Introduction
Sustainable forest management (SFM) emerged as a global response to accelerating forest loss, climate change, and the unsustainable exploitation of timber and non-timber forest products (Prins et al., 2023). Major international milestones have shaped its evolution, notably the 1992 United Nations Conference on Environment and Development (UNCED) in Rio de Janeiro (Agenda 21), the establishment of the Intergovernmental Panel on Forests (IPF) in 1995 (Food and Agriculture Organization of the United Nations, 1997, 1999), and the International Tropical Timber Organization (ITTO) Objective 2000, which called for international trade in tropical timber sourced exclusively from sustainably managed forests (Castañeda, 2000). These initiatives introduced certification schemes and standards promoting best management practices and enabling certified forest products to access international markets (Gupta, 2006). At its core, SFM seeks to balance environmental integrity, social equity, and economic viability to ensure the long-term provision of forest goods and ecosystem services for present and future generations (Prins et al., 2023).
In Nigeria, including Ondo State, forest exploitation remains largely unsustainable, with practices such as clear-cutting without adequate regeneration still prevalent (Ogundele et al., 2016). This contrasts with sustainable forestry approaches that emphasize selective harvesting, species diversity, biodiversity conservation, and ecosystem-based management. Such practices enhance forest resilience to climate change, protect ecosystem functions, reduce soil erosion, sequester carbon, sustain rural livelihoods, and secure long-term timber supply. Despite the designation of protected areas and forest reserves, illegal logging persists due to weak enforcement, governance gaps, and limited community participation (Ekakitie & Enakireru, 2024).
Nigeria's Land Use Act of 1978 provides the overarching legal framework for land administration, vesting land ownership in state governors to hold in trust for the people, with authority to allocate or revoke rights of occupancy in the public interest. While this framework facilitates land acquisition for conservation, it has also enabled forest exploitation with limited compensation or consultation for affected communities (Federal Republic of Nigeria, 1978).
Globally, forest cover has declined dramatically from approximately 57% of habitable land 10,000 years ago to current levels, with the most significant losses occurring over the past five millennia (Ritchie, 2021). Africa contains an estimated 624 million hectares of forest, representing 20.6% of the continent's land area and about 15.6% of the global forest cover (African Natural Resources Centre, 2021). However, the continent continues to experience substantial deforestation, losing approximately 3.9 million hectares annually between 2015 and 2020. Timber harvesting accounts for an estimated 37% of global forest loss, followed by agricultural expansion (28%), road development (20%), and extractive infrastructure (12%). These trends underscore persistent structural pressures on forest ecosystems and highlight the urgent need for strengthened governance frameworks, cross-sectoral policy coherence, and effective implementation of SFM principles (Nzabarinda et al., 2025).
Prior to 2017, sustainable forestry initiatives in Nigeria were largely implemented through partnerships between government agencies and international organizations, particularly REDD and UN-REDD+ programmes (Amuyou et al., 2021; Asiyanbi et al., 2017). Despite these interventions, forests in Nigeria and in Ondo State in particular remain under severe pressure from rapid population growth, urbanization, agricultural expansion, fuelwood extraction, and industrial development associated with economic diversification (Ogundele et al., 2016). These pressures have contributed to ecosystem degradation and the marginalization of forest-dependent communities.
In May 2017, the Ondo State Government formally launched a state-level sustainable forestry programme. This study evaluates the effectiveness of the programme by analysing tree cover dynamics between 2019 and 2023. Specifically, it quantifies net gains and losses in tree cover across selected Local Government Areas representing the state's five ecological zones, thereby identifying key spatial and ecological patterns of change. Empirical, subnational evidence on recent forest-cover dynamics in sub-Saharan Africa remains limited. This study addresses this gap by providing an updated assessment of timber extraction and associated forest-cover change in Ondo State. The findings contribute to ongoing debates on sustainable forest governance and offer policy-relevant insights for strengthening monitoring frameworks, enhancing community engagement, and aligning subnational forestry practices with broader climate mitigation and biodiversity conservation objectives.
