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• We introduce a flood disturbance module to the LANDIS-II forest succession modelling framework to enable investigations into how inundation interacts with other disturbances and successional processes to alter floodplain forest cover and community dynamics. • In a case study in the Upper Mississippi River floodplain, USA, we illustrate how predictions of total forest cover and the abundance of different forest community types were responsive to patterns of inundation and outbreaks of the emerald ash borer (Agrilus planipennis). • Our results suggest that a deeper understanding of floodplain forest dynamics can be gained through integrative models that combine forest successional processes and other disturbances, with the impacts of inundation. • This modelling framework should allow for future studies that examine how alternative hydrologic scenarios and other disturbances interact to influence floodplain forests in space and time. Simulation models are often used to identify hydrologic regimes suitable for different riparian or floodplain tree species. However, most existing models pay little attention to forest successional processes or other disturbances that may interact with the hydrologic regime of river systems to alter forest dynamics in space and time. In this study, we introduce a flood disturbance module to the LANDIS-II forest succession modelling framework to enable investigations into how inundation interacts with other disturbances and successional processes to alter floodplain forest cover and community dynamics. We illustrate the functionality of the model using a case study with multiple scenarios in the Upper Mississippi River floodplain, USA. We found that model predictions of total forest cover and the abundance of specific forest community types were generally related to uncertainty in the susceptibility of different species and age classes to inundation. By simulation year 100, increases or decreases in total forest cover and forest type distributions were roughly proportional to the initial differences in the susceptibility of species and age classes to inundation. The largest decrease in total forest cover was associated with a scenario that included disturbance by the emerald ash borer (Agrilus planipennis) and when using susceptibility parameters corresponding to the weakest flood tolerance. In contrast, changes in the composition of aboveground biomass were not sensitive to differences in susceptibility, and generally showed shifts toward later successional species with higher shade tolerance and longer lifespans for all scenarios. Our findings suggest that flood inundation interacts with other disturbances (e.g., insect outbreaks) and forest successional processes to alter forest abundance, distribution, and species composition in this system. Our modelling framework should allow for future studies that examine such interactions in other systems, and in the context of alternative hydrologic scenarios and other disturbance regimes. [ABSTRACT FROM AUTHOR]

Highlights • Seed and seedling availability of fire-killed plants decrease under drier climate. • Drier climate affects demographic stages (seeds, seedlings, adults) differently. • Fire-killed plant populations require longer inter-fire period to survive. • Mismatch between required longer and projected shorter fire intervals. Abstract Mediterranean-type ecosystems (MTEs) harbor an exceptionally high biodiversity of vascular plants. At the same time, climatic conditions in many MTE regions are projected to become both drier and hotter, and fire intervals shorter. The Interval Squeeze conceptual model integrates the potential effects of a changing climate and fire regimes on perennial plant population persistence and postulates that warmer, drier conditions will negatively affect multiple plant demographic processes. Dependent on species-specific traits, the required fire intervals that allow for population persistence might become longer, while projected future fire intervals are shorter, leading to a potential mismatch. However, conceptual models are per se not able to quantify outcomes of multiple stochastic processes or to simulate temporal dynamics. Here, we develop a simple, process-based model for a fire-sensitive woody plant species to evaluate the response of demographic processes to future climatic conditions and to quantify the potential impact also of future changes in fire interval. This allowed us to assess key assumptions of the interval squeeze model, particularly in relation to demographic drivers. We simulated populations of Banksia hookeriana , a typical fire-killed shrub found in MTEs of South-West Australia which stores its seeds in a canopy (serotinous) seedbank and shows strong cohort recruitment in the first year after fire. We estimated suitable fixed fire intervals for population persistence under historic climatic conditions and evaluated impacts of a higher dry year frequency (as projected under future climate by two representative concentration pathways, RCP4.5 and RCP8.5). Our findings support the Interval Squeeze Model: the fire interval allowing plant population persistence is squeezed from currently 10–28 years to 13–28 years for RCP4.5. For RCP8.5 population persistence is not possible under any of the tested fire intervals because of low seed production and low survival probability of both seedlings and adult plants. The results show that projected drier conditions alone will cause a higher extinction risk for fire-sensitive perennial plant populations in MTEs, which is further pronounced in combination with shorter fire intervals. This will likely lead to a strong shift in community composition and a loss of biodiversity. Fire management practices may need to be modified to attempt to counteract prospective biodiversity loss and ecosystem structure change. [ABSTRACT FROM AUTHOR]

The cultivation of Bt maize, genetically modified to be resistant to insect pests, has led to intense scientific and political debate about its possible adverse impacts on biodiversity. To better address this question we developed an individual-based simulation model ( LepiX ). LepiX considers the temporal dynamics of maize pollen shedding and larval phenology, and pollen deposition on host plants related to distance from the maize field, in order to estimate mortality of lepidopteran larvae exposed to toxic Bt pollen. We employed a refined exposure analysis, comparison to previous approaches, using recent evidence on leaf pollen deposition and accounting for the spatial heterogeneity of pollen on leaves. Moreover, we used a stochastic approach, considering literature data on a minimum dataset for butterfly biology in combination with historic data on temporal pollen deposition to predict the coincidence between larval phenology and pollen deposition. Since conservation management actions may act at the level of the individual for protected species, LepiX , as an individual based spatially explicit model, is suited to assist both risk assessment and management measures based on threshold mortalities. We tested our model using Inachis io (Lepidoptera: Nymphalidae) as butterfly species and the cultivation of insect resistant MON810 maize. In accordance to predictions based on other models we identified mortality risks of I. io larvae for the second larval generation. An analysis of the sensitivity of input parameters stressed the importance of both the slope and the LC 50 value of the dose-response curve as well as the earliest day of larval hatching. Using different published data to characterize the dose-response of MON810 pollen to I. io we revealed consequences due to uncertainties in ecotoxicological parameters and thus highlight the importance of key biological parameters for reliable estimates of effects, and decision making (e.g. isolation distances) in risk assessment. [ABSTRACT FROM AUTHOR]

Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition. [ABSTRACT FROM AUTHOR]

Projected climate change implies that site conditions can no longer be expected to remain constant over a tree’s lifetime. The fast and complex changes in site characteristics and growth patterns diminish the value of traditional knowledge and profoundly alter the conditions of forest management. One way to tackle the inherent uncertainties are simulation studies addressing these new dynamics and mechanisms. The aim of this study is to present such a simulation model system comprising various established and validated process-based and statistical models assessing the complex and dynamic response of a forest stand to climate change. For a given climate scenario, these coupled models estimate the potential growth and yield and various risks considering changing site and stand conditions. As an example, the model system is applied to managed forest stands of Norway spruce ( Picea abies (L.) H. Karst.) in a forest district located in central-western Germany. For the changing climate conditions according to SRES B1 and A1B, the model results suggest a positive effect on the site index and, by contrast, a negative impact on tree survival of increasing risks regarding drought stress mortality, wind damage, and bark beetle infestation given the climate change scenario. The annual contribution margin of timber production under consideration of damage risks by drought stress mortality, wind, and bark beetle infestation reveals that, in this case, the increased growth is able to compensate for the higher risks with few exceptions. Furthermore, we discuss the advantages and challenges of employing a dynamic complex simulation model system for climate change impact assessment based on high-resolution climate data. [ABSTRACT FROM AUTHOR]

Freshwater systems provide iconic examples of ecological tipping points. In some lakes and ponds, changes to nutrient levels can drive sudden shifts between primary producer communities dominated by either submerged or floating plants. Several models, ranging in complexity, have been developed to understand the interaction between these primary producer groups. Previous field studies suggest that spatial (e.g., water body size) and temporal (e.g., seasonality) processes are important for the dynamics of this system in nature, but these processes cannot be included in most models without a significant increase in model complexity. Therefore, I developed a spatially- and temporally-explicit model of this system with moderate model complexity that extends a previous model, in which alternative states are known to occur. I found that under low (approximately ≤2 mg total nitrogen L −1 ) or high (approximately ≥6 mg total nitrogen L −1 ) nutrient levels, either submerged or floating plants dominated, respectively. At intermediate nutrient levels, simulations resulted in different final plant states, depending on the initial cover of floating and submerged plants, providing evidence for alternative states. Under most conditions, stable intermediate states were uncommon. Water body size had a large effect on the dynamics of the system, as observed in the field, but only if wind strengths increased with water body size and there was a prevailing wind direction. Surprisingly, species composition and trait diversity did not appear to have major effects on the final plant states. This model allows the integration of processes on multiple scales of biological organization, from species traits and composition, to climate and seasonality or ecosystem-level properties, and it complements the growing realization that spatial context has significant impacts on the dynamics of alternative states in nature. [ABSTRACT FROM AUTHOR]

