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Increasing temperatures over an 18-year period shortens growing season length in a beech (Fagus sylvatica L.)-dominated forest / Quentin Hurdebise in Annals of Forest Science [en ligne], Vol 76 n° 3 (September 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > Vol 76 n° 3 (September 2019) . - 12 p. Titre : Increasing temperatures over an 18-year period shortens growing season length in a beech (Fagus sylvatica L.)-dominated forest Type de document : Article/Communication Auteurs : Quentin Hurdebise, Auteur ; Marc Aubinet, Auteur ; Bernard Heinesch, Auteur ; Caroline Vincke, Auteur Année de publication : 2019 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Belgique [Termes descripteurs IGN] carbone [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] écosystème forestier [Termes descripteurs IGN] Fagus sylvatica [Termes descripteurs IGN] phénologie [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] température de l'air [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Key message: Using long-term measurements in a mature beech (Fagus sylvatica L.)-dominated forest located in east Belgium, this paper showed that spring and autumn temperature increases during the last two decades led to an earlier end and a shortening of the growing season. These phenological shifts impact negatively but not significantly the forest annual net ecosystem productivity. Context: The mechanisms controlling temperate forest phenology are not fully understood nor are the impacts of climate change and the consequences for forest productivity. Aims: The aim of this paper is to contribute to the understanding of how temperate forest phenology and net ecosystem productivity (NEP) interplay and respond to temperature and its evolution. Methods: Indicators of leaf phenology and productivity dynamics at the start and the end of the growing season, as well as combinations of these indicators (length of the growing season), were derived from a long-term (1997–2014) dataset of eddy covariance and light transmission measurements taken over a mature beech-dominated temperate forest. Results: The start and the end of the growing season were correlated to spring (and autumn, for the end) temperatures. Despite no trends in annual average temperatures being detected during the observation period, April and November temperatures significantly increased. As a result, an earlier but slower start and an earlier end, inducing a shorter length of the growing season, were observed over the studied period. The first shift positively impacts the mixed forest NEP but is mainly related to the presence of conifers in the subplot. The earlier end of the growing season, more related to beech phenology, negatively impacts the forest NEP. Overall, these two effects partially compensate each other, leading to a non-significant impact on NEP. Conclusion: Increasing temperatures over the 18-year studied period shortened the growing season length, without affecting significantly the mixed forest NEP. However, as beeches are only affected by the earlier end of the growing season, this suggests a phenologically driven beech productivity reduction in the forest. Numéro de notice : A2019-305 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0861-8 date de publication en ligne : 29/07/2019 En ligne : https://doi.org/10.1007/s13595-019-0861-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93242 [article]

Estimating net biomass production and loss from repeated measurements of trees in forests and woodlands: Formulae, biases and recommendations / Takashi S. Kohyama in Forest ecology and management, vol 433 (15 February 2019)  

Public [article]  inForest ecology and management > vol 433 (15 February 2019) . - pp 729 - 740 Titre : Estimating net biomass production and loss from repeated measurements of trees in forests and woodlands: Formulae, biases and recommendations Type de document : Article/Communication Auteurs : Takashi S. Kohyama, Auteur ; Tetsuo I. Kohyama, Auteur ; Douglas Sheil, Auteur Année de publication : 2019 Article en page(s) : pp 729 - 740 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] arbre mort [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] densité du bois [Termes descripteurs IGN] écosystème forestier [Termes descripteurs IGN] erreur systématique [Termes descripteurs IGN] estimation statistique [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] teneur en carbone [Vedettes matières IGN] Sylviculture Résumé : (auteur) There is widespread interest in ensuring that assessment and knowledge of changes in forest biomass, and associated carbon gains or losses, are accurate and unbiased. Repeated measurements of individually-marked trees in permanent plots permit the estimation of rates of biomass production by tree growth and recruitment and of loss from mortality. But there are challenges, for example, simple estimates of production rate (i.e., the sum of biomass gain by growth of surviving trees and new recruits divided by census duration) decline as the census interval increases due to unrecorded growth. Even if we allow for these unobserved changes, additional biases may arise due to the non-independence of growth and mortality and to the heterogeneity and compositional changes within the forest. Here we examine these issues and demonstrate how problems can be minimized. We provide and compare alternative approaches to estimate net biomass production and loss from tree growth and mortality. Under the assumption that specific rates of biomass production and loss, i.e., turnover, are constant over time, we derive estimates of absolute biomass turnover rates that are independent of census duration. We show census-interval dependence of simple turnover rates grows with increasing specific turnover rates. While the time-dependent bias in simple estimates has previously been suggested to increase in proportion to the square of production, we show this relationship is approximately linear. Correlations between stem growth and mortality do not influence our estimates. We account for biomass gain by recruited stems without discounting their initial biomass in production estimates. We can reduce additional biases by accounting for differences in turnover among subpopulations (such as species, sites) and changes in their abundances. We provide worked examples from four forests covering a range of conditions (in Indonesia and Japan) and show the effects of accounting for these biases. For example, over five years in an Indonesian rain forest, simple estimates and instantaneous estimates neglecting species heterogeneity underestimated production by 4.9% and 1.6%, respectively when compared to comprehensive (instantaneous species-structured) estimates. Numéro de notice : A2019-010 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.foreco.2018.11.010 date de publication en ligne : 08/12/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.11.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91604 [article]

