Structural validation of an individual-based model for plague epidemics simulation

Plague remains endemic in many countries in the world and Madagascar is currently the country where the highest number of human plague cases is reported every year. The investigation of causal factors, which command the disease dynamics in rodent populations, is a crucial step to forecast, control and anticipate the infection extension to humans. This paper presents simulation results obtained from an epidemic model, SIMPEST, designed to simulate bubonic plague in a rodent population at a high level of spatial and temporal resolution. We developed a structurally realistic individual-based model, mobilizing knowledge about fleas and rats behaviour, inter-individual plague transmission, and disease evolution in individual organisms, so that the model reflects the way the real system operates and to generate spatial and temporal patterns of disease spread. To assess the structural validity of our simulations, we perform sensitivity analyses on the initial population size and spatial distribution, and compare our results with theoretical statements, garnered from both previous modelling experiences and repeated field observations. We show our results are consistent with referents about population size conditions for a disease to invade and persist and the effect of the contact network on disease dynamics.     

Testing metabolic scaling theory using intraspecific allometries in Antarctic microarthropods

Quantitative scaling relationships among body mass, temperature and metabolic rate of organisms are still controversial, while resolution may be further complicated through the use of different and possibly inappropriate approaches to statistical analysis. We propose the application of a modelling strategy based on the theoretical approach of Akaike's information criteria and non‐linear model fitting (nlm). Accordingly, we collated and modelled available data at intraspecific level on the individual standard metabolic rate of Antarctic microarthropods as a function of body mass (M), temperature (T), species identity (S) and high rank taxa to which species belong (G) and tested predictions from metabolic scaling theory (mass‐metabolism allometric exponent b = 0.75, activation energy range 0.2–1.2 eV). We also performed allometric analysis based on logarithmic transformations (lm). Conclusions from lm and nlm approaches were different. Best‐supported models from lm incorporated T, M and S. The estimates of the allometric scaling exponent linking body mass and metabolic rate resulted in a value of 0.696 ± 0.105 (mean ± 95% CI). In contrast, the four best‐supported nlm models suggested that both the scaling exponent and activation energy significantly vary across the high rank taxa (Collembola, Cryptostigmata, Mesostigmata and Prostigmata) to which species belong, with mean values of b ranging from about 0.6 to 0.8. We therefore reached two conclusions: 1, published analyses of arthropod metabolism based on logarithmic data may be biased by data transformation; 2, non‐linear models applied to Antarctic microarthropod metabolic rate suggest that intraspecific scaling of standard metabolic rate in Antarctic microarthropods is highly variable and can be characterised by scaling exponents that greatly vary within taxa, which may have biased previous interspecific comparisons that neglected intraspecific variability.     

A simulation framework for modeling anthropogenic disturbances in habitat networks

Anthropogenic disturbances, like roads, increase the landscape fragmentation and affect wildlife migration and biodiversity. Such disturbances often prevent migration of wildlife due to increased barriers and mortality effects.

The aim of our simulation based approach is to assess the landscape permeability considering anthropogenic disturbances. The developed framework SimapD imposes an abstract view of a habitat network, based on an undirected graph. The simulation is done by an individual-oriented approach, where individuals explore the idealized network. Based on the information gained during the simulation, an overall network permeability index is calculated, which can be used to compare different scenarios of landscape development. Disturbances are represented by sub-models, from which appropriate resistance and mortality rates can be deduced. In this paper this is demonstrated by the construction of a fuzzy road kill model for the federal state of Baden-Wuerttemberg, Germany. The utilization of the network permeability index and a comparison to other fragmentation measures is shown by an exemplary application.     

INDISIM, an individual-based discrete simulation model to study bacterial cultures.

