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.     

Optimization of exergy and implications of body sizes of phytoplankton and zooplankton in an aquatic ecosystem model

Size appears to be an important parameter in ecological processes. All physiological processes vary with body size ranging from small microorganisms to higher mammals. In this model, five state variables — phosphorus, detritus, phytoplankton, zooplankton and fish are considered. We study the implications of body sizes of phytoplankton and zooplankton for total system dynamics by optimizing exergy as a goal function for system performance indicator. The rates of different sub-processes of phytoplankton and zooplankton are calculated, by means of allometric relationships of their body sizes. We run the model with different combinations of body sizes of phytoplankton and zooplankton and observe the overall biomass of phytoplankton, zooplankton and fish. The highest exergy values in different combinations of phytoplankton and zooplankton size indicate the maximum biomass of fish with relative proportions of phytoplankton and zooplankton. We also test the effect of phosphorus input conditions corresponding to oligotrophic, mesotrophic, eutrophic system on its dynamics. The average exergy to be maximized over phytoplankton and zooplankton size was computed when the system reached a steady state. Since this state is often a limit cycle, and the exergy copies this behaviour, we averaged the exergy computed for 365 days (duration of 1 year) in the stable period of the run. In mesotrophic condition, maximum fish biomass with relative proportional ratio of phytoplankton, zooplankton is recorded for phytoplankton size class 3.12 (log V μm³ volume) and zooplankton size 4 (log V μm³ volume). In oligotrophic condition the highest average exergy is obtained in between phytoplankton size 1.48 (log V μm³ volume) and zooplankton size 4 (log V μm³ volume), whereas in eutrophic condition the result shows the highest exergy in the combination of phytoplankton size 5.25 (log V μm³ volume) and zooplankton size 4 (log V μm³ volume).     

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.     

A Markovian model for ecosystem flow analysis

Nutrient flow through ecosystems is modeled as a discrete Markov chain whose transition probabilities are stationary or time inhomogenous according to whether a steady state or dynamic ecosystem is modeled, respectively. Expected residence time and number of intercompartmental transfers for a nutrient within a set of compartments are derived. Variances of these random variables are also considered. A measure for ecosystem resource recycling is given as a weighted sum of probabilities.     

A three-trophic level estuarine model: Synergism of two mechanistic simulations

Few numerical simulations have attempted to include a high degree of biological detail for several trophic levels. Typically, in planktonic ecosystem models, if the dynamics of nutrients, phytoplankton and herbivorous zooplankton are formulated with ecological complexity, then carnivores are ignored, forced or modeled in an extremely simplified manner. Extensive mechanistic detail for important carnivores is difficult to represent because reliable and relevant ecological data are rarely available for appropriate species and local populations. Further, the wide temporal and spatial differences between life histories of lower plankton and carnivores may be technically difficult to model.In Narragansett Bay, Rhode Island, the ctenophore Mnemiopsis leidyi is an important carnivore to which these objections do not apply. A detailed carbon-based simulation model of this population of ctenophores was developed independently from an ecosystem model of Narragansett Bay which included detailed interactions between phytoplankton, primarily herbivorous zooplankton and nutrients. The interfacing of these two models without changing any of the formulations or values of the coefficients provided a test of the commonly used practice of forcing certain components. Both models were originally constructed with the biomass of a critical compartment forced according to observed data; in the plankton model, ctenophores were forced, and in the ctenophore model, zooplankton were forced.Predicted biomasses for zooplankton and ctenophores in the combined model were similar to the results of the two parent models, but improved relative to the actual field observations. From the findings it appears that the strategy of forcing is valid provided the forced patterns are appropriate and reasonable.     

A retrospective Markovian model for ecosystem resource flow

Historic ecosystem resource flow is modeled as a retrospective discrete Markov chain to obtain the expected values and variances of compartmental residence times and numbers of intercompartmental transfers that compartmental standing crops have experienced since their latest entry into the ecosystem. The transition probabilities of the proposed retrospective Markovian model are either stationary or time inhomogeneous according to whether a steady state or non-steady state ecosystem, respectively, is analyzed.     

