Is the Lambda CDM Model Consistent with Observations of Large-Scale Structure?

The claim that large-scale structure data independently prefers the Lambda Cold Dark Matter model is a myth. However, an updated compilation of large-scale structure observations cannot rule out Lambda CDM at 95% confidence. We explore the possibility of improving the model by adding Hot Dark Matter but the fit becomes worse; this allows us to set limits on the neutrino mass.Comment: To appear in Proceedings of "Sources and Detection of Dark Matter/Energy in the Universe", ed. D. B. Cline. 6 pages, including 2 color figure

Nut production in Bertholletia excelsa across a logged forest mosaic: implications for multiple forest use

Although many examples of multiple-use forest management may be found in tropical smallholder systems, few studies provide empirical support for the integration of selective timber harvesting with non-timber forest product (NTFP) extraction. Brazil nut (Bertholletia excelsa, Lecythidaceae) is one of the world’s most economically-important NTFP species extracted almost entirely from natural forests across the Amazon Basin. An obligate out-crosser, Brazil nut flowers are pollinated by large-bodied bees, a process resulting in a hard round fruit that takes up to 14 months to mature. As many smallholders turn to the financial security provided by timber, Brazil nut fruits are increasingly being harvested in logged forests. We tested the influence of tree and stand-level covariates (distance to nearest cut stump and local logging intensity) on total nut production at the individual tree level in five recently logged Brazil nut concessions covering about 4000 ha of forest in Madre de Dios, Peru. Our field team accompanied Brazil nut harvesters during the traditional harvest period (January-April 2012 and January-April 2013) in order to collect data on fruit production. Three hundred and ninety-nine (approximately 80%) of the 499 trees included in this study were at least 100 m from the nearest cut stump, suggesting that concessionaires avoid logging near adult Brazil nut trees. Yet even for those trees on the edge of logging gaps, distance to nearest cut stump and local logging intensity did not have a statistically significant influence on Brazil nut production at the applied logging intensities (typically 1–2 timber trees removed per ha). In one concession where at least 4 trees ha-1 were removed, however, the logging intensity covariate resulted in a marginally significant (0.09) P value, highlighting a potential risk for a drop in nut production at higher intensities. While we do not suggest that logging activities should be completely avoided in Brazil nut rich forests, when a buffer zone cannot be observed, low logging intensities should be implemented. The sustainability of this integrated management system will ultimately depend on a complex series of socioeconomic and ecological interactions. Yet we submit that our study provides an important initial step in understanding the compatibility of timber harvesting with a high value NTFP, potentially allowing for diversification of forest use strategies in Amazonian Perù

Behavioural Susceptibility Theory: Professor Jane Wardle and the Role of Appetite in Genetic Risk of Obesity

Purpose of Review: There is considerable variability in human body weight, despite the ubiquity of the 'obesogenic' environment. Human body weight has a strong genetic basis and it has been hypothesised that genetic susceptibility to the environment explains variation in human body weight, with differences in appetite being implicated as the mediating mechanism; so-called 'behavioural susceptibility theory' (BST), first described by Professor Jane Wardle. This review summarises the evidence for the role of appetite as a mediator of genetic risk of obesity. Recent Findings: Variation in appetitive traits is observable from infancy, drives early weight gain and is highly heritable in infancy and childhood. Obesity-related common genetic variants identified through genome-wide association studies show associations with appetitive traits, and appetite mediates part of the observed association between genetic risk and adiposity. Summary: Obesity results from an interaction between genetic susceptibility to overeating and exposure to an 'obesogenic' food environment

Emotional over- and under-eating in early childhood are learned not inherited

Emotional overeating (EOE) has been associated with increased obesity risk, while emotional undereating (EUE) may be protective. Interestingly, EOE and EUE tend to correlate positively, but it is unclear whether they reflect different aspects of the same underlying trait, or are distinct behaviours with different aetiologies. Data were from 2054 five-year-old children from the Gemini twin birth cohort, including parental ratings of child EOE and EUE using the Child Eating Behaviour Questionnaire. Genetic and environmental influences on variation and covariation in EUE and EOE were established using a bivariate Twin Model. Variation in both behaviours was largely explained by aspects of the environment completely shared by twin pairs (EOE: C = 90%, 95% CI: 89%-92%; EUE: C = 91%, 95% CI: 90%-92%). Genetic influence was low (EOE: A = 7%, 95% CI: 6%-9%; EUE: A = 7%, 95% CI: 6%-9%). EOE and EUE correlated positively (r = 0.43, p < 0.001), and this association was explained by common shared environmental influences (BivC = 45%, 95% CI: 40%-50%). Many of the shared environmental influences underlying EUE and EOE were the same (rC = 0.50, 95% CI: 0.44, 0.55). Childhood EOE and EUE are etiologically distinct. The tendency to eat more or less in response to emotion is learned rather than inherited

Methylation QTLs in the developing brain and their enrichment in schizophrenia risk loci

We characterized DNA methylation quantitative trait loci (mQTLs) in a large collection (n = 166) of human fetal brain samples spanning 56-166 d post-conception, identifying >16,000 fetal brain mQTLs. Fetal brain mQTLs were primarily cis-acting, enriched in regulatory chromatin domains and transcription factor binding sites, and showed substantial overlap with genetic variants that were also associated with gene expression in the brain. Using tissue from three distinct regions of the adult brain (prefrontal cortex, striatum and cerebellum), we found that most fetal brain mQTLs were developmentally stable, although a subset was characterized by fetal-specific effects. Fetal brain mQTLs were enriched amongst risk loci identified in a recent large-scale genome-wide association study (GWAS) of schizophrenia, a severe psychiatric disorder with a hypothesized neurodevelopmental component. Finally, we found that mQTLs can be used to refine GWAS loci through the identification of discrete sites of variable fetal brain methylation associated with schizophrenia risk variants

Dark Energy Surveyed Year 1 results: calibration of cluster mis-centring in the redMaPPer catalogues

The centre determination of a galaxy cluster from an optical cluster finding algorithm can be offset from theoretical prescriptions or N-body definitions of its host halo centre. These offsets impact the recovered cluster statistics, affecting both richness measurements and the weak lensing shear profile around the clusters. This paper models the centring performance of the redMaPPer cluster finding algorithm using archival X-ray observations of redMaPPer selected clusters. Assuming the X-ray emission peaks as the fiducial halo centres, and through analysing their offsets to the redMaPPer centres, we find that ∼75 ± 8 per cent of the redMaPPer clusters are well centred and the mis-centred offset follows a Gamma distribution in normalized, projected distance. These mis-centring offsets cause a systematic underestimation of cluster richness relative to the well-centred clusters, for which we propose a descriptive model. Our results enable the DES Y1 cluster cosmology analysis by characterizing the necessary corrections to both the weak lensing and richness abundance functions of the DES Y1 redMaPPer cluster catalogue

Mass variance from archival X-ray properties of dark energy survey year-1 galaxy clusters

For abstract see published article