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REVIEW article

Front. Ecol. Evol., 09 July 2024
Sec. Conservation and Restoration Ecology
This article is part of the Research Topic Ecosystem Condition Assessments: Progress towards a Global Standard View all 4 articles

Review of forest ecosystem services evaluation studies in East Africa

Erick O. Osewe,*Erick O. Osewe1,2*Bogdan PopaBogdan Popa1Harald VacikHarald Vacik2Ibrahim OseweIbrahim Osewe1Ioan Vasile AbrudanIoan Vasile Abrudan1
  • 1Faculty of Silviculture and Forest Engineering, Transilvania University of Brasov, Brasov, Romania
  • 2Institute of Silviculture, University of Natural Resources and Life Sciences, Vienna, Austria

The East African region hosts diverse forest ecosystems, such as woodlands, highland forests, and coastal mangrove forests. These ecosystems are crucial for biodiversity and support various plant and animal species. They provide essential resources, benefiting livelihoods directly and indirectly. Examining regional and global variations in forest ecosystem valuation, especially regarding livelihood benefits, is crucial for sustainable resource management aligned with forest-based climate solutions. The aim of this review is to assess how regional contextual factors and global trends impact the valuation of ecosystem services (ES) in East Africa, with two main objectives (1) to identify the most evaluated ES in East Africa and (2) to identify the preferred ES valuation methods and approaches applied in East Africa. Data from the Web of Science/Clarivate platform was used in the systematic review process using the Reporting standard for Systematic Evidence Syntheses to retrieve and analyse 222 articles. The ES were categorized using the Millennium Ecosystem Assessment framework and the Common International Classification of Ecosystem Services in order to create a review database. Provisioning services i.e., wood biomass and food production were the most assessed at 55%, followed by 30% regulating services i.e., carbon storage, 8.6% support services i.e., habitat and 6.4% cultural services i.e., ecotourism which reflected communities’ direct reliance on forest resources. The preferred direct ES valuation techniques included market price at 14.9% for assessing provisioning services and travel cost methods at 10.4% for cultural services. Amongst the indirect ES valuation techniques, remote sensing at 14.7% were preferred as they proved efficient for large and remote tropical forest areas. Participatory methods such as interviews at 11.8% were also preferred because they offer holistic perspectives on community priorities. This review provides spatial context on the regional priorities of ES valuation which is vital for safeguarding natural resources for future generations.

1 Introduction

Forest ecosystems are primary habitats for a wide range of species (Isbell et al., 2011) and the abundance of biodiversity provides the flow of ecosystem services (ES), offering multiple benefits for human wellbeing (Sangha et al., 2023; Sharpe et al., 2023). Forest ecosystems are important because they form the baseline for achieving sustainable circular economies as global commitments are being made towards transitioning to carbon neutrality, bioeconomy, and green energy (Baker et al., 2010; Manoj et al., 2024). Moreover, forests contribute towards alleviating climate change by regulating the levels of atmospheric carbon and Green House Gases (GHG) (Jhariya et al., 2024). They also perform mitigation by developing resilient habitats which minimize risks associated with the effects of climate change such as global warming, floods, and low agricultural productivity (Locatelli, 2016; Chapman et al., 2022). The interactions of the living and non-living components of forests as a functional unit allows ecosystems to have dynamic responses to a mix of temporal and spatial disturbances (Calderon-Aguilera et al., 2012), influencing both their structure and function. Ecological variations are also significant when factors such as intensity, magnitude, and frequency of either anthropogenic or natural disturbances are considered (Osewe et al., 2022). Biological diversity is interlinked with ecosystem vitality and health (Manoj et al., 2022). Loss of biodiversity and changes in heterogeneity directly influence the ability of an ecosystem to provide and supply essential services and can affect the long-term capacity of natural systems in adapting and responding to global pressures (Butchart et al., 2010; Nyongesa et al., 2023). Therefore, changes in genetic diversity can affect the ability of an ecosystem to provide essential ecological, economic, and social benefits services needed by society (Roger et al., 2012; Coates et al., 2018).

