• Request for proposal: Innovation LABEX TULIP 2016
  • Financing: LABEX TULIP, Occitanie Region
  • Project managers: Terroïko – SETE-CNRS
  • Partners: Terroïko – SETE-CNRS
  • Contact: Sylvain Moulherat (TerrOïko), Simon Blanchet (SETE)
  • Duration: 12 mois (2017-2018)
  • Total budget: 19,3 k€
  • Grant: 8,4 k€

MetAqua in the news


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MetAqua, extention of the application field of the SimOïko modelling platform to strictly aquatic species

logo Labex Tulip The digital simulation model SimOïko is derived from the research model MetaConnect, developed with a view to analyse meta population dynamics of terrestrial or partially terrestrial species (amphibians). The SimOïko model has though benefited from validation tests carried out for terrestrial species, however the extension of the model to strictly aquatic species still needs to be validated. The MetAqua project is run in collaboration with SETE-CNRS and aims to 1) validate the predictive skills of SimOïko for strictly aquatic species and 2) when appropriate, develop additional MetaConnect algorithms for these species.

Green and blue network (« Trame Verte et Bleue »), is a landscape planning instrument related to the « Grenelle 2 » law. It is mainly used to avoid species extinction due to population isolation. Indeed, isolated populations, especially when small, are more likely to disappear due to genetic and demographic stochastic events. This mechanism known as extinction vortex can be stamp down by dispersal when reproductive individuals can leave their current population and settle in a new one. Green and Blue Network is thus based on the scientific knowledge that networks conservation through dispersal is essential to population conservation. Nevertheless, dispersal is a complex process resulting from a trade-off of ecological and evolutionary constraints. Research in this field has highlighted that because of their multi-causal characteristics, dispersal rate and distance show very high intraspecific and interspecific variations. It has been demonstrated that intraspecific variability is influenced by both environmental and social context and the individual phenotype. Dispersal is thus closely linked to species life history traits and to interaction between individual phenotypes and its environment.

Faced with the difficulty in predicting how species will disperse in a particular landscape, the first ecological network conservation strategy deployed by practitioners has been based on landscape structural connectivity. These methods assume that the ecological network can be defined by similar habitats close to each other. These methods do not explicitly handle dispersal process and population demography. According to this hypothesis, proximity enhances transfer of individuals from one habitat to another. Green and Blue network is thus designed by searching for the each species its favourable habitat patches and selecting those which are close enough.

In order to avoid this oversimplification and explicitly consider dispersal process in the Green and Blue Network design, since 2012 TerrOïko develops a numerical simulation platform (SimOïko) derived from the MetaConnect model. MetaConnect is a spatially explicit and individual-based meta-population model that is able to simulate population dynamics, dispersal and gene flows. Green and Blue Networks studies based on SimOïko significantly enhance studies quality and relevance. However, for now, it is calibrated only for terrestrial or partially terrestrial species (amphibians, dragonflies, etc).

The current project aims at extending the application field of the SimOïko modelling platform to strictly aquatic species, including fish.

Aquatic frame minnow Minnow genetics CETE CNRS

The results of population genetic simulations from SimOïko (left) wild be compared with field data (right).

General methodology :

SimOïko will be used outside its initial scope to simulate population dynamics of strictly aquatic meta populations. The test and validation steps consist in 1)Comparing the results of SimOïko aquatic module with other existing models; 2)Realising several simulations in a landscape for which we have field data and verify the consistency of simulated vs field results.