Emerging multiscale insights on microbial carbon use efficiency in the land carbon cycle
Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial
ecosystems, but its global importance remains uncertain. Accurately modeling and …
ecosystems, but its global importance remains uncertain. Accurately modeling and …
Temperature controls the relation between soil organic carbon and microbial carbon use efficiency
Microbial carbon use efficiency (CUE) is an important variable mediating microbial effects on
soil organic carbon (SOC) since it summarizes how much carbon is used for microbial …
soil organic carbon (SOC) since it summarizes how much carbon is used for microbial …
[HTML][HTML] Simulating the land carbon sink: Progresses and challenges of terrestrial ecosystem models
W Yuan, J **a, C Song, YP Wang - Agricultural and Forest Meteorology, 2024 - Elsevier
Terrestrial ecosystems play an important role in regulating the balance of global carbon
cycle by sequestrating CO 2 of atmosphere. Terrestrial ecosystem models are a critical tool …
cycle by sequestrating CO 2 of atmosphere. Terrestrial ecosystem models are a critical tool …
When and why microbial-explicit soil organic carbon models can be unstable
E Schwarz, S Ghersheen, S Belyazid… - …, 2024 - bg.copernicus.org
Microbial-explicit soil organic carbon (SOC) cycling models are increasingly being
recognized for their advantages over linear models in describing SOC dynamics. These …
recognized for their advantages over linear models in describing SOC dynamics. These …
Biogeochemistry-Informed Neural Network (BINN) for Improving Accuracy of Model Prediction and Scientific Understanding of Soil Organic Carbon
Big data and the rapid development of artificial intelligence (AI) provide unprecedented
opportunities to enhance our understanding of the global carbon cycle and other …
opportunities to enhance our understanding of the global carbon cycle and other …
Parameter Estimation in Land Surface Models: Challenges and Opportunities with Data Assimilation and Machine Learning
Accurately predicting terrestrial ecosystem responses to climate change is crucial for
addressing global challenges. This relies on mechanistic modelling of ecosystem processes …
addressing global challenges. This relies on mechanistic modelling of ecosystem processes …