Three landmark studies on ES have given a comprehensive framework to enable practitioners to categorize and understand with more clarity the various aspects involving ES. They are the Millennium Ecosystem Assessment (MEA), Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) and the Economics of Ecosystems and Biodiversity study (TEEB) (Tisdell, 2014; Reid and Mooney, 2016). Research articles on ES widely accept the classification by the MEA which puts forward four categories: (1) Provisioning services i.e., fibre, food, freshwater, genetic resources and wood, (2) Regulatory services i.e., pollination, water purification, climate regulation and water regulation, (3) Supporting services i.e., nutrient cycling, primary production and soil formation, (4) Cultural services i.e., spiritual, religious, ecotourism, inspirational, aesthetic and cultural heritage benefits (Mooney et al., 2004).

Resource scarcity and environmental awareness have been the major drivers towards understanding the contribution of ES to societies, considering the global concern of climate change (Calderon-Aguilera et al., 2012) and the response to other pressures (Xepapadeas, 2011; Rizos et al., 2019). Concerns over the depletion of natural capital and loss of ES after the industrialization era have become more pronounced resulting in a common understanding of ecosystem benefits of the use and non-use values of nature (Boehnert, 2016). The interdisciplinary intersection between research areas of forest ecology and classical economics has enabled better understanding of natural capital and recognized contribution of ES to the overall economic structure of societies which were previously undervalued. For instance, Costanza et al. (2014) through the quantitative global assessment report on ES estimated the value of natural capital to be significantly higher than the global gross domestic product (GDP).

Different studies on ecosystem valuation have elicited both criticism and support through the varied responses concerning estimates of natural capital being significantly higher than global GDP as reported by Costanza et al. (2014). Across many scholarly articles on ES there’s ambiguity in the definition of reference terms i.e., the definition of ecosystem processes and ecosystem functions, the differences in providing benefits and biophysical relationship that exists between nature and human beings regardless of the benefits (Hooper et al., 2012). These differences, including those related to the used terminology, have limited comparative understanding of asset flows in ecosystem studies and its relation to the end user benefits (Notte et al., 2017). However, the common understanding that daily livelihoods depend on the goods and services provided by nature emphasizes the importance of protecting ecosystems (Chettri et al., 2021; Fan et al., 2022).

Forest ecosystem valuation give quantitative evidence of the ES provided by forests using certain conceptual and methodological frameworks (Mukherjee et al., 2014; Whitham et al., 2015), that estimate the economic value of market and non-market environmental goods and the economic value of various ES which is essential in achieving sustainable forest management. This knowledge of natural capital forms the foundation of sustainable forest programs by prioritizing policies geared for green economies through innovative economic expansion based on natural resources (Wackernagel and Rees, 1997; Engelbrecht, 2009). 13 out of 17 United Nations Sustainable Development Goals are directly or indirectly reliant on the condition of natural resources (Baumgartner, 2019). Therefore, decisions about the sustainable management of natural capital are supported by the valuation of forest ES, which has led to more innovative approaches towards reduction of anthropogenic pressures on forests and climate change (Boehnert, 2016).

Globally, recognition of critical interdependencies between sustainable resource management, socio-economic development and forest conservation plays a key role when establishing approaches for assessing forest ES. Effective methods of ES valuation encapsulate the multifunctionality of forest ecosystems such as ecological, social, and economic parameters to provide information about trade-offs (Börner et al., 2009; Kindu et al., 2022). The existing mechanisms include subsidy schemes that use economic incentives towards resource management practices that ensure continuous provision of quality ES (Börner et al., 2009) i.e., Payment for Ecosystem services (PES) schemes. They are voluntary with a clearly defined ES being traded or bought on the conditionality that the provider safeguards continuous provision of ecosystem services. Long-term sustainability of PES schemes with regards to Carbon as the ES traded, has proven to be more successful when more buyers of the ES like the local governments are included (Osewe et al., 2023a). Moreover, land property rights and tenure, as well as cash transaction types have shown inequities when Carbon is traded in a PES scheme (Kolinjivadi et al., 2023).

