气候变化领域集成服务门户(CCPortal): Both near-surface and satellite remote sensing confirm drought legacy effect on tropical forest leaf phenology after 2015/2016 ENSO drought

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DOI	10.1016/j.rse.2019.111489
	Both near-surface and satellite remote sensing confirm drought legacy effect on tropical forest leaf phenology after 2015/2016 ENSO drought
	Gonçalves N.B.; Lopes A.P.; Dalagnol R.; Wu J.; Pinho D.M.; Nelson B.W.
发表日期	2020
ISSN	00344257
卷号	237
英文摘要	Amazon forest leaf phenology patterns have often been inferred from the Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI). But reliable MODIS detection of seasonal and interannual leaf phenology patterns has also been questioned and is generally not validated with field observation. Here we compare inter-annual patterns of local-scale upper canopy leaf phenology and demography derived from tower-mounted phenocams at two upland forest sites in the Central Amazon, to corresponding satellite vegetation indices retrieved from MODIS-MAIAC (Multi-Angle Implementation of Atmospheric Correction). We focus on forest response to an unprecedented drought caused by the El Niño of 2015-16. At both sites, multi-year phenocam data showed post-drought shifts in leaf demography. These were consistent with MODIS-MAIAC anomalies in two vegetation indices. Specifically, a precocious leaf flush at both sites during the first two post-drought months, Feb-Mar 2016, caused (1) an anomalous decrease in flushing trees in Jun–Jul of 2016 and (2) an increase of trees with early mature stage leaves (2-4 mo age) in Apr-May-Jun of 2016. At both sites, these two phenological anomalies showed up in MODIS-MAIAC as, respectively, (1) a strong negative anomaly in Gcc (Green chromatic coordinate), which prior work has shown to be sensitive to the abundance of leaves 0-1 mo old, and (2) a strong positive anomaly in EVI, which is sensitive to abundance of leaves 2-4 mo age. A shift to sub-optimal seasonal leaf age mix is expected to change the ecosystem-scale intrinsic photosynthetic capacity for ~18 month after the drought. © 2019 Elsevier Inc.
英文关键词	Amazon green-up; El Niño; EVI seasonality; Leaf demography; MODIS-MAIAC; Phenocam
语种	英语
scopus关键词	Drought; Population statistics; Radiometers; Remote sensing; Tropics; Vegetation; Green-up; Leaf demography; MODIS-MAIAC; Phenocam; Seasonality; Forestry; demographic survey; detection method; drought; El Nino-Southern Oscillation; leaf; MODIS; phenology; remote sensing; satellite altimetry; seasonality; tropical forest; vegetation index; Amazonas [Brazil]; Brazil
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179544
作者单位	INPA – National Institute for Amazon Research, Environmental Dynamics Department, Manaus, AM, Brazil; Michigan State University, Department of Forestry, College of Agriculture & Natural Resources, East LansingMI, United States; INPE – National Institute for Space Research, Remote Sensing Division, São José dos CamposSP, Brazil; University of Hong Kong, School of Biological Sciences, China
推荐引用方式 GB/T 7714	Gonçalves N.B.,Lopes A.P.,Dalagnol R.,et al. Both near-surface and satellite remote sensing confirm drought legacy effect on tropical forest leaf phenology after 2015/2016 ENSO drought[J],2020,237.
APA	Gonçalves N.B.,Lopes A.P.,Dalagnol R.,Wu J.,Pinho D.M.,&Nelson B.W..(2020).Both near-surface and satellite remote sensing confirm drought legacy effect on tropical forest leaf phenology after 2015/2016 ENSO drought.Remote Sensing of Environment,237.
MLA	Gonçalves N.B.,et al."Both near-surface and satellite remote sensing confirm drought legacy effect on tropical forest leaf phenology after 2015/2016 ENSO drought".Remote Sensing of Environment 237(2020).