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Bacterial wilt, caused by the Ralstonia solanacearum species complex (RSSC), is the most destructive potato disease in Kenya. Studies were conducted to (i) determine the molecular diversity of RSSC strains associated with bacterial wilt of potato in Kenya, (ii) generate an RSSC distribution map for epidemiological inference, and (iii) determine whether phylotype II sequevar 1 strains exhibit epidemic clonality. Surveys were conducted in 2018 and 2019, in which tubers from wilting potato plants and stem samples of potential alternative hosts were collected for pathogen isolation. The pathogen was phylotyped by multiplex PCR and 536 RSSC strains typed at a sequevar level. Two RSSC phylotypes were identified, phylotype II (98.4%, n = 506 [sequevar 1 ( n = 505) and sequevar 2 ( n = 1)]) and phylotype I (1.6%, n = 30 [sequevar 13 ( n = 9) and a new sequevar ( n = 21)]). The phylotype II sequevar 1 strains were haplotyped using multilocus tandem repeat sequence typing (TRST) schemes. The TRST scheme identified 51 TRST profiles within the phylotype II sequevar 1 strains with a modest diversity index (HGDI = 0.87), confirming the epidemic clonality of RSSC phylotype II sequevar 1 strains in Kenya. A minimum spanning tree and mapping of the TRST profiles revealed that TRST27 ‘8-5-12-7-5’ is the primary founder of the clonal complex of RSSC phylotype II sequevar 1 and is widely distributed via latently infected seed tubers. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

The realized benefits of microbiome analyses for plant health and disease management are often limited by the lack of methods to select manageable and testable synthetic microbiomes. We evaluated the composition and diversity of root-associated fungal communities from grafted tomatoes.

Seed system network analysis can reveal exchange connections between stakeholders and test scenarios such as those of seed systems shocks. We investigated the seed exchange network structure, disease surveillance risk, and gender contribution in Burundi, under two banana disease risk scenarios. Two sites where banana bunchy top disease (BBTD) is endemic in Cibitoke Province were compared with a site free of the disease in Gitega Province. All sites had formal seed interventions using community nurseries. A quantitative survey on seed sharing was done followed by a qualitative evaluation through focus group discussions. Banana seed sourcing options were fewer in the disease-free site, which also had higher cultivar diversity. Most farmers sourced seed informally within a three-kilometer radius. Seed sharing within and between villages was based on social and family linkages, especially for women. The interaction between the formal system and informal seed exchange was more active where new cultivars, or better seed quality was expected. The BBTD endemic region had lower seed quality assessment stringency. Farmers used both direct mother plant assessment and seed source reputation in seed evaluation. The formal banana seed systems are sources of new varieties, and trusted for clean seed but the informal system was still used as a main source of seed, especially local cultivars. Assessing disease surveillance scenarios shows women in a weaker position for healthy seed acquisition. Identifying the roles of individuals in seed systems can support decision processes for seed interventions in vegetatively propagated crops.

Despite the numerous benefits plants receive from probiotics, maintaining consistent results across applications is still a challenge. Cultivation-independent methods associated with reduced sequencing costs have considerably improved the overall understanding of microbial ecology in the plant environment. As a result, now it is possible to engineer a consortium of microbes aiming for improved plant health. Such synthetic microbial communities (SynComs) contain carefully chosen microbial species to produce the desired microbiome function. Microbial biofilm formation, production of secondary metabolites and ability to induce plant resistance are some of the microbial traits to take into consideration when designing SynComs. Plant-associated microbial communities are not assembled randomly. Ecological theories suggest that these communities have a defined phylogenetic organization structured by general community assembly rules. Using machine learning, we can study these rules and target microbial functions that generate desired plant phenotypes. Well-structured assemblages are more likely to lead to a stable SynCom that thrives under environmental stressors, as compared to the classical selection of single microbial activities or taxonomy. However, ensuring microbial colonization and long-term plant phenotype stability are still some of the challenges to overcome with SynComs, as the synthetic community may change over time with microbial horizontal gene transfer and retained mutations. Here, we explored the advances made in SynCom research regarding plant health focusing on bacteria, as they are the most dominant microbial form compared with other members of the microbiome and the most commonly found in SynCom studies.

Modern agricultural practices increase the potential for plant pathogen spread, while the advent of affordable whole genome sequencing enables in-depth studies of pathogen movement. Population genomic studies may decipher pathogen movement and population structure as a result of complex agricultural production systems. We used whole genome sequences of 281 Xanthomonas perforans strains collected within one tomato production season across Florida and southern Georgia fields to test for population genetic structure associated with tomato production system variables. We identified six clusters of X. perforans from core gene SNPs that corresponded with phylogenetic lineages. Using whole genome SNPs, we found genetic structure among farms, transplant facilities, cultivars, seed producers, grower operations, regions, and counties. Overall, grower operations that produced their own transplants were associated with genetically distinct and less diverse populations of strains compared to grower operations that received transplants from multiple sources. The degree of genetic differentiation among components of Florida’s tomato production system varied between clusters, suggesting differential dispersal of the strains, such as through seed or contaminated transplants versus local movement within farms. Overall, we showed that the genetic variation of a bacterial plant pathogen is shaped by the structure of the plant production system.

Climate change already challenges people?s livelihood globally and it also affects plant health. Rising temperatures facilitate the introduction and establishment of unwanted organisms, including arthropods, pathogens, and weeds (hereafter collectively called pests). For example, a single, unusually warm winter under temperate climatic conditions may be sufficient to assist the establishment of invasive plant pests, which otherwise would not be able to establish. In addition, the increased market globalization and related transport of recent years, coupled with increased temperatures, has led to favorable conditions for pest movement, invasion, and establishment worldwide. Most published studies indicate that, in general, pest risk will increase in agricultural ecosystems under climate-change scenarios, especially in today?s cooler arctic, boreal, temperate, and subtropical regions. This is also mostly true for forestry. Some pests have already expanded their host range or distribution, at least in part due to changes in climate. Examples of these pests, selected according to their relevance in different geographical areas, are summarized here. The main pathways used by them, directly and/or indirectly, are also discussed. Understanding these path-ways can support decisions about mitigation and adaptation measures. The review concludes that preventive mitigation and adaptation measures, including biosecurity, are key to reducing the projected increases in pest risk in agriculture, horticulture, and forestry. Therefore, the sustainable management of pests is urgently needed. It requires holistic solutions, including effective phytosanitary regulations, globally coordinated diagnostic and surveillance systems, pest risk modeling and analysis, and preparedness for pro-active management. Made available in DSpace on 2022-09-29T17:05:20Z (GMT). No. of bitstreams: 1 Climate-change-and-pathways-used-by-pests-as-challenges-to-plant-health-in-agriculture-and-forestry-2022.pdf: 461955 bytes, checksum: 6cdb6958897691a0c6b9962fc1a6f01f (MD5) Previous issue date: 2022

The success of intervention projects in ecological systems depends not only on the quality of management technologies, but also patterns of adoption among land managers. Impact network analysis (INA) is a new framework for evaluating the likely success of regional interventions before, during, and after projects, for project implementers, policy makers, and funders. INA integrates across three key system components in a multilayer network analysis: (a) the quality of a management technology and the quality of research supporting it, (b) the socioeconomic networks through which managers learn about management technologies and decide whether to use them, and (c) the linked biophysical network for target species success or failure in the management landscape that results from managers’ decisions. The specific objectives of this paper are (1) to introduce the INA framework and INA R package, (2) to illustrate identification of key nodes for smart surveillance, for networks where the likelihood of invasive species entry into the biophysical network at a given node may be based on information available to the corresponding node in the socioeconomic network, (3) to illustrate application of the INA framework for evaluating the likely degree of success of a project in intervention ecology, before, during and after an intervention, and (4) to illustrate the use of INA for evaluating adaptation strategies under global change scenarios with pulse and press stressors, introducing ‘adaptation functions’ for sustainability and resilience. Examples of use of the INA package show one of the key outcomes of analyses: identifying when systems may be non-responsive to the system components that are readily changed through management decisions, to explore what additional adaptations may be necessary for intervention success. The broader goal for the development of impact network analysis and the INA package is to provide a common framework that integrates across intervention ecology, to enhance opportunities for lessons learned across systems and scientific disciplines, to support the development of a community of practice, and to create a general platform for analysis of sustainability, resilience, and economic viability in intervention ecology applications.

