FACULTY OF RENEWABLE NATURAL RESOURCES
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Item Factors Influencing Spatio-Temporal Variation of Urban Green Space in Ado-Ekiti Metropolis(Commonwealth Forestry Association (CFA) Conference, Nigeria Chapter Federal, 2020) Alegbeleye, O. M.; Alo, A. A.Geographic Information Systems (GIS) and Remote Sensing (RS) have proven to be an accurate means of determining Urban Green Space (UGS), extent and pattern of changes in land use land cover of a large area of land over time. However, there is dearth of information on spatial variation of UGS and its perceived factors in Ado -Ekiti. Therefore, this study adopted RS and GIS techniques to determine the factors responsible for the UGS changes in Ado -Ekiti metropolis. Map of Ado-Ekiti metropolis and Landsat imageries of 1987 (TM), 1998 (TM) and 2019 (OLI) were obtained. A set of 112 well -structured questionnaire was randomly administered to respondents in the study area. Map of Ado -Ekiti was georeferenced and digitized to obtain its shapefile. Landsat imageries were classified using the maximum likelihood algorithm of supervised classification in ArcGIS. The shapefile was superimposed on the classified imageries and clipped for determination of land use land cover sizes. The questionnaire were analyzed to determine the perceived factors responsible for the spatial variation in the UGS using logit regression model in STASTICA. Four land use land cover; Green spaces, Built-up area, water body and bare land, were identified in Ado-Ekiti metropolis. The UGS decreased from 76.1% in 1987to 32.1% in 2019. In the same vein, water body reduced from 0.3% to 0.1% in 1987 to 2019 respectively. However, built up area and bare land increased from 20.3% and 7.5% to 54.6% and 13.2% in 1987 to 2019, respectively. Spatial and temporal variation in UGS was significantly influenced by population growth (103760.20 Odds -Ratio) and demand land for agriculture (15.53 Odds-Ratio) as represented with the equation FAUGS =-26.78+11.50(PG) - 20.20(Poverty) – 15.04(LLE) - 12.59(DT) + 2.74(AGR). However, other factors, whose contributions were not significant include lack of law enforcement, demand for timber and poverty.Item Forested landscape dynamics in Saki-East local government area of Oyo State, Nigeria(Forests and Forest Products Society, 2021) Alo, A. A.; Onilude, Q. AThe prime objective of this study is to apply Remote Sensing and GIS technology in examining the trend and pattern of land cover changes observed between forested and non-forested landscapes in Saki east LGA of Oyo State, Nigeria. This was done for the purposes of determining changes in the vegetation cover for a period of 27 year. Satellite Imageries were obtained from Global Land Cover Facility (GLCF) and GLOVIS. Landsat Thematic Mapper of 1992, 2001, 2010 and Operational Land Imager of 2019 were obtained at 30m resolution. The Image analysis was done and created using ArcGis 10.5 (ESRI, Redland, CA). Satellite imagery was classified into two major categories, Forested landscape and Non-forested landscape. Results from satellite imageries also showed that forested landscape decreased from a total land area of 139,510 ha (84.53%) in 1992 to 102,480 ha (62.09%) in 2019. The amount of land area lost by forested landscape is being added up by the non-forested landscape. 2.53% of forested landscape was lost to non-forested between 1992-2001, with 18.05% and 1.86% lost between 2001-2010 and 2010-2019 respectively. However, percent change per year in lost of forested landscape observed was 0.28%, 2.01% and 0.21% between 1992-2001, 2001-2010 and 2010-2019 respectively. It was concluded that changes observed in forested landscape was due to deforestation to provide raw materials for wood industries, and space for agriculture and building of house for the increasing population in the area. The implications of deforestation for biodiversity and climate change have been highlighted.Item Geospatial Assessment of Akure Forest Reserve in Ondo State, Nigeria(Forests and Forest Products Society, 2022) Alo, A. A.; Komolafe, O.O.Land Use Land Cover (LULC) changes is one of the significant factors that determines the interaction between humans and its environment in the tropics. In Nigeria, the effect of these anthropogenic activities has led to deforestation and consequent degradation. However, there is dearth of information on the dynamics of many forests cover in Southwestern Nigeria, especially in Akure Forest Reserve. Therefore, this study aimed at assessing the LULC change of Akure forest reserve. Landsat imageries (5 TM of 1984, 7 ETM+ of 2000, and 8 OLI/TIRs of 2016 and 2021were obtained and processed. The processed imageries were analyzed using supervised Maximum Likelihood Classification algorithm to determine LULC classes of Akure forest reserve. The LULC classification followed Anderson darling categorization. Five LULC classes were used: Dense Forest (DF), Less Dense Forest (LDF), Built‐Up (BU), Bare Land (BL) and Water Bodies. Normalized difference Vegetation Index (NDVI) was used to determine the greenness of the