Materials and Methods
Study area
The study was conducted in Ondo State, south-western Nigeria (7°10′ N, 5°04′ E). The state comprises 18 Local Government Areas (LGAs), with Akure serving as the administrative capital. Ondo State covers approximately 14,798.8 km2, of which about 16.4% is gazette as forest reserves (Azeez & Aluko, 2019), making it one of the most forest-rich states in Nigeria (Figure 1).
Figure 1.
Location of the study areas: Akure North, Akoko South-West (S-W), Idanre, Okitipupa and Ilaje in Ondo State, Nigeria.
Vegetation in the state spans diverse ecological zones: mangrove-swamp forest along the Bight of Benin coastline, lowland tropical rainforest across the central belt, and wooded savanna on the northern margins adjoining the Yoruba Hills. These ecosystems support diverse flora and fauna, and provide critical ecosystem services, including carbon sequestration, watershed protection, and biodiversity conservation. Dominant indigenous timber species include Milicia excelsa (Welw.) C.C. Berg, Antiaris africana Engl., Terminalia superba Engl. & Diels, Lophira procera A. Chev., Blighia sapida K.D. Koenig, and Parkia biglobosa (Jacq.) R.Br. ex G. Don.
Agriculture is a major land-use activity in the state. Principal tree crops include cocoa, kola, coffee, rubber, oil palm, and citrus, with cocoa representing the most extensive and economically significant plantation crop (Oke & Odebiyi, 2007).
The climate is humid and tropical, characterized by two distinct seasons: a wet season extending from March to November, distinguished by heavy rainfall and high humidity that drive lush vegetation and rapid forest regeneration supporting biodiversity and agriculture, while also increasing risks of flooding and soil erosion, and limiting logging due to poor forest access, with annual rainfall ranging from 1,500 to 2,500 mm and mean daily relative humidity of approximately 84%; and a dry season from December to February, featuring low rainfall which is typically ≤ 250 mm and Harmattan-driven dry, dusty conditions that increase wildfire risk and water scarcity while enabling greater forest access and intensified logging activities. Mean annual temperature averages about 27°C (Olubanjo and Alade, 2018; Ondo State Government, Ministry of Economic Planning and Budget, n.d.).
As of 2022, the projected population of Ondo State was approximately 5.3 million. The population is predominantly rural (60.9%), with livelihoods largely dependent on agro-based activities, including crop cultivation, livestock production, fishing, and forest-related occupations.
Methods
Study stratification and sampling framework
Of the 18 Local Government Areas (LGAs) in Ondo State, four; Okitipupa, Irele, Ese-Odo, and Ilaje are classified administratively as “free areas” because they contain no gazette forest reserves or forestry administrative offices. Nevertheless, revenue is generated from timber harvested within these jurisdictions.
To better evaluate the state's public-private partnership (PPP) forestry initiative's effectiveness, the analysis encompassed the entire state tree cover, including both gazette reserves and free areas. The 18 LGAs were stratified according to the state's diverse vegetation zones: Guinea savanna, dry rainforest, moist rainforest, freshwater swamp, and mangrove forest. One LGA was randomly selected from each ecological stratum using simple random sampling to ensure ecological representation across the state.
Research design and data sources
The study adopted an explanatory sequential mixed-methods design, premised on the assumption that integrating multiple data sources enhances analytical depth and contextual under-standing. The research was implemented in three sequential stages:
Desk-based review: A structured review of peer-reviewed literature, technical reports, policy briefs, and media sources relating to forest governance, afforestation, sustainable forestry, and forest-loss dynamics in Nigeria, with emphasis on Ondo State since its creation in 1976.
Remo tesensing data acquisition: Annual data on primary forest loss and tree cover loss for Ondo State (2019–2023) were obtained from the Global Forest Watch (GFW) platform of the World Resources Institute (n.d.).
Administrative records: Official forestry records documenting annual tree felling across forest reserves and free areas (2019–2023) were obtained from the Ondo State Department of Forestry, Ministry of Agriculture and Natural Resources (Ondo State Ministry of Natural Resources, 2023 unpublished administrative report).
Phase I: Systematic literature review
A systematic screening of scholarly and grey literature was conducted to identify studies relevant to afforestation, forest governance, sustainable forest management, and forest loss dynamics in Ondo State, Nigeria, and the wider West African region.