Before 1991, Xanthomonas euvesicatoria was the causal agent of bacterial spot of tomato in Florida but was quickly replaced by X. perforans. The X. perforans population has changed in genotype and phenotype despite lack of a clear selection pressure. To determine the current Xanthomonas population in Florida, we collected 585 Xanthomonas strains from 70 tomato fields, representing 22 farms across eight counties, in the Florida tomato production region. Strains were isolated from 23 cultivars across eight seed producers and were associated with eight transplant facilities during the fall 2017 season. Our collection was phenotypically and genotypically characterized. Only X. perforans was identified, and all strains except one (99.8%) were tolerant to copper sulfate and 25% of strains were resistant to streptomycin sulfate. Most of the strains (99.3%) that were resistant to streptomycin sulfate were sequence type 1. The X. perforans population consisted of tomato races 3 (8%) and 4 (92%) and all three previously reported sequence types, ranging from 22 to 46% frequency. Approximately half of all strains, none of which were sequence type 2, produced bacteriocins against X. euvesicatoria. Effector profiles were highly variable among strains, which could impact the strains’ host range. The effector xopJ4, which was previously thought to be conserved in X. perforans tomato pathogens, was absent in 19 strains. Nonmetric multidimensional scaling and network analyses show how strains and strain traits were associated with production system variables, including anonymized farms and transplant facilities. These analyses show that the composition of the Florida X. perforans population is diverse and complex.

Seed systems research is central to achieving the United Nations Sustainable Development Goals. Improved varieties with promise for ending hunger, improving nutrition, and increasing livelihood security may be released, but how do they reach and benefit different types of farmers? Without widespread adoption the genetic gains achieved with improved crop varieties can never be actualized. Progress has been made toward demand responsive breeding, however the draft CGIAR 2030 Research and Innovation Strategy fails to recognize the complexity of seed systems and thus presents a narrow vision for the future of seed systems research. This points to the lack of evidence-based dialogue between seed systems researchers and breeders. This perspective paper presents findings from an interdisciplinary group of more than 50 CGIAR scientists who used a suite of seed systems tools to identify four knowledge gaps and associated insights from work on the seed systems for vegetatively propagated crops (VPCs), focusing on bananas (especially cooking bananas and plantains), cassava, potato, sweetpotato, and yam. We discuss the implications for thinking about and intervening in seed systems using a combined biophysical and socioeconomic perspective and how this can contribute to increased varietal adoption and benefits to farmers. The tools merit wider use, not only for the seed systems of VPCs, but for the seed of crops facing similar adoption challenges. We argue for deeper collaboration between seed systems researchers, breeders and national seed system stakeholders to address these and other knowledge gaps and generate the evidence and innovations needed to break through the 40% adoption ceiling for modern varieties, and ensure good quality seed once the new varieties have been adopted. Without this, the achievements of breeders may remain stuck in the seed delivery pipeline.

The geographic pattern of cropland is an important risk factor for invasion and saturation by crop-specific pathogens and arthropods. Understanding cropland networks supports smart pest sampling and mitigation strategies. We evaluate global networks of cropland connectivity for key vegetatively propagated crops (banana and plantain, cassava, potato, sweet potato, and yam) important for food security in the tropics. For each crop, potential movement between geographic location pairs was evaluated using a gravity model, with associated uncertainty quantification. The highly linked hub and bridge locations in cropland connectivity risk maps are likely priorities for surveillance and management, and for tracing intraregion movement of pathogens and pests. Important locations are identified beyond those locations that simply have high crop density. Cropland connectivity risk maps provide a new risk component for integration with other factors—such as climatic suitability, genetic resistance, and global trade routes—to inform pest risk assessment and mitigation.

It is well documented that rice paddy fields act as agricultural wetlands that remove or retain nutrients; however, their associated effects on soil microbial communities are rarely reported. The present study evaluates the impact of rice variety on nutrient removal via plant uptake, nutrient retention in the soil, and bacterial associations in rice paddy fields, using a network analysis that compares the soil bacterial communities of two rice varieties. We found that the high-straw rice variety (YD-1) allows uptake of a high amount of nitrogen (N) and phosphorus (P) from paddy rice fields via harvesting, but causes less residual total N and P to remain in the soil. However, both rice varieties (YD-1 and XS-134 (Xiushui-134)) had non-significant effects on the dominant bacterial taxa. The short-term response of bacterial community diversity to rice variety is found to be mainly due to less frequently recovered species. A network analysis that incorporates soil nutrients as nodes, along with bacterial taxa, found that only one node representing the total P related to the non-dominant species had an indirect association with the rice straw biomass. The observed short-term impact of the two rice varieties (XS-134 and YD-1) on soil bacterial diversity and nutrient surplus in these agricultural wetlands is limited under a high level of fertilization.