In Africa, tropical forest ecosystems are important natural resources because of their immense contribution to livelihoods through direct and indirect ES (Tranquilli et al., 2014). Tropical forest in Sub-Sahara, Central and West Africa cover large areas which act as carbon pools (Fischer et al., 2015)and significantly contribute towards environmental quality and climate stability through carbon sequestration (Adetoye et al., 2018).Studies on African (Keenan et al., 2015; Corbeels et al., 2020) forest ecosystems have shown loss in forested areas often resulted from human-induced pressures such as over exploitation of forest resources, deforestation, increased demand for wood energy and land use change (Müller and Mburu, 2009; Tompkins et al., 2015). The assessment of dry Afromontane Forest ecosystem in Northern Ethiopia (Solomon et al., 2019) using benefit transfer methods revealed a decrease in ecosystem services, which was attributed to the conversion of forest land to arable lands and fuel wood extraction by adjacent communities.

Economic valuation approaches for non-use values like the case study of East Mau Forest in Kenya (Langat et al., 2018), has shown the critical role of forest ecosystems in climate regulation by quantifying the amount of carbon sequestered, which accounted for 80% of the total economic value. Similarly, the valuation of Kakamega National Forest Reserve estimated the total economic value to be over US$ 70 million per year through the supporting and regulatory services (Mutoko et al., 2015). In Tanzania, the valuation was conducted using consumption surveys and choice modelling for non-use values versus market price for use-values. This led to the development of an effective PES model for the wetland area of Kilombero Valley (Mombo et al., 2014), which reduced the rate of deforestation and degradation of catchment forest. The assessment of non-use values (Jensen, 2009) gives insight on the economic potential of forest ecosystems and informs approaches for developing appropriate valuation tools (Sourokou et al., 2023; McIntosh and Zhang, 2024).

Previous studies on forest ES within East Africa revealed that conservation priorities of forest adjacent communities were linked with ES that support subsistence use of resources, because of their direct dependence on forest products such as wood, water, food, and other raw materials to meet basic household needs (Swallow et al., 2009; Anley et al., 2022; Osewe et al., 2023b). Additionally, forest fragmentation and cover loss especially at the edge layers were linked to expansion of agricultural fields in forested areas (Osewe et al., 2022). Similar studies (Heubach et al., 2011; Jamouli and Allali, 2020; Wale et al., 2022; Chama et al., 2023; Charnley, 2023) have also established that ES are beneficial to the communities and perceived priorities influence their attitudes towards utility of forest resources (Apsalyamova et al., 2015). Further, the review by Jamouli and Allali (2020) on economic valuation of ES in Africa established that between the year 2005 and 2020 more than 50% of ecosystem valuation studies in Africa were done in Southern Africa and East Africa (Quijas and Balvanera, 2013).

Our review study builds on the previous findings by detailing the regional variations on ES and the valuation methods. The aim of this review is to assess how regional contextual factors and global trends impact the valuation of ecosystem services (ES) in East Africa, with two main objectives (1) to identify the most evaluated ES in East Africa and (2) to identity the preferred ES valuation methods and approaches applied in East Africa. Data was collected through a meta-analysis of indexed journals in the Web of Science/Clarivate platform and the analysis aimed at providing ground for future ES relates research in the East Africa (i.e. Kenya, Uganda, Tanzania and Ethiopia) regional context, by (a) identifying the ES that have been subject to evaluation, (b) identifying the preferred ES valuation methods and approaches applied in connection with the targeted ES and (c) identifying ES valuation related research gaps that should be addressed in the future for a better understanding of the relationship between forest ecosystems and human communities.

