Enhancing Community and Wildlife Resilience to Sea?Level Rise and Infrastructure Development in the San Pablo Baylands
Description
Considerable public dollars will be invested in both tidal marsh restoration and transportation upgrades in the Baylands; yet the combined and interactive effects of SLR and infrastructure changes on wildlife habitat, local communities, and public access are largely unknown.
Detailed example
Wildlife-habitat relationships will be modeled using boosted regression tree or similar machine learning method
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The goal of our project is to understand the potential impacts of SLR and transportation redesigns on the Baylands and identify management actions that could be taken to achieve desired future habitat and public access targets.
Controls / human review
ATO: No; PIA: Not published