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A meta-analysis of changes in soil organic carbon stocks after afforestation with deciduous broadleaved, sempervirent broadleaved, and conifer tree species / Guolong Hou in Annals of Forest Science [en ligne], vol 77 n° 4 (December 2020)
Titre : A meta-analysis of changes in soil organic carbon stocks after afforestation with deciduous broadleaved, sempervirent broadleaved, and conifer tree species Type de document : Article/Communication Auteurs : Guolong Hou, Auteur ; Claudio O. Delang, Auteur ; Xixi Lu, Auteur ; Lei Gao, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] afforestation
[Termes IGN] arbre caducifolié
[Termes IGN] arbre sempervirent
[Termes IGN] boisement artificiel
[Termes IGN] feuillu
[Termes IGN] Pinophyta
[Termes IGN] puits de carbone
[Termes IGN] sol
[Vedettes matières IGN] Ecologie forestière
Résumé : (auteur) Key message: Different tree species have dissimilar capacities to sequester soil organic carbon (SOC). Deciduous broadleaved trees show the most stable increase in SOC stock after afforestation than other tree species, while sempervirent conifer trees show the lowest rate of SOC stock change. Sempervirent broadleaved trees show the greatest increase in SOC stock 20 years after afforestation.
Context: The rate at which soil organic carbon (SOC) stock changes after afforestation varies considerably with the tree species. A better understanding of the role of tree species in SOC change dynamic is needed to evaluate the SOC sequestration potential of afforestation programs.
Aims: The aim of this paper is to identify the dissimilar rates at which different tree species sequester SOC, following afforestation.
Methods: We complete a meta-analysis with 544 data points from 261 sites in 90 papers. We group tree species into decidious broadleved, sempervirent broadleaved and sempervirent conifer. We use standardization and/or extrapolation methods to standardize soil depths. Statistical analysis test the main effects of tree species and their interactions with previous land use and plantation age on SOC stock change after afforestation.
Results: Deciduous broadleaved trees show a stable increase in SOC stock, and are especially suited for afforestation of grassland or soils with high initial SOC. Sempervirent broadleaved afforestation results in loss of SOC stock in young stands, but greater SOC stock in mature stands. Sempervirent conifer trees show the lowest rate of SOC stock change, but are suitable for nutrient-poor soil.
Conclusion: The results emphasize the importance of considering tree species when estimating SOC stock change, in particular when carbon sequestration is an objective of afforestation programs.
Numéro de notice : A2020-590 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00997-3 Date de publication en ligne : 25/09/2020 En ligne : https://doi.org/10.1007/s13595-020-00997-3 Format de la ressource électronique : URL article Permalink :
in Annals of Forest Science [en ligne] > vol 77 n° 4 (December 2020) . - 13 p.[article]Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands / Fabio Castaldi in ISPRS Journal of photogrammetry and remote sensing, vol 147 (January 2019)
Titre : Evaluating the capability of the Sentinel 2 data for soil organic carbon prediction in croplands Type de document : Article/Communication Auteurs : Fabio Castaldi, Auteur ; Andreas Hueni, Auteur ; Sabine Chabrillat, Auteur ; Kathrin Ward, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 267 - 282 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Allemagne
[Termes IGN] analyse comparative
[Termes IGN] analyse multivariée
[Termes IGN] Belgique
[Termes IGN] bilan du carbone
[Termes IGN] capacité de stockage
[Termes IGN] image APEX
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] Luxembourg
[Termes IGN] puits de carbone
[Termes IGN] rapport signal sur bruit
[Termes IGN] sol
[Termes IGN] surface cultivée
Résumé : (auteur) The short revisit time of the Sentinel-2 (S2) constellation entails a large availability of remote sensing data, but S2 data have been rarely used to predict soil organic carbon (SOC) content. Thus, this study aims at comparing the capability of multispectral S2 and airborne hyperspectral remote sensing data for SOC prediction, and at the same time, we investigated the importance of spectral and spatial resolution through the signal-to-noise ratio (SNR), the variable importance in the prediction (VIP) models and the spatial variability of the SOC maps at field and regional scales. We tested the capability of the S2 data to predict SOC in croplands with quite different soil types and parent materials in Germany, Luxembourg and Belgium, using multivariate statistics and local ground calibration with soil samples. We split the calibration dataset into sub-regions according to soil maps and built a multivariate regression model within each sub-region. The prediction accuracy obtained by S2 data is generally slightly lower than that retrieved by airborne hyperspectral data. The ratio of performance to deviation (RPD) is higher than 2 in Luxembourg (2.6) and German (2.2) site, while it is 1.1 in the