An increasing number of experiments has shown substantial variations in effects of multiple stressors on stream ecosystems. Therefore, an integration of mechanisms is required to capture such variations, starting at the individual level and subsequently upscaled to higher levels of biological organisation, considering biotic interactions and dispersal dynamics. Available modelling approaches are usually expanded from the concepts developed for chemical mixtures based on modes of toxic actions, while there are no specific approaches for other stressors, such as temperature increases, salinisation, and hydromorphological modifications. Such methods are mainly based on data fitting without consideration of underlying mechanisms. This project aims at interpreting effects of binary combinations of the above-mentioned stressors at the individual level in a mechanistic, i.e. process- and size-based, model for various organisms (microorganisms, microphytobenthos, parasites, invertebrates, and fish) by unravelling stressor-response causality. The causal chain from stressors to environmental variables and to biological responses will be delineated, contributing to a mechanistic simulation of stressor interactions. The model will be characterised and calibrated using available data as well as data generated from other projects of the CRC, before being validated using independent data sets.

The developed model will provide a mechanistic understanding of stressor interactions at the individual level, contribute to a better interpretation of stressor interactions at higher levels of biological organisation, and eventually improve capacity for predicting effects of multiple stressors. The model consists of two components: environmental variable modelling including interactions between stressors affecting environmental variables, and effect modelling including interactions between stressors or environmental variables affecting responses of organisms. Moreover, responses of organisms will be related to body size, facilitating extrapolation between organism groups in Phase 1, as well as extrapolation to community and ecosystem levels in Phases 2 and 3 of the CRC. The model will be adjusted in Phase 2 considering influence of biotic interactions (e.g. competition and predation) on the individual responses, and further validated in Phase 3 considering confounding factors under field conditions. As such, the project contributes to address Main Hypotheses 1 and 2 of the CRC and two factors of the Asymmetric Response Concept: interactions between stressors affecting environmental variables, and interactions between stressors or environmental variables affecting responses of organisms.

Luan Farias (University of Duisburg-Essen)

Delineating multiple stressor-response relationships at the individual level: A mechanistic modelling approach

The goal of this thesis is to model the causal chain of effects from multiple stressors to environmental variables to organisms in stream ecosystems. The model will be mechanistic and operates on the individual level. The model will simulate binary combinations of the stressors temperature increase, salinisation, and hydromorphological modifications. These stressors influence environmental variables like dissolved oxygen (DO), dissolved organic carbon (DOC) and electrical conductivity (EC) as well as organisms (microorganisms, microphytobenthos, parasites, invertebrates, and fish). The environmental variables also interact with each other and affect the organisms. The stressors can affect the organisms directly or indirectly through the environmental variables.

The organisms are classified by body size and environmental effects on them are calculated in relation to these size classes. Depending on the size we expect direct or indirect effects of the stressors to be more prevalent. The model will increase the understanding of stressor-response mechanisms and help predict responses of organisms in streams to multiple stressors. In further steps biotic interactions can be added to elevate the model from the individual level to the community level.

Contact: luan.farias@uni-due.de

First Supervisor: Dr. T. T. Yen Le (University of Duisburg-Essen, Aquatic Ecology)
Second Supervisor: Prof. Dr. Ralf Schäfer (University of Koblenz-Landau, Quantitative Landscape Ecology)
Mentor: Dr.-Ing. Daniel Teschlade (Ruhrverband)