Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.

Water quality modelling deals with multidisciplinary questions ranging from fundamental to applied. Addressing this broad range of questions requires multiple analysis techniques and therefore multiple frameworks. Through the recently developed database approach to modelling (DATM), it has become possible to run a model in multiple software frameworks without much overhead. Here we apply DATM to the ecosystem model for ditches PCDitch and its twin model for shallow lakes PCLake. Using DATM, we run these models in six frameworks (ACSL, DELWAQ, DUFLOW, GRIND for MATLAB, OSIRIS and R), and report on the possible model analyses with tools provided by each framework. We conclude that the dynamic link between frameworks and models resulting from DATM has the following main advantages: it allows one to use the framework one is familiar with for most model analyses and eases switching between frameworks for complementary model analyses, including the switch between a 0-D and 1-D to 3-D setting. Moreover, the strength of each framework - including runtime performance - can now be easily exploited. We envision that a community-based further development of the concept can contribute to the future development of water quality modelling, not only by addressing multidisciplinary questions but also by facilitating the exchange of models and process formulations within the community of water quality modellers.

Simulation modelling in ecology is a field that is becoming increasingly compartmentalized. Here we propose a Database Approach To Modelling (DATM) to create unity in dynamical ecosystem modelling with differential equations. In this approach the storage of ecological knowledge is independent of the language and platform in which the model will be run. To create an instance of the model, the information in the database is translated and augmented with the language and platform specifics. This process is automated so that a new instance can be created each time the database is updated. We describe the approach using the simple Lotka–Volterra model and the complex ecosystem model for shallow lakes PCLake, which we automatically implement in the frameworks OSIRIS, GRIND for MATLAB, ACSL, R, DUFLOW and DELWAQ. A clear advantage of working in a database is the overview it provides. The simplicity of the approach only adds to its elegance.

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: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based 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.

Possible effects of climate change on ecological functioning of shallow lakes, Lake Loenderveen as a case study The European Water Framework Directive (WFD) requires all inland and coastal waters to reach "good ecological status" by 2015. The good ecological status of shallow lakes can be characterised by clear water dominated by submerged vegetation. The ecological response of shallow lakes on nutrients largely depends on morphological and hydrological features, such as water depth, retention time, water level fluctuations, bottom type, fetch etc. These features determine the "critical nutrient load" of a lake. When the actual nutrient load of a lake is higher than the critical nutrient load, the ecological quality of this lake will deteriorate, resulting in a turbid state dominated by algae. Climate change might lead to changes in both environmental factors and ecosystem response. This certainly will have an effect on the ecological status. As an illustration the results of a multidiscipline study of a shallow peaty lake (Loenderveen) are presented, including hydrology, geochemistry and ecology. Ground- and surface water flows, nutrient dynamics and ecosystem functioning have been studied culminating in an application of the ecological model of the lake (PCLake). Future scenarios were implemented through changing precipitation, evaporation and temperature. Climate change will lead to higher nutrient loads and lower critical nutrient loads. As a consequence lakes shift easier from clear water to a turbid state.