Questions: Does a reduced nutrient load in open water increase species richness and the importance of regional and local site characteristics for species abundance and spatial distribution? Can we build lake-specific models of macrophyte abundance and distribution based on site characteristics in order to prepare a cost-efficient framework for future surveys?
Location: Lake Constance, 47°39′ N, 9°18′ E.
Methods: Generalized additive models (GAMs) were used to predict the potential distributions of eight species and overall species richness. Submersed macrophyte distribution in 1993 was compared with corresponding data from 1978, when eutrophication was at its maximum.
Results: Spatial predictions for eight species and overall species richness were relatively accurate and independent of water chemistry. Depth was confirmed as a main predictor of species distribution, while effective fetch distance was retained in many models. Mineralogical variables of sediment composition represent allogenic and autogenic sediment sources and their east-west gradient in Lake Constance corresponded to east-west gradients of species distribution and richness. GAMs appeared more efficient than generalized linear models (GLMs) for modelling species responses to environmental gradients.
Conclusions: Reduced trophic status increases species richness and the importance of regional and local site characteristics for species abundance and distribution. Our models represent a spatio-temporal framework for future lake monitoring purposes and allow the development of effective monitoring; this could be generalized for many ecosystem types and would be particularly efficient for large lakes such as Lake Constance.
Abbreviations: Corg = Organic carbon content; EFD = Effective fetch distance; GAM = Generalized Additive Model; GLM = Generalized Linear Model; GRASP = Generalized regression analyses and spatial predictions; MGS = Mean grain size; ROC = Receiving Operating Characteristic; ROCcv = Cross validated ROC; Rtot = Species richness.