Jan H. Janse

Challenges and Opportunities for Integrating Lake Ecosystem Modelling Approaches

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.

A model of nutrient dynamics in shallow lakes in relation to multiple stable states

There is increasing evidence that, within a range of nutrientloadings, shallow lakes may have two alternative stablestates. One is dominated by phytoplankton and the other one bysubmerged macrophytes as the main primary producer. Thequestion arises at what level of nutrient loading a transitionmay occur between the two states. This question was addressedby means of the integrated lake model PCLake. The modeldescribes the competition between phytoplankton andmacrophytes, within the framework of closed nutrient cycles inthe lake system, including the upper sediment. Top-downeffects via the food web were regarded as well. The model wasrun for a hypothetical shallow lake, representative for thesituation in The Netherlands. Long-term simulations werecarried out for a realistic range of nutrient loadings andstarting from different initial conditions. The results showeda highly non-linear response, which also showed hysteresis:the loading level at which a transition occurs turned out tobe dependent on the initial conditions. The results werecompared with empirically derived chlorophyll a tophosphorus relations. Factors influencing the ’criticalnutrient level‘ were the lake dimensions and the netsedimentation rate. The model was also used to evaluate therole of food web management in lake restoration. The resultssuggest that a long-term effect of additional management ispossible only if combined with a decrease in nutrient loading.

A freshwater food web model for the combined effects of nutrients and insecticide stress and subsequent recovery

A microcosm experiment that addressed the interaction between eutrophication processes and contaminants was analyzed using a food web model. Both direct and indirect effects of nutrient additions and a single insecticide application (chlorpyrifos) on biomass dynamics and recovery of functional groups were modeled. Direct toxicant effects on sensitive arthropods could be predicted reasonably well using concentration-response relationships from the laboratory with representative species. Model predictions showed that nutrient additions alone caused only small effects on toxicant fate and effects probably due to the relatively high dissipation rate of chlorpyrifos. Enhancement of eutrophication effects by the insecticide was relatively small and seemed to be additive. The recovery of some affected functional groups was hampered in the indoor microcosms due to their isolation from outdoor seed populations. Introducing recolonization scenarios in the model simulated dose-dependent recovery. Recolonization increased the recovering rate after exposure to the pesticide. Modeling can extend the use of microcosms as a link between laboratory and field as this allows the prediction of effects and recovery of ecosystems for concentrations that have not been experimentally tested.

A community-based framework for aquatic ecosystem models

Here, we communicate a point of departure in the development of aquatic ecosystem models, namely a new community-based framework, which supports an enhanced and transparent union between the collective expertise that exists in the communities of traditional ecologists and model developers. Through a literature survey, we document the growing importance of numerical aquatic ecosystem models while also noting the difficulties, up until now, of the aquatic scientific community to make significant advances in these models during the past two decades. Through a common forum for aquatic ecosystem modellers we aim to (i) advance collaboration within the aquatic ecosystem modelling community, (ii) enable increased use of models for research, policy and ecosystem-based management, (iii) facilitate a collective framework using common (standardised) code to ensure that model development is incremental, (iv) increase the transparency of model structure, assumptions and techniques, (v) achieve a greater understanding of aquatic ecosystem functioning, (vi) increase the reliability of predictions by aquatic ecosystem models, (vii) stimulate model inter-comparisons including differing model approaches, and (viii) avoid ‘re-inventing the wheel’, thus accelerating improvements to aquatic ecosystem models. We intend to achieve this as a community that fosters interactions amongst ecologists and model developers. Further, we outline scientific topics recently articulated by the scientific community, which lend themselves well to being addressed by integrative modelling approaches and serve to motivate the progress and implementation of an open source model framework.

