Integrated Remote Sensing for Biodiversity-Ecosystems Function – IRS4BEF

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.

Climate change and human activities jeopardize ecosystems’ biodiversity, functions, and services. Ecological studies suggest that biodiversity plays an important role in maintaining ecosystem function and stability in response to climate variability and extreme events (BEF relationships). Thus, knowing and exploiting BEF relationships is necessary to understand better how to maintain ecosystem services under the current decline in biodiversity. However, the lack of cost-effective, synoptic, and global biodiversity monitoring systems compromises the adequate implementation of conservation programs and understanding BEF relationships.

Remote sensing (RS) is advancing in studying different facets of plant biodiversity and has emerged as a potential biodiversity monitoring tool. It can capture signals linked with vegetation properties (i.e., plant traits) that govern ecosystems’ functions and responses to the environment and signals directly related to such functions (thermal radiation, photochemical reflectance index (PRI), or sun-induced chlorophyll fluorescence (SIF)). At the same time, the spatial variability of these signals relates to the variability of vegetation functional properties.

However, it is unclear how to exploit this multi-source information to assess biodiversity and BEF relationships. For example, which missions should be combined? And how? IRS4BEF seeks to determine which multi-mission integration methods optimize the characterization of plant functional diversity for analyzing and monitoring BEF relationships from space.