Dennis Trolle

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.

Predicting the effects of climate change on trophic status of three morphologically varying lakes

To quantify the effects of a future climate on three morphologically different lakes that varied in trophic status from oligo-mesotrophic to highly eutrophic, we applied the one-dimensional lake ecosystem model DYRESM-CAEDYM to oligo-mesotrophic Lake Okareka, eutrophic Lake Rotoehu, both in the temperate Bay of Plenty region, and highly eutrophic Lake Ellesmere, in the temperate Canterbury region, New Zealand. All three models were calibrated for a three-year period and validated for a separate two-year period. The model simulations generally showed good agreement with observed data for water column temperature, dissolved oxygen (DO), total phosphorus (TP), total nitrogen (TN) and chlorophyll a (Chl a) concentrations. To represent a possible future climate at the end of this century, mean annual changes in air temperature by 2100, derived from the IPCC A2 scenario downscaled for these lake regions, were added to the daily baseline temperatures for years 2002-2007. Lake model simulations using this future climate scenario indicate differential increases in eutrophication in all three lakes, especially during summer months. The predicted effects on annual mean surface water concentrations of TP, TN and Chl a will be equivalent to the effects of increasing external TN and TP loading by 25-50%. Simulations for the polymictic, eutrophic Lake Rotoehu further indicate that cyanophytes will be more abundant in the future climate, increasing by >15% in their contribution to annual mean Chl a. Therefore, future climate effects should be taken into account in the long-term planning and implementation of lake management as strategies may need to be refined and adapted to preserve or improve the present-day lake water quality.

Biomanipulation as a Restoration Tool to Combat Eutrophication: Recent Advances and Future Challenges

Eutrophication resulting from high nutrient loading has been the paramount environmental problem for lakes world-wide for the past four decades. Efforts are being made in many parts of the world to reduce external nutrient loading via improved wastewater treatment or diversion of nutrient-rich inflows. However, even after a reduction of the external phosphorus loading, the effects obtained may be unsatisfactory. This may reflect an insufficient reduction in the external nutrient loading to effectively limit phytoplankton growth. However, the lack of success may also be due to chemical or biological within-lake inertia preventing or delaying improvements. To overcome the resilience and thereby reinforce recovery, a number of physico-chemical and biological restoration methods have been developed. In this chapter, we describe recent developments of biological restoration methods related to eutrophication, their short-term and long-term effects, and discuss the possibility of using combined physico-chemical and biological methods to improve the long-term stability of restoration and to reduce restoration costs. As comprehensive reviews of the effect of fish manipulation in cold temperate lakes are numerous, for these waterbodies, we highlight recent results, including effects on biodiversity and metabolism, and present new approaches of biomanipulation. Our particular focus is, however, directed at biomanipulation in warm lakes and on combined treatments which are far less well described in the literature.

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.

A Global Lake Ecological Observatory Network (GLEON) for synthesising high–frequency sensor data for validation of deterministic ecological models

Abstract A Global Lake Ecological Observatory Network (GLEON; www.gleon.org) has formed to provide a coordinated response to the need for scientific understanding of lake processes, utilising technological advances available from autonomous sensors. The organisation embraces a grassroots approach to engage researchers from varying disciplines, sites spanning geographic and ecological gradients, and novel sensor and cyberinfrastructure to synthesise high-frequency lake data at scales ranging from local to global. The high-frequency data provide a platform to rigorously validate process-based ecological models because model simulation time steps are better aligned with sensor measurements than with lower-frequency, manual samples. Two case studies from Trout Bog, Wisconsin, USA, and Lake Rotoehu, North Island, New Zealand, are presented to demonstrate that in the past, ecological model outputs (e.g., temperature, chlorophyll) have been relatively poorly validated based on a limited number of directly comparable measurements, both in time and space. The case studies demonstrate some of the difficulties of mapping sensor measurements directly to model state variable outputs as well as the opportunities to use deviations between sensor measurements and model simulations to better inform process understanding. Well-validated ecological models provide a mechanism to extrapolate high-frequency sensor data in space and time, thereby potentially creating a fully 3-dimensional simulation of key variables of interest.

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.

