Impacts of climatic factors and landscape patterns on megacity carbon sink in the mountain–basin transition region: A study based on the XGBoost–SHAP model in Chengdu, China

Carbon sources and sinks are crucial to climate regulation. Megacities, as major emitters, encounter increasing pressure from rapid land-use changes and ecological degradation. These challenges are prominent in mountain–basin transition regions owing to fragmented terrain, ecological sensitivity, and accelerated urbanization. However, the combined effects of climate and landscape patterns on carbon sinks in these regions remain poorly understood. This study investigated the spatiotemporal dynamics (2000−2020) and combined effects of climate and landscape patterns on carbon sinks across production–living–ecological spaces in a typical transition-region megacity. Net ecosystem productivity (NEP) was used as a carbon sink indicator. An interpretable machine learning model, eXtreme Gradient Boosting with Shapley Additive Explanations, was applied to quantify the independent and interactive effects of four key climatic factors (temperature, precipitation, potential evapotranspiration, and sunshine duration) and landscape patterns. Climatic factors exerted stronger effects on NEP than on landscape patterns, with moderate temperatures, sufficient rainfall, and sunshine enhancing sequestration. The key landscape pattern indices were the percentage of landscape, landscape shape index, edge density, and splitting index, with living space being the most sensitive. Climate–landscape interactions were context-dependent: fragmentation and edge density reduced carbon sinks but were potentially mitigated under optimal climate conditions. Improved landscape patterns further enhanced NEP, highlighting the importance of expanding and connecting ecological spaces, using a “large-scattered, small-clustered” layout in production spaces, and integrating green infrastructure in living spaces. These findings inform landscape planning and management to optimize land-use structures and strengthen carbon sinks in megacities under climate change.

Authors

Publication Details

Journal
Ecological Informatics
Published
2025-11-20
DOI
https://doi.org/10.1016/j.ecoinf.2025.103528
Citations
3
Primary Topic
Land Use and Ecosystem Services
Type
article
Field-Weighted Citation Impact
3.32
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Impacts of climatic factors and landscape patterns on megacity carbon sink in the mountain–basin transition region: A study based on the XGBoost–SHAP model in Chengdu, China

Qianna Wang, Xiangyun Shi, Kaixi Liu, Xiaohuan Jiang et al.
3 citations
Ecological Informatics
Land Use and Ecosystem Services
3.32
article

Impacts of climatic factors and landscape patterns on megacity carbon sink in the mountain–basin transition region: A study based on the XGBoost–SHAP model in Chengdu, China

Qianna Wang, Xiangyun Shi, Kaixi Liu, Xiaohuan Jiang, Rui He
article en
3 citations

Abstract

Carbon sources and sinks are crucial to climate regulation. Megacities, as major emitters, encounter increasing pressure from rapid land-use changes and ecological degradation. These challenges are prominent in mountain–basin transition regions owing to fragmented terrain, ecological sensitivity, and accelerated urbanization. However, the combined effects of climate and landscape patterns on carbon sinks in these regions remain poorly understood. This study investigated the spatiotemporal dynamics (2000−2020) and combined effects of climate and landscape patterns on carbon sinks across production–living–ecological spaces in a typical transition-region megacity. Net ecosystem productivity (NEP) was used as a carbon sink indicator. An interpretable machine learning model, eXtreme Gradient Boosting with Shapley Additive Explanations, was applied to quantify the independent and interactive effects of four key climatic factors (temperature, precipitation, potential evapotranspiration, and sunshine duration) and landscape patterns. Climatic factors exerted stronger effects on NEP than on landscape patterns, with moderate temperatures, sufficient rainfall, and sunshine enhancing sequestration. The key landscape pattern indices were the percentage of landscape, landscape shape index, edge density, and splitting index, with living space being the most sensitive. Climate–landscape interactions were context-dependent: fragmentation and edge density reduced carbon sinks but were potentially mitigated under optimal climate conditions. Improved landscape patterns further enhanced NEP, highlighting the importance of expanding and connecting ecological spaces, using a “large-scattered, small-clustered” layout in production spaces, and integrating green infrastructure in living spaces. These findings inform landscape planning and management to optimize land-use structures and strengthen carbon sinks in megacities under climate change.

Ecological InformaticsVol. 92
Openalex Percentile: Top 7%
Land Use and Ecosystem Services
3.32
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.