Aquatic Ecosystem Model Research Articles

The emerging synthesis of evolution with ecology in fisheries science

Fisheries science is currently being transformed through a true integration of ecological and evolutionary perspectives. Many questions are emerging from the recognition that human-induced evolutionary change can elicit ecological change on short time scales, in some cases equal to or exceeding the changes brought on by classical ecological effects. For instance, to what extent does evolutionary change associated with size-selective harvesting, supplementation, captive breeding, aquaculture escapees, and related fisheries activities directly or indirectly affect species demography (persistence, productivity, or recovery), community structure, and ecosystem functioning? Under what conditions do feedbacks between evolution and ecology matter most for managing fisheries activities? Do such feedbacks generate predictable outcomes, and are they reversible? Although as yet, little consensus has been reached on the answers to these questions, it is clear that a synthesis of evolutionary and ecological perspectives holds great promise for improving and generating more biologically realistic modeling, monitoring, rebuilding, and management of fish populations, fish species, and aquatic ecosystems.

Application of a simple genetic algorithm for the calibration of aquatic ecosystem model of an agricultural pond

In this study, we aim to construct and apply a simple genetic algorithm (SGA) to optimize a large number of parameters of an one-box ecosystem model. The ecosystem model was used to simulate the water quality over a 6-month period based on the new observation data in an agricultural pond which was strongly influenced by a green algal bloom. Of the 54 parameters in this model, 10 important parameters were initially selected for the optimization, with one other parameter being subsequently added. The SGA program was used for three purposes, namely (1) to narrow the search space for the 10 parameters, (2) to assess the influence of the additional parameter on the optimization results, and (3) to observe the distribution and convergence of the optimized values for the 10 selected parameters. In the next step, new ranges for these 10 important parameters were assigned and the SGA was applied to all 54 model parameters to seek the optimum value for each parameter. The modeling approach and the results presented here provide valuable and reliable evidences of the optimum parameters for further simulations to clarify the mechanisms of the biochemical processes in the water.

A model of phosphorus cycling to explore the role of biomass turnover in submerged aquatic vegetation wetlands for Everglades restoration

Engineered wetlands using submerged aquatic vegetation (SAV) are a cornerstone to the Stormwater Treatment Area (STA) project for stripping phosphorus from agricultural stormwater and lake water before entering protected Everglades marshes in south Florida, USA. However, recent efforts have suggested that the apparent lowest achievable outflow P (C*) in SAV systems (∼16μg/l) may not be low enough for proposed regulatory criteria. Thus, deepened predictive understanding on the functionality of these systems is of critical importance. Here, we develop a steady-state mass balance model of intermediate complexity to investigate C* in SAV systems. The model focuses on the role of SAV biomass turnover and P release to the water column, drawing upon established principles from shallow lake studies. This study introduces several large and unique datasets collected from a single study site (STA-2 Cell 3) over a 10-year period and demonstrates coherence in these data through the modeling approach. The datasets included inflow–outflow values, P storage in accrued sediment at two intervals, annual surveys of SAV species composition, gradients of SAV tissue-P, and gradients of internal water column P concentration (previously published). The model was implemented and calibrated in an uncertainty framework with Monte Carlo methods, threshold screening, and multi-criteria limits of acceptability. Model calibration and validation appeared successful, resulting distributions of model parameters and accepted model simulations were relatively narrow, and results deepened perspectives on the previously identified C*. Rooted SAV species may be mining substantial P from underlying soils via root uptake and thus contributing internal loads. Steady turnover and decomposition of SAV biomass may be accounting for up to about a third of the background C*. These perspectives are relevant to STA optimization; our unique data, usage, and calibration strategy should be of interest to the aquatic ecosystem modeling community in general.

