Modeling competitive interactions between floating and submerged macrophytes in shallow lakes using field data

Abstract Shallow lakes are ecosystems up to 3 m’ depth and provide a number of ecosystem services such as the habitat of migratory birds, but are also vulnerable to environmental changes such as temperature warming. In shallow lakes, floating macrophytes have greater exposure to the atmosphere than submerged macrophytes, therefore, under global change (increased atmospheric CO 2 and temperatures), floating macrophytes have an advantage and can be more competitive than submerged macrophytes. Since a universal model that is easily tractable and more integrated with data was not available, I developed a model of submerged macrophyte interacting with floating (SMIF), which is a modification of an existing model Scheffer et al. (2003) and incorporation of sub-models (Driever et al. 2005; Peeters et al. 2013). My main goal is to use the developed model to gain insights into the temporal growth dynamics of submerged and floating macrophytes. First, I calibrated the developed model using data at a site in Netherlands. Then I examined the sensitivity of the model to high temperature and low nitrogen levels. The modeling results showed that (1) the model is capable of adequately predicting temporal patterns of biomass for floating and submerged macrophytes and (2) the maximum growth and turnover rates are the most sensitive parameters for biomass of floating and submerged macrophyte. The developed model agreed well with the experimental data for various geographical regions—this indicates that the model can capture species differences. SMIF can be incorporated into land systems models that are often used to examine how climate affects lake ecosystems.