INTEGRATED REMOTE SENSING FOR BIODIVERSITY-ECOSYSTEM FUNCTION (IRS4BEF)

IRS4BEF  seeks to optimise the integration of multi-source remote sensing imagery to quantify plant functional diversity at site scale (e.g., eddy covariance station) and assess Biodiversity-Ecosystem Function relationships. The underlying hypothesis is that missions providing spectral information of different domains could be more informative of the role of plant functional diversity on ecosystem functions than the data provided by a single sensor.

To test this hypothesis and obtain a beyond-empirical understanding of the potential benefits and caveats of the proposed method, IRS4BEF is developing BOSSE, the Biodiversity Observation System Simulation Experiment. BOSSE simulates scenes with different degrees of taxonomic and functional diversity, where species properties evolve in response to meteorology. For these scenes, BOSSE radiative transfer models can generate remote sensing imagery of optical reflectance, sun-induced chlorophyll fluorescence (SIF), and land surface temperature (LST), mimicking the features of multiple sensors (e.g., Sentiel-2, EnMAP, …). The simulator also includes soil-vegetation-atmosphere and other semi-empirical models to produce the time series of ecosystem functions (e.g., gross primary production (GPP), ecosystem respiration (Reco), latent (λE), and sensible (H) heat fluxes, etc.) as a function of meteorology and plant functional traits. From these functions, which are measured in eddy covariance stations, BOSSE calculates the ecosystem functional properties that can be used to assess the role of plant functional diversity on the ecosystem functioning. Different metrics, approaches, and combinations of sensors can be tested to determine the most robust and accurate methods for the estimation of plant functional diversity and BEF analysis.