reserve. Dense Forest has drastically reduced from 82.6% observed in 1984 to 26.41% in 2021, indicating high level of forest deforestation and degradation, while an upsurge was observed in LDF from 1984 (14.19%) to (55.03%) in year 2021. Changes in BU fluctuated between 0.51% in 1984 and 3.16% in 2021. The highest (0.4) and lowest (0.3) NDVI were recorded in 2016 and 2000. Dense forest cover in Akure Forest Reserve has been converted to agricultural activities. Therefore, there is need for conservation of the forest resources to preclude depletion.Item Aboveground biomass allometric models for a private semi-natural forest in Nigeria(AJOL (African Journal of Open Libraries), 2023) Alade, A.A.; Oluwajuwon, T.V.; Alo, A. A.; Ogana, F.N.; Aghimien, E.VPrivate forests with conservation priority such as Abayomi Farm Estate (AFE) Emerald forest reserve, Nigeria can significantly contribute to the global carbon cycle while enhancing sustainable livelihoods. However, little consideration is given to accounting for their biomass pools and carbon sequestration. This study, therefore, developed models for estimating aboveground biomass in the private semi-natural forest. Four (4) temporary sample plots (TSPs) of 50 x 50 m were systematically sampled with a complete, non-destructive enumeration of 176 individual tree species with a diameter at breast height (DBH) > 10 cm. Aboveground biomass models were developed using the enumerated parameters covering a wide range of DBH and total height (H), as well as wood density (WD) as predictor variables. The models were developed for the two most-abundant, native tree species and all species combined in the forest. The models were evaluated using different indices such as coefficients of determination (R2), root mean square error (RMSE). Selected models were cross-validated. The species-specific biomass models with double predictors proved more accurate and reliable for estimating aboveground biomass in the forest than the DBH-only allometry, with their adjusted R2 as high as 95 % and RMSE < 0.23. Mixed-species allometry fitted by all the three predictors (DBH, H and WD) was the most suitable, depicting the added relevance of wood density and sample size in biomass modelling. It recorded RMSE and adjusted R2 of 0.22 and 97 %, respectively. Overall, all the models provided good estimates and could be used for assessing the carbon storage in the forest estateItem Spatio–Temporal Variation of Chlorophyll, Nutrients and Productivity in Lagos Lagoon, Lagos Nigeria Using Remote Sensing Approach(Sciencedomain International, 2022) Adewoyin, J. E.; Olaifa, F. E.; Alo, A. A.; Kappo, A.; Muibi, K. H.Spatio–temporal variation in Chlorophyll, Nutrients and Primary Productivity of some selected sampling stations in Lagos lagoon were investigated using conventional method from November 2019 to July 2020, in order to compare the result with data from satellite image using MODIS Aqua. Global Positioning Receiver was used to capture the geographic coordinates of the sampling stations. Water sampling was carried out monthly using standard methods during wet and dry seasons. The observed data were subjected to statistical analysis using Microsoft Excel and SPSS. version 20. In wet season, the highest mean value for Chlorophyll a (1.15±0.02 μg/L) was recorded in Ofin while the lowest values (0.06±0.01 μg/L) was observed in Okobaba. During the dry season, the highest mean value (0.75±0.10 μg/L) was in Ofin while the lowest mean value (0.27±0.0.08 μg/L) was recorded in Ibeshe. The MODIS satellite variation in chlorophyll-a showed that the highest value of highest recorded value (1.37±0.00 μg/L) was in wet season (Ijede) while the lowest value (0.12±0.01 μg/L) was observed in dry season (Okobaba). The highest transparency value (0.97±0.01 mg/L) was recorded in dry season (Ofin) while the lowest value (0.35±0.25 mg/L) was recorded in wet season (Oworonsoki). The highest mean value of Surface Sea temperature was recorded in the dry season of Apapa (30.28±1.15oC) while the lowest mean value (26.41±1.15oC) was observed in Okobaba in the wet season. The chlorophyll-a concentration analyzed using standard method and MODIS satellite, in both dry and wet seasons in the sampled stations differ greatly from one another in terms of the mean concentration. The primary productivity of Lagos Lagoon was relatively low, with no significant spatial variations between sampling stations. The results of sea surface temperature, transparency and chlorophyll ‘a’ estimation from the MODIS revealed that the values were positively correlated with laboratory result with r2-value of 0.67, 0.80 and 0.77. This indicates that MODIS data and laboratory results generated for Lagos Lagoon were positively related.Item Spatial Distribution of Soil Moisture Content and Tree Volume Estimation in International Institute of Tropical Agriculture Forest, Ibadan, Nigeria(Scientific Research Publishing, 2022) Alo, A. A.; Agbor, C. F.; Jebiwott, A.; Temiloluwa, O.The role of soil moisture in the survival and growth of trees cannot be overemphasized and it contributes to the net