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Article

Shifting from Trade-Offs to Synergies in Ecosystem Services Through Effective Ecosystem Management in Arid Areas

1
State Key Laboratory of Eco-Hydraulics in Northwest Arid Region of China, Xi’an University of Technology, Xi’an 710048, China
2
Engineering Research Center of Water Resources and Ecological Water Conservancy in Cold and Arid Area of Xinjiang (Academician Workstation), Urumqi 830052, China
3
State Key Laboratory of Hydraulic Engineering Intelligent Construction and Operation, Tianjin University, Tianjin 300350, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Remote Sens. 2024, 16(21), 4115; https://doi.org/10.3390/rs16214115
Submission received: 12 September 2024 / Revised: 28 October 2024 / Accepted: 29 October 2024 / Published: 4 November 2024
(This article belongs to the Section Remote Sensing for Geospatial Science)

Abstract

Human activities continuously alter the delivery of ecosystem services (ESs), which play a crucial role in human well-being. There is a pressing need for effective ecological management strategies that consider the spatial heterogeneity of ESs to support the transition from trade-offs to synergies. This study focuses on the Haba River Basin and examines characteristics of land-use change and the shift from trade-offs to synergies. The results indicate that from 1990 to 2000, the initial phase of land development, 10.65% of the land experienced change. Subsequently, during the intensive period of land development from 2000 to 2010, 30.29% of the land underwent significant transformation, with approximately 78% of grassland, sparse grassland, forested land, and desert converted into arable land. However, between 2010 and 2020, as the focus shifted towards the establishment of native vegetation. The intensity of land development decreased, and only a small percentage (3.65%) of the total area underwent changes. Based on an in-depth analysis of spatial heterogeneity from 1990 to 2020, it is believed there has been a shift from trade-offs to co-benefits between 2000–2010 and 2010–2020. The years 2010 and 2020 were pivotal time nodes for the transition from trade-offs to synergies and for reducing trade-offs, with NPP identified as a critical driving factor for comprehensive ES (CES) functions. By considering the trade-off–synergy relationship and hotspots of ecological service functions, combined with unified water resource management policies, comprehensive ecological management measures tailored to different regions are proposed. These measures have facilitated the implementation of robust ecological protection policies to shift ES development from trade-offs to synergies in arid areas, thereby enhancing overall ecosystem service functions in the Haba River Basin. The research findings offer crucial scientific support and guidance for ecosystem management in arid areas, particularly within Central Asia.
Keywords: ecosystem services; spatiotemporal pattern; arid area; trade-offs and synergies; Central Asia ecosystem services; spatiotemporal pattern; arid area; trade-offs and synergies; Central Asia

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MDPI and ACS Style

Xu, Y.; Song, X.; Deng, M.; Bai, T.; Tao, W. Shifting from Trade-Offs to Synergies in Ecosystem Services Through Effective Ecosystem Management in Arid Areas. Remote Sens. 2024, 16, 4115. https://doi.org/10.3390/rs16214115

AMA Style

Xu Y, Song X, Deng M, Bai T, Tao W. Shifting from Trade-Offs to Synergies in Ecosystem Services Through Effective Ecosystem Management in Arid Areas. Remote Sensing. 2024; 16(21):4115. https://doi.org/10.3390/rs16214115

Chicago/Turabian Style

Xu, Yan, Xiaoyun Song, Mingjiang Deng, Tao Bai, and Wanghai Tao. 2024. "Shifting from Trade-Offs to Synergies in Ecosystem Services Through Effective Ecosystem Management in Arid Areas" Remote Sensing 16, no. 21: 4115. https://doi.org/10.3390/rs16214115

APA Style

Xu, Y., Song, X., Deng, M., Bai, T., & Tao, W. (2024). Shifting from Trade-Offs to Synergies in Ecosystem Services Through Effective Ecosystem Management in Arid Areas. Remote Sensing, 16(21), 4115. https://doi.org/10.3390/rs16214115

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