B046-0001
Climatic and biotic factors influencing regional declines and recovery of tropical forest biomass from the 2015/16 El Niño

Thursday, 10 December 2020
Poster
Hui Yang1, Philippe Ciais2, Wigneron Jean-Pierre3, Jérome Chave4, Oliver Cartus5, Xiuzhi Chen6, Lei Fan7, Julia Green8, Yuanyuan Huang1, Emilie Joetzjer9, Heather Kay10, David Makowski11, Fabienne Maignan12, Maurizio Santoro5, Shengli Tao13, Liyang Liu1 and Yitong Yao1, (1)LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette Cedex, France, (2)LSCE Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette, France, (3)ISPA, UMR 1391, INRA Nouvelle-Aquitaine, Villenave-d'Ornon, France, (4)CNRS & Université Paul Sabatier, UMR 5174 Laboratoire Evolution et Diversité Biologique, Toulouse, France, (5)Gamma Remote Sensing, Guemligen, Switzerland, (6)Sun Yat-Sen University, School of Atmospheric Sciences, Guangzhou, China, (7)ISPA, INRA, Bordeaux, France, (8)Columbia University, New York, United States, (9)CNRM-GAME, Toulouse, France, (10)Aberystwyth University, Aberystwyth, United Kingdom, (11)INRA Institut National de la Recherche Agronomique, Paris Cedex 07, France, (12)CEA Saclay DSM / LSCE, Gif sur Yvette, France, (13)Université Toulouse 3 Paul Sabatier, Laboratoire Evolution et Diversité Biologique (EDB), Toulouse, France
Abstract:
The 2015/16 El Niño brought severe drought and record-breaking temperature in the tropics. Here, using satellite-based L-band microwave vegetation optical depth, we mapped changes of above-ground biomass (AGB) during the drought and in subsequent years up to 2019. Over more than 60% of drought-affected intact forests, AGB reduced during the drought, except in wet central Amazon where AGB declined one year after. By 2019, only 44% of the AGB-reduced intact forests have fully recovered to the pre-drought level. Using random forest models, we found that AGB losses during the drought were mainly associated with soil water deficit and soil clay content. For the AGB recovery, we found the strong influences of the previous AGB losses and vertical forest canopy structure. Based on canopy structure information derived from Lidar waveform data, we separated forests into two categories: forests with high dominant understory closing the top of the canopy, and forests with low understory. The first category forests tend to have a stronger capacity to recover, compared to the second ones mainly distributed near the intact forest edges. This highlights the importance of forest structure responding to drought when predicting the consequences of future drought stress.