Leakage effects in natural resource supply chains: a case study from the Peruvian commercial charcoal market

Wood charcoal is generally viewed as a rudimentary form of energy. It is often understood in terms of its role of providing rural poor populations with basic energy needs, and/or the contribution its production makes to local forest degradation. More recently, the potentially much larger impact of urban demands on natural resources is attracting attention. Rural/urban supply chains are becoming an important research focus as nations try to start aligning with international environmental agreements by providing more honest environmental data regarding deforestation and associated emissions. This paper presents results from quantitative and qualitative research investigating the commercial charcoal supply chain servicing the metropolitan area of Lima, the capital of Peru. Long-term conservation initiatives protecting the species algarrobo (Prosopis spp.) were found to have caused a leakage effect in which the species shihuahuaco (Dipteryx spp.) from the Amazon region of Ucayali is compensating for the reduced production of algarrobo charcoal. Charcoal production in the urban area of Pucallpa, Ucayali is estimated to be more than eighty times the official figures, the vast majority of which goes to service the thousands of chicken brasseries in Lima. Commercial Amazonian charcoal is produced predominantly from sawmill by-product, and thus not found to be a direct threat to the rainforest. However, reduced availability of the by-product of the preferred species shihuahuaco to charcoal producers raises concern that this species is being heavily overexploited in the region

Whole-genome sequencing of patients with rare diseases in a national health system

Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 extensively phenotyped participants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data of UK Biobank participants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare