Paper Title Number 1
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This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
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Paper Title Number 2
Published:
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 3
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Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
publications
Modelling Land-surface Time-Series with Recurrent Neural Nets
Published in IGARSS 2018, 2018
Recommended citation: Reichstein, M., Besnard, S., et al. (2018). Modelling Land-surface Time-Series with Recurrent Neural Nets. IGARSS 2018. https://doi.org/10.1109/IGARSS.2018.8518007
Quantifying the effect of forest age in annual net forest carbon balance
Published in Environmental Research Letters, 2018
Recommended citation: Besnard, S., et al. (2018). Quantifying the effect of forest age in annual net forest carbon balance. Environmental Research Letters 13(12). https://doi.org/10.1088/1748-9326/aaeaeb
Memory effects of climate and vegetation affecting net ecosystem CO2 fluxes in global forests
Published in PLoS ONE, 2019
Recommended citation: Besnard, S., et al. (2019). Memory effects of climate and vegetation affecting net ecosystem CO₂ fluxes in global forests. PLoS ONE 14(2), e0211510. https://doi.org/10.1371/journal.pone.0211510
Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach
Published in Biogeosciences, 2020
Recommended citation: Jung, M., Schwalm, C., Migliavacca, M., Walther, S., Camps-Valls, G., Koirala, S., Anthoni, P., Besnard, S., et al. (2020). Scaling carbon fluxes from eddy covariance sites to globe: synthesis and evaluation of the FLUXCOM approach. Biogeosciences 17, 1343–1365. https://doi.org/10.5194/bg-17-1343-2020
Emulating Ecological Memory with Recurrent Neural Networks
Published in Deep Learning for the Earth Sciences (Wiley & Sons), 2021
Recommended citation: Kraft, B., Besnard, S., & Koirala, S. (2021). Emulating Ecological Memory with Recurrent Neural Networks. In Deep Learning for the Earth Sciences, Wiley & Sons. https://doi.org/10.1002/9781119646181.ch18
Global sensitivities of forest carbon changes to environmental conditions
Published in Global Change Biology, 2021
Recommended citation: Besnard, S., Santoro, M., Cartus, O., Fan, N., Linscheid, N., Nair, R., Weber, U., Koirala, S., & Carvalhais, N. (2021). Global sensitivities of forest carbon changes to environmental conditions. Global Change Biology. https://doi.org/10.1111/gcb.15877
Mapping global forest age from forest inventories, biomass and climate data
Published in Earth System Science Data, 2021
Recommended citation: Besnard, S., Koirala, S., Santoro, M., Weber, U., Nelson, J., Gütter, J., Herault, B., Kassi, J., N'Guessan, A., Neigh, C., Poulter, B., Zhang, T., & Carvalhais, N. (2021). Mapping global forest age from forest inventories, biomass and climate data. Earth System Science Data 13, 4881–4896. https://doi.org/10.5194/essd-13-4881-2021
A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset
Published in Biogeosciences, 2022
Recommended citation: Walther, S., Besnard, S., et al. (2022). A view from space on global flux towers by MODIS and Landsat: The FluxnetEO dataset. Biogeosciences. https://doi.org/10.5194/bg-19-2805-2022
Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR metrics of vegetation structure
Published in Remote Sensing of Environment, 2022
Recommended citation: Santoro, M., Cartus, O., Besnard, S., et al. (2022). Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR metrics of vegetation structure. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2022.113114
Implications of the steady-state assumption for global vegetation carbon turnover
Published in Environmental Research Letters, 2023
Recommended citation: Fan, N., Santoro, M., Besnard, S., et al. (2023). Implications of the steady-state assumption for global vegetation carbon turnover. Environmental Research Letters. https://doi.org/10.1088/1748-9326/acfb22
Global increase in biomass carbon stock dominated by growth of northern young forests
Published in Nature Geoscience, 2023
Recommended citation: Yang, H., Ciais, P., Besnard, S., et al. (2023). Global increase in biomass carbon stock dominated by growth of northern young forests. Nature Geoscience. https://doi.org/10.1038/s41561-023-01274-4
The global carbon balance of forests based on flux towers and forest age data
Published in Nature Geoscience (in review), 2024
Recommended citation: Ciais, P., Yao, Y., Besnard, S., et al. (2024). The global carbon balance of forests based on flux towers and forest age data. Nature Geoscience (in review). https://doi.org/10.21203/rs.3.rs-5183310/v1
Natural disturbances increasingly affect Europe’s most mature and carbon-rich forests
Published in Biogeosciences (in review), 2025
Recommended citation: Besnard, S., et al. (2025). Natural disturbances increasingly affect Europe's most mature and carbon-rich forests. Biogeosciences (in review). https://doi.org/10.5194/egusphere-2025-6288
Global covariation of forest age transitions with the net carbon balance
Published in Nature Ecology & Evolution, 2025
Recommended citation: Besnard, S., et al. (2025). Global covariation of forest age transitions with the net carbon balance. Nature Ecology & Evolution. https://doi.org/10.1038/s41559-025-02821-5
gediDB: A toolbox for processing and providing GEDI LiDAR data at scale
Published in Journal of Open Source Software, 2025
Recommended citation: Besnard, S., et al. (2025). gediDB: A toolbox for processing and providing GEDI LiDAR data at scale. Journal of Open Source Software. https://doi.org/10.21105/joss.08593