A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: superindividual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

Meromictic lakes located in landlocked steppes of central Asia (~2500 km inland) have unique geophysiochemical characteristics compared to other meromictic lakes. To characterize their bacteria and elucidate relationships between those bacteria and surrounding environments, water samples were collected from three saline meromictic lakes (Lakes Shira, Shunet and Oigon) in the border between Siberia and the West Mongolia, near the center of Asia. Based on in-depth tag pyrosequencing, bacterial communities were highly variable and dissimilar among lakes and between oxic and anoxic layers within individual lakes. Proteobacteria, Bacteroidetes, Cyanobacteria, Actinobacteria and Firmicutes were the most abundant phyla, whereas three genera of purple sulfur bacteria (a novel genus, Thiocapsa and Halochromatium) were predominant bacterial components in the anoxic layer of Lake Shira (~20.6% of relative abundance), Lake Shunet (~27.1%) and Lake Oigon (~9.25%), respectively. However, few known green sulfur bacteria were detected. Notably, 3.94% of all sequencing reads were classified into 19 candidate divisions, which was especially high (23.12%) in the anoxic layer of Lake Shunet. Furthermore, several hydro-parameters (temperature, pH, dissolved oxygen, H2S and salinity) were associated (P< 0.05) with variations in dominant bacterial groups. In conclusion, based on highly variable bacterial composition in water layers or lakes, we inferred that the meromictic ecosystem was characterized by high diversity and heterogenous niches.

The year-to-year variations of vertical distribution and biomass of anoxic phototrophic bacteria were studied during ice periods