Quantification of regional carbon stocks in the ecoregions of Cross River State, Nigeria

Quantification of above-ground biomass over the Cross River State, Nigeria using Sentinel 2 data: Higher-resolution wall-to-wall carbon monitoring in tropical Africa across a range of woodland types is necessary in reducing uncertainty in the global carbon budget and improving accounting for REDD+. This study uses Sentinel-2 multispectral imagery combined with climatic and edaphic variables to estimate the regional distribution of above-ground biomass (AGB) for the year 2020 over the CRS, a tropical forest region in Nigeria, using the Random Forest (RF) machine learning. Forest Inventory plots were collected over the whole state for training and testing of the RF algorithm, and spread over undisturbed and disturbed tropical forests, and woodlands in croplands and plantations. The maximum plot AGB was estimated to be 588 t/ha with an average of 121.98 t/ha across the entire CRS. The AGB was estimated using Random Forest and yielded an R2 of 0.88, RMSE of 40.9 t/ha, a relRMSE of 30 %, bias of +7.5 t/ha and a total woody AGB of 0.246 Pg for CRS. These results compare favourably to previous tropical AGB products; with total AGB of 0.290, 0.253, 0.330 and 0.124 Pg, relRMSE of 49.69, 57.09, 24.06 56.24 % and -41, -48, -17 t/ha bias over the CRS for the Saatchi, Baccini, Avitabile and ESA CCI maps respectively. These are all compared to the current REDD+ estimate of total AGB over the Cross River State of 0.268 Pg. This study shows that obtaining independent reference plot datasets, from a variety of woodland cover types, can reduce uncertainties in local to regional AGB estimation compared with those products which have limited tropical African and Nigerian woodland reference plots. Though REDD+ biomass in the region is relatively larger than the estimates of this study, REDD+ provided only regional biomass rather than pixel-based biomass and used estimated tree height rather than the actual tree height measurement in the field. These may cast doubt on the accuracy of the estimated biomass by REDD+. These give the biomass map of this current study a comparative advantage over others. The 20 m wall-to-wall biomass map of this study could be used as a baseline for REDD+ Monitoring, Evaluation and Reporting for equitable distribution of payment for carbon protection benefits and its management. Digital mapping of soil organic carbon from sentinel-2 data in the tropical ecosystem of Cross River State, southeast-Nigeria: Digital mapping of Soil organic carbon (SOC) is fundamental in achieving the mandates of the REDD project. As an essential climate variable, SOC is a constituent of the ecological system that supports chemical, biological and physical processes and can be used to infer the quality of the ecosystem. In Nigeria, estimates revealed that 40 percent of greenhouse gas (GHG) emissions comes from the forestry and land use sector. On the strength of this, the quantification of the total SOC stock in CRS Nigeria, will aid in putting in place land use policies that will achieve the twin goal of SOC protection and enhance the living conditions of those whose livelihood is nature dependent. This study used random forest (RF) regression; a machine learning algorithm to identify key predictors of SOC through the integration of field, Sentinel 2A (S2) derived vegetation indices, selected reanalysis climate variables with topography. Three land cover types (LCTs); undisturbed, disturbed and croplands were purposively mapped out, and 72 soil samples collected at soil depth of 20 cm across the study area. 70 % of points data were used to train the RF model while the remaining 30 % was used to validate the predicted SOC model. We estimated 0.147 Pg with mean of 72.94 t/ha of SOC compared to African Soil Information Service (fSIS) 0.124 Pg and Innovative Solution for Digital Agriculture (ISDA) 0.217 Pg of SOC over the area. Model analysis indicates that key predictors (topography, rainfall, maximum air temperature, OSAVI, EVI and NDVI) achieved a high prediction accuracy with lower uncertainty unlike the global and continental SOC maps over the study area (R2 of 0.82, RMSE of 22.54 (t/ha), and uncertainty of 39.4 % compared to AfSIS; RMSE=35.29 t/ha, uncertainty=61.69 % and iSDA; RMSE= 38.58 t/ha, uncertainty=57.21 %). Our results showed lower uncertainty compared to the coarse spatial resolution maps of AfSIS (30 m) and ISDA (250 m). The final model output was used to spatialize the SOC distribution across the CRS subregion using ArcGIS package. The 20 m resolution SOC map of this study could be referenced in the REDD+ Monitoring, Evaluation and Reporting for equitable distribution of payment for carbon protection benefits and its management. Livelihood impacts of forest carbon protection in the context of redd+ in Cross River State, southeast Nigeria: The rate of landcover change linked to deforestation and forest degradation in tropical environments has continued to surge despite series of forest governance policy instruments over the years. These informed the launch of one of the most important international policies called Reducing Emission from Deforestation and Forest Degradation Plus (REDD+) to combat forest destruction. REDD+ assumes that communities will have increased access to natural capital which will enhance their livelihood portfolio and mitigate the effects of climate variability and change across biomes. The aim of this study is to ascertain the livelihoods impacts of forest carbon protection within the context of REDD+ in Cross River State, Nigeria. Six forest communities were chosen across three agroecological zones of the State. Anchored on the Sustainable Livelihood Framework, a set of questionnaires were administered to randomly picked households. The results indicate that more than half of the respondents aligned with financial payment and more natural resources as the perceived benefits of carbon protection. More so, a multinomial logistic regression showed that income was the main factor that influenced respondent’s support for forest carbon protection. Analysis of income trends from the ‘big seven’ non-timber forest resources in the region showed increase in Gnetum africanum, Bushmeat, Irvingia gabonensis, Garcinia kola, while carpolobia spp., Randia and rattan cane revealed declining income since inception of REDD+. The recorded increase in household income was attributed to a ban in logging. It is recommended that the forest communities should be more heavily involved in the subsequent phases of the project implementation to avoid carbon leakages.