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Geography investigates changes in physical structures and distributions of objects in spatiotemporal world, which are shaped by geographic process (geo-process). With extensive simulation models used to study geo-process, this paper examines the status of geo-process modeling (namely model-based simulation) for multidisciplinary geo-processes across scales in virtual geographic environments (VGEs). The conceptual framework of integrated modeling in VGEs is proposed with a review of specific issues, including model sharing and management, collaborative modeling and uncertainty analysis. The contribution of a model base in model reusability and modeling management, concerning input data, parameterization, and simulation output, is detailed. Finally, this paper concludes with a discussion of future research directions for holistic geo-process modeling. [ABSTRACT FROM AUTHOR]

The construction of ecological network or other continuous habitat is essential for urban eco-system; however, to quantify the heterogeneous functional connectivity for eco-network is academically attractive and challenging. The dynamic lines of space syntax, tenable to simulate perception and navigation flows in network-configured human settlements, is introduced to inspire idea and approach to modeling connectivity in eco-network, while the classical graphic notions and variables are assumed functional to new relationship between other species and eco-network. After mapping continuous functional components among land layout into free space and then into dynamic lines that influence bio-flows, the paper conducts an exploration on functional connectivity of Singapore's green network. Conclusions involves the distribution heterogeneity of basic variables, Connectivity , Control , Mean Depth and Integration , demonstrating each meaning for functional connectivity in the network, with a step-wise Integration further comparing the connectivity patterns under different behavioral ranges. Moreover, a scale robustness determined via linear regression between Integration and Connectivity reveals network functionality as behavioral scale varying. The analogical modeling of space syntax raised in this paper is adaptive and instructive, particularly if original essential traits remain valid between the substituted species and space, because several principles and characteristics of conventional connectivity models can be logically inherited, while the graphic notions of dynamic line shares unique advantages. [ABSTRACT FROM AUTHOR]

Abstract: In this paper the results of several new experiments concerning the allelopathic competition between the two algal species Chlorella vulgaris (C. vulgaris) and Pseudokirchneriella subcapitata (P. subcapitata) have been reported. They show that the growth rates of the two species are different and can be modeled by the Andrews function (P. subcapitata) and Michaelis–Menten one (C. vulgaris). They also prove that the two species have different yields and that allelochemicals produced by C. vulgaris (called chlorellin) produce inhibitory effects on P. subcapitata. These results have been used to validate a mathematical modeling approach widely applied in eco-toxicology. The validation test being based on the comparison between the experimental outcome of the competition and the possible dynamical behaviors exhibited by the mathematical model. The paper consists of two parts devoted to the experiments and to the mathematical model, respectively. The mathematical analysis of the experimental results allowed to compute the numerical values of some parameters appearing in the growth-rate functions of the two species, and in the function which represents the inhibitory effect of chlorellin. The stability properties of some biologically meaningful steady-state solutions have been investigated. Moreover, by means of numerical simulations, it has been shown that the outcome of the real competition is foreseen by our model, and it can be easily simulated, provided that suitable numerical values for the parameters and initial conditions are chosen. [Copyright &y& Elsevier]

Abstract: In any ecosystem the equilibrium condition may gradually turn into a chaotic situation for different reasons. In this paper a three species (phytoplankton, zooplankton and fish) model is proposed. Rate parameters are changed according to the change of the size of the organisms. The model is run in different conditions with different sizes of zooplankton by increasing the grazing rate and consequently decreasing the half saturation constant of this organisms following allometric principles. The system exhibits different states (equilibrium point–stable limit cycle–doubling and ultimately chaos) by gradual increment of zooplankton grazing rate and decrease of half saturation constant. This paper also tests the high level of exergy (thermodynamic goal function) of the systems at the edge of oscillation before entering into the chaotic situation. This high level of information supports the hypothesis that the system can coordinate the most complex behavior in these situations. [Copyright &y& Elsevier]

Abstract: An important topic in the registration of pesticides and the interpretation of monitoring data is the estimation of the consequences of a certain concentration of a pesticide for the ecology of aquatic ecosystems. Solving these problems requires predictions of the expected response of the ecosystem to chemical stress. Up until now, a dominant approach to come up with such a prediction is the use of simulation models or safety factors. The disadvantage of the use of safety factors is a crude method that does not provide any insight into the concentration–response relationships at the ecosystem level. On the other hand, simulation models also have serious drawbacks like that they are often very complex, lack transparency, their implementation is expensive and there may be a compilation of errors, due to uncertainties in parameters and processes. In this paper, we present the expert model prediction of the ecological risks of pesticides (PERPEST) that overcomes these problems. It predicts the effects of a given concentration of a pesticide based on the outcome of already performed experiments using experimental ecosystems. This has the great advantage that the outcome is more realistic. The paper especially discusses how this model can be used to translate measured and predicted concentrations of pesticides into ecological risks, by taking data on measured and predicted concentrations of atrazine as an example. It is argued that this model can be of great use to evaluate the outcome of chemical monitoring programmes (e.g. performed in the light of the Water Framework Directive) and can even be used to evaluate the effects of mixtures. [Copyright &y& Elsevier]

Abstract: In this paper we explore the possibilities of the network simulation method (NSM) to simulate the behaviour of an ecosystem with three or more interacting species. To check the capabilities of the method we have applied it to a model based on that proposed by [Kmet’, T., Holcík J., 1994. The diffusive Lotka-Volterra model as applied to the population dynamics of the German carp and predator and prey species in the Danube river basin. Ecol. Model. 74, 277–285] to explain the population explosion of the German carp in the Lower Danube. The mathematical model of our system is a diffusive Lotka-Volterra model, in which we suppose the birth rate of forage species to be time-dependent. The simplicity of modelling the introduction or extraction of individuals in a very short time is another interesting feature of the NSM, which allows the permanence or extinction of a species to be predicted. It is seen that the actual time that a new species is introduced in an stable oscillatory ecosystem is a determining factor not only as regards the modification of the maximum and minimum density values recorded for the oscillations of other species (or even their disappearance), but also as regards whether the new species manages to remain in the ecosystem. The possibility that NSM will provide information on how densities and flows evolve in the same simulation is used in this paper to know how the ecosystem itself behaves. [Copyright &y& Elsevier]

The problem of greenhouse effect due to the anthropogenic influence on the global cycles of greenhouse gases is discussed extensively in the scientific literature. This paper aims to contribute solving this problem by presenting the simulation results of a new model of combined carbon and methane biogeochemical cycles considering the spatial structure of their sources and sinks on a global scale. All reservoirs and fluxes of the carbon and methane that are taken into consideration in the model have different temporal scales, while the spatial scale for sources and sinks of carbon and methane on the land is considered as 4° by latitude and 5° by longitude. The World Ocean is parameterized by two-point models with four levels in depth with a separation between pelagic and upwelling zones. In addition, the interaction between the atmosphere and carbon reservoirs on the land and in the ocean includes the processes of photosynthesis, decomposition, respiration and burning. The global cycle of methane in the atmosphere-hydrosphere-land system is described by the scheme that takes into account the potential of the radiation fluxes, which is a function of time. Furthermore, the structure of the model used for the coupling of the carbon and methane cycles consists of 12 blocks, which carry out basic calculation procedures for their fluxes. Finally, the results of simulation experiments are discussed considering scenarios for changes in forest areas, showing their significant role in the climate change issue. [ABSTRACT FROM AUTHOR]

