Global Cropland Connectivity: A Risk Factor for Invasion and Saturation by Emerging Pathogens and Pests

Xing, Yao‐Wu; Nopsa, John Fredy Hernández; Andrade-Piedra, Jorge; Beed, Fen D.; Blomme, Guy; Yepes, Mónica Carvajal; Coyne, Danny; Forbes, Gregory A.; Kreuze, Jan; Kroschel, J.; Kumar, Lava; Legg, J.P.; Parker, Monica; Schulte-Geldermann, Elmar; Garrett, Karen A.

doi:10.1101/106542

Cited by 11 publications

(15 citation statements)

References 93 publications

(90 reference statements)

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“…This can result in multiple and, perhaps, contrasting preferences that vary according to the user’s role within the food chain, implying that the input and decision‐making roles of different users is of primary importance in crop breeding. Breeding programs have historically focused on yield and disease resistance to face the challenges of food security in terms of feeding a growing population (Ceballos et al ., 2004; Manu‐Aduening et al ., 2006; Ojulong et al ., 2008; Ceballos et al ., 2020), and on malnutrition and safety issues (Adenle et al ., 2012; Peprah et al ., 2020; Xing et al ., 2020), with lower priority on post‐harvest quality characteristics, and processor and consumer demand. In addition, information on product characteristics is often overly simplified by not including information on the optimal range or description that would help breeder’s ability to meet user needs.…”

Section: Introductionmentioning

confidence: 99%

From cassava to gari: mapping of quality characteristics and end‐user preferences in Cameroon and Nigeria

Ndjouenkeu¹,

Kégah²,

Teeken

et al. 2020

Int J of Food Sci Tech

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User's preferences of cassava and cassava products along the value chain are supported by specific root quality characteristics that can be linked to root traits. Therefore, providing an evidence base of user preferred characteristics along the value chain can help in the functional choice of cassava varieties. In this respect, the present paper presents the results from focus group discussions and individual interviews on user preferred quality characteristics of raw cassava roots and the derived product, gari,one of the major cassava products in Sub-Saharan Africain major production and consumption areas of Cameroon and Nigeria. Choice of cassava varieties for farming is mainly determined by the multiple end uses of the roots, their agricultural yield and the processing determinants of roots that support their major highquality characteristics: size, density, low water content, maturity, colour and safety. Processing of cassava roots into gari goes through different technological variants leading to a gari whose high-quality characteristics are dryness, colour, shiny/attractive appearance, uniform granules and taste. Eba, the major consumption form of gari in Cameroon and Nigeria, is mainly characterised by its textural properties: smoothness, firmness, stickiness, elasticity and mouldability. Recommendations are made, suggesting that breeding will have to start evaluating cassava clones for brightness/shininess, as well as textural properties such as mouldability and elasticity of cassava food products, for the purpose of supporting decision-making by breeders and the development of high-throughput selection methods of cassava varieties. Women are identified as important beneficiaries of such initiatives giving their disadvantaged position and their prominent role in cassava processing and marketing of gari.

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Section: Introductionmentioning

confidence: 99%

From cassava to gari: mapping of quality characteristics and end‐user preferences in Cameroon and Nigeria

Ndjouenkeu¹,

Kégah²,

Teeken

et al. 2020

Int J of Food Sci Tech

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“…Users can evaluate the importance of nodes in their specific biophysical networks, and potentially include new analyses such as evaluating whether node demographic or other traits are associated with higher or lower importance for surveillance. Analyses such as evaluating the connectivity of host populations (Xing et al 2020), can be used to characterize landscapes for application with smartsurv. In on-going surveillance analyses, the importance of nodes could be updated as more information about the system becomes available.…”

Section: Discussionmentioning

confidence: 99%

“…Nodes might be groups of people (as hosts to human pathogens), farms, habitat patches, or other land management units. Links between nodes indicate the potential for the spread of undesirable species or genotypes, such as antibiotic resistant human or agricultural pathogens (Margosian et al 2009;Sutrave et al 2012;Xing et al 2020), or of desirable species or genotypes, such as endangered species or improved crop varieties (such as orange-fleshed sweetpotatoes to support Vitamin A consumption, e.g., evaluated in Andersen et al (2019)). In some cases, the same type of biophysical network model may usefully be applied to related abiotic processes, such as the spread of pollutants, soil erosion, and provisioning of fresh water (Baron et al 2002).…”

Section: Figurementioning

confidence: 99%

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Impact network analysis and the INA R package: Decision support for regional management interventions

Garrett

2020

Preprint

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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.

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“…Hub nodes (nodes with many links) and bridge nodes (nodes that connect distinct regions of a network) will tend to have important roles in the risk of disease spread, and in sampling and mitigation (Hernandez Nopsa et al 2015). However, nodes on the periphery of a network could be the entry point for an invasion of that network (Xing et al 2017). While the importance of hub and bridge nodes is intuitive, key roles of other nodes may be revealed in more detailed analyses of likely patterns of disease spread.…”

mentioning

confidence: 99%

Epidemic network analysis for mitigation of invasive pathogens in seed systems: Potato in Ecuador

Buddenhagen

Nopsa

Andersen

et al. 2017

Preprint

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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 method for evaluating the epidemiological role of nodes in seed networks, and apply it to a regional potato farmer consortium (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 and/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. Women had a smaller amount of the market share for seed-tubers and ware potato, however. Understanding seed system networks provides input for scenario analyses to evaluate potential system improvements.

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Global Cropland Connectivity: A Risk Factor for Invasion and Saturation by Emerging Pathogens and Pests

Cited by 11 publications

References 93 publications

From cassava to gari: mapping of quality characteristics and end‐user preferences in Cameroon and Nigeria

From cassava to gari: mapping of quality characteristics and end‐user preferences in Cameroon and Nigeria

Impact network analysis and the INA R package: Decision support for regional management interventions

Epidemic network analysis for mitigation of invasive pathogens in seed systems: Potato in Ecuador

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