Using dynamic vegetation models to simulate plant range shifts

Dynamic vegetation models (DVMs) follow a process‐based approach to simulate plant population demography, and have been used to address questions about disturbances, plant succession, community composition, and provisioning of ecosystem services under climate change scenarios. Despite their potential, they have seldom been used for studying species range dynamics explicitly. In this perspective paper, we make the case that DVMs should be used to this end and can improve our understanding of the factors that influence species range expansions and contractions. We review the benefits of using process‐based, dynamic models, emphasizing how DVMs can be applied specifically to questions about species range dynamics. Subsequently, we provide a critical evaluation of some of the limitations and trade‐offs associated with DVMs, and we use those to guide our discussions about future model development. This includes a discussion on which processes are lacking, specifically a mechanistic representation of dispersal, inclusion of the seedling stage, trait variability, and a dynamic representation of reproduction. We also discuss upscaling techniques that offer promising solutions for being able to run these models efficiently over large spatial extents. Our aim is to provide directions for future research efforts and to illustrate the value of the DVM approach.     

Using in silico models to simulate dual perturbation experiments: procedure development and interpretation of outcomes

Background  

A growing number of realistic in silico models of metabolic functions are being formulated and can serve as 'dry lab' platforms to prototype and simulate experiments before they are performed. For example, dual perturbation experiments that vary both genetic and environmental parameters can readily be simulated in silico. Genetic and environmental perturbations were applied to a cell-scale model of the human erythrocyte and subsequently investigated.     

Biomechanical models to simulate consequences of maxillofacial surgery

This paper presents the biomechanical finite element models that have been developed in the framework of the computer-assisted maxillofacial surgery. After a brief overview of the continuous elastic modelling method, two models are introduced and their use for computer-assisted applications discussed. The first model deals with orthognathic surgery and aims at predicting the facial consequences of maxillary and mandibular osteotomies. For this, a generic three-dimensional model of the face is automatically adapted to the morphology of the patient by the mean of elastic registration. Qualitative simulations of the consequences of an osteotomy of the mandible can thus be provided. The second model addresses the Sleep Apnoea Syndrome. Its aim is to develop a complete modelling of the interaction between airflow and upper airways walls during breathing. Dynamical simulations of the interaction during a respiratory cycle are computed and compared with observed phenomena.     

Experimental models to study development and function of the human immune system in vivo

The study of development and function of the immune system in vivo has made intensive use of animal models, but performing such work in humans is difficult for experimental, practical, and ethical reasons. Confronted with this scientific challenge, several pioneering groups have developed in the late 1980s mouse models of human immune system development. Although these experimental approaches were proven successful and useful, they were suffering from limitations due to xenograft transplantation barriers. By reviewing the characteristics of the successive models over the last 20 years, it becomes apparent that screening of potentially interesting mouse strains and usage of combinations of genetic deficiencies has led to major advances. This is particularly true for human T cell development in the murine thymus. This review will focus on these advances and the potential future improvements that remain to be accomplished.     

The evolution of song repertoires and immune defence in birds

Song repertoires (the number of different song types sung by a male) in birds provide males with an advantage in sexual selection because females prefer males with large repertoires, and females may benefit because offspring sired by preferred males have high viability. Furthermore, males with large repertoires suffer less from malarial parasites, indicating that a large repertoire may reflect health status. We hypothesize that sexual selection may cause a coevolutionary increase in parasite virulence and host immune defence because sexual selection increases the risk of multiple infections that select for high virulence. Alternatively, a female mate preference for healthy males will affect the coevolutionary dynamics of host-parasite interactions by selecting for increased virulence and hence high investment by hosts in immune function. In a comparative study of birds, repertoire size and relative size of the spleen, which is an important immune defence organ, were strongly, positively correlated accounting for almost half of the variance. This finding suggests that host-parasite interactions have played an important role in the evolution of song repertoires in birds.     