Individual-based or population-level simulation approaches are often employed alternatively in eco-epidemiological modeling. In this paper, we introduce an original coupling approach applied to bubonic plague zoonotic infection in the Pre-Balkhash focus (central Asia), with main host Rhombomys opimus (Rodentia: Gerbillidae) and vector its associated ectoparasite flea Xenopsylla gerbilli minax . An Individual-Based Model (IBM) is first developed as a Multi-Agent System (MAS), addressing the seasonally forced internal dynamics of a typical burrow system based upon individual processes and interaction rules of the host-vector parasitoid system. Key population parameters and incidence functions are derived from simulations on the IBM and introduced in a second stochastic Population-Level Model (PLM), operating at the level of a metapopulation composed of interacting communities occupying burrow systems. The methodology facilitates knowledge integration and encourages bridging scales at which determinant contagion processes occur. Through simulations, we bring new insights about conditions for the local persistence of plague in a seasonally constrained environment. Under the seasonal scenario where half of the fleas overwinter in an active state, the introduction of the plague pathogen in spring in a metapopulation composed of 20 communities leads in one case out of two to epizootics surviving the first winter, while the infection has a 5% chance of passing the second winter. If the metapopulation is extended to 70 communities, simulations suggest the same 5% chance is estimated for plague persisting almost 4 years. Optimal vector community sizes or host dispersal intensities for the persistence of epizootics are also highlighted by sensitivity analyses. [ABSTRACT FROM AUTHOR]

MOM A (Model Of Mosquito Aedes) is a spatially explicit agent-based simulation model of Aedes aegypti female mosquito, the dengue vector. The model aims to produce statistical data on mosquito behaviours and population dynamics that are difficult to obtain through field surveys such as population densities in various geographical and climatic conditions. It can also be used to explore effects of vector control strategies on population dynamics. The model simulates adult mosquitoes as ‘agents’ which interact with their local environment. The latter provides resources for their biological development and can also constrain their flight or egg-laying behaviours. Variations in environmental configurations such as land-use and climate make it possible to explore the dependence of mosquito population dynamics on the context. This paper gives a detailed description of the model's various components and the overall approach used to calibrate and validate it. Study of simulated mosquito behaviours reveals the model's ability to produce the mosquito's realistic life cycle. The mosquito cohort's flight distance in various urban landscapes is also explored. The latter represent a developing neighbourhood in Delhi (India) processed using a Geographical Information System (GIS). The initial results reveal a significant relation between urban topology, human densities and adult mosquito flight. [ABSTRACT FROM AUTHOR]

The worldwide increase in the hazelnut demand and cultivated area are explained by the rising importance of this species for the food industry. However, no simulation models are available to support the analysis of the impact of environmental conditions and management practices on hazelnut production. This paper presents two modelling solutions to simulate hazelnut tree growth and development under potential and water-limiting conditions, partly based on generic approaches used in tree modelling and on new modules specifically developed to address hazelnut tree peculiarities. The two solutions differed in the simulation of the photosynthetic rate, in one case reproduced using a Farquhar-type model (gross photosynthesis), whereas a radiation use efficiency approach (net photosynthesis) was used in the other. The coherence of simulation outputs at leaf, organ and plant level and the models responsiveness to weather conditions was verified and discussed with literature data, and the performances of the modelling solutions were evaluated using experimental data collected between 2002 and 2013 growing seasons in Piedmont region (northern Italy). Results highlighted the reliability of both the solutions in reproducing phenological development (mean relative root mean squared error, RRMSE = 8.61%), as well as the time trend of specific leaf area (RRMSE = 26.32%) and leaf area index (RRMSE = 18.46%). Also, the simulation of the temporal dynamics of soil water content and temperature along the soil profile led to outputs very close to observations (RRMSE = 14.02% and 10.32%, respectively). The solution based on gross photosynthesis resulted slightly more accurate in reproducing the year-to-year fluctuation in yields (RRMSE = 25.03%) compared to the one based on net photosynthesis (RRMSE = 30.40%). These results proved the suitability of these modelling solutions to be used as simulation engines within a variety of applications, ranging from decision support systems for the management of the orchard to complex yield forecasting systems. [ABSTRACT FROM AUTHOR]

For more than a century, planted shelterbelts in Saskatchewan, Canada have protected farmyards from the elements, decreased soil erosion, sequestered atmospheric carbon, as well as provided many other ecological functions. It is estimated that there are >60,000 km of planted shelterbelts throughout the province, and considerably more in all of the Canadian Prairies. This paper details the overall process of quantifying and mapping the carbon stocks in white spruce ( Picea glauca ) shelterbelts planted in Saskatchewan. Shelterbelt data collected from field sampling sites, which were identified by a unique site selection approach, were used to parameterize two models for use in shelterbelt systems; an independent data set was used to validate model predictions. Shelterbelt tree growth was modeled with the Physiological Principles in Predicting Growth (3PG) model, and carbon flux and stocks in shelterbelts were modeled with the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3). Annual total ecosystem carbon (TEC) flux in white spruce shelterbelts increased one order of magnitude, from −0.33 to 4.4 Mg C km −1 yr −1 , for age 1–25 years, and reached a peak of 5.5 Mg C km −1 yr −1 (age 39 years). An initial soil carbon loss from the shelterbelt, caused by the land-use change, was offset in full by tree growth by age 17, 18, and 21 years for trees planted at 2.0, 3.5, and 5.0 m spacing within a row, respectively. Increase in carbon stocks, after 60 years of growth, was predicted in the litter layer (21.8 Mg C km −1 ), belowground biomass (26.1 Mg C km −1 ), and aboveground biomass (117.6 Mg C km −1 ). Across all the different provincial soils, carbon additions were 106–195 Mg C km −1 in 60-yr-old white spruce shelterbelts. Cumulatively, accounting for eight decades of white spruce shelterbelt planting and tree growth, carbon additions totaled 50,440 Mg C province-wide in 991 km of white spruce shelterbelts. The C additions represented 38% of the province-wide TEC stocks, which totaled 131,750 Mg C. The cumulative carbon storage in all components of planted white spruce shelterbelts far exceeded the initial carbon levels present at the time of shelterbelt planting. [ABSTRACT FROM AUTHOR]

The remobilization of carbon reserves accumulated in stems during vegetative growth is known to significantly contribute to yield formation in many cereals, and to be modulated by water and nitrogen availability during grain filling. However, despite the extensive use of crop models to support irrigation and fertilization plans, current knowledge on carbohydrate remobilization is rarely formalized in the available simulation tools. This paper presents a model to simulate carbohydrate remobilization in rice, based on the balance between source (i.e., the carbon reserves in stems) and sink (i.e., the grains) strength and on the impact of water stress and nitrogen luxury consumption. The new approach was included in the WARM model and evaluated using data from published experiments where two cultivars were grown under two nitrogen fertilization levels and two irrigation strategies. Results highlighted the model effectiveness in reproducing the amount of remobilization under non stressed conditions ( R 2 = 0.99), as well as the impact of water and nitrogen availability (average R 2 = 0.97) for Indica and Japonica rice cultivars. The proposed model can be easily plugged into available rice simulators to increase their adherence to the underlying system. [ABSTRACT FROM AUTHOR]

In this paper, we study the dynamics of a time fractional order toxic-phytoplankton–phytoplankton–zooplankton system (TPPZS). Routh–Hurwitz criteria is applied to discuss the stability analysis of biologically feasible equilibrium points for the given system in terms of reproduction numbers (associated with ecological as well as disease phenomena). Local stability properties of the toxic-phytoplankton-free equilibrium are also investigated. Numerical simulations are performed for a hypothetical set of parameter values in support of our analytic results. [ABSTRACT FROM AUTHOR]

There are different methods for quantifying the relative contribution of input-variables to the nonlinear regression function provided by a Multilayer Perceptron. Unfortunately most of the systematic method comparisons available to date suffer from a set of characteristic shortcomings. This paper elaborates on these methodological shortcomings and presents a simulation study that demonstrates how to avoid them in future method comparisons. Results of the simulation study indicate that Garson's weight method is preferable to the connection weight method proposed by Olden et al., (2004) for each of the samples simulated. [ABSTRACT FROM AUTHOR]