An individual-based model has been developed and designed to simulate the growth and behaviour of bacterial colonies. The simulator is called INDISIM, which stands for INDividual DIScrete SIMulations. INDISIM is discrete in space and time, and controls a group of bacterial cells at each time step, using a set of random, time-dependent variables for each bacterium. These variables are used to characterize its position in space, biomass, state in the cellular reproduction cycle as well as other individual properties. The space where the bacterial colony evolves is also discrete. A physical lattice is introduced, subject to the appropriate boundary conditions. The lattice is subdivided into spatial cells, also defined by a set of random, time-dependent variables. These variables may include concentrations of different types of particles, nutrients, reaction products and residual products. Random variables are used to characterize the individual bacterium and the individual particle, as well as the updating of individual rules. Thus, the simulations are stochastic rather than deterministic. The whole set of variables, those that characterize the bacterial population and the environment where they evolve, enables the simulator to study the behaviour of each microorganism-such as its motion, uptake, metabolism, and viability-according to given rules suited for the system under study. These rules require the input of only a few parameters. Once this information is inputted, INDISIM simulates the behaviour of the system providing insights into the global properties of the system from the assumptions made on the properties of the individual bacteria. The relation between microscopic and global properties of the bacterial colony is obtained by using statistical averaging. In this work INDISIM has been used to study (a) biomass distributions, (b) the relationship between the rate of growth of a bacterial colony and the nutrient concentration and temperature, and (c) metabolic oscillations in batch bacterial colonies. The simulation results are found to be in very good qualitative agreement with available experimental data, and provide useful insights into the mechanisms involved in each case.     

General response patterns of fish populations to stress: an evaluation using an individual-based simulation model

General response patterns of fish populations tostress, originally proposed by Colby for fisheriesrehabilitation and later adapted by Munkittrick forcontaminants, were evaluated using an individual-basedsimulation model. General response patterns relatechanges in population-level variables to the type ofstress. The model follows the daily growth,mortality, and spawning of individual yellow perch andwalleye through their lifetime, and was corroboratedusing Oneida Lake data. Two versions of the model wereused: population (yellow perch only) and community(dynamic predation on yellow perch by walleye). Eightstresses were imposed on the population and communityversions of the model and 100-year simulations wereperformed. Response patterns were defined by changesin predicted yellow perch mean population abundance,mean age of adults, and mean adult growth (representedby mean length at age-7). Proposed response patternswere similar to those predicted using the populationversion of the model. Simulations using the communityversion of the model distorted the response patterns,either causing amplification, dampening, or reversalof many of the patterns. Predicted response patternsbecame unique when additional variables were included.Our model results suggest that caution is appropriatein interpreting general response patterns based onmean age, or when the population of interest plays amajor role in a relatively simple food web. The responsepattern approach may be better at identifying the lifestage impacted rather than the mechanism of the stress.     

Stochastic simulation of size variation in turbot: possible causes analysed with an individual-based model

Causes of size variation in a population of juvenile turbot were studied using an individual based model (IBM). Each simulation started with 800 (divided into eight groups of 100 each) 120-day-old (posthatch) juveniles and was run for 140 days, and the data gained from model simulations compared directly with the result of a laboratory study with size-graded turbot. Stochastic growth with memory, which was included in the models as an individual genetical growth rate variation, is important in explaining size variation, and the combination between individual genetic growth rate and social interactions related to size-dependent hierarchies also contributes to size variation. The use of size-dependent growth rate alone fails to explain size variation, and is of little value in predicting size variation in turbot culture. Further, the results indicate formation of different types of size hierarchies for different sizes of juvenile turbot.     

Deciduous and evergreen trees differ in juvenile biomass allometries because of differences in allocation to root storage

Background and Aims

Biomass partitioning for resource conservation might affect plant allometry, accounting for a substantial amount of unexplained variation in existing plant allometry models. One means of resource conservation is through direct allocation to storage in particular organs. In this study, storage allocation and biomass allometry of deciduous and evergreen tree species from seasonal environments were considered. It was expected that deciduous species would have greater allocation to storage in roots to support leaf regrowth in subsequent growing seasons, and consequently have lower scaling exponents for leaf to root and stem to root partitioning, than evergreen species. It was further expected that changes to root carbohydrate storage and biomass allometry under different soil nutrient supply conditions would be greater for deciduous species than for evergreen species.

