Karen Garrett

Microbiome Networks: A Systems Framework for Identifying Candidate Microbial Assemblages for Disease Management

Network models of soil and plant microbiomes provide new opportunities for enhancing disease management, but also challenges for interpretation. We present a framework for interpreting microbiome networks, illustrating how observed network structures can be used to generate testable hypotheses about candidate microbes affecting plant health. The framework includes four types of network analyses. General network analysis identifies candidate taxa for maintaining an existing microbial community. Host-focused analysis includes a node representing a plant response such as yield, identifying taxa with direct or indirect associations with that node. Pathogen-focused analysis identifies taxa with direct or indirect associations with taxa known a priori as pathogens. Disease-focused analysis identifies taxa associated with disease. Positive direct or indirect associations with desirable outcomes, or negative associations with undesirable outcomes, indicate candidate taxa. Network analysis provides characterization not only of taxa with direct associations with important outcomes such as disease suppression, biofertilization, or expression of plant host resistance, but also taxa with indirect associations via their association with other key taxa. We illustrate the interpretation of network structure with analyses of microbiomes in the oak phyllosphere, and in wheat rhizosphere and bulk soil associated with the presence or absence of infection by Rhizoctonia solani.

Plant Pathogens as Indicators of Climate Change

Publisher Summary nPlant disease risk is strongly influenced by environmental conditions. While some animal hosts may provide their pathogens with a consistent range of body temperatures, plant pathogens are generally much more exposed to the elements. Plant diseases will tend to respond to climate change, though a number of interactions taking place among host, pathogen, and potential vectors. In some cases, the actions of land managers may also complicate interpretation of climate change effects. This chapter presents a brief introduction to plant diseases and a synthesis of research in plant pathology related to climate change. It discusses the types of evidence for climate change impacts that might be observed in plant disease systems and evaluates what evidence of climate change fingerprints currently exists. The battle against plant disease is not a new one, and plant disease management is essential to feed a growing human population. Plant pathogen groups include fungi, prokaryotes, oomycetes, viruses and viroids, nematodes, parasitic plants, and protozoa. The very different life histories of this diverse group of organisms and their different interactions with host plants produce a wide range of responses to environmental and climatic drivers. Pathogen species may quickly develop resistance to pesticides or adapt to overcome plant disease resistance, and may also adapt to environmental changes, where the rate of adaptation depends on the type of pathogen. Pathogen populations may explode when weather conditions are favorable for disease development. The potentially rapid onset of disease makes it difficult to anticipate the best timing of management measures, especially in areas with high levels of interannual variability in climatic conditions.

History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust.

Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.

Crop health and its global impacts on the components of food security

The literature on the importance of plant pathogens sometimes emphasizes their possible role in historical food shortages and even in famines. Aside from such major crises, plant pathogens should also be seen as important reducers of crop performances, with impacts on system sustainability, from the ecological, agronomical, social, and economic standpoints – all contributing ultimately to affecting food security. These views need reconciliation in order to produce a clearer picture of the multidimensional effects of plant disease epidemics. Such a picture is needed for disease management today, but would also be useful for future policies. This article attempts to develop a framework that would enable assessment of the impacts of plant diseases, referred collectively to as crop health, on food security via its components. We have combined three different existing definitions of food security in order to develop a framework consisting of the following six components: (1) Availability. Primary production; (2) Availability. Import - Stockpiles; (3) Access. Physical and supply chain; (4) Access. Economic; (5) Stability of food availability; (6) Utility-Safety-Quality-Nutritive value. In this framework, components of food security are combined with three attributes of production situations: the nature of the considered crop (i.e. food- or non-food), the structure of farms (i.e. subsistence or commercial), and the structure of markets (i.e. weakly organized and local, to strongly organized and globalized). The resulting matrix: [Food security components]xa0×xa0[Attributes of production situations] provides a framework where the impacts of chronic, acute, and emerging plant disease epidemics on food security can be examined. We propose that, given the number of components and interactions at play, a systems modelling approach is required to address the functioning of food systems exposed to plant disease risks. This approach would have application in both the management of the current attrition of crop performances by plant diseases, and also of possible disease-induced shocks. Such an approach would also enable quantifying shifts in disease vulnerability of production situations, and therefore, of food systems, as a result of climate change, globalization, and evolving crop health.

