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Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
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EVALUATING DEFORESTATION PATTERNS IN MBAAV 1 FOREST RESERVE, GWER EAST, BENUE STATE

Authors: Oluwaseun, Grace Ifeoma;

EVALUATING DEFORESTATION PATTERNS IN MBAAV 1 FOREST RESERVE, GWER EAST, BENUE STATE

Abstract

The study investigates the ongoing issue of deforestation in Mbaav1 Forest Reserve, located in Gwer East Local Government Area (LGA), Benue State, Nigeria. Deforestation in the reserve is exacerbated by socio-economic factors such as agricultural expansion, population growth, logging, and development projects. Understanding these drivers is crucial for effective policy formulation and sustainable forest management. The primary aim of this study is to assess changes in forest cover in Mbaav1 Forest Reserve between 1989 and 2019, with particular emphasis on the socio-economic factors driving deforestation. The study specifically examines the socio-economic characteristics of local communities, land use changes, the extent of deforestation, and the key drivers of these changes. Data were collected using both primary and secondary methods. Primary data were gathered through semi-structured questionnaires and interviews with 387 community members, while secondary data were obtained from Landsat satellite imagery (1989, 2009, and 2019), For socio-economic analysis, simple descriptive statistics were used to present data on respondents' characteristics, including income, age, education, occupation, and household size. To examine the influence of socioeconomic factors on deforestation, a binary logistic regression model was adopted. Landsat satellite imageries were analyzed using Geographic Information Systems (GIS) and remote sensing tools. The supervised and unsupervised classification methods were used to detect and classify land cover changes. The Normalized Difference Vegetation Index (NDVI) was also used to map vegetation changes. The results of analysis revealed significant relationships between deforestation and factors such as income, population growth, developmental projects, and land-use activities. Notably, income had the highest influence on deforestation, with a unit increase in income leading to a 1.35 increase in deforestation (β = 1.35, p<0.05). Population growth (β = 1.02, p<0.05) and development projects (β = 0.77, p<0.05) also significantly contributed to forest loss. Logging (β = 0.10, p<0.05) and farming (β = 0.39, p<0.05) further exacerbated deforestation, although to a lesser degree. The percentage of land cover change between 1989, 2009, and 2019 revealed a consistent decline in forest area. In 1989, the forest area covered 75.56% of the total land, but by 2019, this had dropped to 36.25%. Meanwhile, farmland increased from 5.86% in 1989 to 29.83% in 2019, reflecting the expansion of agricultural activities. The study concludes that the rapid deforestation in Mbaav1 Forest Reserve is driven by human activities, particularly agricultural expansion and logging, compounded by socio-economic pressures such as income and population growth. The study recommends that addressing these drivers through sustainable practices like agroforestry, improving forest management, and implementing policies that integrate forest conservation with agricultural development are essential. Furthermore, public awareness campaigns on the environmental and socio-economic consequences of deforestation are crucial for fostering community participation in conservation efforts.

Keywords

Deforestation, Forest Degradation, Mbaav1 Forest Reserve, Land-use Change, Remote Sensing and GIS

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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