2 Methodological frame

2.1 Study area

The study area consists of four East African countries i.e., Kenya, Uganda, Tanzania, and Ethiopia. The region has a wide range of forest ecosystems such as tropical rainforest, dryland forest, savannah woodlands, afro-alpine habitat, coastal forest, montane forest, and mangrove forest (Tekalign et al., 2018). These forest ecosystems provide a wide range of goods and services that support livelihoods of the local communities, as detailed in Table 1. Forest management approaches across the region have slight variations but stress on: (a) conservation effort to balance socio-economic and ecological need, (b) sustainable practices and (c) involvement of local communities (Wangai et al., 2016). In Kenya majority of the forest is managed by Kenya Forest Service (Ototo and Vlosky, 2018), in Uganda by National Forest Authority (Obua et al., 2010), in Tanzania by the Forest and Bee keeping Division (Mgaya, 2021), and in Ethiopia by different entities including the Ethiopian Environment and Forest Institute (Kassa et al., 2022). The region experiences an array of climates due to varying geographical location and topography. In Kenya, the western region experiences tropical climate, with consistent rain throughout the year while the north and northeastern region experience hot and dry climate. Uganda has tropical climate with two rainy seasons and short dry seasons. In Tanzania the coastal region has topical climate with high humidity with two rainy seasons, and Ethiopia experience mostly tropical monsoon climate with two rainy seasons (Wangai et al., 2016).

Table 1
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Table 1 Summary of ecosystem service categories assessed in East Africa.

In Kenya, the total forest area is estimated at 4.3 million ha (Ototo and Vlosky, 2018), which comprises of two forest types i.e., natural and plantation forest: natural forest consisting of montane forest, western rainforest, coastal forest, and dryland forest, while plantation forest consists of both exotic and indigenous trees meant for production purposes. The main issues affecting the forestry sector include population pressure, increased demand for agricultural land, and demand for wood products to supply the deficit of industrial raw materials. Forest types in Uganda include dryland, montane, swamp, savanna woodlands, and tropical rainforest totalling to about 3.6 million ha (Masiga et al., 2012). The main issues in the forestry sector are inadequacies in implementation of forest plans, legislation and policy, technical constraints, and inadequate financing of forest resource management. In Tanzania the main forest types include montane, miombo woodlands (Næsset et al., 2020), coastal mangrove, and tropical rainforest with a total area coverage of 35.2 million ha (Ntiyakunze and Stage, 2022), while the main challenges of the sector are forest degradation and deforestation, limited access to alternative source of energy, and poor forest governance. In Ethiopia the main forest types are Afromontane Forest (Kassun et al., 2024), dry Afromontane Forest, riparian forest, dry deciduous forest, and savanna woodlands forest. Total forest area is estimated at 13.6 million ha (Kassun et al., 2024) and the main challenges include population pressure on forest, land tenure issues, and inadequate financing (Kimengsi et al., 2022; Tebkew and Atinkut, 2022).

2.2 Data collection

Data search on evaluated forest ES categories and valuation methods was conducted on the Web of Knowledge/Clarivate database platform (https://www.webofscience.com) accessed in March 2023 (Yeung, 2023). The search function used key words “forest ecosystem services” to retrieve articles on relevant studies published from 2007 to 2023. A systematic review process was conducted using the Reporting standards for Systematic Evidence Syntheses [ROSES] (Haddaway et al., 2018) in three main phases: (1) search from database using key words, (2) screening process using established parameters, and (3) critical analysis of selected articles (Figure 1). Retrieved papers having key words in their abstracts or titles were restricted to display case studies from Kenya, Tanzania, Uganda, and Ethiopia. The exclusion parameters at the screening stage considered the availability of articles at full text and relevancy by checking titles, abstracts, and introduction sections. Articles with only the authors from region of interest or institutional affiliations without a case study from the study area were also excluded during the second phase. To determine suitability of the articles, further examination of the methodology and discussion sections was done at the critical analysis stage. The data was extracted from suitable articles and used to create a database for analysis of categories of ES assessed, methods and approaches of ecosystem valuation.

Figure 1
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Figure 1 Conceptual framework using ROSES systematic review adapted from (Haddaway et al., 2018) systematic flowchart diagrams.