Using NCSWAP to simulate seasonal nitrogen dynamics in soil and corn

The objective of this study was to determine if a re-calibrated version of the computer model NCSWAP (version 36) could accurately predict corn growth and soil N dynamics in conventionally tilled (CT) and no-till (NT) corn supplied with legume green manure or ammonium nitrate as N sources. We also attempted to ascertain the reasons for limitations in the model's ability to simulate corn growth and soil N dynamics found by our colleagues in a previous study and to propose potential improvements. The model was calibrated to accurately simulate total available N (N in plant above-ground biomass plus soil nitrate in the 0 to 45 cm profile) for a control and a fertilizer CT treatment in the 1992 growing season. To do so, input values defining the quantities of active soil organic N had to be reduced to 19% of the values proposed by the model developers and a solute transport factor defining the mobile vs. immobile fractions of soil nitrate adjusted from 0.8 to 0.2. The discrepancies between the proposed values and the lower values employed in this study might be due to the uncertainties in quantitatively describing soil N mineralization processes and the way they are handled in the model, as well as the lack of a component simulating macroporous-influenced water flow and solute transport in the model. With the current version, until one knows how to predict what these values are, the model needs to be re-calibrated for each experimental site and condition and thus is of limited value as a general model.With no further adjustment of input values, model validation success was mixed. The model accurately predicted total available N for treatments in the second year of the experiment that had the same N source and tillage as the treatments used for the calibration year but with the different weather and growing conditions. However, total available N was underpredicted where legume green manure was the N source and overpredicted with no-till cultivation. The model was accurate in simulating seasonal corn growth for nearly all the treatments, judged by nonsignificant mean difference (MD) values and highly significant correlation coefficients (r). Prediction of seasonal soil nitrate concentration was less accurate compared to total available N and corn growth variables. Potential improvements in the model's simulation of a no-till system as well as for predicting corn harvest yield and seasonal soil nitrate concentration where N deficiency occurs were discussed.     

Evaluation of chronic immune system stimulation models in growing pigs

Two experiments (EXPs) were conducted to evaluate models of immune system stimulation (ISS) that can be used in nutrient metabolism studies in growing pigs. In EXP I, the pig's immune response to three non-pathogenic immunogens was evaluated, whereas in EXP II the pig's more general response to one of the immunogens was contrasted with observations on non-ISS pigs. In EXP I, nine growing barrows were fitted with a jugular catheter, and after recovery assigned to one of three treatments. Three immunogens were tested during a 10-day ISS period: (i) repeated injection of increasing amounts of Escherichia coli lipopolysaccharide (LPS); (ii) repeated subcutaneous injection of turpentine (TURP); and (iii) feeding grains naturally contaminated with mycotoxins (MYCO). In EXP II, 36 growing barrows were injected repeatedly with either saline (n = 12) or increasing amounts of LPS (n = 24) for 7 days (initial dose 60 μg/kg body weight). Treating pigs with TURP and LPS reduced feed intake (P < 0.02), whereas feed intake was not reduced in pigs on MYCO. Average daily gain (ADG; kg/day) of pigs on LPS (0.50) was higher than that of pigs on TURP (0.19), but lower than that of pigs on MYCO (0.61; P < 0.01). Body temperature was elevated in pigs on LPS and TURP, by 0.8°C and 0.7°C, respectively, relative to pre-ISS challenge values (39.3°C; P < 0.02), but remained unchanged in pigs on MYCO. Plasma concentrations of interleukin-1β were increased in pigs treated with LPS and TURP (56% and 55%, respectively, relative to 22.3 pg/ml for pre-ISS; P < 0.01), but not in MYCO-treated pigs. Plasma cortisol concentrations remained unchanged for pigs on MYCO and TURP, but were reduced in LPS-treated pigs (30% relative to 29.8 ng/ml for pre-ISS; P < 0.05). Red blood cell glutathione concentrations were lower in TURP-treated pigs (13% relative to 1.38 μM for pre-ISS; P < 0.05), but were unaffected in pigs on LPS and MYCO. In EXP I, TURP caused severe responses including skin ulceration and substantial reductions in feed intake and ADG, whereas MYCO did not induce effective ISS. In EXP II, ISS increased relative organ weights, eye temperature, white blood cell count and plasma acute-phase proteins (P < 0.05), confirming that repeated injection with increasing amounts of LPS induced chronic and relatively mild ISS. Repeated injection with increasing amounts of LPS is a suitable model for studying nutrient metabolism and evaluating the efficacy of nutritional intervention during chronic ISS in growing pigs.     

