The importance of biotic interactions for the prediction of macroinvertebrate communities under multiple stressors

Abstract

Summary1. 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. 2. 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. 3. 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. 4. 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. 5. 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. 6. 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.

Ecological Models to Infer the Quantitative Relationship between Land Use and the Aquatic Macroinvertebrate Community

“…Examples for surface water are modelling of discharges from a wastewater treatment plant, industries, and storm water; agricultural/urban runoff; and a food chain [131]. Paillex et al [132] and Schuwirth et al [49] showed the use of such mechanistic models in ecological water quality studies. Mechanistic models allowed them to understand the mechanism behind the presence of taxa based on a combination of traits and environmental conditions [49,132].…”

“…Paillex et al [132] and Schuwirth et al [49] showed the use of such mechanistic models in ecological water quality studies. Mechanistic models allowed them to understand the mechanism behind the presence of taxa based on a combination of traits and environmental conditions [49,132]. Nevertheless, these mechanistic models have disadvantages.…”

“…Besides the required long process in building such a mathematical model, there is no guarantee that the mechanistic explanation of the model is correct [131]. Especially in ecological studies, the available trait information that is necessary in a mathematical model might not be complete, and there is a possibility that an important variable required to understand the system is missing [49,132]. With the complexities and uncertainties of aquatic ecosystems, it is not surprising that this technique is not as popular as descriptive and predictive models.…”

Biotic and abiotic factors investigated in two Drosophila species – evidence of both negative and positive effects of interactions on performance

“…Indeed, such interactions can be more important than abiotic habitat requirements when predicting community assemblies6, highlighting the importance of integrating interactions in ecological prediction models. Environmental factors may also interact with the genotype of individuals and the genetic constitution of populations.…”

“…This may result in underestimating the effect of multiple environmental factors on population persistency and the stability of communities4, a risk exemplified by the combination of thermal extremes and drought stress resulting from climate change10. The predictability and generalizability of responses to multiple environmental factors should be incorporated in general global climate change models11, and in ecological risk assessments212 for increased accuracy and prediction power of community assembly modelling6.…”