The Simulation of the Wetland Biodiversity Pattern Under Different Land Use Policies on the Sanjiang Plain

Involving wetland protection policies in the simulation of the wetland biodiversity pattern has the potential to improve the accuracy of policy-making. In this research, by combining the Cellular Automata Markov Model (CA-Markov) for land use change simulation and a wetland Biodiversity Estimation Model Based on Hydrological Pattern and Connectivity (BEHPC), we put forward a comprehensive framework that integrates policy stage division, the identification of stage characteristics, and biodiversity prediction. This framework divided the wetland conservation policies implemented in the study area into three stages: promoting (1995−2005), strengthening (2005–2010), and stabilizing (2010–2020). CA-Markov verification confirmed the stages’ consistency with actual policy implementation, indicating its usability. Using the land use data of different policy stages as input for the CA-Markov model, we then predicted the wetland biodiversity pattern in 2030 under different scenarios. The results showed that the land use and wetland protection policies implemented during 2010–2020 were most beneficial for enhancing wetland biodiversity in the study area, with an expected increase of about 8% if continued. This study offers technical and scheme references for the future evaluation of wetland-related policies at the regional scale. It also provides guidance for optimizing the spatial structure and providing numerical goals for land use and wetland protection.