Evaluation of driving effects of carbon storage change in the source of the Yellow River: A perspective with CMIP6 future development scenarios

IF 5.8 2区环境科学与生态学 Q1 ECOLOGY

Ecological Informatics Pub Date : 2024-08-22 DOI:10.1016/j.ecoinf.2024.102790

Ming Ling , Zihao Feng , Zizhen Chen , Yanping Lan , Xinhong Li , Haotian You , Xiaowen Han , Jianjun Chen

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引用次数: 0

Abstract

Understanding how future climate scenarios impact land use/cover (LUC) and carbon storage (CS) is crucial for achieving carbon neutrality. However, research often overlooks the spatiotemporal impacts of future climate and socioeconomic changes on CS. This study integrates system dynamic (SD), patch-generating land use simulation (PLUS), the integrated valuation of ecosystem services and tradeoffs (InVEST) model, and the geographical detector to assess the LUC and CS evolution in the source of the Yellow River (SYR) from 2020 to 2060. Utilizing carbon density and LUC data, we explored the influence of natural and socioeconomic factors on CS under five shared socioeconomic pathways and representative concentration pathways (SSP-RCPs) scenarios. Our findings demonstrate that: (1) Ecological land, including woodland, grassland, and wetland, expanded more under SSP126 compared to SSP245, with SSP345, SSP460, and SSP585 showing a trend of degradation tied to deeper economic contribution. (2) By 2060, CS in terrestrial ecosystem under SSP126, SSP245, SSP345, SSP460, and SSP585 were 702.33 × 10⁶ t, 700.33 × 10⁶ t, 697.22 × 10⁶ t, 696.03 × 10⁶ t, and 691.21 × 10⁶ t, respectively. This represents changes of 3.69 × 10⁶ t, 1.69 × 10⁶ t, −1.49 × 10⁶ t, −2.68 × 10⁶ t, and −7.43 × 10⁶ t compared to 2020. (3) Soil type predominantly influenced the spatial differentiation of CS, with significant interactions with precipitation. This research provides new insights into land redistribution, economic strategies, and achieving carbon neutrality.

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黄河源头碳储量变化的驱动效应评估：以 CMIP6 未来发展情景为视角

了解未来气候情景如何影响土地利用/覆盖（LUC）和碳储存（CS）对于实现碳中和至关重要。然而，研究往往忽略了未来气候和社会经济变化对碳储存的时空影响。本研究整合了系统动力学（SD）、斑块生成土地利用模拟（PLUS）、生态系统服务和权衡综合评价（InVEST）模型以及地理探测器，以评估 2020 至 2060 年黄河源头（SYR）的土地利用变化（LUC）和碳储存（CS）演变。利用碳密度和LUC数据，我们探讨了五种共享社会经济路径和代表性浓度路径（SSP-RCPs）情景下自然和社会经济因素对CS的影响。我们的研究结果表明(1) 与 SSP245 相比，SSP126 下的生态用地（包括林地、草地和湿地）扩大得更多，而 SSP345、SSP460 和 SSP585 则显示出与更深的经济贡献相关的退化趋势。(2) 到 2060 年，SSP126、SSP245、SSP345、SSP460 和 SSP585 条件下陆地生态系统的 CS 分别为 702.33 × 106 t、700.33 × 106 t、697.22 × 106 t、696.03 × 106 t 和 691.21 × 106 t。与 2020 年相比，分别变化了 3.69×106 t、1.69×106 t、-1.49×106 t、-2.68×106 t 和-7.43×106 t。(3）土壤类型主要影响 CS 的空间分异，并与降水有显著的相互作用。这项研究为土地再分配、经济战略和实现碳中和提供了新的视角。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Ecological Informatics 环境科学-生态学

CiteScore

8.30

自引率

11.80%

发文量

346

审稿时长

46 days

期刊介绍： The journal Ecological Informatics is devoted to the publication of high quality, peer-reviewed articles on all aspects of computational ecology, data science and biogeography. The scope of the journal takes into account the data-intensive nature of ecology, the growing capacity of information technology to access, harness and leverage complex data as well as the critical need for informing sustainable management in view of global environmental and climate change. The nature of the journal is interdisciplinary at the crossover between ecology and informatics. It focuses on novel concepts and techniques for image- and genome-based monitoring and interpretation, sensor- and multimedia-based data acquisition, internet-based data archiving and sharing, data assimilation, modelling and prediction of ecological data.