Thermoregulatory traits combine with range shifts to alter the future of montane ant assemblages

Predicting and understanding the biological response to future climate change is a pressing challenge for humanity. In the 21st century, many species will move into higher latitudes and higher elevations as the climate warms. In addition, the relative abundances of species within local assemblages are likely to change. Both effects have implications for how ecosystems function. Few biodiversity forecasts, however, take account of both shifting ranges and changing abundances. We provide a novel analysis predicting the potential changes to assemblage‐level relative abundances in the 21st century. We use an established relationship linking ant abundance and their colour and size traits to temperature and UV‐B to predict future abundance changes. We also predict future temperature driven range shifts and use these to alter the available species pool for our trait‐mediated abundance predictions. We do this across three continents under a low greenhouse gas emissions scenario (RCP2.6) and a business‐as‐usual scenario (RCP8.5). Under RCP2.6, predicted changes to ant assemblages by 2100 are moderate. On average, species richness will increase by 26%, while species composition and relative abundance structure will be 26% and 30% different, respectively, compared with modern assemblages. Under RCP8.5, however, highland assemblages face almost a tripling of species richness and compositional and relative abundance changes of 66% and 77%. Critically, we predict that future assemblages could be reorganized in terms of which species are common and which are rare: future highland assemblages will not simply comprise upslope shifts of modern lowland assemblages. These forecasts reveal the potential for radical change to montane ant assemblages by the end of the 21st century if temperature increases continue. Our results highlight the importance of incorporating trait–environment relationships into future biodiversity predictions. Looking forward, the major challenge is to understand how ecosystem processes will respond to compositional and relative abundance changes.     

Bioenergy and climate change mitigation: an assessment

Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land‐use and energy experts, land‐use and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life‐cycle assessment experts. We summarize technological options, outline the state‐of‐the‐art knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end‐use efficiency, improved land carbon‐stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small‐scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100 EJ: high agreement; 100–300 EJ: medium agreement; above 300 EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245 EJ yr^?1 to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large‐scale deployment (>200 EJ), together with BECCS, could help to keep global warming below 2° degrees of preindustrial levels; but such high deployment of land‐intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options.     

Seasonal Influenza Vaccination amongst Medical Students: A Social Network Analysis Based on a Cross-Sectional Study

Introduction

The Chief Medical Officer for England recommends that healthcare workers have a seasonal influenza vaccination in an attempt to protect both patients and NHS staff. Despite this, many healthcare workers do not have a seasonal influenza vaccination. Social network analysis is a well-established research approach that looks at individuals in the context of their social connections. We examine the effects of social networks on influenza vaccination decision and disease dynamics.

Methods

We used a social network analysis approach to look at vaccination distribution within the network of the Lancaster Medical School students and combined these data with the students’ beliefs about vaccination behaviours. We then developed a model which simulated influenza outbreaks to study the effects of preferentially vaccinating individuals within this network.

Results

Of the 253 eligible students, 217 (86%) provided relational data, and 65% of responders had received a seasonal influenza vaccination. Students who were vaccinated were more likely to think other medical students were vaccinated. However, there was no clustering of vaccinated individuals within the medical student social network. The influenza simulation model demonstrated that vaccination of well-connected individuals may have a disproportional effect on disease dynamics.

Conclusions

This medical student population exhibited vaccination coverage levels similar to those seen in other healthcare groups but below recommendations. However, in this population, a lack of vaccination clustering might provide natural protection from influenza outbreaks. An individual student’s perception of the vaccination coverage amongst their peers appears to correlate with their own decision to vaccinate, but the directionality of this relationship is not clear. When looking at the spread of disease within a population it is important to include social structures alongside vaccination data. Social networks influence disease epidemiology and vaccination campaigns designed with information from social networks could be a future target for policy makers.     