Drosophila mediopunctata belongs to the tripunctata group, which is the second largest Neotropical group of the Drosophila genus, with 64 species described. This paper presents a p-fuzzy system to describe its population dynamics. An approach using fuzzy set theory was chosen to handle some problems of uncertainty in knowledge-based modeling. This model is based on population density, climatic variation and extractive activity. Simulations allow us to visualize the behavior of the population in different environments and seasons of the year. The results are consistent with previous studies showing that in preserved area the population exhibits oscillations with return to equilibrium while in altered area it can be extinguished after a certain time. [ABSTRACT FROM AUTHOR]

Abstract: While they can be useful tools to support decision-making in ecosystem management, robust simulation models of ecosystems with alternative states are challenging to build and validate. Because of the possibility of alternative states in model dynamics, no trivial criteria can provide reliable and useful metrics to assess the goodness-of-fit of such models. This paper outlines the development of the model TRITON, and presents simulation-based validation and analysis of model sensitivity to input parameters. TRITON captures the local dynamics of seaweed-based rocky reef communities in eastern Tasmania, which now occur in two alternative persistent states: (1) either as dense and productive seaweed beds, (2) or as sea urchin ‘barrens’ habitat, i.e. bare rock largely denuded of macroalgae and benthic invertebrates due to destructive grazing by sea urchins. Pattern-oriented-modelling, i.e. comparing patterns in model dynamics across Monte–Carlo simulations with direct observations of Tasmanian reef communities over large scales, provides a valuable approach to calibrate the dynamics of TRITON. Using the computationally efficient, model-independent extended Fourier amplitude sensitivity test, we identify fishing down of predatory lobsters, sea urchin recruitment rate, as well as seaweed growth rate as key parameters of influence on overall model behaviour. Through a set of independent sensitivity tests, we isolate different sets of drivers facilitating the ‘forward’ shift from the seaweed bed to the urchin-dominated state, and the reverse or ‘backward’ shift from denuded sea urchin barren to recovery of seaweed cover. The model suggests that rebuilding populations of large rock lobsters, which predate the urchins, will be effective in limiting ongoing formation of sea urchins barrens habitat, but that the chances of restoring seaweed beds from extensive barrens are relatively low if management relies solely on rebuilding stocks of large rock lobsters. Moreover, even when it does occur, seaweed bed restoration takes up to three decades in the simulations and so is arguably unrealistic to implement under short-term fishery management plans. The process of model validation provided both a better understanding of the key drivers of community dynamics (e.g. fishing of predatory lobsters), and an assessment of priority areas for future research. [Copyright &y& Elsevier]

Tropical mountain forest in the Andes of southeastern Ecuador is regularly destroyed to gain pasture land by cultivating the C4 grass Setaria sphacelata. After recurrent burning of the pastures, the grass is partly outcompeted by the C3 southern bracken (Pteridium arachnoideum). This competition represents the problematic of pasture degradation and increasing deforestation, due to the necessity of new pasture land. Because no information on the growth potential of both species in the Andes of Ecuador is available, a growth simulation model has been improved and properly parameterized with field observations. The measured species- and site-specific physiological and edaphic parameters are presented in this paper, as well as the model validation with field observations of leaf CO2 assimilation. The validation showed deviations of simulated from observed leaf net assimilation lower than 5% of the observed values. The validated model was run with a fully realistic meteorological forcing of the year 2008 (10min time step). The main result points to slightly higher growth potential of Setaria with 5879gm−2 a−1, based on an annual CO2 net assimilation rate of 217molCO2 m−2 a−1. The calculated growth potential of bracken was 5554gm−2 a−1, based on the CO2 net assimilation of 197molCO2 m−2 a−1. In addition, it was shown that decreasing incoming solar radiation and low temperature are favourable weather conditions for bracken in contrary to the pasture grass Setaria. [Copyright &y& Elsevier]

Abstract: The double-crested cormorant is a native North American waterbird that recently underwent a dramatic population expansion. Population control efforts in the USA and Canada attempt to mitigate cormorant damages to natural resources and aquaculture. However, there is currently no coordination among the various stakeholders involved in management activities as well as no attempt to optimize population control efficiency. In this paper, we present for the first time a spatially explicit stage-structured metapopulation model parameterized for the cormorant. We developed simulation tools to get insights into the efficiency gain that can be expected from a better planning of management activities in both space and time. A case study is presented, in which we randomized where (on which colonies) and when (which years) a pre-determined amount of management activities would occur on 4 or 8 of 16 active colonies arranged on a 4×4 or 2×8 spatial grid over a period of 8 years, including 2 or 4 management years. We calculated two indices measuring the location of management activities, namely the average date of management years and the average degree of peripherality of colonies undertaking management, together with two indices measuring the resulting correlation of management activities, i.e., the degree of clustering of management activities both in space and time. Different spatio-temporal configurations of management activities generally yielded different metapopulation trajectories. Room for improving management efficiency increased with the intensity of management activities. However, the greatest efficiency gains are to be expected when colonies are far from carrying capacity, while the majority of management operations are undertaken when colonies are near or at carrying capacity. Locations of management activities in space and time appeared more important than resulting spatio-temporal correlations to explain the dispersion of metapopulation trajectories. When colonies were far from their individual carrying capacity, management was more efficient when applied earlier (a consequence of delayed reproductive maturity) and to more central colonies (due to greater immigration). The situation was more complex when colonies were closer to or at carrying capacity. Our modelling framework is flexible enough to allow more complex scenarios to be investigated in the future. [Copyright &y& Elsevier]

Ecological agriculture (eco-agriculture) is an approach to agriculture that seeks a balance between ecological and economic benefits to promote the sustainable development of both. This paper proposes a scientific method for analyzing the environmental and economic effects of eco-agriculture and simulating their long-term trend. Here, we focus on the eco-agriculture system of Kongtong District, Pingliang City, Gansu Province, China, and we build a system dynamics model named “AEP-SD” to evaluate the integrated effects of the system from 2009 to 2050. Under business as usual conditions, simulation results show rapid improvement until a peak is reached in 2027, after which the system will decline gradually. The model identifies some defects and disadvantages of the current agriculture system, such as the excessive increase of cattle slaughter, unstable production of methane, slow development of organic agriculture, and unsustainable energy structure. System improvement policies are offered and then proven by the model that they can indeed reduce the negative effects and eliminate the potential risks of system decline. [Copyright &y& Elsevier]

Different methodologies for evaluating aspects of model performance going beyond the pure agreement between measured and simulated data have been recently proposed. These indicators and criteria for the evaluation of, e.g., complexity and robustness can be used in conjunction with well-known metrics for the evaluation of model accuracy – such as root mean square error and modelling efficiency – to get a deeper knowledge about models structure and behaviour. The aim of this paper is to propose an indicator of model plasticity, defined as the aptitude of a model to change the sensitivity to its parameters while changing the conditions of application. Sensitivity was here analyzed using the Sobol’ method for sensitivity analysis (SA). Concordance among parameters relevance (total order effect) estimated under different conditions allowed to quantify changes in the way models react to different environments. The concordance among the different SA results was related to the variability of a normalized agrometeorological indicator used to characterize the explored conditions. The plasticity indicator was tested using three different crop models (WARM, CropSyst, WOFOST; rice was simulated), 10 European locations, and 10 years for each location, for a total of 5,939,200 simulations and 300 SA experiments. Results indicated WOFOST as the most plastic, both within location, year, and using all the combinations location×year, whereas WARM showed to be the less plastic across the conditions explored. Previous studies carried out on the same models in northern Italy seem to suggest a direct relationship between model complexity and plasticity, whereas model accuracy seems to be unrelated to these features. This consideration underlines that, in case of availability of different models with a similar degree of accuracy, different choices should be performed for different modelling studies, characterized by different aims and conditions of application. [Copyright &y& Elsevier]

