FACULTY OF RENEWABLE NATURAL RESOURCES

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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.V
Private 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 estate
An Investigation of the Factors That Motivated Illegal Settlements in the Mau Forest, Kenya
(Scientific Research Publishing, 2021) Jebiwott1, A.; Ogendi, G. M.; Alo A. A.; Kibet, R.
The Mau Forest has in the recent past elicited serious political and environmental debates regarding its conservation status, as the forest is fast dwindling and the repercussions felt widely across the country. The forest, regarded as the largest indigenous montane forest in east Africa, has been hard hit by land-use changes mainly extensive and ill-planned human settlements. To save the forest, the government has resorted to forced evictions of the settlers. We sought to understand the drivers and causes for the observed illegal settlements in the Mau Forest. To collect data, we conducted focus group discussions and administered household questionnaires on evictees in the South-West and Eastern Mau. Data were analyzed using descriptive and inferential statistics. The results of the binary logistic regression model indicate that Poverty (p = 0.000), Agricultural production (p = 0.000) and Land Given by Government (p = 0.018) contributed significantly to the prediction of people’s motivation of settling in the Mau Forest. In conclusion, population pressure, laxity in forest law enforcement and insecure land tenure and politics were identified as some of the factors that motivated the observed rise in illegal settlements in Mau Forest. Such information on the factors that led to the illegal settlements in Mau Forest would be useful for forest conservation policy makers and managers. It will be a basis upon which interventions can be undertaken to enhance sustainable forest management in Kenya and beyond.
Assessment of land surface temperature and factors influencing urban green space dynamics in Sapele, Delta State of Nigeria
(Faculty of Agriculture, Usmanu Danfodiyo, Sokoto, Nigeria, 2024) Akintunde-Alo, D. A.; Joy, A.; Komolafe, O.O.
Forest is a carbon sink contributing to the tropical Land Surface Temperature (LST) changes. However, information on the nexus between Urban Green Space (UGS) and LST of most cities is limited. Therefore, spatiotemporal variability in UGS and LST, and factors affecting UGS dynamics were examined in Sapele, Delta State, Nigeria. Landsat imageries of 2002, 2012, and 2022 were obtained and classified using Iso Cluster Classification with point pixel-based correction for accuracy improvement. The LST was extracted from the imageries. Relationship between NDVI and LST was established using R. Structured questionnaire was used to elucidate information on factors affecting UGS (FAUGS); population growth (PG), lack of law enforcement (LLE), demand for timber (DT), agricultural expansion (AE), overgrazing (O), soil characteristics (SC), urban sprawl (US) and lack of land tenure system (LLTS), using logit regression at α=0.05. Four LULC were identified; UGS, water bodies, bare land, and built-up areas. The UGS decreased from 88.55% in 2002 to 81.83% in 2022, built-up area expanded from 4.64% to 12.55%. Highest mean LST (27.46°C) and lowest NDVI (0.54) were recorded in 2012, least LST (26.46°C) and highest NDVI (0.69) were recorded in 2002. Negative nexus was observed between NDVI and LST for 2002 (-0.453), to 2022 (-0.393). The odd ratio showed that PG (1.2x108), US (13.8), and LLTS (3.0) significantly affected UGS dynamics with the regression model (FAUGS) = -9.7 + 18.6(PG) – 8.0(LLE) - 23.61(DT) - 18.5(AE) -10.8(O) - 25.7(SC) + 2.6(US) + 1.1(LLTS). This study affirmed that urban green space was affected by urbanization.
Assessment of the availability and affordability of mushroom raw-materials in Ibadan metropolis
(Horticultural Society of Nigeria (HORTSON), 2023) Oladoja, S. A.; Ajewole, O. I.; Akintunde-Alo, D. A.; Ibe, R. B.
Mushroom is regarded as mother of all vegetables because of its roles in human nutritional supply with abundant number of essential vitamins, minerals and protein. However, there is dearth of information on what goes into its domestication, therefore this study assessed the availability and affordability of raw-materials for mushroom production in Ibadan metropolis with a view to encourage sustainable production for economic growth. Ibadan metropolis was purposively chosen based on the abundance of various institutions who are actively involved in the production of mushroom and presence of some trained farmers who are into the production. Information was elicited from 36 mushroom producers with the aid of structured questionnaire. Data were analysed using descriptive statistics such as frequencies and percentages. Findings revealed that 58.3% respondents rarely had materials for mushroom production whenever they intend to produce, 50% respondents cannot afford relevant materials needed for the production, while 30.5% respondents revealed that spawn production cost between 500-1,000 naira. Also, lack of capital and favourable environment are key factors contribution to no increase in mushroom production. It is therefore recommended that basic and necessary production materials be made available and accessible to producers at subsidized rates. In order to enhance production, credit support should be made available to producers at affordable interest rates.
