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Data from: Quantifying ecological and social drivers of ecological surprise

Citation

Filbee-Dexter, Karen et al. (2019), Data from: Quantifying ecological and social drivers of ecological surprise, Dryad, Dataset, https://doi.org/10.5061/dryad.2c8f32s

Abstract

1. A key challenge facing ecologists and ecosystem managers is understanding what drives unexpected shifts in ecosystems and limits the effectiveness of human interventions during these events. Research that integrates and analyzes data from natural and social systems can provide important insight for unraveling the complexity of these dynamics, and is a critical step towards development of evidence-based, whole systems management approaches. 2. To examine our ability to influence ecosystems that are behaving in unexpected ways, we explore three prominent cases of ‘ecological surprise’. We capture the social-ecological systems using key variables and interactions from Ostrom’s social-ecological systems framework, which integrates broader ecosystem processes (e.g. climate, connectivity), management variables (e.g. quotas, restrictions, monitoring), resource use behaviours (e.g. harvesting), and the resource unit (e.g. trees, fish, clean water) being managed. 3. Structural equation modelling (SEM) revealed that management interventions often influenced resource use behaviours (e.g. rules and limits strongly affected harvest or pollution), but they did not have a significant effect on the abundance of the resource being managed. Instead, most resource variability was related to ecological processes and feedbacks operating at broader spatial or temporal scales than management interventions, which locked the resource system into the degraded state. 4. Synthesis and applications. Mismatch between the influence of management systems and ecosystem processes can limit the effectiveness of human interventions during periods of ecological surprise. Management strategies should shift from a conventional focus on removal or addition of a single resource towards solutions that influence the broader ecosystem. Operationalizing Ostrom’s framework to quantitatively analyze social-ecological systems using SEMs shows promise for testing solutions to navigate these events.

Usage Notes

Funding

National Science Foundation, Award: DBI-1052875

Location

USA
Interior British Columbia Canada
Lake Champlain
Bay of Fundy Canada