Sediment and nutrient accumulation rates in sediments of twelve New Zealand lakes: influence of lake morphology, catchment characteristics and trophic state

Intact sediment cores were collected from the deepest basins of 12 lakes in the Rotorua District, New Zealand, to test for effects of morphological features, catchment characteristics and lake trophic state on net sedimentation rates and sediment nutrient concentrations. Multiple linear regression was used to show that 68% of the variation in net sedimentation rates across the lakes could be explained by lake trophic state and catchment area. Comparison of 2006 data with results from a survey in 1995 showed that surficial sediment (0–2 cm) total phosphorus concentrations (TP) have increased in three of the 12 lakes, at rates ranging from 27.5 to 114.4 mg P kg–1 dry wt y–1. Total nitrogen (TN) concentrations in surficial sediments have increased in nine of the 12 lakes at rates ranging from 51.8 to 869.2 mg N kg–1 dry wt y–1. Temporal changes in sediment TP and TN concentrations were not significantly linearly related (P = 0.12–0.88) to catchment area or different water column indices considered to reflect lake trophic state, including annual mean water column concentrations of TP, TN or chlorophyll a. It is concluded that between-lake variations in sediment TP and TN concentrations are influenced by a range of complex interacting factors, such as sediment redox conditions (and periodic anoxia in the hypolimnion of some lakes) as well as variations in sediment mineral composition (which influences retention and release of various sediment phosphorus and nitrogen species). Subsequently, these factors cause sediment TP and TN concentrations across the 12 lakes to respond differently to temporal changes in water column TP and TN concentrations.

Effects of climate and nutrient load on the water quality of shallow lakes assessed through ensemble runs by PCLake

Complex ecological models are used to predict the consequences of anticipated future changes in climate and nutrient loading for lake water quality. These models may, however, suffer from nonuniqueness in that various sets of model parameter values may yield equally satisfactory representations of the system being modeled, but when applied in future scenarios these sets of values may divert considerably in their simulated outcomes. Compilation of an ensemble of model runs allows us to account for simulation variability arising from model parameter estimates. Thus, we propose a new approach for aquatic ecological models creating a more robust prediction of future water quality. We used our ensemble approach in an application of the widely used PCLake model for Danish shallow Lake Arreskov, which during the past two decades has demonstrated frequent shifts between turbid and clear water states. Despite marked variability, the span of our ensemble runs encapsulated 70–90% of the observed variation in lake water quality. The model exercise demonstrates that future warming and increased nutrient loading lead to lower probability of a clear water, vegetation-rich state and greater likelihood of cyanobacteria dominance. In a 6.0°C warming scenario, for instance, the current nutrient loading of nitrogen and phosphorus must be reduced by about 75% to maintain the present ecological state of Lake Arreskov, but even in a near-future 2.0°C warming scenario, a higher probability of a turbid, cyanobacteria-dominated state is predicted. As managers may wish to determine the probability of achieving a certain ecological state, our proposed ensemble approach facilitates new ways of communicating future stressor impacts.

Assessing ways to combat eutrophication in a Chinese drinking water reservoir using SWAT

Across China, nutrient losses associated with agricultural production and domestic sewage have triggered eutrophication, and local managers are challenged to comply with drinking water quality requirements. Evidently, the improvement of water quality should be targeted holistically and encompass both point sources and surface activities within the watershed of a reservoir. We expanded the ordinary Soil Water Assessment Tool - (SWAT) with a widely used empirical equation to estimate total phosphorus (TP) concentrations in lakes and reservoirs. Subsequently, we examined the effects of changes in land and livestock management and sewage treatment on nutrient export and derived consequences for water quality in the Chinese subtropical Kaiping (Dashahe) drinking water reservoir (supplying 0.4 million people). The critical load of TP was estimated to 13.5 tonnes yr � 1 in order to comply with the minimum drinking waterrequirements,whichcorrespondsto87%ofthesimulatedloadtothereservoiratpresent.Boththeimplementationof buffer zones along rivers and removal of sewage discharges showed marked improvement in reservoir water quality. Future research should focus on both hydrological model performance and nutrient transport pathways, which are challenged by a complex artificially altered water infrastructure in the form of ditches, channels and ponds in monsoon- influenced subtropical watersheds. Additional keywords: agriculture, reservoir water quality, sewage, subtropical watershed.

Modelling the response of a highly eutrophic lake to reductions in external and internal nutrient loading

The reduction of macronutrients to levels that limit primary production is often a critical element of mitigating eutrophication and reducing the potential for algal blooms. Lake Okaro has remained highly eutrophic despite an intensive catchment and in-lake restoration programme, including implementation of a constructed wetland, riparian protection, an alum application and application of a modified zeolite mineral (Z2G1) to reduce internal nutrient loading. A one-dimensional process-based ecosystem model (DYRESM-CAEDYM) was used in this study to investigate the need for further nutrient loading reductions of both nitrogen (N) and phosphorus (P). The model was calibrated against field data for a 2-year period and validated over two separate 1-year periods. Model simulations suggest that the trophic status of the lake, measured quantitatively with the Trophic Level Index (TLI), could shift from highly eutrophic to mesotrophic with external and internal loads of both N and P reduced by 75–90%. The magnitude of the nutrient load reductions is indicative of a major challenge in being able to effect transitions across trophic state categories for eutrophic lakes.