Comparison of Four Distribution Functions for Fitting Diameter in Second Rotation Tectona grandis Linn. f. Plantations in Eda Forest Reserve, Nigeria
(Forest and Forest Products Society, 2017) Alo, A.A.; Chukwu, O.; Ogunleye, B. C.
Tree diameter is a very important variable in forestry; its accurate description is vital to planning if the forest is to be managed in a sustainable manner. Probability density functions are widely used for characterizing tree diameter. However, there is limited information on the diameter distribution for most of plantation in the country especially in the study area. Therefore, this research assesses the performance and suitability of beta, 3-parameter gamma, 3-parameter lognormal and 3-parameter Weibull distribution functions for fitting diameter at breast height (Dbh) of the second rotation of Tectona grandis Linn.F plantation in Eda Forest Reserve, Nigeria. Sixteen (16) temporary sample plots, (each 20 m x 20 m) were randomly selected across four second rotation age series (7, 8, 10 and 11years), whose originalages were 24, 31, 32 and 37 respectively. The distribution functions were fitted using maximum likelihood estimators. The performance of each function was tested using the Kolmogorov-Smirnov (K-S) statistic, Anderson Darling test, Chi-square, mean absolute error (MAE) and mean square error (MSE). The test results revealedthat 3-Parameter Weibull distribution was the most suitable for characterising Dbh. Weibull distribution had the least Kolmogorov-Smirnov statistic (0.0453), Anderson Darling test (1.231), Chi-square (24.9700), mean absolute error (0.0964) and mean square error (2.1688). Therefore, 3-parameter Weibull distribution is the best and recommended for fitting Dbh of second rotation T. grandis species in the study area for sustainable teak timber management.
Development of a location-enabled application for threatened tree species at the university of Ibadan, Nigeria.
(Forestry Research Institute of Nigeria (FRIN), 2024) Mustapha M.B.; Akintunde-Alo D. A.
Combining geospatial tools and data provision elements can greatly benefit threatened species management, particularly where location services are added. Therefore, this study was designed to develop a location-enabled mobile application for managing threatened trees within the University of Ibadan. The selection of threatened trees was based on the IUCN Red List. Threatened trees with a diameter at breast height of not less than 10cm within the University of Ibadan were identified to species level and wholly enumerated. The growth variables of each threatened tree were estimated, and each identified tree was georeferenced. Identified threatened trees were categorized based on their IUCN status, and the mean growth variables and the total number of trees, families and species per family were displayed. Icons on a map also represented identified trees to show their spatial. A data addition form was created, and the Google Firebase Real-time Database was used as a temporary repository of user-suggested data. A navigation system was also designed to navigate to threatened tree locations. A user-friendly mobile application called "UITTNav" was developed within the scope of this study. The application can be downloaded with the name "UITTNav" for free on the Google Play store without any restriction from June 2024. The application combines the ability to show where trees are, help users find their way to these trees, give detailed information about them, and allow users to suggest tree data. It will provide adequate location and tree data to manage threatened trees within the University of Ibadan.
"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.
Development of Digital Elevation Models for Omo Forest Reserve Nigeria
(Commonwealth Forestry Association, 2016) Alo, A.A.
Digital Elevation Model (DEM) is a very important geospatial data used in modeling different hydrological and ecological phenomenon which are required in preserving our micro environment. DEMs are typically used to represent terrain relief. DEMs are particularly relevant for many applications such as lake and water volumes estimation, soil erosion volumes calculations, flood estimate, quantification of earth materials to be moved for channels, roads, dams, embankment etc. In this study, a total of 1,849 points coordinates with their respective elevations were obtained covering the entire study area. The algorithm used includes interpolated natural neighbour of Quantum Geographic Information System (QGIS) to generate Digital Elevation Model (DEMs) for the forest reserve. The contour lines were extracted from DEM at interval of 20 m from one another. It was observed that the presence of Omo river at the southern part of the reserve is responsible for the very low altitude obtained. On the other hand, the altitude at the northern part of the reserve is relatively high because of the presence of rock outcrop, which also makes the vegetation to be scanty. Therefore, Geographic Information System was used to develop Digital Elevation Model for Omo forest reserve to serve as baseline information for the study area.
