Thriving arid oasis urban agglomerations: Optimizing ecosystem services pattern under future climate change scenarios...

Area of Science:

• Environmental Science
• Ecology
• Climate Change Research

Background:

• Global climate change and human activities significantly threaten ecosystem services (ESs), especially in arid urban areas.
• Urban agglomerations in arid regions face unique challenges in balancing development and ecological sustainability.

Purpose of the Study:

• To develop and apply an integrated framework for predicting land use change and optimizing ESs spatial patterns under future climate scenarios.
• To assess the impacts of climate change and human activities on ESs in the oasis urban agglomeration on the northern slope of the Tianshan Mountains (UANSTM).

Main Methods:

• Integration of dynamic Bayesian network (DBN), system dynamics (SD), Patch-generating Land Use Simulation (PLUS), and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models.
• Utilized SSP-RCP scenarios from CMIP6 for future land use and ESs predictions.
• Validated SD and PLUS models for land use forecasting and DBN for ESs relationship simulation.

Main Results:

• SD and PLUS models accurately forecasted land use distribution (SD relative error < 2.32%, PLUS Kappa coefficient = 0.89).
• Future land use in UANSTM is characterized by expansion of cultivated and construction land, showing spatial heterogeneity.
• DBN model effectively simulated ESs relationships with low classification error rates for Net Primary Productivity (NPP), Habitat Quality (HQ), Water Yield (WY), and Soil Retention (SR).

Conclusions:

• The integrated framework provides accurate predictions for land use change and ESs optimization in arid urban areas.
• Natural factors predominantly influence most ESs in UANSTM, with socio-economic development having a lesser role.
• Findings offer crucial insights for ecological protection and land use planning in arid urban agglomerations globally.