Awareness, Understanding, and Knowledge of the Risk Management Framework (RMF) Among Forestry Stakeholders in Northern Ghana: Implications for Forest Sustainability and Climate Resilience

1. Introduction

Forest ecosystems are central to the functioning of the biosphere, regulating carbon and water cycles, sustaining biodiversity, and underpinning the livelihoods of more than 1.6 billion people globally (FAO, 2022; IPCC, 2022). In Sub-Saharan Africa, forests deliver critical ecosystem services, ranging from soil stabilization and microclimate regulation to the provision of non-timber forest products that buffer rural communities against climate and economic shocks. Yet the region continues to lose forest cover at one of the fastest rates worldwide, with nearly 65% of land affected by some form of environmental degradation driven by deforestation, soil erosion, and unsustainable land use (Arun, 2024; Croitoru et al., 2019). These losses translate directly into reduced carbon sequestration capacity, declining biodiversity, and weakened ecological resilience to climate variability, undermining both planetary and local environmental stability (Mpuure & Mengba, 2023; Muchunguzi, 2023).

Ghana exemplifies this ecological paradox. Although the country is endowed with rich forest, mineral, and agricultural resources, weak governance and unsustainable extraction have eroded the very ecosystems on which national development depends (Asiedu et al., 2021; Totouom et al., 2024). Northern Ghana, situated within the Guinea Savannah ecological zone, is particularly vulnerable. Its sparse but ecologically vital tree cover, dominated by shea (Vitellaria paradoxa), dawadawa (Parkia biglobosa), neem (Azadirachta indica), and baobab (Adansonia digitata), forms a parkland mosaic that supports biodiversity, regulates local microclimates, and sustains carbon stocks in a semi-arid landscape already experiencing rising temperatures and erratic rainfall (Fagariba et al., 2018; Ankomah et al., 2020). Over 60% of forest reserves in this zone are under severe threat from illegal logging, charcoal production, agricultural expansion, and bushfires, accelerating biodiversity loss, soil degradation, and the erosion of climate buffering capacity. Despite policy interventions such as the 1994 Forest and Wildlife Policy and various afforestation programmes, forest governance has been hampered by weak enforcement, fragmented institutional coordination, and limited stakeholder engagement, leaving the ecosystem highly exposed to compounding environmental risks (Sarfo-Adu, 2021; Nyamekye et al., 2023).

Effective response to these biosphere-level pressures requires governance instruments capable of anticipating, assessing, and mitigating environmental risk in a systematic and adaptive manner. The Risk Management Framework (RMF) offers such a structured approach, providing tools for risk identification, assessment, mitigation, and continuous monitoring across complex socio-ecological systems (Adebisi et al., 2023). Although originally developed for financial and corporate sectors, RMF has been successfully adapted to disaster risk reduction, climate resilience planning, and infrastructure governance (Hilbig & Rudolph, 2019; Forson & Gavu, 2017). Its application to forestry governance holds significant promise for strengthening ecological resilience: by formalising risk anticipation and adaptive management, RMF can support climate-smart forest stewardship, reduce biodiversity loss, and enhance the long-term sustainability of forest-dependent ecosystems (Acheampong et al., 2019; Somuah et al., 2021). However, the operational integration of RMF into Ghana’s forestry sector remains weak, and there is little empirical evidence on whether key stakeholders, those whose decisions and practices directly shape forest outcomes, possess the awareness and understanding required to implement it effectively.

This gap is particularly consequential in Northern Ghana, where ecological fragility, climate exposure, and institutional limitations intersect. Without a clear understanding of how stakeholders perceive and engage with risk-based environmental governance tools, efforts to translate RMF principles into measurable improvements in forest cover, biodiversity, and climate adaptation outcomes will remain limited. To date, no study has systematically assessed the extent of RMF awareness, the depth of stakeholder understanding, or the determinants of risk literacy across the diverse actors that shape Northern Ghana’s forest landscape. This study addresses that gap by examining the awareness, understanding, and knowledge of the RMF among forestry stakeholders in Northern Ghana, and by analysing how socio-demographic and institutional factors shape engagement with risk governance. In doing so, the study contributes to biosphere-level understanding of how human knowledge systems mediate ecological outcomes in dryland forest landscapes and provides evidence-based insights to strengthen forest sustainability, biodiversity conservation, and climate resilience in similar socio-ecological contexts across Sub-Saharan Africa.

2. Literature Review

2.1. Theoretical Background/ Conceptual Framework: An Integrated Risk Governance Lens for Forest Ecosystems

[This study is grounded in an integrated conceptual framework that draws on four complementary theoretical traditions, governance theory, institutional theory, systems theory, and adaptive management/resilience thinking, to explain how stakeholder awareness and understanding of risk management frameworks shape forest ecosystem outcomes in Northern Ghana. Together, these perspectives provide an analytical lens for examining the relationship between human knowledge systems, institutional structures, and biosphere-level ecological resilience.

Governance theory emphasizes that environmental risk management is most effective when decision-making processes are collaborative, inclusive, and accountable across multiple stakeholders, including government agencies, civil society, traditional authorities, and private actors (Caraiman & Mateș, 2020; Renn et al., 2020). Within this framework, risk is treated as an inherent feature of socio-ecological systems, requiring deliberate coordination among actors with differing levels of knowledge, authority, and access to resources. Collaborative governance models foster participation, enhance policy legitimacy, and improve alignment of stakeholder interests, which is critical for achieving Sustainable Development Goals related to life on land, climate action, and sustainable resource use (Okeyo et al., 2020; Bodin, 2017). Applied to forestry, this perspective implies that effective RMF integration depends not only on the quality of the framework itself but on the awareness and capacity of the stakeholders expected to operationalise it.

Institutional theory complements this view by explaining how formal regulations, social norms, and cultural beliefs shape organizational risk management practices (Suray et al., 2019). The regulatory, normative, and cultural-cognitive pillars of institutions help explain why some stakeholders comply with risk governance rules while others resist or reinterpret them based on shared mental models and local traditions. In contexts such as Northern Ghana, where customary institutions coexist with formal forestry agencies, institutional pluralism creates both opportunities for participatory governance and risks of fragmented enforcement (Ahmed et al., 2022; Loro & Zeitoune, 2017).

Systems theory frames forest landscapes and their governance as interconnected socio-ecological systems characterised by interdependence, feedback loops, and emergent behaviour (Zhang et al., 2022; Hatefi et al., 2019). From this perspective, risks to forest cover, biodiversity, and climate buffering capacity cannot be addressed in isolation; they emerge from the interaction of ecological, institutional, and socio-economic subsystems. Risk management is therefore most effective when it accounts for these interactions, enabling proactive, integrated, and adaptive responses to both predictable and emergent environmental threats (Wu et al., 2021; Li et al., 2017).

Finally, adaptive management and resilience thinking emphasize continual learning, flexibility, and system-level robustness in the face of uncertainty (Folke, 2016; Olsson et al., 2015). Adaptive management enables institutions to revise strategies as new ecological knowledge emerges, while resilience thinking focuses on maintaining ecosystem functionality under shocks such as drought, fire, and land-use change. Community engagement and traditional ecological knowledge are critical components of this approach, ensuring that governance strategies are socially legitimate, context-sensitive, and capable of sustaining ecological and social systems (Jozaei et al., 2022; Salomon et al., 2019). Taken together, these theoretical perspectives converge on a central proposition that guides the present study: the effective integration of risk management frameworks into forest governance depends on stakeholders’ awareness, understanding, and applied knowledge of risk processes, mediated by institutional support, sociocultural context, and adaptive learning capacity. This integrated lens informs the study’s analytical focus on assessing stakeholder awareness and knowledge of RMF, and on identifying the socio-demographic and institutional determinants that shape engagement with risk governance in Northern Ghana’s forest landscape (Figure 1).

2.2. Stakeholder Awareness and Knowledge as Drivers of Forest Ecosystem Outcomes

Effective implementation of Risk Management Frameworks (RMFs) in forestry depends on the awareness, knowledge, and capacity of diverse stakeholders, whose decisions ultimately shape forest cover, biodiversity, and climate resilience outcomes. Forestry systems face increasing vulnerabilities from climate change, deforestation, and socio-economic pressures, making stakeholder understanding of RMFs essential for sustainable governance (Jamil et al., 2024). Awareness of RMF principles enables stakeholders to anticipate environmental risks, participate in adaptive decision-making, and contribute to long-term ecosystem stewardship rather than reacting only to past disturbances.

Empirical studies indicate that contextual and cultural relevance of RMFs is crucial for their uptake. Mahadewi et al. (2022) argue that conventional risk management approaches often neglect local socio-cultural perspectives, highlighting the need to design RMFs that are responsive to the lived realities of forest-dependent communities. Similarly, Eriksson (2017) shows that demographic factors such as gender, education, and geographic location significantly influence stakeholders’ engagement and coherence in risk governance. In dryland and savannah ecosystems, where ecological pressures intersect with poverty and weak extension services, these contextual factors become particularly consequential for translating awareness into improved forest outcomes. Capacity-building initiatives, including participatory learning and targeted awareness campaigns, can help overcome cognitive and social barriers, enabling stakeholders to anticipate future risks rather than focus solely on past experiences (Vulturius & Swartling, 2015).

