The potential of marginal coastal nursery habitats for the conservation of a culturally important Caribbean marine species

Aim: Identifying the potential of marginal habitats for species conservation is of key importance when their core high-quality habitats are under substantial disturbances and threats. However, there is currently a knowledge gap on how useful marine marginal habitats may be for conserving endangered marine species. Here, we investigate the potential of groundwater-fed coastal areas for the conservation of the queen conch, an economically and culturally important marine gastropod. Location: The inlet of Xel-Ha, typical of groundwater-fed coastal areas widely distributed along the Yucatan Peninsula coast in Mexico and partially protected by a network of marine protected areas. Methods: We tracked 66 queen conchs (Lobatus gigas) using acoustic telemetry over a period of 3.5 years. We investigated for ontogenetic niche shift using a network analysis and by modelling their growth. Results: The queen conchs exhibited the same ontogenetic niche shift required to complete their life cycle in this marginal habitat as they do in offshore core habitats. A total of 33 individuals departed the inlet and migrated from shallow groundwater-affected nursery grounds to deeper marine habitats more suitable for breeding aggregation. Main conclusions: As the broad-scale movement behaviour of queen conch in this inlet is similar to that observed on the overfished core habitats, our findings suggest that groundwater-fed coastal areas should be included in conservation planning for an effective management of this species within a network of marine protected areas

High Prevalence of Mycoplasma pneumoniae and Chlamydia pneumoniae in Children with Acute Respiratory Infections from Lima, Peru

Background Mycoplasma pneumoniae and Chlamydia pneumoniae are atypical pathogens responsible for pneumonia and a leading cause of morbidity and mortality in low income countries. The study objective is to determine the prevalence of this pathogens in Peruvian children with acute respiratory infections. Methods A consecutive cross-sectional study was conducted in Lima, Peru from May 2009 to September 2010. A total of 675 children admitted with clinical diagnoses of acute respiratory infections were tested for Mycoplasma pneumoniae and Chlamydia pneumoniae detection by polymerase chain reaction (PCR), and clinical symptoms were registered by the attending physician. Results Mycoplasma pneumonia was detected in 25.19% (170/675) of nasopharyngeal samples and Chlamydia pneumonia in 10.52% (71/675). The most common symptoms in patients with these atypical pathogens were rhinorrhea, cough and fever. A higher prevalence of Mycoplasma pneumoniae cases were registered in summer, between December 2009 and March 2010. Conclusions Mycoplasma pneumoniae and Chlamydia pneumonia are a significant cause of morbidity in Peruvian children with acute respiratory infections (ARI). Further studies should evaluate the use of reliable techniques such as PCR in Peru in order to avoid underdiagnoses of these atypical pathogens

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Valorisation of Biowastes for the Production of Green Materials Using Chemical Methods

With crude oil reserves dwindling, the hunt for a sustainable alternative feedstock for fuels and materials for our society continues to expand. The biorefinery concept has enjoyed both a surge in popularity and also vocal opposition to the idea of diverting food-grade land and crops for this purpose. The idea of using the inevitable wastes arising from biomass processing, particularly farming and food production, is, therefore, gaining more attention as the feedstock for the biorefinery. For the three main components of biomass—carbohydrates, lipids, and proteins—there are long-established processes for using some of these by-products. However, the recent advances in chemical technologies are expanding both the feedstocks available for processing and the products that be obtained. Herein, this review presents some of the more recent developments in processing these molecules for green materials, as well as case studies that bring these technologies and materials together into final products for applied usage

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost