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Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients / Clémentine Ols in Ecosystems, vol 24 n° inconnu ([01/07/2021])  

Public [article]  inEcosystems > vol 24 n° inconnu [01/07/2021] Titre : Unexpected negative effect of available water capacity detected on recent conifer forest growth trends across wide environmental gradients Type de document : Article/Communication Auteurs : Clémentine Ols , Auteur ; Thomas Gschwantner, Auteur ; Klemens Schadauer, Auteur ; Jean-Daniel Bontemps , Auteur Année de publication : 2021 Projets : ARBRE / AgroParisTech, LUE / Université de Lorraine Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies alba [Termes IGN] analyse diachronique [Termes IGN] Autriche [Termes IGN] cerne [Termes IGN] changement climatique [Termes IGN] croissance des arbres [Termes IGN] gradient d'altitude [Termes IGN] hétérogénéité environnementale [Termes IGN] inventaire forestier étranger (données) [Termes IGN] inventaire forestier national (données France) [Termes IGN] Larix decidua [Termes IGN] modèle de croissance végétale [Termes IGN] Picea abies [Termes IGN] Pinus sylvestris [Termes IGN] ressources en eau [Termes IGN] structure d'un peuplement forestier [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) National Forest Inventories (NFIs) perform systematic forest surveys across space and time. They are hence powerful tools to understand climate controls on forest growth at wide geographical scales and account for the effects of local abiotic and biotic interactions. To investigate the effects of climate change upon growth dynamics of four major European conifer species along elevation and continentality gradients, we herein provide an original harmonization of the French and Austrian NFI datasets. The growth of Norway spruce, Scots pine, silver fir and European larch over the 1996–2016 period was studied in pure and even-aged plots across different ecological regions. We derived climate-driven growth trends from > 65, 000 radial increment series filtered out from major biotic and abiotic influences using statistical modeling. We further identified primary environmental drivers of conifer growth by regressing growth trends against regionally aggregated biotic and abiotic forest attributes. Negative growth trends were observed in continental regions undergoing the most rapid warming and thermal amplitude contraction over the study period. Negative trends were also associated with lower forest structural heterogeneity and, surprisingly, with greater available water capacity. Remarkably, we observed these associations both at the inter- and intra-species levels, suggesting the universality of these primary growth determinants. Our study shows that harmonized NFI data at the transnational level provide reliable information on climate–growth interactions. Here, greater forest structural complexity and greater water resource limitation were highlighted as drivers of greater forest resilience to climate change at large-scale. This result forms crucial bases to implementing climate-smart forest management. Numéro de notice : A2021-504 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10021-021-00663-3 En ligne : https://doi.org/10.1007/s10021-021-00663-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98116 [article]

A new small area estimation algorithm to balance between statistical precision and scale / Cédric Vega in International journal of applied Earth observation and geoinformation, vol 97 (May 2021)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 97 (May 2021) . - n° 102303 Titre : A new small area estimation algorithm to balance between statistical precision and scale Type de document : Article/Communication Auteurs : Cédric Vega , Auteur ; Jean-Pierre Renaud, Auteur ; Ankit Sagar , Auteur ; Olivier Bouriaud , Auteur Année de publication : 2021 Projets : LUE / Université de Lorraine, DIABOLO / Packalen, Tuula, ARBRE/CHM-era / Jolly, Anne Article en page(s) : n° 102303 Note générale : bibliographie This research was funded by The French Environmental Management Agency (ADEME), grant number 16-60-C0007. The methods and algorithms for processing photogrammetric data were supported by DIABOLO project from the European Union’s Horizon 2020 research and innovation program under grant agreement No 633464, as well as CHM-ERA project from the French National Research Agency (ANR) as part of the “Investissements d’Avenir” program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE). Ankit Sagar received the financial support of the French PIA project “Lorraine Université d’Excellence”, reference ANR-15-IDEX-04-LUE, through the project Impact DeepSurf. Langues : Anglais (eng) Descripteur : [Termes IGN] arbre BSP [Termes IGN] capital sur pied [Termes IGN] données auxiliaires [Termes IGN] données de terrain [Termes IGN] estimation bayesienne [Termes IGN] inventaire forestier national (données France) [Termes IGN] réduction d'échelle [Termes IGN] seuillage [Termes IGN] surface terrière [Vedettes matières IGN] Sylviculture Résumé : (auteur) Combining national forest inventory (NFI) data with auxiliary information allows downscaling and improving the precision of NFI estimates for small domains, where normally too few field plots are available to produce reliable estimates. In most situations, small domains represent administrative units that could greatly vary in size and forested area. In small and poorly sampled domains, the precision of estimates often drop below expected standards. To tackle this issue, we introduce a downscaling algorithm generating the smallest possible groups of domains satisfying prescribed sampling density and estimation error. The binary space partitioning algorithm recursively divides the population of domains in two groups while the prescribed precision conditions are fulfilled. The algorithm was tested on two major forest attributes (i.e. growing stock and basal area) in an area of 7,500 km2 dominated by hardwood forests in the centre of France. The estimation domains consisted in 157 municipalities. The field data included 819 NFI plots surveyed during a 5 years period. The auxiliary data consisted in 48 metrics derived from a forest map, photogrammetric models and Landsat images. A model-assisted framework was used for estimation. For each forest attribute, the best model was selected using a best-subset approach using a Bayesian Information Criteria. The retained models explained 58% and 41% of the observed variance for the growing stocks and basal areas respectively. The performance of the algorithm was evaluated using a minimum of 3 NFI points per domain and estimation errors varying from 10 to 50%. For a target estimation error set to 10%, the algorithm led to a limited number of estimation domains ( The algorithm provides a flexible estimation framework for small area estimation. The key advantages of the approach are relying on its capacity to produce estimations based on a preselected precision threshold and to produce results over the whole area of interest, avoiding areas without any estimates. The algorithm could also be used on any kind of polygon layers (not only administrative ones), provided that the field sampling design enable estimation. This makes the proposed algorithm a convenient tool notably for decision makers and forest managers. Numéro de notice : A2021-067 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2021.102303 date de publication en ligne : 25/01/2021 En ligne : https://doi.org/10.1016/j.jag.2021.102303 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96992 [article]

