Dynamic Variation of Ecosystem Services Value under Land Use/Cover Change in the Black Soil Region of Northeastern China

Int J Environ Res Public Health. 2022 Jun 20;19(12):7533. doi: 10.3390/ijerph19127533.

Abstract

A better understanding of the dynamic variation in the ecosystem service value (ESV) under land use/cover change (LUCC) is conductive to improving ecosystem services and environmental protection. The present study took Landsat TM/ETM remote sensing images and socio-economic statistic data as data sources and extracted land-use data using RS and GIS technology at 5-year intervals from 1990 to 2020. Then, we interpreted the spatio-temporal characteristics of LUCC and analyzed ESV changes using the value equivalence method in the black soil region of northeastern China (BSRNC). The main results showed that land use changed significantly during the study period. Cultivated land continued to expand, especially paddy areas, which increased by 1.72 × 106 ha, with a relative change of 60.9% over 30 years. However, grassland decreased by 2.47 × 106 ha, with a relative change of -60.6% over 30 years. The ESV showed a declining trend, which decreased by CNY 607.96 million during 1990-2020. The decline in forest and grassland caused a significant decline in the ESV. Furthermore, the ESV sensitivity coefficients were less than one for all of the different categories of ecosystem services. LUCC has a considerable impact on ESV in the BSRNC, resulting in ecosystem function degradation. As a result, future policies must emphasize the relationship between food security and environmental protection in situations of significant land-use change.

Keywords: black soil region; dynamic variation; ecosystem services value; land use/cover change; northeastern China.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Conservation of Natural Resources
  • Ecosystem*
  • Forests
  • Soil*

Substances

  • Soil

Grants and funding

This research was funded by National Natural Science Foundation of China, grant numbers 41901208, National Natural Science Foundation of China, grant number 42101217, China Postdoctoral Science Foundation, grant number 2021M700738.