UK Environmental Change Network (ECN) rabbit and deer data: 1993-2015

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Environmental Information Data Centre
Last updated:
29 June 2024
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Summary

Rabbit and deer data from the UK Environmental Change Network (ECN) terrestrial sites. These data are collected by transect at ECN's terrestrial sites using a standard protocol. The protocol uses an index method based on dropping counts (of deer, rabbits - and where appropriate sheep and Grouse) to estimate relative abundance. They represent twice-yearly continuous records from 1993 to 2015. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/0be0aed3-f205-4f1f-a65d-84f8cfd8d50f

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Link to the data Format File added Data preview
Download the data N/A 29 June 2024 Not available
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Added to data.gov.uk
2024-02-27
Access contraints
© UK Centre for Ecology & Hydrology
Harvest GUID
0be0aed3-f205-4f1f-a65d-84f8cfd8d50f
Extent
Latitude: 60.861° to 49.864°
Longitude: -8.648° to 1.768°
Spatial reference system
Dataset reference date
2017-12-15 (publication)
Frequency of update
notPlanned
Responsible party
(author, publisher, custodian, owner); UK Environmental Change Network (pointOfContact)
ISO 19139 resource type
dataset
Metadata language
eng
Source Metadata
XML
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