How do seasonal temperature variations influence interplay between toxic and non-toxic cyanobacterial blooms? Evidence from modeling and experimental data.

Summer cyanobacterial blooms exhibit a dynamic interplay between toxic and non-toxic genotypes, significantly influencing the cyanotoxin levels within a lake. The challenge lies in accurately predicting these toxin concentrations due to the significant temporal fluctuations in the proportions of toxic and non-toxic genotypes. Typically, the toxic genotypes dominate during the early and late summer periods, while the non-toxic variants prevail in mid-summer. To dissect this phenomenon, we propose a model that accounts for the competitive interaction between toxic and non-toxic genotypes, as well as seasonal temperature variations. Our numerical simulations suggest that the optimal temperature of the toxic genotypes is lower than that of the optimal temperatures of the non-toxic counterparts. This difference of optimal temperature may potentially contribute to explain the dominance of toxic genotypes at the early and late summer periods, situation often observed in the field. Experimental data from the laboratory align qualitatively with our simulation results, enabling a better understanding of complex interplays between toxic and non-toxic cyanobacteria.

Equity and modeling in sustainability science: Examples and opportunities throughout the process.

Equity is core to sustainability, but current interventions to enhance sustainability often fall short in adequately addressing this linkage. Models are important tools for informing action, and their development and use present opportunities to center equity in process and outcomes. This Perspective highlights progress in integrating equity into systems modeling in sustainability science, as well as key challenges, tensions, and future directions. We present a conceptual framework for equity in systems modeling, focused on its distributional, procedural, and recognitional dimensions. We discuss examples of how modelers engage with these different dimensions throughout the modeling process and from across a range of modeling approaches and topics, including water resources, energy systems, air quality, and conservation. Synthesizing across these examples, we identify significant advances in enhancing procedural and recognitional equity by reframing models as tools to explore pluralism in worldviews and knowledge systems; enabling models to better represent distributional inequity through new computational techniques and data sources; investigating the dynamics that can drive inequities by linking different modeling approaches; and developing more nuanced metrics for assessing equity outcomes. We also identify important future directions, such as an increased focus on using models to identify pathways to transform underlying conditions that lead to inequities and move toward desired futures. By looking at examples across the diverse fields within sustainability science, we argue that there are valuable opportunities for mutual learning on how to use models more effectively as tools to support sustainable and equitable futures.

Basic human values during the COVID-19 outbreak, perceived threat and their relationships with compliance with movement restrictions and social distancing.

This study examines the evolution of Schwartz's Basic Human Values during the COVID-19 outbreak, and their relationships with perceived threat, compliance with movement restrictions and social distancing. An online questionnaire was administered to a heterogeneous sample of French citizens (N = 1025) during the first French lockdown related to the outbreak. Results revealed a significant evolution of values; the conservation value was higher during the outbreak than usual, and both self-enhancement and openness-to-change values were lower during the COVID-19 outbreak than usual. Conservation and perceived threat during the outbreak were robustly and positively related to both compliance with movement restrictions and social distancing. Conservation during the outbreak emerged as a significant partial mediator of the relationship between perceived threat and outcomes (i.e., compliance with movement restrictions and social distancing). Implications of these results for the malleability of values and the COVID-19 modelling are discussed.

In situ tracking of microbeads for the detection of biofilm formation.

In this study, we utilize the free motion of beads incorporated in bacterial suspension to investigate the behavior of the medium surrounding the beads during biofilm formation. The use of imaging techniques such as digital image correlation enables tracking of the movement of beads, which serve as markers in the processed images. This method is applied to detect and characterize biofilm formation. The main originality of this study lies in characterizing the evolution of the typology of bead movements during biofilm formation. The aim is to identify bead behaviors that represent the start of biofilm formation. By observing inert bead movements introduced into the bacterial environment, changes in trajectory typologies are detected and appear to be related to sessile bacterial activity, bacterial hindrance, and adhesion or formation of extracellular material. We use our approach to discriminate between the presence or absence of antibiotics mixed with bacteria and to assess their effectiveness. The results highlight the potential of our approach as nondestructive tracking of biofilm dynamics over time based on optical microscope images.

