DDG temporal change
We showed that the stability of the pattern depends on the DDG measure
(question 3.1). D(β,max) andD(γ,max) were quite variable measures over years,
while D(α,max), R(α,max),
R(β,max) and R(γ,max) are
comparatively stable measures. This may be related to the fact that
there is neither pair-wise correlation nor explaining model forD(β,max) and D(γ,max) .
Contrary to our expectations we see no general trend of increasing
species richness or decreasingDmax . (question 3.2). Although we
observe high variety in DDG temporal change between lakes, the DDG
temporal change for single lakes, especially forD(α,max) , is low and develops into different
directions for different lakes. Still, we see linear trends that are
consistent over time within lakes. These patterns suggest that global
change effects will be more complex than anticipated. In fact, climate
and land use change influence all the highly connected chemical and
physical gradients known to significantly affect DDG (Hossain et al.
2017). Thus, the following hypothesis can be set (Fig. 4): (1) As
temperatures rise, so do lake surface water temperatures as well
(O’Reilly et al. 2015). This seems to result in shallower epilimnion
(Kraemer et al. 2015) and generally shallowerDmax and a lower Rmax . (2)
Furthermore, rising temperature entail higher P content, as they promote
internal fertilization. But also extreme weather events combined with
enriched fertilization in agriculture can cause fertilization events
(Rose et al. 2016), which might result in shallower light depth
consequently in shallower DDG. (3) Browning, which is generally
increasing due to temperature induced decomposition rates and changes in
precipitation events (Sobek et al. 2007, Weyhenmeyer and Karlsson 2009,
Guarch-Ribot and Butturini 2016), leads to a shallowerDmax . (4) However, water management reduced the
external nutrient loading of European lakes enormously during the last
decades (Eigemann et al. 2016, Murphy et al. 2018). This trend is still
ongoing and might still lead towards lower nutrient contents and thus to
deeper Dmax . All these opposing environmental
trends make it hard to draw a general trend for multiple lakes for short
timespans. However, for long timespans it seems to be a race between
climate change impacts (Hypothesis 1-3 in Fig. 4) that might lead to a
shallower Dmax and thus generally less
macrophytes and water management impacts that might deepen theDmax via improved water quality (Hypothesis 4 in
Fig. 4).