A simulation testing framework was developed to evaluate the efficacy of detecting population trends of two sampling methods used to monitor inshore fish populations: angling and baited remote underwater stereo-video systems (stereo-BRUVs). The study is based on data collected as part of a long-term monitoring program in the Tsitsikamma National Park marine protected area, South Africa. As a test scenario, declining population trajectories of the most abundant species, Chrysoblephus laticeps , were simulated by introducing consecutive years of reduced recruitment over periods of 10 and 20 years applying an age-structured operating model. The operating model was designed to generate method-specific relative abundance indices and length–frequency data, using parameters derived from existing data collected in the long-term monitoring program. These were then fitted with an age-structured estimation model. Estimated spawner-biomass depletion was compared to the ‘true’ simulated population to quantify method-specific accuracy and bias using root-mean-squared error. Due to higher data variability and inherent size selectivity of angling, stereo-BRUVs provided more accurate spawner-biomass trends when describing a distinct population decline over 10 and 20 years. Additionally, spawner-biomass was found to be a more accurate population estimate than relative abundance indices due to the inclusion of population size structure information. The study demonstrates the potential of using simulation testing to evaluate sampling methods, given that the process generates the ‘true’ population with a known abundance and size structure. [ABSTRACT FROM AUTHOR]

• Citizen data was successfully integrated in a mechanistic moose population model. • Moose abundance between 2012 and 2020 was estimated. • The model was most sensitive to the recruitment parameter. • The model can be used in moose management at various scales. Long-term and wide-ranging citizen science programs provide a unique opportunity to monitor wildlife populations and trends through time while encouraging stakeholder participation, engagement, and trust. Hunter observations is such a program that in Sweden is used on a regular basis to monitor population trends of moose. However, hunter observations are not reliable to determine the actual population size. We developed a mechanistic moose population model that integrated citizen science data and used it at various geographical scales to estimate moose population size between 2012 and 2020. A sensitivity analysis, specifically performed for recruitment, adult sex ratio and calf sex ratio, showed that the simulated population size was most sensitive for variation in recruitment. According to the results, Sweden had a total moose population of ∼311 000 (± 4%) individuals pre-hunt and ∼228 000 (± 4%) post-hunt in 2020. The post-hunt moose abundance has decreased nationwide with 15%, from 0.72 to 0.61 moose per km2 during the 2012 – 2020 period. The present post-hunt moose density was estimated at 0.39, 0.78, 0.84 and 0.54 per km2 for the regions northernmost, northern, central and southern Sweden, respectively. The simulation model can be used for strategic and operative management at various geographical scales and is publicly available. By integrating citizen data with a mechanistic population model, a new low-cost method of estimating population size and relevant population dynamics was established. [ABSTRACT FROM AUTHOR]

Indirect effects in ecosystems in response to perturbations remain a topic of much discussion. We continue on the theoretical path set by Nakajima and Higashi (1995, Indirect effects in ecological interaction networks (II): the conjugate variable approach. Mathematical Biosciences 130, 129–150) and extend their approach for quantifying indirect effects of press perturbations under steady-state conditions to pulse perturbations in steady state and to press and pulse perturbations under time-varying conditions. We illustrate with a commonly used lake ecosystem model how to estimate total, direct, and indirect effects on one species’ biomass (e.g., game fish) from perturbations to a second species (e.g., forage fish). We use the daily output of species biomasses from multi-year model simulations to test whether the computed total, direct, and indirect effects are equal for pulse and press perturbations of equal magnitude, and whether the types (pulse and press) and timing of perturbations alter the relative importance of indirect effects. Our results were consistent with the original theory of Nakajima and Higashi; under steady-state conditions, press and pulse perturbations to the forage fish produced similar effects on the game fish. Under these same conditions, indirect effects on the game fish were more than 3.5 times larger than the direct effects. Under time-varying conditions, all classes of pulse effects, but not press, depended on the day the perturbation was imposed. Indirect effects of pulse and press perturbations under time-varying conditions were always negative (offsetting) and of similar magnitude as the direct effects. When forage fish biomass was growing rapidly, the indirect effect on game fish biomass of a pulse perturbation was relatively smaller compared to the direct effect, whereas the indirect and direct effects were similar at other times. We consider the general implications of these results for the analysis of natural ecosystems. [ABSTRACT FROM AUTHOR]

Pulsing is prevalent in nature. As resource pulse has been recognized as one of the major factors influencing ecosystem structures and processes, it is important to investigate why nature pulses and what benefits an ecosystem obtains from pulsed resources. The main question of this study was that if a system could be exposed to either constant external resources or pulsed external resources of the same temporal average intensity, which resources would maximize power acquisition of a system. To answer the question, this study tested how matching of pulsed resources affects total empower acquisition of a system using numerical simulation models and a refined dynamic emergy accounting method. A producer–consumer model system was built and simulated by varying phases and frequencies of pulsed energy sources. It was hypothesized that matching of frequency and phase among two or more pulsed energy sources increases the empower acquisition of a system, compared with a system under constant energy sources. The simulation results showed that in systems of two energy sources, matching phases and frequencies of the pulsed energy sources involved in primary production is critical to increase total empower acquisition and consumer energy storage. The primary mechanism was that the matching of pulsed resources in phase and frequency promotes energy acquisition of primary producers that is further efficiently transferred for the production of consumers. Energy acquisition of consumers was strongly correlated with total empower acquisition of the system presumably because the consumers are in the high energy hierarchical position controlling the producers thus contributing to the total empower acquisition through the system. [Copyright &y& Elsevier]

• Biological control is often the only option for widespread pest invasions. • Pre-screening biological control agents through modelling can save time and money. • We develop a simulation model for biocontrol of an invasive social insect. • The model is calibrated and validated with data from south-eastern australia. • The model measures technical feasibility, a prerequisite for economic feasibility. Established pests are often overlooked as candidates for eradication or containment programmes because the use of traditional control techniques over very large areas usually becomes uneconomic. In such cases, classical biological control can be an attractive option. If biocontrol agents become established in equilibrium with the invasive species, there are no ongoing costs of control. Arriving at the point of biocontrol release, however, requires significant time and investment in research and testing, and success of biocontrol agents is not guaranteed. It is therefore advisable to undertake preliminary analysis of the likelihood of success. Simulation modelling using population dynamics models can be very useful in this regard. Here we develop a model for biocontrol of an invasive social insect, the European wasp (Vespula germanica) and derive the conditions for success of a biocontrol program. [ABSTRACT FROM AUTHOR]

Highlights: [•] Data-based validation of a dynamics model for uneven-aged mixed species forests. [•] Over 70-year time-series forest growth dataset used for model validation. [•] Model projected tree density, diameter, basal area and live aboveground biomass. [•] Mean annual diameter growth increments for native species in Callitris forests. [•] Projected attributes were between 88% and 94% of the observed. [Copyright &y& Elsevier]

Abstract: A potential environmental risk of the field cultivation of insect-resistant (Bt-toxin expressing) transgenic maize (Zea mays) is the consumption of Bt-containing pollen by herbivorous larvae of butterflies (Lepidoptera). Maize is wind-pollinated, and at flowering time large amounts of pollen can be deposited on various plants growing in the landscape, leading to inadvertent ingestion of toxic pollen with plant biomass consumed by these butterfly larvae. To examine the possible effect of this coincidence, we focused our study on the protected butterfly Inachis io and two regions of Europe. Using climatic records, maize and butterfly phenology data, we built a simulation model of the butterfly''s annual life cycle, overlaid with the phenology of maize pollen deposition on the leaves of the food plant Urtica dioica, and linked these with the dose–response curve of I. io larvae to Bt-maize pollen (event MON810). The simulations indicated that in Northern Europe, where I. io is univoltine, Bt-maize pollen would not be present on the food plant at the same time as the I. io larvae. However, in Central and Southern Europe, where I. io is bivoltine, Bt-maize pollen and the second generation I. io larvae would coincide, and an increased mortality of the larvae was predicted. This prediction differs from earlier studies which predicted negligible effect of field-grown Bt-maize on I. io larvae. Our model is an improvement over previous efforts since it is based on more detailed, empirical data, includes more biological detail, and provides explicit estimation of all model parameters. The model is open-source software and is available for re-use and for modelling the effects on other species or regions. [Copyright &y& Elsevier]

