Spatial-temporal variation characteristics of ecosystem service bundles in the Wei river basin based on the SOFM model

This research focuses on the Weihe River Basin (WRB) as the study area and quantified five key ESs (Habitat Quality-HQ, Water Yield-WY, Carbon Sequestration-CA, Soil Conservation-SD, Food Provision -FP) from 2000 to 2020 using multisource remote sensing and the InVEST model. Spearman correlation and Geographically Weighted Regression (GWR) analyzed ES trade-offs/synergies, while a Self-Organizing Feature Map (SOFM) neural network identified spatial bundles. The results are presented as follows: (1) The ESs in the WRB exhibited significant spatiotemporal heterogeneity. Between 2000 and 2020, the total amounts of HQ, WY, SD, and FP increased by 5.34 %, 45.03 %, 9.20 %, and 32.08 %, respectively, while CA decreased by 0.38 %, primarily due to the decline in vegetation carbon sequestration resulting from land use changes. (2) HQ and CA exhibited significant synergistic relationships at both basin and spatial scales ( P < 0.01), with other pairs showing pronounced spatial heterogeneity. (3) Four ecosystem service bundles were identified via the SOFM model: Ecological protection bundle (A), dominated by WY, was distributed in forest ecosystems such as the Qinling Mountains, Liupan Mountains, and Ziwuling Forest, accounting for 27.04 % of the total area. The food supply bundle (B), which is located primarily in the agricultural region of the Loess Plateau, covered the largest area (82,564.74 km 2 , 61.24 %). Ecological fragile bundle (C); and Urban Development bundle (D) (smallest at 829.58 km 2 , Guanzhong Plain), defined by trade-offs among HQ, CA, and SD. These findings provide a foundation for optimizing regional ecological zoning and promoting sustainable development. • Vital for optimizing regional ecological zoning and advancing green sustainable development. • Using Spearman and GWR for trade-off and synergy analysis. • Using SOFM and RDA to characterize ecosystem service bundles. • Identify 4 ecosystem service bundles among 5 ecosystem services in the WRB.

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Publication Details

Journal
Environmental and Sustainability Indicators
Published
2025-12-06
DOI
https://doi.org/10.1016/j.indic.2025.101080
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
0.00
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article

Spatial-temporal variation characteristics of ecosystem service bundles in the Wei river basin based on the SOFM model

Yajuan Gao, Dongmei Zhou, Jiankun Chen, Jun Zhang et al.
Environmental and Sustainability Indicators
Land Use and Ecosystem Services
article

Spatial-temporal variation characteristics of ecosystem service bundles in the Wei river basin based on the SOFM model

Yajuan Gao, Dongmei Zhou, Jiankun Chen, Jun Zhang, Jing Jiang
article en

Abstract

This research focuses on the Weihe River Basin (WRB) as the study area and quantified five key ESs (Habitat Quality-HQ, Water Yield-WY, Carbon Sequestration-CA, Soil Conservation-SD, Food Provision -FP) from 2000 to 2020 using multisource remote sensing and the InVEST model. Spearman correlation and Geographically Weighted Regression (GWR) analyzed ES trade-offs/synergies, while a Self-Organizing Feature Map (SOFM) neural network identified spatial bundles. The results are presented as follows: (1) The ESs in the WRB exhibited significant spatiotemporal heterogeneity. Between 2000 and 2020, the total amounts of HQ, WY, SD, and FP increased by 5.34 %, 45.03 %, 9.20 %, and 32.08 %, respectively, while CA decreased by 0.38 %, primarily due to the decline in vegetation carbon sequestration resulting from land use changes. (2) HQ and CA exhibited significant synergistic relationships at both basin and spatial scales ( P < 0.01), with other pairs showing pronounced spatial heterogeneity. (3) Four ecosystem service bundles were identified via the SOFM model: Ecological protection bundle (A), dominated by WY, was distributed in forest ecosystems such as the Qinling Mountains, Liupan Mountains, and Ziwuling Forest, accounting for 27.04 % of the total area. The food supply bundle (B), which is located primarily in the agricultural region of the Loess Plateau, covered the largest area (82,564.74 km 2 , 61.24 %). Ecological fragile bundle (C); and Urban Development bundle (D) (smallest at 829.58 km 2 , Guanzhong Plain), defined by trade-offs among HQ, CA, and SD. These findings provide a foundation for optimizing regional ecological zoning and promoting sustainable development. • Vital for optimizing regional ecological zoning and advancing green sustainable development. • Using Spearman and GWR for trade-off and synergy analysis. • Using SOFM and RDA to characterize ecosystem service bundles. • Identify 4 ecosystem service bundles among 5 ecosystem services in the WRB.

Environmental and Sustainability IndicatorsVol. 29
Gansu Agricultural University (CN)
Openalex Percentile: Top 64%
Land Use and Ecosystem Services
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