Scholarly works in Social and Environmental Forestry
Permanent URI for this collectionhttps://repository.ui.edu.ng/handle/123456789/13518
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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 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.Item Spatial Trend Analysis of Temperature and Rainfall and Their Perceived Impacts on Ecosystem Services in Mau Forest, Kenya(International Information and Engineering Technology Association, 2021) Jebiwott1, A.; Ogendi, G. M.; Agbeja, B. O.; Alo A. A.; Mukonambi, M. M.The Mau Forest Complex is an important ecosystem in Kenya providing many ecosystem services to the local communities. However, its degradation has rendered its ability to deliver its ecosystem services such as climate regulation ineffective. This study's objective was to assess the local climate trend in terms of rainfall and temperature and their perceived impacts on ecosystem services in Mau Forest, from 1984 to 2020. We obtained gridded meteorological data for the study area from the Kenya Meteorological Department and analyzed it using Mann Kendell’s test to identify significant trends in temperature and rainfall. Focus Group Discussions were also carried out to establish the people's perceptions of local climate change and its impacts on ecosystem services. The results of the study indicate no significant trend, p>0.05, in annual rainfall over time. On the other hand, the results show a significant trend, p=3.696e-06, in average annual temperature with approximately 2℃ increase. from 1984 to2020. The local climate change has seen a decline in ecosystem services, mainly water levels and agricultural produce. To cope with and mitigate the effects of climate change, there is need to emphasize establishment of agroforestry woodlots and practice of climate-smart agriculture among the forest adjacent communitiesItem 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.Item Temperature variability and impact of vegetation cover in Ibadan metropolis, Ibadan, Nigeria(Faculty of Agriculture, Usmanu Danfodiyo University, Sokoto, Nigeria, 2021) Nwatu, U. J.; Alo A. A.; Agbor, C. F.This study evaluates the changes in Urban Green Spaces (UGS) and the impact of such changes on surface temperature in Ibadan Metropolis between 1984 and 2018 using Landsat images. Digital numbers of the imageries were converted to physical quantities, radiance, and brightness temperature, while the temperature retrieval from thermal channels of Landsat imagery was carried out and the derived surface temperature validation was done through near-surface air temperature. This was followed by the reclassification of the images using Normalized Difference Vegetation Index (NDVI) as a proxy for vegetation cover and was regressed with urban temperature to observe their nexus, which explains the ability of UGS to absorb solar radiation in the study area. The land use land cover maps of the metropolis were developed from green, red and near-infrared channels of Landsat data in Idrisi software environment using maximum likelihood classifier. Results show that the mean temperature of Ibadan metropolis increased from 33.29℃ to 35.76℃ over 34 years, and the temperature of different land cover types considered in this study revealed that built-up and bare soil areas recorded the highest temperature changes compared to other land cover types (green spaces and water body). Also, the correlation analysis between UGS and ST showed a strong negative relationship with R2 values ranging from -0.71 to -0.89. The study, therefore, concludes that the relationship is strong enough to ascertain that urban vegetation cover has the capacity to mitigate climate change effects. The increase in temperature may contribute to the variations in surface temperature, thus giving rise to the urban heat island effect. The study revealed the efficiency of geospatial techniques in data capturing for reliable information on sustainable management of urban green spaces.Item 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.Item Spatio-Temporal Dynamics of Urban Green Space and Temperature in Ado-Ekiti Metropolis, Nigeria(Forests and Forest Products Journal, 20, pp.40-53, 2020) Okikiola M. A.; Alo A. A.The Nexus between the Urban Green Space (UGS) and Land Surface Temperature (LST) helps to formulate policy for sustainable management of UGS where there is an urban sprawl like Ado Ekiti. However, there is a dearth of information on UGS and LST in Ado-Ekiti. Therefore, this study adopted remote sensing and geographic information system techniques to determine the dynamics and nexus between UGS and LST as well as investigating the perceived factors responsible for the UGS changes in Ado-Ekiti metropolis, Nigeria with a view to providing relevant information for sustainable management of the UGS and mitigating the Urban Heat Island. Landsat imageries of 1987 (TM), 1998 (ETM) and 2019 (OLI) were obtained. Map of Ado-Ekiti was georeferenced and digitized to obtain its shapefile. The maximum likelihood algorithm of supervised classification in ArcGIS was used to classify Landsat imageries. The shapefile was superimposed on the classified imageries and clipped for the determination of land use land cover sizes. The LST was extracted from the imageries by converting the digital numbers to the surface temperature. Correlation analysis was used to determine the nexus between the UGS and LST. Four land use land cover: green spaces, built-up area, water bodies and bare land, were identified in the Ado-Ekiti metropolis. The UGS decreased from 74.4% in 1987 to 38.7% in 2019. Similarly, water bodies reduced from 0.9% in 1987 to 0.1% in 2019 respectively. However, built-up area and bare land increased from 21.9% and 2.9% in 1987 to 51.1% and 10.5% in 2019 respectively. The LST in Ado-Ekiti metropolis increased from 22.1°C in 1987 to 30.5 °C in 2019 respectively. The Built-up area and bare land had the highest LST values compared with UGS and water body in all the years. The relationship between the UGS dynamics and LST was negatively correlated with r2 ranging from -0.51 to -0.83. By the year 2049, the vegetation would have reduced to 36.0% while built-up and bare land would have increased to 52.4%. on the other hand, water with no significant change.Item 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.