Understanding patterns of species covariation using a trait based approach with field data and models

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Our goal is to understand how functional diversity impacts the stability of lake ecosystem functions such as plankton biomass and primary production. The stability is influenced by the degree of covariation among component species which may or may not be related to their functional similarity. We will adopt a trait based approach linking species and function mechanistically and use it to quantify functional diversity through time. We aim to unmask how various ecological processes (abiotic environmental forcing, competition, and grazing), in isolation and in concert, impact (1) pair-wise species covariation, (2) the relationship between species covariation and functional similarity (difference), and (3) the temporal dynamics in trait variation, and to clarify how this translates into dynamics of ecosystem function. To accomplish this goal we will combine an in-depth data analysis with advanced tools for time series analysis and simulation-based modelling using freshwater phyto- and zooplankton (ciliates, rotifers, cladocerans, copepods) as model systems for which long-term high frequency observations are available (e.g. Lake Constance). We propose to develop new theory to explain how the diversity of functional traits exhibited by species impacts their covariation patterns. This is of importance for both, conservation and ecosystem management.