Exploring non-linear transition pathways in social-ecological systems.

Tipping point dynamics are fundamental drivers for sustainable transition pathways of social-ecological systems (SES). Current research predominantly analyzes how crossing tipping points causes regime shifts, however, the analysis of potential transition pathways from these social and ecological tipping points is often overlooked. In this paper, we analyze transition pathways and the potential outcomes that these may lead to via a stylized model of a system composed of interacting agents exploiting resources and, by extension, the overall ecosystem. Interactions between the social and the ecological system are based on a perception-exploitation framework. We show that the presence of tipping points in SES may yield counter-intuitive social-ecological transition pathways. For example, the high perception of an alarming ecological state among agents can provide short-term ecological benefits, but can be less effective in the long term, compared to a low-perception condition. This work also highlights how understanding non-linear interactions is critical for defining suitable transition pathways of any SES.

Antibiotic resilience: a necessary concept to complement antibiotic resistance?

Resilience is the capacity of systems to recover their initial state or functions after a disturbance. The concepts of resilience and resistance are complementary in ecology and both represent different aspects of the stability of ecosystems. However, antibiotic resilience is not used in clinical bacteriology whereas antibiotic resistance is a recognized major problem. To join the fields of ecology and clinical bacteriology, we first review the resilience concept from ecology, socio-ecological systems and microbiology where it is widely developed. We then review resilience-related concepts in microbiology, including bacterial tolerance and persistence, phenotypic heterogeneity and collective tolerance and resistance. We discuss how antibiotic resilience could be defined and argue that the use of this concept largely relies on its experimental measure and its clinical relevance. We review indicators in microbiology which could be used to reflect antibiotic resilience and used as valuable indicators to anticipate the capacity of bacteria to recover from antibiotic treatments.

Alkyl-Chitosan-Based Adhesive: Water Resistance Improvement.

A chemical modification by grafting alkyl chains using an octanal (C8) on chitosan was conducted with the aim to improve its water resistance for bonding applications. The chemical structure of the modified polymers was determined by NMR analyses revealing two alkylation degrees (10 and 15%). In this study, the flow properties of alkyl-chitosans were also evaluated. An increase in the viscosity was observed in alkyl-chitosan solutions compared with solutions of the same concentration based on native chitosan. Moreover, the evaluation of the adhesive strength (bond strength and shear stress) of both native and alkyl-chitosans was performed on two different double-lap adherends (aluminum and wood). Alkyl-chitosans (10 and 15%) maintain sufficient adhesive properties on wood and exhibit better water resistance compared to native chitosan.

Knowledge infrastructure and safe operating spaces in social-ecological systems.

Maintaining safe operating spaces for exploited natural systems in the face of uncertainty is a key sustainability challenge. This challenge can be viewed as a problem in which human society must navigate in a limited space of acceptable futures in which humans enjoy sufficient well-being and avoid crossing planetary boundaries. A critical obstacle is the nature of society as a controller with endogenous dynamics affected by knowledge, values, and decision-making fallacies. We outline an approach for analyzing the role of knowledge infrastructure in maintaining safe operating spaces. Using a classic natural resource problem as an illustration, we find that a small safe operating space exists that is insensitive to the type of policy implementation, while in general, a larger safe operating space exists which is dependent on the implementation of the "right" policy. Our analysis suggests the importance of considering societal response dynamics to varying policy instruments in defining the shape of safe operating spaces.

Towards standardized mechanical characterization of microbial biofilms: analysis and critical review.