Drivers of Wetland Conversion: a Global Meta-Analysis

Meta-analysis of case studies has become an important tool for synthesizing case study findings in land change. Meta-analyses of deforestation, urbanization, desertification and change in shifting cultivation systems have been published. This present study adds to this literature, with an analysis of the proximate causes and underlying forces of wetland conversion at a global scale using two complementary approaches of systematic review. Firstly, a meta-analysis of 105 case-study papers describing wetland conversion was performed, showing that different combinations of multiple-factor proximate causes, and underlying forces, drive wetland conversion. Agricultural development has been the main proximate cause of wetland conversion, and economic growth and population density are the most frequently identified underlying forces. Secondly, to add a more quantitative component to the study, a logistic meta-regression analysis was performed to estimate the likelihood of wetland conversion worldwide, using globally-consistent biophysical and socioeconomic location factor maps. Significant factors explaining wetland conversion, in order of importance, are market influence, total wetland area (lower conversion probability), mean annual temperature and cropland or built-up area. The regression analyses results support the outcomes of the meta-analysis of the processes of conversion mentioned in the individual case studies. In other meta-analyses of land change, similar factors (e.g., agricultural development, population growth, market/economic factors) are also identified as important causes of various types of land change (e.g., deforestation, desertification). Meta-analysis helps to identify commonalities across the various local case studies and identify which variables may lead to individual cases to behave differently. The meta-regression provides maps indicating the likelihood of wetland conversion worldwide based on the location factors that have determined historic conversions.

Restoration and resilience to recovery of the Lake Loosdrecht ecosystem in relation to its phosphorus flow

A reduction in external phosphorus loading since 1984 to Loosdrecht lakes system by the dephosphorization of the inlet water, yielded only minor effects in Lake Loosdrecht. This reduction measure turned out to have decreased the loading only by a factor of two. A conceptual model was constructed based on laboratory measurements to describe phosphorus flow in the lake ecosystem for the summer of 1987. The role of zooplankton and fish was more important in phosphorus recycling than diffusion at the sediment-water interface. The input and output of phosphorus of the lake were at equilibrium and therefore, further reduction in external loading was needed for recovery. The results of the conceptual model agreed well with the output of the mathematical model PCLOOS. Additional measures such as dredging, flushing, chemomanipulation, or biomanipulation would be ineffective at the present level of external loading. Only a significant further reduction in external input will restore Lake Loosdrechts water quality over a long period of time.

Potential effects of climate change and eutrophication on a large subtropical shallow lake

In many aquatic ecosystems, increased nutrient loading has caused eutrophication, which is reflected in the trophic structure of the ecosystem. In Lake Mangueira, a large shallow subtropical lake in Brazil, nutrient loading has also increased, but it is still unclear what the effects of this increase will be and how this relates to climate change. To evaluate the effects of increased nutrient loadings in such large lake one would need to integrate hydrological and ecological processes into one model, an approach that has rarely been used before. Here, we apply different versions of a complex 3D ecological model, called IPH-TRIM3D-PCLake, which describes the integrated hydrodynamic, water-quality, and biological processes in the lake. First, the nutrient loadings from the watershed were estimated using a separate hydrological water quality model of the watershed based on field data. Second, we calibrated the 3D ecological model for a 6-year monitoring period in the lake using a simplified non-spatial version of the model. Finally, the calibrated ecological model was applied to evaluate the spatial explicit effects of different scenarios of land use, water pumping for irrigation, and climate change. On short term (1.5 year), the system seemed to be rather resilient, probably because of the lake size related to its high inertia. Our simulations indicated warming can increase water transparency in Lake Mangueira which may be related to two factors: (a) the current meso-oligotrophic state of the lake which may easily lead to nutrient limitation; and (b) submerged macrophytes grow during the whole season. The combined effect of climate change and increased nutrient loading, less strong than increased nutrient loading alone. The model can only be used for qualitative predictions of the effect of management scenarios, such as maintenance of water levels in the dry season, and water-pumping rules for irrigation in order to maintain the ecosystem structure and functions in the future under additional stress caused by increased use or climate change.

