Mapas de sombra

La sombra es un recurso escaso y muy necesario en la mayoría de ciudades y municipios. Este año -el más calido registrado hasta ahora- se estiman casi 5.000 muertes asociadas al calor en España.

Gracias / Thank you

I have just come back from a wonderful meeting of the Spanish Terrestrial Ecology Association ( AEET) where I received a prize for contributing towards a more open and reproducible science.

Using DHARMa to check Bayesian models fitted with brms

UPDATE 26 October 2022: There is now a DHARMa.helpers package that facilitates checking Bayesian brms models with DHARMa. Check it out! The R package DHARMa is incredibly useful to check many different kinds of statistical models.

Accessing data from large online rasters with Cloud-Optimized-Geotiff, GDAL, and terra R package

Quite often we want to extract climatic or environmental data from large global raster files. The traditional workflow requires downloading the rasters (quite often many GB) and then performing data extraction in your local computer.

New website

I created my former website ( in late 2010, when I was starting my first postdoc at the lovely University of Cambridge. After 10 years, it was about time to revamp it!


The MEDECOS-AEET conference on Mediterranean Ecology will be next week here in Sevilla. The programme looks really exciting - I’m looking forward to it. Here is what we are bringing to the meeting:

New Ecoinformatics working group

Earlier this year a few colleagues (Ignasi Bartomeus, Sara Varela, Antonio J. Pérez-Luque, and myself) created a new working group on Ecoinformatics within the Spanish Terrestrial Ecology Association (AEET). Our main goals are to promote knowledge and training and exchange experiences on all aspects of ecoinformatics, including data management, statistical modelling, programming, etc.

Reproducible Science: What, Why, How

Reproducibility is a hot topic in science nowadays (e.g. see this Nature special). Some argue that we are in the middle of a ‘reproducibility crisis’, and thus scientists are being strongly encouraged to increase the reproducibility of their research.

Reproducible workflows

As a side product (or trailer) of our paper on reproducible science, we made a video promoting reproducible workflows. Particularly, showing how using Git and Rmarkdown make your research and scientific collaboration way much easier and better, compared to a typical (non-reproducible) workflow involving Excel, Word, some figure production software, and a lot of manual steps.

Writing papers in Rmarkdown

Rmarkdown is a great tool for reproducible science. You can combine text and code to produce dynamic reports that generate updated results with a single click, as in the example below.