A mass-balanced pelagic ecosystem model with size-structured behaviourally adaptive zooplankton and fish

Mesozooplankton is a highly diverse group of organisms ranging from very small to large herbivorous, omnivorous or predatory forms. However, most aquatic ecosystem models typically contain only one or two state variables which represent all mesozooplankton forms and specify their role in marine food webs. We have extended an existing mass-balanced marine ecosystem model to include a wide range of mesozooplankton size-classes and species growing from small to large, and maturing at different size. The model includes a dynamic pool of fish with a fixed mortality rate as a closure term of the model, and mechanistic expressions for fish predation. The zooplankton consumes phytoplankton and smaller zooplankton, and responds adaptively to the instantaneous local rates of growth and predation by migrating towards more profitable habitats. We run the model for long time in a stable and repetitive diel light cycle, and explore the emerging ecosystem structure and complexity. In the stable environment the presence of fish has strong structuring effects over the size-structure of mesozooplankton, but little influence on phytoplankton because the total biomass of mesozooplankton remains relatively stable over the fish cycles. The inclusion of adaptive and flexible behaviour leads to emergent effects of multiple predators; the removal of intra-guild predation among zooplankton result in low fish abundance because zooplankton spend more time in deeper habitats. The model reveals persistent spatial and cascading behavioural interactions and is a step towards a mechanistic and adaptive representation of the upper trophic levels in ecosystem models.

Metabolic scaling regularity in aquatic ecosystems

We tested the hypothesis that ecosystem metabolism follows a quarter power scaling relation, analogous to organisms. Logarithm of Biomass/Production (B/P) to Trophic Level (TL) relationship was estimated to 98 trophic models of aquatic ecosystems. A normal distribution of the slopes gives a modal value of 0.64, which was significantly different of the theoretical value of 0.75 (p<0.05). After correction for transfer efficiencyamong trophic levels a modal value of 0.726 was obtained through a least squares algorithm which was not significantly different from the theoretical one (p>0.05). We also tested for error in both variables, Log (B/P) and TL, through a Reduced Major Axis regression with similar results, with a modal value of 0.756 (p>0.05). We also explored a geographic distribution showing no significant relation (p>0.05) to latitude and between differentregions of the world. We conclude that: a) cosystem metabolism follows the quarter-power scaling rule; b) transfer efficiency between TL plays a relevant role characterizing local attributes to ecosystem metabolism; and c) there is neither latitudinal nor geographic differences. These findings confirm the existence of a metabolicscaling regularity in aquatic ecosystems.

The effect of zinc on aquatic microbial ecosystems and the degradation of dissolved organic matter

We developed a simple aquatic microbial ecosystem model in order to examine potential effects of zinc on microorganisms and the related degradation of dissolved organic matter (DOM). The model is a combination of both a traditional food chain and a microbial loop. The traditional food chain is mainly composed of phytoplankton and zooplankton, whilst the microbial loop is composed of DOM, bacteria and bacterivorous protozoa. We incorporated the suppressive effect of zinc on the bacterial uptake of DOM and assessed the steady state responses of the model for various zinc concentrations. The analytical and numerical results of the model implied that either zooplankton or bacterivorous protozoa might be the most vulnerable group to excessive zinc load than bacteria, depending on the grazing preference of zooplankton between phytoplankton and bacterivorous protozoa. The sensitivity analyses supported that the microbial loop solely is more sensitive to zinc than the coupled system combining both the traditional food chain and the microbial loop.

Exergy as an indicator: Observations of an aquatic ecosystem model

Exergy is considered as a goal function or ecological orientor. Normally at the edge of oscillation exergy reaches to its maximum value when the ecosystem had no adaptation on it. To study the variation of exergy in different states of ecosystem, a simple three species (phytoplankton, zooplankton and fish) food chain model has been considered. From the model it is shown that the system moves from steady state to chaotic state by decreasing zooplankton body volume in turn increasing its grazing rate. By the property of self-adaptability the system tries to overcome this situation. Two such possible processes are described here: (i) by the toxic effect of phytoplankton and (ii) by reducing half saturation constant of fishes. In both this cases exergy value reduces and the system reaches to stable state. Through the analysis of exergy variation in all these situations this paper shows that the system chose the process in which the reduction of exergy will be the minimum.

