Invasive species are a world-wide scourge, yet at the same time they can provide exceptional models for understanding evolutionary processes. The introduction of invasive species into native species communities can have deleterious effects if native species are unable to adapt, leading to rapid extinction. Alternatively, native communities may be able to adapt to the introduced species, thus shifting their evolutionary trajectory.

To be able to address these questions having access to time series of species before and after the introduction of an invasive species is critical. Historical museum collections can provide unique insights into these questions by proving a window on the anatomy of native species before the arrival of invasive species. Here we will focus on the impact of invasive species on native amphibians on the French Antilles.

Frogs are currently among the most endangered vertebrate taxa and are declining rapidly. The Caribbean region, a global biodiversity hotspot, has not been spared from this phenomenon and much of its endemic diversity has been lost in historical times, amongst others, due to the introduction of invasive species. Yet, some endemic frogs have been able to persist. As these invasive species are phylogenetically and morphologically similar, they likely compete with the native species and likely have impacted their evolutionary trajectory. As these changes are often subtle, accurate descriptions of size and shape made possible using geometric morphometric techniques are needed to detect them.

In the current project we will use the rich collections of the Paris Muséum National d’Histoire Naturelle (MNHN) complemented by specimens from other European natural history collections to investigate these questions. However, one drawback of using historical collections is often the correct identification of specimens and poor locality records. To overcome this hurdle, we will use Artificial Intelligence (AI) based automatic classification algorithms to classify specimens.

In addition to being a critical tool in the current project, the algorithms developed can also be used for rapid species identification and may help biosecurity control by providing an easy to use and automated identification procedure that can assist wildlife authorities at ports of entry. This will be developed with technical assistance of the AI.Nature startup where the PhD student will do an internship. This will allow to develop an AI model for rapid identification of the native and invasive species in target area.

PhD student: Jaleh SARAFRAZ
PhD supervisors: Dr Anthony HERREL (Director)
Research laboratory: MECADEV – UMR 7179 – CNRS/MNHN -- FUNEVOL Team