LIU Yiwen, YUAN Lin, YAN Ziteng. Study on temporal and spatial evolution characteristics and influencing factors of carbon storage in Giant Panda National Park[J]. NATIONAL PARK, 2025, 3(4): 207-223. DOI: 10.20152/j.np.202411292935
Citation: LIU Yiwen, YUAN Lin, YAN Ziteng. Study on temporal and spatial evolution characteristics and influencing factors of carbon storage in Giant Panda National Park[J]. NATIONAL PARK, 2025, 3(4): 207-223. DOI: 10.20152/j.np.202411292935

Study on temporal and spatial evolution characteristics and influencing factors of carbon storage in Giant Panda National Park

  • Giant Panda National Park serves as a crucial ecological barrier in Western China. The research of its carbon storage′s spatio-temporal evolution characteristics and influencing factors is of significant value for maintaining regional carbon balance, promoting ecological conservation, and fostering green development. Based on the PLUS-InVEST-GeoDetector model, as well as five phases of land use data from 2000 to 2020 within the park, this study systematically analyzes the spatio-temporal evolution characteristics and influencing factors. Through the CA-Markov model, the land use patterns under two scenarios of natural development and ecological protection for the year 2030 are further simulated, and the corresponding changes in carbon storage are estimated. The key findings are as follows: (1) During the study period, carbon storage in the Giant Panda National Park initially increased and then decreased. It consistently grew from 2000 to 2010 but declined from 2010 to 2020, with a reduction of 2.061×105 t in 2020 compared to 2000. The spatial distribution remained relatively stable, displaying a pattern of high levels in the northeast and low levels in the southwest. (2) Fluctuation, elevation and average annual temperature are key driving factors affecting the spatio-temporal evolution of carbon storage. Notably, the interaction effect between slope and vegetation coverage significantly impacts carbon storage. (3) Multi-scenario predictive analysis indicates that by 2030, the carbon stock under natural development will decrease by 1.053×105 t compared to 2020. However, the ecological protection measures can increase the carbon stock by 1.160×105 t, providing vital insights for the sustainable development and ecological management of other national parks.
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