Household livelihoods and the uptake of improved forest management practices: a case study in Guinea.
The importance of forests for people's livelihood in developing countries is unquestionable. The Food and Agriculture Organization of the United Nations (FAO) estimates that over 350 million people living within or near forests rely on them for subsistence and income (FAO 2016). According to the World Bank, forests directly contribute to the survival of about 90 percent of the 1.2 billion people living in extreme poverty (World Bank 2004). Poor rural communities are greatly dependent on forest resources (Sunderlin et al. 2005, Appiah et al. 2009), as they provide communities with assets to fill seasonal gaps in the agricultural calendar as well as natural insurance against shocks that may affect people's livelihoods (Wunder et al. 2014, Angelsen et al. 2014), thus granting poor households a chance to overcome economic difficulties (Angelsen et al. 2014). This implies that deforestation and forest degradation primarily affect the poorest households and impact on the communities as a whole. Among the main consequences of deforestation and forest degradation, biodiversity loss, lower availability of forest products for communities, increased frequency of fires and lowered productivity (Foley et al. 2007) should be mentioned. The loss of healthy forests can also disrupt key ecosystem services such as hydrological regulation and carbon storage in biomass and soils, causing an increase in carbon emissions (Springate-Baginski and Wollenberg 2010).
Agricultural expansion has been identified as a key driver of deforestation in the tropics (Barbier & Burgess 2001, Gibbs et al. 2010), although with geographical differences (Rudel et al. 2009, Boucher et al. 2011). In large parts of Africa, fuel wood collection, charcoal production and livestock grazing in forests are important causes of forest degradation.
In this context, actions to support the conservation and enhancement of forest resources are promoted. Growing attention is being dedicated to targeting forest conservation and fighting deforestation, which also play a crucial role in reducing global carbon emissions (Nabuurs et al. 2007). Public support to initiatives aimed at reducing emissions from deforestation and forest degradation in developing countries remains a high priority in the development agenda (Miles and Kapos 2008, Corbera et al. 2010, Bernoux et al. 2010). Sustainable forest management is one option. It ranges from protecting biodiversity and forest ecosystems to safeguarding local livelihoods. It includes forest conservation and restoration, forestry and agroforestry practices (Eriksson et al. 2018) as well as improved forest management practices such as better harvesting and silviculture practices (pruning, liberating thinning, selective weeding, enrichment planting, controlled burning), fire control techniques, measures to diminish pressure on forest resources (e.g. through the adoption of fuel-wood saving stoves), and promotion of non-timber forest product businesses.
Improved forest management practices are extremely relevant to developing countries such as Guinea, where forests are severely fragmented and the natural resource base is undermined (Eben 2003). Consistently with this awareness, many forestry development projects in the last decades have promoted the adoption of improved forest management practices, both on- and off-farm, and have targeted local communities and smallholders.
A key issue regarding these projects is the extent to which they are able to deliver positive and lasting outcomes (1), i.e. how effective and durable they are in addressing households' uptake of improved forest management practices. Literature has studied the main reasons affecting the decision to adopt such practices, among which: timber productivity and cost considerations; markets for wood products and economic incentives; rights, laws and regulations; availability of capital and technical assistance; resistance to change (Boscolo et al. 2009, Blate et al. 2002, Putz et al. 2000, Karsenty 2000). Instead, little information exists on the enabling factors that are likely to influence and underpin the uptake of improved forest management practices by households (Le et al. 2012, 2014). A better understanding of these factors could therefore support the study of the dynamics leading to successful outcomes of forestry interventions, and the development of environmentally, socially and economically sustainable land use systems.
Among these factors, the socio-economic characteristics of the households involved in projects may play a considerable role (Fakoya et al. 2007, Jansen et al. 2006). This article investigates the role of livelihood assets in the household's uptake of improved practices in the context of projects dealing with forest conservation, reforestation and sustainable use of forest resources. Primary data used for the study were collected between May and June 2012 in the Fouta Djallon Highlands (FDH) in Central Guinea, West Africa.
The purpose of the article is to discuss the following hypotheses: (i) livelihood assets of households play a role in the uptake of improved forest management practices promoted by forestry projects; (ii) certain aspects of the livelihood assets, including the gender dimension, are particularly correlated with the long-term outcomes of forestry projects; (iii) the identification of such aspects may provide projects with useful information to target rural households with adequate livelihood assets in order to achieve positive longterm outcomes; and (iv) the degree of local stakeholders' participation in project activities is an enabling condition for long-term outcomes.
The results of the study are meant to contribute to the literature on the uptake of improved forest management practices. They will indicate how people's livelihoods contribute to/affect the achievement of forestry project outcomes. This may support the design of more effective targeting strategies, with the aim of increasing the long-term sustainability of forestry projects.
The next section provides a conceptual framework to discuss the link between improved forest management practices and households' livelihoods. Section 3 describes materials and methods used in the empirical analysis. The results are discussed in Section 4. The conclusions are presented in Section 5.
IMPROVED FOREST MANAGEMENT PRACTICES AND LIVELIHOODS
The literature on the adoption of sustainable land management practices clearly indicates that education increases awareness of the benefits of such practices (Jansen et al. 2006). Women are keener than men on learning and using better practices, and this is especially true for young, educated women (Fakoya et al. 2007). Education also increases the opportunity cost of labour, thus reducing the adoption of labour-intensive conservation practices. Land ownership also drives the successful uptake of sustainable land management practices (Jansen et al. 2003, Fakoya, et al. 2007), along with the presence of community-based organisations, which play a crucial role in disseminating such practices (Jansen et al. 2006).
In the field of forest management, studies conducted in developing countries on REDD (2) interventions suggest that projects are more likely to be successful if they support, rather than conflict with, the interests of people living within and around forests (Springate-Baginski and Wollenberg 2010). Consequently, any actions aimed at improving forest management in developing countries should also contribute to addressing the global challenges of poverty eradication and economic and social development (UNFCC 2008). Chronic rural poverty is typically located close to natural forests and the use of forest resources may prevent rural people from falling into deeper poverty or help them escaping it.
The interactions of forestry projects with the livelihoods of forest-dependent communities can be conveniently analysed through the Sustainable Livelihoods Framework - SLF (DFID 2001).
