黄河上游甘肃-青海毗连区栖息地质量的时空动态和多情景预测

Land Pub Date : 2024-07-15 DOI:10.3390/land13071060
Xuan Zhang, Huali Tong, Ling Zhao, Enwei Huang, Guofeng Zhu
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摘要

人类活动对土地利用和土地覆盖产生了深远的影响,这些变化直接影响着栖息地的质量和生态系统的功能。近年来,在黄河上游甘肃-青海毗连区,由于自然过程和人为干预的协同影响,生境质量发生了巨大变化。因此,评估土地利用变化对生境质量的影响对于促进区域可持续发展和提高生态系统服务价值至关重要。为应对这些挑战,我们设计了一种双管齐下的方法:土地利用模拟(FLUS)模型和生态系统服务与权衡综合评估(InVEST)模型,并充分利用遥感数据。这种综合方法为评估和模拟生境质量的时空变化建立了一个研究框架。研究结果表明:首先,从 1980 年到 2020 年,黄河上游甘肃-青海毗连区的生境质量指数从 0.8528 降至 0.8434。其次,我们预测栖息地质量会下降,但并非所有情景都会明显下降。EP(生态优先)情景下的生境质量值最高,其次是 CLP(耕地优先)情景,而 BAU(一切照旧)情景下的生境质量值在所有三种情景中都是最低的。最后,生态用地(包括林地和草地)始终占据着生境质量较高的区域。与此相反,建设用地则始终位于栖息地质量较低的区域。实施保护措施是一项重要战略,可有效限制建设用地的扩张,促进林地和草地覆盖面积的增加。这种方法有助于提高栖息地的整体质量。这些成果为明智地制定未来的土地使用政策和生态保护措施奠定了科学基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial and Temporal Dynamics and Multi-Scenario Forecasting of Habitat Quality in Gansu–Qinghai Contiguous Region of the Upper Yellow River
Human activities exert a profound influence on land use and land cover, and these changes directly influence habitat quality and ecosystem functioning. In the Gansu–Qinghai contiguous region of the upper Yellow River, habitat quality has undergone substantial transformations in recent years due to the synergistic impacts of natural processes and human intervention. Therefore, evaluating the effects of land use changes on habitat quality is crucial for advancing regional sustainable development and improving the worth of ecosystem services. In response to these challenges, we devised a two-pronged approach: a land use simulation (FLUS) model and an integrated valuation of ecosystem services and trade-offs (InVEST) model, leveraging remote sensing data. This integrated methodology establishes a research framework for the evaluation and simulation of spatial and temporal variations in habitat quality. The results of the study show that, firstly, from 1980 to 2020, the habitat quality index in the Gansu–Qinghai contiguous region of the upper Yellow River decreased from 0.8528 to 0.8434. Secondly, our predictions anticipate a decrease in habitat quality, although the decline is not pronounced across all scenarios. The highest habitat quality values were projected under the EP (Ecology Priority) scenario, followed by the CLP (Cultivated Land Priority) scenario, while the BAU (Business as Usual) scenario consistently yielded the lowest values in all three scenarios. Finally, the ecological land, including forest land and grassland, consistently occupied areas characterized by high habitat quality. In contrast, Construction land consistently appeared in regions associated with low habitat quality. The implementation of conservation measures emerges as a crucial strategy, effectively limiting the expansion of construction land and promoting the augmentation of forest land and grassland cover. This approach serves to enhance overall habitat quality. These outcomes furnish a scientific foundation for the judicious formulation of future land-use policies and ecological protection measures.
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