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Risk Factors for Crop Health Under Global Change and Agricultural Shifts: A Framework of Analyses Using Rice in Tropical and Subtropical Asia as a Model

First and third authors: International Rice Research Institute, IRRI/PBGB Division, DAPO Box 7777, Metro Manila, Philippines; second author: Department of Plant Pathology, North Carolina State University, Campus Box 7405, Raleigh 27695; fourth author: Department of Plant Pathology, University of Wisconsin, 1630 Linden Drive, Madison 53706; fifth author: Horticulture Research Center, Agriculture and Agri-Food Canada, 430 Boulevard Gouin, St-Jean-sur-Richelieu, J3B 3EH, Canada; and sixth author: Plant Pathology Department, University of California, Davis 95616-8751.

Plant disease epidemiology requires expansion of its current methodological and theoretical underpinnings in order to produce full contributions to global food security and global changes. Here, we outline a framework which we applied to farmers' field survey data set on rice diseases in the tropical and subtropical lowlands of Asia. Crop health risks arise from individual diseases, as well as their combinations in syndromes. Four key drivers of agricultural change were examined: labor, water, fertilizer, and land availability that translate into crop establishment method, water shortage, fertilizer input, and fallow period duration, respectively, as well as their combinations in production situations. Various statistical approaches, within a hierarchical structure, proceeding from higher levels of hierarchy (production situations and disease syndromes) to lower ones (individual components of production situations and individual diseases) were used. These analyses showed that (i) production situations, as wholes, represent very large risk factors (positive or negative) for occurrence of disease syndromes; (ii) production situations are strong risk factors for individual diseases; (iii) drivers of agricultural change represent strong risk factors of disease syndromes; and (iv) drivers of change, taken individually, represent small but significant risk factors for individual diseases. The latter analysis indicates that different diseases are positively or negatively associated with shifts in these drivers. We also report scenario analyses, in which drivers of agricultural change are varied in response to possible climate and global changes, generating predictions of shifts in rice health risks. The overall set of analyses emphasizes the need for large-scale ground data to define research priorities for plant protection in rapidly evolving contexts. They illustrate how a structured theoretical framework can be used to analyze emergent features of agronomic and socioecological systems. We suggest that the concept of “disease syndrome” can be borrowed in botanical epidemiology from public health to emphasize a holistic view of disease in shifting production situations in combination with the conventional, individual disease-centered perspective.

Additional keywords: Bayesian analysis, climate change, disease prevention, keystone species, logistic regression, research prioritization.