Recent increases in computation power have prompted enormous growth in the use of simulation models in ecological research. These models are valued for their ability to account for much of the ecological complexity found in field studies, but this ability usually comes at the cost of losing transparency into how the models work. In order to foster greater understanding of the functioning of computer simulation models, we develop an analytical approximation of the Landscape Age-class Demographics Simulator (LADS; ), a representative example of broad group of models that simulate landscape-scale forest dynamics in response to a series of recurring disturbances that interact spatially with existing landscape structure. Much of the model output was produced mathematically, without generating a series of disturbances (in this case, fire) or simulating the forest response to each disturbance. The approximation provides a detailed understanding of the modeled fire regime. Also, it provides equations that directly specify the roles of key input parameters rather than having to infer these roles indirectly from model output in a sensitivity analysis. The application of analytical methods typically has been limited to simple scenarios that lack feedbacks or spatial interactions, but in this exercise, analytical methods address much of the complexity more commonly addressed by simulation: the modeled landscape is composed of two provinces, each with a unique fire frequency and fire-size distribution; stochastic variation in the number of fires per year and the size of each fire; and two levels of fire severity that each have different effects on forest structure. Analytical approximation is not suggested as an alternative to simulation models, but rather, as a complementary approach aimed at improving insight into model function. [Copyright &y& Elsevier]

We describe an ecotoxicological model that simulates the sublethal and lethal effects of chronic, low-level, chemical exposure on birds wintering in agricultural landscapes. Previous models estimating the impact on wildlife of chemicals used in agro-ecosystems typically have not included the variety of pathways, including both dermal and oral, by which individuals are exposed. The present model contains four submodels simulating (1) foraging behavior of individual birds, (2) chemical applications to crops, (3) transfers of chemicals among soil, insects, and small mammals, and (4) transfers of chemicals to birds via ingestion and dermal exposure. We demonstrate use of the model by simulating the impacts of a variety of commonly used herbicides, insecticides, growth regulators, and defoliants on western burrowing owls (Athene cunicularia hypugaea) that winter in agricultural landscapes in southern Texas, United States. The model generated reasonable movement patterns for each chemical through soil, water, insects, and rodents, as well as into the owl via consumption and dermal absorption. Sensitivity analysis suggested model predictions were sensitive to uncertainty associated with estimates of chemical half-lives in birds, soil, and prey, sensitive to parameters associated with estimating dermal exposure, and relatively insensitive to uncertainty associated with details of chemical application procedures (timing of application, amount of drift). Nonetheless, the general trends in chemical accumulations and the relative impacts of the various chemicals were robust to these parameter changes. Simulation results suggested that insecticides posed a greater potential risk to owls of both sublethal and lethal effects than do herbicides, defoliants, and growth regulators under crop scenarios typical of southern Texas, and that use of multiple indicators, or endpoints provided a more accurate assessment of risk due to agricultural chemical exposure. The model should prove useful in helping prioritize the chemicals and transfer pathways targeted in future studies and also, as these new data become available, in assessing the relative danger to other birds of exposure to different types of agricultural chemicals. [Copyright &y& Elsevier]

Previous ecological models for disturbance from energetic perspectives have focused on destructive pulses by which storages in a system are quickly drained during disturbance events and recovered thereafter. However, considering the wide range of disturbance intensities, frequencies, and durations in nature, disturbance effects on ecosystem energetics would be better understood by diversifying the disturbance effects on specific system configurations or energy pathways. Based on two hypotheses, we built simulation models of the variable disturbance–productivity relationships observed in a freshwater aquatic microcosm study. First, we hypothesized that disturbances will differentially alter the intrinsic rates of energy pathways in a system. Second, we hypothesized that there is a disturbance threshold where response of the intrinsic rates changes abruptly. Simulation results showed variable patterns of gross primary productivity (GPP) during the disturbance and post-disturbance periods under the diverse scenarios of disturbance effects on the intrinsic rates. Simulation results confirmed that the second hypothesis (i.e., disturbance threshold) was essential to achieve a U-shaped or peaked disturbance–productivity relationship. We evaluated the models by comparing them with the results of the microcosm tests, and suggested possible mechanisms of the variable disturbance–productivity relationships by varying parameters related to the disturbance effects on the intrinsic rates and the disturbance thresholds. [Copyright &y& Elsevier]

Longleaf pine (Pinus palustris) savannas of the southeastern U.S. represent an archetype of a fire dependent ecosystem. They are known to have very short fire return intervals (∼1–3 years) that perpetuate understory plant diversity (up to 50 species m−2), support pine recruitment, and suppress fire sensitive hardwoods. Understanding the relationships that regulate longleaf and southern hardwoods is especially critical. With decreased fire frequency, insufficient intensity, or lack of underground competition, a woody mid-story rapidly develops, dominated by fire sensitive trees and shrubs that in-turn suppress more fire dependent species (including pine seedlings). This may occur in forest gaps, where pine-needle abundance is diminished, reducing fire spread potential. The interactions between longleaf pine, hardwoods, forest fuels, and fire frequency are complex and difficult to understand spatially. The objective of this study was to develop a spatially explicit longleaf pine–hardwood stochastic simulation model (LLM), incorporating tree demography, plant competition, and fuel and fire characteristics. Data from two longleaf pine study sites were used to develop and evaluate the model with the goal to incorporate simple site-specific calibration parameters for model versatility. Specific model components included pine seed masting, hardwood clonal sprouting, response to fire (re-sprouting, mortality), and tree density driven competition effects. LLM spatial outputs were consistent with observed forest gap dynamics associated with pine seedling establishment and hardwood encroachment. Changes in fire frequency (i.e., fire probability=0.35–0.05) illustrated a shift in community structure from longleaf pine dominated to a hardwood dominated community. This approach to assessing model response may be useful in characterizing longleaf ecosystem resilience, especially at intermediate fire frequencies (e.g., 0.15) where the community may be sensitive to small changes in the fire regime. Height distributions and population densities were similar to in situ findings (field and LIDAR data) for both study sites. Height distributions output by the LLM illustrated fluctuations in population structure. The LLM was especially useful in determining knowledge gaps associated with fuel and fire heterogeneity, plant–plant interactions, population structure and its temporal fluctuations, and hardwood demography. This is the first known modeling work to simulate interactions between longleaf pine and hardwoods and provides a foundation for further studies on fire and forest management, especially in relation to ecological forestry practices, restoration, and site-specific applications. [Copyright &y& Elsevier]

A fundamentally revised version of the HERMES agro-ecosystem model, released under the name of MONICA, was calibrated and tested to predict crop growth, soil moisture and nitrogen dynamics for various experimental crop rotations across Germany, including major cereals, sugar beet and maize. The calibration procedure also included crops grown experimentally under elevated atmospheric CO2 concentration. The calibrated MONICA simulations yielded a median normalised mean absolute error (nMAE) of 0.20 across all observed target variables (n =42) and a median Willmott's Index of Agreement (d) of 0.91 (median modelling efficiency (ME): 0.75). Although the crop biomass, habitus and soil moisture variables were all within an acceptable range, the model often underperformed for variables related to nitrogen. Uncalibrated MONICA simulations yielded a median nMAE of 0.27 across all observed target variables (n =85) and a median d of 0.76 (median ME: 0.30), also showing predominantly acceptable results for the crop biomass, habitus and soil moisture variables. Based on the convincing performance of the model under uncalibrated conditions, MONICA can be regarded as a suitable simulation model for use in regional applications. Furthermore, its ability to reproduce the observed crop growth results in free-air carbon enrichment experiments makes it suited to predict agro-ecosystem behaviour under expected future climate conditions. [Copyright &y& Elsevier]

