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The time scale of resilience-based forecasts and their potential use
Citation:
Batt, R., T. Eason, AND A. Garmestani. The time scale of resilience-based forecasts and their potential use. Ecological Society of America, New Orleans,LA, August 05 - 10, 2018.
Impact/Purpose:
Early warning theory can provide useful information about upcoming state transitions, but that developing the theory of social-ecological dynamics is critical for sustaining ecosystem and human health.
Description:
It is notoriously difficult to predict abrupt changes involving critical transitions (a type of regime shift), and these changes include management-relevant events like fisheries, collapses, and harmful algal blooms. However, recent theoretical and experimental work suggests that even when ecosystem state changes abruptly, the resilience and dynamical behavior of the system changes steadily. These slow changes in resilience might provide early warnings of regime shifts. As early warning theory has developed, many potential barriers toward its implementation have been identified. Among these challenges are issues concerning how to measure ecosystem state and calculating early warning statistics, how managers should respond to these statistics, and whether warnings will provide useful opportunities for intervention. In this talk, I will focus on algal blooms as a case study for discussing how temporal scale can present challenges to implementing resilience-based forecasts. Are forecasts sensitive to the frequency of field measurements and the temporal scale of statistical analyses? How does the time horizon of a forecast interact with the time scale of governance and politics to produce sustainable strategies for managing ecosystems prone to critical transitions?