Fitness,risk taking,and spatial behavior covary with boldness in experimental vole populations

Individuals of a population may vary along a pace‐of‐life syndrome from highly fecund, short‐lived, bold, dispersive “fast” types at one end of the spectrum to less fecund, long‐lived, shy, plastic “slow” types at the other end. Risk‐taking behavior might mediate the underlying life history trade‐off, but empirical evidence supporting this hypothesis is still ambiguous. Using experimentally created populations of common voles (Microtus arvalis)—a species with distinct seasonal life history trajectories—we aimed to test whether individual differences in boldness behavior covary with risk taking, space use, and fitness. We quantified risk taking, space use (via automated tracking), survival, and reproductive success (via genetic parentage analysis) in 8 to 14 experimental, mixed‐sex populations of 113 common voles of known boldness type in large grassland enclosures over a significant part of their adult life span and two reproductive events. Populations were assorted to contain extreme boldness types (bold or shy) of both sexes. Bolder individuals took more risks than shyer ones, which did not affect survival. Bolder males but not females produced more offspring than shy conspecifics. Daily home range and core area sizes, based on 95% and 50% Kernel density estimates (20 ± 10 per individual, n = 54 individuals), were highly repeatable over time. Individual space use unfolded differently for sex‐boldness type combinations over the course of the experiment. While day ranges decreased for shy females, they increased for bold females and all males. Space use trajectories may, hence, indicate differences in coping styles when confronted with a novel social and physical environment. Thus, interindividual differences in boldness predict risk taking under near‐natural conditions and have consequences for fitness in males, which have a higher reproductive potential than females. Given extreme inter‐ and intra‐annual fluctuations in population density in the study species and its short life span, density‐dependent fluctuating selection operating differently on the sexes might maintain (co)variation in boldness, risk taking, and pace‐of‐life.     

Combining industrial ecology tools to assess potential greenhouse gas reductions of a circular economy: Method development and application to Switzerland

Industrial ecology (IE) methodologies, such as input/output or material flow analysis and life cycle assessment (LCA), are often used for the environmental evaluation of circular economy strategies. Up to now, an approach that utilizes these methods in a systematic, integrated framework for a holistic assessment of a geographic region's sustainable circular economy potential has been lacking. The approach developed in this study (IE4CE approach) combines IE methodologies to determine the environmental impact mitigation potential of circular economy strategies for a defined geographic region. The approach foresees five steps. First, input/output analysis helps identify sectors with high environmental impacts. Second, a refined analysis is conducted using material flow and LCA. In step 3, circular strategies are used for scenario design and evaluated in step 4. In step 5, the assessment results are compiled and compared across sectors. The approach was applied to a case study of Switzerland, analyzing 8 sectors and more than 30 scenarios in depth. Carbon capture and storage (CCS) from waste incineration, biogas and cement production, food waste prevention in households, hospitality and production, and the increased recycling of plastics had the highest mitigation potential. Most of the scenarios do not influence each other. One exception is the CCS scenarios: waste avoidance scenarios decrease the reduction potential of CCS. A combination of scenarios from different sectors, including their impact on the CCS scenario potential, led to an environmental impact mitigation potential of 11.9 Mt CO₂-eq for 2050, which equals 14% of Switzerland's current consumption-based impacts.     

Large carbon release legacy from bark beetle outbreaks across Western United States

Warmer conditions over the past two decades have contributed to rapid expansion of bark beetle outbreaks killing millions of trees over a large fraction of western United States (US) forests. These outbreaks reduce plant productivity by killing trees and transfer carbon from live to dead pools where carbon is slowly emitted to the atmosphere via heterotrophic respiration which subsequently feeds back to climate change. Recent studies have begun to examine the local impacts of bark beetle outbreaks in individual stands, but the full regional carbon consequences remain undocumented for the western US. In this study, we quantify the regional carbon impacts of the bark beetle outbreaks taking place in western US forests. The work relies on a combination of postdisturbance forest regrowth trajectories derived from forest inventory data and a process‐based carbon cycle model tracking decomposition, as well as aerial detection survey (ADS) data documenting the regional extent and severity of recent outbreaks. We find that biomass killed by bark beetle attacks across beetle‐affected areas in western US forests from 2000 to 2009 ranges from 5 to 15 Tg C yr^?1 and caused a reduction of net ecosystem productivity (NEP) of about 6.1–9.3 Tg C y^?1 by 2009. Uncertainties result largely from a lack of detailed surveys of the extent and severity of outbreaks, calling out a need for improved characterization across western US forests. The carbon flux legacy of 2000–2009 outbreaks will continue decades into the future (e.g., 2040–2060) as committed emissions from heterotrophic respiration of beetle‐killed biomass are balanced by forest regrowth and accumulation.     