Education and training programmes play a key role in fostering risk literacy and governance skills. Fuller and Quine (2015) suggest that resilience-thinking principles incorporated into educational programs can enable stakeholders to make informed, adaptive decisions. Saeidi et al. (2020) also note that risk-aware organizational cultures facilitate the adoption of RMFs, strengthening compliance and stakeholder confidence. High levels of awareness and applied knowledge are linked to greater community participation, ownership of forest resources, and long-term ecological stewardship, factors that directly influence biodiversity conservation and forest carbon sequestration outcomes (Paletto et al., 2019).

2.3. Determinants of Risk Literacy: Education, Institutional Support, and Engagement

Stakeholder engagement is closely tied to RMF awareness and knowledge, as engagement provides the channels through which information, training, and feedback flow between institutions and forest-dependent communities (Tran et al., 2022). Education is critical for building both technical and conceptual capacity. Training programs enable stakeholders to perceive risks, adapt to changing environmental conditions, and adopt sustainable practices that support forest ecosystem health (Tumuhe & Kiguli, 2019). Institutional support further strengthens engagement by creating enabling environments for collaboration and participatory governance (Asogwa et al., 2023; Iyere & Misopoulos, 2022). Empirical evidence shows that awareness mediates adaptive behaviour and strengthens local ownership and resilience, with measurable effects on forest cover and ecosystem service delivery (Wright & Hylton, 2024; Poudyal et al., 2019).

However, persistent challenges constrain the effectiveness of these determinants. Socio-psychological barriers, limited time and resources, and inconsistent institutional support reduce the depth of engagement that stakeholders can sustain over time. Overcoming these requires context-sensitive, culturally competent approaches, supported by digital tools and remote sensing technologies that enhance communication, real-time risk monitoring, and data-driven decision-making in resource-constrained forest landscapes.

2.4. Barriers to RMF Adoption: Institutional Inertia and Resistance

Even where awareness exists, institutional inertia and resistance to change remain major barriers to the adoption and integration of RMFs in forestry governance. Institutional inertia refers to the tendency of organizations to adhere to traditional practices, maintain vested interests, and resist policy or procedural innovations (Jamil et al., 2024). This resistance often produces bureaucratic inefficiencies, rigid decision-making structures, and a reluctance to incorporate innovative risk management strategies, limiting the flexibility required to respond to emerging ecological threats such as climate-induced drought, biodiversity loss, and forest fires.

Empirical studies highlight the consequences of institutional inertia for environmental outcomes. Kanobe et al. (2022), although focused on cybersecurity, illustrate the broader principle that failure to adapt to emerging risks exacerbates organizational vulnerabilities, a dynamic equally relevant to forest governance institutions. Similarly, Salin and Lundgren (2022) emphasize that organizations not responsive to changing environments risk losing both ecological and socio-economic outcomes. Factors such as fear of the unknown, perceived loss of control, and conflicting stakeholder interests further amplify resistance (Melaku, 2023; Ma et al., 2018). Cultural factors also influence attitudes toward change, making locally sensitive communication and education strategies crucial (Gupta et al., 2019).

Addressing institutional inertia requires fostering a learning and adaptive culture within forestry governance. Leadership commitment, flexible governance structures, and capacity-building programmes can facilitate openness to change, enhance stakeholder participation, and ensure that RMFs are integrated effectively into routine forest management practices (Husain et al., 2022; Gupta et al., 2024).

2.5. Sociocultural and Economic Influences on Risk Perception

Beyond institutional factors, sociocultural and economic conditions strongly shape how stakeholders perceive environmental risks and engage with RMFs. Cultural beliefs, traditions, and values influence stakeholders’ understanding of environmental risks and their responses to forestry management strategies (Dryhurst et al., 2020). In agrarian communities such as those across Northern Ghana, traditional ecological knowledge often prioritizes long-term conservation of culturally significant species such as shea and dawadawa, highlighting the importance of integrating local knowledge into RMF design and implementation.

Economic conditions also shape risk perception and decision-making. Economic insecurity and poverty may prioritize short-term survival over long-term sustainability, amplifying vulnerabilities to environmental risks and weakening the capacity to invest in preventive forest management practices (Li & Lyu, 2021). Additionally, socio-economic inequalities can lead to disparities in access to knowledge, resources, and decision-making processes, reducing the effectiveness of RMFs in marginalized communities.

Media and communication channels further influence risk perception and engagement. Social media, news, and other information sources can rapidly alter public perception and behavior, requiring tailored and culturally sensitive communication strategies (Dryhurst, 2020; Janning et al., 2021). Trust in formal institutions is another critical determinant; low public trust hinders compliance, reduces stakeholder participation, and undermines the legitimacy of forestry governance interventions (Terraneo et al., 2021).

2.6. Knowledge Gaps and Study Contribution

Despite a growing body of research on stakeholder awareness and capacity in forestry risk management, several knowledge gaps remain that this study seeks to address.

First, there is limited empirical evidence on the implementation of Risk Management Frameworks in Northern Ghana’s Guinea Savannah ecosystem, with most studies relying on international examples drawn from temperate or tropical rainforest contexts that may not reflect the ecological, governance, and socio-economic realities of dryland forest landscapes. Second, while sociocultural and economic factors are acknowledged to influence risk perception and engagement with RMFs, little is known about how these factors interact in agrarian savannah communities to shape decision-making, including the role of traditional ecological knowledge associated with culturally significant tree species.

Third, although training programs and extension services are recognised as critical for building technical capacity, few studies have systematically evaluated their effectiveness in sustaining awareness, adaptive capacity, and stakeholder participation in forestry governance in resource-constrained settings. Fourth, institutional inertia and resistance remain significant barriers, yet evidence is limited on how leadership, governance structures, and participatory approaches can overcome these challenges to support RMF integration in Sub-Saharan African forestry contexts.

Fifth, the potential of digital and technological tools, such as mobile applications, geographic information systems (GIS), and remote sensing, to enhance awareness, real-time forest monitoring, and stakeholder engagement is largely unexplored, particularly in rural and resource-constrained settings of Northern Ghana. Finally, there is a lack of context-specific policy analysis linking national forestry policies to RMF uptake, stakeholder engagement, and measurable improvements in forest cover, biodiversity, and climate resilience outcomes]

This study contributes to closing these gaps by providing the first systematic, mixed-methods assessment of RMF awareness, understanding, and knowledge among forestry stakeholders in Northern Ghana, and by analysing the socio-demographic and institutional factors that shape risk literacy in a climate-vulnerable dryland forest landscape. In doing so, it advances biosphere-level understanding of how human knowledge systems mediate ecological resilience, and informs context-specific strategies for sustainable forestry governance in similar socio-ecological contexts across Sub-Saharan Africa.

3. Methodology

3.1. Study Area

The study was conducted in three regions across five districts in Northern Ghana. These included the North-East Region (East Mamprusi and Mamprugu Moagduri Districts), the Savannah Region (North Gonja District), and the Northern Region (Sagnarigu Municipality and Tamale Metropolitan Area).

The North-East Region, with East Mamprusi and Mamprugu Moagduri as key districts, are largely rural and characterized by subsistence farming, savannah vegetation, and limited infrastructural development. East Mamprusi Municipal has a population of 188,006 in the 2021 Population and Housing Census, making it one of the most populous districts in the North-East Region. Mamprugu Moagduri District, also in the North-East Region, recorded 68,746 inhabitants as of 2021.

The Savannah Region’s North Gonja District is noted for its vast land area, low population density, and heavy reliance on agriculture and livestock rearing. North Gonja District has a relatively smaller population of 61,432 in the same census year.

In the Northern Region, the Sagnarigu Municipality and Tamale Metropolitan Area represent more urbanized and peri-urban settings, with relatively better infrastructure, higher population density, and diverse socio-economic activities. Sagnarigu Municipality counted 341,711 residents in 2021, while the Tamale Metropolitan Area recorded 374,744 inhabitants. These two urban areas are among the most densely populated in the northern part of the country and represented major hubs of socio-economic activity.

These three regions together formed a representative mix of rural, peri-urban, and urban environments, allowing the study to capture varied perspectives on forestry governance, natural resource management, and community participation. The selection of the districts also reflected ecological diversity, socio-economic dynamics, and administrative relevance to the forestry sector in Northern Ghana.

3.1.1. Vegetation

The vegetation of the study area is largely classified under the Guinea Savannah ecological zone, which dominated most parts of Northern Ghana. This zone is characterized by vast grasslands interspersed with scattered trees and shrubs, creating a park-like landscape. The major tree species commonly found include shea (Vitellaria paradoxa), dawadawa (Parkia biglobosa), neem (Azadirachta indica), and baobab (Adansonia digitata), which play important ecological roles in supporting biodiversity, regulating local microclimates, and sustaining livelihoods through non-timber forest products.

In the East Mamprusi and Mamprugu Moagduri Districts, vegetation cover is predominantly open savannah woodland, consisting of tall grasses such as Andropogon and Hyparrhenia species, with scattered trees adapted to withstand prolonged dry seasons and bushfires. North Gonja District, which lay within the Savannah Region, is covered by similar Guinea Savannah vegetation, but with relatively more open grassland due to overgrazing and human activities such as charcoal production and shifting cultivation.