Stochastic models for virus and immune system dynamics

New stochastic models are developed for the dynamics of a viral infection and an immune response during the early stages of infection. The stochastic models are derived based on the dynamics of deterministic models. The simplest deterministic model is a well-known system of ordinary differential equations which consists of three populations: uninfected cells, actively infected cells, and virus particles. This basic model is extended to include some factors of the immune response related to Human Immunodeficiency Virus-1 (HIV-1) infection. For the deterministic models, the basic reproduction number, R₀, is calculated and it is shown that if R₀<1, the disease-free equilibrium is locally asymptotically stable and is globally asymptotically stable in some special cases. The new stochastic models are systems of stochastic differential equations (SDEs) and continuous-time Markov chain (CTMC) models that account for the variability in cellular reproduction and death, the infection process, the immune system activation, and viral reproduction. Two viral release strategies are considered: budding and bursting. The CTMC model is used to estimate the probability of virus extinction during the early stages of infection. Numerical simulations are carried out using parameter values applicable to HIV-1 dynamics. The stochastic models provide new insights, distinct from the basic deterministic models. For the case R₀>1, the deterministic models predict the viral infection persists in the host. But for the stochastic models, there is a positive probability of viral extinction. It is shown that the probability of a successful invasion depends on the initial viral dose, whether the immune system is activated, and whether the release strategy is bursting or budding.     

An approximate stochastic optimal control framework to simulate nonlinear neuro-musculoskeletal models in the presence of noise

Optimal control simulations have shown that both musculoskeletal dynamics and physiological noise are important determinants of movement. However, due to the limited efficiency of available computational tools, deterministic simulations of movement focus on accurately modelling the musculoskeletal system while neglecting physiological noise, and stochastic simulations account for noise while simplifying the dynamics. We took advantage of recent approaches where stochastic optimal control problems are approximated using deterministic optimal control problems, which can be solved efficiently using direct collocation. We were thus able to extend predictions of stochastic optimal control as a theory of motor coordination to include muscle coordination and movement patterns emerging from non-linear musculoskeletal dynamics. In stochastic optimal control simulations of human standing balance, we demonstrated that the inclusion of muscle dynamics can predict muscle co-contraction as minimal effort strategy that complements sensorimotor feedback control in the presence of sensory noise. In simulations of reaching, we demonstrated that nonlinear multi-segment musculoskeletal dynamics enables complex perturbed and unperturbed reach trajectories under a variety of task conditions to be predicted. In both behaviors, we demonstrated how interactions between task constraint, sensory noise, and the intrinsic properties of muscle influence optimal muscle coordination patterns, including muscle co-contraction, and the resulting movement trajectories. Our approach enables a true minimum effort solution to be identified as task constraints, such as movement accuracy, can be explicitly imposed, rather than being approximated using penalty terms in the cost function. Our approximate stochastic optimal control framework predicts complex features, not captured by previous simulation approaches, providing a generalizable and valuable tool to study how musculoskeletal dynamics and physiological noise may alter neural control of movement in both healthy and pathological movements.     

