Biondi Maurizio, D'Alessandro Paola, De Simone Walter, Iannella Mattia
Department of Life, Health & Environmental Sciences, University of L'Aquila, Via Vetoio Coppito, 67100 L'Aquila, Italy.
Insects. 2021 Dec 13;12(12):1115. doi: 10.3390/insects12121115.
Areas of endemism (AoEs) are a central area of research in biogeography. Different methods have been proposed for their identification in the literature. In this paper, a "grid-free" method based on the "Density-based spatial clustering of applications with noise" (DBSCAN) is here used for the first time to locate areas of endemism for species belonging to the beetle tribe Chrysomelidae, Galerucinae, Alticini in the Afrotropical Region. The DBSCAN is compared with the "Geographic Interpolation of Endemism" (GIE), another "grid-free" method based on a kernel density approach. DBSCAN and GIE both return largely overlapping results, detecting the same geographical locations for the AoEs, but with different delimitations, surfaces, and number of detected sinendemisms. The consensus maps obtained by GIE are in general less clearly delimited than the maps obtained by DBSCAN, but nevertheless allow us to evaluate the core of the AoEs more precisely, representing of the percentage levels of the overlap of the centroids. DBSCAN, on the other hand, appears to be faster and more sensitive in identifying the AoEs. To facilitate implementing the delimitation of the AoEs through the procedure proposed by us, a new tool named "CLUENDA" (specifically developed is in GIS environment) is also made available.
特有种分布区（AoEs）是生物地理学研究的核心领域。文献中已提出了不同的方法来识别它们。在本文中，首次使用了一种基于“带噪声的基于密度的空间聚类应用”（DBSCAN）的“无网格”方法来定位属于非洲热带地区叶甲科叶甲亚科跳甲族的物种的特有种分布区。将DBSCAN与另一种基于核密度方法的“特有种地理插值法”（GIE）这一“无网格”方法进行了比较。DBSCAN和GIE返回的结果在很大程度上相互重叠，检测到的特有种分布区的地理位置相同，但划分、面积和检测到的特有现象数量不同。GIE获得的共识图总体上比DBSCAN获得的图划分得更不清晰，但仍然使我们能够更精确地评估特有种分布区的核心，即表示质心重叠的百分比水平。另一方面，DBSCAN在识别特有种分布区方面似乎更快且更敏感。为便于通过我们提出的程序实施特有种分布区的划分，还提供了一个名为“CLUENDA”的新工具（专门在GIS环境中开发）。
