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1. Thinning Can Reduce Losses in Carbon Use Efficiency and Carbon Stocks in Managed Forests Under Warmer Climate.

Author

Collalti, Alessio, Trotta, Carlo, Keenan, Trevor F, Ibrom, Andreas, Bond-Lamberty, Ben, Grote, Ruediger, Vicca, Sara, Reyer, Christopher PO, Migliavacca, Mirco, Veroustraete, Frank, Anav, Alessandro, Campioli, Matteo, Scoccimarro, Enrico, Šigut, Ladislav, Grieco, Elisa, Cescatti, Alessandro, and Matteucci, Giorgio

Subjects
CO2 fertilization, ISIMIP, carbon sequestration, climate change, forest management, forest model, Atmospheric Sciences
Abstract

Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here we assess the potential impact of thinning on projected carbon cycle dynamics and implications for forest CUE and its components (i.e., gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process-based forest ecosystem model forced by climate outputs of five Earth System Models under four representative climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO2 concentration, and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development, and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations lead the forests to grow faster, mature earlier, and also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody pools, and reduce physiological-climate-induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest-based mitigation strategies and should be carefully considered within a portfolio of mitigation options.

Published
2018

15. Scientific Committee

Author

Mougenot, Bernard, primary, Lacaze, Bernard, additional, Veroustraete, Frank, additional, Demaze, Moise Tsayem, additional, Oszwald, Johan, additional, Mouillot, Florent, additional, Maille, Eric, additional, Boucher, Olivier, additional, Leon, Jean François, additional, Frejafon, Emeric, additional, De Michele, Marcello, additional, Jappiot, Marielle, additional, Lacroix, Pascal, additional, Allemand, Pascal, additional, Delorme, Arthur, additional, Rouzeau, Olivier, additional, Andreoli, Rémi, additional, Pirard, Eric, additional, Desprats, Jean-François, additional, Froger, Jean Luc, additional, Villeneuve, Nicolas, additional, Dessay, Nadine, additional, Betbeder, Julie, additional, Amsallem, Jennifer, additional, Vignoles, Cécile, additional, Vanwanbeke, Sophie, additional, Baghdadi, Nicolas, additional, and Zribi, Mehrez, additional

Published
2016
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27. VALERI: a network of sites and a methodology for the validation of medium spatial resolution land satellite products

Author

Baret, Frédéric, Weiss, Marie, Allard, Denis, Garrigue, Sébastien, Leroy, Marc, Jeanjean5, Hervé, Fernandes, R, Myneni, R, Privette, J, Morisette, J, Bohbot, Hervé, Bosseno, Roland, Dedieu, Gérard, Di Bella, Carlos, Duchemin, Benoît, Espana, Marisa, Gond, Valery, Gu, Xing, Guyon, Dominique, Lelong, Camille, Maisongrande, Philippe, Mougin, Éric, Nilson, Tiit, Veroustraete, Frank, Vintilla, Roxana, Environnement Méditerranéen et Modélisation des Agro-Hydrosystèmes (EMMAH), Avignon Université (AU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Biostatistique et Processus Spatiaux (BioSP), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National d'Etudes Spatiales - Direction Des Lanceurs. (CNES), Centre d'études et de formation en enseignement supérieur (CEFES), Université de Montréal (UdeM), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), INRA (INRA CSE), Institut National de la Recherche Agronomique (INRA), Centre d'études spatiales de la biosphère (CESBIO), Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Instituto Nacional de Tecnología Agropecuaria (INTA), Universidad Michoacana de San Nicolás de Hidalgo (UMICH), Forêts et Sociétés (UPR Forêts et Sociétés), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Département Environnements et Sociétés (Cirad-ES), Laboratoire de bioclimatologie, Territoires, Environnement, Télédétection et Information Spatiale (UMR TETIS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Tartu Observatory, Flemish Institute for Technological Research (VITO), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Unité mixte de recherche Climat Sol et Environnement (UMR CSE 1114), Institut National de la Recherche Agronomique (INRA)-Avignon Université (AU), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
validation, upscaling, remote sensing, biophysical variable, [SDE]Environmental Sciences, transfer function, kriging
Abstract

Validation is mandatory to quantify the reliability of satellite biophysical products that are now routinely generated by a range of sensors. This paper presents the VALERI project dedicated to the validation of the products derived from medium resolution satellite sensors (www. avignon.inra.fr/valeri/). It describes the sites used, and the methodology developed to get the high spatial resolution map of the biophysical variables considered, i.e. LAI, fAPAR and fCover that can be estimated from ground level gap fraction measurements. Sites were selected to represent , with the other validation projects, the large variation of biomes and conditions observed over the Earth's surface. Each site is about 3×3 km² in size and should be flat and relatively homogeneous at the medium resolution scale. For each site, the methodology used to generate the high spatial resolution biophysical variable maps is described. It is mainly based on concurent use of local gound measurements and a high spatial resolution satellite image, generally SPOT-HRV. Local ground measurements should be representative of an elementary sampling unit (ESU) that has approximately the same size as a SPOT-HRV pixel. The ground measurements mainly consist of gap fraction measurements achieved with LAI-2000 or hemispherical photographs. The ESUs are selected over the whole 3×3 km² site in order to sample the range of vegetation types observed. A transfer function is subsequently established over the ESUs to relate the ground measurements of the biophysical variables considered to the correspodonding high spatial resolution satellite image data. Finally, co-kriging is applied to generate the high spatial resolution map of the biophysical variables over the 3×3 km² area. The methodology presented in this paper can serve as a basis for validating medium resolution satellite products. These methodological aspects are discussed and conclusions drawn on the limitations and prospects of beforementioned validation activity.

Published
2021

39. Extending the SPOT-VEGETATION NDVI time series (1998-2006) back in time with NOAA-AVHRR data (1985-1998) for Southern Africa

Author

Swinnen, Else and Veroustraete, Frank

Subjects
United States. National Oceanic and Atmospheric Administration -- Standards, Remote sensing -- Research, Radiometers -- Usage, Environmental indexes -- Evaluation, Image processing -- Technology application, Time-series analysis -- Methods, Technology application, Business, Earth sciences, Electronics and electrical industries
Abstract

A new consistent long-term normalized difference vegetation index (NDVI) time series at a l-[km.sup.2] resolution for Southern Africa that is based on the data from Satellite Pour l'Observation de la Terre VEGETATION (VGT) (1998-2006) and the National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (AVHRR) (1985-1998) has been produced for vegetation-dynamics monitoring purposes. This paper presents the evaluation of the newly processed AVHRR data set, as well as the integration of this data set with the VGT archive. First, the AVHRR processing chain and the resulting AVHRR data set have been investigated with respect to calibration accuracy, cloud masking, and atmospheric and geometric correction. Second, different calibration approaches, spectral response (SR) functions, spatial resolutions, overpass times, and geometries of observation for the VGT and AVHRR data sets have been compared for a common observation period. The application of published correction functions accounting for the SR differences for both sensors considerably improved the consistency between both data sets. An [r.sup.2] of 0.85 is obtained between paired samples of the NDVI from the VGT and the newly processed AVHRR archive. After the application of the correction functions, the slope of the regression line between the two NDVI data sets was much closer to the 1:1 line. The performance of the correction functions differed among vegetation types. The largest reduction in the root-mean-square error between the NDVI of both sensors is obtained from areas with higher biomass. Large parts of the remaining variability are suggested to be attributed to the bidirectional reflectance distribution function effects, as demonstrated by the intersensor NDVI time-series variability versus the intrasensor NDVI time-series variability. Index Terms--lmage processing, spectral response function (SRF), time series.

Published
2008

46. Application of remote sensing in regional scale estimates of vegetation carbon budgets: The Belfix project

Author

Veroustraete, Frank, Patyn, Johan, and Myneni, R. B

Subjects
Earth Resources And Remote Sensing
Abstract

A concept for coupling the remote sensing derived fraction of the absorbed photosynthetic active radiation (FAPAR) with a functional ecosystem model was developed. The study was named the Belfix procedure. The quantification of changes in carbon dynamics at the ecosystem level is a key issue in studies of global climatic change effects at the vegetation atmosphere interface. An operational procedure, for the determination of carbon fluxes at the regional scale (Belgian territory), is presented. The approach allows for the determination of the sink function of vegetation for carbon (dioxide). The phyto- and litter mass, photosynthetic assimilation, autotroph and heterotroph carbon fluxes and net ecosystem exchange (NEE) of carbon, were evaluated. The results suggest that a single solution can be obtained for ecosystem rates and states, applying an iterative procedure, based on minimizing the change in maximal seasonal green phytomass in function of yearly FAPAR temporal profiles. Total phytomass values obtained are in close range with those obtained by ground sampling.

Published
1994

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