Potato seed systems in Kenya are largely informal, characterized by high seed degeneration due to the buildup of seed- and soil-borne diseases, including bacterial wilt caused by Ralstonia solanacearum . Informal sources of seed include neighbors, local markets and farmer-saved seed, and present a risk for spread and establishment of disease. To understand the larger context of potato disease risk in Kenya, we used network analysis to evaluate (1) epidemic risk through potato trade networks centered around East Africa, and (2) locations in East Africa likely to be particularly important for epidemic management because of their high potato cropland connectivity. We evaluated the interactions of the key stakeholders in a potato seed system and used network analysis to identify locations that are likely to be important for the spread of infection of R. solanacearum in a potato seed distribution network in Meru, Kenya. Household details, seed sources, quantities sold, pest incidence and management practices, knowledge about seed degeneration and farmers' sources of information on potato production were obtained and analyzed. The survey revealed that self-saved, neighbors, seed companies, friends, exchange, and markets are the main seed sources. Only 43% of total seed transacted was certified. Users of uncertified seeds have high disease risk, and this is an especially important risk if their roles in the network give them the potential to be 'superspreaders' of disease.

CONTEXT: Studies in the Andes have demonstrated that seed degeneration of potato occurred in experimental conditions, but was negligible in farmers' conditions. There are two hypotheses for this difference: (1) farmers cultivate resistant varieties, or (2) they use on-farm practices that can manage seed degeneration. Farmers may replace some of the seed saved from their fields with outside seed, but it is an open question what level of benefit farmers experience from partial replacement. OBJECTIVES: The objective of this study was to investigate the role of the cultivated varieties, the on-farm seed management practices, and seed replacement in potato seed degeneration. Moreover, this study evaluated the potential effect of partial replacement of the farmers' seed lot each season with healthy seed, compared to less frequent nearly full replacement, in simulations. METHODS: We surveyed farmers in the Cotopaxi province, Ecuador, in 2008, 2010, and 2018, and performed a study on the incidence of pathogens and pests in farmers' seed lots in 2018. We also evaluated the potential effects of the timing of replacement of farmers' seed lots by healthy seed to manage degeneration, applying the seedHealth model. RESULTS AND CONCLUSIONS: We found that farmers experience no or only slow degeneration in their varieties. Analysing yield data reported by farmers to detect degeneration, we did not detect yield declines. The type of variety and year of data collection explained the variation in yield. These results seem to confirm the hypothesis that varieties cultivated in the Andes are resistant to the impact of seed degeneration on yield, and that seed degeneration depends on the agroecological conditions present within a cropping season or year. Because we did not find an impact on yield, we hypothesized that on-farm practices affect seed-borne pathogens and pests causing seed degeneration. We identified multiple on-farm practices playing a role in the process of seed degeneration: they either slowed down or accelerated this process depending on the seed-borne pathogen and pest causing seed degeneration. Our scenario analyses using the seedHealth model showed how replacing farmers' seed lots by healthy seed could usefully reduce seed degeneration compared to using the same amount of seed to periodically replace nearly all seed in a season. Our results showed that on-farm practices are also critical drivers in the process of seed degeneration. SIGNIFICANCE: This study demonstrated the importance of considering on-farm seed management practices (i.e., use of cultivated varieties) to strengthen seed systems interventions aiming to manage potato seed degeneration. Additionally, this study showed the potential of partially replacing farmers' seed with healthy seed as an alternative when complete seed replacement is not an option.

