Understanding the interactions of the social and biophysical drivers of land degradation is crucial for developing adaptive management actions for future sustainability. A research-praxis project, the ‘Tsitsa Project’ (TP), applies a social-ecological systems (SES) approach where researchers, natural resource managers, and residents collaborate to support sustainable livelihoods and improved natural resource management for the degraded Tsitsa River Catchment (TRC) in South Africa. A system diagramming approach was coupled with findings from interviews, workshops, literature, and two conceptual frameworks. Data inputs were qualitatively integrated to provide a systemic snapshot of how the context-specific social and biophysical drivers are interlinked and how they interact, revealing multiple processes that operate simultaneously to cause and exacerbate land degradation. Physical and climatic variables, changes in land use and cover, and overgrazing were identified as key factors leading to degradation. Additionally, poverty and disempowerment were also important. While little can be done to influence the physical aspects (steep topography and duplex soils) and climatic variables (extreme rainfall and drought), carefully planned changes in land use and management could produce dual-benefits for improving landscape conditions and sustainable livelihoods. This analysis will inform integrated planning processes to monitor, avoid, reduce and reverse land degradation.

Integration and monitoring are pressing conceptual and methodological challenges in social-ecological systems (SES) research. This paper follows a social learning process, called participatory self-observation, piloted by a group of action-researchers to improve SES integration and monitoring, using the Tsitsa River Catchment in South Africa as a case study. The participatory self-observation process reflected on lessons to enhance integration and integrated monitoring of biophysical, social, and social-ecological data in SES projects; for adaptive planning and management. Three focal points emerged for improving the challenges of SES integration: the need for participatory people-based processes, the importance of applied praxis tasks to catalyze meaningful integration, and the need for transdisciplinary teams to value non-biophysical research. Five focal areas emerged as major challenges for SES monitoring: the integration of qualitative and quantitative data, data overload, the scale of SES monitoring, the need to center SES monitoring around learning, and good working relationships to enable data flow. Recommendations to further develop integrated monitoring and management of SESs include (i) using people-based approaches that focus on applied work which includes rigorous collection of quantitative, biophysical data, (ii) identifying essential data needs through an essential variable approach, and (iii) combining quantitative monitoring with participatory people-based processes.