The Northern Region, particularly Sagnarigu and Tamale Metropolis, exhibit savannah woodland vegetation that has been significantly modified by rapid urbanization and agricultural expansion. Much of the natural tree cover has been cleared for housing, markets, and road infrastructure, leaving fragmented patches of indigenous vegetation. Despite this, certain resilient tree species such as neem and baobab continued to thrive in homesteads and community lands.

The regions face high rates of deforestation, land degradation, biodiversity loss, and weak enforcement of environmental policies, making the area an ideal context for assessing how a Risk Management Framework (RMF) could enhance forestry governance and ecological resilience.

Overall, the vegetation across the study districts reflected a transition from relatively intact savannah woodlands in the rural areas to more degraded and fragmented landscapes in the urban centers. Despite the presence of several forest reserves, deforestation and land degradation remain pressing environmental concern. This pattern of vegetation change underscored the increasing pressure on natural resources resulting from population growth, agricultural activities, and urban expansion in Northern Ghana.

3.1.2. Climate

The wet season spans from April to October, while the dry season occurs from January to March, during which the northeast trade winds (Harmattan) bring dry and dusty conditions. The region experiences an annual rainfall ranging from 750mm to 1,050mm and temperature fluctuations between 14°C at night and 40°C during the daytime. These climatic conditions make the area highly vulnerable to drought, erratic rainfall, and bushfire risks, all of which directly influence forest cover and ecosystem stability.

3.1.3. Economic Activities

Northern Ghana is largely agrarian, with over half of the economically active population engaged in agriculture. Key agricultural activities include the cultivation of maize, rice, millet, yams, and groundnuts. Additionally, the regions have significant forest resources, which are increasingly under threat due to unsustainable farming practices, illegal logging, and charcoal production (Ghana Districts, 2025; Ghana Statistical Service, 2021) (Figure 2).

3.2. Research Design

This study used a mixed methods research design, combining quantitative and qualitative approaches to understand forestry governance and risk management in Northern Ghana (Molina-Azorín & López-Gamero, 2016). Specifically, an explanatory sequential design was employed, where quantitative surveys were conducted first, followed by qualitative interviews and focus group discussions to provide deeper insights into the numerical trends (Mertens, 2022).

The quantitative phase targeted forestry officials, policymakers, and community members to assess governance challenges and RMF awareness, while the qualitative phase explored stakeholder perspectives on RMF implementation. The qualitative findings were used to triangulate, contextualise, and explain the quantitative results, ensuring that statistical patterns were interpreted in light of stakeholders’ lived experiences and the socio-cultural realities of forest-dependent communities (Steinmetz-Wood, Pluye, & Ross, 2019).

Although sequential mixed methods can be time-intensive and require careful integration of datasets (O’Sullivan & Howden-Chapman, 2017), it provides a holistic understanding of forestry governance challenges and the applicability of RMFs, offering valuable insights for policymakers and practitioners (Kinnebrew et al., 2020).

3.3. Study Population and Sampling

The study population comprised key stakeholders involved in forestry governance and environmental sustainability in Northern Ghana. This included traditional authorities (chiefs and elders), opinion leaders (community and religious leaders), government agencies (Forestry Commission, EPA, Northern Development Authority, MMDAs, Department of Agriculture, Land Use and Spatial Planning, Ghana Lands Commission), academia and research institutions (University for Development Studies, Tamale Technical University, Savanna Agricultural Research Institute), NGOs and advocacy groups engaged in conservation, climate change, and community-based natural resource management, and Community Resource Management Area (CREMA) groups operating across the study districts.

A mixed sampling approach was used. Simple random sampling selected traditional authorities, opinion leaders, and farmers to ensure equal chances of inclusion and reduce bias. Purposive sampling targeted key informants from government agencies, academia, and NGOs based on their expertise and direct involvement in forestry governance. For the qualitative phase, purposive sampling was also used to select 108 CREMA groups and forestry-related institutional actors with direct experience in community-level forest management. This combination ensured representation of diverse perspectives, enhancing the study’s capacity to assess governance challenges and the integration of a Risk Management Framework (RMF) in the forestry sector.

3.4. Sample Size Determination

To determine an appropriate sample size for the quantitative component, Cochran’s formula for sample size determination was applied. This formula is widely used in survey research when the population size is unknown or large. The formula is expressed as follows:

$$n={\displaystyle \frac{Z^2.p(1-p)}{e^2}}$$

where:

• n= sample size
• z= Z-score corresponding to the desired confidence level (1.96)
• p = Estimated proportion of the population with the characteristic of interest ( 0.5)
• e = Margin of error ( set at 8% or 0.08)

Replacing these into the equation,

We would have;

$$\begin{gathered} n={\displaystyle \frac{{\left(1.96\right)}^2.0.5(1-0.5)}{{\left(0.08\right)}^2}} \\ ={\displaystyle \frac{0.9604}{0.0064}=150.0625} \\ =150 \end{gathered}$$

Thus, the required sample size for this study is 150 respondents. However, this was adjusted to 160 for non-responsive or incomplete responses.

3.5. Data Collection Procedures

Quantitative data were collected through structured questionnaires administered face-to-face to 160 respondents across the five study districts in 2025. The questionnaire was organised into five sections covering: (i) socio-demographic characteristics, (ii) awareness of the Risk Management Framework, (iii) understanding of RMF concepts and elements, (iv) knowledge of RMF components, benefits, and responsible institutions, and (v) sources of information and perceived institutional support.

Prior to full deployment, the questionnaire was pilot-tested with 16 respondents drawn from a non-study district to assess clarity, contextual relevance, and time burden. Feedback from the pilot informed the rewording of ambiguous items, the simplification of technical RMF terminology, and the inclusion of locally relevant examples. The pilot-test responses were not included in the final analysis.

The qualitative component comprised five Focus Group Discussions (FGDs) and seven Key Informant Interviews (KIIs). The FGDs were conducted in five purposively selected communities, namely Bugyinga, Yamah, Jadema, Kategri, and Bulbia, with members of Community Resource Management Area (CREMA) groups and other community-based natural resource management groups. Each FGD comprised 8–10 participants and lasted between 60 and 90 minutes. The KIIs were conducted with seven institutional actors: three officers from the Forestry Commission, two officers from the Environmental Protection Agency (EPA), and two officers from the Ministry of Food and Agriculture (MoFA). All discussions and interviews were audio-recorded with informed consent, transcribed verbatim, and analysed thematically using an inductive coding approach. Codes were grouped into broader analytical categories, and recurring themes were identified across communities and institutional actors. Five major themes emerged from the qualitative analysis: (i) reliance on traditional and indigenous forest management practices, (ii) the central role of CREMA structures, chiefs, and by-law enforcement in local risk governance, (iii) consistently identified environmental risks, including illegal logging, charcoal burning, bushfires, herder–farmer conflicts, and climate change, (iv) climate vulnerability indicators recognised as informal early warning signals, such as erratic rainfall, prolonged drought, and early drying of vegetation, and (v) persistent institutional and capacity gaps, including financial constraints, weak enforcement, conflicts of interest among leaders, and limited technological support for forest monitoring.

A notable cross-cutting observation was that while most community participants reported having "heard of" RMF, their explanations described indigenous practices rather than the formal RMF framework, indicating a divergence between self-reported awareness and conceptual understanding. This finding informed the interpretation of the quantitative results and is discussed further in Section 5.

3.6. Data Analysis

Quantitative data were analysed using descriptive and inferential statistics. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarise socio-demographic characteristics, levels of RMF awareness, sources of information, and stakeholders’ interpretations of RMF concepts and elements.

To provide a standardised measure of stakeholders’ applied knowledge of the RMF, a Knowledge Scoring Index (KSI) was developed and computed as part of the analytical procedure. The index comprised three core knowledge items administered as binary correct/incorrect questions: (i) identification of the components of an RMF; (ii) identification of the primary benefit of integrating RMF into forestry governance; and (iii) identification of the institution primarily responsible for implementing RMF in Ghana’s environmental governance. Each item was scored as 1 for a correct response and 0 for an incorrect or "do not know" response. Individual scores were summed to produce a composite knowledge score, which was then standardised to a 0–1 scale to allow comparison across stakeholder groups.

Content validity of the KSI was established through expert review by three forestry governance specialists drawn from academia and the Forestry Commission, who assessed the relevance, clarity, and adequacy of each item. Construct relevance was further confirmed through pilot testing with 16 respondents prior to full deployment. Internal consistency reliability of the index was tested using Cronbach’s alpha, which yielded a value of α = 0.78, exceeding the conventional 0.70 threshold reliability for the three-item index (Tavakol & Dennick, 2011).

To examine the determinants of RMF knowledge, multiple linear regression analysis was conducted, with the composite RMF knowledge score (ranked on a 1–5 scale) as the dependent variable, and education, occupation, gender, and other socio-demographic factors as independent variables. Multiple linear regression was selected because the dependent variable was continuous and ordinally ranked, allowing for the estimation of the magnitude and direction of effects of each predictor. Assumptions of linearity, normality of residuals, homoscedasticity, and absence of multicollinearity were tested and met prior to model estimation. Statistical significance was assessed at the p < 0.05 level, with marginal significance reported at p < 0.10. All quantitative analyses were performed using SPSS version 26.