This study provides a method for assessing a multiplicity of environmental factors in red spruce growth in the Great Smoky Mountains National Park (GSMNP) of Southeastern USA. Direct and indirect factors in the annual growth increment are first organized into a schematic input–output envirogram (ARIRS), and this information is then used to construct a simulation model (ARIM). The envirogram represents a structured conceptualization of most environmental factors involved in growth, as developed from relevant literature. This interdisciplinary synthesis distinguishes direct vs. indirect factors in growth and takes account of the systems ecology concept that indirect factors may be as important as or more important than direct ones in regulating growth. The ARIRS envirogram summarizes hierarchically organized, within- and cross-scale, local-to-global interactions, and its construction makes it obvious that growth is influenced by many cross-scale spatiotemporal interactions. More research on genecology is still needed to clarify the role of phenotypic plasticity and adaptive capacity in nutrient cycling, global change, and human disturbance. [Copyright &y& Elsevier]

The effect of heterogeneous environments upon the dynamics of invasion and the eradication or control of invasive species is poorly understood, although it is a major challenge for biodiversity conservation. Here, we first investigate how the probability and time for invasion are affected by spatial heterogeneity. Then, we study the effect of control program strategies (e.g. species specificity, spatial scale of action, detection and eradication efficiency) on the success and time of eradication. We find that heterogeneity increases both the invasion probability and the time to invasion. Heterogeneity also reduces the probability of eradication but does not change the time taken for successful eradication. We confirm that early detection of invasive species reduces the time until eradication, but we also demonstrate that this is true only if the local control action is sufficiently efficient. The criterion of removal efficiency is even more important for an eradication program than simply ensuring control effort when the invasive species is not abundant. [Copyright &y& Elsevier]

The distribution of surface water affects herbivore–vegetation interactions in arid and semi-arid regions. Limited access to surface water typically results in the emergence of vegetation gradients around natural and artificial water sources. In particular, African elephants can create large-scale gradients of woody vegetation. Understanding the dynamics of these gradients is of particular importance for the conservation of other, less mobile herbivores that depend on woody vegetation in areas close to water. While rainfall is known to be a key determinant of herbivore–vegetation interactions in dry areas, we only have limited understanding on how it impacts woody vegetation gradients around waterholes. To address this problem, we developed a deterministic simulation model that describes the interplay of rainfall, elephants and woody vegetation in the vicinity of waterholes. The model is based on elephant telemetry data and the ecological conditions in Etosha National Park (ENP), Namibia. We found that decreasing amounts of rainfall led to an increased degradation of woody vegetation, which was particularly severe in areas close to water. Based on this result we conclude that low rainfall was an important driver of recently observed patterns of vegetation degradation in ENP. More generally, rainfall appears to be a key factor that determines elephant–vegetation interactions and thus dynamics of woody vegetation gradients around waterholes. Using long-term rainfall data from ENP, we also demonstrate that an increase in the number of water sources during periods of low rainfall can mitigate the destructive impact of elephants in areas close to water. However, more research is required to assess the sustainability and effectiveness of rainfall-adapted strategies of artificial water provisioning in more detail. In particular it is important to investigate potential effects on elephant population dynamics. [Copyright &y& Elsevier]

Recent studies have reported that earthworm invasions alter native communities and impact nutrient cycling in terrestrial ecosystems. We developed a simulation model to evaluate the potential impacts of earthworm invasions on carbon dynamics, taking into consideration earthworm feeding strategies and priming effects on the microorganisms through their casting activities. Responses of carbon stocks (forest litter, soil organic matter, microbial biomass and earthworm populations) and carbon fluxes (litter decomposition, earthworm consumption, and microbial respiration) were used to evaluate an earthworm invasion of a forest ecosystem. Data from a northern temperate forest (Arnot Forest, New York) were adapted for model calibration and evaluation. Simulation results suggest that the impact and outcome of earthworm invasions are affected by pre-invasion resource availability (litter and soil organic matter), invasive earthworm assemblages (particularly feeding strategy), and invasion history (associated with earthworm population dynamics). The abovementioned factors may also determine invasion progress of earthworm species. The accuracy of the model could be improved by the addition of environmental modules (e.g., soil water regimes), precise parameters accounting for individual species attributes under different environmental conditions (e.g. utilization ability of different types of food resources), as well as earthworm population dynamics (size and structure) and interactions with predators and other invasive/indigenous species during the invasion progress. Such an earthworm invasion model could provide valuable evaluation of the complicated responses of carbon dynamics to earthworm invasions in a range of forest ecosystems, particularly under global change scenarios. [Copyright &y& Elsevier]

Explaining the coexistence of species that basically depend on the same resources has been a brainteaser for generations of ecologists. Different mechanisms have been proposed to facilitate coexistence in plant communities, where space is an important resource. Using a stochastic cellular automaton simulation model we analyze – separately and in combination – the influence of different species traits and processes which alter local competition on the coexistence of plant species over a fixed time horizon. We show that different species traits operate on different time scales in competition. We therefore suggest the concept of weak versus strong traits according to short- or long-term exclusion of species differing in these traits. As a consequence, highly non-linear trade-offs between weak and strong traits can result in communities. Furthermore, we found that trade-offs based on physiological species traits such as plant lifetime, dispersal range and plant growth, did not support broad and long-term coexistence—further processes such as density-dependent mortality and light-dependent colonization were necessary. This suggests that coexistence in plant communities requires (stabilizing) local processes to support the (equalizing) trade-offs in species traits. [Copyright &y& Elsevier]

Over the last decades, agricultural intensification has caused a dramatic reduction of grassy habitats. This habitat loss has had a strong negative effect on many meadow-living insect populations, including butterflies. As a part of the cross-compliance measures of the Common Agricultural Policy of the European Union, subsidies for creation and maintenance of grassy field margins (GFM) have been launched. Among other environmental issues, they may serve as corridors for movement of various meadow-living species between individual meadows. Their role as corridors has, however, not yet been demonstrated at the landscape scale and their characteristics that most significantly increase landscape connectivity are unknown. Empirical data for such studies are missing, as the GFM subsidies were launched only 3 years ago. One possibility to get some predictions of their outcomes is provided by simulation models. Here we present our simulation results, using an extension of the model developed by Kindlmann et al. (2004) for the Meadow Brown butterfly, Maniola jurtina. The extension includes the probability to cross a boundary (Conradt and Roper, 2006) that negatively influences dispersal rates but increases sensitivity to the corridor effect. Our simulations show that GFMs increase the dispersal rates between habitat patches and we predict the optimal combinations of width and number of GFMs in the landscape. This way we provide a decision-making tool for increasing landscape connectivity for M. jurtina and similar species. Although our simulations are based on a particular species, they may be generalized because this species shows dispersal rates that are typical of butterfly metapopulations (Conradt et al., 2000), and a potentially widespread dispersal kernel (i.e. “foray search”) that has been reported in a wide variety of species (see Conradt et al., 2003 for a review). [Copyright &y& Elsevier]

Although increasingly widely used in biology, complex adaptive simulation models such as agent-based models have been criticised for being difficult to communicate and test. This study demonstrates the application of pattern-oriented model testing, and a novel documentation procedure to present a detailed agent-based model of the European brown hare, a species in widespread decline in Europe. The model was built based on available literature data, using multiple field data patterns from an island hare population study to guide model development. A general and widely applicable approach to the pattern-oriented protocol for testing and developing ecological models of this kind was defined together with the development of the ODdox documentation protocol, a combination of the current ODD protocol for describing agent-based models and source-code documentation. The result is a detailed and yet accessible description of the processes included in the model. Application of the model to a comprehensive historical data set supported the hypothesis that interference competition is the primary population regulating factor in the absence of mammal predators in the brown hare, and that the effect works through reduced fecundity. With a clearly defined testing protocol and documentation, this in silico modelling approach has clear advantages for applications requiring integration of many factors, especially when spatio-temporal variability is important. Providing multi-facetted output which can be compared to real-world data allows the formulation and testing of varied hypotheses in ways not tractable to experimentation. In the case of the brown hare the results provide a new insight into population regulation and the causes of the declines. [Copyright &y& Elsevier]