Determination of Foraging Thresholds and Effects of Application on Energetic Carrying Capacity for Waterfowl

Energetic carrying capacity of habitats for wildlife is a fundamental concept used to better understand population ecology and prioritize conservation efforts. However, carrying capacity can be difficult to estimate accurately and simplified models often depend on many assumptions and few estimated parameters. We demonstrate the complex nature of parameterizing energetic carrying capacity models and use an experimental approach to describe a necessary parameter, a foraging threshold (i.e., density of food at which animals no longer can efficiently forage and acquire energy), for a guild of migratory birds. We created foraging patches with different fixed prey densities and monitored the numerical and behavioral responses of waterfowl (Anatidae) and depletion of foods during winter. Dabbling ducks (Anatini) fed extensively in plots and all initial densities of supplemented seed were rapidly reduced to 10 kg/ha and other natural seeds and tubers combined to 170 kg/ha, despite different starting densities. However, ducks did not abandon or stop foraging in wetlands when seed reduction ceased approximately two weeks into the winter-long experiment nor did they consistently distribute according to ideal-free predictions during this period. Dabbling duck use of experimental plots was not related to initial seed density, and residual seed and tuber densities varied among plant taxa and wetlands but not plots. Herein, we reached several conclusions: 1) foraging effort and numerical responses of dabbling ducks in winter were likely influenced by factors other than total food densities (e.g., predation risk, opportunity costs, forager condition), 2) foraging thresholds may vary among foraging locations, and 3) the numerical response of dabbling ducks may be an inconsistent predictor of habitat quality relative to seed and tuber density. We describe implications on habitat conservation objectives of using different foraging thresholds in energetic carrying capacity models and suggest scientists reevaluate assumptions of these models used to guide habitat conservation.     

Host inbreeding increases susceptibility to ectoparasitism

Inbreeding, which increases homozygosity throughout the genome by increasing the proportion of alleles that are identical by descent, is expected to compromise resistance against parasitism. Here, we demonstrate that host inbreeding increases susceptibility to ectoparasitism in a natural fruit fly (Drosophila nigrospiracula) - mite (Macrocheles subbadius) association, and that this effect depends on host genetic background. Moreover, flies generated from reciprocal crosses between susceptible inbred lines exhibited elevated levels of resistance similar to that in the mass-bred base population, confirming in reverse direction the causative link between expected heterozygosity and resistance. We also show that inbreeding reduces the host's ability to sustain energetically expensive behaviours, and that host exhaustion dramatically increases susceptibility. These findings suggest that inbreeding depression for resistance results from an inability to sustain defensive behaviours because of compromised physiological competence.     

From coarse-grain to all-atom: toward multiscale analysis of protein landscapes

Multiscale methods are becoming increasingly promising as a way to characterize the dynamics of large protein systems on biologically relevant time-scales. The underlying assumption in multiscale simulations is that it is possible to move reliably between different resolutions. We present a method that efficiently generates realistic all-atom protein structures starting from the C(alpha) atom positions, as obtained for instance from extensive coarse-grain simulations. The method, a reconstruction algorithm for coarse-grain structures (RACOGS), is validated by reconstructing ensembles of coarse-grain structures obtained during folding simulations of the proteins src-SH3 and S6. The results show that RACOGS consistently produces low energy, all-atom structures. A comparison of the free energy landscapes calculated using the coarse-grain structures versus the all-atom structures shows good correspondence and little distortion in the protein folding landscape.     

Crystal structures of two novel dye-decolorizing peroxidases reveal a beta-barrel fold with a conserved heme-binding motif

BtDyP from Bacteroides thetaiotaomicron (strain VPI-5482) and TyrA from Shewanella oneidensis are dye-decolorizing peroxidases (DyPs), members of a new family of heme-dependent peroxidases recently identified in fungi and bacteria. Here, we report the crystal structures of BtDyP and TyrA at 1.6 and 2.7 A, respectively. BtDyP assembles into a hexamer, while TyrA assembles into a dimer; the dimerization interface is conserved between the two proteins. Each monomer exhibits a two-domain, alpha+beta ferredoxin-like fold. A site for heme binding was identified computationally, and modeling of a heme into the proposed active site allowed for identification of residues likely to be functionally important. Structural and sequence comparisons with other DyPs demonstrate a conservation of putative heme-binding residues, including an absolutely conserved histidine. Isothermal titration calorimetry experiments confirm heme binding, but with a stoichiometry of 0.3:1 (heme:protein).