Predicting stochastic community dynamics in grasslands under the assumption of competitive symmetry.

Community dynamics is influenced by multiple ecological processes such as environmental spatiotemporal variation, competition between individuals and demographic stochasticity. Quantifying the respective influence of these various processes and making predictions on community dynamics require the use of a dynamical framework encompassing these various components. We here demonstrate how to adapt the framework of stochastic community dynamics to the peculiarities of herbaceous communities, by using a short temporal resolution adapted to the time scale of competition between herbaceous plants, and by taking into account the seasonal drops in plant aerial biomass following winter, harvesting or consumption by herbivores. We develop a hybrid inference method for this novel modelling framework that both uses numerical simulations and likelihood computations. Applying this methodology to empirical data from the Jena biodiversity experiment, we find that environmental stochasticity has a larger effect on community dynamics than demographic stochasticity, and that both effects are generally smaller than observation errors at the plot scale. We further evidence that plant intrinsic growth rates and carrying capacities are moderately predictable from plant vegetative height, specific leaf area and leaf dry matter content. We do not find any trade-off between demographical components, since species with larger intrinsic growth rates tend to also have lower demographic and environmental variances. Finally, we find that our model is able to make relatively good predictions of multi-specific community dynamics based on the assumption of competitive symmetry.

Explaining ontogenetic shifts in root-shoot scaling with transient dynamics.

BACKGROUND AND AIMS: Simple models of herbaceous plant growth based on optimal partitioning theory predict, at steady state, an isometric relationship between shoot and root biomass during plant ontogeny, i.e. a constant root-shoot ratio. This prediction has received mixed empirical support, suggesting either that optimal partitioning is too coarse an assumption to model plant biomass allocation, or that additional processes need to be modelled to account for empirical findings within the optimal partitioning framework. In this study, simulations are used to compare quantitatively two potential explanations for observed non-isometric relationships, namely nutrient limitation during the experiments and initial developmental constraints. METHODS: A simple plant growth model was built to simulate the growth of herbaceous species, based on optimal partitioning theory combined with empirically measured plant functional traits. Its ability to reproduce plant relative growth rate and final root weight ratio was assessed against previously published data. Predicted root-shoot ratios during plant ontogeny were compared with experimental observations. The effects of nutrient limitation and initial developmental constraints on root-shoot ratios were then tested. KEY RESULTS: The model was found to reproduce overall plant growth patterns accurately, but failed, in its simplest form, at explaining non-isometric growth trajectories. Both nutrient limitation and ontogenetic developmental constraints were further shown to cause transient dynamics resulting in a deviation from isometry. Nitrogen limitation alone was not sufficient to explain the observed trajectories of most plant species. The inclusion of initial developmental constraints (fixed non-optimal initial root-shoot ratios) enabled the reproduction of the observed trajectories and were consistent with observed initial root-shoot ratios. CONCLUSIONS: This study highlights the fact that considering transient dynamics enables theoretical predictions based on optimal partitioning to be reconciled with empirically measured ontogenetic root-shoot allometries. The transient dynamics cannot be solely explained by nutrient limitation during the experiments, pointing to a likely role for initial developmental constraints in the observed non-isometric growth trajectories.

A newly detected bias in self-evaluation.

The widely observed positive bias on self-evaluation is mainly explained by the self-enhancement motivation which minimizes negative feedbacks and emphasizes positive ones. Recent agent based simulations suggest that a positive bias also emerges if the sensitivity to feedbacks decreases when the self-evaluation increases. This paper proposes a simple mathematical model in which these different biases are integrated. Moreover, it describes an experiment (N = 1509) confirming that the sensitivity to feedbacks tends to decrease when self-evaluation increases and that a directly related positive bias is detected.

Influence of spatial structure on effective nutrient diffusion in bacterial biofilms.

The main contribution of this paper is to use homogenization techniques to compute diffusion coefficients from experimental images of microbial biofilms. Our approach requires the analysis of several experimental spatial structures of biofilms in order to derive from them a Representative Volume Element (RVE). Then, we apply a suitable numerical procedure to the RVE to derive the diffusion coefficients. We show that diffusion coefficients significantly vary with the biofilm structure. These results suggest that microbial biofilm structures can favour nutrient access in some cases.