Epidemic Threshold of an SIS Model in Dynamic Switching Networks

In this paper, we analyze dynamic switching networks, wherein the networks switch arbitrarily among a set of topologies. For this class of dynamic networks, we derive an epidemic threshold, considering the susceptible-infected-susceptible epidemic model. First, an epidemic probabilistic model is developed assuming independence between states of nodes. We identify the conditions under which the epidemic dies out by linearizing the underlying dynamical system and analyzing its asymptotic stability around the origin. The concept of joint spectral radius is then used to derive the epidemic threshold, which is later validated using several networks (Watts-Strogatz, Barabasi-Albert, MIT reality mining graphs, Regular, and Gilbert). A simplified version of the epidemic threshold is proposed for undirected networks. Moreover, in the case of static networks, the derived epidemic threshold is shown to match conventional analytical results. Then, analytical results for the epidemic threshold of dynamic networks are proved to be applicable to periodic networks. For dynamic regular networks, we demonstrate that the epidemic threshold is identical to the epidemic threshold for static regular networks. An upper bound for the epidemic spread probability in dynamic Gilbert networks is also derived and verified using simulation.

Resistance Genes in Global Crop Breeding Networks

Resistance genes are a major tool for managing crop diseases. The networks of crop breeders who exchange resistance genes and deploy them in varieties help to determine the global landscape of resistance and epidemics, an important system for maintaining food security. These networks function as a complex adaptive system, with associated strengths and vulnerabilities, and implications for policies to support resistance gene deployment strategies. Extensions of epidemic network analysis can be used to evaluate the multilayer agricultural networks that support and influence crop breeding networks. Here, we evaluate the general structure of crop breeding networks for cassava, potato, rice, and wheat. All four are clustered due to phytosanitary and intellectual property regulations, and linked through CGIAR hubs. Cassava networks primarily include public breeding groups, whereas others are more mixed. These systems must adapt to global change in climate and land use, the emergence of new diseases, and disruptive breeding technologies. Research priorities to support policy include how best to maintain both diversity and redundancy in the roles played by individual crop breeding groups (public versus private and global versus local), and how best to manage connectivity to optimize resistance gene deployment while avoiding risks to the useful life of resistance genes. [Formula: see text] Copyright

Three pillars of sustainability in fisheries

Significance The United Nations proclaims that sustainable development comprises environmental, economic, and social sustainability. Fisheries contribute to livelihoods, food security, and human health worldwide; however, as the planet’s last major hunting and gathering industry, whether, and if so, how fishing can achieve all three pillars of sustainability is unclear. The relationships between environmental and economic sustainability, as well as between economic and social sustainability, continue to receive attention. We analyzed data from 121 fisheries worldwide to evaluate potential trade-offs. We found no evidence of trade-offs, and instead found that environmental, economic, and social objectives are complementary when fisheries are managed. Our results challenge the idea that the three pillars of sustainability are in conflict, suggesting that rights-based systems can be designed to support all three pillars. Sustainability of global fisheries is a growing concern. The United Nations has identified three pillars of sustainability: economic development, social development, and environmental protection. The fisheries literature suggests that there are two key trade-offs among these pillars of sustainability. First, poor ecological health of a fishery reduces economic profits for fishers, and second, economic profitability of individual fishers undermines the social objectives of fishing communities. Although recent research has shown that management can reconcile ecological and economic objectives, there are lingering concerns about achieving positive social outcomes. We examined trade-offs among the three pillars of sustainability by analyzing the Fishery Performance Indicators, a unique dataset that scores 121 distinct fishery systems worldwide on 68 metrics categorized by social, economic, or ecological outcomes. For each of the 121 fishery systems, we averaged the outcome measures to create overall scores for economic, ecological, and social performance. We analyzed the scores and found that they were positively associated in the full sample. We divided the data into subsamples that correspond to fisheries management systems with three categories of access—open access, access rights, and harvest rights—and performed a similar analysis. Our results show that economic, social, and ecological objectives are at worst independent and are mutually reinforcing in both types of managed fisheries. The implication is that rights-based management systems should not be rejected on the basis of potentially negative social outcomes; instead, social considerations should be addressed in the design of these systems.

