Choosing and using diversity indices: insights for ecological applications from the German Biodiversity Exploratories

• Published in: Ecology and evolution 2014-09, Vol.4 (18), p.3514-3524
• Main Authors: Morris, E. Kathryn, Caruso, Tancredi, Buscot, François, Fischer, Markus, Hancock, Christine, Maier, Tanja S., Meiners, Torsten, Müller, Caroline, Obermaier, Elisabeth, Prati, Daniel, Socher, Stephanie A., Sonnemann, Ilja, Wäschke, Nicole, Wubet, Tesfaye, Wurst, Susanne, Rillig, Matthias C.
• Format: Article
• Language: English
• Subjects: Agricultural land; Arbuscular mycorrhizal fungi; Arbuscular mycorrhizas; Arthropoda; Arthropods; Berger–Parker; Biodiversity; chemical diversity; Data mining; Diversity indices; Dominance; Environmental monitoring; Fungi; Grasslands; Hill's powers; Insects; Landscape; Larvae; molecular diversity; Organic chemistry; Original Research; plant diversity; Plantago lanceolata; Shannon index; Simpson's index; Species diversity; Species richness; Statistical analysis; Trophic levels
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.1155

Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D1), Simpson's dominance (D2), Simpson's evenness (E), and Berger–Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P. lanceolata molecular and chemical diversity. Including these trait‐based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system. Biodiversity is a difficult concept to quantify, partly because of its multidimensional nature, and many simple to complex indices have been developed for this purpose. We collected data on diversity of herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and Plantago lanceolata molecular and chemical diversity in 60 temperate grasslands and calculated a variety of s