Abstract
BackgroundHigh fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama – one of the first UN REDD + partner countries.ResultsIntegrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide.ConclusionsThe national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection.
Highlights
Carbon accounting has reached the vanguard of national resource management
Airborne Light Detection and Ranging (LiDAR) mapping Top-of-canopy height (TCH) was measured at 1.1 m spatial resolution in systematically collected, national LiDAR sampling transects covering a total of 391,857 ha throughout Panama (Figure 1)
Calibration of airborne LiDAR top-of-canopy height (TCH) measurements to estimated aboveground carbon density (ACD) in 228 field plots ranging in size from 0.1-0.36 ha are highly predictive of field-estimated ACD across a range of vegetation types, from forests to grasslands, and across wide-ranging environmental conditions (Figure 2a, Additional file 1: Table S1; Additional file 2: Figure S1)
Summary
Carbon accounting has reached the vanguard of national resource management. The carbon stored in vegetation and soils is a vitally important component of national greenhouse gas mitigation strategies [1], and abrupt changes in carbon storage can indicate interruptions of other ecosystem services such as water quality and biodiversity [2,3]. Plot networks offer direct measurement of a tiny amount of actual forest [9], without an ability to report on spatially explicit carbon stocks and changes in those stocks (emissions). In response to this challenge, there has been rapidly growing interest in the use of geospatial mapping technologies to augment field plot inventories [10], and several new approaches have emerged to extend plotbased carbon estimates to millions of hectares [11], and even globally [12,13]. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama – one of the first UN REDD + partner countries
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