Epidemic Network Analysis for Mitigation of Invasive Pathogens in Seed Systems: Potato in Ecuador

Seed systems have an important role in the distribution of high-quality seed and improved varieties. The structure of seed networks also helps to determine the epidemiological risk for seedborne disease. We present a new approach for evaluating the epidemiological role of nodes in seed networks, and apply it to a regional potato farmer consortium (Consorcio de Productores de Papa [CONPAPA]) in Ecuador. We surveyed farmers to estimate the structure of networks of farmer seed tuber and ware potato transactions, and farmer information sources about pest and disease management. Then, we simulated pathogen spread through seed transaction networks to identify priority nodes for disease detection. The likelihood of pathogen establishment was weighted based on the quality or quantity of information sources about disease management. CONPAPA staff and facilities, a market, and certain farms are priorities for disease management interventions such as training, monitoring, and variety dissemination. Advice from agrochemical store staff was common but assessed as significantly less reliable. Farmer access to information (reported number and quality of sources) was similar for both genders. However, women had a smaller amount of the market share for seed tubers and ware potato. Understanding seed system networks provides input for scenario analyses to evaluate potential system improvements. [Formula: see text] Copyright

Modeling Epidemics in Seed Systems to Guide Management Strategies: The Case of Sweetpotato in Northern Uganda

Seed systems are critical for deployment of improved varieties, but also serve as major conduits for the spread of seed-borne pathogens. We evaluated the structure of an informal sweetpotato seed system for its vulnerability to the spread of epidemics, and its utility for disseminating improved varieties. During the 2014 growing season, vine sellers were surveyed weekly in the Gulu Region of Northern Uganda. Our analysis draws on tools from network theory to evaluate the potential for epidemic spread in this region. Using empirical seed transaction data and estimated spatial spread, we constructed a network of seed and pathogen movement. We modeled the introduction of a pathogen, and evaluated the influence of both epidemic starting point and quarantine treatments on epidemic progress. Quarantine of 30 out of 99 villages reduced epidemic progress by up to 66%, when compared to the control (no quarantine), over 20 time steps. The starting position in the network was critical for epidemic progress and final epidemic outcomes, and influenced the percent control conferred by quarantine treatments. Considering equal likelihood of any node being an introduction point for a new epidemic, villages of particular utility for disease monitoring were identified. Sensitivity analysis identified important parameters and priorities for future data collection. The efficacy of node degree, closeness, and eigenvector centrality was similar for selecting quarantine locations, while betweenness had more limited utility. This analysis framework can be applied to provide recommendations for a wide variety of seed systems.Seed systems are critical for deployment of improved varieties, and serve as major conduits for the spread of seed-borne pathogens. Vegetatively propagated crops in low-income countries are particularly vulnerable to seed degeneration, where yield is lowered through successive cycles of propagation because of pathogen accumulation. We evaluated the structure of an informal sweetpotato seed system for its vulnerability to the spread of epidemics, and its utility for disseminating improved varieties. During the 2014 growing season (April-Oct), vine sellers were surveyed weekly in the Gulu Region of Northern Uganda. Our analysis draws on tools from network theory to evaluate the potential for epidemic spread in this region. Utilizing empirical 2014 seed transaction data and estimated spatial spread, we constructed a seed transaction network, which was used to simulate the introduction of a pathogen, and evaluated the influence of both epidemic starting point and quarantine treatments on epidemic progress. Results indicate that the starting position in the network is critical for epidemic progress and final epidemic outcomes. Quarantine of 30 villages lowered epidemic progress up to 65.7%, when compared to the control (no quarantine), over 20 timesteps in 500 realizations. The percent control conferred by quarantine treatments was also influenced by the epidemic starting point. Considering equal likelihood of any node being an introduction point for a new epidemic, villages of particular utility for disease monitoring were also identified. Sensitivity analysis identified important parameters and priorities for future data collection. We compared the utility of node degree, betweenness, closeness, and eigenvector centrality for selecting quarantine locations, finding that betweenness had more limited utility. This analysis pipeline can be applied to provide recommendations for a wide variety of seed systems.The structure of seed system networks provides important information about epidemic risk within the network. We evaluated the structure of a sweetpotato seed system in Northern Uganda in terms of its utility for distributing improved varieties and its vulnerability to the spread of potential seed-borne pathogens. Sweetpotato sellers were surveyed in the Gulu Region of Northern Uganda. Weekly vine sales transactions were tracked through the growing season (April-October) creating a robust dataset of planting material sales over time, including price, village sold to, volume, and information about the buyer and seller. From this dataset of known transactions and the distance between villages, a network of vine movement was constructed. In silico simulations of the introduction of a novel virus into the systems indicated the potential for rapid spread. Through simulation of multiple epidemic starting points, nodes of particular importance to disease sampling and mitigation were identified. This method can serve as an example, with potential to be used across a wide variety of seed systems.

