Integrating farming techniques in an ecological matrix model: Implementation on the primrose (Primula vulgaris)

Several studies have proven the importance of field margins in sustaining biodiversity and other work has been done on the effect of field management on field margin flora. However few models have been built to predict the effects of field management on the flora. Our project addresses this need for a model capable of predicting the effect of cropping techniques and their timing on the flora of field margins. Primula vulgaris is a biodiversity indicator, characteristic of undisturbed flora and found in field margins and woodlands: its population has been declining for several years. We created a temporal matrix model of P. vulgaris populations on field margins, taking into account the effects of field, field margin and roadside management based on literature and expert knowledge. We then analysed its sensitivity to demographic parameters by comparing lambda (growth rate) sensitivity and elasticity. We compared the management parameter effect using the relative growth rate of the population after 6 years of simulation. Sensitivity analysis to biological parameters showed the importance of adult survival and seed production and germination. Results show that P. vulgaris is particularly sensitive to broad-spectrum herbicides and that other management techniques like early mowing, scything and scrub-killer (diluted broad-spectrum herbicide or specific herbicide) are less aggressive. Our simulations show that management of cash crops in Brittany is too aggressive for P. vulgaris populations and that 4-5 years of grassland in the adjacent field are necessary to maintain populations.     

Zooplankton population model coupled to a biogeochemical model of the North Western Mediterranean Sea ecosystem

A stage structured population (SSP) model based on Fennel's [Fennel, W., 2001. Modelling copepods with links to circulation models. Journal of Plankton Research, 23, 1217–1232] equations is applied to Centropages typicus (Kröyer), a dominant copepod species of the North Western Mediterranean Sea (NWMS) and a prey of small pelagic fish. The model considers five groups of stages and development rates are represented by a mechanistic formulation depending on individual specific growth in each stage. Individual growth is calculated from the individual energy budget depending on food availability and temperature.     

Modeling the population dynamics of cotton bollworm Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) over a wide area in northern China

The cotton bollworm Helicoverpa armigera (Lepidoptera: Noctuidae) is one of the most serious crop pests in northern China, calling for accurate prediction of pest outbreaks and strategies for pest control. A computer model is developed to simulate the population dynamics of H. armigera over a wide area in northern China. The area considered covers 12 provinces where serious outbreaks of H. armigera have been observed. In this model, pest development is driven by local ambient temperature, and adults migrate long distances between regions and select preferred hosts for oviposition within a region. Six types of host including cotton, wheat, corn, peanut, soybean and a single category composed of all other minor hosts are considered in this model. Survival rates of eggs and larvae are based on life-table data, and simulated as a function of host type, host phenology and temperature. The incidence of diapause depends on temperature and photoperiod experienced during the larval stage. Survival rate of non-diapause pupae is a nonlinear function of rainfall, and overwinter survival rate is a nonlinear function of temperature. Insecticide is applied when population density exceeds the economic threshold on a host crop within a region. Comparisons of model output with light-trap data indicate that our model reflects the pest population dynamics over a wide area, and could potentially be used for testing novel pest control strategies in northern China.     

Development and validation of an individual based Daphnia magna population model: The influence of crowding on population dynamics

An individual-based model was developed to predict the population dynamics of Daphnia magna at laboratory conditions from individual life-history traits observed in experiments with different feeding conditions. Within the model, each daphnid passes its individual life cycle including feeding on algae, aging, growing, developing and – when maturity is reached – reproducing. The modelled life cycle is driven by the amount of ingested algae and the density of the Daphnia population. At low algae densities the population dynamics is mainly driven by food supply, when the densities of algae are high, the limiting factor is “crowding” (a density-dependent mechanism due to chemical substances released by the organisms or physical contact, but independent of food competition).     