Phase II: Secondary data analysis
Forest-change data obtained from GFW/WRI were analyzed using Microsoft Excel 2021 (Microsoft Corporation, USA) to generate time-series indicators of annual primary forest loss and tree cover loss between 2019 and 2023.
Administrative records of felled trees were cleaned, coded, and analyzed descriptively and comparatively across the five ecological strata. Comparative analysis enabled assessment of spatial and temporal patterns in harvesting intensity across vegetation zones.
Data triangulation (Jick, 1979) was employed to enhance analytical robustness. Remote-sensing indicators and administrative harvesting records were examined comparatively to identify convergent or divergent trends and to assess whether observed forest-cover changes corresponded with recorded timber extraction under the state's public-private partnership (PPP) forestry framework (2019–2023).
Ethical considerations
Individuals who provided insights into the activities and operations of the Ondo State forestry sector gave verbal informed consent and requested anonymity. Confidentiality was strictly maintained, particularly as participants were not authorized to make official statements regarding state afforestation targets or sustainable forestry policies.
Statistical analysis
All statistical analyses were conducted using Microsoft Excel 2021 Descriptive statistics were used to characterize temporal and spatial patterns in timber harvesting and forest-cover change, with results presented in tables and figures.
Pearson product-moment correlation analysis (Royal Geographical Society, n.d.) was applied to evaluate the strength and direction of linear relationships among felled trees, tree cover loss, and primary forest loss. This method was selected to quantify associations between variables without implying causal relationships.
The analysis was based on annual observations for the period of 2019–2023 (n = 5). Given the limited sample size, the results should be interpreted with caution, as small datasets may increase variability and reduce statistical robustness.
Terminology
For clarity and consistency, three key terms are used throughout this study:
Primary forest loss refers to the loss of primary forests largely undisturbed, naturally regenerated forest ecosystems that retain native species composition, structural complexity, and ecological integrity.
Tree cover loss denotes the annual removal or mortality of woody vegetation taller than 5 m in height. This measure encompasses both natural forests and plantation systems and includes losses resulting from logging, land-use conversion, fire, storms, and other disturbances.
Felled trees represent the number of trees cut through logging or harvesting activities, as documented in official administrative records.
Results
Forestry records from Ondo State, Nigeria, covering the period 2019–2023 were analyzed. A total of 114,629 trees were felled across the 18 Local Government Areas (LGAs), with annual totals ranging from 29,556 in 2019 to 16,751 in 2023 (Table 1). Felling activity was recorded in all LGAs during the study period in consideration by the Department of Forestry field officers.
Table 1.
Felled stems across the 18 Local Government Areas of Ondo State (2019–2023): annual counts, five-year totals, percentage share of the state total, and each LGA's peak year and corresponding value (ranked by the five-year total).
| LGAs/Year | 2019 | 2020 | 2021 | 2022 | 2023 | Total (5Y) | Share (%) | Peak Year |
|---|---|---|---|---|---|---|---|---|
| Akure North | 6680 | 6588 | 5837 | 8327 | 5886 | 33318 | 29.065 | 2022 |
| Owo | 3111 | 1792 | 3528 | 4336 | 1549 | 14316 | 12.488 | 2022 |
| Akure South | 3248 | 2228 | 1682 | 2199 | 2037 | 11394 | 9.939 | 2019 |
| Odigbo | 3848 | 1871 | 1825 | 1795 | 1092 | 10431 | 9.099 | 2019 |
| Ifedore | 2636 | 1948 | 1737 | 2137 | 1752 | 10210 | 8.906 | 2019 |
| Akoko South-West | 1627 | 909 | 1199 | 1605 | 1030 | 6370 | 5.557 | 2019 |
| Ondo East | 1821 | 1181 | 737 | 891 | 733 | 5363 | 4.678 | 2019 |
| Idanre | 1667 | 800 | 741 | 1082 | 446 | 4736 | 4.131 | 2019 |
| Okitipupa | 1207 | 644 | 607 | 903 | 445 | 3806 | 3.320 | 2019 |
| Akoko North-West | 906 | 461 | 851 | 1912 | 495 | 3725 | 3.249 | 2022 |
| Ose | 1076 | 500 | 542 | 938 | 92 | 3148 | 2.746 | 2019 |
| Akoko North-East | 586 | 315 | 625 | 883 | 477 | 2886 | 2.517 | 2022 |
| Irele | 440 | 409 | 412 | 377 | 288 | 1926 | 1.680 | 2019 |
| Ondo West | 545 | 280 | 385 | 348 | 133 | 1691 | 1.475 | 2019 |
| Akoko South-East | 150 | 120 | 222 | 385 | 234 | 1111 | 0.969 | 2022 |
| Ile Oluji/Okeigbo | 3 | 7 | 45 | 52 | 62 | 169 | 0.147 | 2023 |
| Ese Odo | 5 | 0 | 20 | 0 | 0 | 25 | 0.021 | 2021 |
| Ilaje | 0 | 0 | 4 | 0 | 0 | 4 | 0.003 | 2021 |
The number of trees harvested varied spatially. The highest cumulative figures were recorded in Akure North (33,318), Owo (14,316), and Akure South (11,394). Lower figures were observed in Ese-Odo (25), Ilaje (4), and Ile-Oluji/Okeigbo (169). Ese-Odo and Ilaje are characterized by mangrove-swamp vegetation, and these areas, together with Ile-Oluji/Okeigbo, have limited accessibility going by the information from the field officers.