Modeling Epidemics in Seed Systems: Sweetpotato in Northern Uganda

Seed systems are critical for deployment of improved varieties, but also serve as major conduits for the spread of seed-borne pathogens. We evaluated the structure of an informal sweetpotato seed system for its vulnerability to the spread of epidemics, and its utility for disseminating improved varieties. During the 2014 growing season, vine sellers were surveyed weekly in the Gulu Region of Northern Uganda. Our analysis draws on tools from network theory to evaluate the potential for epidemic spread in this region. Using empirical seed transaction data and estimated spatial spread, we constructed a network of seed and pathogen movement. We modeled the introduction of a pathogen, and evaluated the influence of both epidemic starting point and quarantine treatments on epidemic progress. Quarantine of 30 out of 99 villages reduced epidemic progress by up to 66%, when compared to the control (no quarantine), over 20 time steps. The starting position in the network was critical for epidemic progress and final epidemic outcomes, and influenced the percent control conferred by quarantine treatments. Considering equal likelihood of any node being an introduction point for a new epidemic, villages of particular utility for disease monitoring were identified. Sensitivity analysis identified important parameters and priorities for future data collection. The efficacy of node degree, closeness, and eigenvector centrality was similar for selecting quarantine locations, while betweenness had more limited utility. This analysis framework can be applied to provide recommendations for a wide variety of seed systems.Seed systems are critical for deployment of improved varieties, and serve as major conduits for the spread of seed-borne pathogens. Vegetatively propagated crops in low-income countries are particularly vulnerable to seed degeneration, where yield is lowered through successive cycles of propagation because of pathogen accumulation. We evaluated the structure of an informal sweetpotato seed system for its vulnerability to the spread of epidemics, and its utility for disseminating improved varieties. During the 2014 growing season (April-Oct), vine sellers were surveyed weekly in the Gulu Region of Northern Uganda. Our analysis draws on tools from network theory to evaluate the potential for epidemic spread in this region. Utilizing empirical 2014 seed transaction data and estimated spatial spread, we constructed a seed transaction network, which was used to simulate the introduction of a pathogen, and evaluated the influence of both epidemic starting point and quarantine treatments on epidemic progress. Results indicate that the starting position in the network is critical for epidemic progress and final epidemic outcomes. Quarantine of 30 villages lowered epidemic progress up to 65.7%, when compared to the control (no quarantine), over 20 timesteps in 500 realizations. The percent control conferred by quarantine treatments was also influenced by the epidemic starting point. Considering equal likelihood of any node being an introduction point for a new epidemic, villages of particular utility for disease monitoring were also identified. Sensitivity analysis identified important parameters and priorities for future data collection. We compared the utility of node degree, betweenness, closeness, and eigenvector centrality for selecting quarantine locations, finding that betweenness had more limited utility. This analysis pipeline can be applied to provide recommendations for a wide variety of seed systems.The structure of seed system networks provides important information about epidemic risk within the network. We evaluated the structure of a sweetpotato seed system in Northern Uganda in terms of its utility for distributing improved varieties and its vulnerability to the spread of potential seed-borne pathogens. Sweetpotato sellers were surveyed in the Gulu Region of Northern Uganda. Weekly vine sales transactions were tracked through the growing season (April-October) creating a robust dataset of planting material sales over time, including price, village sold to, volume, and information about the buyer and seller. From this dataset of known transactions and the distance between villages, a network of vine movement was constructed. In silico simulations of the introduction of a novel virus into the systems indicated the potential for rapid spread. Through simulation of multiple epidemic starting points, nodes of particular importance to disease sampling and mitigation were identified. This method can serve as an example, with potential to be used across a wide variety of seed systems.