A generic method for estimating and smoothing multispecies biodiversity indicators using intermittent data

Freeman, Stephen N.; Isaac, Nicholas J.B. ORCID: https://orcid.org/0000-0002-4869-8052; Besbeas, Panagiotis; Dennis, Emily B.; Morgan, Byron J.T.. 2021 A generic method for estimating and smoothing multispecies biodiversity indicators using intermittent data. Journal of Agricultural, Biological and Environmental Statistics, 26 (1). 71-89. 10.1007/s13253-020-00410-6

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Official URL: http://dx.doi.org/10.1007/s13253-020-00410-6

Abstract/Summary

Biodiversity indicators summarise extensive, complex ecological data sets and are important in influencing government policy. Component data consist of time-varying indices for each of a number of different species. However, current biodiversity indicators suffer from multiple statistical shortcomings. We describe a state-space formulation for new multispecies biodiversity indicators, based on rates of change in the abundance or occupancy probability of the contributing individual species. The formulation is flexible and applicable to different taxa. It possesses several advantages, including the ability to accommodate the sporadic unavailability of data, incorporate variation in the estimation precision of the individual species’ indices when appropriate, and allow the direct incorporation of smoothing over time. Furthermore, model fitting is straightforward in Bayesian and classical implementations, the latter adopting either efficient Hidden Markov modelling or the Kalman filter. Conveniently, the same algorithms can be adopted for cases based on abundance or occupancy data—only the subsequent interpretation differs. The procedure removes the need for bootstrapping which can be prohibitive. We recommend which of two alternatives to use when taxa are fully or partially sampled. The performance of the new approach is demonstrated on simulated data, and through application to three diverse national UK data sets on butterflies, bats and dragonflies. We see that uncritical incorporation of index standard errors should be avoided.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1007/s13253-020-00410-6
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-)
ISSN:	1085-7117
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	bats, butterflies, dragonflies, hidden Markov models, hierarchical models, state-space models
NORA Subject Terms:	Ecology and Environment
Date made live:	26 Dec 2020 11:16 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/529278

Item Type:

Publication - Article

Digital Object Identifier (DOI):

10.1007/s13253-020-00410-6

UKCEH and CEH Sections/Science Areas:

Biodiversity (Science Area 2017-)

ISSN:

1085-7117

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

bats, butterflies, dragonflies, hidden Markov models, hierarchical models, state-space models