Implementing conservativeness in REDD+ is realistic and useful to address the most uncertain estimates

One of the main challenges in reducing emissions from deforestation and forest degradation(REDD+), either within a future UNFCCC approach or as part of other voluntary initiatives,is to design a system which is credible and broadly implementable by developing countries.To ensure credibility of REDD+ high quality monitoring systems are needed, i.e. capable ofproducing accurate estimates of greenhouse gas (GHG) emissions and removals. However, apossible trade-off exists between the high quality system requirement and broad participa-tion: if a significant number of countries will not fully access REDD+ because of not beingable to produce accurate estimates, the consequent risk of leakage (i.e. emissions displace-ment to these countries) could undermine the ultimate scope of REDD+.Plugge et al. (2012) analyzed the implications of applying the principle of conserva-tiveness in the context of uncertainties of carbon stock change estimates in REDD+. Whilethis principle is included in several UNFCCC documents (e.g., UNFCCC2006), itsapplication to REDD+ was proposed by Grassi et al. (2008) “to address the potentialincompleteness and high uncertainties of REDD+ estimates”;i.e.“when completeness oraccuracy of estimates cannot be achieved the reduction of emissions should not beoverestimated,oratleastthe riskofoverestimationshouldbereduced”.Wide interest hasbeenshown in this proposal (e.g., GOFC-GOLD 2012;HeroldS MeridianInstitute 2011).A key message from Plugge et al. (2012) is that, despite its attractiveness, the conserva-tiveness principle does not appear to be implementable in many cases, because it drasticallyreduces the amount of emission reductions that can be claimed (e.g. “for countries with lowdeforestation rates REDD is obviously not an option for generating benefits, as they wouldneed to implement monitoring systems that are able to estimate carbon stock changes with atotal error well below 1 %”). Similar conclusions, using a similar approach, were alsopresented in Kohl et al. (2009).We believe that this conclusion: on the impossibility for countries with low deforestationrates to generate REDD+ benefits under a conservative approach, is the consequence of theassumptions taken by these authors. In particular, some elements appear to have beenoverlooked by Plugge et al. (2012).

Firstly, one of the underlying basic ideas beyond REDD+ is to incentivize actions (i.e.emission reductions) beyond "business-as-usual".According to this approach, future net emissions from REDD+ should be compared against an agreed "baseline",1 which typically describes the expected business-as-usual net emissions.While in many cases it can be expected that this baseline will be equal to or lower than historical emission levels, in some cases (i.e.countries with low historical deforestation rates) the baseline could potentially include the expectation of increased emissions as compared to the past.Baseline-like concepts have been discussed both within UNFCCC (i.e."reference levels", RL, and "reference emissions levels", REL) (UNFCCC 2012) and within several REDD+ initiatives.Thus, the possibility of countries with low deforestation rates to generate REDD+ benefits will largely depend on the criteria used to set their baselines.
Secondly, Plugge et al. did not consider other and potentially more effective approaches to implement the conservativeness principle in REDD+ (e.g.Grassi et al. 2008).Even more importantly, some very simple conservative approaches have already been implemented by REDD+ initiatives, such as the Amazon fund, 2 demonstrating the feasibility and the utility of this principle.
This comment aims to: & Highlight the technical and scientific differences between the approaches of Plugge et al.
(2012) and Grassi et al. (2008) for the implementation of the conservativeness principle.& Summarize and further discuss a scientifically defensible yet realistic approach to implement conservativeness in REDD+ context.