Further analysis indicates that aggregate levels of felled trees, primary forest loss, and tree cover loss were lower in 2023 than in 2019 (Figure 2). Tree cover loss remained consistently high throughout the study period, fluctuating slightly between approximately 8,000 and 8,500 hectares from 2019 to 2022, before declining to around 7,500 hectares in 2023. In contrast, primary forest loss exhibited a marked and continuous decline, decreasing from about 2,700 hectares in 2019 to below 1,000 hectares by 2022 and remaining low in 2023.
Figure 2.
Primary forest (pcs) and tree cover loss (ha) in Ondo State (2019–2023, hectares, bars) with felled trees (count, line, right-hand axis).
The number of felled trees showed a fluctuating trend over time, with an initial high of approximately 30,000 trees in 2019, a decline in 2020, and a subsequent increase reaching a secondary peak in 2022, followed by a sharp reduction in 2023. Despite the reduction in felled trees in 2023, the overall tree cover loss remained relatively high, indicating that factors other than logging may be contributing to forest cover reduction.
Error bars reveal moderate variability in the estimates, particularly for primary forest loss in earlier years and felled trees across the study period.
The analysis of felled trees by season (Figure 3) indicates that, cumulatively, a higher number of trees were felled during the wet season (March–November) than during the dry season (December–February). The wet season is typically characterized by poorer road conditions and reduced accessibility in some areas of the state due to inadequate infrastructure.
Figure 3.
Seasonal felling of trees in Ondo State (2019–2023), showing higher counts in the wet season (March–November) than in the dry season (December–February).
Figure 4.
Annual counts of felled trees in Ondo State by vegetation zone (2019–2023), with representative LGAs: Guinea Savanna (Akoko South-West), Dry Rainforest (Akure North), Moist Rainforest (Idanre), Freshwater Swamp (Okitipupa), and Mangrove (Ilaje).
The factors associated with the higher level of felling observed during the wet season were not examined in this study.
The distribution of felled trees varied markedly across vegetation zones over the study period (2019–2023). The Dry Rainforest zone (Akure North) consistently recorded the highest number of felled trees, with values increasing from approximately 6,000 in 2019 to a peak of about 8,000 in 2022, followed by a slight decline in 2023. In contrast, the Guinea Savanna (Akoko South-West) and Moist Rainforest (Idanre) zones exhibited moderate levels of tree felling, generally ranging between 1,000 and 1,800 trees, with minor year-to-year fluctuations.
The Moist Rainforest/Freshwater Swamp (Okitipupa) and Mangrove (Ilaje) zones recorded the lowest levels of tree felling throughout the study period, typically below 1,200 trees annually. Across most vegetation zones, a noticeable increase in tree felling was observed in 2022, followed by a general decline in 2023. Error bars indicate greater variability in estimates for the Dry Rainforest zone compared to other zones, suggesting higher uncertainty or spatial heterogeneity in logging activities within this area.
