Advances and Applications in Statistics
Volume 89, Issue 2, Pages 203 - 225
(October 2023) http://dx.doi.org/10.17654/0972361723058 |
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GEOSPATIAL MODELLING OF FOREST CARBON STOCKS IN BURKINA FASO, WEST AFRICA
Fabrice Ouoba, Larba Hubert Balima, Hay Yoba Talkibing and Diakarya Barro
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Abstract: Protected areas in West Africa play a crucial role in climate change mitigation as the major carbon pools. Yet, the spatial distribution of forest carbon stocks is poorly documented, but required for forest management and carbon monitoring. Assessing the spatial distribution of aboveground biomass and carbon stocks is important for the monitoring of carbon sinks and sources within the national adaptation framework. This paper analyzes the spatial distribution of tree aboveground carbon stocks in two forests using geostatistical tools. We derived tree aboveground biomass and carbon stocks from two forests using field data of 2844 trees from 174 inventory plots. The distribution of forest carbon stocks was analyzed using geospatial modelling methods. We fitted different variogram models to carbon data and selected the best model for each forest. The best fitted model was then used to predict the spatial distribution of forest carbon stock using geostatistical analysis. The findings showed that the exponential variogram model better explains the spatial dependence of carbon stock in Bontioli forest, whereas the power variogram model better explains the spatial dependence of stock in Nazinga game ranch. The values of carbon density ranged between 10-45 Mg/ha in Nazinga to 18-35 Mg/ha in Bontioli reserve. This study provides a baseline for the geospatial modelling of forest carbon in West African ecosystems. Such studies should be extended to other forests for a better management of forest carbon in the region.
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Keywords and phrases: carbon stocks, spatial distribution, variogram, stationary process.
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