A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index / Huanhuan Yuan in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 390 - 399 Titre : A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index Type de document : Article/Communication Auteurs : Huanhuan Yuan, Auteur ; Chaoyang Wu, Auteur ; Linlin Lu, Auteur ; Xiaoyue Wang, Auteur Année de publication : 2018 Article en page(s) : pp 390 - 399 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Canada [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] Enhanced vegetation index [Termes descripteurs IGN] forêt [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] nuit [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] température au sol Résumé : (Auteur) Accurate estimation of vegetation phenology (the start/end of growing season, SOS/EOS) is important to understand the feedbacks of vegetation to meteorological circumstances. Because the evergreen forests have limited change in greenness, there are relatively less study to predict evergreen conifer forests phenology, especially for EOS in autumn. Using 11-year (2000–2010) records of MODIS normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), together with gross primary production (GPP) and temperature data at five evergreen conifer forests flux sites in Canada, we comprehensively evaluated the performances of several variables in modeling flux-derived EOS. Results showed that neither NDVI nor EVI can be used to predict EOS as they had no significant correlation with ground observations. In comparison, temperature had a better predictive strength for EOS, and R2 between EOS and mean temperature (Tmean), the maximum temperature (Tmax, daytime temperature) and the minimum temperature (Tmin, nighttime temperature) were 0.45 (RMSE = 5.1 days), 0.32 (RMSE = 5.7 days) and 0.58 (RMSE = 4.6 days), respectively. These results suggest an unreported role of nighttime temperature in regulating EOS of evergreen forests, in comparison with previous study showing leaf-out in spring by daytime temperature. Furthermore, we demonstrated that it may be because nighttime temperature has a higher relationship with soil temperature (Ts) (R2 = 0.67, p  Numéro de notice : A2018-403 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.08.013 date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90855 [article]

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Climate change risk to forests in China associated with warming / Yunhe Yin in Scientific reports, vol 8 (2018)  

Public [article]  inScientific reports > vol 8 (2018) Titre : Climate change risk to forests in China associated with warming Type de document : Article/Communication Auteurs : Yunhe Yin, Auteur ; Danyang Ma, Auteur ; Shaohong Wu, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] Chine [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] écologie forestière [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] vingt-et-unième siècle [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021–2050) to 27.62% (2071–2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China. Numéro de notice : A2018-009 Thématique : FORET Nature : Article DOI : 10.1038/s41598-017-18798-6 En ligne : http://dx.doi.org/10.1038/s41598-017-18798-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89002 [article]

The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)  

Public [article]  inRemote sensing of environment > vol 200 (October 2017) . - pp 63 - 73 Titre : The potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas Type de document : Article/Communication Auteurs : Emanuele Santi, Auteur ; Simonetta Paloscia, Auteur ; Simone Pettinato, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 63 - 73 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] bande C [Termes descripteurs IGN] bande L [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] capacité de stockage [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] forêt méditerranéenne [Termes descripteurs IGN] image ALOS-PALSAR [Termes descripteurs IGN] image Envisat-ASAR [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] modèle de transfert radiatif [Termes descripteurs IGN] production primaire brute [Termes descripteurs IGN] Toscane (Italie) Résumé : (auteur) The extraction of forest information from SAR images is particularly complex in Mediterranean areas, since they are characterized by high spatial fragmentation and heterogeneity. We have investigated the use of multi-frequency SAR data from different sensors (ALOS/PALSAR and ENVISAT/ASAR) for estimating forest biomass in two test areas in Central Italy (San Rossore and Molise), where detailed in-situ measurements and Airborne Laser Scanning (ALS) data were available. The study focused on the estimation of growing stock volume (GS, in m3/ha) by using an inversion algorithm based on artificial neural networks (ANN). The ANN algorithm was first appropriately trained using the available GS estimates obtained from ALS data. The potential of this algorithm was then improved through the innovative use of a simulated dataset, generated by a forward electromagnetic model based on the Radiative Transfer Theory (RTT). The algorithm is able to merge SAR data at L and C bands for predicting GS in diversified Mediterranean environments. The performed analyses indicated that GS was correctly estimated by integrating information from L and C bands on both test areas, with the following statistics: R > 0.97 and RMSE = 28.5 m3/ha for the independent test, and R = 0.86 and RMSE ≈ 77 m3/ha for the final independent validation, the latter performed on the forest stands of both areas not included in the ALS acquisitions and where conventional measurements were available. The research then illustrates the potential of using the obtained GS estimates from SAR data to drive the simulations of forest net primary production (NPP). This experiment produced spatially explicit estimates of GS current annual increments that are slightly less accurate than those obtained from ground observations (R = 0.75 and RMSE ≈ 1.5 m3/ha/year). Numéro de notice : A2017-415 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : https://doi.org/10.1016/j.rse.2017.07.038 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86307 [article]

Testing the applicability of BIOME-BGC to simulate beech gross primary production in Europe using a new continental weather dataset / Marta Chiesi in Annals of Forest Science [en ligne], vol 73 n° 3 (September 2016)  

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De la modélisation du déterminisme environnemental de la productivité forestière / Jean-Daniel Bontemps (2016)

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The potential of the greenness and radiation (GR) model to interpret 8-day gross primary production of vegetation / Chaoyang Wu in ISPRS Journal of photogrammetry and remote sensing, vol 88 (February 2014)

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Prélèvements et production de bois / Nathalie Derrière in Forêt entreprise, n° 212 (septembre - octobre 2013)

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Ten years of fluxes and stand growth in a young beech forest at Hesse, North-eastern France / André Granier in Annals of Forest Science, Vol 65 n° 7 (October - November 2008)

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