Influence of host migration between woodland and pasture on the population dynamics of the tick Ixodes ricinus: A modelling approach

Ticks act as vectors of pathogens that can be harmful to animals and/or humans. Epidemiological models can be useful tools to investigate the potential effects of control strategies on diseases such as tick-borne diseases. The modelling of tick population dynamics is a prerequisite to simulating tick-borne diseases and the corresponding spread of the pathogen. We have developed a dynamic model to simulate changes in tick density at different stages (egg, larva, nymph and adult) under the influence of temperature. We have focused on the tick Ixodes ricinus, which is widespread in Europe. The main processes governing the biological cycles of ticks were taken into account: egg laying, hatching, development, host (small, mainly rodents, or large, like deer and cattle, mammals) questing, feeding and mortality. This model was first applied to a homogeneous habitat, where simulations showed the ability of the model to reproduce the general patterns of tick population dynamics. We considered thereafter a multi-habitat model, where three different habitats (woodland, ecotone and meadow) were connected through host migration. Based on this second application, it appears that migration from woodland, via the ecotone, is necessary to sustain the presence of ticks in the meadow. Woodland can therefore be considered as a source of ticks for the meadow, which in turn can be regarded as a sink. The influence of woodland on surrounding tick densities increases in line with the area of this habitat before reaching a plateau. A sensitivity analysis to parameter values was carried out and demonstrated that demographic parameters (sex ratio, development, mortality during feeding and questing, host finding) played a crucial role in the determination of questing nymph densities. This type of modelling approach provides insight into the influence of spatial heterogeneity on tick population dynamics.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

A process-based population dynamics model to explore target and non-target impacts of a biological control agent

The risks and benefits associated with efforts to control invasive alien species using classical biological control are being subjected to increasing scrutiny. A process-based population dynamics model was developed to explore the interactions between a folivorous biological control agent, Cleopus japonicus, and its plant host Buddleja davidii. The model revealed that climate could have a significant impact upon the interactions between B. davidii and C. japonicus. At the coolest sites, the impact of C. japonicus on B. davidii was slowed, but it was still eventually capable of controlling populations of B. davidii. At the warmer sites where both B. davidii and C. japonicus grew faster, B. davidii succumbed rapidly to weevil damage. We hypothesise that barring an encounter with a natural enemy, C. japonicus will eventually be able to provide sustained control B. davidii throughout the North Island of New Zealand. The model scenarios illustrate the potential for the C. japonicus population to attain high densities rapidly, and to defoliate patches of B. davidii, creating the potential for spill-over feeding on non-target plants. The potential magnitude of this threat will depend partly on the climate suitability for C. japonicus, the pattern by which it migrates in response to a reduction in the available leaf resource, and the suitability of non-target plants as hosts. In all migration scenarios considered, the pattern of population growth and resource consumption by C. japonicus was exponential, with a strong tendency toward complete utilisation of resource patches more quickly at the warmer compared to colder sites. In addition to providing some useful hypotheses about the effects of climate on the biological control system, and the non-target risks, it also provides some insight into the mechanisms by which climate affects the system.     

A population model for the peach fruit moth, Carposina sasakii Matsumura (Lepidoptera: Carposinidae), in a Korean orchard system

A population model for the peach fruit moth, Carposina sasakii Matsumura, was constructed to understand the population dynamics of this pest species and to develop an effective management strategy for various orchard (apple, peach, apple + peach) systems. The model was structured by the five developmental stages of C. sasakii: egg, larva, pupa, larval-cocoon (overwintering larva), and adult. The model consisted of a series of component models: (1) a bimodal spring adult emergence model, (2) an adult oviposition model, (3) stage emergence models of eggs, larvae, and pupae, (4) a larval survival rate model in fruits, (5) a larval-cocoon formation model, and (6) an insecticide effect model. Simulations using the model described the typical patterns of C. sasakii adult abundance in various orchard systems well, and was specific to the composition of host plants: three adult abundance peaks (first peak, mid-season peak, and last peak) a year with decreased peaks after the first peak in monoculture orchards of late apple, two adult peaks a year with a much higher last peak in monoculture orchards of early peach, and three adult peaks a year with much higher later peaks in mixed orchards of late apple and early peach. The average deviation between model outputs and actual records for first and second adult peak dates was 2.8 and 3.9 d, respectively, in simulations without an insecticide effect. The deviation decreased when insecticide effects were incorporated into the model. We also performed a sensitivity analysis of our model, and suggest possible applications of the model.     

