Data from: Functional traits of marine macrophytes predict primary production

The relationship between community structure and the functioning of
ecosystems is the subject of ongoing debate. Biological or functional
trait-based approaches that capture life strategy, morphology and
behavioural characteristics have received far less attention than
taxonomic diversity in this context, despite their more intuitive link to
ecosystem functioning. Macrophyte primary production underpins aquatic
food webs, regulates benthic and pelagic ecosystems and is a key aspect of
the global carbon cycle. This study spans a range of aquatic biomes across
Europe and aims to examine potential for predicting primary production of
macrophyte communities based on the functional traits of species and
identify the traits that are the most informative indicators of macrophyte
production. Macrophyte primary production was assessed based on the oxygen
production of the whole community, linked to biomasses of selected
biological traits derived of its component species and analysed using the
novel boosted regression trees modelling technique. Results showed that
functional traits derived from macrophyte community data explained most of
the variation in primary production of macrophyte communities without the
need to incorporate environmental data on the habitats. Macrophyte primary
production was influenced by a combination of tolerance, morphology and
life habit traits; however tolerance traits contributed most of
variability in macrophyte primary production when all traits were analysed
jointly. This study also showed the existence of trait clustering as the
studied trait categories were not fully independent; strong interlinkages
between and within trait categories emerged. Our study suggests that
functional trait analysis captures different aspects of ecosystem
functioning and thereby enables assessing primary production of macrophyte
communities over geographically distinct areas without extensive taxonomic
and environmental data. This could result in a novel framework through
which a simplification of the general procedure of production estimations
and comparisons across environmental gradients can be achieved.