productivity of the forest. However, information on the spatial distribution of the soil moisture content regarding the tree volume in forest ecosystems especially in Nigeria is limited. Therefore, this study combined spatial and ground data to determine soil moisture distribution and tree volume in the International Institute of Tropical Agriculture (IITA) forest, Ibadan. Satellite images of 1989, 1999, 2009 and 2019 were obtained and processed using topographic and vegetation-based models to examine the soil moisture status of the forest. Satellite-based soil moisture obtained was validated with ground soil moisture data collected in 2019. Tree growth variables were obtained for tree volume computation using Newton’s formular. Forest soil moisture models employed in this study include Topographic Wetness Index (TWI), Temperature Dryness Vegetation Index (TDVI) and Modified Normalized Difference Wetness Index (MNDWI). Relationships between index-based and ground base Soil Moisture Content (SMC), as well as the correlation between soil moisture and tree volume, were examined. The study revealed strong relationships between tree volume and TDVI, SMC, TWI with R2 values of 0.91, 0.85, and 0.75, respectively. The regression values of 0.89 between in-situ soil data and TWI and 0.83 with TDVI ascertain the reliability of satellite data in soil moisture mapping. The decision of which index to apply between TWI and TDVI, therefore, depends on available data since both proved to be reliable. The TWI surface is considered to be a more suitable soil moisture prediction index, while MNDWI exhibited a weak relationship (R2 = 0.03) with ground data. The strong relationships between soil moisture and tree volume suggest tree volume can be predicted based on available soil moisture content. Any slight undesirable change in soil moisture could lead to severe forest conditions.Item Mapping the trends of forest cover change and associated drivers in Mau Forest, Kenya(Elsevier, 2021) Jebiwott, A.; Ogendi, G. M.; Agbeja, B. O.; Alo, A. A.; Kibet, R"Mau Forest in the Rift Valley in Kenya is the largest of the five major water towers in the country and also the largest indigenous montane forest in Eastern Africa. As such, the forest is an important natural resource base not only to the local economy but to the East African region at large. In spite of this, the forest has been highly degraded owing to immense anthropogenic pressure from the forest surrounding communities. The aim of this study was to assess the trends in forest cover and the driving forces leading to its change. Landsat TM images of 1984 and 1995, ETM+of 2008, and OLI/TIRS of 2020 were used to depict the trend in forest cover for the period between 1984 and 2020. Focus Group Discussions (FGD) and in-depth interviews were also used to get the perceptions and experiences of the local people regarding the trend in forest cover and the associated driving forces. The results from the qualitative data were integrated with those of remote sensing for assessment of trend in forest cover. The study findings indicate a decline of 25.2% of forest cover within the Mau Forest complex in a period four years shy of four decades, amounting to approximately 699 km2 of tree cover. This trend was fueled by an increasing demand for agricultural land where farmlands increased by 69.9%, as well as logging-legal or illegal-where grassland area increased by 37.2%. Three major drivers of forest cover change identified by the participants include human settlements, logging and expansion of farmlands. We recommend that forest policymakers and managers involve the local community, as the main stakeholders, in all levels of decision making and management so as to promote sustainable use of forest resources and improved management of the forest."Item Human Settlements Interactions and Deforestation in Gambari Forest Reserve located in Oluyole Local Government Area (LGA) of Oyo State, Nigeria(The University of Port Harcourt, 2021) Agbor, C. F.; Alo, A. A.; Aigbokhan, O.J .This study was designed to examine changes in land cover types and the interaction of human settlements with the forest and impact of such interaction on the reserve. Community leaders and randomly selected community dwellers in each of the selected settlements were sampled for group discussion to obtain information on population and services of the forest that attract them to the reserve. Landsat images of 1984 and 2019 were used to extract land cover types using maximum likelihood classifier in Idrisi environment. The level of attractiveness and Interactions of the communities with the reserve were determined employing gravitational model. Results show that there was an increase in the size and number of settlements within the study area and decrease in in forest cover by 34% and 6.02% respectively. It was also revealed from the study that about 39% of the total area was taken over by development (building, roads and other classes) within the forest reserve, while 3% of the developed area gave way to forest cover. The degraded parts of the reserve in recent time was