A Global review of cumulative effects assessments of disturbances on forest ecosystems.

This paper reviews trends in the academic literature on cumulative effects assessment (CEA) of disturbance on forest ecosystems to advance research in the broader context of impact assessments. Disturbance is any distinct spatiotemporal event that disrupts the structure and composition of an ecosystem affecting resource availability. We developed a Python package to automate search term selection, write search strategies, reduce bias and improve the efficient and effective selection of articles from academic databases and grey literature. We identified 148 peer-reviewed literature published between 1986 and 2022 and conducted an inductive and deductive thematic analysis of the results. Our findings revealed that CEA studies are concentrated in the global north, with most publications from authors affiliated with government agencies in the USA and Canada. Methodological and analytical approaches are less interdisciplinary but mainly quantitative and expert-driven, involving modeling the impacts of disturbances on biophysical valued components. Furthermore, the assessment of socioeconomic valued components, including the effects of disturbance on Indigenous wellbeing connected to forests, has received less attention. Even though there is a high preference for regional assessment, challenges with data access, quality, and analysis, especially baseline data over long periods, are hampering effective CEA. Few articles examined CEA - policy/management nexus. Of the few studies, challenges such as the inadequate implementation of CEA mitigation strategies due to policy drawbacks and resource constraints, the high cost of monitoring multiple indicators, and poor connections between scenarios/modeling and management actions were paramount. Future CEA research is needed to broaden our understanding of how multiple disturbance affects forests in the global south and coupled social and ecological systems and their implications for sustainable forest management.