Development of Information System for Wood-Based Industries in Ekiti State, Nigeria.
(Integrated Publishing Association and Academic Science Publications and Distributions, 2017) Alo, A. A.
Development of information system in forestry sector is crucial in order to manage resources in a sustainable manner. Spatial distribution of forest and wood-based industries is important for sustainability. However, geographic location and other information about the wood-based industries in Ekiti state, which can provide baseline information for investors in wood industry, are dearth. To proffer solution to this, information system was developed for wood-based industries in the State using geographic information system. This was done by taking the coordinates and photographs of all wood-based industries in the State. Types of equipment used for different wood conversion were assessed with the aim of determining their strength and capacity. The photographs and coordinates were loaded into ArcView GIS for analysis. The wood-based industries were represented on the State map using their coordinates while respective pictures were hotlinked appropriately. Various local governments in the State were represented with polygons of different sizes and wood industries were represented with points. The results obtained from the analysis were used to produce database in MS SQL server. The database created by Microsoft SQL server formed the data access (back end) of the software developed using C# Programming Language. Appropriate codes were written at the business logic layer for both the back and the front ends. The software was developed in an Interactive Development Environment (IDE) using visual studio. It was observed that most of the wood-based industries were concentrated at the southern part of the State where there were more forest reserves. Gbonyin Local Government has the highest number of wood industry (46) while Efon Local Government has none at all. Over 95% of the existing wood industry was functioning with 91% of them using CD6 machine. The software developed is user-friendly, facilitates efficient data storage and prompt information retrieval, adequate and has provision for regular updates.
Development of Silvicultural Management Models for Gmelina arborea Roxb. Stands in Area J4, Omo Forest Reserve, Nigeria
(Forest and Forest Products Society, 2021) Aturamu, O. A; Alo A. A.; Ige, P. O.
Plantation establishment of fast-growing species such as Gmelina arborea has been suggested as a quick fix to the perennial problem, especially in Omo Forest Reserve. Management models have been identified as tools for sustainable management and monitoring of Gmelina plantation. Hence, silvicultural management models were developed for sustainable management of Gmelina plantation in Omo Forest Reserve. Nine Gmelina arborea age series (34, 32, 30, 26, 24, 22, 20, 18 and 16 years old) stands were purposively selected in Area J4 of Omo forest reserve. A total of Sixty-five temporary sample plots were demarcated proportionate to size across the age series. In each plot, diameter at breast height and stem height were measured to estimate stand basal area and volume. Silvicultural management models were developed to estimate the optimum rotation volume, area and number of stock to harvest using the linear programme option of the R package to obtain the solutions of the planning model for 20 years at 5 years period. It was observed that the mean tree dbh and stem height ranges from 21.50 to 70.61 cm and 16.08 to 24.98 m respectively. The mean basal area and stem volume had the respective values which range from 33.31 to 413.78 m2/ha and 423.19 to 8413.52 m3/ha. At the individual tree level, mean annual growth is attained at 27 years. This represents the optimal rotation age of any Gmelina arborea stand in Omo forest reserve. If selective logging is applied for timber purpose, a rotation age of 27 years will be the appropriate rotation age. However, if clear-felling is opted for, the appropriate rotation age will be 25 years. The logging plan that optimizes volume in terms of area cut in each stand and period revealed that in 16 years old stands, whole logging will take place only during the last period of the plan, removing 5.00ha. The respective area to be cut during the 1st, 2nd, 3rd and 4th periods are 451.70ha, 517.50ha, 250.80ha and 140.00ha. The harvesting schedules obtained in this study have shown that the management planning model provides rational and practicable results.
Equations for estimating bark thickness of Gmelina arborea (ROXB) trees in Omo forest reserve, Nigeria
(Ministry of Agriculture and Livestock Development, Nepal, 2018) Alo, A.A.; Ogana, F.N.
The measurement of bark thickness is an important factor for computing inside bark volume of a standing tree or log. Bark thickness at breast height can easily be measured. However, when bark thickness at relative height of a standing tree is required, the application of equations becomes imperative. In this study, equations were developed for estimating bark thickness at relative height and at breast height. Stratified random sampling was used to establish 50 sample plots of 0.04 ha size across 10 age series in the Gmelina arborea plantation in Omo Forest Reserve, Nigeria. Eight equations for estimating bark thickness as function of diameter inside bark (dib) and Relative Bark Thickness (RBT) were developed. Equation was also developed for predicting absolute bark thickness at breast height. The equations were assess based on Root Mean Square Error (RMSE), Mean Absolute Bias (MAB), Akaike Information Criterion (AIC) and Shapiro-Wilk test of normality. The results showed that six out of the nine equations performed relatively well in estimating bark thickness. The best equation for estimating bark thickness as function of dib had RMSE, MAB and AIC values of 0.065, 0.049 and -125.989, respectively. The best equation for RBT had 0.109, 0.079 and -75.577, respectively. The equation for absolute bark thickness at breast height had 0.204, 0.152 and -12.697. The equations did not violate the assumption of normality as revealed by normality test (p > 0.05). With these equations, any analytic volume equation can be used to compute the inside bark volume of the standing trees. The relative back thickness and diameter inside back functions developed in this study were found to be satisfactory based on the various criteria used for their assessment. Thus, they are recommended for use in estimating the back thickness and diameter inside bark of Gmelina arborea stands in similar ecosystem.
Evaluation of height-diameter models for community Parkia biglobosa Jacq B. plantation in wasangare, Oyo State.
(Northeast Forestry University and the Ecological Society of China in collaboration with Springer Verlag., 2023) Onilude, Q. A.; |Ige, P.O.; Alo, A.A.
Forest growth and yield models are fundamental tools for sustainable forest management planning and future inventory assessments. In order to quantify the growing stock of Parkia biglobosa in Wasangare, Oyo state, reliable height-diameter (H-D) models are required. Therefore, the aim of this study was to evaluate 2-parameter H-D models for the prediction of heights of Parkia biglobosa tree which are consistent with current forest management practices in the country. Measured 1,196 pairs of height and diameter data were subjected to six (6) 2-parameter H-D models viz Naslund, Meyer, Curtis, Modified Log Logistic, Michaelis-Menten and Wykoff. Model fitting and validation was done in ratio 75:25. With the use of R software tools, the fitting and validation was done. Root mean square error (RMSE), mean absolute bias (MAB), Akaike information (AIC) and Bayesian information criterion (BIC) were used to assess the models. The result showed that all the models were significant but based on the goodness-of-fit statistics, Meyer H-D model had the least rank value, followed by the Modified log logistics H-D (M. LogL) model. The Meyer H-D model had RMSE, MAB, AIC and BIC of 2.996, 2.389, 4520.263 and 4524.660 respectively while M. LogL HD model had 2.999, 2.421, 4522.082 and 4536.480 respectively. Therefore, it was concluded that Meyer H-D model and M. LogL model written as and, respectively were selected as the best candidate models for H-D relationships of Parkia biglobosa plantation especially in the savanna zone of Oyo state.
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.
Forest Cover Dynamics of a Lowland Rainforest in Southwestern Nigeria Using GIS and Remote Sensing Techniques
(Scientific Research Publishing, 2021) Oluwajuwon1, T. V.; Alo A. A.; Ogana, F. N.; Adekugbe, O. A.
The rate of forest degradation and deforestation in Nigeria has been increasing over the years and is prominent in the southwestern parts. Despite the significant change and degradation observed in a lowland rainforest in the region—Ogbese Forest Reserve, there is a great dearth of information about the level of forest cover change. Therefore, this study determined the cover dynamics of the rainforest reserve over the epoch of 20 years using Geographic Information System and remote sensing techniques. Coordinates of the boundary and some other benchmark places within the forest reserve were obtained. Secondary data collection included: Landsat imageries of 1998, 2002 and 2018. An interview guide was used to obtain information from forest officials and locals of the surrounding communities to complement the spatial data obtained. Image classification was done using the maximum likelihood algorithm. The rate of change across the epochs was determined using the area of the land cover classes. The level of vegetation disturbance in the reserve was determined through Normalized Difference Vegetation Index. Five different forest cover classes were identified in the study area: forest, plantation, farmland, grassland, and bare land. The natural forest reduced significantly from 34.43 km2 (48%) in 1998 to 8.73 km2 (12%) in 2002 and was depleted further by 2018, while other cover classes increased. NDVI value also reduced from 0.25 to 0.13. Agriculture, among others, was observed as the main driver of forest degradation and deforestation in Ogbese Forest Reserve. The study concluded that the remaining forest (i.e. plantation) could also be depleted by 2025, as it decreases by −0.94 km2 per year if proper reforestation and management practices are not introduced.