Root, tuber, and banana (RT&B) crops are critical for global food security. They are vegetatively propagated crops (VPCs) sharing common features: low reproductive rates, bulky planting materials, and vulnerability to accumulating and spreading pathogens and pests through seed. These crops are difficult to breed, so new varieties may be released slowly relative to new emerging threats. VPC seed systems are complex and face several challenges: poor-quality seed of existing varieties, low adoption rates of improved varieties, and slow varietal turnover, limiting yield increases and farmers’ ability to adapt to new threats and opportunities. Addressing these challenges requires first identifying key knowledge gaps on seed systems to guide research for development in a holistic and coherent way. Working together across 10 crops and 26 countries in Africa, Asia, and Central and South America, the CGIAR seed systems research community has developed a “Toolbox for Working with Root, Tuber, and Banana Seed Systems,” which introduces 11 tools and a glossary to address four major gaps: (1) capturing the demand characteristics of different types of farmers; (2) identifying effective seed delivery pathways; (3) ensuring seed health and stopping the spread of disease; and (4) designing effective policies and regulations. We describe the toolbox and its creation and validation across 76 crop-and-country use cases, and illustrate how the tools, applied individually or in combination, are addressing the key knowledge gaps in RT&B seed systems. The tool developers are actively working to scale the toolbox, including identifying new partners and models for collaboration, developing new tools, and supporting new applications in VPCs, as well as for fruit, vegetable, grain, and pulse seed systems.

Policymakers and donors often need to identify the locations where technologies are most likely to have important effects, to increase the benefits from agricultural development or extension efforts. Higher-quality information may help to target the high-benefit locations, but often actions are needed with limited information. The value of information (VOI) in this context is formalized by evaluating the results of decision making guided by a set of specific information compared with the results of acting without considering that information. We present a framework for management performance mapping that includes evaluating the VOI for decision making about geographic priorities in regional intervention strategies, in case studies of Andean and Kenyan potato seed systems. We illustrate the use of recursive partitioning, XGBoost, and Bayesian network models to characterize the relationships among seed health and yield responses and environmental and management predictors used in studies of seed degeneration. These analyses address the expected performance of an intervention based on geographic predictor variables. In the Andean example, positive selection of seed from asymptomatic plants was more effective at high altitudes in Ecuador. In the Kenyan example, there was the potential to target locations with higher technology adoption rates and with higher potato cropland connectivity, i.e., a likely more important role in regional epidemics. Targeting training to high management performance areas would often provide more benefits than would random selection of target areas. We illustrate how assessing the VOI can contribute to targeted development programs and support a culture of continuous improvement for interventions. [Formula: see text] Copyright © 2022 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Climate change represents an unprecedented challenge to the world?s biosphere and to the global community. It also represents a unique challenge for plant health. Human activities and increased market globalization, coupled with rising temperatures, has led to a situation that is favourable to pest movement and establishment. This summary for policy makers drawn from the FAO scientific review on the impact of climate change on plant pests, and by extension, on plant health provides concrete recommendations for decision makers on how to address the impact of climate change on plant health. The evidence assessed strongly indicates that climate change has already expanded some pests? host range and geographical distribution, and may further increase the risk of pest introduction to new areas. Increased international cooperation and development of harmonized plant protection strategies are crucial to help countries successfully adapt their pest risk management measures to climate change.

Climate change represents an unprecedented challenge to the world?s biosphere and to the global community. It also represents a unique challenge for plant health. Human activities and increased market globalization, coupled with rising temperatures, has led to a situation that is favourable to pest movement and establishment. This scientific review assesses the potential effects of climate change on plant pests and consequently on plant health. The evidence assessed strongly indicates that climate change has already expanded some pests? host range and geographical distribution, and may further increase the risk of pest introduction to new areas. This calls for international cooperation and development of harmonized plant protection strategies to help countries successfully adapt their pest risk management measures to climate change.

Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover, and evolution of new pathogen lineages. In order to tackle these grand challenges, a new set of tools that include disease surveillance and improved detection technologies including pathogen sensors and predictive modeling and data analytics are needed to prevent future outbreaks. Herein, we describe an integrated research agenda that could help mitigate future plant disease pandemics.

This white paper presents a series of perspectives on current and future phytobiome management, discussed at the Wild and Tamed Phytobiomes Symposium in University Park, PA, U.S.A., in June 2018. To enhance plant productivity and health, and to translate lab- and greenhouse-based phytobiome research to field applications, the academic community and end-users need to address a variety of scientific, practical, and social challenges. Prior discussion of phytobiomes has focused heavily on plant-associated bacterial and fungal assemblages, but the phytobiomes concept covers all factors that influence plant function. Here we discuss various management considerations, including abiotic conditions (e.g., soil and nutrient applications), microorganisms (e.g., bacterial and fungal assemblages, bacterial and fungal inoculants, and viruses), macroorganisms (e.g., arthropods and plant genetics), and societal factors (e.g., communication approaches and technology diffusion). An important near-term goal for this field should be to estimate the potential relative contribution of different components of the phytobiome to plant health, as well as the potential and risk of modifying each in the near future.