Belgian area. After the spectral resampling of the airborne data according to S2 band, the prediction accuracy did not change for four out of five of the sub-regions. The variable importance values obtained by S2 data showed the same trend as the airborne VIP values, while the importance of SWIR bands decreased using airborne data resampled according the S2 bands. These differences of VIP values can be explained by the loss of spectral resolution as compared to APEX data and the strong difference in terms of SNR between the SWIR region and other spectral regions. The investigation on the spatial variability of the SOC maps derived by S2 data has shown that the spatial resolution of S2 is adequate to describe SOC variability both within field and at regional scale. Numéro de notice : A2019-037 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.11.026 Date de publication en ligne : 06/12/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.11.026 Format de la ressource électronique : URL article Permalink :
in ISPRS Journal of photogrammetry and remote sensing > vol 147 (January 2019) . - pp 267 - 282[article]
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Code-barres Cote Support Localisation Section Disponibilité 081-2019011 RAB Revue Centre de documentation En réserve 3L Disponible 081-2019013 DEP-EXM Revue LaSTIG Dépôt en unité Exclu du prêt 081-2019012 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêtBiodiversity effects on ecosystem functioning in a 15-year grassland experiment: patterns, mechanisms, and open questions / Wolfgang W. Weisser in Basic and Applied Ecology, vol 23 (September 2017)
Titre : Biodiversity effects on ecosystem functioning in a 15-year grassland experiment: patterns, mechanisms, and open questions Type de document : Article/Communication Auteurs : Wolfgang W. Weisser, Auteur ; Christiane Roscher, Auteur ; Sebastian Meyer, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Ecologie
[Termes IGN] azote
[Termes IGN] biomasse
[Termes IGN] carbone
[Termes IGN] écosystème
[Termes IGN] gaz à effet de serre
[Termes IGN] nutriment végétal
[Termes IGN] placette d'échantillonnage
[Termes IGN] potassium
[Termes IGN] puits de carbone
[Termes IGN] richesse floristique
[Termes IGN] sol
[Termes IGN] stabilité
Résumé : (auteur) In the past two decades, a large number of studies have investigated the relationship between biodiversity and ecosystem functioning, most of which focussed on a limited set of ecosystem variables. The Jena Experiment was set up in 2002 to investigate the effects of plant diversity on element cycling and trophic interactions, using a multi-disciplinary approach. Here, we review the results of 15 years of research in the Jena Experiment, focussing on the effects of manipulating plant species richness and plant functional richness. With more than 85,000 measures taken from the plant diversity plots, the Jena Experiment has allowed answering fundamental questions important for functional biodiversity research.
First, the question was how general the effect of plant species richness is, regarding the many different processes that take place in an ecosystem. About 45% of different types of ecosystem processes measured in the ‘main experiment’, where plant species richness ranged from 1 to 60 species, were significantly affected by plant species richness, providing strong support for the view that biodiversity is a significant driver of ecosystem functioning. Many measures were not saturating at the 60-species level, but increased linearly with the logarithm of species richness. There was, however, great variability in the strength of response among different processes. One striking pattern was that many processes, in particular belowground processes, took several years to respond to the manipulation of plant species richness, showing that biodiversity experiments have to be long-term, to distinguish trends from transitory patterns. In addition, the results from the Jena Experiment provide further evidence that diversity begets stability, for example stability against invasion of plant species, but unexpectedly some results also suggested the opposite, e.g. when plant communities experience severe perturbations or elevated resource availability. This highlights the need to revisit diversity-stability theory.
Second, we explored whether individual plant species or individual plant functional groups, or biodiversity itself is more important for ecosystem functioning, in particular biomass production. We found strong effects of individual species and plant functional groups on biomass production, yet these effects often occurred mostly in addition to, but not instead of, effects of plant species richness.
Third, the Jena Experiment assessed the effect of diversity on multitrophic interactions. The diversity of most organisms responded positively to increases in plant species richness, and the effect was stronger for above- than for belowground organisms, and stronger for herbivores than for carnivores or detritivores. Thus, diversity begets diversity. In addition, the effect on organismic diversity was stronger than the effect on species abundances.
