Energy investment into maturation encompasses any expenses linked to tissue differentiation, i.e. re-organization of body structure during development. This is different from growth which can be conceptualized as synthesis of more of the same. Energy invested into growth is fixed into the biomass of the organism (with some overheads), but energy invested in maturation is oxidized as metabolic work making it more difficult to quantify in practice. Nonetheless it can be quantified and it can even represent a substantial part of the energy budget of living organisms. In this talk I will give an overview of different studies where investment in maturity was quantified. The focus will be on 4 different types of organisms: cnidarians, ctenophores, teleost fish and frogs. I will further discuss what type of eco-physiological effects might be expected when an organism modifies its investment into these processes. Some intriguing literature studies will be presented which can be re-interpreted in perhaps unexpected ways when investment into maturation is taken into account. This raises the question of just how important and how flexible such costs might actually be. Maturity can be used as a quantifier for internal time. Seven criteria were proposed which should be respected by any such metric: (1) independent of morphology, (2) independent of body size, (3) depend on one a priori homologous event, (4) unaffected by changes in temperature, (5) similar between closely related species, (6) increase with clock time, and (7) physically quantifiable (Reiss 1989). We showed that the maturity concept of Dynamic Energy Budget theory complies with all those criteria and on the basis of this information and the studies presented above I will finish by discussing the potential role of maturity in shaping metabolic flexibility.[-]

Data collection and subsequent interpretation plays an important role in many ecological problems. Quantities such as the total population size and/or average population density are often evaluated based on data collected as a result of a sampling procedure. Accurate evaluation of the above quantities is crucial in ecological applications where they are used for making decision about means of control. Examples include management of pest insects in agricultural fields, prevention of plant diseases and control of geographic spread of invasive species.
One essential feature of ecological data is that the data are often sparse due to financial, labour, and other restrictions on the sampling routine. Meanwhile it is usually assumed by practitioners that estimates of ecological quantities obtained are representative, no matter how coarse a sampling grid is. This assumption is, however, not necessarily true. It will be discussed in the talk that evaluation from sparse data can lead to a loss of important information about the population dynamics. I argue that conclusions about data quality are not always obvious and practitioners can be mislead by the results of standard validation tests. It will then be shown that accuracy of the population size estimation is strongly affected by pattern formation and the number of samples required for accurate evaluation should be related to the properties of a spatial pattern. I will also discuss the effect of synchronization of population dynamics on disjoint habitats in order to demonstrate that the pattern formation, if not taken into account by a sampling procedure, may lead to unjustified or even false conclusions about the absence/presence of synchronization.[-]

The mathematical model of the chemostat has been extensively studied and extended from the eightees, not only as a mathematical representation of the chemostat device invented in the fifties, but also as a general model of resource/consumer dynamics in microbial ecosystems, such as in marine ecology, food fermentation, waste-water treatment, biotechnology.
I will present a survey of some recent and less recent results about extensions of this model, that concern the roles of spatialization, density dependent growth, attachment/detachment and their impacts on stability and biodiversity.[-]

Antibiotic resistance is a serious public health concern. Responding to this problem effectively requires characterising the factors (i.e. evolutionary and ecological processes) that determine resistance frequencies. At present, we do not have ecologically plausible models of resistance that are able to replicate observed trends - we are therefore unable to make credible predictions about resistance dynamics. In this talk, I will present work motivated by three tends observed in Streptococcus pneumoniae resistance data: the stable coexistence of antibiotic sensitivity and resistance, variation between resistance frequencies between pneumococcal lineages and correlation in resistance to different antibiotics. I will propose that variation in the fitness benefit gained from resistance arising from variation in the duration of carriage of pneumococcal lineages is a parsimonious explanation for all three trends. This eco-evolutionary framework could allow more accurate prediction of future resistance levels and play a role in informing strategies to prevent the spread of resistance.[-]

L'écologie est une discipline quantitative dans laquelle les mathématiques sont présentes sous différentes formes depuis très longtemps. En conséquence, l'arrivée massive d'ordinateurs de plus en plus puissants dans les laboratoires dans les dernières décennies, a conduit à une explosion de la modélisation dans ce domaine, sous forme de calculs numériques mais également par l'analyse mathématique de modèles relativement simples. Cette croissance importante de l'activité de modélisation mathématique a été accompagnée par une augmentation de la complexité des modèles d'écologie qui tentent d'intégrer la plus grosse quantité de processus connus possible. Parallèlement, les moyens d'expérimentations et d'observation du milieu naturel n'ont pas cessé de s'améliorer, produisant ainsi des bases de données de plus en plus complètes dans la description du fonctionnement des écosystèmes. Paradoxalement, la formulation de base des processus utilisée dans les modèles complexes est toujours la même et fondée sur des expérimentations réalisées dans des conditions homogènes de laboratoire au cours du XXème siècle. Nous posons la question de l'intérêt d'une description adéquate d'un écosystème pour comprendre ses réponses à différentes perturbations. Une approche consiste à utiliser des formulations mécanistes des processus, c'est à dire des formulations fondées sur des détails expliquant la cause de la réalisation des processus, plutôt que des formulations empiriques acquises dans des conditions différentes du milieu dans lequel on les applique. Cette prise en compte des mécanismes induit encore un surcroit de complexité. Les mathématiques fournissent un ensemble d'idées et de méthodes permettant tout d'abord de produire des formulations adaptées à la prise en compte des mécanismes et également d'aborder cette complexité des modèles écosystémiques, voire dans certains cas de la réduire. Nous illustrerons cette démarche à travers des exemples d'applications variés.[-]

The statement that organisms in their natural environments are subject to a multitude of environmental factors – some beneficial, some adverse and some either favorable or neutral or detrimental depending on their intensity or that of other factors – is a truism that nonetheless stresses a major challenge for ecologists. Societal needs press us to find answers to questions such as “What will be the implications of rising sea surface temperatures, acidifying oceans, increasing run-off and intensifying storms expected due to climate change on reef-building corals?” and “How will materials emerging through technological innovation, such as the rapid development of nanotechnology, compound with existing stress factors to affect organisms in their natural environment and food crops?”.

Perhaps somewhat less of a commonplace statement, a single environmental factor can have multiple physiological effects on a single organism. For instance, ocean acidification, i.e. the changes in the ocean carbonate system due to an increasing atmospheric pCO2, may have physiological impacts that are both positive, e.g. stimulating photosynthesis through CO2 enrichment, and negative, e.g. inducing pH stress and increasing the costs for calcification. As another example, toxic compounds often interfere with several organismal processes; e.g. cadmium may enhance the production of reactive oxygen species, inhibit enzymes via binding to sulfhydryl groups and cause zinc deficiencies, among other potential interferences.

Complex problems such as those outlined abovecall for an integrative metabolic theory, such as Dynamic Energy Budget (DEB) theory, that considers a multivariate environment with stressors that are potentially interfering with several physiological processes simultaneously. I will illustrate how those kinds of complex problems can be addressed in DEB theory with various examples, including the impact of global change induced stress on marine calciferous organisms, the impact of engineered nanoparticles on the stability of symbioses of plants and nitrogen-fixing bacteria with generalized, process-based DEBtox theory.[-]