Qualitative data from FGDs and KIIs were analysed thematically following the six-phase approach by Braun and Clarke (2006): (i) data familiarisation, (ii) initial code generation, (iii) theme search, (iv) theme review, (v) theme definition and naming, and (vi) report production. Coding was conducted manually, with cross-checking between two researchers to enhance inter-coder reliability. Themes derived from the qualitative analysis are integrated within the Discussion section to provide explanatory and contextual depth to the quantitative findings, in line with the explanatory sequential mixed-methods design.

3.7. Ethical Considerations

Ethical approval for the study was obtained from the University for Development Studies Institutional Review Board. Prior to data collection, all participants were briefed on the purpose of the study, their rights, and the confidentiality of their responses. Written informed consent was obtained from literate participants, while verbal consent (witnessed and documented) was obtained from non-literate participants in line with the Declaration of Helsinki. Participation was entirely voluntary, and respondents were assured of their right to withdraw at any stage without consequence. All audio recordings, transcripts, and survey data were anonymised and stored securely on password-protected devices accessible only to the research team.

4. Results

4.1. Socio-Demographic Characteristics of Respondents

A total of 160 stakeholders participated in the quantitative survey across the five study districts in Northern Ghana, namely West Mamprusi, Mamprugu Moagduri, North Gonja, Sagnarigu, and Tamale Metropolitan. Table 1 presents the consolidated socio-demographic profile of respondents, including district distribution, gender, age, marital status, education, occupation, years of experience in forestry or environmental management, and forest land ownership.

The respondent sample reflected a deliberate mix of rural, peri-urban, and urban stakeholders distributed across the Guinea Savannah landscape, with the highest representation drawn from Mamprugu Moagduri (24%) and West Mamprusi (23%), and the lowest from Sagnarigu (11%). In terms of age, the largest group of respondents was 35–44 years (32%), followed by 45–54 years (26%), reflecting an experienced working-age population engaged in forestry and natural resource activities. Most respondents were married (88%), consistent with the predominantly agrarian and household-based economic structure of Northern Ghana.

A pronounced gender imbalance was observed, with 66% of respondents being male and 34% female. This disparity reflects the broader pattern of male dominance in leadership, governance, and formal forestry roles in Northern Ghana, where customary structures, land tenure arrangements, and institutional appointments have historically favoured male representation. The implications of this imbalance for the gender-related findings of the regression analysis are addressed in Section 4.4.2 and the Discussion.

Educational attainment varied considerably across the sample. The largest group, 36%, had no formal education, while 23% had attained tertiary education and 10% held postgraduate qualifications. The remaining respondents had completed primary (7%), junior high (8%), or senior high (16%) levels. This bimodal distribution, with a substantial proportion of respondents at either end of the education spectrum, has direct implications for how RMF information is received, understood, and applied across stakeholder groups.

Occupational composition was dominated by community leaders (38%) and farmers (23%), followed by District Assembly officials (15%), NGO representatives (8%), forestry workers (7%), Community Forest Management group members (5%), and researchers or academics (4%). This distribution mirrors the actual structure of forest governance actors in Northern Ghana, where community-level actors, particularly chiefs, opinion leaders, and farmers, dominate day-to-day decisions on land use, while formal institutions play a more strategic and supervisory role.

Experience in forestry or environmental management was relatively well distributed: 32% of respondents had 6–10 years of experience, 29% had 1–5 years, and 27% had more than 10 years, while only 12% had less than one year of involvement. This depth of experiential knowledge strengthens the credibility of the findings, as the majority of respondents drew on substantive engagement with forest resources rather than peripheral exposure.

Forest land ownership was reported by 78% of respondents, with the highest concentrations in Mamprugu Moagduri and West Mamprusi. The high level of land ownership among respondents is a significant finding for forest governance: it indicates that the majority of the sample holds direct stakes in forest sustainability outcomes, making their awareness and understanding of RMF principles particularly consequential for ecological resilience in the Guinea Savannah landscape.

The full district-level cross-tabulation of socio-demographic variables is provided in Supplementary Table S1.

4.2. Awareness of RMF

4.2.1. General Awareness of Risk Management Framework (RMF)

Overall awareness of the Risk Management Framework (RMF) among forestry stakeholders in Northern Ghana was high, with 94% (n = 150) of the 160 respondents indicating that they had heard of RMF in the context of environmental management. However, this aggregate figure masked important variations in how that awareness was distributed across stakeholder groups. Among those who reported awareness, community forest management groups and government officials accounted for the highest proportions at 15% each, followed by farmers and researchers/academics at 15%. Forestry workers and local community leaders represented 14% each, while NGO representatives accounted for the lowest share at 12% (Figure 3). The relatively even distribution of awareness across categories suggests that RMF concepts have diffused beyond technical institutions into community-level actors, an encouraging signal for participatory forest governance in the Guinea Savannah landscape.

4.2.2. Source of Information on Env’tal Management/Risk Management Framework

Information on environmental management and risk management frameworks reached stakeholders through multiple channels, but local community leaders consistently emerged as the dominant source across all pathways. They accounted for 37% of information from government policies or programmes, 39% from environmental NGOs, 39% from academic and research publications, and 41% each from professional training/workshops and media sources. Farmers also represented a substantial proportion of information access, particularly through government programmes (26%) and media (26%). Government officials reported notable reliance on government policies and academic sources (17% each), while community forest management groups showed relatively balanced access across all information sources (6–7%). Forestry workers and NGOs contributed smaller but consistent proportions across the different channels (Figure 3).

This pattern indicates that information flow on RMF is heavily mediated through community leadership structures rather than reaching grassroots actors directly. While this reflects the trust traditionally vested in chiefs and opinion leaders in Northern Ghana, it also raises concerns about potential bottlenecks, message distortion, and uneven knowledge dissemination, issues that are explored further in the Discussion.

Figure 3. Sources of information on environmental management and RMF across stakeholder groups. 

Figure 3. Sources of information on environmental management and RMF across stakeholder groups. 

4.3. Understanding of RMF Concepts

4.3.1. Level of Understanding of RMF

Levels of RMF understanding varied substantially across stakeholder groups. Forestry workers demonstrated the highest depth of understanding, with 27% reporting expert-level knowledge and 45% indicating good understanding. Government officials also showed relatively strong comprehension, with 42% reporting basic understanding, 21% good understanding, and 8% expert understanding.

Academic respondents largely reported good (50%) or basic (33%) understanding, while community forest management groups showed mixed levels, with 38% indicating basic understanding and 25% each reporting good and moderate understanding. Farmers exhibited the lowest overall understanding, with 30% reporting no understanding and 43% indicating only basic knowledge. Local community leaders similarly showed limited familiarity, with 25% reporting no understanding and 33% indicating moderate understanding. NGO respondents primarily reported moderate (38%) and good (31%) understanding (Figure 4).

These differences reflect the influence of formal education, institutional exposure, and access to structured training. The weaker understanding among farmers and community leaders, despite their high reported awareness, indicates a gap between exposure to RMF terminology and the technical comprehension required to apply it in forest management decision-making.

4.3.2. Interpretation of RMF Concepts by Respondents

Stakeholders differed notably in how they conceptualised the RMF. Local community leaders accounted for the largest share across all interpretation categories, particularly viewing RMF as a strategy for financial risk management (47%) and as a government policy for environmental conservation (42%). Farmers similarly showed broad interpretations, with 23% associating RMF with environmental risk management, government policy, and legal forestry protection.

Government officials primarily interpreted RMF as a legal framework for forestry protection (15%) and as a structured approach to environmental risk management (14%). Forestry workers showed relatively balanced interpretations, while NGO and academic respondents contributed smaller proportions across all categories (Figure 5).

The strong association by community leaders of RMF with "financial risk management" is particularly revealing, it suggests that the concept, although familiar by name, is being interpreted through everyday economic frames rather than as a structured environmental governance tool. This conceptual mismatch has direct implications for how RMF principles are likely to be operationalised at the community level.

4.3.3. Key Elements Identified as Essential in RMF

Local community leaders and farmers were the most prominent stakeholder groups identifying essential elements of the RMF. Local community leaders consistently accounted for the largest proportions across all elements, including risk identification (38%), risk assessment (39%), risk mitigation (37%), risk monitoring and review (39%), stakeholder participation (36%), and policy enforcement mechanisms (36%). Farmers also demonstrated substantial representation, particularly emphasizing stakeholder participation (27%), policy enforcement mechanisms (25%), and risk identification (24%).

Government officials highlighted risk mitigation (16%), stakeholder participation (17%), and risk monitoring and review (15%) as key components. Forestry workers showed relatively balanced contributions across technical elements, while community forest management groups and NGOs contributed smaller but consistent proportions. Academic respondents accounted for the lowest proportions across all elements (Table 2). The strong recognition of risk identification, mitigation, and monitoring as essential RMF elements suggests that stakeholders implicitly grasp the operational core of risk governance. However, the relatively lower emphasis on policy enforcement mechanisms across most groups, except community leaders and farmers, points to a perceived weakness in institutional accountability, a finding consistent with broader concerns about enforcement gaps in Ghana’s forestry sector.

4.4. Knowledge of RMF

4.4.1. Knowledge Scoring Index on RMF

Knowledge Scoring Index (KSI) was developed using three core items designed to assess stakeholders’ understanding of the Risk Management Framework (RMF) in forestry governance. These items included: (1) identification of the key components of the RMF; (2) recognition of its primary benefit within forestry governance; and (3) identification of the institution primarily responsible for RMF implementation in Ghana. Each correct response was coded as 1 and incorrect responses as 0, and a composite mean score was subsequently calculated. To ensure methodological robustness, internal consistency was assessed using Cronbach’s Alpha, which produced an acceptable coefficient for exploratory social science research, indicating moderate reliability among the items. Content validity was established through expert review by specialists in environmental governance and forestry policy, while face validity was confirmed through pre-testing with a small group of stakeholders prior to the main survey.

The revised results indicate that stakeholders’ applied knowledge of the RMF, as measured by the KSI, was generally low across the three items. The mean score for identifying RMF components was 0.56, suggesting that fewer than half of respondents answered correctly. Knowledge of the primary benefit of integrating the RMF into forestry governance showed the highest performance, with a mean score of 0.91, indicating strong awareness of its conceptual value for proactive environmental decision-making. In contrast, awareness of the institution responsible for RMF implementation in Ghana was notably low, with a mean score of 0.32.

These findings point to weak institutional visibility, limited public engagement by responsible agencies, insufficient dissemination of RMF-related information through extension and community sensitisation efforts, overlapping institutional mandates, fragmented governance structures, and limited inter-agency coordination. Collectively, these challenges contribute to low policy literacy and constrained stakeholder participation in forestry governance processes in Ghana.

The composite mean KSI score across the three items was 0.60 (Table 3). Overall, the pattern suggests relatively strong awareness of the conceptual benefits of the RMF but weak knowledge of institutional responsibility. This indicates a clear institutional visibility gap: while stakeholders recognise the importance of the RMF, many are uncertain about which institution is mandated to implement and enforce it. This disconnect limits the translation of awareness into accountability and coordination, thereby constraining effective implementation and long-term forest sustainability outcomes.

4.4.2. Determinants of RMF Knowledge: Multiple Linear Regression Analysis

A multiple linear regression analysis was conducted to identify the socio-demographic and occupational factors that significantly influenced respondents’ RMF knowledge scores (ranked 1–5). The results, presented in able 4, indicate that educational level, knowledge score (as a composite indicator), and occupational category were significant predictors of RMF awareness and knowledge.

Higher educational attainment was associated with increased RMF knowledge (β = 0.042, p = 0.006), and respondents with higher composite knowledge scores were substantially more likely to demonstrate stronger awareness (β = 0.671, p < 0.001). Several occupational categories showed significantly higher scores relative to farmers, who served as the reference group: government officials (β = 0.231, p = 0.011), NGO representatives (β = 0.198, p = 0.026), forestry workers (β =0.284, p = 0.002), and researchers/academics (β = 0.352, p = 0.001) all had significantly greater RMF knowledge, reflecting their closer engagement with formal environmental governance processes and access to institutional information networks. Gender was not a significant predictor (β = 0.058, p = 0.287), and local community leaders did not differ significantly from farmers (β = 0.112, p = 0.185). The model explained 47% of the variance in RMF knowledge (R² = 0.47; Adjusted R² = 0.44), indicating moderately strong explanatory power.

The non-significance of gender is a particularly notable finding. While gender disparities are commonly assumed to shape access to environmental information in rural Northern Ghana, this result suggests that the structural barriers to RMF knowledge including limited extension services, weak institutional visibility, inadequate policy communication, and reliance on community leaders as intermediaries affect men and women similarly. Likewise, the absence of a significant difference between farmers and community leaders, despite the latter’s central role in information dissemination, indicates that holding a leadership position does not automatically translate into deeper technical knowledge of RMF. This finding highlights important gaps in institutional capacity-building and stakeholder training within community governance systems.

The results further reveal critical knowledge and institutional gaps within Ghana’s forestry governance framework. First, the relatively lower RMF knowledge among farmers and local leaders suggests insufficient grassroots dissemination of RMF-related information, despite these groups being directly involved in forest resource management and environmental decision-making. Second, the strong association between education and RMF awareness points to persistent educational inequalities in access to environmental governance knowledge. Third, the significantly higher awareness among government officials, NGO representatives, forestry workers, and academics suggests that RMF knowledge remains concentrated within professional and institutional circles, with limited transfer to local communities. This institutional concentration of knowledge creates a gap between policy formulation and local-level implementation.

Additionally, the findings expose weaknesses in decentralised environmental communication and extension systems. Community stakeholders who are expected to support implementation and monitoring may lack the technical understanding necessary for effective participation. These gaps may reduce stakeholder accountability, weaken collaborative governance, and undermine the effectiveness of RMF implementation in promoting sustainable forest management outcomes in Ghana.

Table 4. Multiple Linear Regression Results on Factors Influencing RMF Knowledge. 

Variable	Coefficient (β)	Std. Error	t-value	p-value
Educational Level	0.042	0.015	2.80	0.006***
Knowledge Score	0.671	0.120	5.59	0.000***
Gender (Male = 1)	0.058	0.054	1.07	0.287
Occupation (Ref = Farmer)
District Assemblies	0.231	0.090	2.57	0.011***
NGO Representative	0.198	0.088	2.25	0.026**
Forestry Worker	0.284	0.092	3.09	0.002**
Researcher/Academic	0.352	0.101	3.48	0.001***
Community Leader	0.112	0.084	1.33	0.185
Constant	0.214	0.121	1.77	0.079*
	R² = 0.47		Adjusted R² = 0.44

Note:*** p < 0.01, ** p < 0.05, * p < 0.1. Source: Field Survey, 2025. 

Table 4. Multiple Linear Regression Results on Factors Influencing RMF Knowledge. 

Variable	Coefficient (β)	Std. Error	t-value	p-value
Educational Level	0.042	0.015	2.80	0.006***
Knowledge Score	0.671	0.120	5.59	0.000***
Gender (Male = 1)	0.058	0.054	1.07	0.287
Occupation (Ref = Farmer)
District Assemblies	0.231	0.090	2.57	0.011***
NGO Representative	0.198	0.088	2.25	0.026**
Forestry Worker	0.284	0.092	3.09	0.002**
Researcher/Academic	0.352	0.101	3.48	0.001***
Community Leader	0.112	0.084	1.33	0.185
Constant	0.214	0.121	1.77	0.079*
	R² = 0.47		Adjusted R² = 0.44

Note:*** p < 0.01, ** p < 0.05, * p < 0.1. Source: Field Survey, 2025. 

5. Discussion

This study examined the awareness, understanding, and applied knowledge of the Risk Management Framework (RMF) among forestry stakeholders in Northern Ghana, and the socio-demographic and institutional factors that shape engagement with risk-based environmental governance. Drawing on both quantitative survey data (n = 160) and qualitative insights from five Focus Group Discussions and seven Key Informant Interviews, the discussion below interprets the findings in light of the integrated risk governance framework outlined in Section 2.1, with explicit attention to their implications for forest sustainability, biodiversity conservation, and climate resilience in the Guinea Savannah ecosystem

5.1. Awareness of the RMF

5.1.1. Awareness Levels Among Stakeholders

The finding that 94% of stakeholders reported awareness of the RMF, with relatively even distribution across community forest management groups, government officials, farmers, researchers, forestry workers, local leaders, and NGOs, suggests that risk-based environmental governance concepts have diffused beyond technical institutions and into community-level forest actors. This even distribution indicates a growing recognition of risk-based approaches in environmental governance at both community and institutional levels and offers an encouraging foundation for participatory forest stewardship in Northern Ghana’s Guinea Savannah landscape.

This finding supports Jamil et al. (2024), who emphasise that stakeholder awareness is a critical foundation for resilient forest governance. However, the qualitative data complicate this optimistic reading. A Regional Planning Officer with the Forestry Commission captured the central tension precisely: "The challenge is not awareness, but operationalisation. Policies exist, but translation into field-level action is weak" (KII, Forestry Commission Officer 3). His district-level colleague described RMF in similar terms, noting that it is "embedded in practice but not formalised" (KII, Forestry Commission Officer 1). These observations align with Eriksson (2017), who cautions that awareness does not automatically translate into effective participation or practical implementation.

The implication for forest ecosystem outcomes is significant. In the Northern Ghana context, stakeholders may possess general familiarity with RMF principles, yet face capacity, institutional, and resource constraints that limit their ability to apply these frameworks to forest management decision-making. High awareness without operational depth risks producing what may be termed "symbolic risk governance", a state in which RMF terminology circulates without producing measurable improvements in forest cover, biodiversity protection, or climate buffering capacity. Consistent with Vulturius and Swartling (2015), strengthening long-term risk literacy through continuous training, institutional embedding, and contextual adaptation of RMF tools will be essential to ensure that awareness contributes meaningfully to sustainable forestry governance and ecological resilience in the Guinea Savannah.

5.1.2. Sources of RMF Information

The finding that local community leaders served as the dominant source of information across all channels, accounting for 37–41% of information access from government policies, NGOs, academic publications, training workshops, and media, reveals a heavily mediated information architecture in Northern Ghana’s forestry sector. Their strong presence across all pathways reflects the trust and authority traditionally vested in chieftaincy and opinion-leader structures, positioning them as essential intermediaries between formal governance institutions and grassroots forest actors.

However, this mediation comes at a cost. A Monitoring Officer with the Environmental Protection Agency articulated the concern with notable candour: "Community leaders play a big role in communication, but sometimes information gets simplified too much" (KII, EPA Officer 5). This observation directly addresses the question of whether community leaders function as effective conduits or as bottlenecks in environmental risk communication. The qualitative evidence suggests they function as both: indispensable for reach and legitimacy, yet vulnerable to message distortion through over-simplification, selective transmission, or alignment with local political and economic interests.

This bottleneck dynamic helps explain a paradox visible in the quantitative results. While community leaders dominate information flows, they did not demonstrate significantly higher RMF knowledge than farmers in the regression analysis (β = 0.112, p = 0.185). Acting as a transmission node does not necessarily entail acquiring the technical depth of the message being transmitted. Information that passes through such a node can therefore arrive at the grassroots in a simplified, partial, or contextually modified form.

Farmers also accessed RMF information substantially through government programmes (26%) and media (26%), indicating the importance of public extension services and communication platforms in reaching primary forest resource users. However, a MoFA Extension Officer pointed to a deeper cognitive constraint: "Farmers focus on immediate survival, not long-term risk frameworks" (KII, MoFA Officer 6). This observation is consistent with Li and Lyu (2021), who note that economic insecurity often forces short-term decision horizons that crowd out engagement with structured risk frameworks. The implication is that information availability alone is insufficient; communication strategies must be designed to bridge the gap between immediate livelihood concerns and longer-term forest sustainability outcomes.

These patterns align with Asogwa et al. (2023) and Iyere and Misopoulos (2022), who emphasise the effectiveness of intermediary actors and participatory channels in strengthening environmental governance knowledge systems. However, the dependence on intermediaries also raises a question about institutional reach. As one Forestry Commission Range Supervisor observed, "information flows mostly through supervisors and community engagement, not formal training" (KII, Forestry Commission Officer 2). The relative absence of formal training as a primary channel is a structural weakness with direct ecological consequences: without formal training, the technical content of RMF, particularly its monitoring, enforcement, and adaptive components, struggles to reach the actors whose decisions most directly shape forest cover, biodiversity, and carbon stocks.

Consistent with Poudyal et al. (2019), strengthening direct institutional communication, localised capacity-building programmes, and simplified knowledge translation tools could improve independent access to RMF information and support more informed and active stakeholder participation in sustainable forestry governance. The findings further suggest that digital tools, mobile-based extension platforms, community radio in local languages, and remote sensing-informed bulletins, offer promising channels for circumventing the simplification bottleneck while preserving the legitimating role of community leaders.

5.2. Understanding of RMF Principles

5.2.1. Level of Understanding of RMF

The clear variation in RMF understanding across stakeholder groups, with forestry workers demonstrating the highest comprehension followed by government officials and academia, while farmers and local community leaders recorded the lowest levels, reflects the influence of institutional exposure, education, and access to structured training in shaping engagement with risk governance tools. Consistent with Jamil et al. (2024) and Tumuhe and Kiguli (2019), actors operating within formal environmental institutions tend to develop stronger technical understanding, whereas community-level actors often receive limited or fragmented knowledge through extension systems.

The qualitative data adds important texture to this finding. The same Forestry Commission Range Supervisor cited above explained: "We do risk management, but I would not say we follow a formal framework. Most of it is based on experience" (KII, Forestry Commission Officer 2). This statement reveals that even within the implementing institution itself, technical understanding of RMF as a structured framework is uneven. If institutional actors themselves rely primarily on experiential rather than codified RMF knowledge, the prospect of cascading that knowledge to community-level actors through formal channels is inevitably constrained.

The low comprehension among farmers and traditional leaders suggests that awareness alone is insufficient without targeted capacity-building efforts. As emphasised by Vulturius and Swartling (2015), rural stakeholders facing immediate livelihood pressures may struggle to engage with long-term risk planning frameworks. This is particularly consequential in the Guinea Savannah context, where deforestation, biodiversity loss, and climate vulnerability demand precisely the kind of long-term, structured risk thinking that the framework is designed to enable. Strengthening localised training, simplifying RMF tools, and embedding learning within community governance structures are therefore essential for improving inclusive and effective RMF integration in forestry governance.

5.2.2. Interpretation of RMF Concepts by Respondents

The findings reveal notable differences in how stakeholders conceptualise the Risk Management Framework. Local community leaders dominated all interpretation categories, particularly viewing RMF as a financial risk management strategy and as a government policy for environmental conservation. Farmers similarly associated RMF with multiple dimensions, including environmental risk management, legal protection, and policy frameworks. This broad and overlapping interpretation suggests that RMF is understood in practical and policy-related terms rather than as a distinct technical framework, reflecting the blended nature of governance knowledge at the community level.

The qualitative data illuminate the source of this conceptual blending. Across all five FGD communities, when participants were asked whether they had heard of RMF, most answered affirmatively but then described indigenous and CREMA-based practices rather than the formal framework. A Jadema participant, for example, explained: "Yes, the community members are using indigenous knowledge like creating fire belt, planting economic trees and sensitization of community members to address land management in terms of farming to conserve the biodiversity" (FGD, Jadema Community), while a Yamah participant simply stated: "Yes, because every household takes it a duty to protect the environment for our own good" (FGD, Yamah Community). These responses demonstrate that "RMF" is being interpreted through the lens of existing indigenous and community-based risk practices rather than as a distinct technical and institutional construct.

Government officials tended to interpret RMF more narrowly as a legal and structured environmental risk management framework, while forestry workers demonstrated relatively balanced perspectives across categories. The smaller contributions from NGO and academic respondents may indicate more specialized or less simplified conceptualisations of RMF. An EPA Environmental Officer, by contrast, described RMF in clearly institutional terms: "Yes, RMF is embedded in environmental impact assessments. We see RMF more as a regulatory tool" (KII, EPA Officer 4). The contrast between this regulatory framing and the indigenous-practice framing prevalent at community level reveals a deep conceptual divide between institutional and grassroots understandings of the same framework.

These patterns support observations by Zong et al. (2024) and Eckert (2017) that community-based actors often merge formal policy concepts with everyday risk management experiences due to fragmented institutional communication and limited access to standardised training. The implication for forest governance is twofold. On the one hand, the merging of formal RMF terminology with indigenous practice represents a strong cultural foundation for risk-conscious forest stewardship: stakeholders are already operationalising the spirit of RMF through fire belts, reforestation, agroforestry, and CREMA-based by-law enforcement. On the other hand, without the formal RMF architecture of standardised assessment protocols, defined institutional roles, and structured monitoring, these community efforts cannot easily be aggregated, evaluated, or scaled to deliver measurable improvements in forest cover, biodiversity, and climate resilience at the landscape level.

As highlighted by Aven and Guikema (2015) and Li et al. (2022), effective risk governance requires shared understanding of frameworks and processes. Harmonised training and simplified, context-specific communication strategies are therefore essential to align stakeholder perceptions and support coherent integration of RMF into sustainable forestry governance in Northern Ghana.

5.2.3. Key Elements Identified as Essential in RMF

Local community leaders and farmers were the most prominent groups identifying the key elements of the RMF, consistently emphasising risk identification, assessment, mitigation, monitoring, stakeholder participation, and policy enforcement mechanisms. Their strong representation across all components highlights the central role community-level actors play in shaping practical risk governance priorities in Northern Ghana. This pattern suggests that RMF is largely understood through lived environmental experiences, where early risk detection, collective action, and enforcement are viewed as essential for effective forest management. The qualitative findings reinforce this: across all five communities, participants consistently identified illegal logging, charcoal burning, bushfires, herder–farmer conflicts, and galamsey as the dominant risks to forest resources, demonstrating strong experiential awareness of the threats that an effective RMF must address.

Government officials and forestry workers placed greater emphasis on technical processes such as mitigation, monitoring, and structured participation, reflecting their institutional responsibilities in implementing and supervising forestry policies. However, the District Forest Manager’s observation that "identification and mitigation are strong, monitoring is moderate, and enforcement is weak" (KII, Forestry Commission Officer 1) indicates that even institutional actors recognise the asymmetric maturity of RMF components in practice. The relatively balanced contributions from these groups indicate alignment with established RMF cycles that stress continuous risk assessment and adaptive management, consistent with global best practices in environmental risk governance (Usman et al., 2018; Gēbczyńska & Vladova, 2023).

Overall, the strong focus on participation and enforcement alongside technical risk processes underscores stakeholders’ recognition that RMF effectiveness depends not only on identifying risks but also on inclusive engagement and institutional accountability. The convergence of community-level emphasis on participation and enforcement with institutional acknowledgement of weak enforcement capacity reveals a shared diagnosis of the system’s central weakness: risks are visible, mitigation is attempted, but enforcement and monitoring infrastructure remains underdeveloped. This diagnosis is critical for guiding the design of future RMF interventions, which must prioritise enforcement and monitoring strengthening alongside the more readily implemented identification and mitigation components, particularly given the accelerating climate and biodiversity pressures on Northern Ghana’s forest landscape.

5.3. Knowledge of RMF

5.3.1. Knowledge Scoring Index on RMF

The Knowledge Scoring Index results revealed notable gaps in stakeholders’ understanding of the RMF, particularly regarding its institutional foundations. While respondents demonstrated relatively strong awareness of RMF’s benefits for proactive environmental decision-making (mean = 0.91), their limited ability to identify core RMF components (mean = 0.56) and, most strikingly, the institution responsible for RMF implementation in Ghana (mean = 0.32) reflects deeper structural weaknesses in technical literacy and institutional visibility within the forestry sector.

The qualitative data offer a clear explanation for this institutional visibility gap. A District Director with the Ministry of Food and Agriculture summarised the structural problem with notable directness: "There is no integrated RMF across institutions. Each agency works in silos" (KII, MoFA Officer 7). This observation is reinforced by a Forestry Commission District Forest Manager, who described the framework as "embedded in practice but not formalised" (KII, Forestry Commission Officer 1). When risk management responsibilities are fragmented across the Forestry Commission, the EPA, MoFA, and District Assemblies, with no single agency clearly identified as the lead implementer, it is unsurprising that only 32% of stakeholders correctly identified the responsible institution. The institutional visibility problem is not primarily a problem of stakeholder ignorance, but a reflection of genuine institutional fragmentation on the ground.

These findings align with earlier studies showing that low technical capacity and weak extension services undermine the adoption of sustainable forest governance tools in rural contexts (Adesoji et al., 2015). However, the present study extends this literature by demonstrating that the problem is not simply one of insufficient training reaching stakeholders, but of insufficient institutional coherence within the system being communicated. As one Forestry Commission Regional Planning Officer observed, "the challenge is not awareness, but operationalisation" (KII, Forestry Commission Officer 3). Even where stakeholders are aware that RMF exists, the absence of a clearly mandated, well-resourced lead institution makes practical engagement difficult.

The literature emphasises that effective RMF implementation requires more than baseline awareness; it depends on risk literacy, contextual understanding, and the ability to interpret complex governance mechanisms (Mahadewi et al., 2022; Vulturius & Swartling, 2015). The implications for forest ecosystem outcomes are direct. Without a clearly identified responsible institution, accountability for risk monitoring is diffuse, enforcement gaps persist, and the adaptive management cycle that RMF is designed to support cannot close. The result is a governance system in which risks are widely recognised but inconsistently addressed, leaving Northern Ghana’s Guinea Savannah forests vulnerable to compounding pressures from illegal logging, agricultural expansion, climate variability, and biodiversity loss. Strengthening institutional visibility, clarifying lead-agency responsibilities, and investing in cross-agency coordination through participatory learning, tailored communication, and targeted capacity-building are therefore essential to translate awareness into measurable improvements in forest sustainability.

5.3.2. Factors Influencing RMF Awareness (Regression Analysis)

The multiple linear regression results show that education and the composite knowledge score were strong predictors of RMF awareness, reinforcing the central role of formal learning and risk literacy in shaping environmental governance engagement. This association is consistent with Fuller and Quine (2015) and Saeidi et al. (2020), who note that education enhances adaptive capacity, strengthens compliance, and improves understanding of risk governance tools. Occupation also significantly influenced awareness, with government officials, NGO staff, forestry workers, and researchers displaying higher awareness than farmers. This pattern mirrors broader empirical findings that individuals embedded within institutional or professional environments have greater exposure to governance frameworks and technical information (Jamil et al., 2024; Paletto et al., 2019).

Two non-significant findings, however, are particularly analytically important and merit careful interpretation.

First, the absence of a significant gender effect (β = 0.058, p = 0.287) is a notable deviation from the dominant assumption in environmental governance literature that women in rural Northern Ghana face systematic disadvantages in accessing risk-related information. While gender disparities in land tenure, leadership representation, and formal sector employment are well documented in the region, the present finding suggests that with respect to RMF awareness specifically, the structural barriers operate similarly across gender lines. Several explanations are plausible. The dominance of community leaders as information conduits (37–41% across all channels) may produce a uniformly mediated, and uniformly thin, information environment that limits both men’s and women’s direct access to formal RMF content. Alternatively, women’s substantial engagement in shea, dawadawa, and non-timber forest product value chains may afford them comparable exposure to forest governance discourse despite their under-representation in formal leadership roles. Either way, this finding cautions against assuming that gender-mainstreaming alone will close RMF knowledge gaps; the structural barriers, weak institutional visibility, simplified communication, and inadequate extension services, affect men and women alike (Li & Lyu, 2021; Dryhurst et al., 2020).

Second, the non-significant difference between farmers and community leaders (β = 0.112, p = 0.185) presents a striking paradox. Community leaders dominate information dissemination across all channels (37–41%), yet they do not demonstrate significantly greater RMF knowledge than the farmers to whom they are presumed to transmit information. This paradox is illuminated directly by the qualitative data. An EPA Monitoring Officer’s observation that "community leaders play a big role in communication, but sometimes information gets simplified too much" (KII, EPA Officer 5) suggests that leaders function more as communication relays than as deeply informed governance actors. Their authority and trust make them indispensable conduits, but the act of relaying does not require, and may not generate, the technical depth of the message being relayed. The implication is that capacity-building efforts targeting community leaders specifically, including tailored RMF training, simplified toolkits, and continuing-engagement structures, could yield disproportionate improvements in grassroots risk literacy.

The moderately strong explanatory power of the model (R² = 0.47; Adjusted R² = 0.44) suggests that while education, occupation, and knowledge significantly shape RMF awareness, other unmeasured factors, such as trust in institutions, communication quality, and cultural perceptions, also influence engagement. As Terraneo et al. (2021) and Janning et al. (2021) argue, risk perception and governance participation are deeply embedded in sociocultural norms, economic realities, and communication networks, all of which merit further exploration. A MoFA Extension Officer’s observation that "farmers focus on immediate survival, not long-term risk frameworks" (KII, MoFA Officer 6) points to one such unmeasured factor: the time-horizon constraint imposed by economic precarity, which structurally limits engagement with frameworks oriented toward long-term ecological outcomes. Future research should explicitly model trust, time-horizon, and communication-quality variables to advance understanding of these mechanisms.

5.4. Environmental and Climate Resilience Implications

The findings of this study carry direct implications for forest sustainability, biodiversity conservation, and climate resilience in the Guinea Savannah ecosystem of Northern Ghana. While much of the existing literature on RMF treats it as a governance instrument in abstract terms, the evidence presented here demonstrates that the way stakeholders perceive, understand, and apply the framework shapes ecological outcomes in measurable ways.

First, the awareness–understanding–operationalisation gap identified in this study has direct consequences for forest cover and ecosystem services. Weak knowledge of RMF components and responsible institutions undermines the timely identification and response to threats such as illegal logging, charcoal production, bushfires, and agricultural encroachment, all of which were consistently identified by FGD participants as dominant risks. The combined effect is continued forest degradation, reduced carbon sequestration, and the erosion of the parkland mosaic of shea, dawadawa, neem, and baobab that defines the ecological character of Northern Ghana’s savannah landscape. Each of these tree species supports specific ecological functions, soil stabilisation, microclimate regulation, pollinator habitat, and the provision of non-timber forest products, and their decline is therefore not merely an aesthetic loss but a systemic weakening of regional biodiversity and ecosystem service delivery.

Second, the strong indigenous early warning systems documented in the FGDs, including community recognition of erratic rainfall, prolonged drought, premature drying of vegetation, and crop failure as ecological warning signs, represent a substantial but underutilised resource for climate-smart forest governance. Integrating these locally calibrated indicators with formal monitoring systems, including remote-sensing-based vegetation indices and climate forecasting tools, could create a hybrid early warning architecture that is both scientifically rigorous and culturally grounded. Such integration would directly strengthen climate resilience in a region where rising temperatures, declining rainfall reliability, and increasing fire frequency threaten both forest ecosystems and the agrarian livelihoods they support.

Third, the institutional visibility gap, evidenced by the 0.32 mean knowledge score for the responsible RMF institution and corroborated by KII observations of inter-agency silos, has direct biodiversity implications. Forest reserves, sacred groves, and shea parklands in Northern Ghana span jurisdictional boundaries between the Forestry Commission, the EPA, MoFA, the Lands Commission, and traditional authorities. Without a clearly mandated lead institution for RMF implementation, biodiversity hotspots fall through the cracks of overlapping mandates, and threats requiring coordinated response, such as transboundary wildfires, herder–farmer conflicts, and illegal mining, are addressed inconsistently. Strengthening institutional clarity is therefore not a bureaucratic concern but a biodiversity conservation priority.

Fourth, the finding that 78% of respondents reported owning forest land elevates the policy stakes of the knowledge gaps identified. The majority of the sample holds direct decision-making authority over forest resources, meaning that their RMF knowledge or its absence translates into immediate land-use decisions with cumulative landscape-level effects. Investment in landowner-targeted RMF training is therefore likely to yield disproportionately large ecological dividends in terms of forest cover retention, agroforestry uptake, and reduced bushfire incidence.

Collectively, these findings situate RMF awareness and knowledge as upstream determinants of forest ecosystem outcomes. They support a growing body of evidence that human knowledge systems are not peripheral to environmental governance but constitutive of it (Folke, 2016; Salomon et al., 2019), and they reinforce the case for treating risk literacy as a core component of the climate adaptation and biodiversity conservation strategy for Sub-Saharan Africa’s dryland forest landscapes.

5.5. Limitations of the Study

Several limitations of this study should be acknowledged. First, the cross-sectional design captures stakeholder awareness, understanding, and knowledge at a single point in time and cannot establish causal relationships between socio-demographic factors and RMF engagement. Longitudinal research would be needed to track how awareness evolves following capacity-building interventions and how changes in knowledge translate into measurable forest outcomes over time.

Second, the study relied on self-reported awareness and understanding, which may overstate familiarity with RMF, particularly in contexts where social desirability bias encourages affirmative responses. The qualitative finding that many respondents who reported "hearing of" RMF in fact described indigenous practices supports this interpretation and highlights the importance of triangulating self-reports with applied knowledge measures such as the Knowledge Scoring Index used here.

Third, while the sample size of 160 respondents satisfies Cochran’s formula requirements and the five FGDs and seven KIIs provide rich qualitative depth, the geographic focus on five districts within Northern Ghana limits the direct generalisability of findings to other forest landscapes. The Guinea Savannah ecosystem and its associated socio-cultural context shape both the risks identified and the governance arrangements observed; transferring conclusions to high-forest zones in southern Ghana or to other Sub-Saharan African forest contexts would require additional empirical validation.

Fourth, the regression model explained 47% of the variance in RMF knowledge, indicating that meaningful additional variation is shaped by factors not measured in this study, including institutional trust, communication quality, time-horizon constraints, and access to digital information channels. Future research incorporating these dimensions would strengthen explanatory power and inform more precisely targeted interventions.

Finally, the Knowledge Scoring Index, while validated through expert review, pilot testing, and Cronbach’s alpha analysis (α = 0.78), comprises three items and therefore represents a focused rather than comprehensive measure of RMF knowledge. Expanded indices covering operational, monitoring, and enforcement dimensions of RMF would offer a richer assessment in future studies.

Despite these limitations, the convergence between the quantitative results, the qualitative findings, and the institutional perspectives provided by KIIs strengthens confidence in the central conclusions of the study and supports the policy implications discussed in the following section.

6. Conclusion

This study examined the awareness, understanding, and applied knowledge of the Risk Management Framework (RMF) among forestry stakeholders in Northern Ghana, and analysed how socio-demographic, institutional, and sociocultural factors shape engagement with risk-based environmental governance. By integrating quantitative survey data from 160 respondents with qualitative insights from five Focus Group Discussions and seven Key Informant Interviews across the Guinea Savannah landscape, the study provides one of the first systematic, mixed-methods assessments of RMF engagement in a dryland forest ecosystem in Sub-Saharan Africa.

The findings revealed that while overall awareness of RMF was high (94%), substantial disparities exist in the depth of stakeholder understanding and applied knowledge. Forestry workers, government officials, NGOs, and researchers demonstrated relatively stronger comprehension of RMF principles, while farmers and community leaders, despite their central role in day-to-day forest decision-making, exhibited notably lower levels of technical understanding. Knowledge of core RMF components and the institution responsible for its implementation in Ghana was particularly limited (mean = 0.32), reflecting deep gaps in institutional visibility, technical capacity, communication architecture, and access to formal training. Education, occupation, and composite knowledge score emerged as significant predictors of RMF knowledge, while gender and community-leader status did not, pointing to structural rather than identity-based barriers to risk literacy.

Three analytical contributions emerge from these findings. First, the study demonstrates that high awareness of risk governance frameworks can coexist with weak operationalisation, what may be termed "symbolic risk governance", in which the language of RMF circulates without translating into measurable improvements in forest management. Second, the study identifies a "community-leader bottleneck" effect: while leaders dominate information flows, they do not exhibit significantly greater RMF knowledge than the farmers to whom they transmit information, indicating that information mediation does not automatically generate technical depth. Third, the study reveals an awareness–understanding divergence in which stakeholders interpret formal RMF terminology through the lens of indigenous and CREMA-based practices, a finding that signals both a strong cultural foundation for risk-conscious forest stewardship and a meaningful conceptual gap that constrains formal RMF integration.

These findings carry direct implications for forest sustainability, biodiversity conservation, and climate resilience in Northern Ghana’s Guinea Savannah ecosystem. Weak institutional visibility and uneven risk literacy compromise the timely identification and response to threats such as illegal logging, charcoal production, bushfires, herder–farmer conflicts, and small-scale illegal mining, all of which were consistently identified by stakeholders as pressing risks. The cumulative effect is continued degradation of the parkland mosaic of shea, dawadawa, neem, and baobab that defines the region’s ecological character, with measurable consequences for carbon sequestration, biodiversity, microclimate regulation, and the non-timber forest product economies that sustain rural livelihoods. Conversely, the strong indigenous early warning systems documented in the study, including community recognition of erratic rainfall, prolonged drought, and premature vegetation drying, represent an underutilised resource that, if integrated with formal monitoring and remote sensing tools, could substantially strengthen climate-smart forest governance in dryland Sub-Saharan Africa.

Theoretically, the study advances biosphere-level understanding of how human knowledge systems mediate ecological outcomes by demonstrating that the integration of governance, institutional, systems, and adaptive management perspectives offers a productive analytical lens for examining risk literacy in socio-ecological systems. Empirically, it provides context-specific evidence on RMF engagement in a region whose ecological and governance dynamics have been under-represented in the global forest risk management literature.

The study also highlights several priorities for future research. Longitudinal designs are needed to track how RMF awareness translates into measurable forest outcomes over time, particularly following capacity-building interventions. Comparative studies across Sub-Saharan African dryland ecosystems would strengthen generalisability and reveal context-dependent patterns of risk governance. Further research should also examine the role of trust in institutions, communication quality, time-horizon constraints, and digital communication channels in shaping risk literacy, dimensions only partially captured in the present analysis. Finally, the integration of indigenous early warning systems with remote sensing and digital monitoring tools warrants dedicated empirical investigation as a pathway for climate-smart forest governance in resource-constrained settings.

Translating awareness into action will require coordinated investment in institutional clarity, targeted capacity-building, simplified knowledge-translation tools, and digitally enabled communication channels, an agenda elaborated in the Recommendations that follow.

7. Recommendations

• The Forestry Commission, in collaboration with NGOs such as Tropenbos Ghana and A Rocha Ghana, should implement continuous and tiered training programmes on risk management for district forest officers, community forest managers, traditional authorities, CREMA executives, and local governance bodies. Simplified, illustrated RMF toolkits, translated into Dagbani, Mampruli, Gonja, and other major local languages, should be developed for community-based organisations, women’s groups, and farmer associations to bridge indigenous practices, such as fire belts, agroforestry, and reforestation, with formal RMF terminology, addressing the awareness–understanding divergence identified in this study.
• The Ministry of Lands and Natural Resources (MLNR) and the Forestry Commission should formally adopt and mainstream the RMF into national forest governance policies and operational manuals. Establishing a dedicated RMF Coordination Unit at national and regional levels, with clearly designated focal persons across the Forestry Commission, EPA, MoFA, and District Assemblies, will close the institutional visibility gap reflected in the low awareness of the responsible RMF institution (mean = 0.32) and the inter-agency silos identified in the qualitative findings.
• District Assemblies and Regional Coordinating Councils (RCCs) should establish multi-stakeholder forest governance platforms that include traditional leaders, youth groups, women’s groups, NGOs, CREMA executives, and private sector actors. This approach promotes inclusive decision-making and supports the practical integration of RMF principles at the community level.
• To strengthen monitoring and bridge the technological gap, the Forestry Commission, in partnership with FORIG, CSIR, and the University for Development Studies, should deploy a phased digital tools roadmap tailored to Northern Ghana. This should include (i) a mobile-based reporting and extension platform accessible via both smartphone applications and USSD short codes to ensure inclusivity across socio-economic groups; (ii) a Forest Monitoring Dashboard built on freely available satellite data (Sentinel-2, Landsat-9, Global Forest Watch) to track forest cover change, fire incidence, and vegetation health; and (iii) the integration of indigenous early warning indicators, such as rainfall patterns and premature drying of vegetation, into the dashboard to create a hybrid early warning system that is both scientifically rigorous and culturally grounded.
• Finally, the Forestry Research Institute of Ghana (FORIG), in partnership with relevant agencies, should develop RMF-based monitoring and evaluation frameworks to track forest governance performance and environmental risks. The M&E framework should include both quantitative indicators (forest cover, biodiversity, fire incidence, RMF knowledge scores) and qualitative measures (community satisfaction and integration of indigenous knowledge), with findings reported annually to inform Ghana’s Forest and Wildlife Policy revision cycle and ensure that RMF integration produces measurable improvements in forest sustainability, biodiversity conservation, and climate resilience.