Fourth, the Jena Experiment aimed to assess the effect of diversity on N, P and C cycling and the water balance of the plots, separating between element input into the ecosystem, element turnover, element stocks, and output from the ecosystem. While inputs were generally less affected by plant species richness, measures of element stocks, turnover and output were often positively affected by plant diversity, e.g. carbon storage strongly increased with increasing plant species richness. Variables of the N cycle responded less strongly to plant species richness than variables of the C cycle.
Fifth, plant traits are often used to unravel mechanisms underlying the biodiversity-ecosystem functioning relationship. In the Jena Experiment, most investigated plant traits, both above- and belowground, were plastic and trait expression depended on plant diversity in a complex way, suggesting limitation to using database traits for linking plant traits to particular functions.
Sixth, plant diversity effects on ecosystem processes are often caused by plant diversity effects on species interactions. Analyses in the Jena Experiment including structural equation modelling suggest complex interactions that changed with diversity, e.g. soil carbon storage and greenhouse gas emission were affected by changes in the composition and activity of the belowground microbial community. Manipulation experiments where particular organisms, e.g. belowground invertebrates, were excluded from plots in split-plot experiments, supported the important role of the biotic component for element and water fluxes.
Seventh, the Jena Experiment aimed to put the results into the context of agricultural practices in managed grasslands. The effect of increasing plant species richness from 1 to 16 species on plant biomass was, in absolute terms, as strong as the effect of a more intensive grassland management, using fertiliser and increasing mowing frequency. Potential bioenergy production from high-diversity plots was similar to that of conventionally used energy crops. These results suggest that diverse ‘High Nature Value Grasslands’ are multifunctional and can deliver a range of ecosystem services including production-related services.
A final task was to assess the importance of potential artefacts in biodiversity–ecosystem functioning relationships, caused by the weeding of the plant community to maintain plant species composition. While the effort (in hours) needed to weed a plot was often negatively related to plant species richness, species richness still affected the majority of ecosystem variables. Weeding also did not negatively affect monoculture performance; rather, monocultures deteriorated over time for a number of biological reasons, as shown in plant-soil feedback experiments.
To summarize, the Jena Experiment has allowed for a comprehensive analysis of the functional role of biodiversity in an ecosystem. A main challenge for future biodiversity research is to increase our mechanistic understanding of why the magnitude of biodiversity effects differs among processes and contexts. It is likely that there will be no simple answer. For example, among the multitude of mechanisms suggested to underlie the positive plant species richness effect on biomass, some have received limited support in the Jena Experiment, such as vertical root niche partitioning. However, others could not be rejected in targeted analyses. Thus, from the current results in the Jena Experiment it seems likely that the positive biodiversity effect results from several mechanisms acting simultaneously in more diverse communities, such as reduced pathogen attack, the presence of more plant growth promoting organisms, less seed limitation, and increased trait differences leading to complementarity in resource uptake. Distinguishing between different mechanisms requires careful testing of competing hypotheses. Biodiversity research has matured such that predictive approaches testing particular mechanisms are now possible.
Numéro de notice : A2017-352 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1016/j.baae.2017.06.002 Date de publication en ligne : 26/06/2017 En ligne : https://doi.org/10.1016/j.baae.2017.06.002 Format de la ressource électronique : URL article Permalink :
in Basic and Applied Ecology > vol 23 (September 2017)[article]A spatial dataset of forest mensuration collected in black pine plantations in central Italy / Paolo Cantiani in Annals of Forest Science [en ligne], vol 74 n° 3 (September 2017)
Titre : A spatial dataset of forest mensuration collected in black pine plantations in central Italy Type de document : Article/Communication Auteurs : Paolo Cantiani, Auteur ; Maurizio Marchi, Auteur Année de publication : 2017 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre (flore)
[Termes IGN] base de données localisées
[Termes IGN] bois mort
[Termes IGN] données de terrain
[Termes IGN] données dendrométriques
[Termes IGN] éclaircie (sylviculture)
[Termes IGN] géoréférencement
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] Pinus nigra
[Termes IGN] placette d'échantillonnage
[Termes IGN] sol
[Termes IGN] Toscane (Italie)
[Vedettes matières IGN] Inventaire forestier
Résumé : (Auteur) Key message : The dataset provides an exhaustive tree inventory with forest mensuration and spatial location carried out in 54 plots sampled in 45- to 55-year-old black pine plantations, located in two areas of Tuscany (central Italy). Forest mensuration includes horizontal and vertical structure measurements and a total of 4171 trees were geo-referenced. The most abundant species was the black pine, Pinus nigra spp. laricio, for which a total of 3631 trees were observed. The dataset was collected as part of the SelPiBio LIFE project (LIFE13 BIO/IT/000282). Dataset access athttp://doi.org/10.5281/zenodo.438681. Associated metadata available athttps://metadata-afs.nancy.inra.fr/geonetwork/apps/georchestra/?uuid=73591027-0f1e-40a3-95d0-b614517c1290&hl=eng.