Forested landscape dynamics in Saki-East local government area of Oyo State, Nigeria
(Forests and Forest Products Society, 2021) Alo, A. A.; Onilude, Q. A
The 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.
Geodatabase and Health Risk Assessment of Avenue Trees on Selected Roads in a Tertiary Institution in Ibadan, Nigeria
(Joint Coordination Centre of the World Bank assisted National Agricultural Research Programme (NARP), 2024) Israel, R.; Akintunde-Alo, D. A.; Mshelia, Z. H.; Oluwajuwon, T.V.
Campuses of Nigerian universities, especially the older ones, are home to aged trees that were originally planted for environmental beautification and aesthetics. However, due to the current global climate change and increased vulnerability to abiotic and biotic stressors, the old trees could pose threats to pedestrians, structures, and roads within the university campus environments. Therefore, the objective of this paper is to develop a geodatabase and evaluate the health risk assessment of avenue trees on selected roads in a tertiary institution in Ibadan, Oyo State, Nigeria using appropriate standard methods. Results obtained reported a total of 121 individual avenue trees belonging to 14 species along the study roads. The geospatial distribution analysis revealed that Emotan road had a lower density of avenue trees compared to Benue and Oduduwa roads. Furthermore, the health risk assessment indicated that 17.35% of the individual avenue trees had defects, posing potential hazards and risks of tree failure, and potential damage to pedestrians, vehicles, and neighboring utilities. The developed geodatabase is user-friendly and allows for easy data storage and quick information retrieval on the avenue trees, enhancing their maintenance and risk management. Furthermore, this study shows that systematic replacement, replanting, and management of avenue tree species could be a proactive initiative for the expansion of the geodatabase and to reduce negative health impacts.
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.
Geospatial assessment of climate sensitivity in Ibarapa North, Oyo State, Nigeria
(Faculty of Agriculture, Usmanu Danfodiyo University, Sokoto, Nigeria, 2024) Agbor, C.F.; Akintunde-Alo, D. A.; Ogunwale, O. R.
This study employed remote sensing and geographic information system (GIS) to evaluate the spatial pattern of carbon(iv)oxide (CO2) concentration and the resulting climate sensitivity in Ibarapa North local government areas of Oyo State, Nigeria. The evaluation was carried out using Landsat images of 2003 and 2023, digital elevation model, as well as CO2 data collected with CO2. meter. Surface temperature and radiative forcing were generated from the satellite images using random forest algorithm in 𝑅 software environment, while the climate sensitivity was evaluated using Drakes’ Sensitivity Linear Model. The results revealed mean air temperature of 31.5oC and 32.7oC in 2003 and 2023 respectively. The area experienced positive radiative forcing mean value of about 2.69𝑊 𝑚−2, which indicates more energy being trapped on the earth’s surface that could cause warming. The climate sensitivity in 2023 was 0.4oC 𝑚−2s-2 which falls below global average of about 3oC 𝑚−2s-1. The CO2 concentration was extrapolated based on the mathematical function derived from the regression function between the variable and elevation. The results revealed positive radiative forcing and low climate sensitivity value. This may seem positive, but that doesn’t negate the need for action to mitigate adverse effects of climate change.
Geospatial modeling of forest landscape assessment: a case study from Ikere forest reserve
(African Journal of Open Libraries (AJOL)., 2020) Chukwuka A. F.; Alo A. A.; Aigbokhan, O. J.
This study set out to assess the dynamic characteristics of the Ikere forest reserve landscape between 1985 and 2017 using remote sensing data and spatial metrics. Landscape of the study area maintained complex patterns of spatial heterogeneity over the years. Forest cover loss to other land cover types results in new large non-forest area at increasing rate. As at the year 2017, the changes in land cover types were not yet at equilibrium, thus the need to determine the future forest cover extent using a three-way markov Chain model. The decrease in number of patches of forest land (NumP) with increase in its mean patch size (MPS) shows that the forest is becoming a single unit probably due to clearing of existing patches of forest trees. The decrease in class diversity and evenness (SDI and SEI) of the general landscape over the years strengthens this assertion. The findings of this study would be very helpful to government and other stakeholders responsible for ensuring sustainable forest and general environment.
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.