Developing reliable anti-biofilm strategies or efficient biofilm-based bioprocesses strongly depends on having a clear understanding of the mechanisms underlying biofilm development, and knowledge of the relevant mechanical parameters describing microbial biofilm behavior. Many varied mechanical testing methods are available to assess these parameters. The mechanical properties thus identified can then be used to compare protocols such as antibiotic screening. However, the lack of standardization in both mechanical testing and the associated identification methods for a given microbiological goal remains a blind spot in the biofilm community. The pursuit of standardization is problematic, as biofilms are living structures, i.e., both complex and dynamic. Here, we review the main available methods for characterizing the mechanical properties of biofilms through the lens of the relationship linking experimental testing to the identification of mechanical parameters. We propose guidelines for characterizing biofilms according to microbiological objectives that will help the reader choose an appropriate test and a relevant identification method for measuring any given mechanical parameter. The use of a common methodology for the mechanical characterization of biofilms will enable reliable analysis and comparison of microbiological protocols needed for improvement of engineering process and screening.

How do environment-dependent switching rates between susceptible and persister cells affect the dynamics of biofilms faced with antibiotics?

Persisters form sub-populations of stress-tolerant cells that play a major role in the capacity of biofilms to survive and recover from disturbances such as antibiotic treatments. The mechanisms of persistence are diverse and influenced by environmental conditions, and persister populations are more heterogeneous than formerly suspected. We used computational modeling to assess the impact of three switching strategies between susceptible and persister cells on the capacity of bacterial biofilms to grow, survive and recover from antibiotic treatments. The strategies tested were: (1) constant switches, (2) substrate-dependent switches and (3) antibiotic-dependent switches. We implemented these strategies in an individual-based biofilm model and simulated antibiotic shocks on virtual biofilms. Because of limited available data on switching rates in the literature, nine parameter sets were assessed for each strategy. Substrate and antibiotic-dependent switches allowed high switching rates without affecting the growth of the biofilms. Compared to substrate-dependent switches, constant and antibiotic-dependent switches were associated with higher proportions of persisters in the top of the biofilms, close to the substrate source, which probably confers a competitive advantage within multi-species biofilms. The constant and substrate-dependent strategies need a compromise between limiting the wake-up and death of persisters during treatments and leaving the persister state fast enough to recover quickly after antibiotic-removal. Overall, the simulations gave new insights into the relationships between the dynamics of persister populations in biofilms and their dynamics of growth, survival and recovery when faced with disturbances.

Relating switching rates between normal and persister cells to substrate and antibiotic concentrations: a mathematical modelling approach supported by experiments.

We developed and compared two mathematical models of variable phenotypic switching rates between normal and persister cells that depend on substrate concentration and antibiotic presence. They could be used to simulate the formation of persisters in environments with concentration gradients such as biofilms. Our models are extensions of a previous model of the dynamics of normal and persistent cell populations developed by Balaban et al. (2004, Science 305: 1622). We calibrated the models' parameters with experimental killing curves obtained after ciprofloxacin treatment of samples regularly harvested from planktonic batch cultures of Klebsiella pneumoniae. Our switching models accurately reproduced the dynamics of normal and persistent populations in planktonic batch cultures and under antibiotic treatment. Results showed that the models are valid for a large range of substrate concentrations and for zero or high doses of antibiotics.

Adaptive management of energy consumption, reliability and delay of wireless sensor node: Application to IEEE 802.15.4 wireless sensor node.

Designing a Wireless Sensor Network (WSN) to achieve a high Quality of Service (QoS) (network performance and durability) is a challenging problem. We address it by focusing on the performance of the 802.15.4 communication protocol because the IEEE 802.15.4 Standard is actually considered as one of the reference technologies in WSNs. In this paper, we propose to control the sustainable use of resources (i.e., energy consumption, reliability and timely packet transmission) of a wireless sensor node equipped with photovoltaic cells by an adaptive tuning not only of the MAC (Medium Access Control) parameters but also of the sampling frequency of the node. To do this, we use one of the existing control approaches, namely the viability theory, which aims to preserve the functions and the controls of a dynamic system in a set of desirable states. So, an analytical model, describing the evolution over time of nodal resources, is derived and used by a viability algorithm for the adaptive tuning of the IEEE 802.15.4 MAC protocol. The simulation analysis shows that our solution allows ensuring indefinitely, in the absence of hardware failure, the operations (lifetime duration, reliability and timely packet transmission) of an 802.15.4 WSN and one can temporarily increase the sampling frequency of the node beyond the regular sampling one. This latter brings advantages for agricultural and environmental applications such as precision agriculture, flood or fire prevention. Main results show that our current approach enable to send more information when critical events occur without the node runs out of energy. Finally, we argue that our approach is generic and can be applied to other types of WSN.

