Otophylloside B 4”’-O- beta-D-oleandropyranoside

28527145

Background
A large proportion of the world’s tropical peatlands occur in Indonesia where rapid conversion and associated losses of carbon, biodiversity and ecosystem services have brought peatland management to the forefront of Indonesia’s climate mitigation efforts. We evaluated peat volume from two commonly referenced maps of peat distribution and depth published by Wetlands International (WI) and the Indonesian Ministry of Agriculture (MoA), and used regionally specific values of carbon density to calculate carbon stocks.

Results
Peatland extent and volume published in the MoA maps are lower than those in the WI maps, resulting in lower estimates of carbon storage. We estimate Indonesia’s total peat carbon store to be within 13.6 GtC (the low MoA map estimate) and 40.5 GtC (the high WI map estimate) with a best estimate of 28.1 GtC: the midpoint of medium carbon stock estimates derived from WI (30.8 GtC) and MoA (25.3 GtC) maps. This estimate is about half of previous assessments which used an assumed average value of peat thickness for all Indonesian peatlands, and revises the current global tropical peat carbon pool to 75 GtC. Yet, these results do not diminish the significance of Indonesia’s peatlands, which store an estimated 30% more carbon than the biomass of all Indonesian forests. The largest discrepancy between maps is for the Papua province, which accounts for 62-71% of the overall differences in peat area, volume and carbon storage. According to the MoA map, 80% of Indonesian peatlands are <300 cm thick and thus vulnerable to conversion outside of protected areas according to environmental regulations. The carbon contained in these shallower peatlands is conservatively estimated to be 10.6 GtC, equivalent to 42% of Indonesia’s total peat carbon and about 12 years of global emissions from land use change at current rates. Conclusions Considering the high uncertainties in peatland extent, volume and carbon storage revealed in this assessment of current maps, a systematic revision of Indonesia’s peat maps to produce a single geospatial reference that is universally accepted would improve national peat carbon storage estimates and greatly benefit carbon cycle research, land use management and spatial planning. Electronic supplementary material The online version of this article (doi:10.1186/s13021-017-0080-2) contains supplementary material, which is available to authorized users.

Tropical peatlands, Wetlands, Climate change mitigation, Carbon pools, Carbon emissions, Peat degradation

An appraisal of Indonesia’s immense peat carbon stock using national peatland maps: uncertainties and potential losses from conversion

Matthew Warren,corresponding author1 Kristell Hergoualc’h,2 J. Boone Kauffman,3,4 Daniel Murdiyarso,3,5 and Randall Kolka6

2017 Dec

29351327

A simple, objective and accurate way of grouping children undergoing surgery into clinically relevant risk groups is needed. The purpose of this study, is to develop and validate a preoperative risk classification system for postsurgical 30-day mortality for children undergoing a wide variety of operations. The National Surgical Quality Improvement Project-Pediatric participant use file data for calendar years 2012-2014 was analyzed to determine preoperative variables most associated with death within 30 days of operation (D30). Risk groups were created using classification tree analysis based on these preoperative variables. The resulting risk groups were validated using 2015 data, and applied to neonates and higher risk CPT codes to determine validity in high-risk subpopulations. A five-level risk classification was found to be most accurate. The preoperative need for ventilation, oxygen support, inotropic support, sepsis, the need for emergent surgery and a do not resuscitate order defined non-overlapping groups with observed rates of D30 that vary from 0.075% (Very Low Risk) to 38.6% (Very High Risk). When CPT codes where death was never observed are eliminated or when the system is applied to neonates, the groupings remained predictive of death in an ordinal manner.

A novel risk classification system for 30-day mortality in children undergoing surgery

Oguz Akbilgic, Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft,#1,2 Max R. Langham, Jr., Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Writing - original draft, Writing - review & editing,#3,* Arianne I. Walter, Conceptualization, Data curation, Formal analysis, Methodology, Writing - review & editing,3,‡ Tamekia L. Jones, Conceptualization, Formal analysis, Methodology, Writing - review & editing,2,4,5,‡ Eunice Y. Huang, Conceptualization, Formal analysis, Investigation, Methodology, Writing - review & editing,3,‡ and Robert L. Davis, Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing - review & editing1,‡ Christos Papadelis, Editor

2018;