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Type: Review Article
Published: 2013-09-26
Page range: 1-21
Abstract views: 99
PDF downloaded: 126

Measuring insect rarity: practical issues, pragmatic approaches

Ph.D. (Associate Research Fellow), Azorean Biodiversity Group (ABG- CITA-A), University of Azores, Angra do Heroísmo, Terceira, PORTUGAL
Department of Sciences, Universiy of Roma Tre, Viale G. Marconi 446, 00146, Rome, Italy
Centre for Ecology, Environment and Conservation, Department of Biological and Medical Sciences, Oxford Brookes University, Headington, Oxford, OX3 0BP, UK
Extinction risk conservation biology vulnerability distribution threat invertebrates arthropods.


Rarity is often considered an indication of species extinction risk, and rarity measures are used as important tools to predict species vulnerability and hence to establish conservation priorities. For these reasons, rarity is among the most important issues involved in conservation programs. A number of studies have attempted to investigate relationships between rarity and extinction risk in plants and vertebrates, whereas only few papers have investigated similar issues in invertebrate taxa. This has limited the use of standardized rarity measures in invertebrate conservation studies. Assessing rarity is especially important when other pieces of information are difficult, or even definitively impossible, to obtain, as commonly found for most insects. Four broad categories of rarity are commonly recognized: geographical, ecological, population and phylogenetic rarity. On the basis of this framework, we present here a short review of the rarity forms most frequently investigated in insect studies, and their relationships with the main species traits related to extinction risk (such as body size, mobility, trophic level, host specificity, larval and adult behaviours, etc.). We discuss what they mean, how they can be measured, which type of data (field collections, museum data, literature information) are needed and how to avoid the most common pitfalls associated with rarity studies, with indications for pragmatic approaches in data analysis.