The overall aim of our research is to develop statistical and modeling tools to improve our ability to understand vegetation patterns and to anticipate changes in those patterns.
Ecological models are invaluable tools that allow ecologists to integrate knowledge about how ecosystems work in order to make reliable predictions under different scenarios. We aim to develop process-based eco-hydrological models of forest functioning and dynamics at scales from stands to landscapes.
To describe and explain of the observed vegetation patterns at several scales we need statistical methods tailored to answer specific research questions. We aim to develop, test, and compare statistical methods for the analysis of vegetation structure, composition and dynamics.
Check our specific research lines and list of R packages below.
Develop tools for assessing spatial and temporal variation of forests in structure and composition
Estimation of historic and future weather over forested landscapes
To improve statical methods to determine indicator species
Process-based models to simulate functioning and dynamics of Mediterranean forests
Conceptual and quantitative tools for the creation and maintenance of classifications
Vegetation functioning and dynamics
Landscape meteorology tools
Statistical relationship between species and groups of sites
Fuzzy clustering of vegetation data
List of additional R packages and functions
A scientific information facility about forest structure and functioning over Catalonia (Spain)