Kim Mi-Young, Lee Sang-Woo
Graduate Program, Department of Environmental Science, Konkuk University, Gwangjin-Gu, Seoul 05029, Korea.
Department of Forestry and Landscape Architecture, Konkuk University, Gwangjin-Gu, Seoul 05029, Korea.
Int J Environ Res Public Health. 2021 May 13;18(10):5150. doi: 10.3390/ijerph18105150.
Multiple studies have been conducted to identify the complex and diverse relationships between stream ecosystems and land cover. However, these studies did not consider spatial dependency inherent from the systemic structure of streams. Therefore, the present study aimed to analyze the relationship between green/urban areas and topographical variables with biological indicators using regression tree analysis, which considered spatial autocorrelation at two different scales. The results of the principal components analysis suggested that the topographical variables exhibited the highest weights among all components, including biological indicators. Moran's I values verified spatial autocorrelation of biological indicators; additionally, trophic diatom index, benthic macroinvertebrate index, and fish assessment index values were greater than 0.7. The results of spatial autocorrelation analysis suggested that a significant spatial dependency existed between environmental and biological indicators. Regression tree analysis was conducted for each indicator to compensate for the occurrence of autocorrelation; subsequently, the slope in riparian areas was the first criterion of differentiation for biological condition datasets in all regression trees. These findings suggest that considering spatial autocorrelation for statistical analyses of stream ecosystems, riparian proximity, and topographical characteristics for land use planning around the streams is essential to maintain the healthy biological conditions of streams.
已经开展了多项研究来确定河流生态系统与土地覆盖之间复杂多样的关系。然而，这些研究没有考虑河流系统结构中固有的空间依赖性。因此，本研究旨在使用回归树分析来分析绿色/城市区域和地形变量与生物指标之间的关系，该分析考虑了两个不同尺度的空间自相关性。主成分分析结果表明，在所有成分（包括生物指标）中，地形变量的权重最高。莫兰指数值验证了生物指标的空间自相关性；此外，营养硅藻指数、底栖大型无脊椎动物指数和鱼类评估指数值均大于0.7。空间自相关性分析结果表明，环境指标与生物指标之间存在显著的空间依赖性。为补偿自相关的出现，对每个指标进行了回归树分析；随后，河岸区域的坡度是所有回归树中生物状况数据集的首要区分标准。这些发现表明，在对河流生态系统进行统计分析时考虑空间自相关性、河岸接近度以及河流周围土地利用规划的地形特征对于维持河流健康的生物状况至关重要。
