Yu Mo

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Research Fellow at the University of Oxford

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Datasets & code

Teaching

Research interests

Coastal ecosystems are vital for climate risk mitigation and adaptation, yet these ecosystems themselves are among the most vulnerable to the impacts of climate change. My research centres on the question: How does the resilience of these ecosystems to climate change affect their functioning under such pressures? I am also passionate about developing new Earth and data science methodologies to deepen our understanding of coastal ecosystem dynamics and their functions at regional and global scales.


Research highlights

The Magic of Mangrove Who defends the defenders?

Some recent publications

Y. Mo, M. Simard, J. W. Hall. Tropical cyclone risk to global mangrove ecosystems: potential future regional shifts. Frontiers in Ecology and the Environment (2023) 21(6): 269–274. doi:10.1002/fee.2650. Access via publisher
Y. Mo, M. S. Kearney, R. E. Turner. The resilience of coastal marshes to hurricanes: the potential impact of excess nutrient. Environmental International (2020) 138: 105409. doi:10.1016/j.envint.2019.105409. Access via pulisher


Projects

CoastNet: ML for storm damage to global mangrove ecosystems. 2022-2024. Funded by Government of Ireland Postdoctoral Fellowship. Find out more

Storm damage to global electricity network: Global storm risk to coastal cities under climate change. 2021-2014. Funded by NERC & Oxford John Fell Fund. Find out more

CHES: Resilience of Coastal Human-Environment Systems. 2020-2022. Funded by Marie Curie Postdoctoral Fellowship. Find out more

Phenology of Louisiana coastal marshes from 1984-2014: Annual growth pattern changes associated with climate change and disastrous events. Find out more


Datasets

Global storm attributes: Global storm attributes derived from historical records from 1980-2020 (at 1 degree). View and download data


Code

A non-linear mixed model: A statistical tool for analysing time series data with complex patterns, such as phenological records. It has the capability of comparing parameter estimates among different vegetation types. Find out more


Teaching

Experimental Design and Analysis. 2022. Trinity College Dublin. Resources