Assessing data availability for the development of REDD-plus national reference levels

Abstract

BackgroundData availability in developing countries is known to be extremely varied and is one of the constraints for setting the national reference levels (RLs) for the REDD-plus (i.e. 'Policy approaches and positive incentives on issues relating to reducing emissions from deforestation and forest degradation in developing countries; and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries') under the UNFCCC. Taking Thailand as a case study country, this paper compares three types of RLs, which require different levels of datasets, including a simple historic RL, a projected forest-trend RL, and a business-as-usual (BAU) RL.ResultsOther than the finding that different RLs yielded different estimations on future deforestation areas, the analysis also identified the characteristics of each RL. The historical RL demanded simple data, but can be varied in accordance with a reference year or period. The forest-trend RL can be more reliable than the historical RL, if the country's deforestation trend curve is formed smoothly. The complicated BAU RL is useful as it can demonstrate the additionality of REDD-plus activities and distinguish the country's unintentional efforts.ConclusionsWith the REDD-plus that involves widespread participation, there should be steps from which countries choose the appropriate RL; ranging from simpler to more complex measures, in accordance with data availability in each country. Once registered with REDD-plus, the countries with weak capacity and capability should be supported to enhance the data collection system in that country.

Recent forest expansion in Thailand: a methodological artifact?

“…One view, discussed in Section 4, has been present since the 1980s in academic and activist circles and holds that official forest statistics overestimate forest cover (e.g. The second view, called the methodological artifact thesis, recognizes the value of official statistics, but nevertheless rejects the idea of recent reforestation (Anonymous, 2006a;DNP and RFD, 2008;FAO, 2009FAO, , 2010cOngsomwang & Rattanasuwan, 2009;Samabuddhi, 2003;Trisurat, Alkemade, & Verburg, 2010;Umemiya et al, 2011). Proponents of this view often reject the idea of a recent forest expansion (e.g.…”

“…Dangulavanich, 2011;Sarnsamak, 2011). The methodological artifact thesis was repeatedly used to explain away the 1998-2000 apparent reforestation episode (DEQP and RRCAP, 2007;DNP and RFD, 2008;FAO, 2009;Kanchanachitra et al, 2010;Trisurat et al, 2010;Umemiya et al, 2011). Proponents of the methodological artifact thesis hold that official forest statistics are composed of two data series, one from 1961 (or 1973) to 1998 and the other from 2000 onwards, and each of them can be described as internally coherent and generally reflecting the true trend of forest cover (FAO, 2005a(FAO, , 2010cFlint, 1994;Myers, 1980, p. 108 extrapolated the results of a selection of official surveys that were either part of the first 'series' (FAO, 2005a) or the second one (FAO, 2010c).…”

Forest cover: setting targets for the future

“…We have to realize that relevant expertise is not available for all countries: the disparity is wide, and calls for due consideration [1]. …”

Influence of carbon mapping and land change modelling on the prediction of carbon emissions from deforestation

“…The use of land change models to set reference emissions levels allows the incorporation of a variety of driving factors to predict deforestation, thus models can project scenarios of deforestation and carbon emissions based on possible changes of input variables as a consequence of changes in national circumstances and not just historic trends (Soares-Filho et al 2006;Parker & Mitchel 2009;Umemiya et al 2010). This is particularly important for countries with historically low deforestation rates and a high proportion of forests remaining, which might be left out from any possibility of obtaining carbon credits if reference emissions levels are set based on only historic deforestation data (daFonseca et al 2007; Cerbu Table 1 Components of uncertainty used to predict carbon emissions from deforestation.…”