The influence of parameter fitting methods on model structure selection in automated modeling of aquatic ecosystems

Modeling dynamical systems involves two subtasks: structure identification and parameter estimation. ProBMoT is a tool for automated modeling of dynamical systems that addresses both tasks simultaneously. It takes into account domain knowledge formalized as templates for components of the process-based models: entities and processes. Taking a conceptual model of the system, the library of domain knowledge, and measurements of a particular dynamical system, it identifies both the structure and numerical parameters of the appropriate process-based model. ProBMoT has two main components corresponding to the two subtasks of modeling. The first component is concerned with generating candidate model structures that adhere to the conceptual model specified as input. The second subsystem uses the measured data to find suitable values for the constant parameters of a given model by using parameter estimation methods. ProBMoT uses model error to rank model structures and select the one that fits measured data best.In this paper, we investigate the influence of the selection of the parameter estimation methods on the structure identification. We consider one local (derivative-based) and one global (meta-heuristic) parameter estimation method. As opposed to other comparative studies of parameter estimation methods that focus on identifying parameters of a single model structure, we compare the parameter estimation methods in the context of repetitive parameter estimation for a number of candidate model structures. The results confirm the superiority of the global optimization methods over the local ones in the context of structure identification.

Impact of DOC trends resulting from changing climatic extremes and atmospheric deposition chemistry on periphyton community of a freshwater tropical lake of India

Recent measurements have demonstrated unprecedented increase in atmospheric deposition of nutrients in many parts of India. To determine whether atmospheric nutrient inputs would increase phytoplankton growth and catchment dissolved organic carbon (DOC) flushing to constrain benthic algae, we analyzed NO3 − and PO 4 −3 in atmospheric deposits; nutrients and DOC in runoff and lake water and standing crop biomass of phytoplankton and periphyton at Jaisamand Lake of Rajasthan, India. Atmospheric deposition of NO3 − (7.18–29.95 kg ha−1 year−1) and PO 4 −3 (0.56–2.15 kg ha−1 year−1) showed a consistently rising trend across the year. Microbial biomass and activity in catchment increased in response to atmospheric deposition. Lake DOC and nutrients showed strong coherence with their terrestrial and atmospheric fluxes. Phytoplankton development showed significant linearity with atmospheric input of nutrients. Air-driven input appeared to have compensated the nutrient constraints to phytoplankton during drought. The N:P stoichiometry of deposition and that of lake water indicated that, although there was a seasonal switchover to N- or P-limitation, phytoplankton were mainly co-limited by N and P due probably to the synergistic effects of combined N + P enrichment in the pelagic zone of the lake. Periphyton standing crop showed inverse relationship with phytoplankton and lake DOC. The study indicated that enhanced phytoplankton development and terrestrial DOC flushing in response to atmospheric nutrient input attenuated light penetration to constrain algal periphyton. We suggests that data on these issues may be considered in developing aquatic ecosystem models to establish future links between changing air–water–land interactions and associated shifts in lake ecosystem functioning for more accurately predicting climate change drivers and designing integrated lake basin management strategies.

Time-scale dependence in numerical simulations: Assessment of physical, chemical, and biological predictions in a stratified lake at temporal scales of hours to months

We evaluated the predictive ability of a one-dimensional coupled hydrodynamic-biogeochemical model across multiple temporal scales using wavelet analysis and traditional goodness-of-fit metrics. High-frequency in situ automated sensor data and long-term manual observational data from Lake Mendota, Wisconsin, USA, were used to parameterize, calibrate, and evaluate model predictions. We focused specifically on short-term predictions of temperature, dissolved oxygen, and phytoplankton biomass over one season. Traditional goodness-of-fit metrics indicated more accurate prediction of physics than chemical or biological variables in the time domain. This was confirmed by wavelet analysis in both the time and frequency domains. For temperature, predicted and observed global wavelet spectra were closely related, while observed dissolved oxygen and chlorophyll fluorescence spectral characteristics were not reproduced by the model for key time scales, indicating that processes not modeled may be important drivers of the observed signal. Although the magnitude and timing of physical and biological changes were simulated adequately at the seasonal time scale through calibration, time scale-specific dynamics, for example short-term cycles, were difficult to reproduce, and were relatively insensitive to the effects of varying parameters. The use of wavelet analysis is novel to aquatic ecosystem modeling, is complementary to traditional goodness-of-fit metrics, and allows for assessment of variability at specific temporal scales. In this way, the effect of processes operating at distinct temporal scales can be isolated and better understood, both in situ and in silico. Wavelet transforms are particularly well suited for assessment of temporal and spatial heterogeneity when coupled to high-frequency data from automated in situ or remote sensing platforms.

