An Integrated Multi-Disciplinary Approach for Studying Multiple Stressors in Freshwater Ecosystems: Daphnia as a Model Organism

The increased overexploitation of freshwater ecosystems and their extended watersheds often generates a cascade of anthropogenic stressors (e.g., acidification, eutrophication, metal contamination, Ca decline, changes in the physical environment, introduction of invasive species, over-harvesting of resources). The combined effect of these stressors is particularly difficult to study, requiring a coordinated multi-disciplinary effort and insights from various sub-disciplines of biology, including ecology, evolution, toxicology, and genetics. It also would benefit from a well-developed and broadly accepted model systems. The freshwater crustacean Daphnia is an excellent model organism for studying multiple stressors because it has been a chosen focus of study in all four of these fields. Daphnia is a widespread keystone species in most freshwater ecosystems, where it is routinely exposed to a multitude of anthropogenic and natural stressors. It has a fully sequenced genome, a well-understood life history and ecology, and a huge library of responses to toxicity. To make the case for its value as a model species, we consider the joint and separate effects of natural and three anthropogenic stressors-climatic change, calcium decline, and metal contaminants on daphniids. We propose that integrative approaches marrying various subfields of biology can advance our understanding of the combined effects of stressors. Such approaches can involve the measuring of multiple responses at several levels of biological organization from molecules to natural populations. For example, novel interdisciplinary approaches such as transcriptome profiling and mutation accumulation experiments can offer insights into how multiple stressors influence gene transcription and mutation rates across genomes, and, thus, help determine the causal mechanism between environmental stressors and population/community effects as well as long-term evolutionary patterns.