An integrated seed health strategy and phytosanitary risk assessment: Potato in the Republic of Georgia

Andersen, Kelsey F.; Forbes, Gregory A.; Andrade-Piedra, Jorge; Buddenhagen, Christopher E.; Fulton, James C.; Gatto, Marcel; Khidesheli, Z.; Mdivani, R.; Xing, Yao‐Wu; Garrett, Karen A.

doi:10.1016/j.agsy.2021.103144

Cited by 17 publications

(17 citation statements)

References 61 publications

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“…A “starting state” row vector the same size as the number of rows of the network adjacency matrix tracks the infection status (1 for infected, 0 for uninfected), and each node is set as a starting point for simulations (the state of node j is in column j).). This vector s t is modified by matrix multiplication s t N t for each time step and then we track infected nodes, with the larger dimension matrix allowing us to track dispersal a similar process was described by Andersen Onofre et al [ 35 ]. The state at the next time step is: This replaces positive values of s t N t by 1, as s t N t can have elements that are greater than 1 and leaves the zeros unchanged so that s t+1 is a row vector of 0s and 1s.…”

Section: Methodsmentioning

confidence: 99%

The phytosanitary risks posed by seeds for sowing trade networks

et al. 2021

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When successful, the operation of local and international networks of crop seed distribution or “seed systems” ensures farmer access to seed and impacts rural livelihoods and food security. Farmers are both consumers and producers in seed systems and benefit from access to global markets. However, phytosanitary measures and seed purity tests are also needed to maintain seed quality and prevent the spread of costly weeds, pests and diseases, in some countries regulatory controls have been in place since the 1800s. Nevertheless, seed contaminants are internationally implicated in between 7% and 37% of the invasive plant species and many of the agricultural pests and diseases. We assess biosecurity risk across international seed trade networks of forage crops using models of contaminant spread that integrate network connectivity and trade volume. To stochastically model hypothetical contaminants through global seed trade networks, realistic dispersal probabilities were estimated from quarantine weed seed detections and incursions from border security interception data in New Zealand. For our test case we use contaminants linked to the global trade of ryegrass and clover seed. Between 2014 and 2018 only four quarantine weed species (222 species and several genera are on the quarantine schedule) warranting risk mitigation were detected at the border. Quarantine weeds were rare considering that average import volumes were over 190 tonnes for ryegrass and clover, but 105 unregulated contaminant species were allowed in. Ryegrass and clover seed imports each led to one post-border weed incursion response over 20 years. Trade reports revealed complex global seed trade networks spanning >134 (ryegrass) and >110 (clover) countries. Simulations showed contaminants could disperse to as many as 50 (clover) or 80 (ryegrass) countries within 10 time-steps. Risk assessed via network models differed 18% (ryegrass) or 48% (clover) of the time compared to risk assessed on trade volumes. We conclude that biosecurity risk is driven by network position, the number of trading connections and trade volume. Risk mitigation measures could involve the use of more comprehensive lists of regulated species, comprehensive inspection protocols, or the addition of field surveillance at farms where seed is planted.

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Section: Methodsmentioning

confidence: 99%

The phytosanitary risks posed by seeds for sowing trade networks

et al. 2021

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“…Thus, one can predict the potential effects on seed security of quality seed sourcing, disease invasion risk, and surveillance objectives. By simulation of potential scenarios of seed systems shocks, this approach can be used to predict the downstream effects on seed health and supply, potentially building on analyses of cropland connectivity (Andersen et al, 2019; Andersen Onofre et al, 2021; Buddenhagen et al, 2017, 2022; Garrett, 2021; Xing et al, 2020). One caveat to keep in mind in evaluating the results is that only a portion of the complete network is reported in studies such as this; a complete census of the networks would reveal other aspects of the seed system structure (Newman, 2018).…”

Section: Discussionmentioning

confidence: 99%

Banana seed exchange networks in Burundi – Linking formal and informal systems

et al. 2022

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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.

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“…Successful seed systems will optimize the maintenance and spread of desirable crop varieties (Labeyrie et al, 2016;Pautasso, 2015;Pautasso et al, 2013) while minimizing the spread of pathogens through seed or grain movement (Andersen et al, 2019; Andersen F I G U R E 4 An uncertainty quantification to evaluate the effect of changing an inverse power law parameter describing the dispersal gradient for a bioentity Onofre et al, 2021;Buddenhagen et al, 2017;Hernandez Nopsa et al, 2015). Linked networks include the global network of crop breeders who exchange genetic material (Garrett et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

“…Layers include the network of seed movement in formal and informal systems, the network of pathogen or pest movement through seed, and the network of information and influence related to integrated seed health strategies (Thomas‐Sharma et al., 2016, 2017). Successful seed systems will optimize the maintenance and spread of desirable crop varieties (Labeyrie et al., 2016; Pautasso, 2015; Pautasso et al., 2013) while minimizing the spread of pathogens through seed or grain movement (Andersen et al., 2019; Andersen Onofre et al., 2021; Buddenhagen et al., 2017; Hernandez Nopsa et al., 2015). Linked networks include the global network of crop breeders who exchange genetic material (Garrett et al., 2017).…”

Section: Discussionmentioning

confidence: 99%

Impact network analysis and the ina r package: Decision support for regional management interventions

Garrett

2021

Methods Ecol Evol

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1. The success of intervention projects for species management depends on both the effectiveness of management technologies and the geographical landscape of management adoption. Impact network analysis (INA) is a new framework for evaluating the likely level of success of regional species management before, during and after projects, for project implementers, policymakers and funders. INA evaluates the effects of management performance in a multilayer network analysis. The socioeconomic network represents manager communication about technologies and influence about technology adoption decisions in an agent-based model. The linked biophysical network represents species dispersal, resulting in regional success or failure of species management. 2. The specific objectives of this paper are to (a) introduce the INA framework and ina r package; (b) illustrate the identification of key nodes for smart surveillance strategies; (c) illustrate the 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 (d) illustrate the use of INA for evaluating adaptation strategies under global change scenarios with pulse and press stressors, introducing 'adaptation functions' to evaluate the management response required for sustainability and resilience.3. Examples of use of the ina package show key outcomes of analyses: identifying the limiting factors for effective regional management, pointing out when systems may be non-responsive to the system components that are readily changed through management decisions, and identifying the additional adaptations that may be necessary for intervention success. 4. The broader goals for the development of impact network analysis and the ina package are 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 to operationalize analysis of sustainability, resilience and economic viability in intervention ecology applications.This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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An integrated seed health strategy and phytosanitary risk assessment: Potato in the Republic of Georgia

Cited by 17 publications

References 61 publications

The phytosanitary risks posed by seeds for sowing trade networks

The phytosanitary risks posed by seeds for sowing trade networks

Banana seed exchange networks in Burundi – Linking formal and informal systems

Impact network analysis and the ina r package: Decision support for regional management interventions

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