张紫怡,曹妍,张立亭,等. 赣州市生境质量和景观格局间时空非平稳性关联[J]. 农业工程学报,2024,40(6):346-355. DOI: 10.11975/j.issn.1002-6819.202307003
    引用本文: 张紫怡,曹妍,张立亭,等. 赣州市生境质量和景观格局间时空非平稳性关联[J]. 农业工程学报,2024,40(6):346-355. DOI: 10.11975/j.issn.1002-6819.202307003
    ZHANG Ziyi, CAO Yan, ZHANG Liting, et al. Spatial and temporal non-stationary relationship between habitat quality and landscape pattern in Ganzhou City of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(6): 346-355. DOI: 10.11975/j.issn.1002-6819.202307003
    Citation: ZHANG Ziyi, CAO Yan, ZHANG Liting, et al. Spatial and temporal non-stationary relationship between habitat quality and landscape pattern in Ganzhou City of China[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2024, 40(6): 346-355. DOI: 10.11975/j.issn.1002-6819.202307003

    赣州市生境质量和景观格局间时空非平稳性关联

    Spatial and temporal non-stationary relationship between habitat quality and landscape pattern in Ganzhou City of China

    • 摘要: 在城市化的高速推进造成景观破碎、威胁生境质量的大背景下,赣州市较好地实现了经济发展与生态保护并行。为探明赣州市景观格局对生境质量的驱动机理,回答“怎样的景观格局有利于生态保护”这一问题,该研究以赣州市为研究区,对其2000—2020年的生境质量进行空间测度并分析其时空跃迁动态特征;分析其景观格局演变特征,并基于时空地理加权回归模型(geographically and temporally weighted regression,GTWR)探明二者关联机制。结果表明:赣州市生境质量呈现“四周高,中部低”的空间分布特征,2000—2020年整体均处于较高水平,呈现积极协同进步的空间动态特征;赣州市景观格局维持在较稳定状态,人造地表扩张优先占用非林非水地类,且与水域增量存在空间伴随;生境质量与景观格局间关联呈现显著的时空非平稳性特征;散布与并列指数(interspersion juxtaposition index ,IJI)显示人造地表、林地和水域交错分布可能降低人造地表对生境质量的负向影响。该研究以提升生境质量为目标,探明了10 km×10 km格网尺度下赣州市各景观格局指数的最优驱动阈值区间,人造地表总面积占比全域应控制在0.68%之内,最大斑块占林地总面积比不宜低于9.8%,且林地总面积占比全域应控制在7.8%之内,斑块IJI指数应大于20%,草地和水域斑块IJI指数应控制在60%内以及超出13%。研究结果可为对国土空间规划和其他区域的生态管理决策提供参考。

       

      Abstract: Landscape fragmentation has threatened the habitat quality in the context of rapid urbanization. A tradeoff between economic development and ecological protection has been achieved in Ganzhou City, Jiangxi Province, China. This study aims to clarify the driving mechanisms of landscape patterns on habitat quality. Land use data was also collected from 2000 to 2020. The optimal landscape patterns were then proposed for ecological protection and decision-making. An InVEST model was applied to measure the spatiotemporal distribution of the quality of the settlement environment using a transition matrix. Furthermore, the global and local spatial autocorrelation of habitat quality was calculated using the GeoDa software. Additionally, the evolution of habitat quality was constructed to balance the LISA time paths and spatiotemporal transition dynamics using scatter plots. The spatiotemporal differentiation of landscape patterns was explored with a 10 km×10 km grid as the measurement unit. A systematic evaluation was implemented to determine the impact of various indices on the habitat quality at the class of land landscape on both time and space using the geographically and temporally weighted regression (GTWR) model. Finally, the optimal threshold intervals were established to regulate regional landscape patterns. Some insights were offered into the interplay between landscape configurations and habitat quality at different spatial scales over time. The results were as follows. The spatial distribution of habitat quality was characterized by 'high in the periphery, low in the center' at an overall high level from 2000 to 2020, indicating positive and synergistic spatial dynamics. There were remarkably stable landscape patterns with the human-driven land expansion to selectively encroach on non-forested and non-aquatic areas. A better agreement was also found on the spatial increment in water bodies, indicating a complex and variable interaction between anthropogenic and natural landscape elements. There was a significantly spatiotemporal non-stationarity in the relationship between habitat quality and landscape patterns. The Index of Interspersion and Juxtaposition (IJI) revealed that the mixed distribution of artificial land, forests, and water bodies was utilized to mitigate the negative impacts of urban expansion on habitat quality. Optimal threshold intervals were identified for the various indices of landscape patterns for better habitat quality in the study area. The landscape configurations had the promising potential to support ecological conservation. The relationship between landscape patterns and habitat quality greatly contributed to sustainable development and integrated management under environmental challenges. The key influencing factors on the habitat quality were determined from the perspective of landscape pattern reconstruction. The findings can provide a strong reference to maintaining a stable ecosystem and sustainable development.

       

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