Deforestation, degradation and violence in the “Gurupi Mosaic” – The most threatened region of Amazonia

O "Mosaico Gurupi" está localizado entre o oeste do Maranhão e o leste do Pará, na Área de Endemismo Belém, que embora seja a região mais desmatada do Bioma Amazônico no Brasil, preserva uma diversidade cultural e biológica superlativa. O mosaico engloba seis Terras Indígenas (Alto Turiaçu, Awá, Caru, Arariboia, Rio Pindaré e Alto Rio Guamá) e uma Unidade de Conservação (Reserva Biológica do Gurupi). Essas áreas protegidas conservam os principais remanescentes florestais da região e garantem a manutenção de serviços ecossistêmicos essenciais aos dois estados, principalmente de regulação hidrológica. No entanto, essa região vive sob ameaças constantes de desmatamento e de degradação pela extração ilegal de madeira, e por incêndios criminosos. Os povos indígenas e lideranças comunitárias da região são vitimados pela violência associada a tais crimes. Para promover a conservação e a restauração dessas áreas, uma rede formada por diversas instituições indígenas e não indígenas vem trabalhando em conjunto para o reconhecimento do "Mosaico Gurupi" pelo Ministério do Meio Ambiente. A proposta aqui apresentada inclui o mosaico em questão e o Corredor Ecológico da Amazônia Maranhense, que irá conectar os principais remanescentes florestais da região, por meio da restauração das matas ciliares ao longo dos rios Buriticupu, Pindaré e Zutiua. A conformação do mosaico visa integrar esforços para a proteção territorial, a restauração florestal e o fortalecimento da cultura e educação indígena; o que poderá converter a região mais ameaçada da Amazônia em um exemplo de conservação e sustentabilidade econômica e social por meio da promoção da restauração florestal.The "Gurupi Mosaic" is located between west Maranhão and east Pará states, in the Belém Endemism Area, which although being the most deforested region of the Amazonian biome in Brazil, preserves superlative biological and cultural diversity. The Mosaic includes six indigenous lands (Alto Turiaçu, Awá, Caru, Araribóia, Rio Pindaré, Alto Rio Guamá) and a conservation unit (Gurupi Biological Reserve). These protected areas conserve the region’s main forest remnants and guarantee the maintenance of essential ecosystem services. However, this region is under constant threats of deforestation and degradation by illegal logging and arson. Indigenous peoples living in the region are victims of the violence associated with such crimes. To promote the conservation and restoration of these areas, several indigenous and non-indigenous institutions have been working together to formalize the "Gurupi Mosaic" with the Ministry of the Environment. The proposal presented here includes the Mosaic and one ecological corridor in the state of Maranhão, which will connect the region’s last forest remnants through the restoration of the riparian forests along the main rivers. The conformation of the Mosaic aims to integrate efforts to protect territories, restore forests and strengthen indigenous culture and education. This could turn the most threatened region of Amazonia into an example of conservation and economic and social sustainability

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Publisher Copyright: © 2021, The Author(s).Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change.Peer reviewe

Performance of the ATLAS electromagnetic calorimeter end-cap module 0

The construction and beam test results of the ATLAS electromagnetic end-cap calorimeter pre-production module 0 are presented. The stochastic term of the energy resolution is between 10% GeV^1/2 and 12.5% GeV^1/2 over the full pseudorapidity range. Position and angular resolutions are found to be in agreement with simulation. A global constant term of 0.6% is obtained in the pseudorapidity range 2.5 eta 3.2 (inner wheel)

Global data on earthworm abundance, biomass, diversity and corresponding environmental properties