The success of intervention projects in ecological systems depends not only on the quality of management technologies, but also patterns of adoption among land managers. Impact network analysis (INA) is a new framework for evaluating the likely success of regional interventions before, during, and after projects, for project implementers, policy makers, and funders. INA integrates across three key system components in a multilayer network analysis: (a) the quality of a management technology and the quality of research supporting it, (b) the socioeconomic networks through which managers learn about management technologies and decide whether to use them, and (c) the linked biophysical network for target species success or failure in the management landscape that results from managers’ decisions.The specific objectives of this paper are (1) to introduce the INA framework and INA R package, (2) to illustrate identification of key nodes for smart surveillance, for networks where the likelihood of invasive species entry into the biophysical network at a given node may be based on information available to the corresponding node in the socioeconomic network, (3) to illustrate application of the INA framework for evaluating the likely degree of success of a project in intervention ecology, before, during and after an intervention, and (4) to illustrate the use of INA for evaluating adaptation strategies under global change scenarios with pulse and press stressors, introducing ‘adaptation functions’ for sustainability and resilience.Examples of use of the INA package show one of the key outcomes of analyses: identifying when systems may be non-responsive to the system components that are readily changed through management decisions, to explore what additional adaptations may be necessary for intervention success.The broader goal for the development of impact network analysis and the INA package is to provide a common framework that integrates across intervention ecology, to enhance opportunities for lessons learned across systems and scientific disciplines, to support the development of a community of practice, and to create a general platform for analysis of sustainability, resilience, and economic viability in intervention ecology applications.

Before 1991

The genus Klebsiella includes pathogenic and nonpathogenic species. We report the 5.57-Mb genome sequences of two Klebsiella variicola strains, G18-1365 and G18-1376, isolated from symptomatic plantain plants in Haiti. These strains are genetically closely related (average nucleotide identity [ANI] > 99%) to the previously described type strain of K. variicola, DSM 15968.

Virus-virus interactions in plants can modify host symptoms. As a result, disease management strategies may be unsuccessful if they are based solely on visual assessment and diagnostic assays for known individual viruses. Papaya ringspot virus is an important limiting factor for papaya production and likely has interactions with other viruses that are not yet known. Using high-throughput sequencing, we recovered known and novel RNA and DNA viruses from papaya orchards in Chiapas, Mexico, and categorized them by host and, in the case of papaya, symptom type: asymptomatic papaya, papaya with ringspot virus symptoms, papaya with nonringspot symptoms, weeds, and insects. Using network analysis, we demonstrated virus associations within and among host types and described the ecological community patterns. Recovery of viruses from weeds and asymptomatic papaya suggests the need for additional management attention. These analyses contribute to the understanding of the community structure of viruses in the agroecological landscape., The study of complex ecological interactions, such as those among host, pathogen, and vector communities, can help to explain host ranges and the emergence of novel pathogens. We evaluated the viromes of papaya orchards, including weed and insect viromes, to identify common viruses in intensive production of papaya in the Pacific Coastal Plain and the Central Depression of Chiapas, Mexico. Samples of papaya cultivar Maradol, susceptible to papaya ringspot virus (PRSV), were categorized by symptoms by local farmers (papaya ringspot symptoms, non-PRSV symptoms, or asymptomatic). These analyses revealed the presence of 61 viruses, where only 4 species were shared among both regions, 16 showed homology to known viruses, and 36 were homologous with genera including Potyvirus, Comovirus, and Tombusvirus (RNA viruses) and Begomovirus and Mastrevirus (DNA viruses). We analyzed the network of associations between viruses and host-location combinations, revealing ecological properties of the network, such as an asymmetric nested pattern, and compared the observed network to null models of network association. Understanding the network structure informs management strategies, for example, revealing the potential role of PRSV in asymptomatic papaya and that weeds may be an important pathogen reservoir. We identify three key management implications: (i) each region may need a customized management strategy; (ii) visual assessment of papaya may be insufficient for PRSV, requiring diagnostic assays; and (iii) weed control within orchards may reduce the risk of virus spread to papaya. Network analysis advances understanding of host-pathogen interactions in the agroecological landscape. IMPORTANCE Virus-virus interactions in plants can modify host symptoms. As a result, disease management strategies may be unsuccessful if they are based solely on visual assessment and diagnostic assays for known individual viruses. Papaya ringspot virus is an important limiting factor for papaya production and likely has interactions with other viruses that are not yet known. Using high-throughput sequencing, we recovered known and novel RNA and DNA viruses from papaya orchards in Chiapas, Mexico, and categorized them by host and, in the case of papaya, symptom type: asymptomatic papaya, papaya with ringspot virus symptoms, papaya with nonringspot symptoms, weeds, and insects. Using network analysis, we demonstrated virus associations within and among host types and described the ecological community patterns. Recovery of viruses from weeds and asymptomatic papaya suggests the need for additional management attention. These analyses contribute to the understanding of the community structure of viruses in the agroecological landscape.