Modelling the distribution and effect of heavy metals in an aquatic ecosystem

Models are reviewed describing the distribution and effect of heavy metals in an aquatic ecosystem. Since a model used for an impact statement should give the maximum concentration level rather than the seasonal variation, a model focussing on this situation is suggested. The basic differential equations describe (1) the variation in concentration of the toxicant per biomass dry matter in a given trophic level, and (2) the exchange of toxicant between sediment and water. Furthermore, since a substantial part of the heavy metal in an aquatic ecosystem is bound to suspended matter, an equation describing the equilibrium between dissolved and suspended matter must be included.A literature review has been carried out on the parameters used in the above mentioned equations and a demonstration, showing how it is possible to find approximate values for such parameters as excretion coefficient and uptake coefficient on the basis of a relationship between these two parameters and the size of an organism, is given.     

A split flow chamber with artificial sediment to examine the below-ground microenvironment of aquatic macrophytes

We present a new experimental set-up enabling fine-scale examination of how changing environmental conditions affect the below-ground biogeochemical microenvironment of aquatic macrophytes. By means of microsensor and planar optode technology, the influence of plant-mediated radial O₂ release on the below-ground chemical microenvironment of Zostera muelleri and Halophila ovalis was determined in high spatio-temporal resolution. The seagrass specimens were cultured in a new split flow chamber with artificial sediment made of a deoxygenated seawater–agar solution with added sulphide. Microelectrode measurements revealed radial O₂ release from the root–shoot junction of both Z. muelleri and H. ovalis during both light stimulation and darkness, resulting in a rapid decrease in H₂S concentration, and a significant drop in pH was observed within the plant-derived oxic microzone of Z. muelleri. No radial O₂ release was detectable from the below-ground tissue of Z. muelleri during conditions of combined water-column hypoxia and darkness, leaving the plants more susceptible to sulphide invasion. The spatial O₂ heterogeneity within the immediate rhizosphere of Z. muelleri was furthermore determined in two dimensions by means of planar optodes. O₂ images revealed a decrease in the spatial extent of the plant-derived oxic microzone surrounding the below-ground tissue during darkness, supporting the microelectrode measurements. This new experimental approach can be applied to all rooted aquatic plants, as it allows for direct visual assessment of the below-ground tissue surface during microprofiling, while enabling modification of the above-ground environmental conditions.     

Different proxies for the reactivity of aquatic sediments towards oxygen: A model assessment

Information on benthic carbon mineralization rates is often derived from the analysis of oxygen microprofiles in sediments. To enable a direct comparison of different sediment environments, it is often desirable to characterize sediments by a single proxy that expresses their “reactivity” towards oxygen. For this, there are three commonly used proxies: the oxygen penetration depth (OPD), the oxygen flux at the sediment-water interface (DOU), and the maximum volumetric oxygen consumption rate (R_max). The OPD can be directly determined from the oxygen depth profile, while the DOU is usually obtained by a linear fit to the oxygen gradient either in diffusive boundary layer. The oxygen consumption rate R_max requires the fitting of a reactive-transport model to the data profile. This article shows that the OPD alone is a suboptimal proxy, because it shows a strong dependence on the half-saturation constant K_s, and secondly, because it is sensitive to the particular re-oxidation conditions right above the oxic-anoxic interface. Similarly, the volumetric oxygen consumption rate R_max is rather strongly dependent on the kinetic model formulation employed. To show this we fitted three different (Bouldin, Blackman and Monod) kinetics to the same oxygen data profiles. When fitting these models, the R_max values obtained differed by 20% for exactly the same oxygen profile. Accordingly, if one reports R_max values, it is crucial to specify the kinetic model alongside. Overall, DOU emerges as sediment reactivity proxy which is the least model dependent.     

