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Indexing butterfly abundance whilst accounting for missing counts and variability in seasonal pattern

Dennis, Emily B., Freeman, Stephen N., Brereton, Tom, Roy, David B. (2013) Indexing butterfly abundance whilst accounting for missing counts and variability in seasonal pattern. Methods in Ecology and Evolution, 4 (7). pp. 637-645. (doi:10.1111/2041-210X.12053) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:57932)

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1. Volunteer-based ‘citizen science’ schemes now play a valuable role in deriving biodiversity indicators, both

method for analysing such data based on counts of invertebrate species characterised by highly variable numbers

makesmore efficient use of the data than previous analyses, whilst accounting for missing values. Firstly, generalised

The estimated daily values were then normalised to estimate a seasonal pattern that is the same across sites

to estimate annual changes in abundance accounting for the varying seasonality.

3. The method was tested and compared against the current approach and a simple linear interpolation using

study demonstrated accurate estimation of linear time trends and improved power for detecting trends compared with

predicted trends over time, but confidence intervals were generally narrower for the two-stage model.

5. In addition to creating more robust trend estimates, the new method allows all volunteer records to contribute

average, the current model only enables data from 60% of 10 km2 grid squares with monitored sites to be

monitored area. As many invertebrate species exhibit similar patterns of emergence or voltinism, our two-stage

method could be applied to other taxa.

Item Type: Article
DOI/Identification number: 10.1111/2041-210X.12053
Uncontrolled keywords: butterfly monitoring, citizen science, count data, generalised additive models, missing data
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Q Science > QH Natural history > QH541 Ecology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
Depositing User: Emily Dennis
Date Deposited: 18 Oct 2016 10:16 UTC
Last Modified: 16 Feb 2021 13:38 UTC
Resource URI: (The current URI for this page, for reference purposes)
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