Thu, Aug 18, 2022: 4:30 PM-4:45 PM
514A
Background/Question/MethodsEcosystem services (ES) are shaped by dynamic social-ecological interactions across a range of scales. However, static methodologies prevail in ES research, and as a consequence, the extent, shapes, and drivers of ES response curves remain largely unexamined, yet may be key for understanding the sustainability of ES. To address this challenge, we compiled historical data sources to analyse changes in the time series of social indicators (market prices and demand) and ecological indicators (biophysical supply, capacity, and flows) for six ES: flood regulation, timber harvesting, fur trapping, big game hunting tourism, subsistence hunting, and the salmon fishery. Each ES was analyzed with at least one social and one ecological indicator and at multiple scales (provincial, regional, and local administrative units), resulting in >1000 individual times series 40 to 100 years in length. We used the Strucchange package in R to analyze the shape of ES change and timing of structural breaks in ES dynamics. To identify drivers, we then qualitatively examined historical events, including global economic recessions and local policy changes that best coincide with the structural breaks effecting ES temporal dynamics.
Results/ConclusionsMost ES time series exhibited non-linear dynamics (62%) or linearly increasing or decreasing trajectories (23%). The remaining 15% were relatively static (following an intercept only model) until abrupt step changes shifted their intercept. Nearly all ES trajectories experienced at least one break in their time series. Some breaks were synchronous across either multiple geographic regions (e.g., hunting tourism) or across multiple ES. For example, the trajectories of timber, hunting tourism, salmon, and fur trapping shifted synchronously when environmental policies in the 1990’s initiated or exacerbated declining trends in provisioning ES. Reflecting on the ESA conference theme ‘a change is gonna come,’ our results demonstrate that change is constant, occurs in many forms (non-linear increases vs. abrupt step changes), and is a result of drivers at many scales (e.g., one ES changes vs. multiple ES change synchronously). Characterizing ES temporal dynamics can reveal emerging threats to ES sustainability, as well as opportunities to lever policy and management for maintaining stable flows of ES into the future. Efforts to reconstruct and analyze temporal change, such as through historical reconstructions, can help foster a paradigm shift in ES research toward more explicit recognition of the inherent social-ecological dynamism of ES.
Results/ConclusionsMost ES time series exhibited non-linear dynamics (62%) or linearly increasing or decreasing trajectories (23%). The remaining 15% were relatively static (following an intercept only model) until abrupt step changes shifted their intercept. Nearly all ES trajectories experienced at least one break in their time series. Some breaks were synchronous across either multiple geographic regions (e.g., hunting tourism) or across multiple ES. For example, the trajectories of timber, hunting tourism, salmon, and fur trapping shifted synchronously when environmental policies in the 1990’s initiated or exacerbated declining trends in provisioning ES. Reflecting on the ESA conference theme ‘a change is gonna come,’ our results demonstrate that change is constant, occurs in many forms (non-linear increases vs. abrupt step changes), and is a result of drivers at many scales (e.g., one ES changes vs. multiple ES change synchronously). Characterizing ES temporal dynamics can reveal emerging threats to ES sustainability, as well as opportunities to lever policy and management for maintaining stable flows of ES into the future. Efforts to reconstruct and analyze temporal change, such as through historical reconstructions, can help foster a paradigm shift in ES research toward more explicit recognition of the inherent social-ecological dynamism of ES.