2.3 Classification of ES and valuation methods for analysis

We selected a total of 222 articles suitable for review i.e., 98 from Ethiopia, 82 from Kenya, 22 from Tanzania, and 20 from Uganda. Data were extracted from the 222 articles that satisfied ROSES criteria for analysis as shown in Figure 1. The ES were categorised using the MEA framework and the Common International Classification of Ecosystem Services [CICES] (Roy and Potschin, 2018). For CICES, the ES had a five-level structure as a reference: Section (e.g., Provisioning services), Division (e.g., biomass), Group (e.g., plants), Class (e.g., cultivated plants) and Class type (e.g., cereals). For the MEA framework (Grima et al., 2023) ES were classified as follows: (1) Provisioning services i.e., fibre, food, freshwater, genetic resources, and wood, (2) Regulatory services i.e., pollination, water purification, climate regulation and water regulation, (3) Supporting services i.e., nutrient cycling, primary production, and soil formation, (4) Cultural services i.e., spiritual, religious, ecotourism, inspirational, aesthetic, and cultural heritage benefits. The valuation methods and approaches (Markanday et al., 2024) were categorised using the following classification: (1) direct valuation methods i.e., revealed preference and stated preference and (2) indirect valuation approaches i.e., participatory approaches, modelling, and mapping as detailed in Figure 2 (Martin and Mazzotta, 2018; Acharya et al., 2019). We first made quantitative research which included count for every country on how many times different ES categories were assessed, and count on how many times a certain method for ES valuation was used. Secondly, we made a qualitative analysis on the results of the studies and presented the results of the analysis.

Figure 2
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Figure 2 Classification model used for identifying ES valuation methods and approaches adapted from Acharya et al. (2019).

Numeric values resulted by counting the number of ES valuations/methods identified in the analysed papers and by classifying them as indicated above.

3 Results and discussions

3.1 Categories of ES that were subject to valuation

More than half of the articles analysed in this review assessed provisioning services as detailed in Figure 3. The ease at which provisioning ES are quantifiable and measurable prioritizes its assessment across most studies, when compared to other ES categories as they are easily associated with tangible and marketable goods or services (Ajwang’ Ondiek et al., 2016; Strauch et al., 2016). Impacts of changes in provision ES were more immediate and visible compared to other ES categories (Tamire et al., 2023).

Figure 3
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Figure 3 Detailing share of the ecosystem categories evaluated in East Africa.

The reliance on provisioning ES by forest adjacent communities in Africa (Egoh et al., 2012), Southeast Asia and South America has been cited as a major cause of ecosystem valuation studies prioritizing this category of ES for assessment (Quijas and Balvanera, 2013). For instance, the valuation of provisioning ES in India linked socio economic factors of households near the tropical dry forest of Vindhyan highlands to their income portfolios and established the significance of provisioning services to their livelihoods (Sharma et al., 2023). Similarly (Wangai et al., 2016), in a review of ES in Africa established that there were more studies focusing on provisioning services such as wood for fuel, a significant number of studies addressed regulating services such as carbon sequestration while fewer studies addressed supporting and cultural services in the context of the communities as opposed to singling out one of the commonly studied services like ecotourism (Samal and Dash, 2023). In contrast, the valuation studies in Europe (Fitter et al., 2010) revealed that ES without the ability to provide goods for conventional markets are usually undervalued, provisioning services such as biodiversity were only valued based on their ability to create marketable goods, while regulating services such as pollination were undervalued despite their linkage to marketable goods from agricultural production (Food Agriculture Organisation (FAO), 2016).

