Simulation and attribution analysis of terrestrial ecosystem carbon storage of Hainan Island from 2015 to 2050

Abstract

Terrestrial ecosystem carbon storage (TECS) could significantly affect the concentration of atmospheric CO2, which is critical for climate change prediction. Along these lines, the Integrated Valuation of Ecosystem Services and Trade-offs model was employed to determine the TECS of Hainan Island (HN) from 2015 to 2050 accurately. Besides, the Future Land-use Simulation model combined with natural and anthropogenic factors was used to forecast the land-use types from 2025 to 2050 in HN by considering different Shared-socioeconomic pathway-Rrepresentative concentration pathway (SSP-RCP) scenarios. Finally, the geographical detector explored the influence mechanism concerning the TECS. Under the SSP1-RCP1.9 scenario, the TECS of HN will be gradually increased to 388.10 million tons in 2050, mainly due to the increase in forest areas and the fact that the majority of grassland in the western part of HN is being converted into forest. Under different SSP-RCP scenarios except for SSP1-RCP1.9, HN's TECS is expected to gradually decrease from 2015 to 2050, mainly due to the loss of grassland and forest in coastal low-altitude areas. From the single/pair factor perspective influenced mechanism concerning the TECS, the elevation (DEM) and DEM∩Slope were found to be the dominant single/pair factor under the SSP1-RCP1.9, SSP1-RCP2.6 and SSP2-RCP4.5 scenarios. The least distance to residential area (LDP) and LDP∩LDR (i.e. LDP and least distance to roads or railways) were found to be the dominant factors under the SSP3-RCP7.0, SSP4-RCP3.4, SSP4-RCP6.0, SSP5-RCP3.4 and SSP5-RCP8.5 scenarios. Besides, the pair factors provided a higher determinant power for TECS than a single factor. Given the results of the TECS and the influence mechanism concerning the TECS under different SSP-RCP scenarios, we suggest reasonably planning the transportation network and limiting the disorderly expansion of construction land.