Modeling dispersal and connectivity
Because it is impossible to fix GPS trackers to fish larvae, one of the best way to study their dispersal in the open ocean is to through numerical simulations. We use biophysical models to study the impact of orientation behaviors, swimming strategies, and other biological traits that have been discovered by field observations and experiments. In these models we try to accurately represent the characteristics of a target species (e.g. a coral, a fish) in order to estimate the connectivity between populations.
Why does its matter? Many organisms, like corals but also most fishes, stay on the same reef during their adult life. The only exchanges between populations happen at the early stage when larvae are dispersed offshore by the currents and then come back to the reef for settlement. This larval phase is essential for the resilience of reef populations. Understanding, and mapping, these exchanges is important. Estimates of connectivity are used to plan the establishment of Marine Protected Areas, help endangered species to recover, manage fishing stocks, … Therefore, we need to have accurate estimates of connectivity.
One way to do this is to be sure to have realistic models that represent all the behaviors of the larvae during their dispersal. In addition, we can control the propagation of uncertainties within the model. In a biophysical model, both the biological and the physical parts can bring uncertainties. However, they are often only acknowledged and quantified for the physical part when the biological part could be a more important source of uncertainties. The biological component of the biophysical model needs to be specific to a target species, but biological traits are rarely well known, variable, and poorly integrated in the model.
To account for biological uncertainties, we characterize the inputs using observed probability density functions rather than arbitrarily fixed parameters. With a polynomial chaos expansion we track the effects of biological traits on the outputs produced by a biophysical model parametrized to estimate the population connectivity of the sergeant major, a model species in tropical marine ecology. The approach used in our study allows to quantify the individual and combined impact of the biological traits on the different metrics used to characterize the connectivity. The propagation of uncertainty through the model allows us to 1) determine the main contributors to the output uncertainties, 2) test hypothesis based on observations, and 3) guide the focus of future modeling effort toward including some biological uncertainty.
Check our publication on the subject in ICES Journal of Marine Science: https://doi.org/10.1093/icesjms/fsac021