3.1.1 Provisioning services

East Africa heavily relies on agriculture and forests for food and to support informal livelihoods (Salami et al., 2010). The region’s fertile soils, diverse climates, and suitable growing conditions support a wide range of crops, including staple foods like maize, sorghum, millet, and beans (Tittonell et al., 2010; Kansiime et al., 2018). Agriculture is a significant contributor to the economy and employment in East Africa, with millions of people involved in farming and related activities. Assessing food production helps understand the availability, accessibility, and sustainability of the region’s food supply facing challenges like climate variability, market demands, policy restrictions etc (Midega et al., 2015). These challenges affect the wellbeing and livelihoods of the locals and exacerbates forest dependency, especially on provisioning ES. This comparative review revealed that all categories of provisioning ES were assessed in different studies, as shown in Table 1, with varying contribution to forest fringe community’s livelihood and use.

In Kenya, 42% of the respondents in Mt Marsabit identified provisioning service like wood fuel and fodder for livestock as the most frequently used amongst other ES (Ouko et al., 2018). According to the respondents, anthropogenic activities like deforestation reduced supply of the provisioning ES to local forest communities. The research findings recommended long term engagement with the local community to initiate social learning processes that improve forest management practices. Similarly, in Uganda (Mawa et al., 2022) about 50% of the Budogo respondents identified wood fuel and raw materials like thatch material as the most frequently used for both subsistence and commercial purposes (Masiga et al., 2012). Mawa et al. (2022) revealed that participants in forest conservation groups had increased income derived from forest stands after two decades of management from USD 281 to USD 359. This was attributed to the allocation of agricultural use sections in forest plantation to participants who planted trees and gained income from the harvest. Another contributing factor was the involvement of participants in PES schemes in the region that promoted farm planting of trees with cash transactions for participating in the PES scheme (Aganyira et al., 2020). Further, the findings recommended that community involvement in forest management would significantly enhance the forest adjacent livelihoods and promote sustainable non-farm economic models with higher returns (Call et al., 2017).

In Rufiji (Tanzania) the respondents identified 67% of the provisional ES as the most important amongst other ES due to their direct market value and ease of accessibility (Nyangoko et al., 2022). Some of the prioritized provisioning ES include poles for building, wood fuel for cooking, and honey used as additive in tea. According to Nyangoko et al. (2022) some other provisioning services were identified but ranked lowly like traditional medicines, which were used in the past before the presence of health care centres offering modern medicines. In contrast to the findings in Mt Marsabit (Kenya), respondents in Rufiji identified fodder as an important provisional ES, but lowly ranked due to inland grazing (i.e., grasses and shrubs). In Ethiopia’s Munessa-Shashemene forest (Furo et al., 2022), the provisioning ES identified as important included wood fuel, honey, construction poles and non-timber forest products that support household income. This overdependence on the forest resulted in forest degradation and deforestation (Duguma et al., 2019). Further, Girma et al. (2022) indicated that wood fuel contributed more to household income compared to other provisioning ES identified by the respondents, mainly attributed to the use of wood fuel in alcohol production within the study area. The policy recommendations of the study were to incentivize and subsidize strategies that increase agricultural income for the studied local communities (Abebaw et al., 2012).

3.1.2 Regulating services

Regulating services occurred as either final or intermediate benefit, and often supporting the delivery of other service categories (Kumar et al., 2010). In most of the economic valuation of ES, high consideration was given to services with a consumptive or productive function (Kieslich and Salles, 2021). Our findings revealed that water regulation, carbon storage and climate regulation had the highest percentage share in terms of assessments amongst the other regulating services (Table 1). These results reflect the general interest to assess deforestation rates and establish sustainable forest management within tropical forest ecosystems in developing countries (Rahman et al., 2017), because of their ability to sequester and store carbon, improve water quality and quantity, regulate floods and climate (Logsdon and Chaubey, 2013; Gould et al., 2024). Interest for regulating ES varies according to the spatial scale. For instance, in Kenya the implementation of a PES mechanism with the aim of equitable payment for watershed in reference to water quality as ES ensured up stream farmers managed their lands to control soil erosion, conservation of riparian lands by reforestation, reduce use of ago- chemicals, and use of grass strips to retain soil (Nyongesa et al., 2016). This improved the water quality downstream, and participants of the PES mechanism reported an improvement in soil fertility and increased crop productivity (Haile et al., 2019).

