Wide-spread inconsistency in estimation of lake mixed depth impacts interpretation of limnological processes.

The mixed layer, or epilimnion, is a physical concept referring to an isothermal layer at the surface of a water body. This concept is ubiquitous within limnology, is fundamental to our understanding of chemical and ecological processes, and is an important metric for water body monitoring, assessment and management. Despite its importance as a metric, many different approaches to approximating mixed depth currently exist. Using data from field campaigns in a small meso-eutrophic lake in the UK in 2016 and 2017 we tested whether different definitions of mixed depth resulted in comparable estimates and whether variables other than temperature could be assumed to be mixed within the layer. Different methods resulted in very different estimates for the mixed depth and ecologically important variables were not necessarily homogenously spread through the epilimnion. Furthermore, calculation of simple ecologically relevant metrics based on mixed depth showed that these metrics were highly dependent on the definition of mixed depth used. The results demonstrate that an idealised concept of a well-defined fully mixed layer is not necessarily appropriate. The widespread use of multiple definitions for mixed depth impairs the comparability of different studies while associated uncertainty over the most appropriate definition limits the confirmability of studies utilising the mixed depths.

Strategies for monitoring and managing mass populations of toxic cyanobacteria in recreational waters: a multi-interdisciplinary approach.

Mass populations of toxin-producing cyanobacteria commonly develop in fresh-, brackish- and marine waters and effective strategies for monitoring and managing cyanobacterial health risks are required to safeguard animal and human health. A multi-interdisciplinary study, including two UK freshwaters with a history of toxic cyanobacterial blooms, was undertaken to explore different approaches for the identification, monitoring and management of potentially-toxic cyanobacteria and their associated risks. The results demonstrate that (i) cyanobacterial bloom occurrence can be predicted at a local- and national-scale using process-based and statistical models; (ii) cyanobacterial concentration and distribution in waterbodies can be monitored using remote sensing, but minimum detection limits need to be evaluated; (iii) cyanotoxins may be transferred to spray-irrigated root crops; and (iv) attitudes and perceptions towards risks influence the public's preferences and willingness-to-pay for cyanobacterial health risk reductions in recreational waters.

Adaptive forecasting of phytoplankton communities.

The global proliferation of harmful algal blooms poses an increasing threat to water resources, recreation and ecosystems. Predicting the occurrence of these blooms is therefore needed to assist water managers in making management decisions to mitigate their impact. Evaluation of the potential for forecasting of algal blooms using the phytoplankton community model PROTECH was undertaken in pseudo-real-time. This was achieved within a data assimilation scheme using the Ensemble Kalman Filter to allow uncertainties and model nonlinearities to be propagated to forecast outputs. Tests were made on two mesotrophic lakes in the English Lake District, which differ in depth and nutrient regime. Some forecasting success was shown for chlorophyll a, but not all forecasts were able to perform better than a persistence forecast. There was a general reduction in forecast skill with increasing forecasting period but forecasts for up to four or five days showed noticeably greater promise than those for longer periods. Associated forecasts of phytoplankton community structure were broadly consistent with observations but their translation to cyanobacteria forecasts was challenging owing to the interchangeability of simulated functional species.

Is the future blue-green? A review of the current model predictions of how climate change could affect pelagic freshwater cyanobacteria.

There is increasing evidence that recent changes in climate have had an effect on lake phytoplankton communities and it has been suggested that it is likely that Cyanobacteria will increase in relative abundance under the predicted future climate. However, testing such a qualitative prediction is challenging and usually requires some form of numerical computer model. Therefore, the lake modelling literature was reviewed for studies that examined the impact of climate change upon Cyanobacteria. These studies, taken collectively, generally show an increase in relative Cyanobacteria abundance with increasing water temperature, decreased flushing rate and increased nutrient loads. Furthermore, they suggest that whilst the direct effects of climate change on the lakes can change the timing of bloom events and Cyanobacteria abundance, the amount of phytoplankton biomass produced over a year is not enhanced directly by these changes. Also, warmer waters in the spring increased nutrient consumption by the phytoplankton community which in some lakes caused nitrogen limitation later in the year to the advantage of some nitrogen-fixing Cyanobacteria. Finally, it is also possible that an increase in Cyanobacteria dominance of the phytoplankton biomass will lead to poorer energy flow to higher trophic levels due to their relatively poor edibility for zooplankton.