According to this framework, people's livelihoods are affected by a web of inter-related influences determined by the vulnerability of the context they live in, the assets they own and the transforming structures and processes that shape livelihood strategies and outcomes. Therefore, the SLF can help understand and analyse the main factors affecting the livelihoods of poor people and their interconnections.
Livelihood assets (Figure 1) are the core of the SLF. They include a set of capitals, as defined by FAO (2003):
1. Human capital, i.e. health, nutrition, education, personal knowledge and skills. It represents the capacity of an individual to work and to pursue adaptive strategies.
2. Social capital, comprising individuals' networks and connections such as neighbourhoods, relations of trust and mutual support, participation to formal and informal groups, collective representation and decision-making power.
3. Natural capital, including land and soil quality, availability of water and aquatic resources, trees and forest products and biodiversity. This capital represents an individual's set of available environmental resources and services.
4. Physical capital, i.e. the infrastructure and technology available to the individual. These include transport, roads, vehicles, building quality and safety, water supply infrastructure, sanitation, energy, communications, tools and the equipment for production, agricultural inputs and implements, etc.
5. Financial capital, i.e. access to funds, either as cash and savings or as loans and external funding. This capital includes formal and informal channels for obtaining credit, as well as remittances and funding from non-governmental organisations (NGOs).
Access to these assets varies as a consequence of the natural and social environment in which people live. People use these assets simultaneously in order to create livelihood strategies aimed at achieving their individual goals. The capacity of local communities and households to develop suitable livelihood strategies drawing on these assets depends on the quantity and balance of assets available (DFID 2001).
The SLF is adopted here in order to assess the extent to which local livelihoods interact with externally-funded forestry interventions and the role they play in shaping the long-term outcomes (Bond and Mukherjee 2002) of forestry projects in developing countries.
MATERIALS AND METHODS
This article is based on primary data collected as part of a larger survey in the FDH, Central Guinea, between May and June 2012, at the onset of the rainy season.
More specifically, data were collected in the Prefecture of Mamou, Sub-prefecture of Tolo (Figure 2); the area is located in the watershed of the Senegal river--one of the major regional rivers - and hosts its spring. The area of the Subprefecture of Tolo is 150 [km.sup.2] and the population density is 50 to [km.sup.2], with a total population of 7,533 people distributed among 748 households (Direction Prefectorale de la Planification et du Developpement de Mamou 2011, Service Prefectoral du Plan et de la Statistique 2010).
The FDH are characterised by a series of high plateaus ranging from 900 to 1,500 metres above sea level and, together with the surrounding foothills, arbour a rich mosaic of savannah and sub-tropical humid forest ecosystems (Ceci et al. 2014). They are considered as the "water tower" of West Africa, as important regional rivers originate from there. The average annual rainfall is between 1,500 and 2,000 mm (ILCA et al. 1980). The FDH are predominantly inhabited by the Fula ethnic group and extensive subsistence agriculture is still the principal source of livelihood for most households. Farming is often complemented by small-scale livestock rearing (cows, goats, sheep and chicken). Due to the mountainous topography of the area, land is exploited for agricultural production via fenced kitchen gardens surrounding the houses and cultivated exclusively by women as well as the fields in valleys, plains and slopes (Ceci et al. 2013, 2014). People in the FDH greatly rely on ecosystem services and goods provided by forests, including hydrological and microclimate regulation, biodiversity, soil fertilisation, water erosion control, fuelwood and food. According to the Government of Guinea, the national forest cover is 6,364,000 ha, with a constant loss since 1990, but with a relative increase in planted forests and exotic species (FAO 2014).
The Sub-prefecture of Tolo has been the focus area of two subsequent projects funded by the French Fonds d'Aide et de Cooperation (26.6 million French Francs) between 1988 and 1996 (3), with co-financing from the Government of Guinea. The projects were implemented within the context of the African Union's Regional Programme for the Integrated Development of the FDH and, because of their continuity, are treated as a single project in this study. Their objectives were the conservation and sustainable use of the natural resources affecting the regional hydrology, with an emphasis on institutional support for the conservation of classified forests (forets classees).
The projects aimed to enhance forest cover and support reforestation mainly with exotic forest species (4) to provide fuelwood and construction material. Project activities had a strong training component and ranged from forest protection to agro-sylvo-pastoral development and the establishment of socio-economic infrastructure to back up conservation efforts with opportunities to support livelihood and income sources. Specific activities included:
* Sensitisation and training: education in environmental protection, training in forest fire control (early fires, fire breaks), in silviculture (forest thinning, tree pruning), in livestock and agricultural practices (vaccinations, cotton seed feeding, lick stones, composting, grafting, cutting) and in sustainable income-generating activities.
* Reforestation and forest cover enhancement: provision of forest tree seedlings, creating community forest nurseries with dedicated nursery practitioners and tree planters, arboretum establishment, reforestation of forets classees, reforestation of community forests, reforestation of quarries, restrictions on tree cutting and enhancing kitchen gardens with forest and fruit trees.
* Soil and water management and conservation: reforesting water sources, managing water sources, construction of improved wells, managing valleys, promoting anti-erosive biological measures and antierosive retaining walls.
* Measures to diminish pressure on natural resources: promoting use of improved cooking stoves, pressed bricks and cattle corridors.
* Committees and socio-economic interest groups: creating village forest patrol and forest fire prevention committees, valley horticultural and livestock rearing groups.
* Socio-economic infrastructures: levelling and maintaining forest roads and refurbishment of the subprefectural forest office.
Both projects were fully concluded when the survey was performed. The area, a case in which improved forest management practices were promoted in the past by international initiatives, offered the opportunity to investigate the drivers underpinning the uptake of better practices by local stakeholders and to assess the role of livelihood assets in this process.
Data collection was conducted in four villages located in the Sub-prefecture of Tolo (5). It should be noted that following the military coup d'etat in 2008, Guinea faced years of political tension, instability, civil unrest and violence, and that from 2013 to 2016 it was severely stricken by the Ebola virus outbreak; the field data collected are therefore particularly valuable.