Hydroinformatics in multi-colours—part green: applications in aquatic ecosystem modelling

The present paper focuses on demonstrating the capabilities of modern hydroinformatics tools in the field of environmental systems by integrating biotic and abiotic process modelling. Abiotic processes like hydrodynamic flow and transport phenomena are often formulated based on physical principles like conservation of mass, momentum and energy. These processes are adequately represented mathematically by second order partial differential equations that can be solved numerically in a variety of ways. However, in aquatic ecosystem modelling, biological/ecological processes play an important role and these processes are not always understood at the required level of detail to be captured in terms of conservation principles. In this paper two modelling approaches for biotic processes are explored for representing spatial pattern dynamics of aquatic ecosystems: (i) cellular automata (CA) and (ii) multi-agent systems (MAS) models, in combination with Delft 3D-WAQ for advanced flow and transport modelling. It is shown that CA are quite capable of capturing discrete growth phenomena like outcompeting plant species which are known to depend mainly on local effects. A MAS approach can combine nonlinearity, randomness and complexity of aquatic ecosystems, which can then be used to enhance the capabilities of available physics-based software systems like the DELFT3D software suite.

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.

Conducting model ecosystem studies in tropical climate zones: Lessons learned from Thailand and way forward

Little research has been done so far into the environmental fate and side effects of pesticides in the tropics. In addition, those studies conducted in tropical regions have focused almost exclusively on single species laboratory tests. Hence, fate and effects of pesticides on higher-tier levels have barely been studied under tropical conditions. To address this lack of knowledge, four outdoor aquatic model ecosystem experiments using two different test systems were conducted in Thailand evaluating the insecticide chlorpyrifos, the herbicide linuron and the fungicide carbendazim. Results of these experiments and comparisons of recorded fate and effects with temperate studies have been published previously. The present paper discusses the pros and cons of the methodologies applied and provides indications for i) possible improvements; ii) important aspects that should be considered when performing model ecosystem experiments in the tropics; iii) future research.

Is it possible to extrapolate results of aquatic microcosm and mesocosm experiments with pesticides between climate zones in Europe?

1 IntroductionHigher tier studies to assess the environmental risks ofpesticides have been performed mainly in Atlantic CentralEurope and North America and results of such studies havebeen extrapolated to other climatic regions such as SouthEurope (Ramos et al. 2000; Lopez-Mancisidor et al. 2008a).Since climate (e.g., sun hours, rainfall, temperature), agro-ecosystems (e.g., crop rotation, field size), and edge-of-fieldsurface waters (e.g., hydrology, ecology) in those regions arequite different, it may be expected that exposure profiles andeffects of pesticides in surface waters are also different(Tarazona 2005; Lopez-Mancisidor et al. 2008a). It may thusbe questionable whether the extrapolation of results fromhigher tier studies over these regions is justified (Ramos etal. 2000; Lopez-Mancisidor et al. 2008a). On the other hand,it is neither financially nor practically feasible to test a largenumber of chemicals on a large number of species andcommunities in different localities (Brock et al. 2006). In theEU, these concerns were acknowledged with the recentadoption of a new regulation concerning the placing of plantprotection products on the market (Regulation (EC) No.1107/2009; EU 2009). According to this regulation, author-izations granted by one Member State should in principle beaccepted by other Member States where agricultural, planthealth, and environmental (including climatic) conditions arecomparable. To this end, three zones with such comparableecological and climatic conditions were distinguished,namely North, Central, and South (Table 1).Van Wijngaarden et al. (2005a), Van den Brink et al.(2006), and Maltby et al. (2009) reviewed aquatic modelecosystem studies carried out with insecticides, herbicides,and fungicides, respectively. The vast majority of theEuropean studies were conducted in the Central zone,whereas very few studies were reported for both the Southand the North zone (Table 1). To account for the lack ofstudies in the South zone, a research project was initiated in2010 that started with the set up of an outdoor microcosmfacility in Lisbon (Portugal). One of the aims of this facilityis to study the possibilities and limitations in the spatialextrapolation of regulatory acceptable concentrations(RACs) derived from outdoor micro-/mesocosm experi-ments between European climate zones. The present paperaims at summarizing differences in (1) ecology of edge-of-field surface waters, (2) exposure conditions to pesticides,(3) direct and indirect effects, and (4) recovery potential inpesticide stressed (semi-)field freshwater ecosystems underSouth zone compared to Central zone conditions that apriori may be anticipated. Implications for choices relatedto the experimental design of experiments in Portugal arediscussed based on this analysis.