Simulated phytoplankton assemblages (species richness and allocation of cells to species) retaining the diversity, evenness, and redundancy of natural assemblages were generated in the present paper. The methodology was validated against phytoplankton data from coastal Mediterranean waters, characteristic of oligotrophy to eutrophication. Two modelling approaches were used: a descriptive based on the log series statistical distribution, and a mechanistic based on the random fraction niche-apportionment model. Two characteristic relationships extracted from field data (888 samples), relating species richness and the abundance of the most dominant species with cell density, formed the basis of the modelling procedure. Simulated assemblages generated by both log series and random fraction models closely matched the structure of natural phytoplankton assemblages, showing however differences in their behaviour and easiness of application. Simulation by the log series model resulted in a wider range of assemblage diversity, closer to reality compared to random fraction model. Nevertheless, the latter includes a stochastic element always present in field assemblages, it is mathematically simpler to be applied, and it is based on a sound theoretical basis linking assemblage structure and resource availability. The proposed simulated assemblages can be used in a variety of applications ranging from the development of systematic methodologies for water quality assessment to the incorporation of a multispecies phytoplankton component in biogeochemical dynamic models. [Copyright &y& Elsevier]

This paper describes a comprehensive model of wastewater treatment in secondary facultative ponds, which combines 3D hydrodynamics with a mechanistic water quality model. The hydrodynamics are based on the Navier–Stokes equation for incompressible fluids under shallow water and Boussinesq assumptions capturing the flow dynamics along length, breadth and depth of the pond. The water quality sub model is based on the Activated Sludge Model (ASM) concept, describing COD and nutrient removal as function of bacterial growth following Monod kinetics, except for Escherichia coli removal, which was modelled as first order decay. The model was implemented in the Delft3D software and was used to evaluate the effect of wind and the addition of baffles on the water flow pattern, temperature profiles in the pond and treatment efficiency. In contrast to earlier models reported in the literature, our simulation results did not show any significant improvement in COD removal (based on the ASM concept) with addition of baffles or under intermittent wind-induced mixing. However, E. coli removal efficiency, based on a first order decay approach, showed a fair improvement in the presence of baffles or intermittent wind-induced mixing. Furthermore, simulations with continuous wind effect showed a decrease in removal efficiency for COD but a further increase in E. coli removal efficiency. Such contrasting results for two different approaches in modelling could indicate that the first order decay concept might not be appropriate to describe all the interactions between biochemical processes in a pond. However, these interpretations remain theoretical, as the model needs validation with field data. [Copyright &y& Elsevier]

Land-use change models are typically calibrated to reproduce known historic changes. Calibration results can then be assessed by comparing two datasets: the simulated land-use map and the actual land-use map at the same time. A common method for this is the Kappa statistic, which expresses the agreement between two categorical datasets corrected for the expected agreement. This expected agreement is based on a stochastic model of random allocation given the distribution of class sizes. However, when a model starts from an initial land-use map and makes changes to it, that stochastic model does not pose a meaningful reference level. This paper introduces K Simulation, a statistic that is identical in form to the Kappa statistic but instead applies a more appropriate stochastic model of random allocation of class transitions relative to the initial map. The new method is illustrated on a simple example and then the results of the Kappa statistic and K Simulation are compared using the results of a land-use model. It is found that only K Simulation truly tests models in their capacity to explain land-use changes over time, and unlike Kappa it does not inflate results for simulations where little change takes place over time. [Copyright &y& Elsevier]

For a large number of environmental studies, it is necessary to modelize numerical vegetal sets as trees or tree crowns. Studies on forest fire propagation or analysis of the photosynthesis in vegetation canopy are some examples. The first step for these studies is to construct vegetation like shapes. The aim of this paper is to propose a new methodology allowing to generate a vegetal set by a fractal approach. Iterated Function Systems (IFS) are associated with a genetic algorithm in order to determine the IFS parameters with respect to some morphological properties of real tree crowns as the Leaf Area Index (LAI) vertical distribution. This new methodology is applied and validated on fifteen deciduous tree and two of them are fully developed: Quercus prinus and Populous tremuloides. A sensitivity study is carried out for the IFS parameters to better understand the influence of each ones on the tree reconstruction. This new methodology has been applied on various tree species in order to provide a data base summarizing the IFS parameters to easily generate realistic tree crowns for further works. [Copyright &y& Elsevier]

The present paper reports how stand size–structure dynamics due to competition between different-sized trees affect long-term forested water balance in Japanese cool-temperate planted stands (evergreen coniferous Cryptomeria japonica and deciduous coniferous Larix kaempferi stands) using a fully coupled multi-layered meteorological surface physics—terrestrial ecosystems model. The simulation captured the well-known annual variation in leaf area index (LAI) accurately with stand age in monocultured and even-aged stands; the occurrence of maximum LAI during the early growth stage and then a gradual decline followed by a steady state after the maximum LAI. The simulations also detected a high dependency of annual evapotranspiration (AETr) on LAI with stand age that is well known by prior observational researches. In the C. japonica (shade-tolerant late-successional species) stand, the relationship between annual net primary productivity of an individual tree (NPPind) and individual tree mass changed from linear to a convex curve during self-thinning, indicating that the degree of asymmetric tree competition intensified with forest stand development. The higher degree of competitive asymmetry characterized by the convex-shaped relationship produced greater size inequality, i.e., the formation of trees stratified by height. Under such conditions, AETr and annual transpiration (ATr) were mainly regulated by larger trees. On the other hand, the relationships in the L. kaempferi (shade-intolerant early-successional species) stand were linear throughout the simulated period, indicating the lower degree of competitive asymmetry. Under such conditions, the growth of intermediate-sized trees was enhanced and these trees became a dominant source of AETr (and also ATr) during self-thinning. Furthermore, the sensitivity analysis of the effects of ecophysiological parameters such as foliage profile (i.e., vertical distribution of leaf area density) of an individual tree (distribution pattern is described by the parameter η), the maximum carboxylation velocity (V cmax0) and biomass allocation pattern of individual plant growth (μ 1) on AETr, ATr and annual runoff (ARoff) showed that the temporal trends of AETr, ATr, ARoff and relationships were completely the same as those in the control simulations. However, the relationship during self-thinning indicated higher degrees of competitive asymmetry when η or V cmax0 were greater than those in the control simulation and generated greater AETr and ATr and thus smaller ARoff. We found that more asymmetric tree competition brings about greater size inequality between different-sized trees and thus more evapotranspiration and less runoff in a forest stand. Overall, our simulation approach revealed that not only LAI dynamics but also plant competition, and thus size–structure dynamics, in a forest ecosystem are essential to long-term future projections of forested water balance. [Copyright &y& Elsevier]

Physically based numerical modelling follows from the basic understanding of the underlying mechanisms and is often represented by a set of (partial differential) equations. It is one of the main approaches in population dynamics modelling. The emphasis of the model introduced in this paper is on the simulation of short-term spatial and temporal dynamics of harmful algal bloom (HAB) events. Total suspended matter (TSM) concentration is one of the dominant factors for harmful algal bloom (HAB) prediction in North Sea. However, the modelling of suspended matter contains a high degree of uncertainty in this area. Therefore, this research aims to achieve a better estimation for the short-term prediction of harmful algal bloom development in both space and time by using spatially distributed TSM retrieved from remotely sensed images as physically based model inputs. In order to supply complete spatially covered datasets for the physically based model instrument: generic ecological model (GEM), this research retrieves TSM information from MERIS images by means of proper estimation techniques including biharmonic splines and self-learning cellular automata. A better estimation of HAB spatial pattern development is achieved by adding spatially distributed TSM data as inputs to original GEM model, and it proved that chlorophyll-a concentration in this area is very sensitive to TSM concentration. [Copyright &y& Elsevier]

