase in disease spread between 2010 and 2030 with most infection concentrated along the north coast between San Francisco and Oregon. Long-range dispersal of inoculum to susceptible host communities in the Sierra Nevada foothills and coastal southern California leads to little secondary infection due to lower host availability and less suitable weather conditions. However, a shift to wetter and milder conditions in future years would double the amount of disease spread in California through 2030. This research illustrates how stochastic epidemiological models can be applied to realistic geographies and used to increase predictive understanding of disease dynamics in large, heterogeneous regions. |