The Interrelationships and Driving Factors of Ecosystem Service Functions in the Tianshan Mountains

Ecosystems offer natural resources and habitats for humans, serving as the foundation for human social development. Taking the Tianshan Mountains as the study area, this study investigated the changing trends, hot spots, and driving factors of water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ), in the Tianshan region, from 1990 to 2020. To determine the trade-offs and synergies between the ESs, we employed the Spearman correlation coefficient, geographically weighted regression, the self-organizing map (SOM), and other methods. Five main results were obtained. (1) There were similar spatial distribution patterns for WY, HQ, CS, and SC, with high-value areas mainly concentrated in grassland zones, forest zones, river valleys, and the intermountain basins of the mountain range, while regions with low value were clustered in desert zones and snow/ice zones. (2) According to the hotspot analysis, areas with relatively strong ES provisioning for WY, HQ, CS, and SC, were primarily concentrated in the BoroHoro Ula Mountains and Yilianhabierga Mountains. In contrast, areas with relatively weak ES provisioning were mainly located in the Turpan Basin. (3) Precipitation was the primary explanatory factor for WY. Soil type, potential evapotranspiration (PET), and the normalized difference vegetation index (NDVI) were the primary explanatory factors for HQ. Soil type and NDVI were the primary explanatory factors for CS. PET was the primary explanatory factor for SC. (4) There were synergistic relationships between the WY, HQ, CS, and SC, with the strongest synergies found between CS–HQ, WY–HQ, and WY–SC. (5) Six ES bundles were identified through the SOM method, with their composition varying at different spatial scales, indicating the need for different ES management priorities in different regions. Our analysis of ESs, from various perspectives, offers insights to aid sustainable ecosystem management and conservation efforts in the Tianshan region and other major economic areas worldwide.

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Publication Details

Journal
Forests
Published
2024-09-23
DOI
https://doi.org/10.3390/f15091678
Citations
3
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.85
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article

The Interrelationships and Driving Factors of Ecosystem Service Functions in the Tianshan Mountains

Xiaohuang Liu, Tao Lin, Yukun Zhang, Zhe Hao et al.
3 citations
Forests
Land Use and Ecosystem Services
0.85
article

The Interrelationships and Driving Factors of Ecosystem Service Functions in the Tianshan Mountains

Xiaohuang Liu, Tao Lin, Yukun Zhang, Zhe Hao, Yu Zheng, Ran Wang, Wudi Chen
article en
3 citations

Abstract

Ecosystems offer natural resources and habitats for humans, serving as the foundation for human social development. Taking the Tianshan Mountains as the study area, this study investigated the changing trends, hot spots, and driving factors of water yield (WY), soil conservation (SC), carbon storage (CS), and habitat quality (HQ), in the Tianshan region, from 1990 to 2020. To determine the trade-offs and synergies between the ESs, we employed the Spearman correlation coefficient, geographically weighted regression, the self-organizing map (SOM), and other methods. Five main results were obtained. (1) There were similar spatial distribution patterns for WY, HQ, CS, and SC, with high-value areas mainly concentrated in grassland zones, forest zones, river valleys, and the intermountain basins of the mountain range, while regions with low value were clustered in desert zones and snow/ice zones. (2) According to the hotspot analysis, areas with relatively strong ES provisioning for WY, HQ, CS, and SC, were primarily concentrated in the BoroHoro Ula Mountains and Yilianhabierga Mountains. In contrast, areas with relatively weak ES provisioning were mainly located in the Turpan Basin. (3) Precipitation was the primary explanatory factor for WY. Soil type, potential evapotranspiration (PET), and the normalized difference vegetation index (NDVI) were the primary explanatory factors for HQ. Soil type and NDVI were the primary explanatory factors for CS. PET was the primary explanatory factor for SC. (4) There were synergistic relationships between the WY, HQ, CS, and SC, with the strongest synergies found between CS–HQ, WY–HQ, and WY–SC. (5) Six ES bundles were identified through the SOM method, with their composition varying at different spatial scales, indicating the need for different ES management priorities in different regions. Our analysis of ESs, from various perspectives, offers insights to aid sustainable ecosystem management and conservation efforts in the Tianshan region and other major economic areas worldwide.

ForestsVol. 15(9)
China Geological Survey (CN), Beijing Municipal Ecological and Environmental Monitoring Center (CN), Land Consolidation and Rehabilitation Center (CN)
Life in Land
Openalex Percentile: Top 28%
Land Use and Ecosystem Services
0.85
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