Methods

Root carbohydrate storage and organ biomass allometries were compared for juveniles of 20 savanna tree species of different leaf habit (nine evergreen, 11 deciduous) grown in two nutrient treatments for periods of 5 and 20 weeks (total dry mass of individual plants ranged from 0·003 to 258·724 g).

Key Results

Deciduous species had greater root non-structural carbohydrate than evergreen species, and lower scaling exponents for leaf to root and stem to root partitioning than evergreen species. Across species, leaf to stem scaling was positively related, and stem to root scaling was negatively related to root carbohydrate concentration. Under lower nutrient supply, trees displayed increased partitioning to non-structural carbohydrate, and to roots and leaves over stems with increasing plant size, but this change did not differ between leaf habits.

Conclusions

Substantial unexplained variation in biomass allometry of woody species may be related to selection for resource conservation against environmental stresses, such as resource seasonality. Further differences in plant allometry could arise due to selection for different types of biomass allocation in response to different environmental stressors (e.g. fire vs. herbivory).     

Egg limitation in host-parasitoid dynamics: an individual-based perspective

Theoretical models of parasitoid-host dynamics predict that egg limitation in parasitoids destabilizes community dynamics. However, although egg limitation is experienced by individual parasitoids with variable success of encountering hosts, such details were neglected in previous models. This study developed an individual-based parasitoid-host model that explicitly incorporates egg limitation and host encounters of individual parasitoids. The model indicates that the combination of egg limitation and variation in the success of encountering hosts stabilizes parasitoid-host dynamics. The stabilizing mechanism emerges from Jensen’s inequality because egg limitation makes the number of offspring inherently concave down in the number of encountered hosts. Reasons for the inconsistent predictions of the effect of egg limitation between the current model and previous models are discussed.     

The interplay of positive and negative species interactions across an environmental gradient: insights from an individual-based simulation model

Positive interspecific interactions are commonplace, and in recent years ecologists have begun to realize how important they can be in determining community and ecosystem dynamics. It has been predicted that net positive interactions are likely to occur in environments characterized by high abiotic stress. Although empirical field studies have started to support these predictions, little theoretical work has been carried out on the dynamic nature of these effects and their consequences for community structure. We use a simple patch-occupancy model to simulate the dynamics of a pair of species living on an environmental gradient. Each of the species can exist as either a mutualist or a cheater. The results confirm the prediction: a band of mutualists tends to occur in environmental conditions beyond the limits of the cheaters. The region between mutualists and cheaters is interesting: population density here is low. Mutualists periodically occupy this area, but are displaced by cheaters, who themselves go extinct in the absence of the mutualists. Furthermore, the existence of mutualists extends the area occupied by the cheaters, essentially increasing their realized niche. Our approach has considerable potential for improving our understanding of the balance between positive and negative interspecific interactions and for predicting the probable impacts of habitat loss and climate change on communities dominated by positive interspecific interactions.     

Trait evolution in an individual-based model of herbaceous vegetation

Many theoretical studies of evolution are based upon the concepts of the evolutionary stable strategy and optimal life-history solutions. An individual based model of vegetation is used to simulate life-history evolution under two different sets of environmental conditions. At one level the results suggest that optimal life-history solutions do appear to evolve. At the end of the simulations the vegetation that evolved in a fertile and uncut environment was taller, thinner and germinated later than that which developed in a less fertile and cut habitat. However, between simulation variation was observed to be high, particularly for the parameter regulating the timing of reproduction, and it showed no indication of reaching fixation. When this trait was prevented from mutating, the variances of other traits were seen to increase. Although at the population level between simulation variation was high, some traits achieved a degree of stability within simulations, suggesting that multiple adaptive peaks may be being approached. However, there was little evidence of trait fixation occurring within the most abundant genotype. It is considered that frequency dependent selection/Red Queen dynamics may be acting to prevent the most abundant genotype from reaching fixation. It is argued that if such processes prevent optimal genetic solutions from being achieved then the search for evolutionary stable strategies within the evolution of life-histories may be over simplistic.     