The representation of cyanobacteria life cycle processes in aquatic ecosystem models

Two simplified versions of a numerical life cycle model for diazotrophic cyanobacteria (of the order Nostocales) are developed and evaluated. Both consider two-life cycle stages, one growing, nitrogen-fixing stage and one stage that combines the resting, germinating and vegetative stages. The versions differ in the vertical resolution of the non-diazotrophic stage: version 1 collects the biomass in one layer at the bottom, version 2 considers sinking and rising of biomass explicitly. The results of the two versions are compared with a complex cyanobacteria life cycle model which describes four different life cycle stages each with two internal quotas for energy and nitrogen. The two simplified approaches show a good agreement with respect to the main characteristics of cyanobacteria dynamics (timing and duration of blooms, magnitude of nitrogen fixation, interannual variability). Our model study shows that both simplified approaches are suitable to be implemented into three-dimensional coastal or lake models.

An integrated model for assessing the risk of TCE groundwater contamination to human receptors and surface water ecosystems

The practical implementation of the European Water Framework Directive has resulted in an increased focus on the hyporheic zone. In this paper, an integrated model was developed for evaluating the impact of point sources in groundwater on human health and surface water ecosystems. This was accomplished by coupling the system dynamics-based decision support system CARO-PLUS to the aquatic ecosystem model AQUATOX using an analytical volatilization model for the stream. The model was applied to a case study where a trichloroethylene (TCE)-contaminated groundwater plume is discharging to a stream. The TCE source will not be depleted for many decades; however, measured and predicted TCE concentrations in surface water were found to be below human health risk management targets. Volatilization rapidly attenuates TCE concentrations in surface water. Thus, only a 30-m stream reach fails to meet surface water quality criteria. An ecological risk assessment found that the TCE contamination did not impact the stream ecosystem. Uncertainty assessment revealed hydraulic conductivity to be the most important site-specific parameter. These results indicate that contaminant plumes with μg L −1 concentrations of TCE entering surface water systems may not pose a significant risk.

Forms and Variability of Phosphorus in the Baltic Sea–-A Challenge to Ecosystem Modeling

Knowledge of the partitioning between the dissolved and particulate phases of nutrient elements is a key factor in aquatic ecosystem modeling since partitioning regulates the availability to demand ratio of the nutrient in question. This is seldom taken into account in environmental monitoring programs. In this paper, the occurrence and variability of particulate and dissolved phosphorus were studied in the coastal zone of the Baltic Sea. The particulate fraction (PF) of total phosphorus (TP) concentration in coastal waters from some forty stations along the east coast of Sweden was, on average, 0.33. Dissolved inorganic phosphorus (DIP) was a poor predictor of total dissolved phosphorus (DP) representing only 20%-30% of this fraction. Sensitivity analyses showed that the value of PF had a significant impact on modeled predictions of TP concentration in the water on a Baltic sub-basin scale, whereas an applied coastal model was insensitive to variations in PF. Hence, this study encourages further sampling efforts on the partitioning of phosphorus in the open waters of the Baltic Sea.