This paper describes the conceptualization and implementation of an agent-based model to investigate how varying levels of human presence could affect elements of wolf behavior, including highway crossings; use of areas in proximity to roads and trails; size of home ranges; activities, such as hunting, patrolling, resting, and feeding pups; and survival of individuals in Banff and Kootenay National Parks, Canada. The model consists of a wolf module as the primary component with five packs represented as cognitive agents, and grizzly bear, elk, and human modules that represent dynamic components of the environment. A set of environmental data layers was used to develop a friction model that serves as a base map representing the landscape over which wolves moved. A decision model was built to simulate the sequence of wolf activities. The model was implemented in a Java Programming Language using RePast, an agent-based modeling library. Six months of wolf activities were simulated from April 16 to October 15 (i.e., a season coherent with regard to known wolf behaviors), and calibrated with GPS data from wolf radiocollars (n =15) deployed from 2002 to 2004. Results showed that the simulated trajectories of wolf movements were correlated with the observed trajectories (Spearman''s rho 0.566, P <0.001); other critical behaviors, such as time spent at the den and not traveling were also correlated. The simulations revealed that wolf movements and behaviors were noticeably affected by the intensity of human presence. The packs’ home ranges shrank and wolves crossed highways less frequently with increased human presence. In an extreme example, a wolf pack whose home range is traversed by a high-traffic-volume highway was extirpated due to inability to hunt successfully under a scenario wherein human presence levels were increased 10-fold. The modeling prototype developed in this study may serve as a tool to test hypotheses about human effects on wolves and on other mammals, and guide decision-makers in designing management strategies that minimize impacts on wolves and on other species functionally related to wolves in the ecosystem. [Copyright &y& Elsevier]

Fire managers are now realizing that wildfires can be beneficial because they can reduce hazardous fuels and restore fire-dominated ecosystems. A software tool that assesses potential beneficial and detrimental ecological effects from wildfire would be helpful to fire management. This paper presents a simulation platform called FLEAT (Fire and Landscape Ecology Assessment Tool) that integrates several existing landscape- and stand-level simulation models to compute an ecologically based measure that describes if a wildfire is moving the burning landscape towards or away from the historical range and variation of vegetation composition. FLEAT uses a fire effects model to simulate fire severity, which is then used to predict vegetation development for 1, 10, and 100 years into the future using a landscape simulation model. The landscape is then simulated for 5000 years using parameters derived from historical data to create an historical time series that is compared to the predicted landscape composition at year 1, 10, and 100 to compute a metric that describes their similarity to the simulated historical conditions. This tool is designed to be used in operational wildfire management using the LANDFIRE spatial database so that fire managers can decide how aggressively to suppress wildfires. Validation of fire severity predictions using field data from six wildfires revealed that while accuracy is moderate (30–60%), it is mostly dictated by the quality of GIS layers input to FLEAT. Predicted 1-year landscape compositions were only 8% accurate but this was because the LANDFIRE mapped pre-fire composition accuracy was low (21%). This platform can be integrated into current readily available software products to produce an operational tool for balancing benefits of wildfire with potential dangers. [Copyright &y& Elsevier]

Many nearshore restoration projects are currently underway at coastal locations where human influence and development have disrupted natural habitat and coastal ecological systems. The objectives of these projects in general are to restore the lost estuarine functions to the tidal marshland. Often these projects are conducted with little understanding of the potential effects of other nearby projects within the ecosystem, and similarly, it is easy to neglect the effect of the local project on the larger estuarine scale. In this paper, a modeling study is presented to evaluate the hydrodynamic responses of multiple restoration projects and their cumulative effect in the Snohomish River estuary in Washington, USA. The concept of absolute mean tidal transport is introduced and used to measure the cumulative effect of the proposed restoration projects on the estuarine hydrodynamics. The results show that the hydrodynamic responses due to multiple restoration projects are additive in the estuary, and the effect is nonlinear. The hydrodynamic response under restoration conditions depends on the size of the restoration area and the geometric configuration of the existing river channels. Within a complex braided estuary such as the Snohomish, the influence of a specific restoration project is not only experienced locally, but also found to significantly affect tidal transport in all distributary branches within the system. [Copyright &y& Elsevier]

One of the mechanisms by which honeybees regulate division of labour among their colony members is age polyethism. Here the younger bees perform in-hive tasks such as heating and the older ones carry out tasks outside the hive such as foraging. Recently it has been shown that the higher developmental temperatures of the brood, which occur in the centre of the brood nest, reduce the age at which individuals start to forage once they are adult. It is unknown whether this effect has an impact on the survival of the colony. The aim of this paper is to study the consequences of the temperature gradient on the colony survival in a model on the basis of empirical data. We created a deterministic simulation of a honeybee colony (Apis mellifera) which we tuned to our empirical data. In the model in-hive bees regulate the temperature of the brood nest by their heating activities. These temperatures determine the age of first foraging in the newly emerging bees and thus the number of in-hive bees present in the colony. The results of the model show that variation in the onset of foraging due to the different developmental temperatures has little impact on the population dynamics and on the absolute number of bees heating the nest unless we increase this effect by several times to unrealistic values, where individuals start foraging up to 10 days earlier or later. Rather than on variation in the onset of foraging due to the temperature gradient it appears that the survival of the colony depends on a minimal number of bees available for heating at the beginning of the simulation. [Copyright &y& Elsevier]

The HOMINIDS ABM is a new Agent Based Model that simulates the actions of two species of proto-human agents defined by a few, simple parameters. These proto-human agents attempt to subsist by foraging and nesting on dynamic, spatially explicit landscapes. The landscapes are described with a number of parameters based on empirical field data collected in habitats in East Africa. The results of three separate scenarios with 1 year model runs repeated 30 times each, for a total of 90 simulations, are presented and discussed to illustrate both the capacity and flexibility of our ABM modeling environment. The simulations show that the model food preferences and anatomy ascribed to Australopithecus boisei resulted in different expressions of foraging behaviors and subsistence strategies in two distinct ecological settings, and that adding tubers to the diet significantly increases the chances of the hominid agents meeting their daily caloric requirements year-round. In addition, this paper provides links to the open-source implementation code, along with the user documentation, design document, java API, and all datasets required to replicate the simulations. [Copyright &y& Elsevier]

