Archetypes for Identifying Systemic Challenges for Convergence Natural Resource Management

Place-based natural resource management is often shaped by complex interdependent social, ecological, and technological systems, characterized by nonlinear dynamics and evolving interactions. Effective research in such contexts requires local stakeholder engagement, in addition to multidisciplinary collaborations, to incorporate community knowledge and lived experience to identify place-specific characteristics and concerns from multiple perspectives. This study developed a systemic analytical framework that integrates information from diverse sources, including academic research, non-academic reports, and expert narratives, to iteratively define system boundaries, scope, key factors, and their interconnections. A systemic analysis serves as a crucial initial step to help researchers and policymakers define system boundaries, identify key factors, and recognize core issues within their local Social-Ecological-Technological System (SETS). This process supports collaborative research and policy development while minimizing fragmented efforts, redundancy, and the omission of critical system components. The framework employs systems archetypes – a set of recurring patterns in system behavior – as analytical lenses to reveal issues and the feedback dynamics that drive them within place-based systems. We applied this approach to the Santa Fe Watershed in New Mexico, a region facing chronic water scarcity and increasingly relying on cross-sector collaboration for sustainable management. We identify key systemic challenges in the watershed’s water management by clarifying the causal relationships that drive system behavior. Based on identified archetype patterns, we offer targeted policy recommendations to disrupt systemic traps. Our findings suggest that using systems archetypes in conjunction with iterative information synthesis is an effective strategy for integrating multidisciplinary knowledge and engaging stakeholders in guiding convergent, place-based research in natural resource management. The resulting systemic issue structures also serve as foundational building blocks for future conceptual modeling and quantitative simulation efforts in place-based cross-boundary collaborative projects.