Location-Based Plant Species Prediction Using A CNN Model Trained On Several Kingdoms - Best Method Of GeoLifeCLEF 2019 Challenge

International audienceThis technical report describes the model that achieved the best performance of the GeoLifeCLEF challenge, the objective of which was to evaluate methods for plant species prediction based on their geographical location. Our method is based on an adaptation of the Inception v3 architecture initially dedicated to the classification of RGB images. We modified the input layer of this architecture so as to process the spatialized environmental tensors as images with 77 distinct channels. Using this architecture, we did train several models that mainly differed in the used training data and in the predicted output classes. One of the main objective, in particular, was to compare the performance of a model trained with plant occurrences only to that obtained with a model trained on all available occurrences, including the species of other kingdoms. Our results show that the global model performs consistently better than the plant-specific model. This suggests that the convolutional neural network is able to capture some inter-dependencies among all species and that this information significantly improves the generalisation capacity of the model for any species

Location-Based Plant Species Prediction Using A CNN Model Trained On Several Kingdoms - Best Method Of GeoLifeCLEF 2019 Challenge

International audienceThis technical report describes the model that achieved the best performance of the GeoLifeCLEF challenge, the objective of which was to evaluate methods for plant species prediction based on their geographical location. Our method is based on an adaptation of the Inception v3 architecture initially dedicated to the classification of RGB images. We modified the input layer of this architecture so as to process the spatialized environmental tensors as images with 77 distinct channels. Using this architecture, we did train several models that mainly differed in the used training data and in the predicted output classes. One of the main objective, in particular, was to compare the performance of a model trained with plant occurrences only to that obtained with a model trained on all available occurrences, including the species of other kingdoms. Our results show that the global model performs consistently better than the plant-specific model. This suggests that the convolutional neural network is able to capture some inter-dependencies among all species and that this information significantly improves the generalisation capacity of the model for any species

Changes in protein expression in mussels Mytilus galloprovincialis dietarily exposed to PVP/PEI coated silver nanoparticles at different seasons

Potential toxic effects of Ag NPs ingested through the food web and depending on the season have not been addressed in marine bivalves. This work aimed to assess differences in protein expression in the digestive gland of female mussels after dietary exposure to Ag NPs in autumn and spring. Mussels were fed daily with microalgae previously exposed for 24 hours to 10 µg/L of PVP/PEI coated 5 nm Ag NPs. After 21 days, mussels significantly accumulated Ag in both seasons and Ag NPs were found within digestive gland cells and gills. Two-dimensional electrophoresis distinguished 104 differentially expressed protein spots in autumn and 142 in spring. Among them, chitinase like protein-3, partial and glyceraldehyde-3-phosphate dehydrogenase, that are involved in amino sugar and nucleotide sugar metabolism, carbon metabolism, glycolysis/gluconeogenesis and the biosynthesis of amino acids KEGG pathways, were overexpressed in autumn but underexpressed in spring. In autumn, pyruvate metabolism, citrate cycle, cysteine and methionine metabolism and glyoxylate and dicarboxylate metabolism were altered, while in spring, proteins related to the formation of phagosomes and hydrogen peroxide metabolism were differentially expressed. Overall, protein expression signatures depended on season and Ag NPs exposure, suggesting that season significantly influences responses of mussels to NP exposure.This work has been funded by the Spanish Ministry of Economy and Competitiveness (NanoSilverOmics project MAT2012-39372), Basque Government (SAIOTEK project S-PE13UN142 and Consolidated Research Group GIC IT810-13) and the University of the Basque Country UPV/EHU (UFI 11/37 and PhD fellowship to N.D.). This study had also the support of Fundação para a Ciência e Tecnologia (FCT) from Portugal through the Strategic Project UID/MAH00350/2013 granted to CIMA. The contribution of K. Mehennaoui was possible within the project NanoGAM (AFR-PhD-9229040) and M. Mikolaczyk was supported by a PhD fellowship from the French Ministry of Higher Education and Research.info:eu-repo/semantics/acceptedVersio

Globally invariant metabolism but density-diversity mismatch in springtails.

Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning

Life cycle optimization of BECCS supply chains in the European Union

ISSN:0306-2619ISSN:1872-911

Globally invariant metabolism but density-diversity mismatch in springtails

Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning

Globally invariant metabolism but density-diversity mismatch in springtails

Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning.The article is an outcome of the #GlobalCollembola community initiative that is voluntarily supported by researchers around the world.</p

Global fine-resolution data on springtail abundance and community structure

International audienceSpringtails (Collembola) inhabit soils from the Arctic to the Antarctic and comprise an estimated ~32% of all terrestrial arthropods on Earth. Here, we present a global, spatially-explicit database on springtail communities that includes 249,912 occurrences from 44,999 samples and 2,990 sites. These data are mainly raw sample-level records at the species level collected predominantly from private archives of the authors that were quality-controlled and taxonomically-standardised. Despite covering all continents, most of the sample-level data come from the European continent (82.5% of all samples) and represent four habitats: woodlands (57.4%), grasslands (14.0%), agrosystems (13.7%) and scrublands (9.0%). We included sampling by soil layers, and across seasons and years, representing temporal and spatial within-site variation in springtail communities. We also provided data use and sharing guidelines and R code to facilitate the use of the database by other researchers. This data paper describes a static version of the database at the publication date, but the database will be further expanded to include underrepresented regions and linked with trait data