Empirical and dynamical models to predict the cover, biomass and production of macrophytes in lakes

Macrophytes play several important roles in lake ecosystems, e.g. proving shelter for small fish, binding nutrients and influencing secondary production by creating habitats for bacteria, benthic algae and zooplankton. However, the quantitative role of macrophytes in lakes is poorly known because few general, validated models yielding high predictive power for macrophyte production, cover and biomass have been presented. There are probably many reasons for this, e.g. related to the costs and efforts required to obtain relevant data. This work is based on a new database established by us from published sources. Many of the lakes included in this study are situated in the former Soviet Union. They were investigated during the Soviet period and those results have been largely unknown in the West. With this new database, we have presented empirical models for macrophyte cover and production yielding predictions close to the theoretical maximum values, as determined by the uncertainty in the empirical data. Using data from 35 lakes covering a wide domain in lake characteristics, we have ranked the factors influencing macrophyte cover and demonstrated that the ratio Secchi depth to mean depth can statistically explain about 40% of the variability among these lakes in macrophyte cover. Other important factors are latitude (related to lake temperature), maximum depth and area of the lake shallower than 1 m. A new regression model based on these four factors can statistically explain 82% of the variation in macrophyte cover among these lakes. We have also presented a dynamic model for macrophyte production and biomass and several critical tests of that model. The dynamic model gives better predictions and a more general structure then the empirical model. We have given algorithms for: (1) the macrophyte production rate; (2) the elimination rate (related to the macrophyte turnover time); (3) the rate of macrophyte consumption by animals; and (4) the rate of macrophyte erosion. Our results indicate that macrophyte production is highly dependent on latitude and temperature, morphometry and sediment character, as well as water clarity, and less dependent on nutrient concentration. Qualitatively, this has been known or suggested before, but this work gives new quantitative support to such conclusions and also a practically useful model for predictions of macrophyte production and biomass.