Predicting the abundance of European stream macroinvertebrates using biological attributes

Abstract

Is there a relationship between the abundance of organisms and particular biological attributes? To assess this old, yet still acutely debated key question of ecology, we have used large databases on 312 stream macroinvertebrate genera (from 27 orders) that describe (1) invertebrate abundance at 527 least human-impacted European stream sites, (2) 11 biological traits (size, life-history, food, among others) described in 61 biological trait categories (BTCs; e.g. small, intermediate or large size) and (3) 14 attributes indicating specialization (AISs; e.g. species richness, size and food diversity). We applied interactive procedures to obtain models (for BTCs, AISs and a mixture of both descriptions) explaining as much as possible of the abundance variability of the genera with the lowest number of significant and ecologically meaningful attributes and assessed the predictive power of these models (in crosswise validations) by comparing predicted and observed abundances. Mean European invertebrate abundance increased with BTC affinities favouring viability in stream systems (e.g. attachment to the stream bottom to resist the flow, aquatic passive dispersal with the flow, exploitation of abundant food sources) and decreased with BTC affinities disfavouring this viability (e.g. drag force increase associated with larger body size, flow exposure associated with aerial respiration). Abundance consistently decreased with specialization of the genera (e.g. low species richness, oddity of their overall BTC profile from an "average" European genus). The model including a mixture of a few BTCs and AISs had the greatest predictive power: it predicted 35% of the observed abundance (ln-transformed) variability of the genera; these predictions were marginally affected by taxonomy (using orders as categorical variables). We conclude that a better appreciation of the influence of the examined taxonomic diversity, number and type of biological attributes, environmental system and spatial scale could enable abundance predictions using different sets of biological attributes for different taxonomic groups and systems.

Can biological invertebrate traits resolve effects of multiple stressors on running water ecosystems?

“…low species richness, oddity of their overall trait profile from an 'average' European genus). Using a subset of these traits, it was possible to predict (in crosswise validations) 35% of the observed mean European (ln-transformed) abundance variability of 312 invertebrate genera (having c. 2200 lotic species in Europe) of 27 orders, or 51% of the abundance variability of 121 genera (having c. 1200 lotic species in Europe) of the may-, stone-and caddisflies (Statzner et al, 2008a).…”

Diversity of macrobenthos in lowland streams: ecological determinants and taxonomic specificity

“…Unfortunately, those groups, more difficult than others to identify on the species level, are at once extremely rich in species and very important in terms of trophic function, e.g., larval Diptera. Therefore, conclusions from such studies about the reaction of diversity of macrobenthos to changes in environmental parameters seem to be controversial, when the most diverse taxonomic groups are identified on the level of genus or tribe (Statzner et al 2008). The idea that the groups richest in species should be excluded from the biomonitoring protocols to make the procedure easier has also been formulated (Rabeni & Wang 2001).…”

“…The lack of researchers' consensus for the former, defined by Jones (2008) as the level of taxonomic details with which organisms must be identified, results in problems with comparing the datasets from different environments. The latter results in preparing and publishing datasets where higher taxa are identified on unequal level (e.g., Angradi 1996;Adams et al 2005;Statzner et al 2008). Both procedures make the potential meta-analyses extremely difficult.…”

The ecological restoration of large rivers needs science‐based, predictive tools meeting public expectations: an overview of the Rhône project

“…Trait predictions were facilitated by the existence of a database on biological species traits compiled by the RRT for a previous Special Issue (Statzner et al, 1994). attachment abilities : Statzner, Bonada & Dol edec, 2008a) after flow increase in the main channel. attachment abilities : Statzner, Bonada & Dol edec, 2008a) after flow increase in the main channel.…”