On our rapidly shrinking capacity to comply with the planetary boundaries on climate change.

The planetary boundary framework constitutes an opportunity for decision makers to define climate policy through the lens of adaptive governance. Here, we use the DICE model to analyze the set of adaptive climate policies that comply with the two planetary boundaries related to climate change: (1) staying below a CO2 concentration of 550 ppm until 2100 and (2) returning to 350 ppm in 2100. Our results enable decision makers to assess the following milestones: (1) a minimum of 33% reduction of CO2 emissions by 2055 in order to stay below 550 ppm by 2100 (this milestone goes up to 46% in the case of delayed policies); and (2) carbon neutrality and the effective implementation of innovative geoengineering technologies (10% negative emissions) before 2060 in order to return to 350 ppm in 2100, under the assumption of getting out of the baseline scenario without delay. Finally, we emphasize the need to use adaptive path-based approach instead of single point target for climate policy design.

Using the Reliability Theory for Assessing the Decision Confidence Probability for Comparative Life Cycle Assessments.

Comparative decision making process is widely used to identify which option (system, product, service, etc.) has smaller environmental footprints and for providing recommendations that help stakeholders take future decisions. However, the uncertainty problem complicates the comparison and the decision making. Probability-based decision support in LCA is a way to help stakeholders in their decision-making process. It calculates the decision confidence probability which expresses the probability of a option to have a smaller environmental impact than the one of another option. Here we apply the reliability theory to approximate the decision confidence probability. We compare the traditional Monte Carlo method with a reliability method called FORM method. The Monte Carlo method needs high computational time to calculate the decision confidence probability. The FORM method enables us to approximate the decision confidence probability with fewer simulations than the Monte Carlo method by approximating the response surface. Moreover, the FORM method calculates the associated importance factors that correspond to a sensitivity analysis in relation to the probability. The importance factors allow stakeholders to determine which factors influence their decision. Our results clearly show that the reliability method provides additional useful information to stakeholders as well as it reduces the computational time.

Using the Viability Theory to Assess the Flexibility of Forest Managers Under Ecological Intensification.

Greater demand for wood material has converged with greater demand for biodiversity conservation to make balancing forest ecosystem services a key societal issue. Forest managers, owners, or policymakers need new approaches and methods to evaluate their ability to adapt to this dual objective. We analyze the ability of forest owners to define sustainable forest management options based on viability theory and a new flexibility index. This new indicator gauges the adaptive capacity of forest owners based on the number of sustainable actions available to them at a given time. Here we study a public forest owner who regulates harvest intensity and frequency in order to meet demand for timber wood at forest scale and to meet a biodiversity recommendation via a minimum permanently maintained volume of deadwood per hectare at stand scale. Dynamical systems theory was used to model uneven-aged forest dynamics-including deadwood dynamics-and the dynamics of timber wood demand and tree removals. Uneven-aged silver fir forest management in the "Quatre Montagnes region" (Vercors, France) is used as an illustrative example. The results explain situations where a joint increase in wood production and deadwood retention does not reduce the flexibility index more than increasing either one dimension alone, thus opening up ecological intensification options. To conclude, we discuss the value of the new flexibility index for addressing environmental management and ecological intensification issues.

How to conduct a proper sensitivity analysis in life cycle assessment: taking into account correlations within LCI data and interactions within the LCA calculation model.