Interpreting spatial heterogeneity of crop yield with a process model and remote sensing

A process-based crop growth model (Vegetation Interface Processes (VIP) model) is used to estimate crop yield with remote sensing over the North China Plain. Spatial pattern of the key parameter—maximum catalytic capacity of Rubisco (V_cmax) for assimilation is retrieved from Normalized Difference of Vegetation Index (NDVI) from Terra-MODIS and statistical yield records. The regional simulation shows that the agreements between the simulated winter wheat yields and census data at county-level are quite well with R² being 0.41-0.50 during 2001-2005. Spatial variability of photosynthetic capacity and yield in irrigated regions depend greatly on nitrogen input. Due to the heavy soil salinity, the photosynthetic capacity and yield in coastal region is less than 50 μmol C m⁻² s⁻¹ and 3000 kg ha⁻¹, respectively, which are much lower than that in non-salinized region, 84.5 μmol C m⁻² s⁻¹ and 5700 kg ha⁻¹. The predicted yield for irrigated wheat ranges from 4000 to 7800 kg ha⁻¹, which is significantly larger than that of rainfed, 1500-3000 kg ha⁻¹. According to the path coefficient analysis, nitrogen significantly affects yield, by which water exerts noticeably indirect influences on yield. The effect of water on yield is regulated, to a certain extent, by crop photosynthetic capacity and nitrogen application. It is believed that photosynthetic parameters retrieved from remote sensing are reliable for regional production prediction with a process-based model.     

Testing a new model of aphid abundance with sedentary and non-sedentary predators

Aphid population dynamics has been thoroughly investigated, especially in tree-dwelling aphids. Among the controls of the aphid rate of increase are the negative effects of antagonists, the positive effects of mutualists, the density-dependence of the aphid dynamics, and the non-stationary quality of plant tissues. Here we present a mechanistic model of aphid growth that considers most of these governing factors using a simple formulation. What is new in this model is that it considers two kinds of antagonists. The first kind is a guild of aphid predator specialists that includes ladybirds (Coleoptera: Coccinellidae), but also species of some families of Hemiptera, Diptera, and Neuroptera. The second kind of antagonists consists of omnivores or generalist predators and in this particular setting is exemplified by the European earwig Forficula auricularia (Dermaptera: Forficulidae). The model developed here compared the effects of these two different kinds of aphid predators, the second one always at the site (sedentary predators) and the first one that arrives in important numbers only once the aphid population has already developed to some degree (non-sedentary predators). Multiple model parameter sets, representing different hypotheses about controls on aphid populations, were evaluated within the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The model correctly reproduced the experimental data obtained in an organic citrus grove showing the important effect that sedentary predators as earwigs can have on the aphid populations. Low densities of sedentary predators or even low predation rates can have a disproportionate effect on the final aphid density, as they prey on small populations, when the per capita effect on the aphid population is higher. During the main spring peak of aphids the role of non-sedentary predators is secondary, as they track the aphid density rather than control it. However, these non-sedentary predators are important within the proposed model to keep the second autumn peak of aphids at low values.     

Identifying key life-traits for the dynamics and gene flow in a weedy crop relative: Sensitivity analysis of the GeneSys simulation model for weed beet (Beta vulgaris ssp. vulgaris)

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.     

Modelling the spatial population dynamics of the green oak leaf roller (Tortrix viridana) using density dependent competitive interactions: Effects of herbivore mortality and varying host-plant quality

Cyclic population dynamics of forest insects with periods of more than two generations have been discussed in relation to a variety of extrinsic and intrinsic forces. In the present study, we employed the selection pressure of density dependent competitive interactions according to Witting's equations (Witting, 2000) as driver for a discrete spatiotemporal model of the green oak leaf roller (Tortrix viridana). The model was successfully parameterised to rebuild the cyclic population dynamics of an empirical data set of a 30-year leaf roller monitoring in Russia. Our analysis focussed on the role of herbivore mortality and host plant food quality, which have a significant effect on T. viridana population dynamics. An additional egg or larvae mortality lowers population density and can lead to selection pressures that favour individuals with higher growth rate. This increased population growth rate can not only compensate the additional mortality, but also can lead to higher average moth abundances in subsequent generations. Furthermore, we analysed the effect of inter- and intraspecific variation in host plant quality on herbivore population dynamics and the spatial distribution of abundance and defoliation patterns. We found significant effects of the qualitative composition of a trees neighbourhood on the herbivore population of the respective tree. Also, the patchy damage patterns observable in reality have been reproduced by the present model. The applicability of the model approach and the putative genetic processes underlying Witting's model are discussed.     

