Coupling PLUS–InVEST Model for Ecosystem Service Research in Yunnan Province, China

Abstract

In efforts to improve regional ecosystem service functions, coordinate land development and ecological conservation, and establish a reference for optimizing land resource allocation and policy formulation to cope with climate change, it is critical to investigate the spatial distribution of land use/cover change (LUCC) and ecosystem services (ESs) under future climate change. This study proposes a framework based on the Shared Socioeconomic Pathway and Representative Concentration Pathway (SSP-RCP), integrating the patch-generating land use simulation (PLUS) model and the integrated valuation of ecosystem services and tradeoffs (InVEST) model to analyze the spatial agglomeration of ESs, to analyze the importance of each driving factors. The results of the study show as follows: (1) the combination of CMIP6 and PLUS models can effectively simulate land use with an overall accuracy of 0.9379. (2) In spatial correlation, ESs show good clustering in all three future scenarios, with similar distribution of cold hotspots in the SSP126 and SSP245 scenarios. Hotspots are more dispersed and cold spots are shifted to the west in the SSP585 scenario. (3) GDP is an important factor in carbon storage and habitat quality, and precipitation has a greater impact on soil retention and water production. Overall, ESs can be increased by appropriately controlling population and economic development, balancing economic development and ecological protection, promoting energy transition, maintaining ecological hotspot areas, and improving cold spot areas.

Simulation and Zoning Research on the Ecosystem Service in the Beijing–Tianjin–Hebei Region Based on SSP–RCP Scenarios

“…This has been confirmed by the findings of other studies [47]. Upon closer examination, we observe a declining trend in both habitat quality and food product services compared to the year 2020, corroborating earlier findings [41,48]. Similarly, the SSP1-2.6 demonstrates the highest carbon storage capacity, aligning with Wang's results [49].…”

Spatiotemporal Evolution and Prediction of Ecosystem Carbon Storage in the Yiluo River Basin Based on the PLUS-InVEST Model

“…SSP585 (coupling the SSP5 and RCP8.5 scenarios) is a high-speed development scenario dominated by fossil fuels, which is a barbaric development, the pursuit of development at all costs [37,38]. In this paper, three scenarios, SSP126, SSP245, and SSP585, were selected to predict carbon storage in the study area by considering the possibility of future development and the status of the study area [16].…”

“…Some scholars use land-use simulation models such as Dyna-CLUE, FLUS, CA-Markov, and other land-use simulation models coupled with InVEST models to predict future carbon stocks. Although the above methods can well simulate future land-use changes, they cannot find out the potential driving factors of land-use changes and the evolution of patches [8,16]. On the basis of these shortcomings, Liang [17] and other scholars proposed the PLUS model, which can improve the mining of transformation rules and the lack of landscape dynamic simulation and obtain higher simulation accuracy and more realistic landscape pattern indicators.…”

Assessment of Habitat Risks Caused by Human Activities and Integrated Approach to Marine Spatial Planning: The Case of Sriracha District—Sichang Island

“…We apply the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model developed by Sharp et al (2016) to assess the ecological impact of land use and marine and coastal changes. This service allows for the quantification of various ecosystem services such as carbon sequestration, habitat quality, and habitat risk assessment [88]. We used the InVEST model to analyze the effects of land use and marine/coastal activities on ecosystem services in the study area.…”