Machine Learning

Building models for explainng and predicting life on Earth

Using machine learning algorithms, we build models that can forecast species distributions and ecosystem responses under various future scenarios.

Explore our projects

Publications in the scope of machine learning

Global seaweed productivity

Seaweed productivity is strongly related to climatic variables, peaking at temperate latitudes and exhibiting exceptionall...

Mapping global biodiversity patterns of marine forests

Stacked species distribution modelling identifies regions of high and low species richness and endemicity of marine forest...

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Projects in the scope of machine learning

Biodiversity database of West Africa for stakeholders

A database structured under Darwin Core standards, offering a stable, straightforward and flexible framework for sharing b...

Understanding aquaculture in a changing climate

A project to enhance aquaculture sustainability and suitability while fostering interdisciplinary collaboration.

Consequences of climate change for marine forests gene pools

A project aimed at investigating the effects of climate change on key marine forest species, such as kelp, fucoids and col...


biodiversityDS.
Centre of Marine Sciences
Faro, Portugal