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Annual estimates of occupancy for bryophytes, lichens and invertebrates in the UK, 1970–2015.

Authors :
Outhwaite, Charlotte L.
Powney, Gary D.
August, Tom A.
Chandler, Richard E.
Rorke, Stephanie
Pescott, Oliver L.
Harvey, Martin
Roy, Helen E.
Fox, Richard
Roy, David B.
Alexander, Keith
Ball, Stuart
Bantock, Tristan
Barber, Tony
Beckmann, Björn C.
Cook, Tony
Flanagan, Jim
Fowles, Adrian
Hammond, Peter
Harvey, Peter
Source :
Scientific Data; 11/5/2019, Vol. 6 Issue 1, pN.PAG-N.PAG, 1p
Publication Year :
2019

Abstract

Here, we determine annual estimates of occupancy and species trends for 5,293 UK bryophytes, lichens, and invertebrates, providing national scale information on UK biodiversity change for 31 taxonomic groups for the time period 1970 to 2015. The dataset was produced through the application of a Bayesian occupancy modelling framework to species occurrence records supplied by 29 national recording schemes or societies (n = 24,118,549 records). In the UK, annual measures of species status from fine scale data (e.g. 1 × 1 km) had previously been limited to a few taxa for which structured monitoring data are available, mainly birds, butterflies, bats and a subset of moth species. By using an occupancy modelling framework designed for use with relatively low recording intensity data, we have been able to estimate species trends and generate annual estimates of occupancy for taxa where annual trend estimates and status were previously limited or unknown at this scale. These data broaden our knowledge of UK biodiversity and can be used to investigate variation in and drivers of biodiversity change. Measurement(s) Occupancy • Species • biodiversity assessment objective Technology Type(s) occupancy modelling • biological records • Trends Factor Type(s) species Sample Characteristic - Organism Lichens • Invertebrates • Bryophytes Sample Characteristic - Location United Kingdom Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.9977426 [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20524463
Volume :
6
Issue :
1
Database :
Complementary Index
Journal :
Scientific Data
Publication Type :
Academic Journal
Accession number :
139501573
Full Text :
https://doi.org/10.1038/s41597-019-0269-1