Effects of thinning practice, high pruning and slash management on crop tree and stand growth in young even-aged stands of planted silver birch (Betula pendula Roth) / Jens Peter Skovsgaard in Forests, vol 12 n° 2 (February 2021)  

Public [article]  inForests > vol 12 n° 2 (February 2021) . - n° 225 Titre : Effects of thinning practice, high pruning and slash management on crop tree and stand growth in young even-aged stands of planted silver birch (Betula pendula Roth) Type de document : Article/Communication Auteurs : Jens Peter Skovsgaard, Auteur ; Ulf Johansson, Auteur ; Emma Hölmstrom, Auteur ; Rebecka McCarthy Tune, Auteur ; Clémentine Ols , Auteur ; Giulia Attocchi, Auteur Année de publication : 2021 Projets : ARBRE / AgroParisTech, LUE / Université de Lorraine Article en page(s) : n° 225 Note générale : bibliographie This work was supported by the Swedish forest-owner association Södra and the Swedish national research program Future Forests. C. Ols was funded by the French National Research Agency (ANR-11-LABX-0002-01 and ANR-15-IDEX-04-LUE) during her review and editing of the paper. Langues : Anglais (eng) Descripteur : [Termes IGN] Betula pendula [Termes IGN] Canada [Termes IGN] croissance des arbres [Termes IGN] éclaircie (sylviculture) [Termes IGN] élagage (sylviculture) [Termes IGN] étude d'impact [Termes IGN] forêt équienne [Termes IGN] Suède [Termes IGN] volume en bois [Vedettes matières IGN] Sylviculture Résumé : (auteur) The objective was to quantify the influence of thinning, high pruning and slash management on crop tree and stand growth in young even-aged stands of planted silver birch (Betula pendula Roth). This study was based on two field experiments, aged six and eleven years at initiation and re-measured after six and eight years, respectively. Treatments included the unthinned control, moderate thinning mainly from below (removing 28–33% of standing volume), point thinning to favor 300 trees per ha and with no thinning elsewhere in the plot (removing 16–25%), and heavy thinning leaving 600 evenly distributed potential future crop trees per ha (removing 64–75%). Slash management (extraction or retention) was applied to heavily thinned plots. High pruning removing 30–70% of the green crown was carried out in some plots with point or heavy thinning on 300 or 600 trees per ha, respectively. Stand volume growth increased with increasing pre-treatment mean annual volume increment and decreased with increasing thinning intensity as compared to the unthinned control. LS-means estimates indicated a reduction for moderate thinning by 14%, for point thinning by 12% and for heavy thinning (combined with pruning) by 62%. However, in the youngest experiment, heavy thinning (without pruning) reduced growth by 54%. Combining these results with results from a similar experiment in Canada, the reduction in stand volume growth (RedIv%) depending on thinning removal (RemV%), both expressed as a percentage of the unthinned control, was quantified as RedIv% = −23.67 + 1.16·RemV% (calibration range: 30–83%). For heavy thinning (large quantities of slash), slash extraction resulted in no reduction in stand volume growth as compared to slash retention. The instantaneous numeric reduction in the average stem diameter of the 300 thickest trees per ha (D300) due to thinning was 3.5, 15–21% and 955–11% with moderate, point and heavy thinning, respectively. The subsequent average annual increase in D300 during the observation period was 8.5%, 25 and 18%, respectively. In the youngest experiment, pruning in unthinned plots led to a reduction in the annual increase of D300 by 14%, and heavy thinning in unpruned plots led to an increase by 30%. The growth of pre-selected potential future crop trees increased with increasing thinning intensity. In heavily thinned plots, pruning reduced growth increasingly with increasing pruning severity; LS-means estimates indicated 21% larger growth on stem diameter for unpruned trees and 3% for pruned trees. As an adverse side effect, heavily thinned plots with only 600 trees per ha were at increased risk of windthrow for some years after the thinning intervention. In the oldest experiment, 95–21% of the trees in these plots were damaged by wind. Numéro de notice : A2021-171 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f12020225 date de publication en ligne : 16/02/2021 En ligne : https://doi.org/10.3390/f12020225 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97132 [article]