Local frequency as a key to interpreting species occurrence data when recording effort is not known

Hill, Mark O.. 2012 Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods in Ecology and Evolution, 3 (1). 195-205. https://doi.org/10.1111/j.2041-210X.2011.00146.x

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Abstract/Summary

1. Data on the occurrence of species in grid cells are collected by biological recording schemes, typically with the intention of publishing an atlas. Interpretation of such data is often hampered by the lack of information on the effort that went into collecting them. This is the ‘recorder effort problem’. 2. One measure of recorder effort is the proportion of a suite of common species (‘benchmark species’) found at a given location and time. Benchmark species have in the past been taken as a uniform set across a territory. However, if records are available from a neighbourhood surrounding a given location, then a local set benchmark species can be defined by pooling records from the neighbourhood and selecting the commonest species in the pooled set. 3. Neighbourhoods differ in species richness, so that the list of species that ‘ought’ to be found in one location may be longer than that for another. If the richness of a neighbourhood can be estimated, then a suite of benchmark species can be standardized to be the commonest of a fixed proportion of the total expected for the neighbourhood. Recording effort is then defined as the proportion of benchmark species that were found. 4. A method of estimating species richness is proposed here, based on the local frequencies fj of species in neighbouring grid cells. Species discovery is modelled as a Poisson process. It is argued that when a neighbourhood is well sampled, the frequency-weighted mean frequency Σfj2/Σfj of species in the neighbourhood will assume a standard value. 5. The method was applied to a data set of 2 000 000 records detailing the occurrence of bryophytes in 3695 out of the total 3854 hectads (10-km squares) in Great Britain, Ireland, the Isle of Man and the Channel Islands. 6. Three main applications are outlined: estimation of recording effort, scanning data for unexpected presences or absences and measurement of species trends over time. An explicit statistical model was used to estimate trends, modelling the probability of species j being found at location i and time t as the outcome of Poisson process with intensity Qijt xjt, where xjt is a time factor for species j, and Qijt depends on recording effort at location i and time t and on the time-independent probability of species j being found in hectad i.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/j.2041-210X.2011.00146.x
Programmes:	CEH Topics & Objectives 2009 - 2012 > Biodiversity > BD Topic 1 - Observations, Patterns, and Predictions for Biodiversity > BD - 1.3 - Long-term/large-scale monitoring and experiments ...
UKCEH and CEH Sections/Science Areas:	UKCEH Fellows
ISSN:	2041-210X
Additional Information. Not used in RCUK Gateway to Research.:	The attached document is the author’s final manuscript version of the journal article, incorporating any revisions agreed during the peer review process. Some differences between this and the publisher’s version remain. You are advised to consult the publisher’s version if you wish to cite from this article.
Additional Keywords:	benchmark species, discovery curve, neighbourhood, rank-frequency curve, species richness
NORA Subject Terms:	Biology and Microbiology
Date made live:	03 Feb 2012 14:50 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/16610

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