Effective Altruism as an Ethical Lens on Research Priorities.

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and also factors such as whether other researchers would be unlikely to replace the research efforts if efforts were withdrawn, such as in the case of orphan crops and orphan pathosystems.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.

Modeling Epidemics in Seed Systems and Landscapes To Guide Management Strategies: The Case of Sweet Potato in Northern Uganda.

Seed systems are critical for deployment of improved varieties but also can serve as major conduits for the spread of seedborne pathogens. As in many other epidemic systems, epidemic risk in seed systems often depends on the structure of networks of trade, social interactions, and landscape connectivity. In a case study, we evaluated the structure of an informal sweet potato seed system in the Gulu region of northern Uganda for its vulnerability to the spread of emerging epidemics and its utility for disseminating improved varieties. Seed transaction data were collected by surveying vine sellers weekly during the 2014 growing season. We combined data from these observed seed transactions with estimated dispersal risk based on village-to-village proximity to create a multilayer network or "supranetwork." Both the inverse power law function and negative exponential function, common models for dispersal kernels, were evaluated in a sensitivity analysis/uncertainty quantification across a range of parameters chosen to represent spread based on proximity in the landscape. In a set of simulation experiments, we modeled the introduction of a novel pathogen and evaluated the influence of spread parameters on the selection of villages for surveillance and management. We found that the starting position in the network was critical for epidemic progress and final epidemic outcomes, largely driven by node out-degree. The efficacy of node centrality measures was evaluated for utility in identifying villages in the network to manage and limit disease spread. Node degree often performed as well as other, more complicated centrality measures for the networks where village-to-village spread was modeled by the inverse power law, whereas betweenness centrality was often more effective for negative exponential dispersal. This analysis framework can be applied to provide recommendations for a wide variety of seed systems.[Formula: see text] Copyright © 2019 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Efficiency of insect-proof net tunnels in reducing virus-related seed degeneration in sweet potato.

Virus-related degeneration constrains production of quality sweet potato seed, especially under open field conditions. Once in the open, virus-indexed seed is prone to virus infection leading to decline in performance. Insect-proof net tunnels have been proven to reduce virus infection under researcher management. However, their effectiveness under farmer-multiplier management is not known. This study investigated the ability of net tunnels to reduce degeneration in sweet potato under farmer-multiplier management. Infection and degeneration were assessed for two cultivars, Kabode and Polista, grown in net tunnels and open fields at two sites with varying virus pressures. There was zero virus incidence at both sites during the first five generations. Sweet potato feathery mottle virus and sweet potato chlorotic stunt virus were present in the last three generations, occurring singly or in combination to form sweet potato virus disease. Virus infection increased successively, with higher incidences recorded at the high virus pressure site. Seed degeneration modelling illustrated that for both varieties, degeneration was reduced by the maintenance of vines under net tunnel conditions. The time series of likely degeneration based on a generic model of yield loss suggested that, under the conditions experienced during the experimental period, infection and losses within the net tunnels would be limited. By comparison, in the open field most of the yield could be lost after a small number of generations without the input of seed with lower disease incidence. Adopting the technology at the farmer-multiplier level can increase availability of clean seed, particularly in high virus pressure areas.

Network Analysis: A Systems Framework to Address Grand Challenges in Plant Pathology.

Plant pathology must address a number of challenges, most of which are characterized by complexity. Network analysis offers useful tools for addressing complex systems and an opportunity for synthesis within plant pathology and between it and relevant disciplines such as in the social sciences. We discuss applications of network analysis, which ultimately may be integrated together into more synthetic analyses of how to optimize plant disease management systems. The analysis of microbiome networks and tripartite phytobiome networks of host-vector-pathogen interactions offers promise for identifying biocontrol strategies and anticipating disease emergence. Linking epidemic network analysis with social network analysis will support strategies for sustainable agricultural development and for scaling up solutions for disease management. Statistical tools for evaluating networks, such as Bayesian network analysis and exponential random graph models, have been underused in plant pathology and are promising for informing strategies. We conclude with research priorities for network analysis applications in plant pathology.

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

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

Rainfastness of Prothioconazole + Tebuconazole for Fusarium Head Blight and Deoxynivalenol Management in Soft Red Winter Wheat.

Fungicides are most warranted for control of Fusarium head blight (FHB), a disease of wheat caused by the fungal pathogen Fusarium graminearum, when wet, rainy conditions occur during anthesis. However, it is unclear whether rainfall directly following application affects fungicide efficacy against FHB and its associated toxin, deoxynivalenol (DON). The objective of this study was to determine the rainfastness of the fungicide tebuconazole + prothioconazole and the residual life of tebuconazole when applied to wheat spikes at anthesis in combination with the nonionic surfactant Induce. Three field experiments were conducted during 2012 and 2013 in Wooster, OH. Simulated rainfall of a fixed intensity and duration was applied to separate plots at five different times after the fungicide treatment (0, 60, 105, 150, or 195 min). Spike samples were collected at 4-day intervals after fungicide application and assayed for tebuconazole residue. A similar set of greenhouse experiments was conducted using six post-fungicide-application rainfall timing treatments (0, 15, 30, 60, 120, or 180 min). All experiments were inoculated at anthesis with spores of F. graminearum, and FHB index (IND) and DON were quantified. In four of the five experiments, all fungicide-treated experimental units (EUs) had significantly lower mean IND and DON than the untreated check, regardless of rainfall treatment. Among rainfall treatments, EUs that received the earliest rains after fungicide application tended to have the highest numerical mean IND and DON, but were generally not significantly different from EUs that received later rain or fungicide without rain. In both years, fungicide residue on wheat spikes decreased rapidly with time after application, but the rate of reduction varied somewhat between years, with a half-life of 6 to 9 days. Rainfall treatment did not have a significant effect on the rate of residue reduction or the level of residue at a fixed sampling time after fungicide application. In this study, tebuconazole + prothioconazole mixed with a nonionic surfactant was fairly rainfast for a fixed set of rainfall characteristics, and tebuconazole residue did not persist very long after application on wheat spikes.

Urinary volatile constituents of the lion, Panthera leo.

The volatile components of urine from lions were investigated using GC-MS headspace techniques. Fifty-five compounds were found in the urine samples. Seven potential species-identifying compounds were found. Male lion scent marks overlapped significantly more in compound composition with other males than they did with female marks. A similar relationship was not found for the females. Males had a significantly higher absolute content of 2-butanone in their urine than females, and females had a significantly higher relative content of acetone than males. Samples from 13/16 individual lions overlapped more within the individual than they did with samples from the other individuals, but only seven significantly so.