The survey was carried out on a sample of 86 households: 21 questionnaires were administered in the village of Guelin, 17 in Gadha Kendouma, 18 in Bafing and 30 in Sala Mayo. The exact number and list of families living in the selected villages were not available at local administrations and traditional chiefs, so it was not possible to design a probabilistic sampling. Furthermore, households and hamlets were spread over large and impervious areas. To overcome this shortcoming, all the accessible and available households willing to be interviewed were surveyed in each village. It was estimated that 50 families at most lived in one village. The questionnaires were administered to household heads--chefs de menage--men or women, or to one of the wives of male household heads in case they were absent for work. Out of the 86 completed questionnaires, 76 were administered to men and 10 to women, two of which were wives of household heads. The age declared by the respondents ranged from 26 to 94 years, with an average of 57.
The questionnaire consisted of 362 closed-ended questions, conceptually structured on the basis of the SLF. It was shaped upon tools used worldwide, in particular: the World Bank's Living Standards Measurement Study (LSMS) (Grosh and Glewwe 2000) and the LSMS-Integrated Surveys on Agriculture (Bandyopadhyay et al. 2011, McCarthy 2011); the Household Food Insecurity Assessment Scale developed by the USAID-funded Food And Nutrition Technical Assistance (Coates et al. 2006, Ballard et al. 2011). It also used as reference the African Union's Monitoring and Management Indicators for the Fouta Djallon Highlands Natural Resources and Environment (ICO-AU 2011).
The questionnaire was divided into nine sections: (i) location, household composition and belongings; (ii) education; (iii) health; (iv) sources of income and production systems; (v) food security and nutrition; (vi) environmental issues and use of natural resources; (vii) overcoming isolation; (viii) participation in socio-economic interest groups; (ix) participation in past project implementation and activities. The first eight sections aimed to gather information on the livelihood assets of the households, whilst the last one focused on project participants' involvement in specific project activities and the continuation of these activities. Sixteen out of the 86 surveyed households had been involved in the French-funded initiatives.
Methodology used in data analysis
To study the role of livelihood assets in the uptake of improved forest management practices, we first selected from the database all the variables describing the status of households' livelihood assets. They were grouped into five categories--one for each asset--according to the SLF. Table 1 summarises the number and type of variables in the questionnaire sections (S1-S9) considered to describe each livelihood asset.
Then, for each set of variables, a Principal Component Analysis (PCA) was implemented to identify the main components expressing the status of the livelihood assets of the sample households. PCA was aimed at catching the factors underpinning the variables selected, thus allowing to express the livelihood assets with few components. For each asset three to five components were selected, according to the variance explained and the eigenvalues of the components. They were thus interpreted on the basis of the matrices of coordinates of the variables and consequently named. Through this process, the status of the livelihood assets of the sample households was assessed.
In order to investigate the extent to which households actually adopted and implemented the improved forest management practices promoted by the projects in the study area, two other sets of variables were considered. The first set (57 variables, referred to in the first row of Table 2) is related to respondents' participation to project activities, such as training, forest cover enhancement, building and improvement of infrastructure. The second set (62 variables, second row in Table 2) describes project long-term outcomes in the target communities--including the continuation of project activities by the households directly involved in the interventions --regarding water management, agricultural production, livestock, upkeep and management of forest resources, livelihood diversification, construction and maintenance of infrastructure, participation in socio-economic interest groups and the deployment of strategies to cope with shocks and climate change impacts. Following the same approach used for the livelihood assets, these two additional sets of variables were treated with the PCA.
The link between the status of livelihood assets and the uptake of improved practices was studied through a regression analysis, where the PCA factors were used as input variables. By using regression analysis, we aimed to address the first and the second research hypotheses, i.e. to study the role of livelihood assets in shaping the project outcomes as well as how they are able to influence the achievement of different types of outcomes.
In doing so, the long-term acceptance and implementation of the approaches, practices and techniques promoted by the projects were studied at the household level in terms of both primary and secondary outcomes. The former refer to changes within the pool of direct project participants, the latter concern spill-over effects affecting the entire community. The components resulting from the PCA performed on project outcome variables were used as dependent synthetic variables to run multiple linear regression models, one for each component. Components related to households' livelihood assets and participation in project activities were used as explanatory variables, with the aim to study their influence on long-term project outcomes at the household level, the significance of such influences as well as the positive and negative relationships.
The diagram in Figure 3 shows the methodological steps and the input data used in the statistical analysis. The results of the quantitative analysis (encompassing the PCAs and the multiple linear regression models) were interpreted also thanks to the qualitative information collected in the field through adapted Participatory Rural Appraisal techniques (PRA) (6).
Results of the Principal Component Analysis
For each set of variables analysed, the most significant principal components were selected. Table 3 shows the number of components selected for each domain.
The components were examined against the matrix of coordinates of the variables, in order to understand the contribution of the original variables to the components themselves, and consequently named and depicted. Table 4 shows an example of this method applied to the social capital domain. Table 5 displays names and descriptions of the components emerging from the analysis.
The interpretation of the components concerning project outcomes was particularly important for the purpose of this study. The component PO1 expressed the highest level of outcome, both primary and secondary, with direct participants in project activities going on implementing sound forest management practices after the end of the project, and other members of the reference community adopting and using such practices. Instead, the component PO2 was related to a low outcome, both for the individuals involved in and trained by the projects and for the community as a whole. The component PO3 described a good secondary outcome in terms of awareness acquired by the community of the importance of forests and of their conservation backed by the implementation of concrete practices, while the outcome concerning project participants was limited. On the contrary, the component PO4 conveyed a sound primary outcome, with only the individuals involved in project activities fostering sound forest management practices.
PO1, PO2, PO3 and PO4 were used as dependent variables in the multiple linear regression models, whereas the 19 components concerning livelihood assets and the component describing participation in project activities were inputted as independent variables.
Results of the regression models
The results of the four regression models are summarised in Table 6. The regression analysis performed on PO1 (good, widespread primary outcome, fairly good secondary outcome) shows a very high [R.sup.2] value (0.911). This indicates that the model closely fits the observation data and that the potential drivers selected explain very well the variance of the dependent variable. The overall significance of the model (Pr < 0.0001) also points out that its predictive capacity is very good. Therefore, it is highly reasonable to expect similar results under similar conditions. Significant drivers belong to the human, social and financial capital domains, as well as to the household participation in project activities. Namely, HC3, SC1 and PA1 positively influence PO1, thus they are able to determine and increase a widespread primary outcome together with a fairly good secondary outcome. Instead, FC3 negatively affects these outcomes.
