Sprawl and Biodiversity in Cross River State, Nigeria

The paper sought to determine the influence of sprawl on crop types and the diversity of birds, butterflies and bumblebees in agricultural lands. The research compared the number and species of crops cultivated, birds, butterflies and bumblebees diversity between 10 peripheral agricultural lands in sprawl areas and 10 peripheral agricultural lands outside sprawl areas. At each of the farms, five sampled points were used and the mean of all observations were used for the analysis. Canonical correlation analysis was used to determine the factors influencing the diversity of birds, butterflies and bumblebees on farmlands. While the difference in crop diversity between and within species was determined by Shannon Weiner diversity index. Butterflies, bumblebees and birds were significantly correlated with the crop diversity of farm lands. Also a positive relationship was observed amongst all inventoried variables. Farms with high crop diversity had high butterfly and bird diversity. The study has implication for the sustainability of biodiversity in urban places. Key words: Sprawl, biodiversity, peripheral lands, Cross River Stat

Impact of Logging on Non-Logged Species in the Moist Forest Region of South Eastern Nigeria

The study examined the effects of logging intensities on the quality, stocking levels and damage to non-logged species. Data was collected using stock inventory methods (SIM) in the tropical rainforest of Ekukunela, Cross River State in South Eastern Nigeria. Four experimental plots of one hectares each were laid in the forested areas with different  logging  intensities (lightly logged, moderately logged, intensively logged) and a control plot which has not been logged (Primary forest).Only tree species up to 30 cm dbh and above were enumerated. The findings show that increasing logging rates directly reduced the quality and quantity of non-logged forest species in the sample plots. The highest number and best quality of species enumerated, were found in the unlogged tropical rainforest plot. Increased government and community participation in forest management, more effective training, better funding, and improved monitoring of logging practices were recommended, Key words: Community forestry, Logging intensities, Stocking levels, Unlogged species, Tropical rainforest.

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