Estimation of potential ecological carrying capacity in China

Abstract

It is urgent to explore the potential ecological carrying capacity (PECC) of regions where the study of ecological carrying capacity (ECC) is difficult to meet the real-world requirements of building an ecological civilization. In this study, classification and regression tree models were applied for estimating potential normalized difference vegetation index (PNDVI) based on climate variables and training data of actual NDVI. Then, potential net primary productivity (PNPP) was simulated by using Carnegie-Ames-Stanford Approach (CASA) model and PNDVI. On this basis, PECC of 31 provinces in China was estimated using the improved ecological footprint model and compared results with actual condition in 2015. The results showed the following: per capita PECC presented immense spatial differences, with high values in the northwest and low values in the southeast. The total PECCs of eight provinces were far greater than their actual total ECCs in 2015. Human activities in five provinces had the greatest negative impact on the ecological environment and the greatest pressure on ecological restoration. This study provided a new way to estimate the spatial distribution of potential ecological carrying capacity and found that spatial simulations of PNDVI, PNPP, and PECC can better quantify the difference between actual and potential ecological conditions under external pressures and can provide a trustworthy scientific basis for formulating differentiated ecological restoration strategies.