Lobo Jorge M, Martín-Piera Fermín
Departamento de Biodiversidad y Biología Evolutiva ( Entomología), Museo Nacional de Ciencias Naturales, c/o José Gutiérrez Abascal, 2.
28006, Madrid, SPAIN.
Conserv Biol. 2002 Feb;16(1):158-173. doi: 10.1046/j.1523-1739.2002.00211.x.
In Mediterranean countries, inventories of many animal groups, particularly insects, are incomplete or nonexistent. Hence, a feasible spatial picture of unequally surveyed areas is required to ascertain which faunistic surveys are good enough to produce reliable estimates of species richness. We used generalized linear models to build a multiple-regression function through which we predicted the distribution of Iberian dung beetle species richness. Given the scarcity and unevenness of the species-richness spatial distribution, the number of records of a dung beetle database ( BANDASCA ), falling within each of the 50 × 50 km grid squares, was chosen as a measure of the sampling effort for that square. Examining the asymptotic relationship between the number of dung-beetle species and database records for each physioclimatic Iberian subregion, we found that 82 grid squares (32% of the total) were adequately sampled. Dung-beetle species richness was related in each of these 82 cells to 24 explanatory variables. Curvilinear functions, interaction terms, and the significant third-degree polynomial terms of latitude and longitude were included to model species-richness distribution. The final model accounted for 62.4% of the total deviance after we eliminated seven outlier squares, with maximum elevation, grassland area, land-use diversity, forest area, geological diversity, interaction of terrestrial area and maximum elevation, and interaction between calcareous rock and geological diversity and latitude being the most significant independent variables. The residuals of the function were not spatially autocorrelated, and we validated the final model by a jackknife procedure. Large and environmentally complex hotspots in the Iberian Central, Baetic, and Subbaetic mountain ranges stand out from the emerging map of species richness. Further detailed research is required to determine the complementarity of the faunas of these two main hotspots, the key question in conservation planning for a dung-feeding beetle.
在地中海国家,许多动物类群的清单,尤其是昆虫的清单并不完整或根本不存在。因此,需要一幅关于调查程度不均衡地区的可行空间图,以确定哪些动物区系调查足以可靠地估计物种丰富度。我们使用广义线性模型构建了一个多元回归函数,通过该函数预测伊比利亚蜣螂物种丰富度的分布。鉴于物种丰富度空间分布的稀缺性和不均衡性,我们选择了蜣螂数据库(BANDASCA)中落入每个50×50千米网格方块内的记录数量,作为该方块采样工作量的一种衡量。通过研究伊比利亚每个生理气候亚区域内蜣螂物种数量与数据库记录之间的渐近关系,我们发现有82个网格方块(占总数的32%)得到了充分采样。在这82个单元格中,蜣螂物种丰富度与24个解释变量相关。我们纳入了曲线函数、交互项以及纬度和经度的显著三次多项式项来模拟物种丰富度分布。在剔除了7个异常方块后,最终模型解释了总偏差的62.4%,其中最大海拔、草地面积、土地利用多样性、森林面积、地质多样性、陆地面积与最大海拔的交互作用,以及钙质岩石与地质多样性和纬度之间的交互作用是最显著的自变量。该函数的残差不存在空间自相关性,我们通过留一法验证了最终模型。伊比利亚中部、贝蒂克山脉和苏贝蒂克山脉中面积大且环境复杂的热点地区,在新出现的物种丰富度地图上格外突出。需要进一步开展详细研究,以确定这两个主要热点地区动物区系的互补性,这是食粪甲虫保护规划中的关键问题。