Tracking bioaccumulation in aquatic organisms: A dynamic model integrating life history characteristics and environmental change

We have developed a dynamic model to track the evolution of contaminant concentration in an aquatic organism as a function of season and ontogeny throughout its life cycle. We have focused our analysis on the round goby (Apollonia melanostoma), a globally distributed invasive forage fish. By integrating bioenergetics with a bioaccumulation model, we illustrate how life history characteristics interact to influence contaminant accumulation. We use uncertainty and sensitivity analyses to assess how the model output is affected by uncertainty and variability in model parameters. We then demonstrate the influence of important physiological characteristics on contaminant accumulation with two scenarios. First, we probe the influence of sexual dimorphism by comparing gender-specific accumulation of a standard polychlorinated biphenyl congener, PCB153, in male and female round gobies. We hypothesize that lipid loss in female gobies during spawning season leads to a decrease in the PCB body burden compared to male gobies. Second, we compare PCB accumulation in the round goby and in the mottled sculpin (Cottus bairdi), the native forage fish that the round goby displaced in southern Lake Michigan, to determine whether the invasive species has an intrinsically different bioaccumulation potential than the native one. Our non-intuitive findings from these simulations illustrate how the interaction of growth rate with other life history characteristics lead to unexpected bioaccumulation patterns. The model we present is a flexible tool that integrates complex and dynamic interactions among environmental parameters, thus providing a means to better assess the potential for chemical accumulation in human and wildlife populations, and aiding the development of ecological forecasts.     

A sensitivity analysis of an ecosystem model of estuarine carbon flow

The North Inlet Marsh-Estuarine System Model (NIMES) is a 19-compartment real-time deterministic ecosystem simulation model of intrasystem carbon flow and exchange between an estuary and adjacent coastal water. A complete sensitivity analysis of this model with regard to POM, DOM and nekton annual exchange and annual system net productivity was completed and the functional relationship between these system behaviors and the perturbed parameters were determined by regression techniques. Simulated POM annual exchange between the estuary and the sea was largely controlled by offshore POM concentration, water column respiration and the gross productivity of the marsh and water column flora. Simulated DOM annual estuarine-oceanic exchange was most sensitive to perturbations in the gross productivity and biomass changes in marsh flora and water column microbial DOM uptake. Simulated nekton exchange reflected a sensitivity to migratory behavior and subtidal benthic biomass changes. System annual net productivity as simulated by the model showed a high sensitivity to all model processes which affected component primary production and respiration. From this sensitivity analysis, a scheme is developed to evaluate research needs for further model development for the North Inlet ecosystem.     

A simple plankton model for the Oregon upwelling ecosystem: Sensitivity and validation against time-series ocean data

Simple plankton models serve as useful platforms for testing our understanding of the mechanisms underlying ecosystem dynamics. A simple, one-dimensional plankton model was developed to describe the dynamics of nitrate, ammonium, two phytoplankton size-classes, meso-zooplankton, and detritus in the Oregon upwelling ecosystem. Computational simplicity was maintained by linking the biological model to a one-dimensional, cross-shelf physical model driven by the daily coastal upwelling index. The model sacrificed resolution of regional-scale and along-shore (north to south) processes and assumed that seasonal productivity is primarily driven by local cross-shelf Ekman transport of surface waters and upwelling of nutrient-rich water from depth.Our goals were to see how well a simple plankton model could capture the general temporal and spatial dynamics of the system, test system sensitivity to alternate parameter set values, and observe system response to the effective scale of potential retention mechanisms. Model performance across the central Oregon shelf was evaluated against two years (2000-2001) of chlorophyll and copepod time-series observations. While the modeled meso-zooplankton biomass was close in scale to the observed copepod biomass, phytoplankton was overestimated relative to that inferred from the observed surface chlorophyll concentration. Inshore, the system was most sensitive to the nutrient uptake kinetics of diatom-size phytoplankton and to the functional grazing response of meso-zooplankton. Meso-zooplankton was more sensitive to alternate parameter values than was phytoplankton. Reduction of meso-zooplankton cross-shelf advection rates (crudely representing behavioral retention mechanisms) reduced the scale of model error relative to the observed seasonal mean inshore copepod biomass but had little effect of the modeled meso-zooplankton biomass offshore nor upon phytoplankton biomass across the entire shelf.     

A simulation model for organic phosphorus transformation in a forest soil ecosystem

A numerical model which simulates the decomposition of litter and mineralization and immobilization of P in the humus layer of a temperate forest (beech site of Solling) is described. The model takes into account the effect of moisture, temperature and C/N ratio. The simulated concentration of P in the effluent of the humus layer agrees well with the measured values. The model predicts an increase in the C/P ratio of the unde-composed litter with time and that there is no direct mineralization of P from litter without passing through a microbial body. The net rate of mineralization is, however, always positive with its highest peak in July. Maximum immobilization of P from solution occurs in June and the minimum in January.The model is stable against changes in the litter input, its C/P ratio and other initial conditions, but it is very sensitive to changes in the efficiency factor which represents the fraction of decomposed C incorporated into microbial tissue. This is a site-specific model but can be used for grassland or agricultural systems with changes in certain parameters.     

