UK Environmental Change Network (ECN) coarse grain vegetation data: 1993-2012

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Dataset information

Country of origin
Updated
Created
Available languages
English
Keywords
Moor House - Upper Teesdale, Glensaugh, NEC04638, Sustainable Land Management, Wytham, Hillsborough, North Wyke, ILTER, Natural Hazards, Environmental Informatics, LTER, Natural Capital, Environmental Monitoring Facilities, Soil, Ecological Processes and Resilience, semi-natural and managed vegetation, Every 9 years, Biosphere-Atmosphere Interactions, Water Resources, Alice Holt, Pollution and Environmental Risk, Monitoring and Observations Systems, Drayton, Rothamsted, Sourhope, vegetation species, Environmental Change Network, biodiversity, Yr Wyddfa - Snowdon
Quality scoring
130

Dataset description

Coarse grain vegetation data from the UK Environmental Change Network (ECN) terrestrial sites. These data are collected at all of ECN's terrestrial sites using a standard protocol (see supporting documentation). In this protocol, 50 2m x 2m plots are randomly selected within each vegetation type on the site - species presence is recorded in 40cm x 40 cm cells randomly selected within these plots. They represent continuous records every nine years from 1993 to 2012. 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/d349babc-329a-4d6e-9eca-92e630e1be3f
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