Neil Sims, Glenn Newnham, Jacqui England, Carly Green & Alex Held Good practice guidance for UN SDG Indicator 15.3.1: Proportion of degraded land over total land area Neil Sims, Glenn Newnham, Jacqui England, Carly Green & Alex Held CSIRO Land & water Neil Sims| Team Leader October 2017

UN SDG 15.3.1 Good Practice Guidance Assist countries in reporting on UN SDG 15.3.1 Proportion of degraded land over total land area Guidance documents, not a ‘cook book’ ‘Living’ documents Recommendations from current datasets & methods Sub-indicator and Indicator Guidance Land cover Land Productivity Carbon Stocks, above & below ground (SOC) Deriving the Indicator Document provides guidance, and helps to set reporting parameters Living document based on datasets and methods available at this point in time GPG for UN SDG 15.3.1 | Neil Sims

Baseline, Reporting & Review Baseline from 1 Jan 2000 to 31 Dec 2015 Reporting every 4 years commencing 2018 In line with UNCCD reporting requirements Review in 2030 Relative to baseline conditions In context of Land Degradation Neutrality Baseline* Reporting Review 2000 2015 2018 2022 2026 2030 Baseline period can be interpreted differently to assess different metrics Have to determine baseline degradation extent to assess change in degraded area over reporting period Success of SDG reviewed in 2030 in context of LDN GPG for UN SDG 15.3.1 | Neil Sims

Sub-Indicator 1 – Land cover & land cover change Ideally use National datasets Land cover meta language (LCML) LCML enables land cover classes to be translated from one classification scheme to another – including National schemes GPG for UN SDG 15.3.1 | Neil Sims

Sub-Indicator 1 – Land cover & land cover change Degradation interpreted from transitions from one landcover type to another Interpreted in National context This sub-indicator detects large step changes in the landscape – eg land clearing This table is an example only. Degradation transitions should be interpreted in national context GPG for UN SDG 15.3.1 | Neil Sims

Sub-Indicator 2: Land Productivity Degradation interpreted from changes in Annual Net Primary Productivity (ANPP) JRC LPD Plant growth (NDVI or similar) Annual growth cycles ‘Small integral’ (h) Area under curve above growing season minimum Trend, State, Performance Year Detects gradual changes Productivity is plant growth Plant growth shows annual cycles over the long term. Timesat can calculate statics for each of the annual growth cycle peaks. Area under growth cycle curve above a growing-season minimum among most highly correlated with ANPP Day GPG for UN SDG 15.3.1 | Neil Sims

Productivity Metric 1. Trend Slope of trend in ANPP change over time 16 data points from baseline Mann-Kendall Z for significance Reporting trend measured from 8 most recent data points Optional calibration for water availability (WUE) All data points used in baseline degradation assessment 8 most recent points for each reporting period GPG for UN SDG 15.3.1 | Neil Sims

Productivity Metric 2: State ANPP compared to historical observations for that spatial unit over time 2000-2012 Over time ANPP has a range of values Baseline degradation: 1. Classify 2000-2012 into 10 classes 2. Identify which class the average of 2013,14&15 lies in 3. Areas in lowest 50% of classes potentially degraded Report periods: 1. Compare average of feporting period ANPP measurements to baseline classes 2. Reduction of two or more classes indicates potential degradation GPG for UN SDG 15.3.1 | Neil Sims

Productivity Metric 3. Performance 1 (90th percentile) 0.5 Min Max Not degraded Potentially degraded ANPP values observed in similar land capability unit ANPP in a pixel or region compared to pixels with similar ANPP potential Phenological groups land cover and climate Baseline average of 2000-2015 Reporting average of years since last report GPG for UN SDG 15.3.1 | Neil Sims

Productivity degradation Potential degradation is: 1. Significant negative ANPP trend OR 2. Non-significant trend with BOTH a. Degradation indicated in State assessment AND b. Degradation indicated Performance assessment Support class matrix GPG for UN SDG 15.3.1 | Neil Sims

