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Researcher Profile: Trent Biggs

Water Production Connections

Edited by Cassie Sevigny

Trent Biggs kneels in a pasture looking at a rainfall simulator set up on the ground. Cleiton Cavalheiro stands next to him, hands on his hips.
Trent Biggs and Cleiton Cavalheiro watching a rainfall simulator.

The Connections between Water and Rural Production project (CAP) investigates whether and which farmers adapt their production systems when they experience changes in rainfall, what adaptations they make, and whether these adaptations reduce income losses expected when drying occurs. Improved understanding of these responses will inform efforts by government agencies and civil society to help farmers adjust to changes in water availability. This profile is based on an interview with Co-Principal Investigator Trent Biggs.


Why and how did you become involved in this project?

My PhD work was in Rondonia (1997-2003). I met Dr. Jill Caviglia-Harris in 2003; I emailed her to see if she was interested in collaborating on data to help interpret stream chemistry data for my PhD. She later invited me to participate in the 2016 SESYNC workshop series, which resulted in this grant proposal and project.

What is your favorite part of being in the field?

Speaking Portuguese and learning from people in Rondonia about their problems, issues, and needs.

What has been the biggest challenge of performing research?

COVID has restricted my hydrology fieldwork, which involves streamflow measurements.

What’s one thing you’ve learned while participating in this project?

Farmers are very actively changing their farming practices as better technology becomes available and as government extension agencies become more active.

Why do you think this project is important?

Climate is changing in the Amazon due to both global warming and deforestation, and we need to figure out the impacts and possible adaptations to mitigate it.

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Connections between Water and Rural Production: Sociohydrological Systems on a Tropical Forest Frontier

Project funded by the National Science Foundation: CNH-L #1825046

A collaboration between:

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