Widespread supplementary feeding in domestic gardens explains the return of reintroduced Red Kites Milvus milvus to an urban area

Reintroductions are commonly used to mitigate biodiversity loss. One prominent example is that of the Red Kite Milvus milvus, a charismatic raptor of conservation concern. This species has been reintroduced across the UK over the last 25 years following its near extinction after centuries of persecution. The species was not expected to recolonize urban areas; its historical association with human settlements is attributed to scavenging on human waste and refuse, a resource now greatly reduced on the streets of modern European cities. However, the species has become a common daytime visitor to a large conurbation centred on the town of Reading, southern England, approximately 20 km from the first English reintroduction site. Given a near‐absence of breeding and roost sites, we investigated foraging opportunities and habitat associations that might explain use by Red Kites of this urban area. Surveys of discarded human foods and road‐kill suggested that these could support at most 13–29 Kites per day. Face‐to‐face surveys of a cross‐section of residents revealed that 4.5% (equivalent to 4349 households) provided supplementary food for Red Kites in their gardens. Using estimates of per‐household resource provision from another study, we calculated that this is potentially sufficient to feed 142–320 Kites, a substantial proportion of the total estimated to visit the conurbation each day (between 140 and 440). Road transects found positive associations between Red Kites and residential areas. We suggest that the decision made by thousands of householders to provide supplementary food for Red Kites in their gardens is the primary factor explaining their daytime abundance in this urban area.     

Systematic Review and Meta-Analysis of Response Rates and Diagnostic Yield of Screening for Type 2 Diabetes and Those at High Risk of Diabetes

Background

Screening for type 2 diabetes (T2DM) and individuals at risk of diabetes has been advocated, yet information on the response rate and diagnostic yield of different screening strategies are lacking.

Methods

Studies (from 1998 to March/2015) were identified through Medline, Embase and the Cochrane library and included if they used oral glucose tolerance test (OGTT) and WHO-1998 diagnostic criteria for screening in a community setting. Studies were one-step strategy if participants were invited directly for OGTT and two, three/four step if participants were screened at one or more levels prior to invitation to OGTT. The response rate and diagnostic yield were pooled using Bayesian random-effect meta-analyses.

Findings

47 studies (422754 participants); 29 one-step, 11 two-step and seven three/four-step were identified. Pooled response rate (95% Credible Interval) for invitation to OGTT was 65.5% (53.7, 75.6), 63.1% (44.0, 76.8), and 85.4% (76.4, 93.3) in one, two and three/four-step studies respectively. T2DM yield was 6.6% (5.3, 7.8), 13.1% (4.3, 30.9) and 27.9% (8.6, 66.3) for one, two and three/four-step strategies respectively. The number needed to invite to the OGTT to detect one case of T2DM was 15, 7.6 and 3.6 in one, two, and three/four-step strategies. In two step strategies, there was no difference between the response or yield rates whether the first step was blood test or risk-score. There was evidence of substantial heterogeneity in rates across study populations but this was not explained by the method of invitation, study location (rural versus urban) and developmental index of the country in which the study was performed.

Conclusions

Irrespective of the invitation method, developmental status of the countries and or rural/urban location, using a multi-step strategy increases the initial response rate to the invitation to screening for diabetes and reduces the number needed to have the final diagnostic test (OGTT in this study) for a definite diagnosis.     

RTTN Mutations Cause Primary Microcephaly and Primordial Dwarfism in Humans

Primary microcephaly is a developmental brain anomaly that results from defective proliferation of neuroprogenitors in the germinal periventricular zone. More than a dozen genes are known to be mutated in autosomal-recessive primary microcephaly in isolation or in association with a more generalized growth deficiency (microcephalic primordial dwarfism), but the genetic heterogeneity is probably more extensive. In a research protocol involving autozygome mapping and exome sequencing, we recruited a multiplex consanguineous family who is affected by severe microcephalic primordial dwarfism and tested negative on clinical exome sequencing. Two candidate autozygous intervals were identified, and the second round of exome sequencing revealed a single intronic variant therein (c.2885+8A>G [p.Ser963^∗] in RTTN exon 23). RT-PCR confirmed that this change creates a cryptic splice donor and thus causes retention of the intervening 7 bp of the intron and leads to premature truncation. On the basis of this finding, we reanalyzed the exome file of a second consanguineous family affected by a similar phenotype and identified another homozygous change in RTTN as the likely causal mutation. Combined linkage analysis of the two families confirmed that RTTN maps to the only significant linkage peak. Finally, through international collaboration, a Canadian multiplex family affected by microcephalic primordial dwarfism and biallelic mutation of RTTN was identified. Our results expand the phenotype of RTTN-related disorders, hitherto limited to polymicrogyria, to include microcephalic primordial dwarfism with a complex brain phenotype involving simplified gyration.     

Phylogenetic analysis based on spectral methods

Whole-genome or multiple gene phylogenetic analysis is of interest since single gene analysis often results in poorly resolved trees. Here, the use of spectral techniques for analyzing multigene data sets is explored. The protein sequences are treated as categorical time series, and a measure of similarity between a pair of sequences, the spectral covariance, is based on the common periodicity between these two sequences. Unlike the other methods, the spectral covariance method focuses on the relationship between the sites of genetic sequences. By properly scaling the dissimilarity measures derived from different genes between a pair of species, we can use the mean of these scaled dissimilarity measures as a summary statistic to measure the taxonomic distances across multiple genes. The methods are applied to three different data sets, one noncontroversial and two with some dispute over the correct placement of the taxa in the tree. Trees are constructed using two distance-based methods, BIONJ and FITCH. A variation of block bootstrap sampling method is used for inference. The methods are able to recover all major clades in the corresponding reference trees with moderate to high bootstrap support. Through simulations, we show that the covariance-based methods effectively capture phylogenetic signal even when structural information is not fully retained. Comparisons of simulation results with the bootstrap permutation results indicate that the covariance-based methods are fairly robust under perturbations in sequence similarity but more sensitive to perturbations in structural similarity.