Changes in soil properties with long-term organic inputs due to distance from homestead and farm characteristics in southern Ethiopian farmlands

Open access via the Elsevier Agreement This original data was collected as part of the project ‘Alternative Carbon Investments in Ecosystems for Poverty Alleviation –below ground versus above ground opportunities for restoration of ecosystem services’ (ALTER), funded with support from the Ecosystem Services for Poverty Alleviation (ESPA) programme (grant no. NE/K010441/1). The analysis of the data and preparation of this paper was undertaken as part of the RALENTIR (Reducing land degradation and carbon loss from Ethiopia's soils to strengthen livelihoods and resilience) project, funded by GCRF (Global Challenges Research Fund) and University of Aberdeen (grant number ES/T003073/1).Peer reviewedPublisher PD

Genomic prediction of complex human traits: relatedness, trait architecture and predictive meta-models

We explore the prediction of individuals' phenotypes for complex traits using genomic data. We compare several widely used prediction models, including Ridge Regression, LASSO and Elastic Nets estimated from cohort data, and polygenic risk scores constructed using published summary statistics from genome-wide association meta-analyses (GWAMA). We evaluate the interplay between relatedness, trait architecture and optimal marker density, by predicting height, body mass index (BMI) and high-density lipoprotein level (HDL) in two data cohorts, originating from Croatia and Scotland. We empirically demonstrate that dense models are better when all genetic effects are small (height and BMI) and target individuals are related to the training samples, while sparse models predict better in unrelated individuals and when some effects have moderate size (HDL). For HDL sparse models achieved good across-cohort prediction, performing similarly to the GWAMA risk score and to models trained within the same cohort, which indicates that, for predicting traits with moderately sized effects, large sample sizes and familial structure become less important, though still potentially useful. Finally, we propose a novel ensemble of whole-genome predictors with GWAMA risk scores and demonstrate that the resulting meta-model achieves higher prediction accuracy than either model on its own. We conclude that although current genomic predictors are not accurate enough for diagnostic purposes, performance can be improved without requiring access to large-scale individual-level data. Our methodologically simple meta-model is a means of performing predictive meta-analysis for optimizing genomic predictions and can be easily extended to incorporate multiple population-level summary statistics or other domain knowledge

Racial differences in human platelet PAR4 reactivity reflect expression of PCTP and miR-376c.

Racial differences in the pathophysiology of atherothrombosis are poorly understood. We explored the function and transcriptome of platelets in healthy black (n = 70) and white (n = 84) subjects. Platelet aggregation and calcium mobilization induced by the PAR4 thrombin receptor were significantly greater in black subjects. Numerous differentially expressed RNAs were associated with both race and PAR4 reactivity, including PCTP (encoding phosphatidylcholine transfer protein), and platelets from black subjects expressed higher levels of PC-TP protein. PC-TP inhibition or depletion blocked PAR4- but not PAR1-mediated activation of platelets and megakaryocytic cell lines. miR-376c levels were differentially expressed by race and PAR4 reactivity and were inversely correlated with PCTP mRNA levels, PC-TP protein levels and PAR4 reactivity. miR-376c regulated the expression of PC-TP in human megakaryocytes. A disproportionately high number of microRNAs that were differentially expressed by race and PAR4 reactivity, including miR-376c, are encoded in the DLK1-DIO3 locus and were expressed at lower levels in platelets from black subjects. These results suggest that PC-TP contributes to the racial difference in PAR4-mediated platelet activation, indicate a genomic contribution to platelet function that differs by race and emphasize a need to consider the effects of race when developing anti-thrombotic drugs

Fuel poverty in the UK: Is there a difference between rural and urban areas?

Fuel poverty is a significant policy issue. An argument often made is that rural households are more likely to be fuel poor due to the nature of rural housing stock and the more limited choice of energy sources in rural areas. This paper uses panel data to compare the level and dynamics of fuel poverty in rural and urban areas of the UK. In addition to descriptive analysis, discrete hazard models of fuel poverty exit and re-entry are estimated and used to assess the influence of housing and personal characteristics on the time spent in fuel poverty. The results indicate that, on average, the experience of fuel poverty in urban areas is longer with a higher probability of fuel poverty persistence. However, on average the rural fuel poor appear more vulnerable to energy price increases while living in private accommodation or a flat increases their probability of remaining fuel poor relative to their urban counterparts. These results indicate policy effectiveness may differ across rural and urban space. However, they also emphasise the limits of spatial targeting. Monitoring the dynamics of fuel poverty is important for ensuring that policy targets are effective and reaching those most in need

Organic resource use in rural households in Ethiopia 2016-2017

Data on household use of organic resources including dung, wood and crop residues and their time use from Halaba district, Southern Nations, Nationalities and Peoples’ Region in Ethiopia. To capture seasonality households were, where possible, interviewed twice. A Baseline Data: collected in October 2016. Second Round Data: collected March/April 2017. In addition to organic resource and time use questions, the baseline survey has information on assets and land use, and the second has limited information on marketing.The shortage of organic resources in rural Sub-Saharan Africa (SSA) for improving long term energy, food and water provision is one of the region's greatest challenges. The Southern Nations, Nationalities and Peoples' Region in Ethiopia (SNNPR) provides an excellent case study for transdisciplinary research on how community sustainability and resilience might be improved by better use of organic resources. Organic resources are scarce, with seasonality causing significant variation in available water across the year, while diverse cultural norms and institutional arrangements, framing access to land, water and energy, emphasise that the success and impact of interventions depends on complex interactions between what science makes possible and how decisions are made by individuals and communities. In a Nexus Network grant, engagement with farmers, householders and policy makers from Halaba District and the wider SNNPR identified key Nexus challenges as complex, multi-dimensional and inter-connected. The interaction between the use of organic resources for energy, water and food in the region is dynamic, extremely complex and highly spatially variable. As elsewhere in SSA, most of the rural population use solid biomass for cooking and heating, with wood, dung and crop residues the main energy sources. However, these resources are also crucial to long term sustainable food production and water use. Dung and crop residues provide organic fertilisers that improve water holding capacity of the soil. Demands on organic wastes for fuel and livestock feed reduce the use of dung and crop residues as soil amendments, which reduces biomass production and organic inputs to the soil.</p