The results of the regression analysis performed on PO2 (low primary outcome, no secondary outcome) are quite different. The [R.sup.2] value (0.306) is not as high as in the previous case and the model does not show a significant predictive capacity (Pr = 0.139). Therefore, although a certain correlation between the potential drivers and the dependent variable PO2 emerges, the former cannot sufficiently predict the value of the latter. Nonetheless, some factors are significantly correlated with PO2; in particular, HC2, NC1, NC4 and PC3 are the components that have the greatest influence in generating the type of outcome described by PO2. However, due to the low [R.sup.2] value and the insufficient predictive capacity of the model, these factors should not be considered as drivers generally capable of enhancing project outcomes in similar contexts.
Regarding the regression analysis performed on PO3 (no primary outcome, fairly good secondary outcome), the model fits the data quite well ([R.sup.2] = 0.470) and reveals a good predictive capacity (Pr = 0.001). The main drivers able to influence the type of outcome described by PO3 belong to the social, natural and financial capital domains. SC1, NC2 and FC4 have a significant and positive effect on PO3. This reveals the factors capable of fostering positive outcomes in the community: a high level of associativism for economic purposes and in activities that benefit the community, the good condition of natural resources and the extent of diversification in household economic activities.
Finally, the parameters of the regression analysis on PO4 (fairly good primary outcome, no secondary outcome) do not produce additional indications. The low [R.sup.2] value (0.215) indicates that the model is not able to effectively fit the observation data or to explain the variance of PO4. Moreover, the predictive capacity of the model is very low (Pr = 0.601), therefore no useful information can be obtained from these results to anticipate what may occur in other contexts. The model does not identify any drivers correlated to the type of outcome described by PO4.
The first aim of the analysis was to understand if households' livelihood assets play a role in the uptake of improved forest management practices promoted by forestry projects. Household surveys can successfully capture livelihood assets and the PCA allows summarising their complex dimensions. Results confirm that livelihood assets have an influence in the uptake of improved forest management practices. The regression analysis shows that the richer the social capital, the better people respond to project contributions. Average human and financial capital exert a positive influence, especially on secondary outcomes, but a lack of capital produces a negative effect able to hinder the overall goal of projects.
A wealth of social capital is found in families who engage in socio-economic interest groups to increase their economic opportunities (formalised horticultural groups in particular) and participate in decision-making processes as well as in other activities affecting the entire community (Woolcock and Narayan 2000). Indeed, families with this status are interested in being primary actors of their own empowerment and development. They are receptive to innovations brought about by projects, particularly to those with a potential for income generation, and they can facilitate the diffusion of practices among the members of the community (see the regression coefficients of the variable SC1 for PO1 and PO3 in Table 6).
As far as human capital is concerned, the analysis suggests that most disadvantaged households lack the necessary means and resources to foster innovation and trigger development dynamics (see the regression coefficient of the variable HC2 for the project outcome PO2 in Table 6). However, households with a significant level of resources are also more likely to engage in deforestation activities for agricultural purposes (Babigumira et al. 2014), highlighting the complex role of targeting in the diffusion of forest conservation practices. The analysis reveals a gender dimension. Households led by unschooled, young women who gained technical skills and an innovative attitude exert a positive influence on secondary outcomes (see the coefficient of the variable HC3 for the outcome PO1 in Table 6). This is consistent with Fakoya et al. (2007) and suggests that these women have learnt to actively cope with constraints because of family responsibilities and possess a strong motivation and interest in building a future for their children, including the natural environment where they will live.
Looking at financial capital, households with mixed livelihood strategies (e.g. trade, craftsmanship, small forest-based businesses) are more prone to adopt innovations than those relying solely on cropping and livestock keeping (see coefficients of variables FC4 for PO3 and FC3 for PO1 in Table 6). This suggests that it is crucial to support economic activities that can lead to the emergence of new forms of sustainable employment, e.g. non-wood forest product enterprises and associations between small producers and traders. Forest conservation and reforestation projects may provide households with the necessary financial instruments to support the development of innovative forest-based economic activities (Scheffran et al. 2012).
Reliable natural resources in good condition such as safe access to land, water and forests provide working assets and conditions enabling the uptake of project-promoted practices beyond the duration and scope of the project itself. A community with a rich natural capital is keen to learn best practices to protect and sustainably exploit their vital resources (see coefficient of variable NC2 for outcome PO3 in Table 6). When the state of natural resources is degraded, especially if water availability is affected, the benefits deriving from the natural capital may decline substantially and, in turn, the motivation to work on its management and rehabilitation. The limited capacity of a project to anticipate the case-specific vulnerability of natural resources and to mitigate resulting shocks can lead to practically null outcomes, as the regression analysis of the outcome PO2 shows for the variables NC1 and NC4 (Table 6).
The analysis also highlights that average physical capital with a fairly good level of access to infrastructure can improve project outcomes (see variable PC3 for outcome PO2 in Table 6). The presence of sufficient water supply infrastructure plays a key role in this sense. As reliable water resources are historically an issue in this area, a lack of access to safe drinking-water and a failure to take advantage of off-season agriculture would discourage any other possible interests and would undermine more long-term aims, including forest conservation and restoration. Improving water supply infrastructure is a prerequisite for starting reforestation activities.
To summarise, the analysis is able to address the second hypothesis of the study, i.e. specific aspects of the livelihood assets are more correlated to the long-term outcomes of initiatives promoting the uptake of innovative practices at the household level.
As far as the third hypothesis is concerned, i.e. how the information on household's livelihood assets can inform the targeting strategy of forestry projects, the analysis highlights the importance of choosing well-defined participants and clarifies the social, human, financial, natural and physical capital characteristics they should possess in order to help achieving positive long-term outcomes, including spill-over effects.
