Abstract

The lack of capacity to monitor forest carbon stocks in developing countries is undermining global efforts to reduce carbon emissions. Involving local people in monitoring forest carbon stocks could potentially address this capacity gap. This study conducts a complete expert remeasurement of community-led biomass inventories in remote tropical forests of Papua New Guinea. By fully remeasuring and isolating the effects of 4,481 field measurements, we demonstrate that programmes employing local people (non-experts) can produce forest monitoring data as reliable as those produced by scientists (experts). Overall, non-experts reported lower biomass estimates by an average of 9.1%, equivalent to 55.2 fewer tonnes of biomass ha-1, which could have important financial implications for communities. However, there were no significant differences between forest biomass estimates of expert and non-expert, nor were there significant differences in some of the components used to calculate these estimates, such as tree diameter at breast height (DBH), tree counts and plot surface area, but were significant differences between tree heights. At the landscape level, the greatest biomass discrepancies resulted from height measurements (41%) and, unexpectedly, a few large missing trees contributing to a third of the overall discrepancies. We show that 85% of the biomass discrepancies at the tree level were caused by measurement taken on large trees (DBH ≥50cm), even though they consisted of only 14% of the stems. We demonstrate that programmes that engage local people can provide high-quality forest carbon data that could help overcome barriers to reducing forest carbon emissions in developing countries. Nonetheless, community-based monitoring programmes should prioritise reducing errors in the field that lead to the most important discrepancies, notably; overcoming challenges to accurately measure large trees.

Highlights

  • Potential exists to mitigate anthropogenic climate change by reducing the rates of forest carbon loss and increasing forest carbon sequestration [1]

  • We explored the influence of the discrepancy in diameter at breast height (DBH) (% error) and height (% error) on discrepancy in tree biomass (% error) using a Generalised Linear Model (GLM) for trees that had both DBH and height measurements from expert and non-experts

  • First we present the final summary of the errors identified through our hierarchal approach; we explore in details the different error types for each field measurements to further understand why non-experts produced generally lower biomass values

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Summary

Introduction

Potential exists to mitigate anthropogenic climate change by reducing the rates of forest carbon loss and increasing forest carbon sequestration [1]. Acknowledging this potential, the PLOS ONE | DOI:10.1371/journal.pone.0130529. Field inventories are resource intensive because they require teams of experts to work, often in remote locations, for extended periods. For this reason, the capacity of most developing countries falls short of the requirements needed to monitor forest carbon stocks.

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