A holistic approach to the development of sustainable agriculture: application of the ecosystem health model

Serious resource depletion has made sustainable agriculture an important and pressing issue for scientists, policy makers, and stakeholders worldwide, particularly in developing countries. Researchers have focused on methods to assess agriculture correctly, and to introduce sound solutions for sustainability, but have reached no agreement. In this paper, we introduce the theoretical framework of the agro-ecosystem health model, a new holistic approach, and apply it at a regional scale using four aspects (4S): sound structure, stable function, safe service, and sustainable development. We examine how 12 indicators of an agro-ecosystem health assessment (AHA) were selected using three dimensions based on this theoretical framework. In an AHA, we used an amoeba approach to examine a high-yield agro-ecosystem in Huantai County, Shandong Province, China. The results indicate that this model of ecosystem health can reflect the complex ecological, economic, and human conditions of an agro-ecosystem and evaluate these conditions using perspectives pertinent to system structure, function, and responses (services).     

A comparison of sensitivity analysis and error analysis based on a stream ecosystem model

When individual model parameters must be measured in field or laboratory experiments, the provision of feedback information for allocation of research efforts is an important function of modeling. Both sensitivity analysis and Monte Carlo error analysis can be used to determine which parameters require intensified measurement effort. When both methods are applied to a stream ecosystem model, the assumptions of sensitivity analysis are violated if reasonable estimates of measurement errors on parameters are used. Sensitivity analysis estimates a linear relationship between a state variable and a parameter and largely ignores higher order effects.In the model investigated in this study, higher-order effects dominate prediction error, and the results of sensitivity analysis are misleading. It is suggested that the simple correlation coefficient derived from analysis of Monte Carlo simulations is a more reasonable way to rank model parameters according to their contribution to prediction uncertainty. For the stream model used in this study, halving variance on the four parameters, indicated as most important by sensitivity analysis, reduces prediction errors by only 2–6%. Halving variance on the four, completely different, parameters with the largest simple correlation coefficients reduces prediction errors by 17–31%.     

Coupling a land use model and an ecosystem model for a crop-pasture zone

This paper describes the development of a land use model coupling ecosystem processes. For a given land use pattern in a region, a built-in regional ecosystem model (TESim) simulates leaf physiology of plants, carbon and nitrogen dynamics, and hydrological processes including runoff generation and run-on re-absorption, as well as runoff-induced soil erosion and carbon and nitrogen loss from ecosystems. The simulation results for a certain period from 1976 to 1999 were then used to support land use decisions and to assess the impacts of land use changes on environment. In the coupling model, the land use type for a land unit was determined by optimization of a weighted suitability derived from expert knowledge about the ecosystem state and site conditions. The model was applied to the temperate crop-pasture band in northern China (CCPB) to analyze the interactions between land use and major ecosystem processes and functions and to indicate the added value of the feedbacks by comparing simulations with and without the coupling and feedbacks between land use module and ecosystem processes. The results indicated that the current land use in CCPB is neither economical nor ecologically judicious. The scenario with feedbacks increased NPP by 46.78 g C m⁻² a⁻¹, or 32.23% of the scenario without feedbacks, also decreased soil erosion by 0.65 kg m⁻² a⁻¹, or 23.13%. Without altering the regional land use structure (proportions of each land use type). The system developed in this study potentially benefits both land managers and researchers.     

