L’apport des dispositifs de suivi vis-à-vis des enjeux de fonctionnement et de gestion des écosystèmes en relation avec les sols

Face aux incertitudes liées aux changements environnementaux, les réseaux de suivi sont une source de données essentielle pour appréhender l’évolution des écosystèmes. En France, trois réseaux nationaux s’intéressent à l’évolution du sol ou de la forêt en relation avec les sols. Initialement conçus pour suivre l’effet des pollutions atmosphériques sur la santé des forêts, le réseau systématique de suivi des dommages forestiers et le réseau RENECOFOR correspondent aux deux composantes extensive et intensive du monitoring forestier paneuropéen (ICP Forests). Créé plus récemment, le RMQS suit spécifiquement la qualité des sols en étendant le maillage extensif du suivi forestier aux autres usages (cultures, prairies, milieux naturels). Initiatives pionnières et encore jeunes au regard de la vitesse d’évolution des sols et des forêts, ces réseaux ont néanmoins déjà apporté de nombreux résultats originaux et démontré leur potentiel à répondre à des attentes de plus en plus diversifiées

Glucose Transporter 1 and Monocarboxylate Transporters 1, 2, and 4 Localization within the Glial Cells of Shark Blood-Brain-Barriers

Although previous studies showed that glucose is used to support the metabolic activity of the cartilaginous fish brain, the distribution and expression levels of glucose transporter (GLUT) isoforms remained undetermined. Optic/ultrastructural immunohistochemistry approaches were used to determine the expression of GLUT1 in the glial blood-brain barrier (gBBB). GLUT1 was observed solely in glial cells; it was primarily located in end-feet processes of the gBBB. Western blot analysis showed a protein with a molecular mass of 50 kDa, and partial sequencing confirmed GLUT1 identity. Similar approaches were used to demonstrate increased GLUT1 polarization to both apical and basolateral membranes in choroid plexus epithelial cells. To explore monocarboxylate transporter (MCT) involvement in shark brain metabolism, the expression of MCTs was analyzed. MCT1, 2 and 4 were expressed in endothelial cells; however, only MCT1 and MCT4 were present in glial cells. In neurons, MCT2 was localized at the cell membrane whereas MCT1 was detected within mitochondria. Previous studies demonstrated that hypoxia modified GLUT and MCT expression in mammalian brain cells, which was mediated by the transcription factor, hypoxia inducible factor-1. Similarly, we observed that hypoxia modified MCT1 cellular distribution and MCT4 expression in shark telencephalic area and brain stem, confirming the role of these transporters in hypoxia adaptation. Finally, using three-dimensional ultrastructural microscopy, the interaction between glial end-feet and leaky blood vessels of shark brain was assessed in the present study. These data suggested that the brains of shark may take up glucose from blood using a different mechanism than that used by mammalian brains, which may induce astrocyte-neuron lactate shuttling and metabolic coupling as observed in mammalian brain. Our data suggested that the structural conditions and expression patterns of GLUT1, MCT1, MCT2 and MCT4 in shark brain may establish the molecular foundation of metabolic coupling between glia and neurons

Towards long-term standardised carbon and greenhouse gas observations for monitoring Europe's terrestrial ecosystems : a review

Research infrastructures play a key role in launching a new generation of integrated long-term, geographically distributed observation programmes designed to monitor climate change, better understand its impacts on global ecosystems, and evaluate possible mitigation and adaptation strategies. The pan-European Integrated Carbon Observation System combines carbon and greenhouse gas (GHG; CO2, CH4, N2O, H2O) observations within the atmosphere, terrestrial ecosystems and oceans. High-precision measurements are obtained using standardised methodologies, are centrally processed and openly available in a traceable and verifiable fashion in combination with detailed metadata. The Integrated Carbon Observation System ecosystem station network aims to sample climate and land-cover variability across Europe. In addition to GHG flux measurements, a large set of complementary data (including management practices, vegetation and soil characteristics) is collected to support the interpretation, spatial upscaling and modelling of observed ecosystem carbon and GHG dynamics. The applied sampling design was developed and formulated in protocols by the scientific community, representing a trade-off between an ideal dataset and practical feasibility. The use of open-access, high-quality and multi-level data products by different user communities is crucial for the Integrated Carbon Observation System in order to achieve its scientific potential and societal value.Peer reviewe

L’apport des dispositifs de suivi vis-à-vis des enjeux de fonctionnement et de gestion des écosystèmes en relation avec les sols

Face aux incertitudes liées aux changements environnementaux, les réseaux de suivi sont une source de données essentielle pour appréhender l’évolution des écosystèmes. En France, trois réseaux nationaux s’intéressent à l’évolution du sol ou de la forêt en relation avec les sols. Initialement conçus pour suivre l’effet des pollutions atmosphériques sur la santé des forêts, le réseau systématique de suivi des dommages forestiers et le réseau RENECOFOR correspondent aux deux composantes extensive et intensive du monitoring forestier paneuropéen (ICP Forests). Créé plus récemment, le RMQS suit spécifiquement la qualité des sols en étendant le maillage extensif du suivi forestier aux autres usages (cultures, prairies, milieux naturels). Initiatives pionnières et encore jeunes au regard de la vitesse d’évolution des sols et des forêts, ces réseaux ont néanmoins déjà apporté de nombreux résultats originaux et démontré leur potentiel à répondre à des attentes de plus en plus diversifiées

How monitoring networks contribute to the understanding and to the management of soil and forest ecosystems?

Faced with the uncertainties linked to environmental change, the monitoring networks are an essential source of data in order to anticipate changes in ecosystems. In France, three national networks are concerned with the change in the soil and/or forest in relation to the soil. Initially designed to monitor the effect of atmospheric pollution on the health of forests, the systematic network for the monitoring of forest damage (RSSDF) and the RENECOFOR network correspond to the two extensive and intensive components of pan-European forest monitoring (ICP Forests). Created more recently, the RMQS specifically monitors soil quality by extending the grid for forest monitoring to other land uses (crops, meadows, natural or urban environments). Pioneering and recent initiatives regarding the speed of change of soils and forests, these networks have nonetheless already generated a large number of original results and have shown their potential to meet expectations that are becoming increasingly diversified

Optimizing pedotransfer functions for estimating soil bulk density using boosted regression trees

International audiencePedotransfer functions (PTFs) are used to estimate certain soil properties that are difficult and costly to measure front others more easily available. Bulk density is one important soil property. Although nor requiring complex analysis, its measurement remains time consuming and is lacking in many soil surveys. For several decades, PTFs have been developed for predicting soil bulk density. Most of these PTFs are suited only for specific agro-pedo-climatic conditions, however, and can be applied only within a limited geographic area. In this study, we derived and experimented with two new PTFs based on a multiple additive regression trees (MART) method, and assessed their performance compared with existing PTFs when applied to a country-level soil database, the Reseau de Mesures de la Qualite des Sols (RMQS) survey network. This database was designed to include the major soil types and land uses in France. The first proposed PTF (Model m) involves only three predictors typically found in the existing PTFs for bulk density (C content and texture) and the second one (Model M) includes eight easily accessible quantitative and qualitative predictors (e.g., soil taxon). Both models significantly outperformed existing PTFs. Without arbitrarily partitioning the data set before fitting the model, the m and M MART models yielded R-2 values of 0.83 and 0.94, respectively. The predictive quality on independent data, assessed using cross-validation, was also improved compared with published PTFs, with R-2 reaching 0.62 and 0.66 and root mean square prediction errors of 0.123 and 0.117 Mg m(-3) for the two MAPT models