1) Revealing the pathways to scale up agricultural transformation: Factors influencing adoption of Silvo pastoral systems in Colombia
2) Developing a field-scale crop yield prediction model using satellite and environmental data
Time: 12:30pm to 1:20pm
Location: Beaty Museum Allan Yap Theatre (Basement, 2212 Main Mall) Please check in at the Admissions Desk first before going to the Theatre.
No food or drinks allowed in the Theatre.
Click here for Zoom link. Zoom will be terminated if we encounter tech problems 5 to 10 mins into the seminar.
Colombia is a global biodiversity hotspot of important ecological significance. However, deforestation is rampant in the country, and its primary cause is extensive cattle ranching which is inefficient, susceptible to climatic events, contributes to poverty, and causes unsustainable levels of environmental degradation such as water pollution. An agroecological alternative to ECR is Silvopastoral systems (SPS) which combine trees and shrubs in forage grasses to enhance cattle production. Thus, the goal of my research is to determine how SPS practices can be scaled out.
Tatiana Chamorro (she/her) is an MSc student in the Working to Restore Connectivity and Sustainability (WoRCS) Lab at IRES and is supervised by Dr. Claire Kremen. Her research focuses on the scaling up of sustainable cattle ranching practices in Colombia, as she is highly interested in biodiversity conservation and ecology. She is a recipient of the Philip A. Jones Fellowship 2022-2023. She is also the trip coordinator for the RES Student Society.
Timely and reliable estimation of crop production is essential for strategic decision making in the agricultural system. Recently, detailed ground-based field-scale yield datasets have become available providing a timely opportunity for using high spatial resolution observational data for model training. The key research objective was to develop a crop-yield prediction model using satellite and biophysical data and calibrated using field-scale yield monitor data.
Jumi recently completed her PhD in IRES under the supervision of Dr. Navin Ramankutty. She is pursuing her research interests in mobilizing methods from data science to answer questions about food security. Her PhD work specifically focuses on developing modeling methods using different datasets for improving prediction of crop production. Jumi has an interdisciplinary academic background and has completed studies in analytics, economics, and business.