Advancing climate-adaptive watershed health by integrating socio-ecological systems and team science

Abstract

Strengthening effective watershed health and adaptive capacity amid accelerating climate change and compounding socio-ecological stressors demands integrative approaches that link systems analysis, risk and vulnerability assessments, and justice-centered collaboration. The Río Grande de Añasco (RGA) watershed in Puerto Rico, a landscape still grappling with cascading post-disaster impacts from recent hurricanes and compounding hazards, illustrates the dynamics of a socio-ecological system (SES) under climate stress. This research advances a SES framework for evaluating watershed health, identifies the coupled natural and social drivers of landslide susceptibility, and synthesizes best practices for equitable, transdisciplinary collaboration in a climate-vulnerable setting. A core contribution of the research is the Socio-Ecological Systems Watershed Health Assessment (SES WHA) Framework, which extends conventional assessment models by embedding climate change impacts, disaster risk reduction, and international guidance within a structure that explicitly integrates justice and equity metrics. Applied to the RGA, the framework evaluates watershed health through interrelated categories (e.g., climate change and disaster resilience, institutional and governance challenges, ecosystem services and ecological needs, infrastructure and resource constraints, long-term monitoring). Each category links indicators to specific challenges and intervention strategies, providing a dynamic approach to diagnosing watershed vulnerabilities and identifying adaptive responses. This approach reveals how ecological degradation, infrastructure fragility, and social vulnerability interact to shape adaptive capacity and inform equitable, climate-adaptive governance. In 2017, Hurricane María triggered more than 16,000 landslides across the RGA, contributing to system-wide failures of critical road infrastructure, stormwater drainage, and damage to homes and farms. The landslide impact analysis presented in this research demonstrates how natural and social factors jointly influence hazard susceptibility in an active post-disaster landscape. Integrating the CDC Social Vulnerability Index within a spatial proximity model of landslides enabled the identification of vulnerable hotspots, particularly in the municipalities of Maricao, Las Marías, and Lares, where socio-economic disparities, infrastructure fragility, and slope instability converge. This dissertation synthesizes best practices for team science, bridging disciplinary approaches to collaborative research in a post-disaster context. The analysis identified critical gaps, including power imbalances and challenges in integrating community priorities into scientific processes. Insights from the CRISP project demonstrate how justice-centered, participatory methods enhance stakeholder trust and data relevance, while also revealing unique obstacles faced in post-disaster environments. This synthesis offers a new framework for guiding team science practices where justice and equity are vital considerations. Collectively, the findings presented in this research advance sustainable, risk-informed watershed management by demonstrating how integrating technical assessments, social vulnerability data, and equitable, collaborative research practices can strengthen climate adaptation and socio-ecological resilience. Philosophically, the research reframes watershed, disaster, climate adaptation, and team science as interdependent fields of study and practice, advancing a justice-centered paradigm for knowledge production, collaboration, and adaptive governance.