Spatiotemporal Characteristics of the Coupled Coordination Degree of Ecosystem Services Supply and Demand in Chinese National Nature Reserves

Abstract

Nature reserves (NRs) are the main components of protected areas and geographic spaces, with unique natural and cultural resources. The establishment of nature reserves has not only strengthened the protection of specific species but has also played a vital role in the protection of ecosystem services (ESs). However, few studies have been conducted to systematically assess the effectiveness of nature reserves from the perspective of ecosystem services supply and demand (S&D) or make comparisons between the conservation effects of different types of nature reserves. This study analyzed the spatiotemporal characteristics of ecosystem service supply and demand in 412 Chinese national nature reserves. The results showed that both supply and demand for ecosystem services per unit area show a spatial pattern of increasing from west to east. The supply–demand matching pattern is dominated by high supply–high demand (H–H) and low supply–high demand (L–H) in the central and eastern regions, and high supply–low demand (H–L) and low supply–low demand (L–L) in the northeast, northwest, and southwest regions. The coupling coordination degree (CCD) of ecosystem services supply and demand increased from 0.53 in 2000 to 0.57 in 2020, and the number of NRs reaching the coordinated level (>0.5) increased by 15 from 2000 to 2020, representing 3.64% of the total number of protected areas. Steppe meadows, ocean coasts, forest ecosystems, wildlife, and wild plant types of nature reserves all improved more obviously. This provides a scientific basis for strengthening the ecological and environmental supervision of nature reserves, and the research methods and ideas can provide references for similar research.

Spatial–Temporal Pattern of Coordination between the Supply and Demand for Ecosystem Services in the Lhasa River Basin

“…Existing research has utilized various research methods and models to analyze the relationships between ES supply and demand. For example, methods such as nonlinear curve-fitting analysis [6], Kernel density estimation [7], and spatial correlation analysis [8] have been used to explore the matching coordination between ES supply and demand. In terms of research content, existing studies have analyzed the coordination between the ES supply and demand of various ES types, such as focusing on soil retention services [9,10], water conservation services [11,12], and cultural services [13].…”