Flow laser cytometry for evaluation of the human immune system

Some flow laser cytometry (FLC) techniques intended for studies of the immune system cells are reviewed. A widespread analytical method is the phenotyping of lymphocytes by the markers they express. The use of FLC permits the evaluation of practically all functional parameters of immunocompetent cells. Thus, to analyze their ingestive and microbicidal activity fluorochrome-labeled microorganisms are used. The apploication of indicator dyes makes it possible to evaluate calcium mobilization and formation of active forms of oxygen. FLC is used for the identification of cytokines inside the cell and in the medium. The authors propose tests for the analysis of the proliferative activity of lymphocytes, the cytotoxicity of natural killers, the evaluation of apoptosis and protein processing with monocytes/macrophages.     

Pattern formation in one- and two-dimensional shape-space models of the immune system.

A large-scale model of the immune network is analyzed, using the shape-space formalism. In this formalism, it is assumed that the immunoglobulin receptors on B cells can be characterized by their unique portions, or idiotypes, that have shapes that can be represented in a space of a small finite dimension. Two receptors are assumed to interact to the extent that the shapes of their idiotypes are complementary. This is modeled by assuming that shapes interact maximally whenever their coordinates in the space-space are equal and opposite, and that the strength of interaction falls off for less complementary shapes in a manner described by a Gaussian function of the Euclidean "distance" between the pair of interacting shapes. The degree of stimulation of a cell when confronted with complementary idiotypes is modeled using a log bell-shaped interaction function. This leads to three possible equilibrium states for each clone: a virgin, an immune, and a suppressed state. The stability properties of the three possible homogeneous steady states of the network are examined. For the parameters chosen, the homogeneous virgin state is stable to both uniform and sinusoidal perturbations of small amplitude. A sufficiently large perturbation will, however, destabilize the virgin state and lead to an immune reaction. Thus, the virgin system is both stable and responsive to perturbations. The homogeneous immune state is unstable to both uniform and sinusoidal perturbations, whereas the homogeneous suppressed state is stable to uniform, but unstable to sinusoidal, perturbations. The non-uniform patterns that arise from perturbations of the homogeneous states are examined numerically. These patterns represent the actual immune repertoire of an animal, according to the present model. The effect of varying the standard deviation sigma of the Gaussian is numerically analyzed in a one-dimensional model. If sigma is large compared to the size of the shape-space, the system attains a fixed non-uniform equilibrium. Conversely if sigma is small, the system attains one out of many possible non-uniform equilibria, with the final pattern depending on the initial conditions. This demonstrates the plasticity of the immune repertoire in this shape-space model. We describe how the repertoire organizes itself into large clusters of clones having similar behavior. These results are extended by analyzing pattern formation in a two-dimensional (2-D) shape-space.(ABSTRACT TRUNCATED AT 400 WORDS)     

Application of mechanoregulatory models to simulate peri-implant tissue formation in an in vivo bone chamber

Several mechanoregulatory tissue differentiation models have been proposed over the last decade. Corroboration of these models by comparison with experimental data is necessary to determine their predictive power. So far, models have been applied with various success rates to different experimental set-ups investigating mainly secondary fracture healing. In this study, the mechanoregulatory models are applied to simulate the implant osseointegration process in a repeated sampling in vivo bone chamber, placed in a rabbit tibia. This bone chamber provides a mechanically isolated environment to study tissue differentiation around titanium implants loaded in a controlled manner. For the purpose of this study, bone formation around loaded cylindrical and screw-shaped implants was investigated. Histologically, no differences were found between the two implant geometries for the global amount of bone formation in the entire chamber. However, a significantly larger amount of bone-to-implant contact was observed for the screw-shaped implant compared to the cylindrical implant. In the simulations, a larger amount of bone was also predicted to be in contact with the screw-shaped implant. However, other experimental observations could not be predicted. The simulation results showed a distribution of cartilage, fibrous tissue and (im)mature bone, depending on the mechanoregulatory model that was applied. In reality, no cartilage was observed. Adaptations to the differentiation models did not lead to a better correlation between experimentally observed and numerically predicted tissue distribution patterns. The hypothesis that the existing mechanoregulatory models were able to predict the patterns of tissue formation in the in vivo bone chamber could not be fully sustained.     

