Building functional groups of marine benthic macroinvertebrates on the basis of general community assembly mechanisms

Abstract

WOS:000394716200001International audienceThe accurate reproduction of the spatial and temporal dynamics of marine benthic biodiversity requires the development of mechanistic models, based on the processes that shape macroinvertebrate communities. The modelled entities should, accordingly, be able to adequately represent the many functional roles that are performed by benthic organisms. With this goal in mind, we applied the emergent group hypothesis (EGH), which assumes functional equivalence within and functional divergence between groups of species. The first step of the grouping involved the selection of 14 biological traits that describe the role of benthic macroinvertebrates in 7 important community assembly mechanisms. A matrix of trait values for the 240 species that occurred in the Rance estuary (Brittany, France) in 1995 formed the basis for a hierarchical classification that generated 20 functional groups, each with its own trait values. The functional groups were first evaluated based on their ability to represent observed patterns of biodiversity. The two main assumptions of the EGH were then tested, by assessing the preservation of niche attributes among the groups and the neutrality of functional differences within them. The generally positive results give us confidence in the ability of the grouping to recreate functional diversity in the Rance estuary. A first look at the emergent groups provides insights into the potential role of community assembly mechanisms in shaping biodiversity patterns. Our next steps include the derivation of general rules of interaction and their incorporation, along with the functional groups, into mechanistic models of benthic biodiversity

Individual-based simulation of the spatial and temporal dynamics of macroinvertebrate functional groups provides insights into benthic community assembly mechanisms

“…These groups were formed out of the 240 benthic macroinvertebrate species that were observed in the Rance estuary in 1995 ( Desroy, 1998 ; for a list of species and their taxonomy, see section S1 in the Supplemental Material ). The grouping was based on 14 biological traits describing initially the species’, and ultimately the groups’, role in a set of general community assembly mechanisms ( Alexandridis et al, 2017a ). The acceptable level of ecological aggregation was defined through evaluation of different grouping levels against the expectations of the emergent group hypothesis, i.e., functional differences among the groups should preserve the species’ niche attributes, while functional differences within them should be neutral ( Hérault, 2007 ).…”

“… Note: Group names starting with ‘FG’ and ‘FGP’ correspond to algae/detritus feeders and predators/scavengers, respectively for details, see Alexandridis et al (2017a) . …”

“…Our objective is to develop an IBM of complete communities of marine benthic macroinvertebrates, explicitly representing the mechanisms that drive their spatial and temporal dynamics. To this end, we adapted the framework of Boulangeat et al (2012) , Boulangeat, Georges & Thuiller (2014) to marine benthos: we used available biological traits as proxies for the role of benthic species in general community assembly mechanisms, aiming to build groups with distinct functional roles through a systematic and testable procedure ( Alexandridis et al, 2017a ); we then employed well-established ecological theory and expert knowledge to derive rules of interaction among the functional groups and their resources ( Alexandridis et al, 2017b ). The use of proxy traits and first principles led to a preliminary semi-quantitative model parameterization, which was largely based on educated guesses.…”

Qualitative modelling of functional relationships in marine benthic communities

“…this framework to the benthic macroinvertebrate communities of the Rance estuary (Brittany, France) can provide the functional components for a mechanistic 102 representation of the system (Alexandridis et al, 2017). Here we implement these 103 components in a demonstration of a systematic procedure for the assignment of 104 functional relationships between them.…”

“…Qualitative modelling can, 634 therefore, direct the initial steps of more quantitative approaches, before investment 635 in model development has rendered structural changes too costly. We plan to use 636 this property to inform the structure of dynamic and spatially explicit trait-based 637 models of marine benthic communities in the Rance estuary (Alexandridis, 2017). .…”