For policy decisions with respect to CO2-mitigation measures in the agricultural sector, national and regional estimations of the efficiency of such measures are required. The conversion of ploughed cropland to zero-tillage is discussed as an option to reduce CO2 emissions and promises at the same time effective soil and water conservation. Based on the upscaling of simulation results with the soil and land resources information system SLISYS-BW, estimations of CO2-mitigation rates in relation to crop rotations and soil type have been made for the state of Baden-Württemberg (Germany). The results indicate considerable differences in the CO2-mitigation rates between crop rotations ranging from 0.48 to 0.03MgCha−1 a−1 for winter cereals–spring cereals–rape rotations and winter cereals–spring cereals–corn silage rotations, respectively. The efficiency of the crop rotations is strongly related to the total carbon input and in particular the amount of crop residues. Among the considered soil types, highest CO2-mitigation rates are associated with Cumulic Anthrosols (0.62MgCha−1 a−1) and the lowest with Gleysols (−0.01MgCha−1 a−1). An agricultural extensification scenario with conventional plowing but conversion of the presently applied intensive crop rotations to a clover–clover–winter cereals rotation indicated a CO2-mitigation potential of 466GgCa−1. However, the present high market prices for cereals and increasing demand for energy production from biomass encourages an intensification of the agricultural production and an excessive removal of biomass which in future will seriously reduce the potential for carbon sequestration on cropland. [Copyright &y& Elsevier]

Abstract: Distribution patterns of plants are affected by human activities such as creation, destruction or modification of habitats. However, another important question is to what extent humans shape plant distributions by acting as dispersal vectors. In order to answer this question we developed a simulation model for the spread of plant species between human settlements. This was done on the basis of extensive sociological and ecological data on a regional scale. With regard to the sociological data, human movement behaviour defined the amount of exchange between the settlements. Gardening types represented the potential habitat in our model. The ecological data was derived from a vegetation survey carried out in 2003, which was a repeat of a survey between 1974 and 1981 along the same transects. From these surveys, we studied the distributions of 13 species in 67 settlements. In our model, the earlier survey provided the data for the initial distribution. The simulated pattern was consequently compared with the distribution pattern in 2003. In the model, dispersal kernels based on patterns of human movement between settlements led to a better match with the distribution patterns than a null model simulating pure distance dependent dispersal for all species. This was statistically significant for seven of the thirteen species. A striking result was that alien species seem to benefit more from human dispersal than native species. We emphasize the importance of the sociological data on human movement behaviour in parameterizing our regional scale model. This study provides quantitative evidence on the impact of human movement behaviour on the distribution of plant species in suburban areas. [Copyright &y& Elsevier]

Abstract: A simple simulation model was developed to describe the growth trends of Cymodocea nodosa (Ucria) Ascherson based on data sets from the Venice lagoon. The model reproduces the seasonal fluctuations in the above and belowground biomass and in shoot density. The modeling results are in good agreement with data on net production, growth rates and chemical–physical parameters of water. It was assumed that light and temperature are the most important factors controlling C. nodosa development, and that the growth was not limited by nutrient availability. The aim was to simulate biomass production as a function of external forcing variables (light, water temperature) and internal control (plant density). A series of simulation experiments were performed with the basic model showing that among the most important phenomena affecting C. nodosa growth are: (1) inhibition of production and recruitment of new shoots by high temperature and (2) light attenuation due to seasonal fluctuation. [Copyright &y& Elsevier]

Abstract: Interspecific competition can have a substantial impact on sympatric carnivore populations and may threaten reintroduction attempts of threatened or endangered species. Coyotes (Canis latrans) are the primary threat to recovery of red wolves (C. rufus) in the wild, through hybridization and loss of the red wolf genotype and habitat occupancy that reduces space available for wolf occupation. We built a stochastic simulation model (using data collected from a recovering red wolf population in northeastern North Carolina as well as from the literature) to examine spatial dynamics of sympatric red wolves and coyotes (independent of habitat influences) and to elucidate the potential role of coyotes on wolf recovery and reintroduction success. Survival of juvenile and adult wolves had the greatest impact on wolf population size and likelihood of extinction. Introducing coyotes to the model had a substantial negative impact on wolf numbers, and the model was highly sensitive to the estimates of the competitive impact of coyotes on red wolves, through declines in wolf productivity. We simulated coyote management from either removal (lower coyote survival) or surgical sterilization (lower coyote reproductive rates) and found that both management strategies increased viability of red wolf populations, especially during initial colonization. Our results suggest that coyotes can inhibit red wolf reintroduction success through competitive interactions, but that management of coyote populations can improve the probability of successful wolf recovery. Additional information on spatial dynamics and dietary overlap between coyotes and wolves in the recovery area is needed to further elucidate the current and potential competitive impact of coyotes on red wolf populations. [Copyright &y& Elsevier]

The use of mathematical and simulation models is widespread in ecology, and individual-based models (IBMs) have proved valuable for exploring individually-explicit interactions and behaviour. The success of a model will depend upon its design and the different assumptions made during construction. In particular, methods implemented in the model to deal with interactions between objects are of fundamental importance for producing appropriate results. Asynchronous and synchronous scheduling are two methods for updating object characteristics during interaction. The consequence of these updating methods has been investigated for cellular automata, but not for IBMs. Here, we assess the two methods for their potential to give different results in a deliberately simple IBM. We show that the two methods produce different results, particularly at high population densities and for increasing interaction complexity (e.g. increasing numbers of trophic levels). This work appears to be the first evidence of the importance of scheduling methods on emergent properties for individual-based models and consequently individually-explicit interactions and behaviour in ecology. [Copyright &y& Elsevier]

A dynamic model for Plasmopara viticola primary infections on grapevine was elaborated according to a mechanistic approach. Development of the sexual stage of the pathogen was split into different state variables, in which changes from one state to another were regulated by rates depending on environmental conditions. The conceptual model was based on the definition of a primary inoculum season, a seasonal oospore (inoculum) dose, and its division into many coeval cohorts. Each cohort progresses along the primary infection cycle (production and survival of sporangia, release, survival and dispersal of zoospores, infection, appearance of disease symptoms) simultaneously, with a time step of one hour. The model was evaluated over a 12-year period (1995–2006) in Emilia-Romagna (Northern Italy) by comparing simulations with actual observations of the first seasonal symptoms of downy mildew in 43 vineyards. This data set was not used in model building and represents different environmental conditions, with both early and late primary infections. The model showed high sensitivity, specificity and accuracy. The achieved probabilities that an oospore cohort produce or not an infection were 0.994 and 0.999, respectively, while there was practically no probability that an oospore cohort produce infection when infection is not predicted by the model. Because of a small probability (<0.01) that a predicted infection is not a true infection, confidence in prediction of non-infections was higher than in prediction of infections. Most of the wrong positive predictions occurred in early season, when the host was in the earlier growth stages, or when the oospore germination was triggered by isolated weak rain events. Considering that neither calibration nor empirical adjustment of model parameters were necessary to obtain accurate simulation, it was concluded that this model produces a reasonable approximation of the primary infection processes underlying oospore development. The model showed that 86% of the oospore cohorts failed infection, because sporangia did not survive till zoospore release (5.6% of these cohorts), zoospores released from sporangia did not survive until dispersal (83.6%), or the zoospores that dispersed to leaves did not cause infection (10.8%). [Copyright &y& Elsevier]

White cypress pine Callitris glaucophylla is an important native tree widespread in heavily cleared savanna woodlands of the south-east Australian wheat-sheep belt. C. glaucophylla woodlands have been the focus of vigorous debate regarding their structure and dynamics during Aboriginal times and following European settlement, and the causes of structural changes are poorly understood. Management of contemporary woodland remnants is therefore controversial, and has so far lacked a predictive, process-based approach. We sought to determine whether a simple process model with recruitment, growth and survival mediated by rainfall and competition, could accurately simulate medium-term dynamics of C. glaucophylla woodlands in which fire has typically been excluded. Model parameters were optimised using reference data from 6- to 36-year silvicultural trials in central-western New South Wales (NSW). Predictions of the calibrated model compared favourably to actual growth, survival and recruitment of C. glaucophylla in the reference data, as well as in an independent dataset not used in optimisation. We tested whether remaining differences between predictions and actual data were related to variation in site productivity (a function of moisture availability as influenced by soil and landscape factors not modelled). Growth was overestimated in low-productivity sites and underestimated in high-productivity sites. Growth predictions were improved by using site-specific expected maximum heights to reflect site productivity. We also tested whether the model and parameter set produce dynamics consistent with those observed over the last half century. Modelled growth, survival, recruitment and competition processes were consistent with data and observations in previous studies on historical dynamics and stand behaviour of C. glaucophylla. The model has a wide range of potential applications for understanding past and predicting future stand dynamics. To illustrate an application of the model to thinning, a strategy currently being implemented to manage tree densities in inland NSW, we compared predicted stand structures in simulations of different thinning treatments. The simulations showed that without careful manipulation of existing canopy cover, stands can re-fill to pre-thinning densities within relatively short periods of time. [Copyright &y& Elsevier]