Earthworms are an important soil taxon as ecosystem engineers, providing a variety of crucial ecosystem functions and services. Little is known about their diversity and distribution at large spatial scales, despite the availability of considerable amounts of local-scale data. Earthworm diversity data, obtained from the primary literature or provided directly by authors, were collated with information on site locations, including coordinates, habitat cover, and soil properties. Datasets were required, at a minimum, to include abundance or biomass of earthworms at a site. Where possible, site-level species lists were included, as well as the abundance and biomass of individual species and ecological groups. This global dataset contains 10,840 sites, with 184 species, from 60 countries and all continents except Antarctica. The data were obtained from 182 published articles, published between 1973 and 2017, and 17 unpublished datasets. Amalgamating data into a single global database will assist researchers in investigating and answering a wide variety of pressing questions, for example, jointly assessing aboveground and belowground biodiversity distributions and drivers of biodiversity change

Prediction of physico-chemical properties in the context of the French PREDIMOL project

The new EU regulation REACH requires the evaluation of the physico-chemical properties of a large number of substances in order to allow their use before 2018. Taking into account the number of substances and properties, the timing, the economic costs, the feasibility at the R&D level and the risks for the manipulator, in particular for the characterization of the dangerous physico-chemical properties (explosibility, flammability), the experimental measurement of all the data is not realistic. Thus, the development of alternative predictive methods for the evaluation of the properties of substances was recommended in the framework of REACH. In this context, the French PREDIMOL (molecular modeling prediction of physico-chemical properties of products) project [1] funded by ANR (National Research Agency) has started in November 2010 for 3 years. This project is conducted by INERIS associated with several public and private partners. Its objective is to demonstrate that molecular modeling is a credible alternative method to experimental characterization to predict in a reliable and fast manner, the whole range of physico-chemical properties of substances required by EU-REACH's regulation (annexes VII and IX) and for the industry in terms of property-screening method. In a first step, the project is focused on the prediction of physico-chemical properties related to organic peroxides, amines and halogenated compounds. In a second phase of the project, high throughout predictions will be considered. More precisely, predictive and validated QSPR (Quantitative Structure-Property Relationship) models related in particular to hazardous properties (like explosibility) are developed whereas molecular simulation methods (Molecular Dynamics, Monte Carlo) are used or adapted for thermo-physical properties like viscosity or density. Another critical objective of this project is the regulatory validation of models by European chemical instances in order that predictive data could be used for registration of chemicals in REACH. Hence, they will be submitted to the JRC comity for acceptance or to existing tools (like QSAR toolbox) for integration. In 2011, existing group contribution methods, QSPR models notably associated with quantum chemical description of molecular structures, SAFT equations, COSMO-RS approach and force fields that could be used for the prediction of the properties of the compounds under concerned have been identified, stressing onto performances and limits of each approach. Inventory of existing experimental data from literature has also been established. As predictivity of QSPR models highly depends on the database pertinence in terms of number of data, coherence and uncertainties of measurements, reliable experimental databases have been consolidated, in particular for the enthalpy of decomposition of organic peroxides

