TY - JOUR
T1 - Extensive gaps and biases in our knowledge of a well-known fauna: Implications for integrating biological traits into macroecology
AU - Tyler, Elizabeth
AU - Somerfield, Paul John
AU - Berghe, Edward Vanden
AU - Bremner, Julie
AU - Jackson, Emma L.
AU - Langmead, Olivia
AU - Palomares, Maria Lourdes Deng
AU - Webb, Thomas J.
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We would like to thank Paul Robinson at the Joint Nature Conservation Committee (Marine Nature Conservation Review), Chris Wood (Seasearch) and the British Oceanographic Data Centre (Cleans Seas Environment Monitoring Programme) for contributing these data sets and Dan Lear at the Data Archive for Seabed Species and Habitats (DASSH) for recommending surveys. Calum Watt, Rachel Mallichan and Ruth Bowyer helped compile data. Andrew Hosie, Dan Bayley and Jaret Bilewitch at the Marine Biological Association helped us utilize BIOTIC data and Susan Luna helped us with FishBase larval data. Dave Palmer, Andy Lawler and Mike Smith at the Centre for Environment, Fisheries and Aquaculture Science (CEFAS) provided commercial ratings for invertebrates. Thanks also to Daniel Pauly of the Sea Around Us project, a scientific cooperation between the University of British Columbia and the Pew Environment Group. This work was improved by comments from Erik Bonsdorff, Anna Tornroos and two anonymous referees, and through discussions with Rob Freckleton. E. V. B. and the OBIS Secretariat are funded by the Sloan Foundation. This work was funded by the Natural Environment Research Council through a Strategic Oceans Funding Initiative grant to T.J.W. and P.J.S. T.J.W. is a Royal Society Research Fellow.
PY - 2011/12/9
Y1 - 2011/12/9
N2 - Aim Ecologists seeking to describe patterns at ever larger scales require compilations of data on the global abundance and distribution of species. Comparable compilations of biological data are needed to elucidate the mechanisms behind these patterns, but have received far less attention. We assess the availability of biological data across an entire assemblage: the well-documented demersal marine fauna of the United Kingdom. We also test whether data availability for a species depends on its taxonomic group, maximum body size, the number of times it has been recorded in a global biogeographic database, or its commercial and conservation importance. Location Seas of the United Kingdom. Methods We defined a demersal marine fauna of 973 species from 15 phyla and 40 classes using five extensive surveys around the British Isles. We then quantified the availability of data on eight key biological traits (termed biological knowledge) for each species from online databases. Relationships between biological knowledge and our predictors were tested with generalized linear models. Results Full data on eight fundamental biological traits exist for only 9% (n= 88) of the UK demersal marine fauna, and 20% of species completely lack data. Clear trends in our knowledge exist: fish (median biological knowledge score = six traits) are much better known than invertebrates (one trait). Biological knowledge increases with biogeographic knowledge and (to a lesser extent) with body size, and is greater in species that are commercially exploited or of conservation concern. Main conclusions Our analysis reveals deep ignorance of the basic biology of a well-studied fauna, highlighting the need for far greater efforts to compile biological trait data. Clear biases in our knowledge, relating to how well sampled or 'important' species are suggests that caution is required in extrapolating small subsets of biologically well-known species to ecosystem-level studies. © 2011 Blackwell Publishing Ltd.
AB - Aim Ecologists seeking to describe patterns at ever larger scales require compilations of data on the global abundance and distribution of species. Comparable compilations of biological data are needed to elucidate the mechanisms behind these patterns, but have received far less attention. We assess the availability of biological data across an entire assemblage: the well-documented demersal marine fauna of the United Kingdom. We also test whether data availability for a species depends on its taxonomic group, maximum body size, the number of times it has been recorded in a global biogeographic database, or its commercial and conservation importance. Location Seas of the United Kingdom. Methods We defined a demersal marine fauna of 973 species from 15 phyla and 40 classes using five extensive surveys around the British Isles. We then quantified the availability of data on eight key biological traits (termed biological knowledge) for each species from online databases. Relationships between biological knowledge and our predictors were tested with generalized linear models. Results Full data on eight fundamental biological traits exist for only 9% (n= 88) of the UK demersal marine fauna, and 20% of species completely lack data. Clear trends in our knowledge exist: fish (median biological knowledge score = six traits) are much better known than invertebrates (one trait). Biological knowledge increases with biogeographic knowledge and (to a lesser extent) with body size, and is greater in species that are commercially exploited or of conservation concern. Main conclusions Our analysis reveals deep ignorance of the basic biology of a well-studied fauna, highlighting the need for far greater efforts to compile biological trait data. Clear biases in our knowledge, relating to how well sampled or 'important' species are suggests that caution is required in extrapolating small subsets of biologically well-known species to ecosystem-level studies. © 2011 Blackwell Publishing Ltd.
UR - http://hdl.handle.net/10754/561953
UR - http://doi.wiley.com/10.1111/j.1466-8238.2011.00726.x
UR - http://www.scopus.com/inward/record.url?scp=84863624840&partnerID=8YFLogxK
U2 - 10.1111/j.1466-8238.2011.00726.x
DO - 10.1111/j.1466-8238.2011.00726.x
M3 - Article
SN - 1466-822X
VL - 21
SP - 922
EP - 934
JO - Global Ecology and Biogeography
JF - Global Ecology and Biogeography
IS - 9
ER -