A model of ditch vegetation in relation to eutrophication

A functional model of a ditch ecosystem has been developed, aimed at describing the relation between nutrient input and water quality and dominant vegetation in drainage ditches. Its aim is the derivation of the ‘critical nutrient loading’ for a shift from submerged vegetation to duckweed dominance. The model, called PCDitch , describes the competition between several functional groups of macrophytes, as well as algae. The macrophyte groups were defined according to the layer(s) in which they grow: submerged, floating or emergent, rooted or non-rooted. The model also includes the cycling of nutrients within the water, the sediment top layer and the vegetation. The model has been applied to the data of 8 experimental ditches located at Renkum (The Netherlands), which received different levels of nutrient loading during 4 years. The controls and the low- and medium-loaded ditches remained dominated by submerged plants, while in the high-loaded ones a dense cover of duckweed developed. In the sand ditches, submerged biomasses were lower than in the respective clay ditches. An optimization study has been performed for a number of sensitive parameters, minimizing the total sum of squared differences between simulated and measured values for all ditches, resulting in a set of parameter values that gives the best overall fit. The parameters included the maximum growth rates, the minimum phosphorus contents and the overwintering fraction of the plant groups. The model simulations by PCDitch were grossly comparable to the field observations, with duckweed in the high-loaded ditches and submerged plants in the other ones. The fit for algae and charophytes remained poor. Further calibration as well as testing the model in field situations are recommended to improve the models predictive value.

Advancing projections of phytoplankton responses to climate change through ensemble modelling

A global trend of increasing health hazards associated with proliferation of toxin-producing cyanobacteria makes the ability to project phytoplankton dynamics of paramount importance. Whilst ensemble (multi-)modelling approaches have been used for a number of years to improve the robustness of weather forecasts this approach has until now never been adopted for ecosystem modelling. We show that the average simulated phytoplankton biomass derived from three different aquatic ecosystem models is generally superior to any of the three individual models in describing observed phytoplankton biomass in a typical temperate lake ecosystem, and we simulate a series of climate change projections. While this is the first multi-model ensemble approach applied for some of the most complex aquatic ecosystem models available, we consider it sets a precedent for what will become commonplace methodology in the future, as it enables increased robustness of model projections, and scenario uncertainty estimation due to differences in model structures.

A model study on the stability of the macrophyte-dominated state as affected by biological factors.

Abstract The transition of shallow lake ecosystems between the clear-water, macrophyte-dominated state and the turbid state dominated by phytoplankton depends on both physico–chemical and biological factors. In this study, the impact of some of these interactions on the stability of the macrophyte-dominated state of a lake are studied by means of the integrated eutrophication model PCLake . The model describes phytoplankton, macrophytes and a simplified food web, within the framework of closed nutrient cycles. The aim of the study is to evaluate the impact of herbivory by birds and fish on the transition from clear to turbid state, including the influence of variability in other biological parameters. The model was applied to the data of a small, biomanipulated lake, dominated by macrophytes, showing signs of a transition back to the turbid state. Simulations were carried out for the lake as well as for an experimental situation where herbivory was impeded. A parameter variation study was performed for 10 parameters, affecting the zooplankton, fish and macrophytes behaviour, to determine the sensitivities and the model uncertainty. The model reproduced adequately the transition of the lake from phytoplankton dominance before the biomanipulation, via dominance of rooted perennial plants in the first years after it, to a state characterized by turion-forming plants in early summer and phytoplankton in autumn. It is shown that the probability of the transition back to phytoplankton dominance is mainly enhanced by herbivory by birds. This caused a shift towards inedible plant species with a shorter natural growing season, allowing the return of a phytoplankton bloom in autumn. If herbivory was impeded, this shift did not occur and phytoplankton remained low due to nitrogen limitation. The model results were quite sensitive to the zooplankton filtering rate and, in the presence of herbivory only, to the macrophytes growth parameters. The impact of the fish parameters showed to be less important. The model may be used to evaluate the relative importance of different assumptions or factors in the success of biomanipulation measures in lakes.