Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin, Northwest China

doi:10.1007/s40333-024-0103-2

Journal of Arid Land

2024, Vol. 16

Issue (7): 943-962 DOI: 10.1007/s40333-024-0103-2

Research article

Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin, Northwest China

ZUBAIDA Muyibul^*(

)

College of Tourism, Xinjiang University, Urumqi 830049, China

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Abstract

The Keriya River Basin is located in an extremely arid climate zone on the southern edge of the Tarim Basin of Northwest China, exhibiting typical mountain-oasis-desert distribution characteristics. In recent decades, climate change and human activities have exerted significant impacts on the service functions of watershed ecosystems. However, the trade-offs and synergies between ecosystem services (ESs) have not been thoroughly examined. This study aims to reveal the spatiotemporal changes in ESs within the Keriya River Basin from 1995 to 2020 as well as the trade-offs and synergies between ESs. Leveraging the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) and Revised Wind Erosion Equation (RWEQ) using land use/land cover (LULC), climate, vegetation, soil, and hydrological data, we quantified the spatiotemporal changes in the five principal ESs (carbon storage, water yield, food production, wind and sand prevention, and habitat quality) of the watershed from 1995 to 2020. Spearman correlation coefficients were used to analyze the trade-offs and synergies between ES pairs. The findings reveal that water yield, carbon storage, and habitat quality exhibited relatively high levels in the upstream, while food production and wind and sand prevention dominated the midstream and downstream, respectively. Furthermore, carbon storage, food production, wind and sand prevention, and habitat quality demonstrated an increase at the watershed scale while water yield exhibited a decline from 1995 to 2020. Specifically, carbon storage, wind and sand prevention, and habitat quality presented an upward trend in the upstream but downward trend in the midstream and downstream. Food production in the midstream showed a continuously increasing trend during the study period. Trade-off relationships were identified between water yield and wind and sand prevention, water yield and carbon storage, food production and water yield, and habitat quality and wind and sand prevention. Prominent temporal and spatial synergistic relationships were observed between different ESs, notably between carbon storage and habitat quality, carbon storage and food production, food production and wind and sand prevention, and food production and habitat quality. Water resources emerged as a decisive factor for the sustainable development of the basin, thus highlighting the intricate trade-offs and synergies between water yield and the other four services, particularly the relationship with food production, which warrants further attention. This research is of great significance for the protection and sustainable development of river basins in arid areas.

Key words： ecosystem services trade-offs synergies water yield, food production habitat quality wind and sand prevention Tarim Basin

Received: 30 January 2024 Published: 31 July 2024

Corresponding Authors: * ZUBAIDA Muyibul (E-mail: zubayda51@163.com)

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Cite this article:

ZUBAIDA Muyibul. Trade-offs and synergies between ecosystem services in Yutian County along the Keriya River Basin, Northwest China. Journal of Arid Land, 2024, 16(7): 943-962.

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http://jal.xjegi.com/10.1007/s40333-024-0103-2 OR http://jal.xjegi.com/Y2024/V16/I7/943

Fig. 1 Location of the Keriya River Basin. DEM, digital elevation model.

Table 1 Data source of parameters for the calculation of ecosystem services (ESs) in the Keriya River Basin

Table 2 Carbon density of different land use types in the Keriya River Basin

Table 3 Biophysical parameters of water yield service

Table 4 Habitat quality parameters of different land use types in the Keriya River Basin

Table 5 Values of ESs in the Keriya River Basin in 1995, 2000, 2005, 2010, 2015, and 2020

Fig. 2 Spatial distribution of carbon storage (CS) in the Keriya River Basin in 1995 (a), 2000 (b), 2005 (c), 2010 (d), 2015 (e), and 2020 (f)

Fig. 3 Spatial distribution of water yield (WY) in the Keriya River Basin in 1995 (a), 2000 (b), 2005 (c), 2010 (d), 2015 (e), and 2020 (f)

Fig. 4 Spatial distribution of food production (FP) in the Keriya River Basin in 1995 (a), 2000 (b), 2005 (c), 2010 (d), 2015 (e), and 2020 (f)

Fig. 5 Spatial distribution of wind and sand prevention (WSP) in the Keriya River Basin in 1995 (a), 2000 (b), 2005 (c), 2010 (d), 2015 (e), and 2020 (f)

Fig. 6 Spatial distribution of habitat quality (HQ) in the Keriya River Basin in 1995 (a), 2000 (b), 2005 (c), 2010 (d), 2015 (e), and 2020 (f)

Fig. 7 Spatial distribution of trade-offs and synergies between ES pairs in the Keriya River Basin in 1995 (a, b, c, d, e, k, l, m, n, and o) and 2020 (f, g, h, i, j, p, q, r, s, and t). Non-significant represents there is no correlation between ES pairs, high-high represents strong synergy relationship and low-low represents low synergy relationship between ES pairs, while high-low represents strong trade-off relationship and low-high represents low trade-off relationship between ES pairs.

Fig. 8 Correlation analysis of ESs in the Keriya River Basin in 1995 (a), 2000 (b), 2005 (c), 2010 (d), 2015 (e), and 2020 (f). ^*, P<0.050 level; ^**, P<0.010 level; ^***, P<0.001 level. Positive numbers represent synergy relationship between ES pair, while negative numbers represent trade-off relationship between ES pair. The size of circle represents the value of the correlation coefficient, i.e., the higher the correlation coefficient, the larger the circle.


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