The coronavirus pandemic (COVID-19) has affected all supply chains through severe disruption of logistics activities, production, and markets. This study aimed to survey the impact of the coronavirus on the poultry supply chain using an exploratory sequential mixed design. We first addressed those stages of the poultry supply chain disrupted in an ongoing pandemic, and then elaborated particular disturbances associated with each stage. This study was based on data collected from Iranian poultry industry owners and experts who had sufficient experience in agricultural supply chains as well. As the qualitative phase, the content analysis was conducted to identify the impacts of the coronavirus on the poultry supply chain. The results and conclusions that emerged from the qualitative phase were refined and weighted by the Fuzzy Delphi Method (FDM) and the Fuzzy Analytic Hierarchy Process (FAHP) respectively, in the quantitative phase. The results suggested that the pandemic has further affected the input supply as a stage in the poultry supply chain. This is probably because of the fact that the poultry industry is heavily dependent on inputs' flow. In addition, supply chain governance was seriously impaired due to the persistence of the pandemic. The coronavirus pandemic has significantly affected the stages that are most reliant on transportation. Finally, we found that a part of the disruptions that occur in the downstream of the supply chain is due to the epidemic's direct adverse effects, and another part is due to indirect consequences received from the upstream. Our findings and implications can be useful in decision-making procedures during ongoing epidemics.

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Southern Iran is a conservation priority area for the endangered Persian onager (Equus hemionus onager), which is threatened by habitat fragmentation and conflict with local communities. To better understand factors that influence onager conservation, we administered a questionnaire in local communities to survey their ecological knowledge, personal experience related to onager, and attitudes toward traditional solutions for reducing crop damage by onager. In addition, we used resistant kernel and factorial least-cost path analyses to identify core areas and corridors for onager movement, and spatial randomization of vehicle collisions and crossing locations to test the predictive ability of resistant kernel and factorial least-cost path predictions of movement. We found that local communities that were knowledgeable about onagers experienced less crop damage from onager compared with those who used traditional methods. Habitat connectivity models revealed that core areas of movement are highly concentrated at the center of protected areas. Some sections of core areas have been cut off by roads where most vehicle collisions with onagers occurred. We propose that effective onager conservation will require integrated landscape-level management to reduce mortality risk, protection of core areas and corridors, development of mitigation strategies to reduce vehicle collisions, and conflict mediation between local communities and onagers.

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