The correlation analysis of felled trees, tree cover loss, and primary forest loss (Table 2) indicate that all variables are positively correlated, although the strength and statistical significance of these relationships vary. A moderate positive correlation was observed between felled trees and tree cover loss (r = 0.576, p = 0.310), as well as between felled trees and primary forest loss (r = 0.471, p = 0.423). Similarly, tree cover loss showed a moderate association with primary forest loss (r = 0.653, p = 0.232). However, none of these relationships were statistically significant at the conventional α = 0.05 level.
Table 2.
Pearson correlation matrix (2019–2023) for felled trees, tree cover loss (ha), primary forest loss (ha), and estimated felled area (ha, assuming 103 trees ha−1).
| Variable Pair | r | p | Significance | Interpretation |
|---|---|---|---|---|
| Felled trees – Tree cover loss | 0.576 | 0.310 | ns | Moderate positive |
| Felled trees – Primary forest loss | 0.471 | 0.423 | ns | Weak-moderate positive |
| Tree cover loss – Primary forest loss | 0.653 | 0.232 | ns | Moderate positive |
| Felled trees – Felled trees | 1.000 | <.001 | *** | Near-perfect positive* |
| Tree cover loss – Felled trees | 0.0575 | 0.310 | ns | Moderate positive |
| Primary forest loss – Felled trees | 0.471 | 0.424 | ns | Weak-moderate positive |
A near-perfect positive correlation was found between cut trees and the corresponding area (r = 1.000, p < 0.001), indicating a statistically significant relationship. This result is expected, as the area variable is directly derived from the number of trees cut (based on a fixed conversion factor of 103 felled trees per hectare), thus reflecting a deterministic rather than independent association.
Overall, while the observed correlations suggest consistent positive relationships among forest disturbance indicators, the lack of statistical significance in most cases is likely due to the small sample size. Consequently, these findings should be interpreted with caution, and further analysis using a larger temporal dataset is recommended to confirm these patterns.
Discussion
Spatial and temporal patterns of timber extraction
The results reveal clear spatial and temporal patterns in forest exploitation across Ondo State between 2019 and 2023. The total number of felled trees (114,629) indicates substantial extraction pressure, although the observed decline from 2019 to 2023 suggests a potential reduction in harvesting intensity. This trend is broadly consistent with earlier observations reported by Adeoye & Ayeni (2011), who documented dynamic land-use transitions in the Ijesa-Ekiti region. It was originally designated as a forest reserve in 1978 when it formed part of the former Ondo State prior to the creation of Ekiti State in 1996. The area had largely transitioned to fallow and arable farmland by 1986. By 1994, however, forest cover had re-emerged in certain locations without any deliberate afforestation interventions, underscoring the dynamic nature of forest regeneration in the region.
The peak in tree felling observed in 2022, followed by a decline in 2023, highlights the variability of forest exploitation over time. Such fluctuations may be influenced by governance structures, market demand, or enforcement effectiveness. The recent downward trend in harvesting intensity may reflect changing socio-political or economic conditions; however, the absence of supporting empirical evidence limits definitive interpretation.
Seasonal analysis further indicates that higher levels of tree felling occurred during the wet season, contrary to expectations given reduced accessibility during periods of heavy rainfall. This finding differs somewhat from the results reported by Adeyekun et al. (2023), which showed that the number of tree stems harvested was higher during the dry season (November–March) than in the rainy season (April–October). The observed pattern in this study suggests that logging activities may not be strictly constrained by infrastructural limitations, but may instead be driven by market cycles, labour availability, or regulatory enforcement dynamics.
The underlying drivers of this seasonal variation were not explicitly examined in the present study. Nevertheless, the observed differences in felling between wet and dry periods indicate that operational, economic, or institutional factors may play a significant role in shaping harvesting patterns. These findings highlight the need for targeted future research to better understand the mechanisms influencing seasonal forest exploitation dynamics.
Spatial variation in harvesting
Spatially, felling activity was highly uneven across Local Government Areas (LGAs), with Akure North, Owo, and Akure South accounting for a substantial proportion of total extraction. This concentration may be attributed to relatively better accessibility, more developed infrastructure, and the predominance of commercially valuable forest types, particularly within the dry rainforest zone. In contrast, minimal felling recorded in mangrove- and swamp-dominated LGAs such as Ilaje and Ese-Odo reflects ecological constraints and limited accessibility, underscoring the influence of physical geography on harvesting patterns.