Revealing spatial pattern dynamics in aquatic ecosystem modelling with Multi-Agent Systems in Lake Veluwe

Aquatic ecosystems are among the most complex due to the highly nonlinearity, randomness, as well as interactive multi-processes in multi-scales. Besides, highly limited understanding and very limited measurement data make the modelling of such kind of systems a very challenging task, which needs to combine domain knowledge, available data and other models. The concept of Multi-Agent Systems (MAS) in modelling spatial population dynamics of aquatic plant growth is explored in this research due to the capability of MAS in utilizing various information and data, reflecting both the interactions among different entities and entity's own properties. Expert biological knowledge, GIS maps and environmental conditions are used as input information and data in the development of MAS model. Several different aspects are included: plant agents, environmental backgrounds, and animal influences. Environmental background factors include flow pattern, light visibility, water temperature, water depth and wind, which are all abiotic factors. Plant agents represent different plant species; the ones in this research are Potamogeton pectinatus ( Pp) and Chara aspera ( Cs), while animals here refer to water birds. Based on biological knowledge and data supplied for Lake Veluwe, the MAS modelling rules were developed. Through these MAS rules, agents are linked to environmental and biological processes. The resulting spatial pattern dynamics indicates that a multi-agent approach can exhibit complex behaviour even when the individual strategies of each agent are simple. The test case for Lake Veluwe showed quite good agreement compared to the GIS maps available and the biological knowledge presented. Multi-Agent Systems show a promising approach to modelling spatial population dynamics for aquatic plants.

Evaluation of biological water purification functions of inland lakes using an aquatic ecosystem model

An effective measure to cope with eutrophication of lakes is to remove nutrients that can cause algal blooming by taking advantage of natural water purification processes. Here the term “ purification” is defined, in a wide sense, as the potential role of a water body to contribute to the reduction of pollutants and thus controlling eutrophication. Also regarded as a kind of ecological regulating services, biological purification involves various processes concerning seasonal nutrient fixation, such as uptake by aquatic macrophytes, biofouling onto foliage substrates, feeding by organisms in higher trophic level, and eternal loss or removal of substance from the water. In order to evaluate the water purification ability, a numerical lake ecosystem model highlighting the role of macrophyte colonies in the shore zone was developed and applied to Lakes Suwa, Kasumi and Biwa, as well as five small lakes attached to Lake Biwa. The model includes the biological interactions between pelagic compartments (phyto- and zooplankton, detritus, dissolved organic matter, pelagic fish and nutrients) and benthic compartments (macrophytes, epiphytic algae, phytal animals, macro- and megalobenthos, and demersal fish). Under dynamic forcing of meteorological and hydrological parameters, the model was run over a year to evaluate the annual nutrient cycles and purification functions. The reproducibility of the model was validated for each water body by comparison with the field data from the water quality monitoring campaign. Numerical results revealed that the water purification ability, from viewpoints of both stock and flux, generally tends to be higher in the shore region than in the offshore region owing to a wide variety of aquatic biota. Moreover, it increases almost in proportion to the density of vegetation in the shore region. Nutrient fluxes representing the purification processes turned out to be closely connected with the surface area or equivalently with the retention time of the water bodies, suggesting that biological purification does not become dominant against physical turnover until the surface area reaches around 10 3 ha or the retention time exceeds the order of 10 2 days.

Spatiotemporal pattern formation in a diffusive predator-prey system: an analytical approach

In this paper, we propose and analyse a mathematical model to study the mathematical aspect of reaction diffusion pattern formation mechanism in a predator-prey system. An attempt is made to provide an analytical explanation for understanding plankton patchiness in a minimal model of aquatic ecosystem consisting of phytoplankton, zooplankton, fish and nutrient. The reaction diffusion model system exhibits spatiotemporal chaos causing plankton patchiness in marine system. Our analytical findings, supported by the results of numerical experiments, suggest that an unstable diffusive system can be made stable by increasing diffusivity constant to a sufficiently large value. It is also observed that the solution of the system converges to its equilibrium faster in the case of two-dimensional diffusion in comparison to the one-dimensional diffusion. The ideas contained in the present paper may provide a better understanding of the pattern formation in marine ecosystem.