Biological traits as functional indicators to assess and predict (using statistical models) the status of different habitats -

Type Scientific report
Date 2015
Language English
Ref. EU-FP7 Benthis Delivrable D3.4
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Author(s) Bolam Stéphane3, Eggleton Jacqueline D.3, Garcia Clement3, Kenny Andrew J.3, Buhl-Mortensen Lene2, Gonzalez Genoveva2, Kooten Tobias1, Dinesen Grete E.6, Hansen Jorgen6, Hiddink Jan Geert4, Sciberras Marija4, Smith Chris8, Papadopoulou K. Nadia8, Gumus Aysun9, Van Hoey Gert2, Laffargue PascalORCID5, Eigaard Ole6, Bastardie Francois6
Affiliation(s) 1 : IMARES, Wageningen UR, PO Box 68, 1970 AB IJmuiden, The Netherlands
2 : Institute for Agricultural and Fisheries Research, Animal Sciences Unit—Fisheries and Aquatic Production, Ankerstraat 1, 8400 Oostende, Belgium
3 : CEFAS, Pakefield Road, Lowestoft NR33 0HT, UK
4 : School of Ocean Sciences, Bangor University, Menai Bridge, Anglesey LL59 5AB, UK
5 : IFREMER, Unité Ecologie et Modèles pour l'Halieutique,44000 Nantes, France
6 : National Institute for Aquatic Resources, Technical University of Denmark, Charlottenlund Castle, 2920 Charlottenlund, Denmark
7 : Institute of Marine Research, PO Box 1870, 5817 Bergen, Norway
8 : Hellenic Centre for Marine Research, PO Box 2214, 71003 Heraklion, Crete, Greece
9 : Central Fisheries Research Institute, Kasu¨stu¨, Trabzon 61100, Turkey
Version 7
Note Grant Agreement number: 312088 Project acronym: BENTHIS Project title: Benthic Ecosystem Fisheries Impact Study Funding Scheme: Collaborative project Project coordination: IMARES, IJmuiden, the Netherlands Project website:
Abstract One of the most widespread yet manageable pressures imposed on the seabed is that resulting from disturbance of the substrate by towed demersal fishing gear (bottom fishing and dredging). Demersal fishing gears are deployed on every continental shelf in the world and, in UK waters, the footprint of fishing is estimated to account for over 99% of the known footprint of all human pressures on the seabed. It is, therefore, essential that current and future management of fishing activities are based on an improved scientific rationale in order to improve the long-term sustainability of this activity.
While the impacts of demersal fishing on the biological characteristics of the seabed have been well-studied, the approaches have tended to focus on assessing impacts on the structural (e.g. changes in species composition, diversity, etc.) characteristics of seabed biological assemblages. However, it is being increasingly appreciated that observing changes solely in the structural attributes of benthic assemblages provides only a limited capacity to inform us of the implications for, arguably far more important, ecosystem function. The present study aims to bridge this knowledge gap by analysing data regarding the biological assemblages of a large number of stations covering a range of habitats across the European continental shelf. We perform this using a biological traits analysis (BTA) in which the assemblages, and the differences between them, are quantified by their relative differences in the morphological, behavioural and life history characteristics of their individuals, as opposed to their taxonomic (i.e., based on species identity) differences. This BTA approach affords the opportunity to understand the potential differences in ecological functioning due to fishing impacts, beyond that which would otherwise be possible from structural approaches.
Traits data regarding the infauna (those organisms that live within the sediment) were available for 819 sampling stations, while for the epifauna (those living on the sediment), data for 1316 stations were analysed. BTA was undertaken on these two biological components independently. The infaunal stations were categorised into 13 EUNIS habitats (level 4) while the epifaunal data represented seven EUNIS (level 3) habitats. Additionally, the data for the infaunal stations were classed according to habitats that were derived following a k-means clustering approach of the environmental characteristics; this allowed an assessment (for the infauna) of the importance of using different habitat derivation methods for biological traits assessments over large spatial scales.
Using data from relatively non-fished stations, fuzzy correspondence analysis (FCA), a multivariate analysis approach particularly suitable for traits data, revealed that traits composition of infaunal and epifaunal assemblages did not vary markedly between habitats. This result was generally observed for all 10 of the infaunal, and 12 of the epifaunal, traits examined. Moreover, the proportional compositions of the various biological traits showed a high amount of within-habitat variability, even in the absence of moderate or high fishing pressure.
FCA was then used to allow an assessment of how biological trait compositions were related to total fishing pressure, both within and between habitats. The results suggested that the effects of fishing on trait compositions are complex; assemblages vary in their response both within and between habitats and, while some biological traits showed more-or-less consistent responses across habitats, others displayed varying relationships with fishing pressure across habitats. There is evidence to suggest that at least some of this habitat-specificity in response reflects differences in fishing gear, as opposed to differences in the inherent responses of the biological assemblages between habitats. We discuss the implications of these findings with respect to the impacts of fishing on the functional properties of seabed biological assemblages, and how the results presented here are to be used further within other work being conducted under Benthis.
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Bolam Stéphane, Eggleton Jacqueline D., Garcia Clement, Kenny Andrew J., Buhl-Mortensen Lene, Gonzalez Genoveva, Kooten Tobias, Dinesen Grete E., Hansen Jorgen, Hiddink Jan Geert, Sciberras Marija, Smith Chris, Papadopoulou K. Nadia, Gumus Aysun, Van Hoey Gert, Laffargue Pascal, Eigaard Ole, Bastardie Francois (2015). Biological traits as functional indicators to assess and predict (using statistical models) the status of different habitats -. EU-FP7 Benthis Delivrable D3.4.