These findings are consistent with earlier studies by Adedeji & Adeofun (2014) and Ebire et al. (2025), which reported that forest reserves previously managed for sustainable timber production have become increasingly fragmented and degraded, often overtaken by destructive activities such as illegal logging, bush burning, and poaching. The observed spatial concentration of felling may therefore also reflect localized pressures on accessible and economically viable forest resources.
The five LGAs selected for detailed sampling provided indicative trends; however, the results may not fully capture fine-scale spatial heterogeneity across the entire state. Continued monitoring across all LGAs, incorporating species-specific data, would significantly improve understanding of spatial patterns in timber extraction and their potential implications for biodiversity conservation and ecosystem service provision.
Data limitations and implications for monitoring
The predominance of felling within the dry rain-forest zone aligns with broader patterns of tropical forest exploitation, whereby more accessible and economically valuable forest types are subjected to higher harvesting pressure. These findings are consistent with those of Torres-Celi et al. (2025) and Rivas et al. (2021), who reported that long-term land-use transformation, coupled with unsustainable management practices, has resulted in the conversion of nearly two-thirds of the original forest cover to alternative uses.
However, the absence of species-level data constrains the ability to determine whether current logging practices are selective or indiscriminate an important distinction for assessing impacts on biodiversity and long-term forest resilience. The integration of species-specific data, alongside systematic monitoring of replanting and natural regeneration, would significantly strengthen existing assessment frameworks. Such improvements would provide a more robust basis for evaluating forest sustainability, supporting evidence-based management decisions, and informing the development of targeted conservation strategies.
Policy and management relevance
The absence of a documented replanting or afforestation programme raises significant concerns regarding the sustainability of current harvesting practices and their implications for subnational forest governance, particularly in relation to climate commitments under the 2015 Paris Agreement. This concern is consistent with findings reported by Adeyekun et al. (2023), who emphasized that forest reserves across Ondo State must be managed sustainably by ensuring that tree removal is offset by adequate replacement. Specifically, the number of trees harvested should be exceeded by replanting efforts to sustain the provision of forest goods and ecosystem services over the long term.
In the absence of systematic restoration measures, continued extraction may result in progressive degradation of forest ecosystems, with potential consequences for soil stability, hydrological processes, and habitat integrity. Although causal relationships cannot be definitively established due to the limited temporal scope of the dataset, the observed associations suggest that increased harvesting pressure may be linked to broader patterns of forest degradation.
The lack of species-specific data, coupled with the relatively short temporal coverage (five years), represents a key limitation of this study. These constraints restrict more detailed ecological interpretation, including assessments of biodiversity loss, changes in carbon stocks, and the impacts of selective versus non-selective logging practices.
Strengthening monitoring systems to incorporate species composition, regeneration rates, and replanting activities would provide a more comprehensive basis for sustainable forest management. Such improvements would support the development of evidence-based strategies aimed at balancing timber extraction with conservation objectives. Furthermore, targeted interventions to regulate seasonal harvesting patterns, improve access for sustainable operations, and systematically document restoration efforts would enhance alignment between local forest management practices and national climate and biodiversity goals.
Conclusion
This study documents temporal, seasonal, and spatial patterns of forest exploitation in Ondo State, Nigeria, between 2019 and 2023. The results indicate sustained timber extraction with interannual variability and a recent decline in felling intensity. Spatial analysis shows that harvesting pressure is concentrated in dry rainforest zones, while mangrove and swamp forests experience comparatively lower levels of extraction, reflecting differences in accessibility and forest type.
Seasonal patterns reveal higher levels of felling during the wet season, suggesting that logging activities are influenced by factors beyond physical accessibility, although these drivers were not directly examined.
The absence of documented replanting or afforestation initiatives highlights a potential imbalance between extraction and regeneration. Continued harvesting without systematic restoration may affect forest structure, carbon storage, and ecosystem functions, with implications for subnational forest management and climate commitments under the Paris Agreement.
Given the limited temporal scope and lack of species-level data, strengthened monitoring systems and integrated management approaches are essential to support long-term forest sustainability.