Forums | HES 健康与环境科学

14 November 2022, 4:45 PM

Speaker: Dr. Yi Yang

Time: 10:45-12:00

Location: ES354

Title

Carbon dynamics in abandoned agricultural lands and croplands

Abstract

#1 Abandoned agricultural lands (old fields) have the potential to sequester C and mitigate atmospheric CO₂. Currently, factors controlling the soil C and N dynamics after agricultural cessation are poorly understood, especially the long-term effect of burrowing animal soil disturbance, although they are ubiquitous in abandoned agricultural lands. Also, most C sequestration research only focuses on the top 30 cm, and we lack a clear understanding of C dynamics below 30 cm. I developed a developing a process model to simulate the effect of pocket gopher disturbance on soil C accumulation in the old field ecosystems). I found pocket gopher disturbance reduced soil C accumulation rates, and vegetation recolonization on gopher mounds was the critical factor that determines the impact that gophers have on the soil C pool. Next, I examined the changes in C and N pools in both surface and subsurface soil at 21 old fields. I found the C accumulation in the surface soil was offset by the losses in the subsurface soil.

#2 Improving the prediction of crop production is critical for strategy development associated with global food security, particularly as the climate continues to change. Process-based ecosystem models are increasingly used for simulating global agricultural production. However, such simulations often use a single crop variety in global assessments, implying that major crops are identical across all regions of the world. To address this limitation, I applied a Bayesian approach to calibrate regional types of maize (Zea mays L), capturing the aggregated traits of local varieties, for DayCent ecosystem model simulations, using global crop production data from 2001 to 2013. We selected major cropping regions from the FAO Global Agro-Environmental Stratification as a basis for the regionalization and identified the most important model parameters through a global sensitivity analysis. We calibrated DayCent using the sampling importance resampling algorithm and found significant improvement in DayCent simulations of maize yields with the calibrated regional varieties.