Bacterial communities of the marine sponges Hymeniacidon heliophila and Polymastia janeirensis and their environment in Rio de Janeiro, Brazil

In this study we performed a survey of the bacterial communities associated with the Western Atlantic demosponges Hymeniacidon heliophila and Polymastia janeirensis, based on 16S rRNA sequencing and transmission electron microscopy (TEM). We compared diversity and composition of the sponge-associated bacteria to those of environmental bacteria, represented by free-living bacterioplankton and by bacteria attached to organic particulate matter in superficial sediments. Partial bacterial 16S rRNA sequences from seawater, sediment, and sponges were retrieved by PCR, cloning, and sequencing. Sequences were subjected to rarefaction analyses, phylogenetic tree construction, and LIBSHUFF quantitative statistics to verify coverage and similarity between libraries. Community structure of the free-living bacterioplankton was phylogenetically different from that of the sponge-associated bacterial assemblages. On the other hand, some sediment-attached bacteria were also found in the sponge bacterial community, indicating that sponges may incorporate bacteria together with sediment particles. Rare and few prokaryotic morphotypes were found in TEM analyses of sponge mesohyl matrix of both species. Molecular data indicate that bacterial richness and diversity decreases from bacterioplankton, to particulate organic sediment, and to H. heliophila and P. janeirensis. Sponges from Rio de Janeiro harbor a pool of novel and exclusive sponge-associated bacterial taxa. Sponge-associated bacterial communities are composed of both taxons shared by many sponge groups and by species-specific bacteria.     

Evaluating global interest in biodiversity and conservation

The first target of the Convention for Biological Diversity (Aichi target 1) was to increase public awareness of the values of biodiversity and actions needed to conserve it—a key prerequisite for other conservation targets. Monitoring success in achieving this target at a global scale has been difficult; however, increased digitization of human life in recent decades has made it easier to measure people's interests at an unprecedented scale and allows for a more comprehensive evaluation of Aichi target 1 than previously attempted. We used Google search volume data for over a thousand search terms related to different aspects of biodiversity and conservation to evaluate global interest in biodiversity and its conservation. We also investigated the correlation of interest in biodiversity and conservation across countries to variables related to biodiversity, economy, demography, research, education, internet use, and presence of environmental organizations. From 2013 to 2020, global searches for biodiversity components increased, driven mostly by searches for charismatic fauna (59% of searches were for mammal species). Searches for conservation actions, driven mostly by searches for national parks, decreased since 2019, likely due to the COVID-19 pandemic. Economic inequality was negatively correlated with interest in biodiversity and conservation, whereas purchasing power was indirectly positively correlated with higher levels of education and research. Our results suggest partial success toward achieving Aichi target 1 in that interest in biodiversity increased widely, but not for conservation. We suggest that increased outreach and education efforts aimed at neglected aspects of biodiversity and conservation are still needed. Popular topics in biodiversity and conservation could be leveraged to increase awareness of other topics with attention to local socioeconomic contexts.     

Sustainable red ceramic block: recycling of a sewage sludge as raw material

Journal of Material Cycles and Waste Management - Sewage sludge (SS) is a residue resulting from wastewater treatment, which is widely increasing due to population growth and economic development....     

A simple spectroscopic method to determine dimethoate in water samples by complex formation

Abstract

A simple and rapid method for the determination of dimethoate in water was developed based on the monitoring of the complex formation between bis 5-phenyldipyrrinate of nickel (II) and the herbicide dimethoate. The method showed a short response time (10?s), high selectivity (very low interference from other sulfate and salts), high sensitivity (limit of detection (LOD) 0.45?µM, limit of quantitation (LOQ) of 1.39?µM), and a K_d of 2.4?µM. Stoichiometry experiments showed that complex formation occurred with a 1:1 relation. The method was applied to different environmental water samples such as lagoon, stream, urban, and groundwater samples. The results indicated that independently from the water source, the method exhibited high precision (0.25–2.47% variation coefficient) and accuracy (84.42–115.68% recovery). In addition, the method was also tested using an effluent from a wastewater treatment plant from Mexico; however, the results indicated that the presence of organic matter had a pronounced effect on the detection.     

Activity of nucleoside triphosphate diphosphohydrolase, 5′-nucleotidase,and adenosine deaminase in cattle fed on pastures treated with different nitrogen fertilizers

The aim of this study was to evaluate nucleoside triphosphate diphosphohydrolase, 5′-nucleotidase, and adenosine deaminase activities in cattle fed on cuttings from pastures fertilized with urea compared to animals fed on cuttings from organically fertilized or from non-fertilized pastures. Blood samples were collected up to 9 h after feeding, and nitrite and enzyme activities were evaluated. The animals feeding on urea-fertilized pasture suffered subclinical intoxication. Serum nitrite levels increased by about 50% and adenosine deaminase activity increased almost sixfold 4 and 6 h after feeding on urea-fertilized pasture, and adenosine deaminase in platelets almost doubled 6 and 9 h after feeding. In platelets, nucleoside triphosphate diphosphohydrolase activity with adenosine triphosphate as substrate increased 2, 4, 6 and 9 h after feeding while nucleoside triphosphate diphosphohydrolase with adenosine diphosphate as substrate and 5′-nucleotidase activities increased only 9 h after feeding. Increased activities of these enzymes may be implicated in the pathophysiology of subclinical intoxication since they are involved in many biochemical functions.     

Using machine learning to disentangle homonyms in large text corpora

Systematic reviews are an increasingly popular decision‐making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine‐learning methods to handle and screen big data for relevant information in conservation science.     

Soil carbon stock estimations: methods and a case study of the Maranhão State,Brazil

Environment, Development and Sustainability - Soils feature significant variations in soil carbon stocks through land-use changes, management practices, and intrinsic characteristics. The aim of...     

Metal- and metal/oxide-based engineered nanoparticles and nanostructures: a review on the applications,nanotoxicological effects,and risk control strategies

Environmental Science and Pollution Research - The production and demand of nanoparticles in the manufacturing sector and personal care products, release a large number of engineered nanoparticles...     

Electrochemical treatment of penicillin,cephalosporin, and fluoroquinolone antibiotics via active chlorine: evaluation of antimicrobial activity,toxicity, matrix,and their correlation with the degradation pathways

Environmental Science and Pollution Research - Antibiotics are pharmaceuticals widely consumed and frequently detected in environmental water, where they can induce toxic effects and development of...