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Abstract
Disturbances, such as hurricanes, fires, droughts, and pest outbreaks, can cause major changes in ecosystem conditions that threaten nature’s contributions to people (ecosystem services). However, approaches to assess these impacts on diverse services under climate change are rare. To advance such efforts, we build on the accelerating research on disturbance ecology and ecosystem services to develop a functional trait-based approach to quantify ecological, ecosystem service, and economic outcomes under risk and climate change. We demonstrate this general approach by quantifying impacts to ecosystem services—timber and recreational enjoyment—from extreme windstorms in a mid-latitude forest. We find that expected ecosystem service losses from these windstorm disturbances are large and likely to increase with climate change. Yet, we show that common ecological metrics of compositional and biomass stability are inadequate for predicting these impacts to ecosystem service, necessitating more direct measures of services with disturbance. We then illustrate our approach for other applications spanning different ecosystems, services, and disturbances, including crop pollination, flood hazard mitigation, and cultural values. These examples highlight the pressing need to consider disturbances in future ecosystem service assessments, given the increase in mega-disturbances occurring globally with climate change.
DOI
https://doi.org/10.32942/X26D0M
Subjects
Biodiversity, Ecology and Evolutionary Biology, Life Sciences
Keywords
Nature’s contributions to people, Extreme Events, climate change, functional traits, 27 response and effect traits, Risk, future scenarios, response and effect traits, nature's contributions to people, extreme events, Risk, climate change, functional traits, response and effect traits, future scenarios
Dates
Published: 2024-08-27 17:51
License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
Additional Metadata
Language:
English
Conflict of interest statement:
None
Data and Code Availability Statement:
We use publicly available data and provide references to relevant data sources. We provide a link in the paper to our GitHub project page referenced in the paper.
There are no comments or no comments have been made public for this article.