Journal of Geographical Sciences ›› 2017, Vol. 27 ›› Issue (6): 681-696.doi: 10.1007/s11442-017-1400-x

• Orginal Article • Previous Articles     Next Articles

Mapping the hotspots and coldspots of ecosystem services in conservation priority setting

Yingjie LI1,*(), Liwei ZHANG1(), Junping YAN1, Pengtao WANG1, Ningke HU1, Wei CHENG2, Bojie FU2   

  1. 1. Department of Geography, Tourism and Environment College of Shaanxi Normal University, Xi'an 710119, China
    2. State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, CAS, Beijing 100085, China
  • Received:2016-03-15 Accepted:2016-07-29 Online:2017-06-10 Published:2017-06-10
  • Contact: Yingjie LI;
  • About author:

    Author: Li Yingjie (1990-), specialized in environmental change and ecosystem services. E-mail:

    *Corresponding author: Zhang Liwei (1985-), Assistant Professor, specialized in landscape ecology and ecosystem services. E-mail:

  • Supported by:
    National Natural Science Foundation of China, No.41601182;National Social Science Foundation of China, No.14AZD094;National Key Research and Development Plan of China, No.2016YFC0501601;China Postdoctoral Science Foundation, No.2016M592743;Fundamental Research Funds for the Central Universities, No.GK201603078;Key Project of the Ministry of Education of China, No.15JJD790022


Spatial-explicitly mapping of the hotspots and coldspots is a vital link in the priority setting for ecosystem services (ES) conservation. However, little research has identified and tested the compactness and efficiency of their ES hotspots and coldspots, which may weaken the effectiveness of ecological conservation. In this study, based on the RUSLE model and Getis-Ord Gi* statistics, we quantified the variation of annual soil conservation services (SC) and identified the statistically significant hotspots and coldspots in Shaanxi Province of China from 2000 to 2013. The results indicate that, 1) areas with high SC presented a significantly increasing trend as well, while areas with low SC only changed slightly; 2) SC hotspots and coldspots showed an obvious spatial differentiation—the hotspots were mainly spatially aggregated in southern Shaanxi, while the coldspots were mainly distributed in the Guanzhong Basin and Sand-windy Plateau; and 3) the identified hotspots had the highest capacity of providing SC, with 29.6% of the total area providing 59.7% of the total service. In contrast, the coldspots occupied 46.3% of the total area, but only provided 17.2% of the total SC. In addition to conserving single ES, the Getis-Ord Gi* statistics method can also help identify multi-functional priority areas for conserving multiple ES and biodiversity.

Key words: ecosystem services mapping, soil conservation, spatial clustering, Getis-Ord Gi* statistics, Shaanxi Province