Beschreibung

• We aim to improve our understanding of the extremely important but severely understudied feedback loop of biodiversity-related flexibility and ecological systems, which enables adjustment to altered abiotic and biotic conditions. Depending on the different facets of biodiversity (e.g., genetic, phenotypic and species diversity), individuals, populations and communities possess an inherent flexibility, which allows them to adjust to ambient conditions improving their fitness. This influences their dynamics and consequently those of the entire food web. For example, enhanced grazing may lead to a higher proportion of less edible algae. This, in turn, dampens the reduction of algal biomass, which likely will have a feedback on the biomass and community composition of herbivores, e.g., the share of herbivorous species able to exploit less edible algae may increase. As a result, the advantage of less edible algae compared to edible ones is reduced, which promotes the coexistence of different algal types and hence biodiversity. The Priority Programme moves away from the classical static species-based approach where rigid properties are assigned to each organism or species independent of ambient conditions, to an innovative, flexible, trait-based approach. It considers functional traits, which are measureable properties (e.g., edibility of prey, selectivity of consumers) that may change over time depending on the prevailing conditions. We want a mutually stimulating interplay between experimental approaches, field measurements and mathematical modelling using mostly plankton and biofilms. These microbial food webs comprise multiple trophic levels with internal feedbacks and their small size and short generation times enables measuring and manipulating trait variations and estimating the major trade-off(s) among traits. Population dynamics can be quantified for many generations, which reveals the effect of eco-evolutionary feedbacks within feasible time scales. We want to broaden our very limited quantitative knowledge and predictive power on how biodiversity affects the type of ecological dynamics (e.g., static or oscillating) and responses to environmental changes. This will likely call for a profound reconsideration of classical "well-established" theoretical concepts and will enable us to identify and experimentally test mechanisms maintaining biodiversity that can then be implemented in (applied, forecasting) models to improve their validity.