Implications of sampling design and sample size for national carbon accounting systems

Michael Köhl,Charles T Scott,Andrew Lister,Thomas Baldauf,Daniel Plugge

doi:10.1186/1750-0680-6-10

Abstract

BackgroundCountries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. Due to the extensive areas covered by forests the information is generally obtained by sample based surveys. Most operational sampling approaches utilize a combination of earth-observation data and in-situ field assessments as data sources.ResultsWe compared the cost-efficiency of four different sampling design alternatives (simple random sampling, regression estimators, stratified sampling, 2-phase sampling with regression estimators) that have been proposed in the scope of REDD. Three of the design alternatives provide for a combination of in-situ and earth-observation data. Under different settings of remote sensing coverage, cost per field plot, cost of remote sensing imagery, correlation between attributes quantified in remote sensing and field data, as well as population variability and the percent standard error over total survey cost was calculated. The cost-efficiency of forest carbon stock assessments is driven by the sampling design chosen. Our results indicate that the cost of remote sensing imagery is decisive for the cost-efficiency of a sampling design. The variability of the sample population impairs cost-efficiency, but does not reverse the pattern of cost-efficiency of the individual design alternatives.Conclusions, brief summary and potential implicationsOur results clearly indicate that it is important to consider cost-efficiency in the development of forest carbon stock assessments and the selection of remote sensing techniques. The development of MRV-systems for REDD need to be based on a sound optimization process that compares different data sources and sampling designs with respect to their cost-efficiency. This helps to reduce the uncertainties related with the quantification of carbon stocks and to increase the financial benefits from adopting a REDD regime.

Highlights

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes
The design alternative that used only field plots (SRS) and not any remote sensing derived auxiliary information consistently resulted in the largest percent standard errors
The functional pattern of sample size and percent standard error is similar for all design alternatives except stratified sampling; under stratified sampling the gain in precision with increasing sample size is more pronounced

Summary

Introduction

Countries willing to adopt a REDD regime need to establish a national Measurement, Reporting and Verification (MRV) system that provides information on forest carbon stocks and carbon stock changes. FAO [3] estimated an annual loss of carbon stocks in forest biomass of 0.5 Gt between 1990 and 2010, which is considered to be mainly a result of tropical deforestation. At their 16th meeting in Cancun in 2010, the Parties of the United Nations Framework Convention on Climate change (UNFCCC) approved the inclusion of a reduction of emissions from deforestation and forest. Countries willing to adopt a REDD regime need to establish a national system for Measurement, Reporting and Verification (MRV) that provides information on forest carbon stock changes. While some authors see MRV systems as easy-to-apply tools [6], others describe the difficulties of implementation and operational applications [7,8,9]

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Results

Conclusion