Resisting hostility generated by terror: An agent-based study.

We propose an agent-based model leading to a decrease or an increase of hostility between agents after a major cultural threat such as a terrorist attack. The model is inspired from the Terror Management Theory and the Social Judgement Theory. An agent has a cultural identity defined through its acceptance segments about each of three different cultural worldviews (i.e., Atheist, Muslim, Christian) of the considered society. An agent's acceptance segment is composed from its acceptable positions toward a cultural worldview, including its most acceptable position. An agent forms an attitude about another agent depending on the similarity between their cultural identities. When a terrorist attack is perpetrated in the name of an extreme cultural identity, the negatively perceived agents from this extreme cultural identity point of view tend to decrease the width of their acceptance segments in order to differentiate themselves more from the threatening cultural identity. We generated a set of populations with cultural identities compatible with data from a survey on attitudes among a large sample representative of the population of France; we then simulated the reaction of these agents facing a terrorist attack from Muslim extremists. For most populations, the average attitude toward Muslims becomes more negative. However, for some specific populations, we noticed the opposite effect as the average attitude of the population toward Muslims becomes less negative. In these populations, the Muslim agents strongly differentiate themselves from the terrorists' extreme cultural identity, and the other agents are aware of these changes. These reactions are due to particular properties of their cultural identities that are identified in this paper.

Systems Thinking in Practice: Participatory Modeling as a Foundation for Integrated Approaches to Health.

One Health (OH), EcoHealth (EH), and Planetary Health (PH) share an interest in transdisciplinary efforts that bring together scientists, citizens, government and private sectors to implement contextualized actions that promote adaptive health management across human, animal and ecosystem interfaces. A key operational element underlying these Integrated Approaches to Health (IAH) is use of Systems Thinking as a set of tools for integration. In this paper we discuss the origins and epistemology of systems thinking and argue that participatory modeling, informed by both systems theory and expertise in facilitating engagement and social learning, can help ground IAH theoretically and support its development. Participatory modeling is iterative and adaptive, which is necessary to deal with complexity in practice. Participatory modeling (PM) methods actively involve affected interests and stakeholders to ground the field of inquiry in a specific social-ecological context. Furthermore, PM processes act to reconcile the diverse understandings of the empirical world that stem from divergent discipline and community viewpoints. In this perspective article, we argue that PM can support systems thinking in practice and is essential for IAH implementation. Accordingly we invite PH, OH, and EH practitioners to systematically incorporate specialists in systems science and social engagement and facilitation. This will enable the appropriate contextualization of research practice and interventions, and ensure a balanced representation of the roles and relationships of medical, biological, mathematical, and social disciplines. For completeness, funding schemes supporting IAH need to follow the same iterative, adaptive, and participative processes to accompany IAH projects throughout their implementation.

The Combined Use of Correlative and Mechanistic Species Distribution Models Benefits Low Conservation Status Species.

Species can respond to climate change by tracking appropriate environmental conditions in space, resulting in a range shift. Species Distribution Models (SDMs) can help forecast such range shift responses. For few species, both correlative and mechanistic SDMs were built, but allis shad (Alosa alosa), an endangered anadromous fish species, is one of them. The main purpose of this study was to provide a framework for joint analyses of correlative and mechanistic SDMs projections in order to strengthen conservation measures for species of conservation concern. Guidelines for joint representation and subsequent interpretation of models outputs were defined and applied. The present joint analysis was based on the novel mechanistic model GR3D (Global Repositioning Dynamics of Diadromous fish Distribution) which was parameterized on allis shad and then used to predict its future distribution along the European Atlantic coast under different climate change scenarios (RCP 4.5 and RCP 8.5). We then used a correlative SDM for this species to forecast its distribution across the same geographic area and under the same climate change scenarios. First, projections from correlative and mechanistic models provided congruent trends in probability of habitat suitability and population dynamics. This agreement was preferentially interpreted as referring to the species vulnerability to climate change. Climate change could not be accordingly listed as a major threat for allis shad. The congruence in predicted range limits between SDMs projections was the next point of interest. The difference, when noticed, required to deepen our understanding of the niche modelled by each approach. In this respect, the relative position of the northern range limit between the two methods strongly suggested here that a key biological process related to intraspecific variability was potentially lacking in the mechanistic SDM. Based on our knowledge, we hypothesized that local adaptations to cold temperatures deserved more attention in terms of modelling, but further in conservation planning as well.

