Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis

The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought–vegetation interaction in this ar...

Full description

Bibliographic Details
Published in:Remote Sensing
Main Authors: Jie Lu, Tianling Qin, Denghua Yan, Xizhi Lv, Zhe Yuan, Jie Wen, Shu Xu, Yuhui Yang, Jianming Feng, Wei Li
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2024
Subjects:
Q
Online Access:https://doi.org/10.3390/rs16040630
https://doaj.org/article/c32b517463bf4682ac3ab4f51a7713e4
id ftdoajarticles:oai:doaj.org/article:c32b517463bf4682ac3ab4f51a7713e4
record_format openpolar
spelling ftdoajarticles:oai:doaj.org/article:c32b517463bf4682ac3ab4f51a7713e4 2024-09-15T18:29:51+00:00 Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis Jie Lu Tianling Qin Denghua Yan Xizhi Lv Zhe Yuan Jie Wen Shu Xu Yuhui Yang Jianming Feng Wei Li 2024-02-01T00:00:00Z https://doi.org/10.3390/rs16040630 https://doaj.org/article/c32b517463bf4682ac3ab4f51a7713e4 EN eng MDPI AG https://www.mdpi.com/2072-4292/16/4/630 https://doaj.org/toc/2072-4292 doi:10.3390/rs16040630 2072-4292 https://doaj.org/article/c32b517463bf4682ac3ab4f51a7713e4 Remote Sensing, Vol 16, Iss 4, p 630 (2024) vapor pressure deficit (VPD) soil moisture (SM) normalized differential vegetation index (NDVI) solar-induced fluorescence (SIF) frozen soil degradation area causal analysis Science Q article 2024 ftdoajarticles https://doi.org/10.3390/rs16040630 2024-08-05T17:49:58Z The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought–vegetation interaction in this area under the influence of climate–permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter–Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the ... Article in Journal/Newspaper permafrost Directory of Open Access Journals: DOAJ Articles Remote Sensing 16 4 630
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic vapor pressure deficit (VPD)
soil moisture (SM)
normalized differential vegetation index (NDVI)
solar-induced fluorescence (SIF)
frozen soil degradation area
causal analysis
Science
Q
spellingShingle vapor pressure deficit (VPD)
soil moisture (SM)
normalized differential vegetation index (NDVI)
solar-induced fluorescence (SIF)
frozen soil degradation area
causal analysis
Science
Q
Jie Lu
Tianling Qin
Denghua Yan
Xizhi Lv
Zhe Yuan
Jie Wen
Shu Xu
Yuhui Yang
Jianming Feng
Wei Li
Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis
topic_facet vapor pressure deficit (VPD)
soil moisture (SM)
normalized differential vegetation index (NDVI)
solar-induced fluorescence (SIF)
frozen soil degradation area
causal analysis
Science
Q
description The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought–vegetation interaction in this area under the influence of climate–permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter–Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the ...
format Article in Journal/Newspaper
author Jie Lu
Tianling Qin
Denghua Yan
Xizhi Lv
Zhe Yuan
Jie Wen
Shu Xu
Yuhui Yang
Jianming Feng
Wei Li
author_facet Jie Lu
Tianling Qin
Denghua Yan
Xizhi Lv
Zhe Yuan
Jie Wen
Shu Xu
Yuhui Yang
Jianming Feng
Wei Li
author_sort Jie Lu
title Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis
title_short Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis
title_full Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis
title_fullStr Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis
title_full_unstemmed Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis
title_sort response of vegetation to drought in the source region of the yangtze and yellow rivers based on causal analysis
publisher MDPI AG
publishDate 2024
url https://doi.org/10.3390/rs16040630
https://doaj.org/article/c32b517463bf4682ac3ab4f51a7713e4
genre permafrost
genre_facet permafrost
op_source Remote Sensing, Vol 16, Iss 4, p 630 (2024)
op_relation https://www.mdpi.com/2072-4292/16/4/630
https://doaj.org/toc/2072-4292
doi:10.3390/rs16040630
2072-4292
https://doaj.org/article/c32b517463bf4682ac3ab4f51a7713e4
op_doi https://doi.org/10.3390/rs16040630
container_title Remote Sensing
container_volume 16
container_issue 4
container_start_page 630
_version_ 1810471314748604416