Prédiction des propriétés physico-chimiques dans le cadre du projet PREDIMOL

La nouvelle réglementation européenne REACH nécessite, d'ici à 2018, l'évaluation des propriétés physico-chimiques d'un grand nombre de substances afin de permettre leur utilisation. Prenant en compte le nombre de substances et de propriétés, le temps, le coût, la faisabilité au niveau R&D et les risques pour les manipulateurs, en particulier pour la caractérisation des propriétés physico-chimiques dangereuses (explosibilité, inflammabilité), la détermination expérimentale de toutes les données requises n'est pas réaliste. Aussi, le développement de méthodes prédictives alternatives pour l'évaluation des propriétés des substances est recommandé dans le cadre de REACH. Dans ce contexte, le projet ANR PREDIMOL (PREDIction des propriétés physico-chimiques des produits par modélisation MOLéculaire) [1] a débuté en novembre 2010 pour 3 ans, coordonné par l'INERIS associé à différents partenaires publiques et privés. Il a pour but de démontrer que la modélisation moléculaire représente une alternative fiable et rapide à l'expérimentation afin de prédire les propriétés physico-chimiques requises par REACH (Annexes VII et IX) et utiles à l'industrie dans des démarches de screening de propriétés. Dans un premier temps, il se focalise sur les propriétés de peroxydes organiques et d'amines, avant d'envisager des prédictions à haut-débits. Plus précisément, des modèles QSPR (pour Quantitative Structure Property Relationships) prédictifs et validés sont développés pour les propriétés dangereuses (comme l'explosibilité) alors que des méthodes de simulation moléculaire (Dynamique Moléculaire, Monte Carlo) sont utilisées pour les propriétés thermo-physiques telles que la viscosité ou la densité. Un autre objectif du projet est la validation règlementaire des modèles par les instances européennes afin que les données prédites puissent être utilisées pour l'enregistrement des produits chimiques. Ainsi, les modèles seront soumis au JRC (Joint Research Center) pour acceptation ou à des outils existants (comme la QSAR Toolbox de l'OCDE et de l'ECHA [2]) pour intégration. Depuis 2010, les méthodes existantes (par contribution de groupes, modèles QSPR (notamment associés à des descripteurs de chimie quantique des structures moléculaires), équations SAFT, approche COSMO et champs de force) utilisables pour la prédiction des propriétés des composés ciblés ont été identifiées ainsi que leurs performances et leurs limites. Un inventaire des données expérimentales disponibles dans la littérature a également été réalisé. Comme la prédictivité des modèles QSPR dépend fortement de la qualité des bases de données, des bases de données expérimentales ont été consolidées, en particulier pour la chaleur et la température de décomposition des peroxydes organiques. Finalement, des modèles QSPR existants ont été testés et de nouveaux modèles ont été développés

Prediction of physico-chemical properties in the context of the French PREDIMOL project

The new EU regulation REACH requires the evaluation of the physico-chemical properties of a large number of substances in order to allow their use before 2018. Taking into account the number of substances and properties, the timing, the economic costs, the feasibility at the R&D level and the risks for the manipulator, in particular for the characterization of the dangerous physico-chemical properties (explosibility, flammability), the experimental measurement of all the data is not realistic. Thus, the development of alternative predictive methods for the evaluation of the properties of substances was recommended in the framework of REACH. In this context, the French PREDIMOL (molecular modeling prediction of physico-chemical properties of products) project [1] funded by ANR (National Research Agency) has started in November 2010 for 3 years. This project is conducted by INERIS associated with several public and private partners. Its objective is to demonstrate that molecular modeling is a credible alternative method to experimental characterization to predict in a reliable and fast manner, the whole range of physico-chemical properties of substances required by EU-REACH's regulation (annexes VII and IX) and for the industry in terms of property-screening method. In a first step, the project is focused on the prediction of physico-chemical properties related to organic peroxides, amines and halogenated compounds. In a second phase of the project, high throughout predictions will be considered. More precisely, predictive and validated QSPR (Quantitative Structure-Property Relationship) models related in particular to hazardous properties (like explosibility) are developed whereas molecular simulation methods (Molecular Dynamics, Monte Carlo) are used or adapted for thermo-physical properties like viscosity or density. Another critical objective of this project is the regulatory validation of models by European chemical instances in order that predictive data could be used for registration of chemicals in REACH. Hence, they will be submitted to the JRC comity for acceptance or to existing tools (like QSAR toolbox) for integration. In 2011, existing group contribution methods, QSPR models notably associated with quantum chemical description of molecular structures, SAFT equations, COSMO-RS approach and force fields that could be used for the prediction of the properties of the compounds under concerned have been identified, stressing onto performances and limits of each approach. Inventory of existing experimental data from literature has also been established. As predictivity of QSPR models highly depends on the database pertinence in terms of number of data, coherence and uncertainties of measurements, reliable experimental databases have been consolidated, in particular for the enthalpy of decomposition of organic peroxides

Author Correction:Benchmark maps of 33 years of secondary forest age for Brazil (Scientific Data, (2020), 7, 1, (269), 10.1038/s41597-020-00600-4)

Following publication of this Data Descriptor it was found that the affiliation, Programa de Pós-graduação em Agroecologia, Universidade Estadual do Maranhão (UEMA), São Luís, Brazil was spelled incorrectly. This has now been corrected in both the HTML and PDF versions.</p