Concerning the fourth hypothesis, among the main factors that should be considered as enabling conditions for project success, the direct participation of local stakeholders in project activities was found to be crucial to maximise positive results. In this regard, only 19% of surveyed households (16 over 86) in the study area were found to have participated in past projects. In order to achieve better primary outcomes, the number of direct beneficiaries should be higher, as it is demonstrated by the strong significance of the synthetic variable PA1 - conveying project activities with highest rate of participation from households - and its highly positive coefficient in the regression analysis of PO1. These results suggest that the active involvement of the local population would foster the uptake and replication of project approaches and reduce the risk of breakdown into isolated, narrowlyfocused activities disjointed from the overall development rationale. External assistance can effectively support people to make their management practices more sustainable (Jansen et al. 2006), but the risks of abandonment of project-promoted practises must be limited. This can be achieved by encouraging stakeholders to contribute with some of their own resources to the implementation of project activities, e.g. through their own land in case of reforestation actions (conveyed by PA1, see Table 5 and Table 6). This cost-sharing approach can be a means to achieve a sense of ownership and ensure continued interest in perpetuating the project activities, as it has already been demonstrated for the adoption of sustainable land management practices in general (Jansen et al. 2003). At the same time, land tenure and agreed use rights must be guaranteed and monitored over time.
This multi-disciplinary study examines the uptake of improved forest management practices at the household level as a result of the implementation of forest conservation and reforestation initiatives. It uses the SLF approach to study the role that the target population's social and economic characteristics play in determining the adoption of improved forest management practices and in attaining the long-term outcomes of forestry projects. It relies on data from a survey conducted on 86 households in Guinea. It shows that livelihood assets, particularly human, social and financial capitals, are key driving factors in the uptake of sustainable forestry practices. Low human capital negatively shapes the response of individual households to project activities limiting the extent of the primary outcome. Medium human capital level displays adaptive capacity and openness to innovation, especially in female-led households, and helps achieving a positive secondary outcome. Social capital characterised by participation in interest groups positively impacts both the primary and secondary outcomes. This is consistent with existing literature that recognises the role of community-based organisations in spreading sustainable land management practices (Jansen et al. 2006).
Overall, the main outcome of the study is the recommendation that every project should consider in the design phase the status of the livelihood assets in the target area, as they are shown to be crucial for projects' success. Proper data collection and analysis should be foreseen. In this respect, the framework adopted in this study could be successfully used for targeting responsive project stakeholders and designing robust monitoring systems for forestry development initiatives. Our findings provide specific targeting indications for project designers. Targeting disadvantaged households through project activities aimed at environmental protection and resource conservation may be ineffective if they lack the necessary livelihood means and assets. Households adopting outdated and scarcely innovative livelihood strategies based on dwindling conventional sources of income negatively affect project outcomes, while families with average financial capital and relying on diversified economic activities could drive a positive secondary outcome. Owning adequate financial resources is crucial to support the implementation of improved forest management options. The achievement of positive outcomes in forestry projects should therefore be sustained by promoting parallel economic activities that can increase the financial capital of rural communities. We also find that achieving positive project outcomes largely depends on the quality and accessibility of the natural capital stock. Households and communities with reliable access to land, water and forest resources are among the best recipients of initiatives aiming at demonstrating improved practices. As far as the physical capital is concerned, the presence of adequate water supply infrastructure proves to be a driver of uptake of sustainable practices even in the case of low project outcomes. Promoting a wider participation of local stakeholders in project activities is a sound strategy to create the conditions for project success.
The analysis of the uptake of improved forest management practices herein presented would have greatly benefitted from the availability of baseline data and of a counterfactual scenario through a control group, including similar communities not benefitting from project interventions. This would have allowed comparing the pre-intervention conditions with the post-project ones. Unfortunately, baseline and counterfactual data were not available, limiting the validity of the results presented in this article.
Despite this constraint, our findings highlight a twofold implication for the management of forestry initiatives that can be useful for project designers and policy makers. Firstly, context-specific livelihood assets should be taken into consideration in the targeting process. Secondly, the relevance and effectiveness of investments in forestry development projects require thorough and accurate monitoring and evaluation frameworks capable of detecting success drivers and lasting outcomes.
The Authors wish to thank the Water and Mountains Team, Forestry Department, FAO and the staff of the Fouta Djallon Highlands Integrated Natural Resources Management Project (EP/INT/503/GEF), FAO, for the financial support provided to the study. Moreover, we would like to acknowledge the contribution of Guinean institutions and organisations to the development of the survey, in particular: Direction Nationale de l'Hydraulique (DNH), Centre d'Etude et de Recherche en Environnement (CERE)-Universite Gamal Abdel Nasser de Conakry (UGANC), ONG Volontaires Africains pour l'Assistance Technique (VAATEC).
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P. CECI (a), C. CICATIELLO (b), L. MONFORTE (c), E. BLASI (b), S. FRANCO (d), G. BRANCA (d) and G. SCARASCIA-MUGNOZZA (b)
(a) Royal Botanic Gardens, Kew, Wellcome Trust Millennium Building, RH17 6TN, Wakehurst Place, Ardingly, West Sussex, U.K.
(b) Universita degli Studi della Tuscia, Department for Innovation in Biological, Agro-food and Forest Systems, via San Camillo de Lellis snc, 01100, Viterbo, Italy
(c) Food and Agriculture Organization of the United Nations (FAO), Office of Evaluation (OED), viale delle Terme di Caracalla, 00153, Rome, Italy
(d) Universita degli Studi della Tuscia, Department of Economics, Engineering, Society and Business Organization, via del Paradiso 47, 01100, Viterbo, Italy
Email: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com, firstname.lastname@example.org
(1) The term "outcome" is used to designate the long-term results of projects, going beyond beneficiaries directly involved and intervention lifespan, and including behavioural change towards forest conservation and uptake of improved practices, thus leading to permanent environmental and socio-economic impacts.
(2) The REDD programme is a subsidising mechanism for initiatives aimed at the reduction of greenhouse gas emissions linked to deforestation and forest degradation. REDD+ is the current evolution of the former REDD mechanism, with a focus on reforestation and improvement of forest carbon stocks.
(3) Projet d'Amenagement des Bassins Representatifs Pilotes de Bafing et Bale, and Gestion de l'Espace Rural et des Forets, Cellule d'Appui a la Decentralisation-Bafing (GERF CAD-Bafing).
