BOSSE v1.0: the Biodiversity Observing System Simulation Experiment

Abstract. As global and regional vegetation diversity loss threatens essential ecosystem services under climate change, monitoring biodiversity dynamics and its role in ecosystem services is crucial in predicting future states and providing insights into climate adaptation and mitigation. In this context, remote sensing (RS) offers a unique opportunity to assess long-term and large-scale biodiversity dynamics. However, the development of this capability suffers from the lack of consistent, global, and spatially matched ground diversity measurements that enable testing and validating generalizable methodologies. The Biodiversity Observing System Simulation Experiment (BOSSE) aims to alleviate the lack of this information by means of simulation. BOSSE simulates synthetic landscapes featuring communities of various vegetation species whose traits's seasonality and ecosystem functions (e.g., biospheric fluxes) respond to meteorology and environmental factors. Simultaneously, BOSSE can generate various types of remote sensing imagery linked to the traits and functions via radiative transfer theory. Specifically, it simulates hyperspectral reflectance factors (R), which can be convolved to the bands of specific RS missions, sun-induced chlorophyll fluorescence (SIF), and land surface temperature (LST). The resolution of the RS imagery can be degraded to test the robustness of different approaches to information loss and the capability of new methodologies to overcome this limitation. Therefore, BOSSE enables users to evaluate the capability of different methods to estimate plant functional diversity (PFD) from RS and link it to ecosystem functions. We expect BOSSE to support the benchmarking and improvement of old and novel methods dedicated to estimating plant diversity and exploring the biodiversity–ecosystem function (BEF) relationships, facilitating advances in this growing area of research and supporting the analysis and interpretation of real-world measurements. We also expect BOSSE to be extended and include new features that provide more realistic simulations that help answer more complex questions related to climate change and global warming.

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Publication Details

Journal
Geoscientific model development
Published
2025-11-11
DOI
https://doi.org/10.5194/gmd-18-8401-2025
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

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BOSSE v1.0: the Biodiversity Observing System Simulation Experiment

Martin Jung, Ulisse Gomarasca, Javier Pacheco‐Labrador, Wantong Li et al.
1 citations
Geoscientific model development
Remote Sensing in Agriculture
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article

BOSSE v1.0: the Biodiversity Observing System Simulation Experiment

Martin Jung, Ulisse Gomarasca, Javier Pacheco‐Labrador, Wantong Li, Daniel E. Pabon‐Moreno, Mirco Migliavacca, Grégory Duveiller
article en
1 citations

Abstract

Abstract. As global and regional vegetation diversity loss threatens essential ecosystem services under climate change, monitoring biodiversity dynamics and its role in ecosystem services is crucial in predicting future states and providing insights into climate adaptation and mitigation. In this context, remote sensing (RS) offers a unique opportunity to assess long-term and large-scale biodiversity dynamics. However, the development of this capability suffers from the lack of consistent, global, and spatially matched ground diversity measurements that enable testing and validating generalizable methodologies. The Biodiversity Observing System Simulation Experiment (BOSSE) aims to alleviate the lack of this information by means of simulation. BOSSE simulates synthetic landscapes featuring communities of various vegetation species whose traits's seasonality and ecosystem functions (e.g., biospheric fluxes) respond to meteorology and environmental factors. Simultaneously, BOSSE can generate various types of remote sensing imagery linked to the traits and functions via radiative transfer theory. Specifically, it simulates hyperspectral reflectance factors (R), which can be convolved to the bands of specific RS missions, sun-induced chlorophyll fluorescence (SIF), and land surface temperature (LST). The resolution of the RS imagery can be degraded to test the robustness of different approaches to information loss and the capability of new methodologies to overcome this limitation. Therefore, BOSSE enables users to evaluate the capability of different methods to estimate plant functional diversity (PFD) from RS and link it to ecosystem functions. We expect BOSSE to support the benchmarking and improvement of old and novel methods dedicated to estimating plant diversity and exploring the biodiversity–ecosystem function (BEF) relationships, facilitating advances in this growing area of research and supporting the analysis and interpretation of real-world measurements. We also expect BOSSE to be extended and include new features that provide more realistic simulations that help answer more complex questions related to climate change and global warming.

Geoscientific model developmentVol. 18(21)
Joint Research Centre (IT), National Research Council (LK), Max Planck Institute for Biogeochemistry (DE), University of California, Berkeley (US)
Ministerio de Ciencia, Innovación y Universidades, European Space Agency, Agencia Estatal de Investigación
Openalex Percentile: Top 12%
Remote Sensing in Agriculture
1.72
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