Dambros Lab

 

I am a professor at the Federal University of Santa Maria, Brazil. I work with biological communities trying to disentangle the processes generating and maintain species diversity. Currently, I am involved in collaborative projects with plants, termites, small mammals, and other organisms. Most of this research is in the Amazonian forest or on the global/continental scale.

 

The research focus my lab have today certainly reflects my past academic journey. There are two experiences in particular that shaped my view of Ecology and science as a whole - my masters at the National Institute for Amazonian Research (INPA) and my Ph.D. at the University of Vermont (USA). In Amazonia, I developed my Masters in Entomology with a strong focus on data-driven research and heavy data-collection in the forest. In contrast, part of my Ph.D. was model-based, sometimes a complete modeling experience. That is, most of the time I was playing on a computer with statistics, R, math, etc. In my lab, I try to combine field data and theoretical ecological models to estimate population/community level parameters (eg. extinction rates) and predict population and community dynamics. Therefore, I have a strong focus both on theoretical and applied ecology.

 

My way of thinking science also reflects much of the advice I received from my Ph.D. advisor, Nick Gotelli, and my Ph.D. committee, especially my appreciation for efficient scientific communication and data sharing. Moreover, there are some contemporary ecologists that I use as references for best practices, such as Brian McGill and Jeremy Fox (check Dynamic Ecology blog).

 

I conduct my work mostly in the R program, which I use to analyze, simulate and integrate data. My students and I make all the data we collect and all main R functions available online (look for my GitHub and Figshare accounts) free for use and distribution. You can find functions to extract partial scores from a multiple regression, to construct a model of the ecological neutral theory, to nicely plot species distributions along environmental gradients, etc.