Author : Food and Agriculture Organization of the United Nations
Release : 2019-01-14
Genre : Technology & Engineering
Kind : eBook
Book Rating : 354/5 ( reviews)
Book Synopsis Measuring and modelling soil carbon stocks and stock changes in livestock production systems – A scoping analysis for the LEAP work stream on soil carbon stock changes by : Food and Agriculture Organization of the United Nations
Download or read book Measuring and modelling soil carbon stocks and stock changes in livestock production systems – A scoping analysis for the LEAP work stream on soil carbon stock changes written by Food and Agriculture Organization of the United Nations. This book was released on 2019-01-14. Available in PDF, EPUB and Kindle. Book excerpt: In order to build consensus on methods to measure and model soil carbon stocks and stock changes, the Steering Committee of the Livestock Environmental Assessment and Performance (LEAP) Partnership mandated a task force to develop this scoping analysis and pave the way towards the formation of the LEAP Tecnical Advisory Group on soil carbon stock changes. Soil carbon sequestration and storage in grasslands offers a significant potential to compensate for GHG emissions from livestock, but the lack of consensus on the appropriate methodologies to account for soil carbon stock changes hinders robust and standardized assessments. In this report, we reviewed several published soil organic carbon (SOC) models, and evaluated their aptitude to combine them with life cycle assessments (LCAs). Among contentious issues, the most relevant are: a) the lack of universal models, b) the uneven data availability, comparability and quality between countries and regions, and c) the difficulty to match measurable SOC fractions with those determined by the models. Taking this into account, a tiered approach is proposed, according to the availability of original data to run the models. The use of IPCC carbon (C) accounting system appears to be the simplest approach suitable to countries with scarcity of original C data. Conversely, more complex models such as Century (Parton 1987, 1988) or Roth C (Smith 1998) are likely to perform better and give less uncertainty when original input data are easily available.
