Low carbon development and poverty: exploring poverty alleviating mitigation action in developing countries

Climate change and poverty mostly fall into the adaptation category in the current research literature and relevant policy-making. The strong connection between poverty and adaptation rests on the assumption that poor countries produce only low carbon emissions. They will also be most affected by the impacts of climate change. Therefore, efforts on poverty and climate change concentrate mostly on adapting to the consequences of climate change. If we acknowledge current findings of poverty research, we find that this separation between mitigation and adaptation does not hold anymore. Recent research suggests that poverty demographics have changed between 1990 and 2010. The majority of the poor nowadays live in middle-income countries, and not only in low-income countries. Emissions in middle-income countries increase, while their governments try to reduce emissions in the long term without jeopardising socio-economic development. Climate change presents a threefold policy challenge for middle-­income countries. They need to: i) design mitigation actions in such a way that they contribute to alleviate poverty; ii) reduce emissions, helping to slow global warming in a way that does not compromise the competitiveness of their economies, because without collective action by all, the costs of inaction affect mostly the poor; and iii) prepare to adapt to the unavoidable consequences of climate change. The paper unpacks the linkages between low-­carbon development, mitigation and poverty in middle-­income countries (where the majority of the poor live). Most middle-­income countries pursue carbon-­intensive development paths and will need to mitigate emissions towards low-­carbon development paths. How can mitigation actions contribute to poverty alleviation? An explorative analysis of mitigation actions in five middle-­income countries shows that mitigation has moved on the political agendas over the past five years. Yet, these efforts are not necessarily linked with poverty alleviation instruments. Most mitigation action can have positive and negative poverty effects. Their impacts depend on an adequate pro-­poor policy mix

South African approaches to measuring, reporting and verifying: a scoping report

The South African government announced its intention to make emissions data reporting mandatory for emitters of more than a 0.1Mt of greenhouse gases per year in the 2011 National Climate Change Response White Paper. The government intends to establish a ‘climate change response monitoring and evaluation system’, that ‘evolves with international measuring, reporting and verification (MRV) requirements.’ MRV is one of the key topics in the international climate negotiations to create trust and legitimacy. This report presents a mapping exercise of South African approaches to MRV. Research shows that a lot of databases and collections exist already, particularly in the emissions intensive energy sector. However, there is no coherent overall approach to the management of these data. Coordination is necessary for a comprehensive system. Government needs to lead this process ensuring the participation of all departments. It will be necessary to build on the existing structures and capacities to achieve the commitments in the White Paper. Three case studies present existing approaches to GHG reporting, besides the overall scoping. This scoping report is the result from the first phase of the Measurement and Performance Tracking Project that the World Resource Institute conducts in cooperation with the German Ministry for Environment and the Energy Research Centre

The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p\u3c0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p\u3c0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior

Student Learning Outcomes Poster Session for CSB/SJU Joint Board of Trustees Meeting, December 5th, 2014

A faculty and student poster session was held focusing on student learning outcomes at the December 5th, 2014 joint Board of Trustee meeting. The posters focused on using assessment of student learning to improve teaching and learning and covered student learning outcomes at the course, departmental, and institutional levels

Associations between self-reported sleep quality and white matter in community-dwelling older adults: A prospective cohort study

Both sleep disturbances and decline in white matter microstructure are commonly observed in ageing populations, as well as in age-related psychiatric and neurological illnesses. A relationship between sleep and white matter microstructure may underlie such relationships, but few imaging studies have directly examined this hypothesis. In a study of 448 community-dwelling members of the Whitehall II Imaging Sub-Study aged between 60 and 82 years (90 female, mean age 69.2 ± 5.1 years), we used the magnetic resonance imaging technique diffusion tensor imaging to examine the relationship between self-reported sleep quality and white matter microstructure. Poor sleep quality at the time of the diffusion tensor imaging scan was associated with reduced global fractional anisotropy and increased global axial diffusivity and radial diffusivity values, with small effect sizes. Voxel-wise analysis showed that widespread frontal-subcortical tracts, encompassing regions previously reported as altered in insomnia, were affected. Radial diffusivity findings remained significant after additional correction for demographics, general cognition, health, and lifestyle measures. No significant differences in general cognitive function, executive function, memory, or processing speed were detected between good and poor sleep quality groups. The number of times participants reported poor sleep quality over five time-points spanning a 16-year period was not associated with white matter measures. In conclusion, these data demonstrate that current sleep quality is linked to white matter microstructure. Small effect sizes may limit the extent to which poor sleep is a promising modifiable factor that may maintain, or even improve, white matter microstructure in ageing. Hum Brain Mapp 38:5465-5473, 2017. © 2017 Wiley Periodicals, Inc

The common genetic influence over processing speed and white matter microstructure: Evidence from the Old Order Amish and Human Connectome Projects.

Speed with which brain performs information processing influences overall cognition and is dependent on the white matter fibers. To understand genetic influences on processing speed and white matter FA, we assessed processing speed and diffusion imaging fractional anisotropy (FA) in related individuals from two populations. Discovery analyses were performed in 146 individuals from large Old Order Amish (OOA) families and findings were replicated in 485 twins and siblings of the Human Connectome Project (HCP). The heritability of processing speed was h(2)=43% and 49% (both p<0.005), while the heritability of whole brain FA was h(2)=87% and 88% (both p<0.001), in the OOA and HCP, respectively. Whole brain FA was significantly correlated with processing speed in the two cohorts. Quantitative genetic analysis demonstrated a significant degree to which common genes influenced joint variation in FA and brain processing speed. These estimates suggested common sets of genes influencing variation in both phenotypes, consistent with the idea that common genetic variations contributing to white matter may also support their associated cognitive behavior

\u3ci\u3eDrosophila\u3c/i\u3e Muller F Elements Maintain a Distinct Set of Genomic Properties Over 40 Million Years of Evolution

The Muller F element (4.2 Mb, ~80 protein-coding genes) is an unusual autosome of Drosophila melanogaster; it is mostly heterochromatic with a low recombination rate. To investigate how these properties impact the evolution of repeats and genes, we manually improved the sequence and annotated the genes on the D. erecta, D. mojavensis, and D. grimshawi F elements and euchromatic domains from the Muller D element. We find that F elements have greater transposon density (25–50%) than euchromatic reference regions (3–11%). Among the F elements, D. grimshawi has the lowest transposon density (particularly DINE-1: 2% vs. 11–27%). F element genes have larger coding spans, more coding exons, larger introns, and lower codon bias. Comparison of the Effective Number of Codons with the Codon Adaptation Index shows that, in contrast to the other species, codon bias in D. grimshawi F element genes can be attributed primarily to selection instead of mutational biases, suggesting that density and types of transposons affect the degree of local heterochromatin formation. F element genes have lower estimated DNA melting temperatures than D element genes, potentially facilitating transcription through heterochromatin. Most F element genes (~90%) have remained on that element, but the F element has smaller syntenic blocks than genome averages (3.4–3.6 vs. 8.4–8.8 genes per block), indicating greater rates of inversion despite lower rates of recombination. Overall, the F element has maintained characteristics that are distinct from other autosomes in the Drosophila lineage, illuminating the constraints imposed by a heterochromatic milieu