Understanding factors influencing microbial interactions, and designing methods to identify key taxa, are complex challenges for achieving microbiome-based agriculture. Here we study how grafting and the choice of rootstock influence root-associated fungal communities in a grafted tomato system. We studied three tomato rootstocks (BHN589, RST-04-106 and Maxifort) grafted to a BHN589 scion and profiled the fungal communities in the endosphere and rhizosphere by sequencing the Internal Transcribed Spacer (ITS2). The data provided evidence for a rootstock effect (explaining ~2% of the total captured variation, p < 0.01) on the fungal community. Moreover, the most productive rootstock, Maxifort, supported greater fungal species richness than the other rootstocks or controls. We then constructed a phenotype-OTU network analysis (PhONA) using an integrated machine learning and network analysis approach based on sequence-based fungal Operational Taxonomic Units (OTUs) and associated tomato yield data. PhONA provides a graphical framework to select a testable and manageable number of OTUs to support microbiome-enhanced agriculture. We identified differentially abundant OTUs specific to each rootstock in both endosphere and rhizosphere compartments. Subsequent analyses using PhONA identified OTUs that were directly associated with tomato fruit yield, and others that were indirectly linked to yield through their links to these OTUs. Fungal OTUs that are directly or indirectly linked with tomato yield may represent candidates for synthetic communities to be explored in agricultural systems.IMPORTANCEThe realized benefits of microbiome analyses for plant health and disease management are often limited by the lack of methods to select manageable and testable synthetic microbiomes. We evaluated the composition and diversity of root-associated fungal communities from grafted tomatoes. We then constructed a phenotype-OTU network analysis (PhONA) using these linear and network models. By incorporating yield data in the network, PhONA identified OTUs that were directly predictive of tomato yield, and others that were indirectly linked to yield through their links to these OTUs. Follow-up functional studies of taxa associated with effective rootstocks, identified using approaches like PhONA, could support the design of synthetic fungal communities for microbiome-based crop production and disease management. The PhONA framework is flexible for incorporation of other phenotypic data and the underlying models can readily be generalized to accommodate other microbiome or other ‘omics data.

Effective altruism is an ethical framework for identifying the greatest potential benefits from investments. Here, we apply effective altruism concepts to maximize research benefits through identification of priority stakeholders, pathosystems, and research questions and technologies. Priority stakeholders for research benefits may include smallholder farmers who have not yet attained the minimal standards set out by the United Nations Sustainable Development Goals; these farmers would often have the most to gain from better crop disease management, if their management problems are tractable. In wildlands, prioritization has been based on the risk of extirpating keystone species, protecting ecosystem services, and preserving wild resources of importance to vulnerable people. Pathosystems may be prioritized based on yield and quality loss, and also factors such as whether other researchers would be unlikely to replace the research efforts if efforts were withdrawn, such as in the case of orphan crops and orphan pathosystems. Research products that help build sustainable and resilient systems can be particularly beneficial. The “value of information” from research can be evaluated in epidemic networks and landscapes, to identify priority locations for both benefits to individuals and to constrain regional epidemics. As decision-making becomes more consolidated and more networked in digital agricultural systems, the range of ethical considerations expands. Low-likelihood but high-damage scenarios such as generalist doomsday pathogens may be research priorities because of the extreme potential cost. Regional microbiomes constitute a commons, and avoiding the “tragedy of the microbiome commons” may depend on shifting research products from “common pool goods” to “public goods” or other categories. We provide suggestions for how individual researchers and funders may make altruism-driven research more effective. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

