Local land‐use decisions drive losses in river biological integrity to 2099: Using machine learning to disentangle interacting drivers of ecological change in policy forecasts

Local land‐use decisions drive losses in river biological integrity to 2099: Using machine learning to disentangle interacting drivers of ecological change in policy forecasts

Abstract Climate and land‐use/land‐cover (LULC) change each threaten the health of rivers. Rising temperatures, changes in rainfall and runoff, and other perturbations, will all impact rivers' physical, biological, and chemical characteristics over the next century. While scientists and policym...

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Bibliographic Details
Main Authors: Kimberly Bourne, Ryan S. D. Calder, Shan Zuidema, Celia Y. Chen, Mark E. Borsuk
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Meteorological Applications
Subjects:
biological integrity
climate change
decision support
forecasting
green infrastructure
land use
Online Access:https://doi.org/10.1002/met.70024
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https://doi.org/10.1002/met.70024

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