Axis 2 leaders: 

• Thierry Frédou (UFRPE)
• Audrey Darnaude (CNRS-MARBEC)
• Claire Carré (IRD-MARBEC)

Axis 2 aims to understand the biodiversity and functioning of the ecosystems, including their response to climate variability and human impacts such as overfishing, habitat loss, and pollution. The axis also seeks to identify priority areas for conservation and management of marine resources.

 

Problematic and Gaps

Marine biodiversity is important for the sustainability of marine resources and ecosystems. However, there is a lack of knowledge on the diversity and ecology of several species, especially in the deep-sea, and a limited understanding of the spatiotemporal connections among marine communities. There is a need for effective networks of protected areas, sustainable fisheries management, and sound estimates of the ocean capacity to mitigate atmospheric CO2 level rises.

 

Main Objectives

Our main goal is to deepen the research undertaken during the 1st phase of TAPIOCA by gathering additional key information on the diverse marine taxa present in North-eastern Brazil, their spatiotemporal dynamics, and their respective roles in ecosystem functioning and connecting.

 

Main Topics  – Two main topics are addressed:

• The geographic and taxonomic gaps remaining in the current map of local biodiversity.
• The comprehension of  the movements of key species and the associated fluxes of individuals and biomass across ecosystems, as well as the resulting horizontal (coast-ocean) and vertical (diel vertical migrations) carbon fluxes.

Main tools – Four types of main tools are being used:

• Biodiversity inventory, monitoring and quantification.
• Analyses of the Population ecology and dynamics will be carried on using natural tags (isotopic or chemical markers in soft and hard tissues) and artificial marks (acoustic or archival tags). Moreover, other aspects of species’ ecology (such as populations’ age structure, growth parameters and reproductive traits) will be investigated, especially for deep-sea species in which they are largely unknown.
• Integrated database of Tapioca data.
• Biostatistics and modelling.