FUS: a system to simulate conformational changes in biological macromolecules

In order to study the dynamics of protein and nucleic acid conformations,a molecular folding-unfolding system (FUS written in Lisp) hasbeen developed. Secondary structure features of protein andnucleic acids are graphically represented by cubes in a modified‘Blocks World’ paradigm. Modeling of protein andnucleic acid unfolding (denaturation) and folding of their three-dimensionalstructure is possible by the use of high level ‘block’operators which allow displacement of these structural featuresin space. Due to the flexible nature of this program, FUS isa useful tool for the rapid evaluation of user-defined rulesgoverning conformational changes. The use of FUS to unfold threecommon proteins (prealbumin, flavodoxin and triose phosphateisomerase) and a tRNA is presented. Received on March 22, 1988; accepted on June 1, 1988     

A system to simulate gas exchange in humans to control quality of metabolic measurements

We have developed a gas exchange simulation system (GESS) to assess the quality control in measurements of metabolic gas exchange. The GESS simulates human breathing from rest to maximal exercise. It approximates breath-by-breath waveforms, ventilatory output, gas concentrations, temperature and humidity during inspiration and expiration. A programmable motion control driving two syringes allows the ventilation to be set at any tidal volume (V _T), respiratory frequency (f), flow waveform and period of inspiration and expiration. The GESS was tested at various combinations of V _T (0.5–2.5 l) and f (10–60 stroke · min⁻¹) and at various fractional concentrations of expired oxygen (0.1294–0.1795); and carbon dioxide (0.0210–0.0690) for a pre-set flow waveform and for expired gases at the same temperature and humidity as room air. Expired gases were collected in a polyethylene bag for measurement of volume and gas concentrations. Accuracy was assessed by calculating the absolute and relative errors on parameters (error = measured−predicted). The overall error in the gas exchange values averaged less than 2% for oxygen uptake and carbon dioxide output, which is within the accuracy of the Douglas bag method. Accepted: 4 June 1998     

Social evolution: lazy wasps look to the future

Female hairy-faced hover wasps forage for the young of a dominant breeder, but some forage more than others. New research shows that helpers decide how much to help by looking to the future.     

Using input minimization to train a cerebellar model to simulate regulation of smooth pursuit

Cerebellar learning appears to be driven by motor error, but whether or not error signals are provided by climbing fibers (CFs) remains a matter of controversy. Here we show that a model of the cerebellum can be trained to simulate the regulation of smooth pursuit eye movements by minimizing its inputs from parallel fibers (PFs), which carry various signals including error and efference copy. The CF spikes act as “learn now” signals. The model can be trained to simulate the regulation of smooth pursuit of visual objects following circular or complex trajectories and provides insight into how Purkinje cells might encode pursuit parameters. In minimizing both error and efference copy, the model demonstrates how cerebellar learning through PF input minimization (InMin) can make movements more accurate and more efficient. An experimental test is derived that would distinguish InMin from other models of cerebellar learning which assume that CFs carry error signals.     

Diverse lectin repertoires in tunicates mediate broad recognition and effector innate immune responses

It is widely recognized that humoral and phagocyte-associated lectins constitute critical components of innate immunity in vertebrates and invertebrates. Their functions include not only self/non-self recognition but also engaging associated effector mechanisms, such as complement-mediated opsonization and killing of potential pathogens. One of the unresolved questions concerns the diversity in recognition capacity of the lectin repertoire, particularly in those organisms lacking adaptive immunity. In this paper, we discuss evidence suggesting that lectin repertoire in invertebrates and protochordates is highly diversified, and includes most of the lectin classes described so far in vertebrate species, as well as associated effector pathways.     