Abstract: We present a simulation model for risk assessment of the impact of insecticide inhibitors of cholinesterase (ChE) applied in irrigated agricultural fields on non-target wildlife. The model, which we developed as a compartment model based on difference equations (Δt =1h), consists of six submodels describing the dynamics of (1) insecticide application, (2) insecticide movement into floodable soil, (3) irrigation and rain, (4) insecticide dissolution in water, (5) foraging and insecticide intake from water, and (6) ChE inhibition and recovery. To demonstrate application of the model, we simulated historical and “worst-case” scenarios of the impact of ChE-inhibiting insecticides on white-winged doves (Zenaida asiatica) inhabiting natural brushland adjacent to cotton and sugarcane fields in the Lower Rio Grande Valley of Texas, USA. Only when a rain event occurred just after insecticide application did predicted levels of ChE inhibition surpass the diagnostic level of 20% exposure. The present model should aid in assessing the effect of ChE-inhibiting insecticides on ChE activity of different species that drink contaminated water from irrigated agricultural fields, and in identifying specific situations in which the juxtaposition of environmental conditions and management schemes could result in a high risk to non-target wildlife. [Copyright &y& Elsevier]

Variation in population dynamics is inherently related to life history characteristics of species, which vary markedly even within phylogenetic groups such as passerine birds. We computed the finite rate of population change (λ) from a matrix projection model and from mark-recapture observations for 23 bird species breeding in northern Arizona. We used sensitivity analyses and a simulation model to separate contributions of different life history traits to population growth rate. In particular we focused on contrasting effects of components of reproduction (nest success, clutch size, number of clutches, and juvenile survival) versus adult survival on λ. We explored how changes in nest success or adult survival coupled to costs in other life history parameters affected λ over a life history gradient provided by our 23 Arizona species, as well as a broader sample of 121 North American passerine species. We further examined these effects for more than 200 passeriform and piciform populations breeding across North America. Model simulations indicate nest success and juvenile survival exert the largest effects on population growth in species with moderate to high reproductive output, whereas adult survival contributed more to population growth in long-lived species. Our simulations suggest that monitoring breeding success in populations across a broad geographic area provides an important index for identifying neotropical migratory populations at risk of serious population declines and a potential method for identifying large-scale mechanisms regulating population dynamics. [Copyright &y& Elsevier]

Abstract: Dispersal of airborne spores, pollen and seeds is important for various ecological and biological processes, and therefore modeling tools are needed in order to predict the dispersal patterns of these particles. In this study, we use a Lagrangian stochastic (LS) modeling approach to describe airborne particles dispersal in the atmospheric boundary layer. The LS dispersal model is extended to include non-Gaussian turbulence in the upper parts of the atmospheric boundary layer, as well as the reduction of the autocorrelation time in trajectories due to the high terminal velocity of particles. The sensitivity of particle dispersal on biological and atmospheric factors is assessed by simulating dispersal patterns under varying environmental conditions. Similarly, the level of needed model complexity for describing the particle dispersal is examined. Our particle dispersal simulations suggest that the level of model complexity and accuracy needed in the description of biological and atmospheric factors depends on the particle size and the distance and time-scale over which the particle dispersal is monitored. More simplification is justified for light particles, whereas heavy particles require more accuracy in modeling. For example, we found out that the local dispersal of light particles is hardly affected by the atmospheric stability whereas it has a strong effect on the dispersal of heavy particles. Based on our simulations, we developed guidelines for modeling airborne particle dispersal. Together with the detailed description of the LS dispersion model and its parameterization throughout the atmospheric boundary layer, these can serve as basis for various particle dispersal studies and help ecologists and biologists not so familiar with meteorological modeling tools to apply the LS model for spore, pollen and seed dispersal. [Copyright &y& Elsevier]

We explored the factors that contribute to fish school formation and maintenance using a series of computer simulation experiments. The factors we examined were mostly social, and included the functional form of attraction to – and repulsion from – neighbors, alignment with neighbors, regions of no social force (“neutral zones”), scaling of neighbor influence, random noise, and frictional drag. For each experiment, we compared the results from changing one factor with those of a “base case” that included a neutral zone 1 body length wide, linear attraction and repulsion forces, no alignment force, no scaling of neighbor influence, medium randomness, and no friction drag. We computed eight schooling metrics, two at the individual level (curvature and nearest-neighbor distance), four at the group level (group speed, polarity, group size, and expanse), and two at the population level (percent of stragglers and collision rate). For the parameter space we examined, all factors except random noise were important in determining the emergent properties of the group, as characterized by our schooling metrics. In some cases, schooling behavior was affected strongly by the presence or absence of a factor, but not to the value of the factor (e.g., drag) or its functional form (e.g., alignment force). In other cases, the results depended entirely on the functional form of the factor (e.g., attraction–repulsion; neighbor scaling). Our results indicate that a steep repulsion function is necessary to prevent collisions, and that this function must respond to local density. Second, a neutral zone must exist in which neither attraction nor repulsion operate. Third, to obtain polarity, there must be a modest alignment impulse, strong enough to induce polarity in the group, but weak enough to allow individual non-conformity. Fourth, the number and weighting of influential neighbors is crucially important in maintaining school structure. Fifth, the speed of motion is clearly important, leading to strong differences in school packing, individual path curvature, and polarization, between rapidly moving (with no drag present) and slow-moving (with high drag present) groups. Finally, individuality or non-conformity to group behavior, which most authors represent by randomness, likely plays a role in determining schooling behavior, although it was not a strong factor in our model. Each of these factors is important in determining the local interactions that give rise to emergent properties in fish schools. [Copyright &y& Elsevier]

In a dynamic landscape the rate of change in landscape structure can be even more important than the degree of patch isolation in determining population survival and abundance. If the changes in landscape structure occur at an “extremely” high rate (as in some anthropogenic changes), dispersal may not be able to keep up with the high rates of local extinction. Understanding impacts of such changes is thus crucial for determination of the driving factors for species survival in agricultural landscapes and for elaboration of conservation plans. Here we studied the effects of landscape dynamics under local farming practices on movements and population dynamics of a diurnal butterfly Maniola jurtina L. (Satyridae), specifically the impacts of regular yearly mowing on butterfly movements, distribution and abundance over many years. We used an existing simulation model, extended it by the effect of the intensity of disturbance (amount of mown habitat) and timing of disturbance within the reproductive season on the butterfly population dynamics, and validated on our data from a field experiment using a mark-release method. Increase in the amount of disturbed habitats in the landscape led to an increasing isolation of the remnant habitat patches for butterflies. This resulted in decreasing movements between habitat patches and ultimately to population decline, especially in less accessible patches. In the past, influence of landscape dynamics on species survival was usually considered at the long-term scale. Our results demonstrate that the short time scale landscape dynamics induced by farming practices should not be neglected. The novelty of this paper stems in the combination of inclusion of landscape dynamics, of realistic dispersal strategies of individuals, and of considering real landscapes. The effect of man-induced landscape changes on population persistence of a real species in a real landscape has not been possible to be studied by any of the previously developed models. [Copyright &y& Elsevier]