Context : The main aim of the SelPiBio LIFE project (www.selpibio.eu) is to demonstrate the effects of two thinning regimes, selective and from below, on soil biodiversity in young black pine stands. The spatial structure of forests and the relationships between trees are a good proxy of overall biodiversity level. Spatial datasets with geo referenced trees and related mensurational data represent the highest level of information for forest inventories and research activities.
Aims : This dataset has been developed during the A2 Action (Assessment of structural and mensurational parameters of the forest stands and the dead wood) of the project, to record the main mensurational parameters of the studied black pine stands. A tree-level database was compiled to describe the vertical and horizontal structure of 54 monitoring plots before the application of the silvicultural treatment.
Methods : In addition to classical in-field measurements (e.g. diameters at breast height, total height of the tree, crown depth etc.), all trees were georeferenced by means of polar coordinates collected from the centre of each monitoring plot, including crown projection on the ground, described with eight points. Then, a polynomial spline function was fitted across the recorded data to obtain a convex polygon and to calculate crown area and crown perimeter of each measured tree in GIS environment.
Results : A polygonal ESRI shapefile in ETRS89/UTM32N reference system (EPSG: 25832) with 4171 records representing the crown projections on the ground of each measured tree with all the mensurational parameters included into the attribute table. The database is freely available under the Creative Commons Attribution-NonCommercial 4. 182 0 License.
Conclusion : With this database, a wide range of forestry-related indices could be easily calculated, including geostatistical analysis and autocorrelation functions, to compare Italian artificial black pine stands with other studied forests.
Numéro de notice : A2017-355 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1007/s13595-017-0648-8 Date de publication en ligne : 26/06/2017 En ligne : https://doi.org/10.1007/s13595-017-0648-8 Format de la ressource électronique : URL article Permalink :
in Annals of Forest Science [en ligne] > vol 74 n° 3 (September 2017)[article]TM-Based SOC models augmented by auxiliary data for carbon crediting programs in semi-arid environments / Salahuddin M. Jaber in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 6 (June 2017)
Titre : TM-Based SOC models augmented by auxiliary data for carbon crediting programs in semi-arid environments Type de document : Article/Communication Auteurs : Salahuddin M. Jaber, Auteur ; Mohammed I. Al-Qinna, Auteur Année de publication : 2017 Article en page(s) : pp 447 - 457 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] données auxiliaires
[Termes IGN] image Landsat-TM
[Termes IGN] Jordanie
[Termes IGN] matière organique
[Termes IGN] prédiction
[Termes IGN] sol
[Termes IGN] teneur en carbone
[Termes IGN] zone semi-aride
Résumé : (Auteur) This study aimed at testing the hypothesis that augmenting Landsat TM-based models for predicting soil organic carbon (SOC) with auxiliary data about variables that might affect the spatial distribution of SOC might improve the predictability of these models in the Zarqa Basin in Jordan (a typical semi-arid watershed) and enable them to be used for implementing carbon crediting programs in semi-arid environments. Six modeling procedures, namely stepwise regression, partial least squares, recursive partitioning analysis, screening regression analysis, artificial neural networks, and combined models, were calibrated and validated for the basin and for the land cover types that exist in the basin. Although none of the developed models was powerful for predicting SOC, artificial neural networks models were more applicable specifically in agricultural lands. However, the margins of error associated with the best models were high, and hence hindered the applicability of these models in carbon crediting programs in semi-arid environments. Numéro de notice : A2017-350 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.83.6.447 En ligne : https://doi.org/10.14358/PERS.83.6.447 Format de la ressource électronique : URL article Permalink :
in Photogrammetric Engineering & Remote Sensing, PERS > vol 83 n° 6 (June 2017) . - pp 447 - 457[article]
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