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Javier Pacheco-Labrador

Which multi-mission integration methods can optimize the characterization of plant functional diversity for analyzing and monitoring Biodiversity-Ecosystems Function relationships from space?

Javier Pacheco-Labrador is a postdoctoral researcher at the Max Planck Institute for Biogeochemistry (MPI-BGC) in Germany. He is interested in understanding ecosystem properties, functions, biodiversity, and responses to the environment from space. Javier confronts models and data to improve models, methods, and assimilation schemes and answer ecological questions regarding ecosystems’ adaptation to climate change.

He completed an MSc in remote sensing at the University of Alcalá, Spain, and then his Ph.D. at the Spanish National Research Council (SpecLab-CSIC) on automated proximal sensing and BRDF modeling in a heterogeneous Mediterranean ecosystem. Then he moved to MPI-BGC, participating in projects focused on linking radiative transfer modeling with physiological processes, which he used together with hyperspectral, thermal, and sun-induced fluorescence data to study ecosystem functions and biodiversity, focusing on Mediterranean ecosystems.


Research Objectives

The combination of information provided by different optical and thermal spaceborne imagers can give complementary information about vegetation plant biodiversity and ecosystem functions to understand their links (BEF relationships) better. However, how integrating multi-mission information in this context remains unclear. Therefore, IRS4BEF wants to solve relevant methodological questions regarding the integration and analysis of these data.

IRS4BEF seeks to:

1) understand how multi-mission data in the optical and thermal domains can be integrated to provide enhanced estimates of plant functional diversity that are linked to ecosystem functions and their responses to the environment, considering the added value of the different missions.

2) determining the optimal approaches to integrate remote biodiversity estimates with ecosystem function responses to the environment as measured in eddy covariance stations to assess and monitor BEF relationships.