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 a 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 assets 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

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 Reducing Emissions from Deforestation and forest Degradation Plus (REDD+). This study uses Sentinel-2 multispectral imagery combined with climatic and edaphic variables to estimate the regional distribution of aboveground biomass (AGB) for the year 2020 over the Cross River State, a tropical forest region in Nigeria, using 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 AGB plot was estimated to be 588 t/ha with an average of 121.98 t/ha across the entire Cross River State. AGB estimated using random forest 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 regional AGB of 0.246 Pg for the Cross River State. These results compare favorably 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 and 56.24% and −41, −48, −17 and −50 t/ha bias over the Cross River State 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