Abstract
BackgroundTo reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed. This allows a better representation of the spatial distribution of carbon and nitrogen stocks across LULC. The aim of this study was to emphasize the relevance of using in situ carbon and nitrogen content of the main tree species of the site when quantifying the aboveground carbon and nitrogen stocks in the context of carbon accounting. This paper contributes to that, by combining satellite images with in situ carbon and nitrogen content in dry matter of stem woods together with locally derived and published allometric models to estimate aboveground carbon and nitrogen stocks at the Dassari Basin in the Sudan Savannah zone in the Republic of Benin.ResultsThe estimated mean carbon content per tree species varied from 44.28 ± 0.21% to 49.43 ± 0.27%. The overall mean carbon content in dry matter for the 277 wood samples of the 18 main tree species of the region was 47.01 ± 0.28%—which is close to the Tier 1 coefficient of 47% default value suggested by the Intergovernmental Panel on Climate Change (IPCC). The overall mean fraction of nitrogen in dry matter was estimated as 0.229 ± 0.016%. The estimated mean carbon density varied from 1.52 ± 0.14 Mg C ha−1 (for Cropland and Fallow) to 97.83 ± 27.55 Mg C ha−1 (for Eucalyptus grandis Plantation). In the same order the estimated mean nitrogen density varied from 0.008 ± 0.007 Mg ha−1 of N (for Cropland and Fallow) to 0.321 ± 0.088 Mg ha−1 of N (for Eucalyptus grandis Plantation).ConclusionThe results show the relevance of using the in situ carbon and nitrogen content of the main tree species for estimating aboveground carbon and nitrogen stocks in the Sudan Savannah environment. The results provide crucial information for carbon accounting programmes related to the implementation of the REDD + initiatives in developing countries.
Highlights
To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed
The aim of this study was to quantify the aboveground carbon and nitrogen stocks at the landscape level for the current (2013–2014) land use/land cover at the scale of a watershed in the West African Sudan Savannah using in situ carbon and nitrogen content of the main tree species of the site
The lowest carbon content of dry matter was obtained for Combretum glutinosum with the mean of the species of 44.72 ± 0.44% and the highest for Acacia seyal with the mean of the species of 46.50 ± 0.68%
Summary
To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on the carbon density per land use/land cover (LULC) class and in situ carbon and nitrogen data is needed. This allows a better representation of the spatial distribution of carbon and nitrogen stocks across LULC. Reducing emissions from deforestation and degradation, biodiversity conservation, sustainable forest management and enhancement of forest carbon stocks (REDD +) in developing countries has become important frameworks to mitigate climate change and limit the rise in global temperature to no more than 2 °C [1,2,3]. The accuracy of the estimation of mean carbon and nitrogen density for each land use/ land cover class depends thereby on reliable carbon and nitrogen content estimates per main tree species, species frequency estimates per land use/land cover class and the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from tree census data [8]
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.