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The importance of biotic interactions for the prediction of macroinvertebrate communities under multiple stressors
Author(s) -
Schuwirth Nele,
Dietzel Anne,
Reichert Peter
Publication year - 2016
Publication title -
functional ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.272
H-Index - 154
eISSN - 1365-2435
pISSN - 0269-8463
DOI - 10.1111/1365-2435.12605
Subject(s) - biological dispersal , ecology , taxon , biology , habitat , invertebrate , trait , community , population , demography , sociology , computer science , programming language
Summary The community assembly of macroinvertebrates in streams depends on the regional taxon pool, dispersal limitations, local habitat conditions and biotic interactions. By integrating existing knowledge about these processes from theoretical ecology in a mechanistic model, we can test our mechanistic understanding and disentangle multiple stressor effects on community assembly. To assess to which degree we can predict the community composition of macroinvertebrates, we integrated these processes in the mechanistic food web model Streambugs and tested it on 36 sites in the Glatt catchment on the Swiss plateau. The model predicts the observation probability of taxa from a regional taxon pool at each site taking into account uncertain knowledge on parameters, environmental conditions at the sites and sampling errors. We use allometric scaling according to the metabolic theory of ecology, ecological stoichiometry and autecological data from trait databases that include the current knowledge on habitat requirements of the different taxa to parameterize their growth, respiration and death. Without any calibration, for the majority of taxa at the 36 sites, the difference between the observed and predicted relative frequency of occurrence is <50% when taking prior parameter uncertainty and the uncertainty of environmental conditions into account (79% compared to 61% for the random model). By calibrating taxon‐specific modification factors for the growth rate, we can increase the model compliance with data. Analysing the influence of different ecological traits and their corresponding environmental influence factors reveals that feeding types and sensitivity to organic toxicants contribute most to the predictive capabilities of the model in this catchment. The influence of temperature stress and oxygen depletion due to pollution with organic matter on the community composition is negligible. These results confirm our expectations regarding the most important water quality issues of streams on the Swiss plateau. Current velocity plays an intermediate role in this model application. The contribution of the feeding types to model performance highlights the importance of taking biotic interactions (competition for food sources and predator–prey interactions) into account to predict the coexistence of taxa. Better knowledge of the actual feeding links in the food web (e.g. from gut content or stable isotope data) that are currently inferred from feeding types, body size and food availability could further improve this approach.