(4) Acacia auriculiformis, Acacia mangium, Pinus kesya, Pinus caribaea, Pinus oocarpa, Eucalyptus camaldulensis, Eucalyptus torreliana, Tectona grandis, Gmelina arborea, Erythrophleum guineense and Afzelia africana.
(5) Data collection was conducted within the FAO-led Fouta Djallon Highlands Integrated Natural Resources Management Project EP/INT/503/GEF - 2009-2021, funded by the Global Environment Facility (GEF). This project is meant to capitalise on past initiatives linked to the African Union's Regional Programme for the Integrated Development of the FDH. The four villages included in the survey were selected to provide an overlap between sites covered by the two past projects analysed in this article and sites concerned by the present FAO's project, in order to make a quantitative baseline available to FAO as a monitoring tool.
(6) Open interviews, transect walks and direct observation, focus group discussions with semi-structured interviews and the compilation of village histories.
TABLE 1 Variables selected to describe the livelihood assets Livelihood N[degrees] of variables selected from each section assets of the questionnaire S1 S2 S3 S4 S5 S6 S7 S8 S9 HC - Human 5 4 3 3 7 - - - - capital SC - Social - - - 7 - - 4 12 - capital NC - Natural - - - 4 - 11 - - - capital PC - Physical 12 2 - 5 - 5 1 - - capital FC - Financial - 1 1 17 1 - 2 - - capital Livelihood Total Topics covered assets n[degrees] of variables HC - Human 22 Family composition, out-migration, capital education, knowledge and skills, health, food security, adaptive capacity. SC - Social 23 Information networks, relations of trust capital and mutual support, mechanisms for participation in decision-making, common rules and sanctions, formal and informal groups. NC - Natural 15 Forests and forest products, water, capital land, climate variability, biodiversity, environmental services, trends in the state of natural resources. PC - Physical 25 Transport, roads, housing, water supply capital infrastructure and sanitation, personal goods, facilities, access to communication, tools, technologies. FC - Financial 22 Financial stock, access to credit, capital remittances, livestock. Source: Authors ' elaboration TABLE 2 Variables selected to describe participation in project activities and project outcomes Domains N[degrees] of variables selected from each section of the questionnaire S1 S2 S3 S4 S5 S6 S7 S8 S9 PA - Participation - - - - - - - - 57 in project activities PO - Project - - - 1 - 28 - 1 32 outcomes Domains Total n[degrees] Topics covered variables PA - Participation 57 Involvement in forest cover in project activities enhancement and protection, fighting against wildfires, agro-sylvo-pastoral development, training, socio-economic infrastructures, climactic and environmental monitoring. PO - Project 62 Sustainability, replicability, outcomes impact on agriculture and natural resources (soil, forests and water), livelihood diversification and coping strategies. Source: Authors ' elaboration TABLE 3 Overview of the results of the PCAs Domain Code Number of variables Human capital HC 22 Social capital SC 23 Natural capital NC 15 Physical capital PC 25 Financial capital FC 22 Participation in project activities PA 57 Project outcomes PO 62 Domain Number of selected Explained components variance Human capital 4 49.0% Social capital 3 49.0% Natural capital 4 46.8% Physical capital 3 39.5% Financial capital 5 58.0% Participation in project activities 1 47.5% Project outcomes 4 47.2% Source: Authors' elaboration TABLE 4 Coordinates of source variables and interpretation of components (social capital) Social capital Source variables Variable coordinates - Component 1 Labour provided to the community 0.155 Labour obtained from the community 0.162 Forest fire control measures 0.154 Community fire control committee 0.253 Participation in the fire control committee 0.316 Community reforestation 0.341 Participation in community reforestation 0.603 Community road maintenance 0.088 Participation in community road maintenance 0.163 Participation in community decision-making 0.388 Frequency of decision-making meetings 0.634 Membership in socio-economic interest groups 0.938 HH men # involved in socio-economic interest groups 0.802 HH women # involved in socio-economic interest groups 0.697 Participation in a forest interest group 0.230 Participation in a horticultural group 0.667 Participation in a soap-making group 0.382 Participation in a dyeing group 0.386 Participation in a nursery, livestock or beekeeping group 0.085 Legally recognised group 0.863 Management role in the group 0.476 Frequency of group management meetings 0.761 Satisfaction with group functioning 0.920 Names of the components SC1 - Associativism for economic purposes and for the sake of the community Descriptions of the components Men and women of the family participate in a socio-economic interest group (dealing with horticulture or dyeing or soap making). The group is legally recognised, the family is represented in the management and the overall functioning is considered satisfactory. The family is also actively involved in decision-making meetings and forest protection activities. Social capital Source variables Variable coordinates - Component 2 Labour provided to the community -0.097 Labour obtained from the community -0.164 Forest fire control measures 0.134 Community fire control committee 0.315 Participation in the fire control committee 0.147 Community reforestation -0.118 Participation in community reforestation -0.099 Community road maintenance -0.631 Participation in community road maintenance -0.642 Participation in community decision-making -0.091 Frequency of decision-making meetings -0.038 Membership in socio-economic interest groups -0.057 HH men # involved in socio-economic interest groups -0.119 HH women # involved in socio-economic interest groups 0.134 Participation in a forest interest group 0.022 Participation in a horticultural group -0.514 Participation in a soap-making group 0.774 Participation in a dyeing group 0.770 Participation in a nursery, livestock or beekeeping group 0.052 Legally recognised group -0.006 Management role in the group 0.086 Frequency of group management meetings -0.031 Satisfaction with group functioning -0.003 Names of the components SC2 - Associativism for economic purposes Descriptions of the components The household (women) only participates in a socio-economic interest group (dealing with dyeing or soap making). Social capital Source variables Variable coordinates - Component 3 Labour provided to the community 0.280 Labour obtained from the community 0.011 Forest fire control measures 0.533 Community fire control committee 0.672 Participation in the fire control committee 0.479 Community reforestation 0.139 Participation in community reforestation 0.066 Community road maintenance 0.623 Participation in community road maintenance 0.602 Participation in community decision-making -0.055 Frequency of decision-making meetings 0.096 Membership in socio-economic interest groups -0.208 HH men # involved in socio-economic interest groups -0.071 HH women # involved in socio-economic interest groups -0.077 Participation in a forest interest group 0.136 Participation in a horticultural group -0.312 Participation in a soap-making group 0.146 Participation in a dyeing group 0.252 Participation in a nursery, livestock or beekeeping group -0.274 Legally recognised group -0.126 Management role in the group 0.056 Frequency of group management meetings -0.167 Satisfaction with group functioning -0.181 Names of the components SC3 - Associativism for the sake of the community Descriptions of the components The household participates in a committee to fight against forest fires, in road maintenance activities, provides labour to relatives and neighbours and is slightly involved in a soap-making group. Source: Authors' elaboration TABLE 5 List of selected components and their names and descriptions Human capital Descriptions of the components HC1 - Least vulnerable, Large family led by young man, with knowledgeable, male-led family no emigrants. Children go to school and are vaccinated. The household has access to modern medicine. They make compost, use fertilisers and vaccinate livestock. Food insecurity problems during rainy season. HC2 - Very vulnerable family Small household, with no emigrants. Main problems include lack of access to modern medicine and education, poor diet and strong food insecurity during the rainy season. HC3 - Slightly vulnerable, Family led by unschooled, young adaptive female-led family woman. The household compensates the lack of education with technical and practical skills (compost making, use of fertilisers, livestock vaccination). They consume few meals a day, but they try to follow a balanced diet. HC4 - Vulnerable family led by Family led by aged woman, with aged woman (out-migration) emigrated members. Boys go to school and children are vaccinated. Imbalanced diet and food insecurity problems during the rainy season. Social capital Descriptions of the components SC1 - Associativism for Men and women of the family economic purposes and for the participate in a socio-economic sake of the community interest group (dealing with horticulture or dyeing or soap making). The group is legally recognised, the family is represented in the management and the overall functioning is considered satisfactory. The family is also actively involved in decision-making meetings and forest protection activities. SC2 - Associativism for The household (women) only economic purposes participates in a socio-economic interest group (dealing with dyeing or soap making). SC3 - Associativism for the sake The household participates in a of the community committee to fight against forest fires, in road maintenance activities, provides labour to relatives and neighbours and is slightly involved in a soap-making group. Natural capital Descriptions of the components NC1 - Potentially vulnerable Problematic access to water sources water resources (lack of water and lack of forests to protect them. protection forests) The rainfall pattern is regular and water sources have not dried up. No forest fires occur, the trend has definitely decreased. Near the village, there are protected and natural forests that provide edible fruits and leaves. NC2 - Good state of natural High availability of land of all resources types. Villagers own private forest plantations and forest cover has increased (natural and riparian forests). Rainfall pattern has not significantly changed and there are abundant water resources. NC3 - Vulnerable forest Near the village there are natural resources (fires) forests but no protected forests and frequent forest fires occur. It rains more than in the past during the dry season and the rainy season starts earlier. There are no conflicts over the access to water resources. NC4 - Vulnerable water Valley land is sufficiently resources (erratic, decreased available. Presence of protected precipitation) forests near the village, very few forest fires occur and the trend has decreased. There is no consensus on the precipitation trend during the dry season, the rainy season starts later than in the past and rainfall intensity has decreased. Physical capital Descriptions of the components PC1 - Traditional housing, good Traditional housing and no recent access to infrastructures home maintenance. Good access to infrastructure, borehole is the main source of drinking water and roads are maintained. Technical equipment includes a fenced perimeter for livestock and anti-erosion structures. PC2 - Modern housing, average Modern housing and no more than access to infrastructures, modest three houses in the compound, no equipment recent home maintenance. Good access to school (including secondary school) and health care, but not to water supply infrastructure. Roads are not maintained. Agricultural fields are fenced with barbed wire. PC3 - Modern housing, fairly Modern housing and more than three good access to infrastructure, houses in the compound. Fairly good modest equipment access to infrastructure (health care centre and water supply), drinking water from traditional wells. Transport facilities to market are not satisfactory and roads are not maintained. Goods include a bicycle. Financial capital Descriptions of the components FC1 - Agriculture-based, Agriculture, including dry-season economically stable family agriculture, is the main livelihood. More than three family members contribute to the income. The family frequently attends the market to buy and sell products. They own sheep and chickens and sell a few of the latter. FC2 - No agriculture-based, Agriculture, including dry-season economically stable family agriculture, or livestock rearing are the second source of income. The household owns goats and chickens and usually sells them. FC3 - Family with mixed The household relies on livestock livelihood strategy and livestock rearing as its second source of income. They do not receive food from visiting emigrants. The household usually sells goats. FC4 - Family with mixed The household relies on livelihood strategy and craftsmanship or trade or other alternative activities alternative activities as second source of income. No more than three members contribute to the income. Agriculture is very insecure and is not practiced during the dry season. The household owns goats and chickens and sells goats. FC5 - Family with mixed The household relies mainly on livelihood strategy and livestock rearing or craftsmanship, remittances trade and other alternative activities as its first source of income, but remittances are an important second source of income. The household usually sells goats. Participation in project activities Description of the component PA1 - Project activities with Reforestation and forest protection highest rate of participation activities, especially on land donated by the beneficiaries themselves, ranked highest in terms of participation, followed by socio-economic infrastructures and agro-sylvo-pastoral development activities. Project outcomes Descriptions of the components PO1 - Good, widespread Project participants continue to primary outcome, fairly good implement a wide array of secondary outcome activities, including reforestation and fighting against forest fires. These activities are also conducted by other community members so that awareness of the importance of the natural resource base is achieved. PO2 - Low primary outcome, no Limited project outcome in secondary outcome connection with increased awareness of the importance of forests and of their protection: all reforestation activities have ceased. Erosion control measures, use of improved stoves and enrichment of kitchen gardens continue, along with use of water supply infrastructure and livestock rearing practices. PO3 - No primary outcome, The community understands the value fairly good secondary outcome of forests and is actively committed to increase the forest cover, especially for future availability of timber. Instead, participants to the projects do not continue activities, not deeming them relevant or remunerative. PO4 - Fairly good primary Even if participants in the projects outcome, no secondary outcome continue reforestation activities, the community at large does not carry them out in spite of its impoverished forest resources. Source: Authors' elaboration TABLE 6 Synthesis of the results obtained through the four regression analyses Project outcomes PO1 Principal components Good, widespread primary outcome, fairly good secondary outcome [R.sup.2] 0.911 Predictive capacity Pr < 0.0001 HC1 - Least vulnerable, knowledgeable, 0.074 male-led family HC2 - Very vulnerable family -0.005 HC3 - Slightly vulnerable, adaptive female-led 0.242 (**) family HC4 - Vulnerable family led by aged woman -0.126 (out-migration) SC1 - Associativism for economic purposes and 0.140 (*) for the sake of the community SC2 - Associativism for economic purposes 0.078 SC3 - Associativism for the sake of the 0.076 community NC1 - Potentially vulnerable water resources -0.056 NC2 - Good state of natural resources 0.086 NC3 - Vulnerable forest resources (fires) -0.043 NC4 - Vulnerable water resources (erratic, -0.105 decreased precipitation) PC1 - Traditional housing, good access to 0.053 infrastructure PC2 - Modern housing, average access to 0.194 infrastructure, modest equipment PC3 - Modern housing, good access to -0.118 infrastructure, modest equipment FC1 - Agriculture-based, economically stable -0.018 family FC2 - Not agriculture-based, economically -0.062 stable family FC3 - Family with mixed livelihood strategy -0.223 (*) and livestock FC4 - Family with mixed livelihood strategy -0.069 and alternative activities FC5 - Family with mixed livelihood strategy 0.043 and remittances PA1 - Project activities with highest rate of 0.657 (***) participation Project outcomes PO2 Principal components Low primary outcome, no secondary outcome [R.sup.2] 0.306 Predictive capacity Pr = 0.139 HC1 - Least vulnerable, knowledgeable, -0.019 male-led family HC2 - Very vulnerable family -0.470 (**) HC3 - Slightly vulnerable, adaptive female-led 0.245 family HC4 - Vulnerable family led by aged woman 0.051 (out-migration) SC1 - Associativism for economic purposes and 0.107 for the sake of the community SC2 - Associativism for economic purposes -0.063 SC3 - Associativism for the sake of the 0.210 community NC1 - Potentially vulnerable water resources -0.475 (*) NC2 - Good state of natural resources 0.022 NC3 - Vulnerable forest resources (fires) 0.170 NC4 - Vulnerable water resources (erratic, -0.441 (*) decreased precipitation) PC1 - Traditional housing, good access to -0.072 infrastructure PC2 - Modern housing, average access to -0.205 infrastructure, modest equipment PC3 - Modern housing, good access to 0.413 (*) infrastructure, modest equipment FC1 - Agriculture-based, economically stable -0.321 family FC2 - Not agriculture-based, economically -0.102 stable family FC3 - Family with mixed livelihood strategy 0.248 and livestock FC4 - Family with mixed livelihood strategy 0.005 and alternative activities FC5 - Family with mixed livelihood strategy -0.160 and remittances PA1 - Project activities with highest rate of 0.046 participation Project outcomes PO3 Principal components No primary outcome, fairly good secondary outcome [R.sup.2] 0.470 Predictive capacity Pr = 0.001 HC1 - Least vulnerable, knowledgeable, 0.072 male-led family HC2 - Very vulnerable family 0.139 HC3 - Slightly vulnerable, adaptive female-led 0.033 family HC4 - Vulnerable family led by aged woman 0.084 (out-migration) SC1 - Associativism for economic purposes and 0.270 (**) for the sake of the community SC2 - Associativism for economic purposes -0.263 SC3 - Associativism for the sake of the -0.150 community NC1 - Potentially vulnerable water resources -0.081 NC2 - Good state of natural resources 0.466 (**) NC3 - Vulnerable forest resources (fires) -0.123 NC4 - Vulnerable water resources (erratic, 0.190 decreased precipitation) PC1 - Traditional housing, good access to 0.052 infrastructure PC2 - Modern housing, average access to -0.069 infrastructure, modest equipment PC3 - Modern housing, good access to 0.144 infrastructure, modest equipment FC1 - Agriculture-based, economically stable -0.048 family FC2 - Not agriculture-based, economically 0.144 stable family FC3 - Family with mixed livelihood strategy 0.144 and livestock FC4 - Family with mixed livelihood strategy 0.420 (**) and alternative activities FC5 - Family with mixed livelihood strategy -0.029 and remittances PA1 - Project activities with highest rate of -0.070 participation Project outcomes PO4 Principal components Fairly good primary outcome, no secondary outcome [R.sup.2] 0.215 Predictive capacity Pr = 0.601 HC1 - Least vulnerable, knowledgeable, -0.006 male-led family HC2 - Very vulnerable family 0.106 HC3 - Slightly vulnerable, adaptive female-led 0.003 family HC4 - Vulnerable family led by aged woman 0.088 (out-migration) SC1 - Associativism for economic purposes and -0.192 for the sake of the community SC2 - Associativism for economic purposes -0.016 SC3 - Associativism for the sake of the -0.159 community NC1 - Potentially vulnerable water resources -0.184 NC2 - Good state of natural resources -0.156 NC3 - Vulnerable forest resources (fires) -0.012 NC4 - Vulnerable water resources (erratic, 0.053 decreased precipitation) PC1 - Traditional housing, good access to -0.023 infrastructure PC2 - Modern housing, average access to -0.136 infrastructure, modest equipment PC3 - Modern housing, good access to -0.040 infrastructure, modest equipment FC1 - Agriculture-based, economically stable -0.083 family FC2 - Not agriculture-based, economically -0.094 stable family FC3 - Family with mixed livelihood strategy 0.017 and livestock FC4 - Family with mixed livelihood strategy 0.052 and alternative activities FC5 - Family with mixed livelihood strategy -0.058 and remittances PA1 - Project activities with highest rate of 0.053 participation NB: significant coefficients for a < 0.10 are marked with (*); significant coefficients for a < 0.05 are marked with (**); significant coefficients for a < 0.01 are marked with (***). Source: Authors' elaboration
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|Author:||Ceci, P.; Cicatiello, C.; Monforte, L.; Blasi, E.; Franco, S.; Branca, G.; Scarascia-Mugnozza, G.|
|Publication:||International Forestry Review|
|Article Type:||Case study|
|Date:||Dec 1, 2018|
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