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2.
J Anim Sci ; 99(2)2021 Feb 01.
Article in English | MEDLINE | ID: mdl-33626146

ABSTRACT

Worldwide, our collective research and policy institutions, including the American Society of Animal Science (ASAS), are calling for more systems-based research and analysis of society's most pressing and complex problems. However, the use of systems analysis within animal science remains limited and researchers may not have the tools to answer this call. This review thus introduces important concepts in systems thinking methodology, such as policy resistance, feedback processes, and dynamic complexity. An overall rationale for systems thinking and analysis is presented, along with examples of the application of these concepts in current animal science research. In order to contrast systems approaches to more frequently employed event-oriented research frameworks, both frameworks are then applied to the ASAS' identified "Grand Challenge" problem of antimicrobial resistance (AMR) in order to compare these two kinds of analyses. Systems thinking stresses the importance of underlying system structures that lead to persistent problem behaviors vs a focus on unidirectional cause-and-effect relationships. A potential systems framework for animal production decisions to use antimicrobials is shown that more explicitly accounts for AMR in a way that can lead to different animal production decisions than the event-oriented framework. Acknowledging and accounting for fundamental system structures that can explain persistent AMR will lead to different potential solutions to this problem than would be suggested from more linear approaches. The challenges and benefits of incorporating systems methods into animal science research are then discussed.


Subject(s)
Systems Analysis , Animals , United States
3.
Nat Food ; 1(9): 541-551, 2020 Sep.
Article in English | MEDLINE | ID: mdl-37128008

ABSTRACT

Many conceptual frameworks have been developed to facilitate understanding and analysis of the linkages between agriculture and food security. Despite having usefully guided analysis and investment, these frameworks exhibit wide diversity in perspectives, assumptions and application. This Review Article examines this diversity, providing an approach to assess frameworks and suggesting improvements in the way they are specified and applied. Using criteria-based systems modelling conventions, we evaluate 36 frameworks. We find that many frameworks are developed for the purpose of illustration rather than analysis and do not clearly indicate causal relationships, tending to ignore the dynamic (stability) dimensions of agriculture and food security and lacking clear intervention points for improving food security through agriculture. By applying system modelling conventions to a widely used framework, we illustrate how such conventions can enhance the usefulness of a framework for overall illustration purposes, delineate hypotheses on agriculture-food security links and examine potential impacts of interventions.

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