Frota Augusto, da Graça Weferson Júnio
Universidade Estadual de Maringá (UEM), Centro de Ciências Biológicas (CCB), Departamento de Biologia (DBI), Programa de Pós-Graduação em Ecologia de Ambientes Aquáticos Continentais (PEA), Av. Colombo, 5790, Maringá, 87020900, Paraná, Brazil.
UEM, CCB, Programa de Pós-Graduação em Biologia Comparada (PGB), Av. Colombo, 5790, Maringá, 87020900, Paraná, Brazil.
Cladistics. 2025 Oct;41(5):493-512. doi: 10.1111/cla.70002. Epub 2025 Jun 19.
Delineating Areas of Endemism (AEs) is crucial for identifying priority areas for biodiversity conservation in a spatial planning framework. Endemicity Analysis in the NDM/VNDM software is one of the primary methodologies for its delineation. Larger grid sizes have been employed to yield higher endemicity scores for AEs, recovering more endemic species and enhancing their conservation appeal. Compiling a robust geographic distribution dataset for 399 freshwater fish species from Southern Brazil, we identified AEs by conducting endemicity analyses with three different grid sizes. We also developed a spatial conservation Priority Index incorporating three grid-size-dependent attributes. We identified 153 AEs, each varying in endemicity scores, species richness, and threatened species. These variations were influenced by the analysed grid size and spatial overlap with specific freshwater ecoregions. The recovered AEs show freshwater fish distribution patterns corroborating significant vicariance events and faunal exchanges between river basins in distinct bordering ecoregions. We found an almost 50% reduction in spatial area when ranking Endemicity and Priority Index scores. This finding demonstrates the effectiveness of the Priority Index in highlighting similar sets of endemic, sympatric, and threatened species within smaller areas. This approach can effectively reconcile attributes easily extracted from the NDM/VNDM program when prioritizing spatial conservation.
划定特有区域(AE)对于在空间规划框架内确定生物多样性保护的优先区域至关重要。NDM/VNDM软件中的特有性分析是其划定的主要方法之一。已采用更大的网格尺寸来为特有区域得出更高的特有性得分,从而发现更多特有物种并增强其保护吸引力。通过汇编巴西南部399种淡水鱼的强大地理分布数据集,我们使用三种不同的网格尺寸进行特有性分析来确定特有区域。我们还开发了一个空间保护优先指数,该指数纳入了三个与网格尺寸相关的属性。我们确定了153个特有区域,每个特有区域的特有性得分、物种丰富度和受威胁物种各不相同。这些差异受到所分析的网格尺寸以及与特定淡水生态区域的空间重叠的影响。所发现的特有区域显示出淡水鱼的分布模式,证实了不同相邻生态区域内流域之间显著的间断分布事件和动物区系交流。我们发现,在对特有性和优先指数得分进行排名时,空间面积减少了近50%。这一发现表明优先指数在突出较小区域内类似的特有、同域和受威胁物种集合方面的有效性。在确定空间保护优先级时,这种方法可以有效地协调从NDM/VNDM程序中轻松提取的属性。