Sensitivity analysis (SA) is a significant tool for studying the robustness of results and their sensitivity to uncertainty factors in life cycle assessment (LCA). It highlights the most important set of model parameters to determine whether data quality needs to be improved, and to enhance interpretation of results. Interactions within the LCA calculation model and correlations within Life Cycle Inventory (LCI) input parameters are two main issues among the LCA calculation process. Here we propose a methodology for conducting a proper SA which takes into account the effects of these two issues. This study first presents the SA in an uncorrelated case, comparing local and independent global sensitivity analysis. Independent global sensitivity analysis aims to analyze the variability of results because of the variation of input parameters over the whole domain of uncertainty, together with interactions among input parameters. We then apply a dependent global sensitivity approach that makes minor modifications to traditional Sobol indices to address the correlation issue. Finally, we propose some guidelines for choosing the appropriate SA method depending on the characteristics of the model and the goals of the study. Our results clearly show that the choice of sensitivity methods should be made according to the magnitude of uncertainty and the degree of correlation.

Moment approximation of infection dynamics in a population of moving hosts.

The modelling of contact processes between hosts is of key importance in epidemiology. Current studies have mainly focused on networks with stationary structures, although we know these structures to be dynamic with continuous appearance and disappearance of links over time. In the case of moving individuals, the contact network cannot be established. Individual-based models (IBMs) can simulate the individual behaviours involved in the contact process. However, with very large populations, they can be hard to simulate and study due to the computational costs. We use the moment approximation (MA) method to approximate a stochastic IBM with an aggregated deterministic model. We illustrate the method with an application in animal epidemiology: the spread of the highly pathogenic virus H5N1 of avian influenza in a poultry flock. The MA method is explained in a didactic way so that it can be reused and extended. We compare the simulation results of three models: 1. an IBM, 2. a MA, and 3. a mean-field (MF). The results show a close agreement between the MA model and the IBM. They highlight the importance for the models to capture the displacement behaviours and the contact processes in the study of disease spread. We also illustrate an original way of using different models of the same system to learn more about the system itself, and about the representation we build of it.

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.

Development of a chitosan-based biofoam: application to the processing of a porous ceramic material.

Developing biofoams constitutes a challenging issue for several applications. The present study focuses on the development of a chitosan-based biofoam. Solutions of chitosan in acetic acid were dried under vacuum to generate foams with high-order structures. Chitosan concentration influenced significantly the morphology of developed porosity and the organization of pores in the material. Physico-chemical characterizations were performed to investigate the effects of chitosan concentration on density and thermal conductivity of foams. Even if chitosan-based biofoams exhibit interesting insulating properties (typically around 0.06 W·m(-1)·K(-1)), it has been shown that their durabilities are limited when submitted to a wet media. So, a way of application consists to elaborate a ceramic material with open porosity from a slurry prepared with an organic solvent infiltrating the porous network of the foam.

TWIG: a model to simulate the gravitropic response of a tree axis in the frame of elasticity and viscoelasticity, at intra-annual time scale.

Trees are able to maintain or modify the orientation of their axes (trunks or branches) by tropic movements. For axes in which elongation is achieved but cambial growth active, the tropic movements are due to the production of a particular wood, called reaction wood which is prestressed within the growing tree. Several models have been developed to simulate the gravitropic response of axes in trees due to the formation of reaction wood, all within the frame of linear elasticity and considering the wood maturation as instantaneous. The effect viscoelasticity of wood has, to our knowledge, never been considered. The TWIG model presented in this paper aims at simulating the gravitropic movement of a tree axis at the intra-annual scale. In this work we studied both the effect of a non-instantaneous maturation process and of viscoelasticity. For this purpose, we considered the elastic case with maturation considered as an instantaneous process as the reference. The introduction of viscoelasticity in TWIG has been done by coupling TWIG to a model developed for bridges. Indeed from a purely mechanical point of view, bridges and trees are very similar: they are structures which are built in stages, they are made of several materials (composite structures), their materials are prestressed (wood is prestressed during the maturation process as a result of polymerisation of lignin and cellulose to form the secondary cell wall and concrete is prestressed during drying). Simulations gave evidence that the reorientation process of axes can be significantly influenced by the kinetics of maturation. Moreover the model has now to be tested with more experimental data of wood viscoelasticity but it appears that in the range of a relaxation time from 0 to 50 days, viscoelasticity has an important effect on the evolution of tree shape as well as on the values of prestresses.