Experience

Machine Learning and Geospatial processing. Developed machine learning models and automated workflows to predict forest structure from remote sensing (LiDAR and satellite images).

Performed a global meta-analysis of changes in population performance across species ranges, in relation to recent warming trends.

Performed a global meta-analysis of tree canopies buffering of forest understory temperatures.

Compiled historical records and carried out field vegetation surveys to analyse changes in southern Spanish forests in the last 25 years, in the light of climate change and forest management practices.

Collaborated on several biogeographical studies involving species distribution modelling of Carex species.

Hierarchical Bayesian modelling, R and C++ programming.

Developed an statistical framework (based on hierarchical Bayesian state-space models) to reconstruct species range dynamics with climate changes.

Also, assessing the importance of microclimates and climatic refugia to facilitate species’ persistence under climate change.

Hierarchical Bayesian modelling of tree demography.

Dendrochronology. Climate change impacts on relict tree species.

Years of intensive field work inventorying forest plots and monitoring tree demography in southern Spain to better understand the persistence of relict species under climate change. Also travelling across the Mediterranean collecting samples for a genetic study on the phylogeography of laurel tree species. Finally, implementing species distribution models to reconstruct the range dynamics of several Mediterranean species in the last million years, and to forecast their future distributions with climate change.