The benefits of genetically modified herbicide-tolerant (GMHT) sugar beet (Beta vulgaris) varieties stem from their presumed ability to improve weed control and reduce its cost, particularly targeting weed beet, a harmful annual weedy form of the genus Beta (i.e. B. vulgaris ssp. vulgaris) frequent in sugar beet fields. As weed beet is totally interfertile with sugar beet, it is thus likely to inherit the herbicide-tolerance transgene through pollen-mediated gene flow. Hence, the foreseeable advent of HT weed beet populations is a serious threat to the sustainability of GM sugar beet cropping systems. For studying and quantifying the long-term effects of cropping system components (crop succession and cultivation techniques) on weed beet population dynamics and gene flow, we developed a biophysical process-based model called GeneSys-Beet in a previous study. In the present paper, the model was employed to identify and rank the weed life-traits as function of their effect on weed beet densities and genotypes, using a global sensitivity analysis to model parameters. Monte Carlo simulations with simultaneous randomization of all life-trait parameters were carried out in three cropping systems contrasting for their risk for infestation by HT weed beets. Simulated weed plants and bolters (i.e. beet plants with flowering and seed-producing stems) were then analysed with regression models as a function of model parameters to rank processes and life-traits and quantify their effects. Key parameters were those determining the timing and success of growth, development, seed maturation and the physiological end of seed production. Timing parameters were usually more important than success parameters, showing for instance that optimal timing of weed management operations is more important than its exact efficacy. The ranking of life-traits though depended on the cropping system and, to a lesser extent, on the target variable (i.e. GM weeds vs. total weed population). For instance, post-emergence parameters were crucial in rotations with frequent sugar beet crops whereas pre-emergence parameters were most important when sugar beet was rare. In the rotations with frequent sugar beet and insufficient weed control, interactions between traits were small, indicating diverse populations with contrasted traits could prosper. Conversely, when sugar beet was rare and weed control optimal, traits had little impact individually, indicating that a small number of optimal combinations of traits would be successful. Based on the analysis of sugar beet parameters and genetic traits, advice for the future selection of sugar beet varieties was also given. In climatic conditions similar to those used here, the priority should be given to limiting the presence of hybrid seeds in seed lots rather than decreasing varietal sensitivity to vernalization. [Copyright &y& Elsevier]

Across forest ecosystems worldwide, alternative silvicultural practices such as partial or “structural retention” harvesting are gaining increasing use as means to balance economic and ecological management goals. Recent studies have documented highly elevated rates of residual-tree mortality and growth, both of which are likely to influence post-harvest stand development. Explicit consideration of residual-tree responses to partial harvest is therefore required to make accurate growth and yield predictions. In this paper we incorporate empirically based, spatially explicit tree growth and mortality predictors into a forest simulation model in order to quantify stand dynamics following a range of simulated partial harvests. We consider lowland black spruce boreal forests and use a common strip-cutting technique, Harvest with Advance Regeneration Protection, as a reference against which to compare alternative scenarios. Predicted stand development proceeded most rapidly in scenarios with reduced skidding impacts and relatively high levels of retention, since these treatments were associated with lower residual-tree mortality rates and larger growing stocks respectively. Stand development was also influenced on a proportional basis by residual-tree growth rates, which increased with declining neighbourhood competition. Across a range of harvest scenarios with equivalent retention levels (20%), differences in residual-tree responses among treatments led to a 35-year range in projected basal area return intervals (70–105 years). Our results demonstrate that short-term responses of residual trees affect stand development rates over long (>100-year) time scales, and show that post-harvest stand recovery rates are influenced not only by the retention level but also by the specific parameters of partial harvest prescriptions, including the layout of skid trails and the spatial arrangement of residual trees. Results from this study provide essential information for evaluating partial harvests in the black spruce boreal forest and supply modelling tools for assessing alternative silvicultural treatments in other forest ecosystems. [Copyright &y& Elsevier]

Harmful algae can cause damage to co-existing organisms, tourism and farmers. Accurate predictions of algal future composition and abundance as well as when and where algal blooms may occur could help early warning and mitigating. The Generic Ecological Model is an instrument that can be applied to any water system (fresh, transitional or coastal) to calculate the primary production, chlorophyll-a concentration and phytoplankton species composition. It consists of physical, chemical and ecological model components which are coupled together to build one generic and flexible modelling tool. In this paper the model has been analyzed to assess sensitivity of the simulated chlorophyll-a concentration to a subset of ecologically significant input factors. Only a small number of approaches could be considered as suitable for several reasons including the model complexity, engagement of numerous interacting parameters and relatively long time of a single simulation. Thus, sensitivity analysis has been carried out with the use of the Morris method and later enriched by the computation of the correlation ratios of the selected parameters on the model response at more than a few locations in the modelled area. The obtained results are in agreement with expert knowledge of the ecological processes in the North Sea and correspond well with local characteristics. [Copyright &y& Elsevier]

Forest fires have a significant economic, social, and environmental impact in Portugal. For that its fire risk was assessed through Bayes Formalism, where the main component of the risk of fire was assessed by the conditional probability of fire I(u,t) given a class of the daily severity rating (DSR) for a specific period of time—P[I(u,t)|R(u,t)]. The evaluation of this a posterior probability, P[I(u,t)|R(u,t)], was based on the update of marginal local probability of fire in each chosen region u (Durão, 2006). DSR values were used to calculate fire's risk, taking into account historical data, I(s,t), in a given region s, and also to define DSR's local thresholds in order to have P [I(u,t)|R(u,t)]≥0.65. In this paper we characterize these posterior probabilities using direct sequential simulation models (DSS models) to obtain the spatial distribution of these probabilities over the entire Portugal, in order to assess the risk of fire and associated spatial uncertainty. Local probability density functions (pdfs) and spatial uncertainty are evaluated by a set of equiprobable simulated images of these posterior probabilities. Results are presented and discussed for the Portuguese fire seasons of the 2-year period, 2003–2004. The conditional probabilities reproduced reasonably well what was officially published for the studied fire seasons. We expect that a better understanding of both spatial and temporal patterns of fire in Portugal together with uncertainty measures constitutes an important tool for managers, helping to improve the effectiveness of fire prevention, detection and fire fighting resources allocation in critical social and environmental areas. [Copyright &y& Elsevier]

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common. [Copyright &y& Elsevier]

Savannas are ecosystems known for their high environmental and economic value. They cover at least 20% of the global land surface and, in some cases, can act as a boundary between tropical rainforest and deserts. Water is an important determinant of savanna ecosystems. In this paper, we present a theoretical stochastic model of root competition for water, which couples, soil water availability, phenology, and root and shoot architecture applied to three Neotropical savanna grasses. Soil moisture was simulated using a daily balance, as proposed by Rodriguez-Iturbe et al. [Rodriguez-Iturbe, I., Porporato, A., Ridolfi, L., Isham, V., Cox, D.R., 1999. Probabilistic modelling of water balance at a point: the role of climate, soil and vegetation. Proc. R. Soc. London, Ser. A 455, 3789–3805.]. To simulate rainfall stochasticity, we used daily precipitation data from the airport weather station in the State of Barinas, Venezuela, for the period 1991–2007. Competition among neighbouring plants took into account the spatial distribution of the individuals. As a final step, the model allowed us to calculate the shoot dynamic of the species as a function of soil water availability. Using these data, we compared the behaviour of isolated plants, pairs and trios, and we found below-ground competition to be a fundamental component of global (shoot+root) competition. Finally, our model suggests various circumstances that allow poor competitor plants to coexist in competition for water with more successful competitors. Apparently, this is not only due to transpiration rates, but also to differences in shoot emergence and shoot growth. [Copyright &y& Elsevier]

The implementation of the European Water Framework Directive requires reliable tools to predict the water quality situations in streams caused by planned land use changes at the scale of large regional river basins. This paper presents the results of modelling the in-stream nitrogen load and concentration within the macro-scale basin of the Saale river (24,167km2) using a semi-distributed process-based ecohydrological dynamic model SWIM (Soil and Water Integrated Model). The simulated load and concentration at the last gauge of the basin show that SWIM is capable to provide a satisfactory result for a large basin. The uncertainty analysis indicates the importance of realistic input data for agricultural management, and that the calibration of parameters can compensate the uncertainty in the input data to a certain extent. A hypothesis about the distributed nutrient retention parameters for macro-scale basins was tested aimed in improvement of the simulation results at the intermediate gauges and the outlet. To verify the hypothesis, the retention parameters were firstly proved to have a reasonable representation of the denitrification conditions in six meso-scale catchments. The area of the Saale region was classified depending on denitrification conditions in soil and groundwater into three classes (poor, neutral and good), and the distributed parameters were applied. However, the hypothesis about the usefulness of distributed retention parameters for macro-scale basins was not confirmed. Since the agricultural management is different in the sub-regions of the Saale basin, land use change scenarios were evaluated for two meso-scale subbasins of the Saale. The scenario results show that the optimal agricultural land use and management are essential for the reduction in nutrient load and improvement of water quality to meet the objectives of the European Water Framework Directive and in view of the regional development plans for future. [Copyright &y& Elsevier]