Agent-based simulation of effects of stress on forest tent caterpillar (Malacosoma disstria Hübner) population dynamics

The forest tent caterpillar (Malacosoma disstria Hübner) (FTC) has an outbreak cycle of approximately 10 years; however, smaller spatial scale analyses show some regions have longer or more frequent periods of high defoliation. This may be a result of local forest fragmentation, pollution or other sources of stress that may affect FTC directly or indirectly through stress on their hosts or parasitoids. Population dynamics of FTC were examined to investigate how stress may alter the severity and frequency of defoliation. We developed a spatially explicit agent-based model to simulate the host-parasitoid dynamics of FTC. Theoretical and empirically derived parameters were established using past literature and over 50 years of population data of FTC from Ontario, Canada. We find that increasing FTC fecundity, FTC dispersal or parasitoid mortality resulted in more severe outbreaks while a decrease in parasitoid fecundity or searching efficiency resulted in an overall elevation of defoliation. Parasitoid efficiency was the most effective parameter for altering the FTC defoliation. Since plant stress has been shown to alter several of these parameters in nature due to changes in food quality, habitat suitability, and chemical cue interference, our results suggest that forests affected by stressors such as climate change and pollution will have more severe and frequent defoliation from these insects than surrounding unaffected forests. As stressors such as drought and pollution emissions are predicted to increase in frequency or intensity over the next few decades, understanding how they may affect the outbreak cycle of a forest defoliator can aid in planning strategies to reduce the detrimental effects of this insect.     

A system dynamics model for the management of the Manila clam, Ruditapes philippinarum (Adams and Reeve, 1850) in the Bay of Arcachon (France)

The Manila clam Ruditapes philippinarum (Adams and Reeve, 1850) is one of the mollusc species that, driven mainly by the shellfish market industry, has extended throughout the world, far beyond the limits of its original habitat. The Manila clam was introduced into France for aquaculture purposes, between 1972 and 1975. In France, this venerid culture became increasingly widespread and, since 1988, this species has colonised most of the embayments along the French Atlantic coast. In 2004, this development resulted in a fishery of ca. 520 t in Arcachon Bay.     

Modeling individual and population dynamics in a consumer–resource system: Behavior under food limitation and crowding and the effect on population cycling in Daphnia

In population modeling, a considerable level of complexity is often required to provide trustworthy results, comparable with field observations. By assuring sufficient detail at the individual level while preserving the potential to explore the consequences at higher levels, individual-based modeling may thus provide a useful tool to investigate dynamics at different levels of organization. Still, population dynamics resulting from such models are often at odds with observations from the field. This may be partly caused by a lack of focus on the individual dynamics under conditions of food stress and starvation. I developed a physiologically structured, individual-based simulation model to investigate life history of Daphnia and its effect on population dynamics in response to the productivity of the system. In verifying model behavior with available literature data on life history and physiology, I paid special attention to the dynamics of food intake and the verification of individual level results under conditions of food limitation and starvation. I show that the maximum filtering rates under low food levels used in the current model are much closer to measured filtering rates than the ones used in other models. Being consistent with results on physiology and life history from experiments at a wide range of food availability (including starvation), the model generates low amplitude or high amplitude population density cycles depending on the productivity of the system, as observed in field and experimental populations of Daphnia and with the minimum population densities being one to two orders of magnitude lower in the high amplitude than in the low amplitude cycles. To generate results which are not only qualitatively but also quantitatively comparable to experimental and field observations, however, a crowding effect on the filtering response has to be incorporated in the model.     

On the sudden disappearance of Egeria densa from a Ramsar wetland site of Southern Chile: A climatic event trigger model

Contemporary shallow lakes theory proposes that these ecosystems may experience abrupt regime shifts due to small changes in controlling variables or triggers. So far, these triggers have been related mostly to nutrients as the immediate driver. During May 2004 the río Cruces wetland, a Ramsar site located in Southern Chile, underwent a major regime shift, from a clear water state, vastly dominated by the invasive macrophyte Egeria densa, to a turbid water state. In this article we show, through the analysis of long-term meteorological data that late fall 2004 was anomalous due to the presence of a high-pressure cell that persisted most of the month of May over Southern Chile. This climatic event caused an almost complete absence of precipitations and lower temperatures during this period, including several freezing nights. Eco-physiological experiments showed that 6 h exposure to desiccation kill the macrophyte. We developed a simple-biology dynamic model, under Stella Research 9.1, to show that the climatic anomaly of May 2004, plus the increased sedimentation of the wetland's floodplains, and the associated response of E. densa, explains its sudden disappearance from río Cruces wetland.     

