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Journal of the Australian Rangeland Society
RESEARCH ARTICLE

Monitoring and analysing grassland ecosystem service values in response to grassland area changes – an example from northwest China

Asiya Manlike B , Rukeya Sawut A C , Fengling Zheng B , Xuesen Li B and Rena Abudukelimu B
+ Author Affiliations
- Author Affiliations

A Navigation College, Dalian Maritime University, Dalian 116026, China.

B Xinjiang Academy of Animal Science, Grassland Research Institute of Xinjiang Animal Science Academy, Urumqi 830011, China.

C Environmental Information Institute, Dalian Maritime University, Dalian 116026, China.

D Corresponding author. Email: rukeyars@163.com

The Rangeland Journal 42(3) 179-194 https://doi.org/10.1071/RJ20014
Submitted: 3 March 2020  Accepted: 30 September 2020   Published: 4 November 2020

Abstract

Using remote sensing technology, this study evaluates changes in mountain grassland ecosystem service values (ESVs) and the factors driving them. Degraded grasslands in Urumqi city, northwest China, reached 1.22×105 ha in 2000. However, the grassland degradation rate decreased by 387 ha annually from 2000 to 2015. Total grassland ESVs decreased unpredictably with an annual reduction of USD$1.64×107. Ecological losses were mainly caused by degradation of mountain desert grassland, mountain desert steppe-type rangeland, and mountain meadow and mountain steppe-type rangeland. Among individual ESVs, grasslands contributed more to regulating and supporting services, while grassland provisioning and cultural services were relatively low, comprising 0. 7 and 0.5% of the total ESV respectively. The mean Moran’s I value was 0.869 for grassland ESVs (from 1994 to 2015), and exhibited high spatial autocorrelation. A driving factor analysis indicated that grassland degradation is continuing as a consequence of meteorological factors and overgrazing. Controlling grazing intensity has a positive impact on growth of grassland ESVs.

Keywords: driving factors, ecosystem services, ecosystem service values, ESV, grassland degradation, grid cell analysis, overgrazing, remote sensing, special autocorrelation.


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