Is Labor Green?

In this article, we assess whether unionization of national workforces influences growth in national carbon dioxide (CO2) emissions per capita. Political-economic theories in environmental sociology propose that labor unions have the potential to affect environmental conditions. Yet, few studies have quantitatively assessed the influence of unionization on environmental outcomes using cross-national data. We estimate multilevel regression models using data on OECD member nations from 1970 to 2014. Results from our analysis indicate that unionization, measured as the percentage of workers who are union members, is negatively associated with CO2 emissions per capita, even when controlling for labor conditions. This finding suggests that unionization may promote environmental protection at the national level

Is Labor Green? A Cross-National Panel Analysis of Unionization and Carbon Dioxide Emissions

In this article, we assess whether unionization of national workforces influences growth in national carbon dioxide (CO2) emissions per capita. Political-economic theories in environmental sociology propose that labor unions have the potential to affect environmental conditions. Yet, few studies have quantitatively assessed the influence of unionization on environmental outcomes using cross-national data. We estimate multilevel regression models using data on OECD member nations from 1970 to 2014. Results from our analysis indicate that unionization, measured as the percentage of workers who are union members, is negatively associated with CO2 emissions per capita, even when controlling for labor conditions. This finding suggests that unionization may promote environmental protection at the national level

MOESM1 of Lignolytic-consortium omics analyses reveal novel genomes and pathways involved in lignin modification and valorization

Additional file 1: Table S1. Compounds identified by gas chromatography–mass spectrometry (GC-MS) in the lignin-waste stream used for establishment of the lignin-degrading microbial community (LigMet). Table S2. Sequencing statistics and data processing of amplicon libraries constructed for profiling LigMet and soil samples analyzed. Table S3. Diversity and richness indices of the LigMet and soil samples based on 16S rRNA and ITS2 region sequences. Table S4. Protozoa identified in LigMet based on 18S rRNA sequencing. Table S5. Assembly statistics from draft genomes recovered from LigMet (all assemblies). Table S6. Genome statistics of Paenarthrobacter sp. str. HW13. Figure S1. Microbial growth was monitored by OD 600 nm, observing exponential growing during the first 40 hours of consortium growth. The consumption of reducing sugars over time as monitored by DNS, the exponential phase was completed after the first 40 hours of growth when monitoring sugar consumption. Figure S2. Rarefaction curves based on targeted sequencing of 16S rRNA gene amplicons derived from the LigMet (A) and sugarcane soil (B) samples. The rarefaction curves of each biological replicate are shown in different colors. Figure S3. Rarefaction curves based on targeted sequencing of the ITS2 region derived from the LigMet sample. The rarefaction curves of each biological replicate are shown in different colors. Figure S4. The taxonomic profiles from LigMet and sugarcane soil samples at the class level based on 16S rRNA gene amplicon. The respective relative abundances of each biological replicate for LigMet and sugarcane soil are shown. Figure S5. The archaeal phylum abundance in LigMet and sugarcane soil sample. The relative abundance is shown in percentage for each biological replicate of the LigMet and sugacarcane soil. Figure S6. Metabolic pathways related to aromatic compound degradation identified in LigMet according to KEGG automatic annotation. Figure S7. Classification of the predicted proteins from the LigMet according to the dbCAN database. Figure S8. Predicted auxiliary activity (AA) and carbohydrate esterase (CE) families from LigMet and draft genomes, based on the dbCAN database. AA and CE families are related to peroxidase activity and break down of lignin ester cross links, respectively. Figure S9. Phylogenetic relationship of the strain HW13 relative to the most closely related strains of the genus Paenarthrobacter. EzBioCloud webserver was used to perform a similarity-based search of HW13 16S rRNA to retrieve the most closely related sequences. The resulting 16S rRNA sequences were aligned using the MAFFT v7.299b software. A phylogenetic tree was inferred using the maximum likelihood method implemented in RAxML v8.2.0, evolutionary distances were based on the GTRGAMMAI model, inferred as the best model by jModelTest2. Numbers at the nodes are percentages of bootstrap values obtained by repeating the analysis 1,000 times. The type strains are marked with a superscript ‘T’. Accession numbers are shown in parentheses. Figure S10. Phylogenetic relationships among feruloyl-CoA synthetase (upper) and Enoyl-CoA hydratase/aldolase. The phylogenetic tree was generated using amino acid sequences retrieved from NCBI and Uniprot database. The sequences were aligned using MAFFT v7.299b software [5]. The phylogenetic tree was reconstructed using maximum likelihood method implemented in RAxML v8.2.0 [6], evolutionary distances were based on the GTRGAMMAI model, inferred as the best model by jModelTest2 [7]. The bootstrap values (1,000 replicate runs, shown as %) higher than 70 % are represented. Accession numbers are listed in parentheses. The FerA_B3 and FerB_B11 amino acid sequence retrieved from LigMet data set is printed in bold

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data