Using network models to approximate spatial point-process models

Spatial effects are fundamental to ecological and epidemiological systems, yet the incorporation of space into models is potentially complex. Fixed-edge network models (i.e. networks where each edge has the same fixed strength of interaction) are widely used to study spatial processes but they make simplistic assumptions about spatial scale and structure. Furthermore, it can be difficult to parameterize such models with empirical data. By comparison, spatial point-process models are often more realistic than fixed-edge network models, but are also more difficult to analyze. Here we develop a moment closure technique that allows us to define a fixed-edge network model which predicts the prevalence and rate of epidemic spread of a continuous spatial point-process epidemic model. This approach provides a systematic method for accurate parameterization of network models using data from continuously distributed populations (such as data on dispersal kernels). Insofar as point-process models are accurate representations of real spatial biological systems, our example also supports the view that network models are realistic representations of space.     

Trade-offs in antibody repertoires to complex antigens

Pathogens vary in their antigenic complexity. While some pathogens such as measles present a few relatively invariant targets to the immune system, others such as malaria display considerable antigenic diversity. How the immune response copes in the presence of multiple antigens, and whether a trade-off exists between the breadth and efficacy of antibody (Ab)-mediated immune responses, are unsolved problems. We present a theoretical model of affinity maturation of B-cell receptors (BCRs) during a primary infection and examine how variation in the number of accessible antigenic sites alters the Ab repertoire. Naive B cells with randomly generated receptor sequences initiate the germinal centre (GC) reaction. The binding affinity of a BCR to an antigen is quantified via a genotype–phenotype map, based on a random energy landscape, that combines local and distant interactions between residues. In the presence of numerous antigens or epitopes, B-cell clones with different specificities compete for stimulation during rounds of mutation within GCs. We find that the availability of many epitopes reduces the affinity and relative breadth of the Ab repertoire. Despite the stochasticity of somatic hypermutation, patterns of immunodominance are strongly shaped by chance selection of naive B cells with specificities for particular epitopes. Our model provides a mechanistic basis for the diversity of Ab repertoires and the evolutionary advantage of antigenically complex pathogens.     

Response of the insect immune system to three different immune challenges

Insects rely on an innate immune system to effectively respond to pathogenic challenges. Most studies on the insect immune system describe changes in only one or two immune parameters following a single immune challenge. In addition, a variety of insect models, often at different developmental stages, have been used, making it difficult to compare results across studies. In this study, we used adult male Acheta domesticus crickets to characterize the response of the insect innate immune system to three different immune challenges: injection of bacterial lipopolysaccharides (LPS); injection of live Serratia marcescens bacteria; or insertion of a nylon filament into the abdomen. For each challenge, we measured and compared hemolymph phenoloxidase (PO) and lysozyme-like enzyme activities; the number of circulating hemocytes; and the nodulation responses of challenged and un-challenged crickets. We found that injection of an LD₅₀ dose of LPS from Escherichia coli elicited a more rapid response than an LD₅₀ dose of LPS from S. marcescens. LPS injection could cause a rapid decrease 2 hpi, followed by an increase by 7 dpi, in the number of circulating hemocytes. In contrast, injection of live S. marcescens produced a rapid increase and then decrease in hemocyte number. This was followed by an increase in the number of hemocytes at 7 dpi, similar to that observed following LPS injection. Both LPS and live bacteria decreased hemolymph PO activity, but the timing of this effect was dependent on the challenge. Live bacteria, but not LPS, induced an increase in lysozyme-like activity in the hemolymph. Insertion of a nylon filament induced a decrease in hemolymph PO activity 2 h after insertion of the filament, but had no effect on hemocyte number or lytic activity. Our results indicate that the innate immune system’s response to each type of challenge can vary greatly in both magnitude and timing, so it is important to assess multiple parameters at multiple time points in order to obtain a comprehensive view of such responses.