Botham, M.S.; Brereton, T.; Harris, S.; Harrower, C.; Middlebrook, I.; Randle, Z.; Roy, D.B.

United Kingdom Butterfly Monitoring Scheme: species trends 2018

This dataset provides linear trends, over varying time periods, for the UK Butterfly Monitoring Scheme (UKBMS) collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976 to 2018), for the last 20 years, and for the last decade. In addition a trend class, based on slope direction and its significance, and a percentage change for that time period are provided to describe the statistical trends. These trend data are provided for 59 UK butterfly species. Trends across different time series allow us to determine the long and short-term trends for individual species. This enables us to focus conservation and research and also to assess species responses to conservation already in place.

The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the Centre for Ecology & Hydrology (CEH), the British Trust for Ornithology (BTO), and the Joint Nature Conservation Committee (JNCC). The UKBMS is indebted to all volunteers who contribute data to the scheme.

Publication date: 2019-11-01

Get the data

This dataset is available under the terms of the Open Government Licence

Format of the dataset : Comma-separated values (CSV)

You must cite: Botham, M.S.; Brereton, T.; Harris, S.; Harrower, C.; Middlebrook, I.; Randle, Z.; Roy, D.B. (2019). United Kingdom Butterfly Monitoring Scheme: species trends 2018. NERC Environmental Information Data Centre. https://doi.org/10.5285/ee4b440e-2604-40b9-bca7-19d6392bd9ea

 

© Centre for Ecology & Hydrology (Natural Environment Research Council)

© Butterfly Conservation

© British Trust for Ornithology

© Natural Environment Research Council

© Joint Nature Conservation Committee

This dataset is part of the following

Where/When

Study area
Temporal extent
2018-04-01    to    2018-09-30

Provenance & quality

Trends are calculated by performing a linear regression on the annual Collated Indices for each species. Indices are calculated for all species (across WCBS squares and traditional UKBMS sites) using the Generalised Abundance Index (GAI) method developed in 2016 with an additional modification that the data from each site in each year is weighted in the final stage relative to the proportion of the species flight period surveyed that year for that site. They give a statistical measure of how the abundance of each species has changed on monitored sites since 1976, over the last 20 years, and over the last decade. Because the Collated indices are only calculated for each species in years in which there was sufficient data available, the starting year for the series is later than 1976 for a number of rarer species.

Supplemental information

Other useful information regarding this dataset:

Correspondence/contact details

Marc Botham
Centre for Ecology & Hydrology
Maclean Building, Benson Lane, Crowmarsh Gifford
Wallingford
Oxfordshire
OX10 8BB
United Kingdom
 enquiries@ceh.ac.uk
Tom Brereton
Butterfly Conservation
 tbrereton@butterfly-conservation.org

Authors

Botham, M.S.
Centre for Ecology & Hydrology
Brereton, T.
Butterfly Conservation
Harris, S.
British Trust for Ornithology
Harrower, C.
Centre for Ecology & Hydrology
Middlebrook, I.
Butterfly Conservation
Randle, Z.
Butterfly Conservation
Roy, D.B.
Centre for Ecology & Hydrology

Other contacts

Custodian
Environmental Information Data Centre
 eidc@ceh.ac.uk
Publisher
NERC Environmental Information Data Centre
 eidc@ceh.ac.uk

Additional metadata

Topic categories
Biota
Keywords
annual,  Biodiversity butterflies,  England Lepidoptera,  Northern Ireland Scotland United Kingdom Wales
INSPIRE Theme
Species Distribution
Funding
Natural Environment Research Council
Spatial representation type
Tabular (text)
Spatial reference system
OSGB 1936 / British National Grid
Last updated
04 November 2019 15:37