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. 2025 Jul 28:13:e19681.
doi: 10.7717/peerj.19681. eCollection 2025.

Using PLUS-InVEST-OPGD model to explore spatiotemporal variation of ecosystem carbon storage and its drivers in Jinsha river basin, China

Lichang Huang  1   2   3 , Xue Ding  1   2   3 , Jinliang Wang  1   2   3 , Shuangyun Peng  1
Affiliations

Using PLUS-InVEST-OPGD model to explore spatiotemporal variation of ecosystem carbon storage and its drivers in Jinsha river basin, China

Lichang Huang et al. PeerJ. .

Abstract

Land-Use/Land-Cover Change (LUCC) is a key disturbance factor of the carbon cycle in terrestrial ecosystems, and the study on the coupling mechanism between LUCC and carbon storage is of great scientific value for implementing a regional carbon-neutral strategy. In this study, the Jinsha River Basin in Yunnan Province, which has outstanding ecological vulnerability, is taken as the research object, and a synergistic analytical framework of "spatial and temporal pattern drivers" is constructed by integrating multi-temporal remote sensing data and multi-model coupling method. Based on the high-precision 30 m land use data from 1990 to 2020, the PLUS-InVEST-OPGD multi-model coupled system was used to simulate and predict the characteristics of spatial and temporal carbon storage differentiation in 2030 under four development scenarios, namely, natural development (ND), ecological protection (EP), farmland protection (FP), and economic development (ED), and to analyze the driving mechanism using the Optimal Parameter Geodetic Probe (OPGP). The driving mechanism is analyzed using an optimal parameter geodetector. The main findings were: (1) The land use structure of the watershed in the study area showed a significant ecological-productive dichotomy, with forest land (60.58%), grassland (28.85%) and cultivated land (7.19%) constituting the core carbon sink carriers (the average proportion of which was 96.62% from 1990 to 2020). Still, the area of forest and grassland decreased by a total of 2,757.84 km2 in the past 30 years, and the expansion of construction land amounted to 2,321.91 km2; (2) the spatial and temporal evolution of carbon storage shows the heterogeneous characteristics of "overall decreasing and local optimization", in which the carbon loss from forest to grassland conversion is as high as 30% of the total carbon loss, and the expansion of construction land leads to irreversible decay of carbon sinks of about 50%; (3) a multi-scenario simulation shows that the EP scenario minimizes the loss of carbon storage (-2.46 × 106 t) by maintaining a 96.82% ecological land share in 2030, reducing the carbon deficit by 7.79 × 106 t compared with the ND scenario; (4) the average annual temperature is the largest single factor affecting carbon storage, and its interaction with the population factor has a high q value of 0.84. This study innovatively reveals the nonlinear threshold effect of LUCC-carbon storage response in the Jinsha River Basin of Yunnan Province, and the proposed optimization model of "ecological protection" can provide decision support and corresponding reference for the construction of ecological security barriers in the upper reaches of the Yangtze River.

Keywords: Carbon storage; Driving mechanism; Future scenario simulation; Jinsha River Basin in Yunnan Province; Land Use and Cover Change (LUCC); Multi-scenario simulation; PLUS-InVEST model.

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Conflict of interest statement

The authors declare there are no competing interests.

Figures

Figure 1
Figure 1. Location map of Jinsha River Basin in Yunnan Province.
(A) Yunnan Province on the Chinese border; (B) Jinsha River Basin in Yunnan Province and abbreviations of various states and cities; (C) specific scope of Jinsha River Basin in Yunnan Province.
Figure 2
Figure 2. Twelve types of driving factors visualization.
Figure 3
Figure 3. Overall technology road map.
Figure 4
Figure 4. Comparison of land use simulation of study area in 2020.
Figure 5
Figure 5. Distribution pattern of land use in Jinsha River Basin, Yunnan Province, 1990–2020.
Figure 6
Figure 6. Land use area transfer in the Jinsha River Basin in Yunnan Province (Note: area transferred out on the left, area transferred in on the right km2).
Figure 7
Figure 7. Distribution of carbon storage in the Jinsha River Basin of Yunnan Province from 1990 to 2020.
Figure 8
Figure 8. Changes in the spatial distribution pattern of carbon storage in the Jinsha River Basin of Yunnan Province from 1990 to 2020.
Figure 9
Figure 9. Forecast of land use distribution by scenarios in Jinsha River Basin, Yunnan Province, 2030.
Figure 10
Figure 10. Projected spatial distribution of carbon storage in the Jinsha River Basin of Yunnan Province by scenario, 2030.
Figure 11
Figure 11. Evolutionary trends of carbon storage in the Jinsha River Basin, Yunnan Province, 1990–2030.
Figure 12
Figure 12. Changes in carbon storage distribution patterns under different scenarios in the Jinsha River Basin, Yunnan Province, 2020–2030.
Figure 13
Figure 13. Drivers affecting the expansion of each taxon in the Jinsha River Basin, Yunnan Province.
Figure 14
Figure 14. Combination of discretized parameters and q-value changes for each driver factor.
Figure 15
Figure 15. Interpretation of carbon storage changes in the study area by single and interactive factors.
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