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 46.78gCm−2 a−1, or 32.23% of the scenario without feedbacks, also decreased soil erosion by 0.65kgm−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. [Copyright &y& Elsevier]

Sensitivity analysis consists of an integral and important validatory check of a computer simulation model before the code is used in performing any kind of analysis operation. The present paper demonstrates the use of a relatively new method and tool for conducting global sensitivity analysis (GSA) for environmental models, providing simultaneously the first GSA study of the widely used 1d soil–vegetation–atmospheric transfer (SVAT) model named SimSphere. A software platform called the Gaussian emulation machine for sensitivity analysis (GEM SA), which has been developed for performing a GSA via Bayesian theory, is applied to SimSphere model in order to identify the most responsive model inputs to the simulation of key model outputs, detect their interactions and derive absolute sensitivity measures concerning the model structure. This study is also very timely in that, use of this particular SVAT model is currently being considered to be used in a scheme being developed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2016. The employed GSA method was found capable of identifying the most responsive SimSphere inputs and also of capturing their key interactions for each of the simulated target quantities on which the GSA was conducted. The most sensitive model inputs were the topography parameters (slope, aspect) as well as the fractional vegetation cover and soil surface moisture availability. The implications of these findings for the future use of SimSphere are discussed. [Copyright &y& Elsevier]

In marine ecosystems ecological and environmental conditions continuously change, possibly supporting the wide range of phytoplankton species coexisting in aquatic environments. Phytoplankton communities are not homogeneously distributed in the water column due to the spatial and temporal variability of turbulent mixing and the concurrent biological response. In this paper an individual-based model (Lagrangian method) simulating the basic physiology of two coexisting phytoplankton species has been developed. The species, sharing the same availability of light and nutrient resource, are characterized by different photo-physiological parameters. The spatial and temporal evolution of turbulent mixing is simulated introducing vertical profiles of measured eddy diffusivity. Three case studies have been examined to analyze the role of environment–individual interactions in determining bloom conditions for both the selected species. The organisms experience recurrent fluctuations of light, temperature, and nutrient concentration gradients, due to the turbulent mixing in the water column, which have significant effects on the growth of the phytoplankton species. In all the numerical experiments, the temporal and spatial variability of different forcings do not support the prevalence of one species over the other over the time scale typical of a phytoplankton bloom. A well mixed water column favours the growth of both the populations while a variable mixing regime limits their growth reducing the photophysiological differences between the species. [Copyright &y& Elsevier]

Detention areas provide a means to lower peak discharges in rivers by temporarily storing excess water. In the case of extreme flood events, the storage effect reduces the risk of dike failures or extensive inundations for downstream reaches and near the site of abstraction. Due to the large amount of organic matter contained in the river water and the inundation of terrestrial vegetation in the detention area, a deterioration of water quality may occur. In particular, decay processes can cause a severe depletion of dissolved oxygen (DO) in the temporary water body. In this paper, we studied the potential of a water quality model to simulate the DO dynamics in a large but shallow detention area to be built at the Elbe River (Germany). Our focus was on examining the impact of spatial discretization on the model¿s performance and usability. Therefore, we used a zero-dimensional (0D) and a two-dimensional (2D) modeling approach in parallel. The two approaches solely differ in their spatial discretization, while conversion processes, parameters, and boundary conditions were kept identical. The dynamics of DO simulated by the two models are similar in the initial flooding period but diverge when the system starts to drain. The deviation can be attributed to the different spatial discretization of the two models, leading to different estimates of flow velocities and water depths. Only the 2D model can account for the impact of spatial variability on the evolution of state variables. However, its application requires high efforts for pre- and post-processing and significantly longer computation times. The 2D model is, therefore, not suitable for investigating various flood scenarios or for analyzing the impact of parameter uncertainty. For practical applications, we recommend to firstly set up a fast-running model of reduced spatial discretization, e.g. a 0D model. Using this tool, the reliability of the simulation results should be checked by analyzing the parameter uncertainty of the water quality model. A particular focus may be on those parameters that are spatially variable and, therefore, believed to be better represented in a 2D approach. The benefit from the application of the more costly 2D model should be assessed, based on the analyses carried out with the 0D model. A 2D model appears to be preferable only if the simulated detention area has a complex topography, flow velocities are highly variable in space, and the parameters of the water quality model are well known. [Copyright &y& Elsevier]

Abstract: The interactions between bed sediments and the water column in shallow, eutrophic lakes have tremendous implications for the fate and transport of nutrients in those water bodies. This has resulted in the development of water quality models for lakes incorporating the processes of sediment resuspension. Reliable resuspension models are thus needed to accurately represent this phenomenon. In this paper, three different sediment-resuspension models are combined with a hydrodynamic and water quality model, dynamic lake model-water quality (DLM-WQ), and the resulting models are used to simulate nutrient distributions in the highly eutrophic Salton Sea, California, USA. One of the resuspension formulas is based upon sediment characteristics as well as the bed shear stress exerted by wind-induced waves and currents, while the other two are standard, power-law-type formulas for cohesive sediments with two different exponents. The outputs for water quality variables, such as temperature, chlorophyll a, dissolved oxygen and nutrients, obtained from the three resulting models and from an earlier DLM-WQ run with a simple empirical sediment-resuspension model are compared with measured data. The level of agreement between the simulations and the measured data is assessed by using both statistical and graphical model evaluation methods, including measures of residual errors, sample autocorrelations, t-tests, and box plots. Based on these assessments, DLM-WQ with an extended version of the García and Parker [García, M.H., Parker, G., 1993. Experiments on the entrainment of sediment into suspension by a dense bottom current. J. Geophys. Res.-Oceans 98, 4793–4807] relationship gave the best results for water quality in the Salton Sea, confirming that the use of formulas with more information on the sediment characteristics yields more accurate results. To the best of our knowledge, this is the first effort to combine water quality models for lakes and reservoirs with a sediment-resuspension model which was originally intended for open-channel flows. The simulations confirm that sediment resuspension is the most dominant process in the Salton Sea''s nutrient cycling. The effect of proposed physical changes to the Salton Sea on water quality characteristics is also addressed. [Copyright &y& Elsevier]

The search for a balance between nature conservation and tourism development within protected areas is becoming an increasingly multifaceted problem worldwide, as outlined by an increasing number of authors and highlighted at several international events. Since it is unlikely that all management objectives will reach their optimum values simultaneously, an optimization approach is required to meet multiple, conflicting goals and to obtain an overall trade-off in terms of the conceived objectives. In this paper we propose a new model for optimizing the allocation of tourist infrastructures (refuges and camping sites), and apply it to a protected area in the European Alps, where tourism has grown considerably in recent years. To reach this goal, a complex model based on genetic algorithms was required (instead of a common multicriteria analysis) to obtain a complex interplay in the form of a dynamical simulation where candidate solutions are interactively evaluated. In accordance with local actors, we selected 18 quantifiable criteria encompassing all relevant tourist activities within the study area. These were translated into geographic information system (GIS) layers, submitted to a genetic optimization procedure and compared the performances of the optimized tourist allocations with those of existing infrastructures and with worst case scenarios. Resulting tourist allocations perform very well, while existing tourist sites behaved halfway between the fittest and the least fit genetic solutions, since they prioritized logistic and safety criteria rather than ecological ones. The proposed model is a very flexible and effective tool, easily exportable to any protected area, with implications for researchers and policymakers who aim to provide an effective balance between nature and human impact. [Copyright &y& Elsevier]

