長江流域における生態系サービス価値と土地利用炭素排出のデュアルスケール時空間相関分析

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Useful for spatial analysis methods (bivariate spatial autocorrelation) applied to carbon and ecosystem service interactions.

🏢実務担当者:Land-use planners and regional development agencies can apply the approach to balance ecological conservation and emission reduction.

🏛政策担当者:Highlights the need for spatial targeting in carbon neutrality policies to avoid conflicts between emission hotspots and ecological service areas.

生態系サービス価値（ESV）と土地利用炭素排出量との時空間的相関は、地域の生態保護と社会経済発展の調整、および「ダブルカーボン」目標の実施促進にとって極めて重要である。長江流域をケーススタディ地域とし、2002年から2022年までのマルチソースデータに基づき、本研究は等価因子法、炭素排出係数法、二変量空間自己相関分析を採用する。グリッド（20 km）と県レベルの両方のスケールから、長江流域におけるESVと土地利用炭素排出量の時空間的進化特性と空間的相関パターンを体系的に分析する。結果は以下のことを示す：（1）研究期間中、長江流域のESVはわずかな増加を伴い安定を維持し、「西部で高く東部で低く、山岳地域で高く平野で低い」という空間分布パターンを示した。林地がESVの主要な貢献者であり、その貢献率は65.17%から68.22%に増加した一方、建設用地の負の影響は継続的に強まった。（2）土地利用炭素排出量の総量は2億6100万トンから7億3800万トンに増加し、建設用地が主要な炭素源、林地が最大の炭素吸収源であった。高炭素排出地域は下流の長江デルタ、中流の都市群、成都・重慶地域に集中し、高炭素吸収地域は上流の山岳地域と中流の森林地域に位置し、「東部に炭素源、西部に炭素吸収源」という顕著なパターンを示した。（3）二変量空間自己相関分析は、ESVと土地利用炭素排出量の間に有意な負の相関があることを明らかにし、負の相関の程度は研究期間中継続的に強化された。県スケールでの負の相関はグリッドスケールよりも有意に強かった。低高集中地域は上流の生態機能区に安定して分布し、高低集中地域は下流の都市群と農業核心地域に集中しており、生態サービス供給地域と炭素排出ホットスポットの間の高い空間的分離を反映している。

AI 翻訳（deepseek-v4-flash）。 正確を期す場合は下の原文を参照してください。

The spatiotemporal correlation between ecosystem service value (ESV) and land use carbon emissions is of great significance for coordinating regional ecological protection with socio-economic development and promoting the implementation of the "dual carbon" goals. Taking the Yangtze River Basin as the case study area, based on multi-source data from 2002 to 2022, this study employs the equivalent factor method, carbon emission coefficient method, and bivariate spatial autocorrelation analysis. From both grid (20 km) and county-level scales, we systematically analyze the spatiotemporal evolution characteristics and spatial correlation patterns of ESV and land use carbon emissions in the Yangtze River Basin. The results show that: (1) During the study period, the ESV of the Yangtze River Basin remained stable with a slight increase, exhibiting a spatial distribution pattern of "high in the west and low in the east, high in mountainous areas and low in plains"; forestland was the primary contributor to ESV, with its contribution rate increasing from 65.17% to 68.22%, while the negative impact of construction land continued to intensify. (2) The total land use carbon emissions increased from 261 million tons to 738 million tons, with construction land as the dominant carbon source and forestland as the largest carbon sink; high carbon emission areas were concentrated in the Yangtze River Delta in the lower reaches, urban agglomerations in the middle reaches, and the Chengdu-Chongqing region, while high carbon sink areas were located in the upstream mountainous regions and mid-reach forest areas, showing a significant pattern of "carbon sources in the east and carbon sinks in the west". (3) The bivariate spatial autocorrelation analysis reveals a significant negative correlation between ESV and land use carbon emissions, and the degree of negative correlation continuously strengthened during the study period; the negative correlation at the county scale was significantly stronger than that at the grid scale; the Low-High concentration areas were stably distributed in the upstream ecological functional areas, while the High-Low concentration areas were concentrated in the downstream urban agglomerations and agricultural core areas, reflecting the high spatial separation between ecological service supply areas and carbon emission hotspots.

• semanticscholar https://doi.org/10.62381/i265302first seen 2026-07-24 06:56:38 · last seen 2026-09-22 05:23:23