Error propagation and scaling for tropical forest biomass estimates

Chave, Jérôme; Chust, Guillem; Condit, Richard; Aguilar, Salomón; Hernández, Andrés; Lao, Suzanne; Pérez, Rolando

doi:10.1093/acprof:oso/9780198567066.003.0013

Cited by 177 publications

(311 citation statements)

References 499 publications

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“…Greater uncertainty in the N region is caused by generally weaker relationships between environmental variables and measured ACD (Figure 5). Nonetheless, a 35% uncertainty at the pixel level is on par with errors inherent to field inventory plots [30,31], and when averaged over much larger jurisdictional scales of thousands to millions of hectares, the overall uncertainty drops to extremely low values [3,17]. …”

Section: Resultsmentioning

confidence: 99%

Human and environmental controls over aboveground carbon storage in Madagascar

Asner

Clark

Mascaro

et al. 2012

Carbon Balance Manage

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BackgroundAccurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar.ResultsWe found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR.ConclusionsHigh-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.

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Section: Resultsmentioning

confidence: 99%

Human and environmental controls over aboveground carbon storage in Madagascar

Asner

Clark

Mascaro

et al. 2012

Carbon Balance Manage

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“…This diagram is for illustrative purposes and should not be seen as an attempt to set out a comprehensive list of all errors, for all estimates of AGB. The references included are: [17], [19], [23], [28], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42].…”

Section: Discussionmentioning

confidence: 99%

Are Inventory Based and Remotely Sensed Above-Ground Biomass Estimates Consistent?

et al. 2013

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Carbon emissions resulting from deforestation and forest degradation are poorly known at local, national and global scales. In part, this lack of knowledge results from uncertain above-ground biomass estimates. It is generally assumed that using more sophisticated methods of estimating above-ground biomass, which make use of remote sensing, will improve accuracy. We examine this assumption by calculating, and then comparing, above-ground biomass area density (AGBD) estimates from studies with differing levels of methodological sophistication. We consider estimates based on information from nine different studies at the scale of Africa, Mozambique and a 1160 km2 study area within Mozambique. The true AGBD is not known for these scales and so accuracy cannot be determined. Instead we consider the overall precision of estimates by grouping different studies. Since an the accuracy of an estimate cannot exceed its precision, this approach provides an upper limit on the overall accuracy of the group. This reveals poor precision at all scales, even between studies that are based on conceptually similar approaches. Mean AGBD estimates for Africa vary from 19.9 to 44.3 Mg ha−1, for Mozambique from 12.7 to 68.3 Mg ha−1, and for the 1160 km2 study area estimates range from 35.6 to 102.4 Mg ha−1. The original uncertainty estimates for each study, when available, are generally small in comparison with the differences between mean biomass estimates of different studies. We find that increasing methodological sophistication does not appear to result in improved precision of AGBD estimates, and moreover, inadequate estimates of uncertainty obscure any improvements in accuracy. Therefore, despite the clear advantages of remote sensing, there is a need to improve remotely sensed AGBD estimates if they are to provide accurate information on above-ground biomass. In particular, more robust and comprehensive uncertainty estimates are needed.

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“…To account for errors associated with estimating AGC [43], we (1) collected data on d.b.h., height and species of each tree, to use the best available allometric equations, (2) merged data collected in plots sampled within a transect, to maximize the area sampled per data point, and (3) evaluated the representation achieved by our sampling design. We followed the conventional assumption that half of a tree’s biomass consists of carbon [44].…”

Section: Methodsmentioning

confidence: 99%

“…Even though these equations should not be used for trees outside the range size for which they were built, they remain the best available method to estimate this crucial component of total tree aboveground biomass [43]. Specific wood densities were calculated from the average wood density referenced for each species in the global wood density database [44], [46].…”

Section: Methodsmentioning

confidence: 99%

Can REDD+ Help the Conservation of Restricted-Range Island Species? Insights from the Endemism Hotspot of São Tomé

Lima

Olmos²,

Dallimer

et al. 2013

PLoS ONE

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REDD+ aims to offset greenhouse gas emissions through “Reduced Emissions from Deforestation and forest Degradation”. Some authors suggest that REDD+ can bring additional benefits for biodiversity, namely for the conservation of extinction-prone restricted-range species. Here, we assess this claim, using São Tomé Island (Democratic Republic of São Tomé and Príncipe) as a case study. We quantified the abundance of bird and tree species, and calculated the aboveground carbon stocks across a gradient of land-use intensity. We found a strong spatial congruence between carbon and the presence and abundance of endemic species, supporting the potential of REDD+ to protect these taxa. We then assessed if REDD+ could help protect the forests of São Tomé and Príncipe. To do so, we used OSIRIS simulations to predict country-level deforestation under two different REDD+ designs. These simulations showed that REDD+ could promote the loss of forests in São Tomé and Príncipe through leakage. This happened even when additional payments for biodiversity were included in the simulations, and despite São Tomé and Príncipe having the fourth highest carbon stocks per land area and the second highest biodiversity values according to the OSIRIS database. These results show weaknesses of OSIRIS as a planning tool, and demonstrate that the benefits that REDD+ might bring for biodiversity are strongly dependent on its careful implementation. We recommend that payment for ecosystem services programmes such as REDD+ develop safeguards to ensure that biodiversity co-benefits are met and perverse outcomes are avoided across all tropical countries. In particular, we advise specific safeguards regarding the conservation of extinction-prone groups, such as island restricted-range species.

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Error propagation and scaling for tropical forest biomass estimates

Cited by 177 publications

References 499 publications

Human and environmental controls over aboveground carbon storage in Madagascar

Human and environmental controls over aboveground carbon storage in Madagascar

Are Inventory Based and Remotely Sensed Above-Ground Biomass Estimates Consistent?

Can REDD+ Help the Conservation of Restricted-Range Island Species? Insights from the Endemism Hotspot of São Tomé

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