about 16% of the total reserve area and about 78% remained forest cover. From the results it is obvious that the level of interaction and imparts of such interaction depends on the community’s population size rather than distance. It is therefore imperative to regulate the activities of adjoining communities and those within the Gambari forest reserve by appropriate authorities.Item The Use of Forest Inventory in Estimating Illegally Felled Trees of Tectonagrandis Plantation in Agudu Forest Reserve,Lafia, Nasarawa State, Nigeria(Redshine Publication, 2019) Egbewole Z. T.; Rotowa O. J.; Alo, A. A.; Ojo A. S.; Oluwasanmi T. D.; Enenche J. A.; Oluwaseesin, M. BThe aim of this study is to evaluate the Use of Forest Inventory in Estimating Illegally Felled Trees of Tectonagrandis Plantation in Agudu Forest Reserve. Seven (7)plots were randomly selected from different area of the whole plantation. Perimeter measurement for each plot were; Permanent Sample Plot 1 (PSP1) to (PSP3) and Temporary Sample Plot 4 (TSP4) to Temporary Sample Plot 7(TSP7) with size 30m by 30m each totaling 0.63ha. Six (6) mean trees in respect of girth class and height class and 1 plus tree were identified and the stumps of felled trees were measured in each of the 7plots. The study was laid out in a 7 x 6 x 6 factorial experiment in a Randomized Complete Block Design (RCBD) with a total of 252 treatment combinations in order to facilitate the interpretation of the main and the evolving interaction effect. Treatments were analyzed with respect to 7 Sample plots, 6 girth classes and 6 height classes. It was observed that a total of 640 Teak stand and 250 stumps of felled trees on 7plots of size 30m by 30m each totaling 0.63ha.The average tree height was 14.56m, average merchantable height was 11.56m, total basal area (BA) for the 7plots was 48.15m2 and the mean BA was 0.08m2. Total tree Volume (using Newton’s fomular) was 147.69m3 and the mean volume/tree was 0.23m3. The average stump girth (SG) was 30.54cm, 0.09m2 Stump Basal area, the estimated mean tree height was 14.34m while the average Estimated Stump Volume (ESvol) was 0.62m3. The Total Stump Basal area for the whole 250 felled tree stumps was 21.44m2 on the 0.63ha sampled plots, this will amount to 34.03m2/ha while the Total Estimated Stump Volume (ESvol) was 154.18m3 on 0.63ha sampled plots, this will amount to 244.73m3/ha. Based on ‘International prices for teak: Historical and current, and price forecasts’ the World Market Price of Teak as at 2018 is put at 1221.31USD/m3at N355/USD, this will amount to (N433565.1/m3x 244.73m3/ha x 161.28ha) the sum of N17,112,838,083.00 equivalent to a total loss of about (48,205,177.70USD)of felled Teakat 2018 year ending.Comparing all the models tried in this study using the fit statistics, model2: ESV = -0.26 – 1.71BD + 11.38BAs + 0.03MeanTHp ……………….Eq23.With basal diameter (BD), Basal area and mean Tree Height as the independent variables which had (R2 = 99.80, SEE = 0.02, with a negative intercept of -0.26) is the most appropriate prediction model. For predicting tree stump volume of Teak in Agudu Forest Reserve, the 5 ranked models are considered fit because they meet the basic requirement of a good fit model having negative intercept whereas the rest model with positive intercept may be discarded. The stand volume equations, which incorporated various tree growth variables, will enhance future yield prediction of the trees in the study areas since they provide quantitative basis for estimating stand growth parameters. It is believed that these models and volume prediction equations will enhance sound and informed management decisions and conservation measures for the remaining Tectonagr and is stands.Item "Development of digital elevation model for Okomu National Park, Nigeria"(TMKarpiński Publisher, 2018) Chukwu, O.; Alo, A. A.; Ezenwenyi, J. U.The type of soil, fauna and flora species that are found in an environment is affected by the elevation characteristics of the land. However, the ability to provide techniques and model that will effectively explain the elevation patterns of protected areas will aid sustainable management of the forest and its resources. This study developed Digital Elevation Model (DEM) for Okomu National Park, Nigeria. Point coordinates (2,272) with their respective elevations were randomly obtained covering the entire study area. Interpolated natural neighbor algorithm of the Quantum Geographic Information System was used to generate Digital Elevation Model for the National Park from the elevation data. Topographic map was extracted from the DEM at an interval of 10 m from one another. It was observed that the elevation in the study area ranged from 19 m to 105 m with an average of 56.32 m above sea level. Hence, the parkland is regarded as a gentle slope. This study revealed that the study area is not prone to flood or runoff due to its gentle slope nature. Therefore, this study is recommended as baseline information for ecological management as well as guide in the development of conservation strategies for flora and fauna species in the study area.