PIXGRO: A model for simulating the ecosystem CO2 exchange and growth of spring barley

A model, PIXGRO, developed by coupling a canopy flux sub-model (PROXEL_NEE; PROcess-based piXEL Net Ecosystem CO₂ Exchange) to a vegetation structure submodel (CGRO), for simulating both net ecosystem CO₂ exchange (NEE) and growth of spring barley is described. PIXGRO is an extension of the stand-level CO₂ and H₂O-flux model PROXEL_NEE, that simulates the NEE on a process basis, but goes further to include the dry matter production, partitioning, and crop development for spring barley. Dry matter partitioned to the leaf was converted to leaf area index (LAI) using relationships for the specific leaf area (SLA). The canopy flux component, PROXEL_NEE was calibrated using information from the literature on C3 plants and was tested using CO₂ flux data from an eddy-covariance (EC) method in Finland with long-term observations. The growth component (CGRO) was calibrated using data from the literature on spring barley as well as data from the Finland site. It was then validated against field data from two sites in Germany and partly via the use of MODIS remotely sensed LAI from the Finland site.Both the diurnal and the seasonal patterns of gross CO₂ uptake were very well simulated (R² = 0.92). A slight seasonal bias may be attributed to leaf ageing. Crop growth was also well simulated; simulated dry matter agreed with field observed data from Germany (R² = 0.90). For LAI, the agreement between the simulated and observed was good (R² = 0.80), giving an indication that functions describing the conversion of fixed CO₂ to dry matter and the subsequent partitioning leaf dry matter and LAI simulation were robust and provided reliable estimates.The MODIS LAI at a resolution of 1000 m agreed poorly (R² = 0.45) with the PIXGRO simulated LAI and the observed LAI at the Finland site in 2001. We attributed this to the coarse resolution of the image and/or the small size of the barley field (about 17 ha or 0.25 km²) at the Finland site. By deriving a regression relation between the observed LAI and NDVI from a higher resolution MODIS (500 m resolution), the MODIS-recalculated LAI agreed better with the PIXGRO-simulated LAI (R² = 0.86).PIXGRO provides a prototype model bridging the disciplines of plant physiology, crop modeling and remote sensing, for use in a spatial context in evaluating carbon balances and plant growth at stand level, landscape, regional, and with some care, continental scales. Since almost 50% of the European land surface is covered by crops, such a model is needed for the dynamic estimation of LAI and NEE of croplands.     

A grassland ecosystem model of the Xilingol steppe, Inner Mongolia, China

The natural grassland ecosystem of the Xilingol steppe has traditionally been the source of the most productive and highest quality agriculture in northern China. Unfortunately, the area is now experiencing degradation due to resource overuse. In an attempt to forecast grassland production and to sustain the ecosystem, we built a time-dependent simulation model of the ecosystem based on long-range weather forecasts (several weeks to several months). The model incorporated five state variables including above- and belowground biomass, the amount of standing dead plant material, livestock (sheep) weight, and the amount of excrement per unit ground area. Within the model, solar light energy is fixed by grassland vegetation and flows through the other variables via a variety of organism-environment interactions. The model was written using a set of simultaneous differential equations and was numerically analyzed. The values of the time-dependent parameters controlling energy flow were determined based on data accumulated in experiments and field surveys executed at a grassland experimental station located in Xilingol, as well as by reference to related literature. We used daily meteorological data including air temperature and rainfall recorded at the Xilinhot Meteorological Observatory. Simulated results for several stocking densities coincided well with the data of aboveground plant biomass observed at the experimental station in 1990, 1993, and 1997. We obtained reasonable simulation results for five stocking densities, three air temperature patterns, and five rainfall patterns. When a month-long drought, which sometimes occurs in this area, was forecast by a local weather station, a decrease in grassland production was forecast by the model. Such forecasts will assist in the management of livestock, forage preservation, and grassland conservation.     

Bioavailability of copper and cadmium in sediment of nanjing section of Changjiang river to aquatic organisms

Bioavailabilities of metals in sediment to aquatic organisms depend on the strength of metal bonding to particulates. The accumulation tests of Cu and Cd in carp and in snails have been studied in vitro with the solution containing semisynthetic sediment samples in which the contents of various speciation of metal in sediment have been extended. For carp, the accumulation of Cu and Cd is related to the concentration of dissolved metal which in turn is affected by the distributions of speciations in sediment under given environmental conditions. It is another pattern for snails, various speciations of metal in sediment can contribute indirectly to metal accumulation. The contribution ratio, or relative importance of various speciations of metal in sediment can be expressed by multiple linear regression formulas. The contribution of ion‐exchangable speciation and coprecipition with carbonate speciation is 10⁵ times larger than that of residue speciation in sediment.