| Abstract: | Alpha‐diversity of geometrid moths was investigated along an elevational gradient in a tropical montane rainforest in southern Ecuador. Diversity was measured using 1) species number, 2) extrapolated species number (Chao 1 estimator), 3) rarefied species number, and 4) Fisher's alpha. When applied to the empirical data set, 1 and 2 strongly depended on the sample size, whereas 3 and 4 were suitable and reliable measures of local diversity. At single sites, up to 292 species were observed, and extrapolation estimates range from 244 to 445 species. Values for Fisher's alpha are among the highest ever measured for this moth family, and range from 69 to 131 per site. In contrast to theoretical assumptions and empirical studies in other regions of the world, the diversity of geometrid moths remained consistently high along the entire gradient studied. Diversity measures correlated with neither altitude nor ambient temperature. The large subfamily Ennominae has previously been assumed to be a group that occurs mainly at low and medium elevations. However, no decline in diversity was found in the study area. The diversity of the other large subfamily, Larentiinae, even increased from the lowest elevations and was highest at elevations above 1800 m. The roles of a decreasing diversity of potential host‐plants, decreasing structural complexity of the vegetation, increasingly unfavourable climatic conditions and possible physiological adaptations in determining herbivore species richness are discussed. A relatively low predation pressure might be an advantage of high‐altitude habitats. The physiognomy of the Andes (folded mountains, large areas at high altitudes) might also have allowed speciation events and the development of a species‐rich high‐altitude fauna. There is evidence that the species‐richness of other groups of herbivorous insects in the same area declines as altitude increases. This emphasises difficulties that are associated with biodiversity indicator groups, and calls for caution when making generalisations from case studies. |
