Courses.

Courses in the scope of biodiversity data science, aimed to built skills on analyses exploring the processes driving the distribution of biodiversity, to provide high quality biodiversity impact assessments and to identify priority conservation areas.

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Marine species distribution modelling and global climate change

Programming language:

The course 'Marine Ecological Modelling and Global Climate Change' was designed as an elective course within the Master programme Marine Biology at the University of Algarve.

Scope

The course covers the interactions and potential impacts of global climate changes (past, ongoing and future) on different levels of marine biodiversity. It is mostly hands­-on oriented, with a strong component on biodiversity and climate data acquisition, management and visualisation (e.g., the new Representative Concentration Pathway scenarios of climate change), as well as on ecological modelling using state of the art mechanistic and correlative approaches (e.g., machine learning algorithms).

Target audience

The course is targeted to PhD students (MSc students can also apply) in the fields of marine biology, ecology, conservation and evolution. Students must be fluent in English and have some basic knowledge on marine ecology, statistics and R computing language (although not mandatory). Students are highly encouraged to bring their own datasets (if data are not available, the professor will provide own data).

Topics

Exploring interactions and potential impacts of global climate changes (past, ongoing and future) on different levels of marine biodiversity.

Goals

Get to know the foundations of ecological niche theory and marine macroecology;
Develop skills on marine biodiversity and climate data acquisition, management and visualisation;
Develop skills on mechanistic and correlative species distribution modelling (SDM);
Understand the strengths of SDM and the concept of transferability across space and time;
Develop skills on good practice SDM following proper parametization and evaluation of performance;
Develop skills on integrating physiological information into hybrid ENM to improve transferability;
Develop skills on niche analyses to infer potential climate drivers of evolution and diversification;
Get to know how to discuss the results of ENM and the potential impacts of climate change on the distribution of marine biodiversity, and defend them to a wide audience.

biodiversityDS.

Jorge Assis [PhD, Research Assistant]
Centre of Marine Sciences, University of Algarve [Faro, Portugal]
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