Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model

The changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial ecosystem carbon...

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Main Authors: Huihui Zhao, Bing Guo, Guojun Wang
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Forests
Subjects:
Online Access:https://www.mdpi.com/1999-4907/14/7/1352
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author Huihui Zhao
Bing Guo
Guojun Wang
author_facet Huihui Zhao
Bing Guo
Guojun Wang
author_sort Huihui Zhao
collection DOAJ
description The changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial ecosystem carbon storage and their influencing factors during a long study period had important theoretical and practical significance for achieving the goal of carbon neutrality. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) was used to analyze the changes in carbon storage based on vegetation-type data during 2000–2020. The Path-generating Land-Use Simulation model (PLUS) was then used to predict the spatial distribution of carbon storage in the Tibetan Plateau in 2030 and 2060 under inertial development, farmland protection and ecology priority scenarios. The results showed that: (1) The degradation of vegetation types reduced the carbon storage during the study period. During 2000–2020, the desert shrub and non-vegetation area expanded by 63.21% and 13.35%, respectively, while the deciduous scrub, mixed forest and low coverage grassland decreased accordingly. The carbon storage of the Tibetan Plateau showed a decreasing trend by 0.37 × 10<sup>6</sup> t. (2) The spatial distribution patterns of carbon storage were consistent with that of the vegetation types. (3) In 2030 and 2060, under the constraint of the ecological priority development, the reduction in carbon storage was the smallest, at 0.01 × 10<sup>6</sup> t and 0.16 × 10<sup>6</sup> t, respectively. Under the constraint of the inertial development, carbon storage had the largest reduction, at 0.12 × 10<sup>6</sup> t and 0.43 × 10<sup>6</sup> t, respectively. (4) During 2000–2020, the dominant single factor that had the greatest impacts on the changes in carbon storage was FVC (vegetation coverage), with q values of 0.616, 0.619 and 0.567, respectively. The interactive dominant effects were mainly nonlinear enhancement and double-factor enhancement. The interactive dominant factors that had the greatest impact were FVC and the DEM (Digital Elevation Model), with q values of 0.94, 0.92 and 0.90, respectively. Therefore, ecological land with a high FVC should be protected and the expansion of non-vegetation areas should be restricted in future planning to improve the carbon storage level of the Tibetan Plateau and achieve the goal of carbon neutrality.
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spelling doaj.art-34fbb876a24943578961ce4bbe5ae8f92023-11-18T19:23:02ZengMDPI AGForests1999-49072023-06-01147135210.3390/f14071352Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST ModelHuihui Zhao0Bing Guo1Guojun Wang2Research Institute of Aerospace Information, Chinese Academy of Sciences, Beijing 100101, ChinaResearch Institute of Aerospace Information, Chinese Academy of Sciences, Beijing 100101, ChinaResearch Institute of Aerospace Information, Chinese Academy of Sciences, Beijing 100101, ChinaThe changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial ecosystem carbon storage and their influencing factors during a long study period had important theoretical and practical significance for achieving the goal of carbon neutrality. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) was used to analyze the changes in carbon storage based on vegetation-type data during 2000–2020. The Path-generating Land-Use Simulation model (PLUS) was then used to predict the spatial distribution of carbon storage in the Tibetan Plateau in 2030 and 2060 under inertial development, farmland protection and ecology priority scenarios. The results showed that: (1) The degradation of vegetation types reduced the carbon storage during the study period. During 2000–2020, the desert shrub and non-vegetation area expanded by 63.21% and 13.35%, respectively, while the deciduous scrub, mixed forest and low coverage grassland decreased accordingly. The carbon storage of the Tibetan Plateau showed a decreasing trend by 0.37 × 10<sup>6</sup> t. (2) The spatial distribution patterns of carbon storage were consistent with that of the vegetation types. (3) In 2030 and 2060, under the constraint of the ecological priority development, the reduction in carbon storage was the smallest, at 0.01 × 10<sup>6</sup> t and 0.16 × 10<sup>6</sup> t, respectively. Under the constraint of the inertial development, carbon storage had the largest reduction, at 0.12 × 10<sup>6</sup> t and 0.43 × 10<sup>6</sup> t, respectively. (4) During 2000–2020, the dominant single factor that had the greatest impacts on the changes in carbon storage was FVC (vegetation coverage), with q values of 0.616, 0.619 and 0.567, respectively. The interactive dominant effects were mainly nonlinear enhancement and double-factor enhancement. The interactive dominant factors that had the greatest impact were FVC and the DEM (Digital Elevation Model), with q values of 0.94, 0.92 and 0.90, respectively. Therefore, ecological land with a high FVC should be protected and the expansion of non-vegetation areas should be restricted in future planning to improve the carbon storage level of the Tibetan Plateau and achieve the goal of carbon neutrality.https://www.mdpi.com/1999-4907/14/7/1352vegetation type changesInVEST modelmulti-scenario constraintscarbon storageTibetan Plateau
spellingShingle Huihui Zhao
Bing Guo
Guojun Wang
Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
Forests
vegetation type changes
InVEST model
multi-scenario constraints
carbon storage
Tibetan Plateau
title Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
title_full Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
title_fullStr Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
title_full_unstemmed Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
title_short Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
title_sort spatial temporal changes and prediction of carbon storage in the tibetan plateau based on plus invest model
topic vegetation type changes
InVEST model
multi-scenario constraints
carbon storage
Tibetan Plateau
url https://www.mdpi.com/1999-4907/14/7/1352
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AT bingguo spatialtemporalchangesandpredictionofcarbonstorageinthetibetanplateaubasedonplusinvestmodel
AT guojunwang spatialtemporalchangesandpredictionofcarbonstorageinthetibetanplateaubasedonplusinvestmodel