气候变化领域集成服务门户(CCPortal): A land degradation interpretation matrix for reporting on UN SDG indicator 15.3.1 and land degradation neutrality

CCPortal

DOI	10.1016/j.envsci.2020.07.015
	A land degradation interpretation matrix for reporting on UN SDG indicator 15.3.1 and land degradation neutrality
	Sims N.C.; Barger N.N.; Metternicht G.I.; England J.R.
发表日期	2020
ISSN	14629011
起始页码	1
结束页码	6
卷号	114
英文摘要	The Land Degradation Neutrality Initiative of the UN Convention to Combat Desertification (UNCCD) encourages each of the 123 signatory countries to stabilise or reduce their extent of degraded land. Land degradation is assessed using the methods described in the Good Practice Guidance (GPG) document for Sustainable Development Goal (SDG) Indicator 15.3.1 (the proportion of land that is degraded over total land area), using three sub-indicators: land cover change, land productivity and soil organic carbon (SOC) stocks (as a proxy for carbon stocks above and below ground). The GPG identifies degraded areas by aggregating the sub-indicator assessments using a one-out-all-out (1OAO) approach, in which an area is identified as degraded if any one or more of the sub-indicators shows degradation i.e. a land cover transition defined as degradation, a reduction in productivity, and/or a reduction in SOC stocks. Under some circumstances, however, the 1OAO method can result in a counterintuitive degradation assessment, such as where the removal of invasive plant species reduces plant biomass, which would normally suggest degradation of net primary production, but which in this circumstance is considered a positive change in the context of land remediation activities. Each country has the opportunity to report areas within its sovereign bounds as an error of ‘false positive’ or ‘false negative’ degradation with sufficient justification, however it is vital that this is done in a way that ensures consistency of reporting amongst countries at regional and global scales. This paper describes scenarios in which the 1OAO process can lead to a counterintuitive degradation assessment, focusing on the potential impacts of invasive plants, woody encroachment (i.e. bush encroachment), and land remediation activities on SOC stocks as examples. We present an interpretation matrix to assist with determining how to report degradation in these cases, and help identify the drivers of degradation and potential remediation activities. Increased clarity around degradation labelling and interpretation could improve reporting consistency and transparency, and increase the efficiency and effectiveness of land degradation remediation actions. © 2020
英文关键词	Decision support; Invasive plant species; Land productivity; Soil organic carbon; UN sustainable development goals; Woody encroachment
scopus关键词	organic carbon; agricultural land; Article; biomass production; carbon sequestration; carbon storage; decision support system; desertification; ecosystem; irrigation (agriculture); land use; practice guideline; priority journal; socioeconomics; surface soil; sustainable development; woody plant
来源期刊	Environmental Science and Policy
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/176564
作者单位	CSIRO Astronomy and Space Science, Clayton, VIC 3168, Australia; Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, CO 80309-0334, United States; Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia; CSIRO Land and Water, Clayton, VIC 3168, Australia
推荐引用方式 GB/T 7714	Sims N.C.,Barger N.N.,Metternicht G.I.,et al. A land degradation interpretation matrix for reporting on UN SDG indicator 15.3.1 and land degradation neutrality[J],2020,114.
APA	Sims N.C.,Barger N.N.,Metternicht G.I.,&England J.R..(2020).A land degradation interpretation matrix for reporting on UN SDG indicator 15.3.1 and land degradation neutrality.Environmental Science and Policy,114.
MLA	Sims N.C.,et al."A land degradation interpretation matrix for reporting on UN SDG indicator 15.3.1 and land degradation neutrality".Environmental Science and Policy 114(2020).