Using Participatory System Dynamics Modeling to Address Complex Conservation Problems: Tiger Farming as a Case Study

Abstract

Conservation practitioners routinely work within complex social-ecological systems to address threats facing biodiversity and to promote positive human-wildlife interactions. Inadequate understanding of the direct and indirect, short- and long-term consequences of decision making within these dynamic systems can lead to misdiagnosed problems and interventions with perverse outcomes, exacerbating conflict. Participatory system dynamics (SD) modeling is a process that encourages stakeholder engagement, synthesizes research and knowledge, increases trust and consensus and improves transdisciplinary collaboration to solve these complex types of problems. Tiger conservation exemplifies a set of interventions in a complex social-ecological system. Wild tigers remain severely threatened by various factors, including habitat constraints, human-wildlife conflict, and persistent consumer demand for their body parts. Opinions differ on whether commercial captive tiger facilities reduce or increase the threat from poaching for trade, resulting in policy conflict among diverse stakeholder groups. This paper explains how we are working with international conservation partners in a virtual environment to utilize a participatory SD modeling approach with the goal of better understanding and promoting coexistence of humans and wild tigers. We highlight a step-by-step process that others might use to apply participatory SD modeling to address similar conservation challenges, building trust and consensus among diverse partners to reduce conflict and improve the efficacy of conservation interventions.

The sustainable development goals in a Bachelor of Design course; current integration and benefits, constraints and opportunities for deeper integration

“…Participatory system dynamics modelling (PSDM) is a validated approach that encourages and values stakeholder input and expertise, and synthesises research and knowledge, thereby increasing trust and endorsement of system change, particularly change that benefits from trans-disciplinary collaboration. PDSM, along with approaches that are consistent with Leal Filho et al (2021a, 2021b) framework, is likely to be particularly useful for bringing about deeper incorporation of the SDGs into curricula (Rieder et al , 2021; Zimmerman et al , 2016).…”

Understanding the Influence of Community-Level Determinants on Children’s Social and Emotional Well-Being: A Systems Science and Participatory Approach

“…The emergent themes of our CLD on a community's built environment and, specifically, the availability of and access to child and family primary care and support services are consistent with previous evidence of key systemic barriers involving critical shortages in specialized services and supports available (e.g., wait lists for mental health services) and challenges in coordination and collaboration of multiple service systems that, individually, may lack the resources and training to attend to children's social and emotional concerns [53]. Although the individual variables of the CLD in isolation may not necessarily yield new knowledge related to the multi-level social determinants affecting social and emotional well-being, the strengths and contributions of the GMB process and CLDs stem from their capacity to facilitate the development of a more comprehensive understanding of the complex dynamics at play within the system [54], including potential leverage points within the system which can lead to systems change actions over time [55]. They may also help to identify some of the more subtle intangible variables (e.g., collective buy-in) in the system, which may be key precursors for more tangible variables operating within and outside the community, such as government investment.…”

Model‐informed health system reorganization during emergencies

“…Participatory systems modeling is frequently used to support decision‐making in dynamic complex settings involving multiple stakeholders (Freebairn et al., 2018; Kopainsky et al., 2017; Osgood, 2017; Rouwette et al., 2016; Vennix, 1999). While participatory systems modeling can use different methods and tools, they typically share common attributes, such as (i) active engagement of decision‐makers in model development and (ii) coproduction of knowledge and collaborative learning (Kopainsky et al., 2017; Rieder et al., 2021). As a result, models resulting from participatory processes tend to be more robust and credible to decision‐makers, who engage with modelers to include realistic concepts and assumptions (Freebairn et al., 2022), and more useful and fit for purpose, since they do a better job capturing the available policy landscape (Gilbert et al., 2018).…”