Models that describe the ecological stoichiometry of individuals and populations often include a simplifying assumption that nutrient ratios in consumers are constant. However, several experiments suggest that organisms can alter their internal stoichiometry under nutrient poor conditions. These experiments also suggest that the production efficiency (biomass produced per unit ingested) of limiting nutrients increases when food quality is poor. We explored how these two physiological adaptations affected growth and reproduction in Daphnia under low nutrient levels by developing three different dynamic simulation models of an individual daphnid under stoichiometric constraints. All three models were converted into individual-based population models interacting with a process-based algal population model. Calibration of the three individual models demonstrated that the assumption of constant nutrient ratios was unable to replicate experimental observations of Daphnia growth under nutrient limited conditions. The addition of increasing phosphorous production efficiency improved the Daphnia''s ability to survive and grow, but still not within reported ranges. The addition of variable stoichiometry in the form of increasing nutrient use efficiency yielded an individual daphnid model that could be calibrated across reported food quantity/quality gradients. Further, the model accurately simulated the demonstrated ability of Daphnia to overcome the limitation of poor food quality and eventually suppress the algal population in a high-energy, low-nutrient system. The model accurately predicted the timing of the peak of the Daphnia population as well as the equilibrium biomass levels for both populations reported in a recent experiment. Explorations of model behavior further demonstrated that the adaptations under consideration increase total system P cycling which increases total system production. [Copyright &y& Elsevier]

We present a modeling approach where we use one common model formulation of a 11 state variable lower trophic level model that includes two groups of phytoplankton, three groups of zooplankton, and representations of nitrogen and silicate embedded in a three-dimensional ocean general circulation model (OGCM) and forced with a common climate forcing. Results are applied to a fish bioenergetics model for two geographically distinct ocean regions off Japan including the Oyashio, mixed, and Kuroshio subregions and off California including the subarctic, transition and subtropical subregions. The model is applied to two fish species (Pacific saury: Cololabis saira and Pacific herring: Clupea harengus pallasi) with different life histories in each region and the influence of three different “regime shift” periods was explored. With this approach, we narrow the observed biological response and model dynamics to reflect local conditions and eliminate differences related to the model formulations in each region. In general, the trend in temperature was negatively correlated with trends in the zooplankton community. Out-of-phase herring growth trends were observed between the Japan and California regions (r =−0. 259, p =0. 02). In-phase growth trends between herring and saury were observed at the California region (r =0. 61, p <0. 01). We did note some evidence of a basin-scale PDO mode response. During 1980–1985, simulated saury and herring in both regions showed a consistent increase in weight-at-age. In the Oyashio subregion, temperature decreased and all three zooplankton groups increased beginning around 1980. The same pattern of a decrease in temperature and an increase in zooplankton densities was observed between 1980 and 1985 in the subarctic subregion of California. Results are discussed in the context of ecosystem-based fisheries management. [Copyright &y& Elsevier]

Soil salinity plays a very important role in determining the distribution of vegetation, plant productivity, and biogeochemical processes in coastal marsh ecosystems. Salinity gradients and salinity–vegetation associations in salt marshes have often been observed but rarely explained. A quantitative and systematic study on the soil salinity distribution in salt marshes is not only important to the understanding of coastal marsh ecosystems but also to the development of a potentially useful ecological and environmental indicator. In this research, we developed a salt marsh soil salinity model based on an existing salt and water balance model with modifications to several key features to examine the impacts of tidal forcing, climate, soil, vegetation, and topography on soil salinity distributions of the Atlantic and Gulf coastal marshes. This model was calibrated and validated using field observations from the St. Marks National Wildlife Refuge (NWR) of northwestern Florida, USA. The results showed that the model had good agreement (r 2 =0.84, n =15, P <0.001) with field observations. We found that the mean higher high water (MHHW) level determines the location of the salinity maximum in a coastal salt marsh. Simulations indicate that tidal irregularity primarily controls the width of the salinity maximum band. Evapotranspiration, temperature, hydraulic conductivity, and incoming tidal salinity significantly affect the salinity maximum band, which may lead to the formation of salt barrens/flats when reaching a threshold level. [Copyright &y& Elsevier]

There is increasing awareness that solutions to degraded quality and excessive quantity of stormwater and resulting impacts on downstream water bodies may require a watershed approach to management rather that the incremental approach that is now common. Examination of low-relief watersheds characteristic of the southeastern coastal plain reveals common hierarchical patterns of surface water convergence that may be emulated in developed watersheds to enhance the efficacy of peak-flow attenuation and pollutant removal. A dynamic systems model was developed to compare stormwater management using a hierarchical network of treatment wetlands with the standard incremental approach wherein treatment systems are designed considering only site-level effluent criteria. The model simulates watershed hydrology, suspended sediment transport and phosphorus removal and transformation. Results indicate that watershed planning of stormwater collection and treatment systems using hierarchical networks can greatly enhance overall effectiveness (annual retention improvements of 31% for flow, 36% for sediment and 27% for phosphorus) with respect to an equal area of uniformly sized wetlands. Further, network proportions can be adjusted to specific runoff characteristics. Distinct roles were observed for each wetland size class: small headwater wetlands effectively removed sediment, medium-sized mid-reach wetlands retained phosphorus, while large wetlands primarily stored and attenuated long-period hydrologic flows. [Copyright &y& Elsevier]

Abstract: It is an ongoing challenge to develop and demonstrate management practices that increase the sustainability of agricultural systems. Soil carbon and nitrogen dynamics directly affect soil quality, crop productivity and environmental impacts. Root systems are central to the acquisition of water and nutrients by plants, but are also a major pathway for the inputs of carbon and nutrients to soil. The complexity of both biotic and abiotic interactions, combined with stochastic changes in root architecture, makes it difficult to understand below-ground dynamics on the basis of experimentation alone. The integration of dynamic models of above-ground growth, three-dimensional root system demography, and interactions between plants and the environment, into one single model is a major challenge because of the complexity of the systems. In order to understand the interaction between a plant and the environment, it is advantageous to develop a model framework to integrate submodels that simulate various plant and environmental components. The objective of this paper is to outline a mechanistic and process-based model, which is capable of simulating interactions among environmental conditions around plants, plant growth and development, nitrogen and carbon cycles, with a three-dimensional root system submodel as an interface. The model presented in this paper is a mixed dimensional, multi-layer, field scale, weather-driven and daily time-step dynamic simulation model. The current version includes a plant growth and development component, a nitrogen cycling component, a carbon cycling component, plus a soil water component that includes representation of water flow to field drains as well as downwards through the soil layers, together with a heat transfer component. The components themselves and linkage among components are designed using object-oriented techniques, which makes the model robust, understandable and reusable. The components are implemented in the C++ programming language, and inputs and outputs of all components are organised as a database in either Microsoft® SQL Server 2000, Access 2000 or MySQL5.0. Root architecture is visualised by using the OpenGL graphics system. Preliminary validation with two separate experimental datasets shows that the model can reasonably simulate root systems, nitrogen cycling, water movement and plant growth. [Copyright &y& Elsevier]

Abstract: Run-time calibration, i.e. adjusting simulation results for field observations of model driving variables during run-time, may allow correcting for deviations between complex mechanistic simulation model results and actual field conditions. Leaf area index (LAI) and canopy nitrogen contents (LeafNWt) are the most important driving variables for these models, as they govern light interception and photosynthetic production capacity of the crop. Remote sensing may provide (spatial) data from which such information can be estimated. How, when and at what frequency such additional information is integrated in the simulation process may have various effects on the simulations. The objective of this study was to quantify the effects of different run-time calibration scenarios for final grain yield (FGY) simulations in order to optimize remote sensing image (RS) acquisition. The PlantSys model was calibrated on LAI and LeafNWt for maize in France and used to simulate maize crop growth in the Argentina and the USA, for which non-destructive estimates of LAI and leaf chlorophyll contents were acquired by optical measurement techniques. Leaf chlorophyll data were used to estimate LeafNWt. Due to its structure, the PlantSys model was more susceptible to run-time calibration with LeafNWt than with LAI. Run-time calibration with LAI showed the largest effect on FGY before and around flowering, and could mainly be related to maintenance respiration costs. Run-time calibration with LeafNWt showed the largest effect on FGY at and after flowering and could mainly be related to the change in effective radiation interception due to change in leaf life. The accuracy of LAI estimates showed a major effect on FGY for underestimations but was small in absolute sense. The accuracy of LeafNWt estimates had significant impact at all crop development stages, but was the strongest after flowering where crop growth and nitrogen uptake are less able to recuperate from changes in LeafNWt. In absolute sense, the effect on FGY was as strong as the accuracy of the LeafNWt estimates when applied in the early reproductive stages. Based on these results it was concluded that remotely sensed in-field variability of LAI and LeafNWt is valuable information that can be used to spatially differentiate model simulations. Run-time calibration at sub-field level may lead to more accurate simulation results for whole fields. [Copyright &y& Elsevier]

