Climate change has been suggested to lead to higher temperature and increased heterotrophy in aquatic systems. The aim of this study was to test how these two factors affect metazooplankton and food web efficiency (FWE was defined as metazooplankton production divided by basal production). We tested the following hypotheses: (1) that lower metazooplankton production and lower FWE would be found in a food web based on heterotrophic production (bacteria) relative to one based on autotrophic production (phytoplankton), since the former induces a larger number of trophic levels; (2) the metazooplankton in the heterotrophic food web would contain less essential fatty acids than those from the autotrophic food web; and (3) that higher temperature would lead to increased FWE. To test these hypotheses, a mesocosm experiment was established at two different temperatures (5 and 10A degrees C) with a dominance of either autotrophic (NP) or heterotrophic basal production (CNP). Metazooplankton production increased with temperature, but was not significantly affected by differences in basal production. However, increased heterotrophy did lead to decreased fatty acid content and lower individual weight in the zooplankton. FWE increased with autotrophy and temperature in the following order: 5CNP < 10CNP < 5NP < 10NP. Our results indicate that in the climate change scenario we considered, the temperature will have a positive effect on FWE, whereas the increase in heterotrophy will have a negative effect on FWE. Furthermore, the quality and individual weight of the metazooplankton will be reduced, with possible negative effects on higher trophic levels.

This study explores: (1) whether the abundance of macroinvertebrates differs between macrophytes differing in both morphological complexity and tolerance to nutrient enrichment; (2) whether the distribution of invertebrates between macrophytes is due to active habitat choice; and (3) whether invertebrates prefer structurally complex to simple macrophytes. Macroinvertebrate abundance was compared between two common soft-bottom plants in the Baltic Sea that are tolerant to eutrophication, Myriophyllum spicatum and Potamogeton pectinatus, and one common plant that is sensitive to eutrophication, Chara baltica. Both field sampling and habitat choice experiments were conducted. We recorded higher total macroinvertebrate abundance on the structurally complex M. spicatum than on the more simply structured P. pectinatus and C. baltica, but found no difference in macroinvertebrate abundance between P. pectinatus and C. baltica. In accordance with the field results, our experiment indicated that the crustacean Gammarus oceanicus actively chose M. spicatum over the other macrophytes. Besides, we found that G. oceanicus actively preferred complex to simply structured artificial plants, indicating that the animal distribution was at least partly driven by differences in morphological complexity between plant species. In contrast, the gastropod Theodoxus fluviatilis did not make an active habitat choice between the plants. Our findings suggest that human-induced changes in vegetation composition can affect the faunal community. Increased abundance of structurally complex macrophytes, for example, M. spicatum, can result in increased abundance of macroinvertebrates, particularly mobile arthropods that may actively choose a more structurally complex macrophyte.

Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5-10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.