In order to provide reliable scientific advice and support for fisheries management, it is necessary to evaluate the biological and economic sustainability of complex fisheries, such as multi-species multi-fleet fisheries. Existing policy-screening modelling tools are not fully suitable in this purpose due to either an over-simplified description of population dynamics, or due to the lack of consideration of economic aspects. In this paper, we present a package that enables quantitative bioeconomic assessment of management scenarios. Population dynamics is described through spatially- and seasonally-explicit models. Exploitation dynamics is characterized by several fishing activities with specific spatial and seasonal features, and practiced by several kinds of vessels with specific technical characteristics. Exploitation costs and revenues are considered at several levels: the fishing trip, the fishing unit (vessel and crew), and the vessel owner. The model is generic and can be used for different types of fisheries. A database is attached to the software for the storage and updating of information for each fishery. This includes the specification of model dimensions and of the parameters describing populations and exploitation. Several model assumptions regarding either population or exploitation may be adapted to suit a specific fishery. Both policies and corresponding fishers’ response may be interactively specified through JAVA™ scripts. This version of ISIS-Fish allows for the calculation of biological and economic consequences of a range of policies, including conventional ones like catch and effort controls, and alternative policies such as marine protected areas. To facilitate policy-screening in a high-dimension parameter space, the software includes features, like interfaces for sensitivity analysis and simulation queues. [Copyright &y& Elsevier]

In this paper, we report an application of neural networks to simulate daily nitrate-nitrogen and suspended sediment fluxes from a small 7.1km2 agricultural catchment (Melarchez), 70km east of Paris, France. Nitrate-nitrogen and sediment losses are only a few possible consequences of soil erosion and biochemical applications associated to human activities such as intensive agriculture. Stacked multilayer perceptrons models (MLPs) like the ones explored here are based on commonly available inputs and yet are reasonably accurate considering their simplicity and ease of implementation. Note that the simulation does not resort on water quality flux observations at previous time steps as model inputs, which would be appropriate, for example, to predict the water chemistry of a drinking water plant a few time steps ahead. The water quality fluxes are strictly mapped to historical mean flux values and to hydro-climatic variables such as stream flow, rainfall, and soil moisture index (12 model input candidates in total), allowing its usage even when no flux observations are available. Self-organizing feature maps based on the network structure established by Kohonen were employed first to produce the training and the testing data sets, with the intent to produce statistically close subsets so that any difference in model performance between validation and testing has to be associated to the model and not to the data subsets. The stacked MLPs reached different levels of performance simulating the nitrate-nitrogen flux and the suspended sediment flux. In the first instance, 2-input stacked MLP nitrate-nitrogen simulations, based on the same-day stream flow and on the 80-cm soil moisture index, have a performance of almost 90% according to the efficiency index. On the other hand, the performance of 3-input stacked MLPs (same-day stream flow, same-day historical flux, and same-day stream flow increment) reached a little more than 75% according to the same criterion. The results presented here are deemed already promising enough, and should encourage water resources managers to implement simple models whenever appropriate. [Copyright &y& Elsevier]

Plant–pollinator interaction networks are characterized by several features that cannot be obtained from a totally random network (e.g. nestedness, power law distribution of degree specialization, temporal turnover). One reason is that both plants and pollinators are active for only a part of the year, and so a plant species flowering in spring cannot interact with a pollinator species that is active only in autumn. In this paper we build a stochastic model to simulate the plant–pollinator interaction network, taking into account the duration of activity of each species. To build the model we used an empirical plant–pollinator network from a Mediterranean scrub community surveyed over four years. In our simulated annual cycle we know which plant and pollinator species are active, and thus available to interact. We can obtain simulated plant–pollinator interaction networks with properties similar to the real ones in two different ways: (i) by assuming that the frequency distribution of both plant and pollinator duration of activity follow an exponential function, and that interaction among temporally coexisting species are totally random, and (ii) by assuming more realistic frequency distributions (exponential for pollinators, lognormal for plants) and that the interaction among coexisting species is occurring on a per capita basis. In the latter case we assume that there is a positive relationship between abundance and duration of activity. In our model the starting date of the species activity had little influence on the network structure. We conclude that the observed plant–pollinator network properties can be produced stochastically, and the mechanism shaping the network is not necessarily related to size constraints. Under such conditions co-evolutionary explanations should be given with caution. [Copyright &y& Elsevier]

Forest development can be predicted by the use of forest simulators based on various statistical models describing the forest and its dynamics. One potential approach to study the reliability of the simulators is to utilise Monte Carlo simulation techniques to generate a predictive distribution of a forest characteristic. One problem in examining the effect of model uncertainty in forestry decision making, however, is correlation between the models. If this is not taken into account, predictions of the model systems may become biased, and the effect of errors on decision making may be underestimated. In reality, the models often are interdependent, but the correlations usually are not known because the models have been estimated in separate studies. The aim of this paper is to study the impacts of between-model dependencies on the predictive distribution of forest characteristics by Monte Carlo simulation techniques. We utilise a case of predicting seedling establishment of planted Norway spruce (Picea abies (L.) Karst.) stands as an example with multivariate multilevel model structures. Regardless of low cross-correlations between the models, ignoring them led to significant underestimation of the amount of competing broadleaves to be removed in pre-commercial thinning. Therefore, we recommend that between-model dependencies are clarified and considered in stochastic simulations. In our case, between-model interdependencies can be reliably estimated with a limited dataset. In addition, estimating the models separately and using the model residuals to estimate interdependencies between models were also sufficient to take the between-model dependencies into account when producing stochastic predictions for silvicultural decision making. [Copyright &y& Elsevier]

This paper introduces an innovative modelling strategy aimed at simulating the main terms of net forest carbon budget (net primary production, NPP and net ecosystem exchange, NEE) in Tuscany (Central Italy). The strategy is based on the preliminary calibration and application of parametric and bio-geochemical models (C-Fix and BIOME-BGC, respectively), which simulate the behaviour of forest ecosystems close to equilibrium condition (climax). Next, the ratio of actual over-potential tree volume is computed as an indicator of ecosystem distance from climax and is combined with the model outputs to estimate the NPP and NEE of real forests. The per-pixel application of the new modelling strategy was made possible by the collection of several data layers (maps of forest type and volume, daily meteorological data and monthly normalized difference vegetation index (NDVI) images for the years 1999–2003) which served to characterize the eco-climatic and forest features of the region. The obtained estimates of forest NPP and NEE were evaluated against ground measurements of accumulated woody biomass and net carbon exchange. The results of these experiments testify the good potential of the proposed strategy and indicate some problem areas which should be the subject of future research. [Copyright &y& Elsevier]

Abstract: Water footprint is an indicator showing the consumption impact on environment with water equivalent, which allows a detailed quantification of water use directly and indirectly in sectors for the domestic and abroad final consumption. This paper presents a framework of calculating national water footprint (NWF) with input–output method on China 2002. The results indicated that the NWF of China was 381m3/capyr in 2002. A new indicator termed as national water footprint intensity (NWFI) is also derived from NWF to evaluate the water consumption intensities of different sectors. Then the evaluation of virtual water trade in sectors is followed, the results of which give a detailed quantification of net virtual water import of sectors, verifying that China is a net virtual water exporter concerning the whole national sectors, which is different from the previous studies. Finally, it is suggested that the sectors with high NWFI and volume of net virtual water export should be regarded as the priority of Chinese water-saving strategy. [Copyright &y& Elsevier]