Multiple interacting environmental drivers reduce the impact of solar UVR on primary productivity in Mediterranean lakes

The impact of extreme weather events exceeds those due to global-change drivers on coastal phytoplankton assemblages

Extreme wind and rainfall events have become more frequent phenomena, impacting coastal ecosystems by inducing increased mixing regimes in the upper mixed layers (UML) and reduced transparency (i.e. browning), hence affecting phytoplankton photosynthesis. In this study, five plankton assemblages from the South Atlantic Ocean, from a gradient of environmental variability and anthropogenic exposure, were subjected to simulated extreme weather events under a global change scenario (GCS) of increased temperature and nutrients and decreased pH, and compared to ambient conditions (Control). Using multiple linear regression (MLR) analysis we determined that evenness and the ratio of diatoms/ (flagellates + dinoflagellates) significantly explained the variations (81-91 %) of the photosynthesis efficiency (i.e. Pchla/ETRchla ratio) for each site under static conditions. Mixing speed and the optical depth (i.e. attenuation coefficient * depth, kdz), as single drivers, explained 40-76 % of the variability in the Pchla/ETRchla ratio, while GCS drivers <9 %. Overall, assemblages with high diversity and evenness were less vulnerable to extreme weather events under a GCS. Extreme weather events should be considered in global change studies and conservation/management plans as even at local/regional scales, they can exceed the predicted impacts of mean global climate change on coastal primary productivity.

Flexible Goal Programming for Supporting Lake Karla’s (Greece) Sustainable Operation

Sustainable management is a prerequisite for a lake to provide a range of ecosystem services. The prioritization of needs is a difficult task, especially when the needs are in conflict and threaten water security. Lake Karla, situated in the Thessaly plain, Greece, was decimated in 1957–1962; due to environmental impacts, it was later refilled as a multipurpose reservoir with high ecological significance. The research objective is to achieve a compromise with respect to both the economic benefits derived from agricultural water use and environmental protection based on the minimum intersection. For this purpose, first, new managerial practices are introduced. Second, the ideas are quantified based on the hydrological budget, and these are used as input for flexible (fuzzy) programming. Under hypotheses about the acceptable range, the (flexible) fuzzy programming is identical with the MINMAX goal programming model, although the weights are not used directly in the first case. An understandable compromise (the maximum economic benefit from irrigation areas and the minimization of water retention time) is achieved, and the values of the membership functions can be used to verify the solution. The proposed solution leads to a quantitative proposition, incorporating new findings from modeling the recent real operation of the reservoir.