Monitoring land use and soil salinity changes in coastal landscape: a case study from Senegal.

Soil salinity is a major issue causing land degradation in coastal areas. In this study, we assessed the land use and soil salinity changes in Djilor district (Senegal) using remote sensing and field data. We performed land use land cover changes for the years 1984, 1994, 2007, and 2017. Electrical conductivity was measured from 300 soil samples collected at the study area; this, together with elevation, distance to river, Normalized Difference Vegetation Index (NDVI), Salinity Index (SI), and Soil-Adjusted Vegetation Index (SAVI), was used to build the salinity model using a multiple regression analysis. Supervised classification and intensity analysis were applied to determine the annual change area and the variation of gains and losses. The results showed that croplands recorded the highest gain (17%) throughout the period 1984-2017, while forest recorded 3%. The fastest annual area of change occurred during the period 1984-1994. The salinity model showed a high potential for mapping saline areas (R2 = 0.73 and RMSE = 0.68). Regarding salinity change, the slightly saline areas (2 < EC < 4 dS/m) increased by 42% whereas highly saline (EC > 8 dS/m) and moderately saline (4 < EC < 8 dS/m) areas decreased by 23% and 26%, respectively, in 2017. Additionally, the increasing salt content is less dominant in vegetated areas compared with non-vegetated areas. Nonetheless, the highly concentrated salty areas can be restored using salt-resistant plants (e.g., Eucalyptus sp., Tamarix sp.). This study gives more insights on land use planning and salinity management for improving farmers' resilience in coastal regions.

The relevance of using in situ carbon and nitrogen data and satellite images to assess aboveground carbon and nitrogen stocks for supporting national REDD + programmes in Africa.

BACKGROUND: 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. 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. RESULTS: The 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). CONCLUSION: The 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.

Erratum to: Allometric models and aboveground biomass stocks of a West African Sudan Savannah watershed in Benin.

[This corrects the article DOI: 10.1186/s13021-016-0058-5.].

Allometric models and aboveground biomass stocks of a West African Sudan Savannah watershed in Benin.

BACKGROUND: The estimation of forest biomass changes due to land-use change is of significant importance for estimates of the global carbon budget. The accuracy of biomass density maps depends on the availability of reliable allometric models used in combination with data derived from satellites images and forest inventory data. To reduce the uncertainty in estimates of carbon emissions resulting from deforestation and forest degradation, better information on allometric equations and the spatial distribution of aboveground biomass stocks in each land use/land cover (LULC) class is needed for the different ecological zones. Such information has been sparse for the West African Sudan Savannah zone. This paper provides new data and results for this important zone. The analysis combines satellite images and locally derived allometric models based on non-destructive measurements to estimate aboveground biomass stocks at the watershed level in the Sudan Savannah zone in Benin. RESULTS: We compared three types of empirically fitted allometric models of varying model complexity with respect to the number of input parameters that are easy to measure at the ground: model type I based only on the diameter at breast height (DBH), type II which used DBH and tree height and model type III which used DBH, tree height and wood density as predictors. While for most LULC classes model III outperformed the other models even the simple model I showed a good performance. The estimated mean dry biomass density values and attached standard error for the different LULC class were 3.28 ± 0.31 (for cropland and fallow), 3.62 ± 0.36 (for Savanna grassland), 4.86 ± 1.03 (for Settlements), 14.05 ± 0.72 (for Shrub savanna), 45.29 ± 2.51 (for Savanna Woodland), 46.06 ± 14.40 (for Agroforestry), 94.58 ± 4.98 (for riparian forest and woodland), 162 ± 64.88 (for Tectona grandis plantations), 179.62 ± 57.61 (for Azadirachta indica plantations), 25.17 ± 7.46 (for Gmelina arborea plantations), to 204.92 ± 57.69 (for Eucalyptus grandis plantations) Mg ha-1. The higher uncertainty of agroforestry system and plantations is due to the variance in age which affects biomass stocks. CONCLUSION: The results from this study help to close the existing knowledge gap with respect to biomass allometric models at the watershed level and the estimation of aboveground biomass stocks in each LULC in the Sudan Savannah in West Africa. The use of model type I, which relies only on the easy to measure DBH, seems justified since it performed almost as good as the more complex model types II and III. The work provided useful data on wood density of the main species of the Sudan Savannah zone, the related local derived biomass expansion factor and the biomass density in each LULC class that would be an indispensable information tool for carbon accounting programme related to the implementation of the Kyoto Protocol and REDD+ (reducing emissions from deforestation and forest degradation, and forests conservation, sustainable management of forests, and enhancement of forest carbon stocks) initiatives.