Deriving the number of jobs in proximity services from the number of inhabitants in French rural municipalities.

We use a minimum requirement approach to derive the number of jobs in proximity services per inhabitant in French rural municipalities. We first classify the municipalities according to their time distance in minutes by car to the municipality where the inhabitants go the most frequently to get services (called MFM). For each set corresponding to a range of time distance to MFM, we perform a quantile regression estimating the minimum number of service jobs per inhabitant that we interpret as an estimation of the number of proximity jobs per inhabitant. We observe that the minimum number of service jobs per inhabitant is smaller in small municipalities. Moreover, for municipalities of similar sizes, when the distance to the MFM increases, the number of jobs of proximity services per inhabitant increases.

A universal model of commuting networks.

We show that a recently proposed model generates accurate commuting networks on 80 case studies from different regions of the world (Europe and United-States) at different scales (e.g. municipalities, counties, regions). The model takes as input the number of commuters coming in and out of each geographic unit and generates the matrix of commuting flows between the units. The single parameter of the model follows a universal law that depends only on the scale of the geographic units. We show that our model significantly outperforms two other approaches proposing a universal commuting model [1], [2], particularly when the geographic units are small (e.g. municipalities).

Bacteria can form interconnected microcolonies when a self-excreted product reduces their surface motility: evidence from individual-based model simulations.

Recent experimental observations of Pseudomonas aeruginosa, a model bacterium in biofilm research, reveal that, under specific growth conditions, bacterial cells form patterns of interconnected microcolonies. In the present work, we use an individual-based model to assess the involvement of bacteria motility and self-produced extracellular substance in the formation of these patterns. In our simulations, the pattern of interconnected microcolonies appears only when bacteria motility is reduced by excreted extracellular macromolecules. Immotile bacteria form isolated microcolonies and constantly motile bacteria form flat biofilms. Based on experimental data and computer simulations, we suggest a mechanism that could be responsible for these interconnected microcolonies.

An iterative approach for generating statistically realistic populations of households.

BACKGROUND: Many different simulation frameworks, in different topics, need to treat realistic datasets to initialize and calibrate the system. A precise reproduction of initial states is extremely important to obtain reliable forecast from the model. METHODOLOGY/PRINCIPAL FINDINGS: This paper proposes an algorithm to create an artificial population where individuals are described by their age, and are gathered in households respecting a variety of statistical constraints (distribution of household types, sizes, age of household head, difference of age between partners and among parents and children). Such a population is often the initial state of microsimulation or (agent) individual-based models. To get a realistic distribution of households is often very important, because this distribution has an impact on the demographic evolution. Usual techniques from microsimulation approach cross different sources of aggregated data for generating individuals. In our case the number of combinations of different households (types, sizes, age of participants) makes it computationally difficult to use directly such methods. Hence we developed a specific algorithm to make the problem more easily tractable. CONCLUSIONS/SIGNIFICANCE: We generate the populations of two pilot municipalities in Auvergne region (France) to illustrate the approach. The generated populations show a good agreement with the available statistical datasets (not used for the generation) and are obtained in a reasonable computational time.

Viability and resilience of languages in competition.

We study the viability and resilience of languages, using a simple dynamical model of two languages in competition. Assuming that public action can modify the prestige of a language in order to avoid language extinction, we analyze two cases: (i) the prestige can only take two values, (ii) it can take any value but its change at each time step is bounded. In both cases, we determine the viability kernel, that is, the set of states for which there exists an action policy maintaining the coexistence of the two languages, and we define such policies. We also study the resilience of the languages and identify configurations from where the system can return to the viability kernel (finite resilience), or where one of the languages is lead to disappear (zero resilience). Within our current framework, the maintenance of a bilingual society is shown to be possible by introducing the prestige of a language as a control variable.