Transducers: an emerging probabilistic framework for modeling indels on trees

Contact: ihh{at}berkeley.edu Associate Editor: Alex Bateman     

Testing transition rates in generalized binomial models

In toxicological experiments the type II error is of important interest, but it is seldom discussed. For certain experiments like those in reproduction toxicology this paper gives some ideas to calculate it analytically. The basis is a generalized binomial model describing transition processes in experimental units. Each experimental unit contains a set of × members which develop from one to another specified state with some probability P. This transition probability P is allowed to vary from one experimental unit to the other; there is no restriction on the distribution of P and X, nor is P assumed to be independent of the total number × in contrast to the commonly used models. The model is extended to describe the treatment of an experimental unit, which permits to separate the treatment effect from the spontaneous development. This allows to investigate the power of some statistical tests for calculating sample sizes and for comparing different experimental designs.     

Developing a systematic framework for consistent allocation in LCA

Purpose

Multifunctionality in life-cycle assessment (LCA) is solved with allocation, for which many different procedures are available. Lack of sufficient guidance and difficulties to identify the correct allocation approach cause a large number of combinations of methods to exist in scientific literature. This paper reviews allocation procedures for recycling situations, with the aim to identify a systematic approach to apply allocation.

Methods

Assumptions and definitions for the most important terms related to multifunctionality and recycling in LCA are given. The most relevant allocation procedures are identified from literature. These procedures are expressed in mathematical formulas and schemes and arranged in a systematic framework based on the underlying objectives and assumptions of the procedures.

Results and discussion

If the LCA goal asks for an attributional approach, multifunctionality can be solved by applying system expansion—i.e. including the co-functions in the functional unit—or partitioning. The cut-off approach is a form of partitioning, attributing all the impacts to the functional unit. If the LCA goal asks for a consequential approach, substitution is applied, for which three methods are identified: the end-of-life recycling method and the waste mining method, which are combined in the 50/50 method. We propose to merge these methods in a new formula: the market price-based substitution method. The inclusion of economic values and maintaining a strict separation between attributional and consequential LCA are considered to increase realism and consistency of the LCA method.

Conclusions and perspectives

We identified the most pertinent allocation procedures—for recycling as well as co-production and energy recovery—and expressed them in mathematical formulas and schemes. Based on the underlying objectives of the allocation procedures, we positioned them in a systematic and consistent framework, relating the procedures to the LCA goal definition and an attributional or consequential approach. We identified a new substitution method that replaces the three existing methods in consequential LCA. Further research should test the validity of the systematic framework and the market price-based substitution method by means of case studies.

     

Diffusion-limited predator-prey dynamics in Euclidean environments: an allometric individual-based model

We claim that diffusion-limited rates of reaction can be an explanation for the altered population dynamics predicted by models incorporating local interactions and limited individual mobility. We show that the predictions of a spatially explicit, individual-based model result from reduced rates of predation and reproduction caused by limited individual mobility and patchiness. When these reduced rates are used in a mean-field model, there is better agreement with the predictions of the simulation model incorporating local interactions. We also explain previous findings regarding the effects of dimensionality on population dynamics in light of diffusion-limited reactions and Pólya random walks. In particular, we demonstrate that 3D systems are better "stirred" than 2D systems and consequently have a reduced tendency for diffusion-limited interaction rates.     