Climate change affects all segments of the agricultural enterprise, and there is mounting evidence that the continuing warming trend with shifting seasonality and intensity in precipitation will increase the vulnerability of agricultural systems. Agricultural is a complex system within the USA encompassing a large number of crops and livestock systems, and development of indicators to provide a signal of the impact of climate change on these different systems would be beneficial to the development of strategies for effective adaptation practices. A series of indicators were assembled to determine their potential for assessing agricultural response to climate change in the near term and long term and those with immediate capability of being implemented and those requiring more development. The available literature reveals indicators on livestock related to heat stress, soil erosion related to changes in precipitation, soil carbon changes in response to increasing carbon dioxide and soil management practices, economic response to climate change in agricultural production, and crop progress and productivity. Crop progress and productivity changes are readily observed data with a historical record for some crops extending back to the mid-1800s. This length of historical record coupled with the county-level observations from each state where a crop is grown and emerging pest populations provides a detailed set of observations to assess the impact of a changing climate on agriculture. Continued refinement of tools to assess climate impacts on agriculture will provide guidance on strategies to adapt to climate change.

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.

CONTEXT Potato is an essential food staple and a critical crop for rural livelihoods in the Republic of Georgia, where many phytosanitary risks threaten production. OBJECTIVE The objectives of this study were, first, to characterize the current seed and ware potato transaction network, value chain, varietal adoption, and phytosanitary risks for Georgia. Second, we modeled scenarios for the spread of an emerging pathogen, Synchytrium endobioticum, in Georgia as part of a geographic risk assessment analysis. Third, we coupled risk estimated in our simulation experiments with risk of reintroduction or invasion of pathogens via international trade or habitat connectivity. We found that a majority of seed potato is obtained from local sources in Georgia, and is of unknown phytosanitary quality. METHODS An expert elicitation workshop was held to characterize the potato value chain as well as potato production more generally in the Republic of Georgia. To characterize future risk of pathogen spread through Georgia we leveraged epidemic network analysis, an analysis of potato cropland connectivity, and an evaluation of international potato trade in a multi-step risk assessment. RESULTS AND CONCLUSIONS Five varieties, including the variety Jelly, made up 65% of planted area throughout the country. Several pathogens and pests were listed as contributing to annual yield loss with S. endobioticum, causing potato wart, identified as the greatest emerging risk to the country. Through simulation analyses of potential spread scenarios within country, we identified municipalities in Adjara and Samtskhe-Javakheti to be at particularly high risk for introduction of potato wart and we recommend enhanced surveillance in these regions. Our analysis of cropland connectivity revealed that the region where Georgia, Azerbaijan, and Armenia meet are at a high risk for local spread of seedborne pathogens such as S. endobioticum. We propose these locations as targets for enhanced surveillance and mitigation strategies. SIGNIFICANCE We introduce these methods as a general framework for the rapid assessment of phytosanitary risks of regional seed systems, especially where information available to guide interventions is scarce.

Seedborne pathogens and pests limit production in many agricultural systems. Quarantine programs help prevent the introduction of exotic pathogens into a country, but few regulations directly apply to reducing the reintroduction and spread of endemic pathogens. Use of phytosanitary thresholds helps limit the movement of pathogen inoculum through seed, but the costs associated with rejected seed lots can be prohibitive for voluntary implementation of phytosanitary thresholds. In this paper, we outline a framework to optimize thresholds for seedborne pathogens, balancing the cost of rejected seed lots and benefit of reduced inoculum levels. The method requires relatively small amounts of data, and the accuracy and robustness of the analysis improves over time as data accumulate from seed testing. We demonstrate the method first and illustrate it with a case study of seedborne oospores of Peronospora effusa, the causal agent of spinach downy mildew. A seed lot threshold of 0.23 oospores per seed could reduce the overall number of oospores entering the production system by 90% while removing 8% of seed lots destined for distribution. Alternative mitigation strategies may result in lower economic losses to seed producers, but have uncertain efficacy. We discuss future challenges and prospects for implementing this approach.

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 © 2017 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .