Land use intensification increasingly drives the spatiotemporal patterns of the global human appropriation of net primary production in the last century

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primary production (HANPP) to quantify and map land-use-induced alterations of the carbon flows in ecosystems. We find that, while at the global aggregate level HANPP growth slowed down during the century, the spatial dynamics of changes in HANPP were increasing, with the highest change rates observed in the most recent past. Across all biomes, the importance of changes in land-use areas has declined, with the exception of the tropical biomes. In contrast, increases in land-use intensity became the most important driver of HANPP across all biomes and settings. We conducted uncertainty analyses by modulating input data and assumptions, which indicate that the spatial patterns of land use and potential net primary production are the most critical factors, while spatial allocation rules and uncertainties in overall harvest values play a smaller role. Highlighting the increasing role of land-use intensity compared to changes in the areal extent of land uses, our study supports calls for better integration of the intensity dimension into global analyses and models. On top of that, we provide important empirical input for further analyses of the sustainability of the global land system.     

New players in the field: Ecology and biocontrol potential of three species of mollusc-parasitic nematodes of the genus Phasmarhabditis

BioControl - Nematodes of the genus Phasmarhabditis are facultative parasites of molluscs with a world-wide distribution but, so far, only one species P. hermaphrodita has been thoroughly studied...     

The tails of two invasive species: genetic responses to acute and chronic bottlenecks

Biological Invasions - Genetic diversity can affect population viability and can be reduced by both acute and chronic mechanisms. Using the history of the establishment and management of two...     

Is reduced ferredoxin the physiological electron donor for MetVF-type methylenetetrahydrofolate reductases in acetogenesis? A hypothesis

International Microbiology - The methylene-tetrahydrofolate reductase (MTHFR) is a key enzyme in acetogenic CO2 fixation. The MetVF-type enzyme has been purified from four different species and the...     

The origin and future of an endangered crater lake endemic; phylogeography and ecology of Oreochromis hunteri and its invasive relatives

Hydrobiologia - Cichlids of the genus Oreochromis (“Tilapias”) are intensively used in aquaculture around the world. In many cases, when “Tilapia” were introduced for...     

Studies of membranotropic and fusogenic activity of two putative HCV fusion peptides

Over the past decades, membranotropic peptides such as positively charged cell-penetrating peptides (CPPs) or amphipathic antimicrobial peptides (AMPs) have received increasing interest in order to improve therapeutic agent cellular uptake.As far as we are concerned, we were interested in studying HCV fusion peptides as putative anchors. Two peptides, HCV6 and HCV7, were identified and conjugated to a fluorescent tag NBD and tested for their interaction with liposomes as model membranes. DSC and spectrofluorescence analyses demonstrate HCV7 propensity to insert or internalize in vesicles containing anionic lipids DMPG whereas no activity was observed with zwitterionic DMPC. This behavior could be explained by the peptide sequence containing a cationic arginine residue. On the contrary, HCV6 did not exhibit any membranotropic activity but was the only sequence able to induce liposomes' fusion or aggregation monitored by spectrofluorescence and DLS. This two peptides mild activity was related to their inefficient structuration in contact with membrane mimetics, which was demonstrated by CD and NMR experiments.Altogether, our data allowed us to identify two promising membrane-active peptides from E1 and E2 HCV viral proteins, one fusogenic (HCV6) and the other membranotropic (HCV7). The latter was also confirmed by fluorescence microscopy with CHO cells, indicating that HCV7 could cross the plasma membrane via an endocytosis process. Therefore, this study provides new evidences supporting the identification of HCV6 as the HCV fusion peptide as well as insights on a novel membranotropic peptide from the HCV-E2 viral protein.     

A field portable method for the semi‐quantitative estimation of dehydration tolerance of photosynthetic tissues across distantly related land plants

Desiccation tolerant (DT) plants withstand complete cellular dehydration, reaching relative water contents (RWC) below 30% in their photosynthetic tissues. Desiccation sensitive (DS) plants exhibit different degrees of dehydration tolerance (DHT), never surviving water loss >70%. To date, no procedure for the quantitative evaluation of DHT extent exists that is able to discriminate DS species with differing degrees of DHT from truly DT plants. We developed a simple, feasible and portable protocol to differentiate between DT and different degrees of DHT in the photosynthetic tissues of seed plants and between fast desiccation (< 24 h) tolerant (FDT) and sensitive (FDS) bryophytes. The protocol is based on (1) controlled desiccation inside Falcon tubes equilibrated at three different relative humidities that, consequently, induce three different speeds and extents of dehydration and (2) an evaluation of the average percentage of maximal photochemical efficiency of PSII (F_v/fm) recovery after rehydration. Applying the method to 10 bryophytes and 28 tracheophytes from various locations, we found that (1) imbibition of absorbent material with concentrated salt‐solutions inside the tubes provides stable relative humidity and avoids direct contact with samples; (2) for 50 ml capacity tubes, the optimal plant amount is 50–200 mg fresh weight; (3) the method is useful in remote locations due to minimal instrumental requirements; and (4) a threshold of 30% recovery of the initial F_v/fm upon reaching RWC ≤ 30% correctly categorises DT species, with three exceptions: two poikilochlorophyllous species and one gymnosperm. The protocol provides a semi‐quantitative expression of DHT that facilitates comparisons of species with different morpho‐physiological traits and/or ecological attributes.     

BaSIQS - basic scale on insomnia complaints and quality of sleep: reliability,norms, validity,and accuracy studies,based on clinical and community samples

This research focused on the Basic Scale on Insomnia Symptoms and Quality of Sleep (BaSIQS), formerly validated in undergraduates using the Pittsburgh Sleep Quality Index (PSQI), and aimed to expand internal consistency analysis, examine thoroughly its validity, and determine its clinical accuracy. Considering objective and subjective measures, recruiting non-clinical and clinical samples, this research implemented a comprehensive approach to examine convergent and discriminant validity, confirmatory factor analyses, and the BaSIQS sensitivity and specificity. The BaSIQS was filled out along with the Insomnia Severity Index (ISI), questions on sleep-wake schedules, Composite Scale of Morningness (CSM) and Brief Symptom Inventory-18 (BSI-18) by 1198 adults, 18–64 years old, plus another 30 who wore actimeters, recruited in community settings. A clinical group of 30 chronic insomnia disorder patients also participated. Cronbach alpha coefficient was 0.80. A two-factor structure was confirmed. The association between BaSIQS and ISI was large, whereas actigraphy correlations were medium or small. Medium to non-significant correlations were found concerning conceptually different self-report measures. Comparing the clinic and control groups, the former showed poorer sleep, with a large effect size. Receiver operating characteristic analysis revealed an area under curve = 0.9, and an optimal cut-off score >15. In conclusion, results on reliability, validity, and accuracy provide support to the utility of the BaSIQS both in community and clinical settings, for research and practical purposes.     

Vaccination with SARS-CoV-2 variants of concern protects mice from challenge with wild-type virus

Vaccines against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have been highly efficient in protecting against Coronavirus Disease 2019 (COVID-19). However, the emergence of viral variants that are more transmissible and, in some cases, escape from neutralizing antibody responses has raised concerns. Here, we evaluated recombinant protein spike antigens derived from wild-type SARS-CoV-2 and from variants B.1.1.7, B.1.351, and P.1 for their immunogenicity and protective effect in vivo against challenge with wild-type SARS-CoV-2 in the mouse model. All proteins induced high neutralizing antibodies against the respective viruses but also induced high cross-neutralizing antibody responses. The decline in neutralizing titers between variants was moderate, with B.1.1.7-vaccinated animals having a maximum fold reduction of 4.8 against B.1.351 virus. P.1 induced the most cross-reactive antibody responses but was also the least immunogenic in terms of homologous neutralization titers. However, all antigens protected from challenge with wild-type SARS-CoV-2 in a mouse model.

This study explores the immune response induced by wild type and variant SARS-CoV-2 spike proteins, and the protection that these immune responses provide against challenge with wild type virus in the mouse model.     

Predicting dengue incidence leveraging internet-based data sources. A case study in 20 cities in Brazil

The dengue virus affects millions of people every year worldwide, causing large epidemic outbreaks that disrupt people’s lives and severely strain healthcare systems. In the absence of a reliable vaccine against dengue or an effective treatment to manage the illness in humans, most efforts to combat dengue infections have focused on preventing its vectors, mainly the Aedes aegypti mosquito, from flourishing across the world. These mosquito-control strategies need reliable disease activity surveillance systems to be deployed. Despite significant efforts to estimate dengue incidence using a variety of data sources and methods, little work has been done to understand the relative contribution of the different data sources to improved prediction. Additionally, scholarship on the topic had initially focused on prediction systems at the national- and state-levels, and much remains to be done at the finer spatial resolutions at which health policy interventions often occur. We develop a methodological framework to assess and compare dengue incidence estimates at the city level, and evaluate the performance of a collection of models on 20 different cities in Brazil. The data sources we use towards this end are weekly incidence counts from prior years (seasonal autoregressive terms), weekly-aggregated weather variables, and real-time internet search data. We find that both random forest-based models and LASSO regression-based models effectively leverage these multiple data sources to produce accurate predictions, and that while the performance between them is comparable on average, the former method produces fewer extreme outliers, and can thus be considered more robust. For real-time predictions that assume long delays (6–8 weeks) in the availability of epidemiological data, we find that real-time internet search data are the strongest predictors of dengue incidence, whereas for predictions that assume short delays (1–3 weeks), in which the error rate is halved (as measured by relative RMSE), short-term and seasonal autocorrelation are the dominant predictors. Despite the difficulties inherent to city-level prediction, our framework achieves meaningful and actionable estimates across cities with different demographic, geographic and epidemic characteristics.