Maintaining and restoring hydrologic habitat connectivity in mediterranean streams: an integrated modeling framework

Hydrologic alterations designed to provide a stable water supply and to prevent flooding are commonly used in mediterranean-climate river (med-rivers) basins, and these alterations have led to habitat loss and significant declines in aquatic biodiversity. Often the health of freshwater ecosystems depends on maintaining and recovering hydrologic habitat connectivity, which includes structural components related to the physical landscape, functionality of flow dynamics, and an understanding of species habitat requirements for movement, reproduction, and survival. To advance our understanding of hydrologic habitat connectivity and benefits of habitat restoration alternatives we provide: (1) a review of recent perspectives on hydrologic connectivity, including quantitative methods; and (2) a modeling framework to quantify the effects of restoration on hydrologic habitat connectivity. We then illustrate this approach through a case study on lateral hydrologic habitat connectivity that results from channel restoration scenarios using scenarios with different historic and climate-change flows to restore fish floodplain habitat in a med-river, the San Joaquin River, California. Case study results show that in addition to the channel alterations, higher flows are required to recover significant flooded habitat area, especially given reductions in flows expected under climate change. These types of studies will help the planning for restoration of hydrologic habitat connectivity in med-rivers, a critical step for mediterranean species recovery.     

Evolution of cell motility in an individual-based model of tumour growth

Tumour invasion is driven by proliferation and importantly migration into the surrounding tissue. Cancer cell motility is also critical in the formation of metastases and is therefore a fundamental issue in cancer research. In this paper we investigate the emergence of cancer cell motility in an evolving tumour population using an individual-based modelling approach. In this model of tumour growth each cell is equipped with a micro-environment response network that determines the behaviour or phenotype of the cell based on the local environment. The response network is modelled using a feed-forward neural network, which is subject to mutations when the cells divide. With this model we have investigated the impact of the micro-environment on the emergence of a motile invasive phenotype. The results show that when a motile phenotype emerges the dynamics of the model are radically changed and we observe faster growing tumours exhibiting diffuse morphologies. Further we observe that the emergence of a motile subclone can occur in a wide range of micro-environmental growth conditions. Iterated simulations showed that in identical growth conditions the evolutionary dynamics either converge to a proliferating or migratory phenotype, which suggests that the introduction of cell motility into the model changes the shape of fitness landscape on which the cancer cell population evolves and that it now contains several local maxima. This could have important implications for cancer treatments which focus on the gene level, as our results show that several distinct genotypes and critically distinct phenotypes can emerge and become dominant in the same micro-environment.     

Drivers of plant individual-based pollinator visitation network topology in an arid ecosystem

Interactions with pollinators underlie the structure and function of plant communities. Network analysis is a valuable tool for studying plant-pollinator interactions, but these networks are most frequently built by aggregating interactions at the species level. Interactions are between individuals and an advantage of individual-based networks is the ability to integrate inter-individual variation in traits and environmental context within complex ecological networks. We studied the influence of inter-individual variation on pollinator sharing among foundation shrubs and cactus in a desert ecosystem using plant individual-based pollinator visitation networks. We hypothesized that the traits that alter attractiveness of plants to pollinators will also influence an individual plant's role within the visitation network. Foundation plants growing with higher densities of nearby blooming shrubs had higher pollinator visitation rates and had greater access to the conspecific mating pool, suggesting widespread and diffuse pollination facilitation within this community. Further, shrub density influenced the role of betweenness centrality and the effective number of partners (e^H). Floral display size also influenced the effective number of interaction partners but did not directly influence the centrality measures for individual plants or other measures of network structure despite increasing visitation rates. The individual-based visitation networks were significantly modular and module membership was predicted by species identity and pollinator visitation rates. Ecological and individual context mediate the outcome of pollinator-mediated interactions and are fundamental drivers of whole community structure. This study shows that the density of immediate neighbours can influence the overall structure of plant-pollinator interaction networks. Exploring the contribution of intraspecific variation to community interaction networks will improve our understanding of drivers of community-level ecological dynamics.     

Mass and energy allocation method analysis for an oil refinery characterization using multi-scale modeling

Purpose

The goal of this study is to characterize a single oil refinery using a mass and energy multi-scale allocation method for 13 different fossil fuel-based products. This method structures a rigorous modeling and data collection approach to fill the gap that exists in traditional methods of life cycle assessment (LCA).

Methods

The refinery system’s information is used to subdivide a main process at different sub-process levels and obtain multi-scale information using calculated factors for the main process system’s raw material inputs and outputs. The analysis was performed using derived sub-models from an overall technological model that individually simulate the production of each final refinery product. Based on the technological models of the individual product refineries, the same environmental indicators identified for mass and energy allocation were calculated.

Results and discussion

With this approach, it was possible to build a mass and energy LCA model of a fully parameterized refinery capable to accurately describe up to 98% the analyzed system. Incoming raw materials and effluents are weighted by specific factors calculated from the total of each principal process refining amount and the percentage outputs of the intermediate products. From a bottom-up approach, a primary data questionnaire was obtained with the total raw materials and waste quantities for each of the five key processes and their auxiliary processes. Information that previously appeared at the system (global refinery) and processes (main processes) level can now be accounted for in sub-process terms, thus allowing the monitoring information and environmental performance of the product and intermediate products to be found in a multiproduct system.

Conclusions

The refining sub-process’ environmental impact with regard to specific and intermediate products within the refinery processing steps was accurately estimated. This resulted not only in improvement of the property allocation but also in the identification of critical points in the processing steps, thus enabling optimization and innovation with regard to the processing lines and the refining process and producing a more efficient environmental impact analysis with great quality. The obtained formulations can be extended to more complex refining systems and other manufacturing processes.

     

Density distribution and size sorting in fish schools: an individual-based model

In fish schools the density varies per location and often individualsare sorted according to familiarity and/or body size. High densityis considered advantageous for protection against predatorsand this sorting is believed to be advantageous not only toavoid predators but also for finding food. In this paper, welist a number of mechanisms and we study, with the help of anindividual-based model of schooling agents, which spatial patternsmay result from them. In our model, schooling is regulated bythe following rules: avoiding those that are close by, aligningto those at intermediate distances, and moving towards othersfurther off. Regarding kinship/familiarity, we study patternsthat come about when agents actively choose to be close to relatedagents (i.e., ‘active sorting’). Regarding bodysize, we study what happens when agents merely differ in sizebut behave according to the usual schooling rules (‘sizedifference model’), when agents choose to be close tothose of similar size, and when small agents avoid larger ones(‘risk avoidance’). Several spatial configurationsresult: during ‘active sorting’ familiar agentsgroup together anywhere in the shoal, but agents of differentsize group concentrically, whereby the small agents occupy thecenter and the large ones the periphery (‘size differencemodel’ and ‘active sorting’). If small agentsavoid the risk of being close to large ones, however, smallagents end up at the periphery and large ones occupy the center(‘risk avoidance’). Spatial configurations are alsoinfluenced by the composition of the group, namely the percentageof agents of each type. Furthermore, schools are usually oblongand their density is always greatest near the front. We explainthe way in which these patterns emerge and indicate how resultsof our model may guide the study of spatial patterns in realanimals.     

Molecular characterization and phylogenetic inferences of Dermanyssus gallinae isolates in Italy within an European framework

In order to investigate the genetic relationships between Dermanyssus gallinae (Metastigmata: Dermanyssidae) (de Geer) isolates from poultry farms in Italy and other European countries, phylogenetic analysis was performed using a portion of the cytochrome c oxidase subunit 1 (cox1) gene of the mitochondrial DNA and the internal transcribed spacers (ITS1+5.8S+ITS2) of the ribosomal DNA. A total of 360 cox1 sequences and 360 ITS+ sequences were obtained from mites collected on 24 different poultry farms in 10 different regions of Northern and Southern Italy. Phylogenetic analysis of the cox1 sequences resulted in the clustering of two groups (A and B), whereas phylogenetic analysis of the ITS+ resulted in largely unresolved clusters. Knowledge of the genetic make‐up of mite populations within countries, together with comparative analyses of D. gallinae isolates from different countries, will provide better understanding of the population dynamics of D. gallinae. This will also allow the identification of genetic markers of emerging acaricide resistance and the development of alternative strategies for the prevention and treatment of infestations.