A generalized abundance index for seasonal invertebrates

Emily B. Dennis*, Byron J T Morgan, Stephen N. Freeman, Tom M. Brereton, David B. Roy

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

36 Citations (Scopus)
633 Downloads (Pure)

Abstract

At a time of climate change and major loss of biodiversity, it is important to have efficient tools for monitoring populations. In this context, animal abundance indices play an important rôle. In producing indices for invertebrates, it is important to account for variation in counts within seasons. Two new methods for describing seasonal variation in invertebrate counts have recently been proposed; one is nonparametric, using generalized additive models, and the other is parametric, based on stopover models. We present a novel generalized abundance index which encompasses both parametric and nonparametric approaches. It is extremely efficient to compute this index due to the use of concentrated likelihood techniques. This has particular relevance for the analysis of data from long-term extensive monitoring schemes with records for many species and sites, for which existing modeling techniques can be prohibitively time consuming. Performance of the index is demonstrated by several applications to UK Butterfly Monitoring Scheme data. We demonstrate the potential for new insights into both phenology and spatial variation in seasonal patterns from parametric modeling and the incorporation of covariate dependence, which is relevant for both monitoring and conservation. Associated R code is available on the journal website.

Original languageEnglish
Pages (from-to)1305-1314
Number of pages10
JournalBiometrics
Volume72
Issue number4
Early online date22 Mar 2016
DOIs
Publication statusPublished - 1 Dec 2016

Keywords

  • Butterflies
  • Citizen science
  • Concentrated likelihood
  • Normal mixtures
  • Phenology
  • UKBMS

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