Detection of Carbon Use Efficiency Extremes and Analysis of Their Forming Climatic Conditions on a Global Scale Using a Remote Sensing-Based Model

Carbon use efficiency (CUE) represents the proficiency of plants in transforming carbon dioxide (CO2) into carbon stock in terrestrial ecosystems. CUE extremes represent ecosystems' extreme proficiency in carbon transformation. Studying CUE extremes and their forming climate conditions is critical for enhancing ecosystem carbon storage. However, the study of CUE extremes and their forming climate conditions on the global scale is still lacking. In this study, we used the results from the daily Boreal Ecosystem Productivity Simulator (BEPS) model to detect the positive and negative CUE extremes and analyze their forming climatic conditions on a global scale. We found grasslands have the largest potential in changing global CUE, with the contribution being approximately 32.4% to positive extremes and 30.2% to negative extremes. Spring in the Northern Hemisphere (MAM) contributed the most (30.5%) to positive CUE extremes, and summer (JJA) contributed the most (29.7%) to negative CUE extremes. The probabilities of gross primary production (GPP) extremes resulted in CUE extremes (>25.0%) being larger than autotrophic respiration (Ra), indicating CUE extremes were mainly controlled by GPP rather than Ra extremes. Positive temperature anomalies (0 similar to 1.0 degrees C) often accompanied negative CUE extreme events, and positive CUE extreme events attended negative temperature anomalies (-1.0 similar to 0 degrees C). Moreover, positive (0 similar to 20.0 mm) and negative precipitation (-20.0 similar to 0 mm) anomalies often accompanied positive and negative CUE extremes, respectively. These results suggest that cooler and wetter climate conditions could be beneficial to enhance carbon absorptions of terrestrial ecosystems. The study provides new knowledge on proficiency in carbon transformation by terrestrial ecosystems.