Assessing recovery time of ecosystems in China : insights into flash drought impacts on gross primary productivity
Lu, Mengge LU ; Sun, Huaiwei ; Yang, Yong ; Xue, Jie ; Ling, Hongbo ; Zhang, Hong and Zhang, Wenxin LU
(2025)
In Hydrology and Earth System Sciences
29(3).
p.613-625
- Abstract
Recovery time, referring to the duration that an ecosystem needs to return to its pre-drought condition, is a fundamental indicator of ecological resilience. Recently, flash droughts – characterised by rapid onset and development – have gained increasing attention. Nevertheless, the spatiotemporal patterns in gross primary productivity (GPP) recovery time and the factors influencing it remain largely unknown. In this study, we investigate the recovery time patterns in a terrestrial ecosystem in China based on GPP using a random forest regression model and the SHapley Additive exPlanations (SHAP) method. A random forest regression model was developed to analyse the factors influencing recovery time and establish response functions... (More)
Recovery time, referring to the duration that an ecosystem needs to return to its pre-drought condition, is a fundamental indicator of ecological resilience. Recently, flash droughts – characterised by rapid onset and development – have gained increasing attention. Nevertheless, the spatiotemporal patterns in gross primary productivity (GPP) recovery time and the factors influencing it remain largely unknown. In this study, we investigate the recovery time patterns in a terrestrial ecosystem in China based on GPP using a random forest regression model and the SHapley Additive exPlanations (SHAP) method. A random forest regression model was developed to analyse the factors influencing recovery time and establish response functions through partial correlation for typical flash drought recovery periods. The dominant driving factors of recovery time were determined using the SHAP method. The results reveal that the average recovery time across China is approximately 37.5 d, with central and southern regions experiencing the longest durations. Post-flash-drought radiation emerges as the primary environmental factor, followed by the aridity index and post-flash-drought temperature, particularly in semi-arid and sub-humid areas. Temperature exhibits a non-monotonic relationship with recovery time, where both excessively cold and hot conditions lead to longer recovery periods. Herbaceous vegetation recovers more rapidly than woody forests, with deciduous broadleaf forests demonstrating the shortest recovery time. This study provides valuable insights for comprehensive water resource and ecosystem management and contributes to large-scale drought monitoring efforts.
(Less)
- author
- Lu, Mengge
LU
; Sun, Huaiwei
; Yang, Yong
; Xue, Jie
; Ling, Hongbo
; Zhang, Hong
and Zhang, Wenxin
LU
- organization
- publishing date
- 2025-02-04
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Hydrology and Earth System Sciences
- volume
- 29
- issue
- 3
- pages
- 13 pages
- publisher
- European Geophysical Society
- external identifiers
-
- scopus:85218344489
- ISSN
- 1027-5606
- DOI
- 10.5194/hess-29-613-2025
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2025 Mengge Lu et al.
- id
- 91c92646-c464-4dcb-b752-808fba8332f6
- date added to LUP
- 2025-03-16 19:12:42
- date last changed
- 2025-04-04 14:58:24
@article{91c92646-c464-4dcb-b752-808fba8332f6,
abstract = {{<p>Recovery time, referring to the duration that an ecosystem needs to return to its pre-drought condition, is a fundamental indicator of ecological resilience. Recently, flash droughts – characterised by rapid onset and development – have gained increasing attention. Nevertheless, the spatiotemporal patterns in gross primary productivity (GPP) recovery time and the factors influencing it remain largely unknown. In this study, we investigate the recovery time patterns in a terrestrial ecosystem in China based on GPP using a random forest regression model and the SHapley Additive exPlanations (SHAP) method. A random forest regression model was developed to analyse the factors influencing recovery time and establish response functions through partial correlation for typical flash drought recovery periods. The dominant driving factors of recovery time were determined using the SHAP method. The results reveal that the average recovery time across China is approximately 37.5 d, with central and southern regions experiencing the longest durations. Post-flash-drought radiation emerges as the primary environmental factor, followed by the aridity index and post-flash-drought temperature, particularly in semi-arid and sub-humid areas. Temperature exhibits a non-monotonic relationship with recovery time, where both excessively cold and hot conditions lead to longer recovery periods. Herbaceous vegetation recovers more rapidly than woody forests, with deciduous broadleaf forests demonstrating the shortest recovery time. This study provides valuable insights for comprehensive water resource and ecosystem management and contributes to large-scale drought monitoring efforts.</p>}},
author = {{Lu, Mengge and Sun, Huaiwei and Yang, Yong and Xue, Jie and Ling, Hongbo and Zhang, Hong and Zhang, Wenxin}},
issn = {{1027-5606}},
language = {{eng}},
month = {{02}},
number = {{3}},
pages = {{613--625}},
publisher = {{European Geophysical Society}},
series = {{Hydrology and Earth System Sciences}},
title = {{Assessing recovery time of ecosystems in China : insights into flash drought impacts on gross primary productivity}},
url = {{http://dx.doi.org/10.5194/hess-29-613-2025}},
doi = {{10.5194/hess-29-613-2025}},
volume = {{29}},
year = {{2025}},
}