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(Dutertre et al. 2013 ; Hillebrand 2004 ; Posey et al. 1995 ). Additionally, biological
interactions (e.g. competition, predation) among species in
uence the diversity of
marine assemblages (Defeo and McLachlan 2005 ). Many benthic species constitute
a food source for
fl
fish may directly
reduce epifaunal abundances while their effects on infaunal species may be limited
(Schlacher and Wooldridge 1996 ).
Marine ecosystems are routinely subjected to a wide range of anthropogenic
disturbances (Marques et al. 2009 ; van der Molen et al. 2013 ). Exposure to bottom
trawling, aggregate extraction and pollution are responsible for alteration of bottom
habitats and may contribute to changes in growth, mortality and recruitment rate of
species (Bergman and Hup 1992 ; Dannheim et al. 2014 ; Worm et al. 2006 ). These
changes have the potential to modify the structure and functioning of benthic
communities (van der Linden et al. 2012 ; Worm et al. 2006 ).
Ecosystem functioning is a general concept that encompasses a variety of phe-
nomena, including ecosystem processes (e.g. energy
fish and other predators (Pinto 2011 ). Predatory
fluxes), properties (e.g. pools
of carbon and organic matter) and services (e.g. human alimentation) as well as the
resistance or resilience of these factors in response to
fl
fl
fluctuating abiotic conditions
í
(Bremner et al. 2006 ;D
az et al. 2008 ; Hooper et al. 2005 ; Loreau et al. 2001 ; van
der Linden et al. 2012 ). Ecosystem functioning mainly depends on traits or char-
acteristics of the constituent functional groups of organisms (Snelgrove 1997 ).
Traditional analytical procedures, which derive biodiversity and community
structure from species abundance/biomass data, do not take into account functional
features of species (van der Linden et al. 2012 ). However, functional diversity, i.e.
the range and number of functional traits performed within an ecosystem (D
az and
Cabido 2001 ), is a useful indicator of ecosystem functioning (Hooper et al. 2005 ).
Several methods based on species morphological and ecological traits have been
proposed to describe and quantify functional diversity of benthic assemblages
(Beche et al. 2006 ; Bremner et al. 2006 ; Pacheco et al. 2011 ; van der Molen et al.
2013 ). We used biological trait analysis (BTA) to explore the ecological func-
tioning of benthic assemblages (Sigala et al. 2012 ; van der Linden et al. 2012 ) and
to compare functional diversity across different assemblages. BTA combines
quantitative structural data (e.g. abundance) with information on biological char-
acteristics of the taxa (Shettleworth 2012 ) to functionally characterise species
assemblages (Bremner et al. 2006 ). This method is suitable for analysing assem-
blage responses to environmental parameters (Paganelli et al. 2012 ; Shettleworth
2012 ). Hence, BTA provides a link between benthic assemblages, environment and
ecosystem processes (Oug et al. 2012 ; Pacheco et al. 2011 )
The objectives of this study were (a) to determine the dominant functional
characteristics of the German Bight benthos and (b) to identify functional differ-
ences between benthic communities at different sites by comparing functional
diversity.
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