Different approaches to implementing convervativeness lead to different conclusions
The different possible approaches for implementing the principle of conservativeness in REDD+ include the following: 1) The "Reliable Minimum Estimate" (RME), i.e. approach A2 in Grassi et al. (2008) and the approach used by Plugge et al. (2012).This approach has been suggested by the IPCC (2003) in the context of assessing changes in soil carbon.In practice, the changes in the carbon content between two temporally-separated sample pools are quantified by comparing the difference between the lower limit of the confidence interval of the first temporal sample and the higher limit of the confidence interval of the second temporal sample. 3This approach ignores possible correlation among errors.The red dotted lines in the figure within the box show the application of this approach to carbon stock changes.
2) The "trend uncertainty" approach (approach B1 in Grassi et al. 2008).The trend uncertainty represents the uncertainty of the difference of net emissions over time, or in the case of REDD+ it may represent the difference between actual net emissions (in the accounting period) and a previously agreed baseline.Given that an estimate of net emission is the result of an Activity Data (AD, e.g.deforested area) multiplied by the relevant Emission Factor (EF, e.g.loss of carbon per unit of deforested area), the uncertainty of the trend is extremely dependent on whether or not the errors of AD and EF are correlated between the baseline and the accounting period.The basic assumption of IPCC ( 2003) is that errors of AD are not correlated and errors of EF are fully correlated.A full correlation of errors over time is like saying that, if one measures the diameter of the same tree over time with a biased caliper, the percentage error of the estimate will remain the same.The green dotted lines in the figure within the box show the application of this approach to carbon stock changes, assuming full correlation of EF errors over time.However, it should be noted that the assumption of correlation of EF errors may not always be true; e.g. when a forest inventory is implemented (i.e. a tier 2 or 3 method), EFs are often not fully correlated.
Based on a series of simulations, Grassi et al. (2008) concluded that, by using the RME approach, no or very limited reductions of emissions from deforestation could be conservatively demonstrated, unless a large reduction of deforestation occurred (as compared to a baseline) and uncertainties are low.On the contrary, with the uncertainty of the trend approach, and when full correlation of EF errors may be assumed, conservative reductions of emissions can be demonstrated also with relatively small reductions of deforestation (as compared to a baseline) or with relatively high uncertainties.Plugge et al. (2012) correctly reiterate the difficulty of implementing the conservativeness concept through the RME approach, but do not consider the uncertainty of the trend and the associated analysis of correlation among errors.
Thus, the conclusions of the two papers differ essentially because a unique approach ('RME with 95 % confidence interval') is used in Plugge et al. (2012), while a set of different approaches were compared by Grassi et al. (2008).
2 A realistic and robust approach to implement conservativeness in REDD+ context Grassi et al. (2008) highlighted the need for further tests on the assumptions and possible refinements to the implementation of the conservativeness principle.Furthermore, the modality of application of this concept was left quite open, i.e.: -Should conservativeness be applied in all circumstances, and to all types of estimates?-Should uncertainty be taken into account in implementing conservativeness?If yes, which value of uncertainty and which confidence interval should be used?
Below we address these questions, summarizing and further discussing several refinements to the implementation of the conservativeness principle, partly already presented in Bucki et al. (2012).
Firstly, we propose to restrict the possible application of the conservativeness principle to those estimates of emission reductions which do not fully comply with IPCC methodological guidance in terms of completeness or accuracy of the estimates.Here we focus on the accuracy of the EF, e.g. when tier 1 values of carbon stock per unit of deforested area are used for a "key category". 5The rationale behind this approach is that tier-1 estimates are assumed to have inherently larger uncertainties than tier 2 or 3 estimates; i.e. while tier-1 cannot a priori be assumed bias, due to larger uncertainties the risk of overestimating significantly emission reductions (thus the risk of receiving significant credits not associated to real emission reductions), is expected to be higher. 6Treating equally estimates which fulfill IPCC guidance and those that do not would be unfair.This approach is fully in line with the spirit of the current UNFCCC guidance on reporting, reviewing and accounting GHG inventories of Annex 1 countries.7A review team may "adjust" the estimate of an Annex 1 country (through the application of a conservative factor) only if the GHG inventory does not follow the IPCC guidance.Similarly, we believe that if a REDD+ country uses adequate methods to estimate emissions there is no reason to apply conservative discounts.In practice, conservativeness could be applied to those countries having the capacity to assess AD (changes in forest area) following IPCC guidance, but without a proper forest inventory to estimate country-specific EFs (carbon stocks per unit of deforested area).In that case, the use of tier-1 EFs could be the only option for the country to estimate REDD+ emissions.Given the relatively good access to remote sensing data for estimating forest area changes, and the very limited number of countries which are already prepared to apply tier 2 or 3 methods for carbon stocks (Romijn et al. 2012), we believe that our approach could be of interest in a large number of cases.
Secondly, we believe that uncertainty should somehow be taken into account for implementing conservativeness in a scientifically robust way.Various sources of uncertainty may be recognized in the REDD+ context (e.g.see Pelletier et al. 2012).For the scope of this comment, we note that the conservative correction of tier-1 values could be easily implementable using the uncertainties provided by the IPCC for each tier-1 value, and using the 50 % confidence interval.The rationale behind this approach is to be consistent with the procedure already used in the context of Kyoto Protocol review process (see UNFCCC 2006 and the conservative factors therein).As compared to the current review and accounting rules, a novelty of our approach is noting that, when the same EFs are used both in the baseline and in the accounting period, a full correlation of errors always occurs.Under this specific condition, the trend uncertainty approach can be implemented with a lot of advantages as compared to the RME approach (see the example in the box).
It is worth noting that our approach to implement conservativeness is potentially implementable both in the context of a future UNFCCC REDD+ approach and within other REDD+ initiatives.Our approach is entirely consistent with the logic behind simpler approaches, such as that applied by the Amazon fund.The difference is that we propose the theoretical background of a more elaborated approach, where in the absence of a country-specific and detailed forest inventory it may be possible to use highly uncertain tier-1 IPCC carbon stock values (disaggregated by forest type) in combination with a conservative discount to reduce the risk of overestimation of emission reductions.This approach, which builds on Grassi et al. (2008) proposal, is similar to what Bucki et al. (2012) tested in a case-study and to what Norway proposed in its submission to UNFCCC (Norway 2012, p.8).The added value of our approach lies in its defensibility (i.e. the conservative discount is based on IPCC uncertainty values) and in the consistency with the spirit of UNFCCC review and accounting rules.As shown by the example in the box, this approach can allow a country to claim emission reduction credits even when relatively small reductions of deforestation occurred (as compared to a baseline) or when uncertainties are relatively high, in contrast with the conclusions by Plugge et al. (2012).

Conclusions
If REDD+ aims to reduce emissions from deforestation and forest degradation globally, it should aim to be accessible to all.
A snowball does not need to be perfectly round to start rolling down.Similarly, we believe that the conservativeness principle may help to address uncertain estimates in the initial phases of most REDD+ initiatives.Conservativeness may be applied in many different ways.The possible approach which we propose here, i.e. to apply conservative discounts to those estimates which may be assumed to be inherently more uncertain (e.g. when tier-1 carbon stock factors are used), may represent a fair and realistic approach to: -Help broaden the participation to REDD+, allowing also those countries with limited forest monitoring capacity to join, i.e. those capable of assessing changes in forest area following IPCC guidance but without a proper forest inventory to estimate the amount of carbon per unit of area.In these cases, and in the absence of any better alternative, our proposal would allow the use of tier-1 IPCC carbon stocks with limited conservative discounts.
-Increase if needed the credibility of emission reductions estimated with highly uncertain tier-1 IPCC carbon stocks (the conservative discount significantly decreases the risk of undue credits, i.e. not associated to real emission reductions), while maintaining strong incentives for further increasing the accuracy of the estimates, i.e. to move to higher tiers.