Allowing macroalgae growth forms to emerge: Use of an agent-based model to understand the growth and spread of macroalgae in Florida coral reefs,with emphasis on Halimeda tuna

The growth patterns of macroalgae in three-dimensional space can provide important information regarding the environments in which they live, and insights into changes that may occur when those environments change due to anthropogenic and/or natural causes. To decipher these patterns and their attendant mechanisms and influencing factors, a spatially explicit model has been developed. The model SPREAD (SPatially-explicit Reef Algae Dynamics), which incorporates the key morphogenetic characteristics of clonality and morphological plasticity, is used to investigate the influences of light, temperature, nutrients and disturbance on the growth and spatial occupancy of dominant macroalgae in the Florida Reef Tract. The model species, Halimeda and Dictyota spp., are modular organisms, with an “individual” being made up of repeating structures. These species can also propagate asexually through clonal fragmentation. These traits lead to potentially indefinite growth and plastic morphology that can respond to environmental conditions in various ways. The growth of an individual is modeled as the iteration of discrete macroalgal modules whose dynamics are affected by the light, temperature, and nutrient regimes. Fragmentation is included as a source of asexual reproduction and/or mortality. Model outputs are the same metrics that are obtained in the field, thus allowing for easy comparison. The performance of SPREAD was tested through sensitivity analysis and comparison with independent field data from four study sites in the Florida Reef Tract. Halimeda tuna was selected for initial model comparisons because the relatively untangled growth form permits detailed characterization in the field. Differences in the growth patterns of H. tuna were observed among these reefs. SPREAD was able to closely reproduce these variations, and indicate the potential importance of light and nutrient variations in producing these patterns.     

A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations

In forest management and ecological research, consideration of the impacts and risks of climate change or management optimisation is complex. Computer models have long been applied as tools for these tasks. Process-based forest growth models claim to overcome the limitations of empirical statistical models, but the capacity of different process-based models and modelling approaches have rarely been compared directly. This study evaluates stepwise multiple regression models in comparison to four process-based modelling approaches (3-PG, 3-PG+, CABALA and Forest-DNDC) for greenfield predictions of Eucalyptus globulus plantation growth from 2 to 8 years after planting throughout southern Australia.     

COLIWAVE a simulation model for survival of E. coli O157:H7 in dairy manure and manure-amended soil

A simulation model was developed to investigate the relative effects of temperature, oxygen concentration, substrate content and competition by autochthonous microbial community on the oscillatory behaviour and survival of Escherichia coli O157:H7 in manure and manure-amended soil. The overall decline in E. coli O157:H7 was primarily determined by competition with autochthonous copiotrophic bacteria simulated by an inter-specific competition term according to Lotka-Volterra. Oscillations of bacterial populations were attained by the relationships between relative growth and death rates with readily available substrate content. The model contains a logistic and exponential relation of relative growth and death rates, respectively, of E. coli O157:H7 and copiotrophic bacteria with temperature, resulting in optimum curves for net growth rates similar to the curves reported in the literature. The model has been both calibrated and validated on experimental data. The model was used to perform sensitivity analysis and to evaluate different manure and soil management scenarios in terms of survival of E. coli O157:H7. The relative effects of changes in temperature on simulated survival time of E. coli O157:H7 were more pronounced than changes in oxygen condition. Testing manure storage scenarios with realistic data revealed that manure stored in a heap that was turned every week resulted in almost 70% reduction of E. coli O157:H7 survival compared to unturned manure. At the surface of a heap with unturned manure, simulated survival time was the longest (2.4 times longer than inside the same heap). The simulation model provides a new approach to investigating dynamic changes of invasive microorganisms in natural substrates such as manure or manure-amended soil.