Sub-Indicator 3: Carbon stocks, above and below ground Degradation indicated by reduction in Soil Organic Carbon (SOC) stocks Top 30cm of soil profile To be replaced by Total Carbon Stock analysis when ready Land cover / unit SOC IPCC or CCI-LC defaults SoilGrids 250m or National datasets Field data, models Stock change assessment Land use & management, (tillage, fertiliser), Emissions (drainage, burning) Mineral & organic soils Change in SOC Assess change between baseline and reporting period SOC Default/reference SOC stocks from land cover data, or other SOC maps or models (SoilGrids is a static map so…) Modify default levels using stock change assessment Compare change in SOC between reporting and baseline periods GPG for UN SDG 15.3.1 | Neil Sims

Change in Soil Organic Carbon Statistical methods based on confidence intervals of change Slow rate of change High uncertainty in many estimates increase potential errors Threshold based on direction and magnitude of relative change Regions with >10% average net reduction in SOC 𝑟 𝑆𝑂𝐶 = ( 𝑆𝑂𝐶 𝑡 𝑛 −𝑆𝑂𝐶 𝑡 0 ) 𝑆𝑂𝐶 𝑡 0 ×100 Where: 𝑟 𝑆𝑂𝐶 = relative change in soil organic carbon for spatial feature (%) 𝑆𝑂𝐶 𝑡 0 = baseline soil organic carbon stock for spatial feature (t C ha-1) 𝑆𝑂𝐶 𝑡 𝑛 = soil organic carbon stock at the end of the monitoring period for spatial feature (t C ha-1) Potential for significant errors in the statistical method Threshold method arbitrary, but GPG for UN SDG 15.3.1 | Neil Sims

Calculating the Indicator One-Out-All-Out One-Out-All-Out Reported as degradation if identified in any one of the sub-indicators Aggregation From pixels to regions Significant when 10% of region is degraded Identification of false positives and anomalies   Sub indicator Indicator Support Class Land cover Productivity SOC Degraded 1 Y 2 N 3 4 5 6 7 8 GPG for UN SDG 15.3.1 | Neil Sims

Reporting degradation Where: 𝐴(𝐷𝑒𝑔𝑟𝑎𝑑𝑒𝑑) 𝑖,𝑛 is the total area degraded in the land cover class i in the year of monitoring n (ha) 𝐴𝑟𝑒𝑐𝑒𝑛𝑡 𝑖,𝑛 is the area defined as degraded in the monitoring year 𝐴𝑝𝑒𝑟𝑠𝑖𝑠𝑡𝑒𝑛𝑡 𝑖,𝑛 is the area previously defined as degraded which remains degraded in the monitoring year 𝑃 n = 𝐴(𝐷𝑒𝑔𝑟𝑎𝑑𝑒𝑑) n 𝑖 𝑚 A(Total) 𝑃 n is the proportion of land that is degraded over total land area 𝐴(𝐷𝑒𝑔𝑟𝑎𝑑𝑒𝑑) n is the total area degraded in the year of monitoring n (ha) A(Total) is the total area within the national boundary (ha) GPG for UN SDG 15.3.1 | Neil Sims

Recommended minimum reporting inclusions Descriptions and justification of National sub-indicators Details of data sources and calculations Land cover legend and transition matrix (maps and justification) Degradation maps at Indicator and Sub-Indicator level Justification for “explained anomalies” or “false positives” Descriptive review of areas identified as degraded GPG for UN SDG 15.3.1 | Neil Sims

Reviewers and collaborators GPG for UN SDG 15.3.1 | Neil Sims

Thank you CSIRO LAND & WATER Neil Sims Remote sensing research scientist t +61 3 9545 2163 e Neil.Sims@csiro.au w www.csiro.au Land and water

ESA Climate Change Initiative – Land Cover 22 classes, annual between 1992-2015 GPG for UN SDG 15.3.1 | Neil Sims

Land Productivity Trend (over time) Metrics correlated with ANPP (NDVI etc) Performance (relative to other similar land capability units) All data points used in baseline degradation assessment 8 most recent points for each reporting period State (relative to past) GPG for UN SDG 15.3.1 | Neil Sims

Soil Carbon data IPCC default reference SOC stocks Some examples of datasets, IPCC default SOC stocks and stock change factors IPCC default reference SOC stocks IPCC stock change factors GPG for UN SDG 15.3.1 | Neil Sims