| Literature DB >> 35733266 |
Hui Yang1, Philippe Ciais1, Jean-Pierre Wigneron2, Jérôme Chave3, Oliver Cartus4, Xiuzhi Chen5, Lei Fan6, Julia K Green1, Yuanyuan Huang7, Emilie Joetzjer8, Heather Kay9, David Makowski10, Fabienne Maignan1, Maurizio Santoro4, Shengli Tao3, Liyang Liu1,5, Yitong Yao1.
Abstract
The 2015/16 El Niño brought severe drought and record-breaking temperatures 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 the wettest part of the central Amazon, where it declined 1 y later. By the end of 2019, only 40% of AGB reduced intact forests had fully recovered to the predrought level. Using random-forest models, we found that the magnitude of AGB losses during the drought was mainly associated with regionally distinct patterns of soil water deficits and soil clay content. For the AGB recovery, we found strong influences of AGB losses during the drought and of [Formula: see text]. [Formula: see text] is a parameter related to canopy structure and is defined as the ratio of two relative height (RH) metrics of Geoscience Laser Altimeter System (GLAS) waveform data-RH25 (25% energy return height) and RH100 (100% energy return height; i.e., top canopy height). A high [Formula: see text] may reflect forests with a tall understory, thick and closed canopy, and/or without degradation. Such forests with a high [Formula: see text] ([Formula: see text] ≥ 0.3) appear to have a stronger capacity to recover than low-[Formula: see text] ones. Our results highlight the importance of forest structure when predicting the consequences of future drought stress in the tropics.Entities:
Keywords: drought; forest structure; recovery; tropical forest
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Year: 2022 PMID: 35733266 PMCID: PMC9245643 DOI: 10.1073/pnas.2101388119
Source DB: PubMed Journal: Proc Natl Acad Sci U S A ISSN: 0027-8424 Impact factor: 12.779