Abstract: Current threats of invasive species have significant implications for ecological systems. Given their potential impacts, invasive species have been the subject of extensive empirical and theoretical studies. However, these studies have tended to focus on species that produce highly visible ecological and economic impacts. In our study, we take a step back from focusing on these high-impact invasive species, and examine the general colonization (invasion) process of exotic species that have various “competitive abilities” against the native species. Using a two-species cellular automaton model, we demonstrate that: (1) a threshold level of competitive ability is required for the exotic species to successfully establish in a new landscape and (2) an exotic species with superior competitive ability does not necessarily become dominant in a landscape (alternatively, a species that has inferior competitive ability may successfully colonize a new system). Our findings have significant implications for the study of species invasions and also provide clues to how species assemble in ecological communities. [Copyright &y& Elsevier]

Abstract: We have developed a simulation model for predicting the recruitment response of Pinus nigra from unburned edges in areas affected by large wildfires, where the regeneration of burned forests of this tree species is very low. We have simulated the distribution of P. nigra seedlings at different distances from the unburned edges by integrating empirical field data for the different processes affecting seed and seedling success. The simulation model determines the final number of seedlings established in any subplot, within the burned area, as the multiplication of a number of statistically independent processes, from cone and seed production and predation, to seed germination and seedling establishment. Probabilities are drawn at random at each time step from the experimental distributions that describe those processes. The model runs for a given number of years, thus simulating the accumulative effects on the total number of established seedlings of the different processes involved. That represents one model run, which is then repeated a sufficient number of times to calculate simulated distributions of established seedlings as a function of distance from the forest edge. The validation of those results with data from field measurements of seedling establishment in old-burned areas has demonstrated the ability of the simulation algorithm to reproduce observed results. Furthermore, the simulations carried out with the model for actual plots, located near the margins of the burned areas affected by the largest fires affecting P. nigra forests in Catalonia in recent years, have all shown striking similarities. The simulated values of established seedlings follow a Gaussian-like distribution in the first 100m, with a wide range of 2000–25,000seedlings/ha. There is also a clear trend for plots with medium and large trees to show an increment in increasing seedling establishment with tree density, whereas plots dominated by small trees give very low regeneration values. [Copyright &y& Elsevier]

Abstract: An important determinant of local population growth is the strength of density regulation resulting from intraspecific competition. Using a simulation model, it was analysed how density regulation interacts with dispersal properties (composed of density-dependent emigration, dispersal range and mortality) and landscape dynamics (patch destruction and regeneration) to affect the persistence of metapopulations. The results show that the complex interactions between intraspecific density regulation, dispersal and landscape dynamics do not allow for general conclusions for each of these factors. Therefore, a concept of connectivity which combines species and landscape attributes is used. To interpret the modelling results it was necessary to extend this concept considering two aspects: (1) the strength of connectivity determined by the mean number of immigrants (amplified by high emigration rates, low dispersal mortality and low landscape dynamics) and (2) the heterogeneity of connectivity determined by the spatio-temporal variability of immigration (enhanced by short-range dispersal, density-dependent emigration and landscape dynamics). Strong and homogeneous connectivity results in strong synchronization of local dynamics but allows for efficient colonization, whereas weak and heterogeneous connectivity has the reverse effects. It was found that metapopulations with compensatory density regulation always profit from strong and homogeneous connectivity. In contrast, metapopulations with strong over-compensatory density regulation have an intrinsically high local extinction risk due to their complex dynamics and therefore require both high colonization and low synchronization. Thus, they suffer from a combination of strong and homogeneous as well as weak and heterogeneous connectivity. In conclusion, the study suggests that conservation plans for metapopulations should consider the impact of the management strategies on the strength and heterogeneity of the connectivity pattern with respect to the mode of intraspecific competition of the target species. The establishment of dispersal corridors, stepping stones or a decrease in landscape dynamics are likely to be advantageous for species with compensatory density regulation but may be detrimental to species with over-compensatory density regulation. [Copyright &y& Elsevier]

Abstract: The model TREEDEV is developed based on the TREEDYN and TREEGROW models. In TREEDEV model the characteristics and available data of Masson pine (Pinus massoniana) forest in Dinghushan Biosphere Reserve are taken into account as a demonstration. The model was validated by plantation forest and natural forest data. Calculation of tree growth is based on carbon and nitrogen balance, which depends on the photoproduction of its needles, respiration, nitrogen content of all organisms and that in soil, and other losses due to respiration, litterfall and renewal of stem, branch, needle and root. The model includes four aspects: (1) Exogenous driving force solar radiation, which is a function of latitude, specific meteorological conditions and seasonal time. (2) Canopy photoproduction, in this submodel the influence of temperature, solar radiation, seasonal time and nitrogen content of the soil are taken into account. (3) Biomass compartment into needles, fine roots, coarse roots, branches and stems, enabling us to calculate the appropriate respiration demands for the maintenance of the living biomass fractions, fine roots and needles renewal more accurately. (4) The cycle of carbon and nitrogen in soil, which is related to the decomposition and humification of soil organic matter and litter, nitrogen mineralization from litter, and nitrogen leaching. The dynamics of nitrogen include nitrogen uptake demand of the tree, the loss of nitrogen, and nitrogen relocation before litter shedding and the nitrogen supply from soil. Combined with field condition, scenarios involving litter removal and protective fencing were taken into account. Sensitivity analysis was performed in which 43 model independent variables were varied and analyzed in respect to their influence on 22 dependent variables describing forest state. Simulation results showed that litter removal has an influence on the growth of vegetation, which changes the environment, and retards the renewal of litter and reduces the uptake and fixation of available nitrogen, especially to needle and fine root. The forest with low intensity disturbance can be restored if it is fenced within an appropriate time (30 years in this paper), but this retards the maturation time of stands and depreciates the economic value of the wood. In this paper carbon and nitrogen cycles are analyzed in view of physiological processes with the goal of improving forest management planning. [Copyright &y& Elsevier]

Abstract: We developed an individual-based model to study the effects of different regimes of harvesting eggs and natural predation on reproductive success in a colony of the glaucous-winged gull (Larus glaucescens) in Glacier Bay National Park, Alaska. The model incorporates the sequence of egg laying, relaying, and incubation to hatching for individual nests and calculates hatching success, incubation length, and the total number of eggs laid (as a result of re-nesting and relaying) in all nests in the colony. Stochasticity is incorporated in the distribution of nest lay dates, predation rates, and nests attacked during predation and harvest events. We estimated parameter values by fitting the model to data collected at a small colony during 1999 and 2000 using maximum likelihood. We then simulated harvests and analyzed model predictions. Model outputs indicate that harvesting early, and at one time, provides a predictable take of eggs with the least impact to gulls. [Copyright &y& Elsevier]

Abstract: Ecological models have their greatest potential for conservation in the context of adaptive management, but there are few examples where models have been updated as new data have become available. We update a predator–prey model built to anticipate the consequences of wolf (Canis lupus) reintroduction into Yellowstone National Park, with new data accumulated since wolves were released in 1995. Observed response to wolf recovery allows us to evaluate our ability to predict system dynamics and thereby address concerns about future impacts of predation on elk (Cervus canadensis) numbers and harvest by hunters. Structural assumptions of the model include a dynamic carrying capacity for elk, K elk(t), varying as a function of winter severity and summer forage production. During severe winters the aerial extent of Yellowstone''s Northern Range gets smaller resulting in density-dependent migration of elk outside the park where they are subject to hunter harvest. The updated model predicts that hunter harvest of elk will cause a decline of mean herd size relative to that expected without harvest. Wolf predation results in a further 21% reduction in elk herd size with wolf consumption averaging approximately 1035 elk annually. Elk harvest is reduced by wolves yet annual hunter harvest was sustained at an average of 1089 elk. Predation and hunter harvest is density-dependent providing a stabilizing influence that reduces the risk of severe elk population decline. Using simulation models in adaptive management of the wolf–ungulate system in Yellowstone reinforces agency management policies, especially the density-dependent harvest quota for elk. [Copyright &y& Elsevier]