Free-Riding in Plant Health: A Social-Ecological Systems Approach to Collective Action.

Plant disease epidemics often transcend land management boundaries, creating a collective-action problem where a group must cooperate in a common effort to maximize individual and group benefits. Drawing upon the social-ecological systems framework and associated design principles, we review variables of resource systems, resource units, actors, and governance systems relevant to collective action in plant health. We identify a need to better characterize how attributes of epidemics determine the usefulness of collective management, what influences actors' decisions to participate, what governance systems fit different plant health threats, and how these subsystems interact to lead to plant health outcomes. We emphasize that there is not a single governance structure that ensures collective action but rather a continuum of structures that depend on the key system variables identified. An integrated social-ecological systems approach to collective action in plant health should enable institutional designs to better fit specific plant health challenges.

Fungicide Use Patterns in Select United States Wine Grape Production Regions.

Wine grape production (Vitis sp.) in the United States requires fungicide inputs for disease control. Currently, there is limited data available on vineyard fungicide use patterns. This information is important in developing tailored recommendations for disease management and fungicide stewardship. In this paper, we summarize the wine grape vineyard fungicide use patterns from four major regions: Napa and Sonoma valleys (California), Willamette Valley (Oregon), Columbia Valley (Washington), and several smaller regions east of the Mississippi River in years 2009 to 2020. We learned that the average in-season total fungicide applications ranged regionally from 5.6 to 8. The most commonly applied Fungicide Resistance Action Committee (FRAC) codes in spray programs were FRAC 3, 13, and M02 across all regions, with some variation to the top four groups in each region. Most applications were made on 14-day intervals; however, shorter intervals (7-day) were favored early season, and longer intervals (21-day) were favored late season. Tank-mixing multiple active ingredients was common east of the Mississippi River during all stages of grape development; this action was typically favored during the bloom period in other regions. In a subset of records that participated in FRAC 11 fungicide resistance testing, the average number of FRAC 11 applications after testing was reduced to either no applications or one application in Napa and Sonoma valleys. This survey provides regionally specific data related to fungicide stewardship practices that could be a focus for future stewardship messaging and fungicide resistance selection training, including total product use (selection events), spray intervals (selection pressure), and tank mixing (selection management).[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

A Rapid Glove-Based Inoculum Sampling Technique to Monitor Erysiphe necator in Commercial Vineyards.

Information on the presence and severity of grape powdery mildew (GPM), caused by Erysiphe necator, has long been used to guide management decisions. While recent advances in the available molecular diagnostic assays and particle samplers have made monitoring easier, there is still a need for more efficient field collection of E. necator. The use of vineyard worker gloves worn during canopy manipulation as a sampler (glove swab) of E. necator was compared with samples identified by visual assessment with subsequent molecular confirmation (leaf swabs) and airborne spore samples collected by rotating-arm impaction traps (impaction traps). Samples from United States commercial vineyards in Oregon, Washington, and California were analyzed using two TaqMan qPCR assays targeting the internal transcribed spacer regions or cytochrome b gene of E. necator. Based on qPCR assays, visual disease assessments misidentified GPM up to 59% of the time with a higher frequency of misidentification occurring earlier in the growing season. Comparison of the aggregated leaf swab results for a row (n = 915) to the row's corresponding glove swab had 60% agreement. The latent class analysis (LCA) indicated that glove swabs were more sensitive than leaf swabs in detecting E. necator presence. The impaction trap results had 77% agreement to glove swabs (n = 206) taken from the same blocks. The LCAs estimated that the glove swabs and impaction trap samplers varied each year in which was more sensitive for detection. This likely indicates that these methods have similar levels of uncertainty and provide equivalent information. Additionally, all samplers, once E. necator was detected, were similarly sensitive and specific for detection of the A-143 resistance allele. Together, these results suggest that glove swabs are an effective sampling method for monitoring the presence of E. necator and, subsequently, the G143A amino acid substitution associated with resistance to quinone outside inhibitor fungicides in vineyards. Glove swabs could reduce sampling costs due to the lack of need for specialized equipment and time required for swab collection and processing.

Identification of Putative SDHI Target Site Mutations in the SDHB, SDHC, and SDHD Subunits of the Grape Powdery Mildew Pathogen Erysiphe necator.

Succinate dehydrogenase inhibitors (SDHIs) are fungicides used in control of numerous fungal plant pathogens, including Erysiphe necator, the causal agent of grapevine powdery mildew (GPM). Here, the sdhb, sdhc, and sdhd genes of E. necator were screened for mutations that may be associated with SDHI resistance. GPM samples were collected from 2017 to 2020 from the U.S. states of California, Oregon, Washington, and Michigan, and the Canadian province of British Columbia. Forty-five polymorphisms were identified in the three sdh genes, 17 of which caused missense mutations. Of these, the SDHC-p.I244V substitution was shown in this study to reduce sensitivity of E. necator to boscalid and fluopyram, whereas the SDHC-p.G25R substitution did not affect SDHI sensitivity. Of the other 15 missense mutations, the SDHC-p.H242R substitution was shown in previous studies to reduce sensitivity of E. necator toward boscalid, whereas the equivalents of the SDHB-p.H242L, SDHC-p.A83V, and SDHD-p.I71F substitutions were shown to reduce sensitivity to SDHIs in other fungi. Generally, only a single amino acid substitution was present in the SDHB, SDHC, or SDHD subunit of E. necator isolates, but missense mutations putatively associated with SDHI resistance were widely distributed in the sampled areas and increased in frequency over time. Finally, isolates that had decreased sensitivity to boscalid or fluopyram were identified but with no or only the SDHC-p.G25R amino acid substitution present in SDHB, SDHC, and SDHD subunits. This suggests that target site mutations probably are not the only mechanism conferring resistance to SDHIs in E. necator.

Agricultural investments and hunger in Africa modeling potential contributions to SDG2 - Zero Hunger.

We use IFPRI's IMPACT framework of linked biophysical and structural economic models to examine developments in global agricultural production systems, climate change, and food security. Building on related work on how increased investment in agricultural research, resource management, and infrastructure can address the challenges of meeting future food demand, we explore the costs and implications of these investments for reducing hunger in Africa by 2030. This analysis is coupled with a new investment estimation model, based on the perpetual inventory methodology (PIM), which allows for a better assessment of the costs of achieving projected agricultural improvements. We find that climate change will continue to slow projected reductions in hunger in the coming decades-increasing the number of people at risk of hunger in 2030 by 16 million in Africa compared to a scenario without climate change. Investments to increase agricultural productivity can offset the adverse impacts of climate change and help reduce the share of people at risk of hunger in 2030 to five percent or less in Northern, Western, and Southern Africa, but the share is projected to remain at ten percent or more in Eastern and Central Africa. Investments in Africa to achieve these results are estimated to cost about 15 billion USD per year between 2015 and 2030, as part of a larger package of investments costing around 52 billion USD in developing countries.