East Africa is the preferred destination for most of the carbon sequestration PES in Africa (Jindal et al., 2008; Lee et al., 2016). For instance, in Kibale (Uganda) (Cavanagh and Benjaminsen, 2014) the carbon sequestration PES has led to 1.2 million tons of carbon sequestered since inception (Omeja et al., 2011). The project totals about 6,500 ha of restored natural forest and has directly created 140 permanent jobs. Some of the PES schemes indirectly promoted regulation ES which was not the focus of the PES schemes. For instance, the PES scheme in Kenya (Khalifa et al., 2021) with the aim of incentivizing local communities to be involved in forest management by using commercial insects, led to increased abundance of pollinating bees which benefited the horticultural famers.

In Tanzania, Nyangoko et al. (2022) assessed ES in Rufiji Delta and established that 53% of the respondents identified three regulating ES that improved their well-being i.e., sediment trappings, coastal protection, and climate regulation. Further, Ntibona et al. (2022), revealed that respondent’s insight on the value of mangrove forest protecting their villages coincided with coastal flooding due to overflow of River Rufiji. The respondents also identified rain formation as a contribution of mangrove forest, which provided suitable conditions for agricultural activities (Njana, 2020). Sediment trappings had the lowest score from rankings of the regulating ES, and this was attributed to its intangible value, which made it difficult to identify and rank. In Ethiopia, Mekuria et al. (2018) determined that changes in regulating ES occurred in communal grazing lands after the establishment of enclosures. The study revealed that all the enclosures displayed a higher ES than communal lands. Over a 30-year period, 246 Mg ha -1 of carbon was sequestered while the total soil nitrogen increased by 7.9 Mg ha -1. The net ES value of the enclosures was 28% more than alternative wheat production. This highlighted how enclosures were a better competitive alternative land use than communal lands (Mekuria et al., 2018; Kleinschroth et al., 2021).

3.1.3 Supporting services

The valuation of supporting ES was limited due to a lack of consensus in the definition of terms when the intermediate benefits were assessed (Khan, 2020). In this review, supporting services were the least assessed category at 6.42%. Moreover, only three services resulted from this meta-analysis of ES valuation i.e., habitat at 62%, nutrient cycling at 21% and soil formation at 17% (Table 1). Similarly, a study on the global perspective of ecosystem classification by Notte et al. (2017) established that some studies opted to exclude the economic valuation of support services because of the difficulty in finding a valuation technique which distinguishes between intermediate services and final benefits (Boerema et al., 2017). Further, some services such as soil formation often require a much longer time frame for proper assessment, while others, like nutrient cycling, must be evaluated while considering underlying ecological systems which pose a potential for duplicity in evaluation (Khan, 2020; Kadykalo et al., 2021; Ingram et al., 2023).

Provision of ES is dependent on the state and maintenance of habitats which form the grounds for most biological interactions between organisms (Rajpar, 2018). For instance, the ecosystem accounting study in Uganda by UNEP revealed that protected wildlife habitats prevented loss of natural ecosystem benefits and had a higher diversity index compared to degraded habitats (King and Obst, 2017). Similarly, the mangrove ecosystems along the coast of Kenya and Tanzania have also been credited for harbouring different species of crabs, which recycle nutrients by feeding on detritus that provide a food source for other marine species (Theuerkauff et al., 2018; Kimeli et al., 2021; Naidoo, 2023). In Ethiopia (Fashing et al., 2022), the isolated Afromontane regions exhibited higher levels of biodiversity and ecosystem services compared to the explored sections in the lowlands which consequently exhibited lower quality of ecosystem services (Mengist et al., 2022). Therefore, the quality of support ES which often stems from high species diversity relies on habitat status (Durán et al., 2020).

3.1.4 Cultural services

East Africa is one of the leading tourist destinations in the African continent, with a diverse portfolio ranging from clear sandy beaches, wildlife safaris and cultural tourism (Okello and Novelli, 2014; Gogo and Masaki, 2022). This review established that ecotourism ranked highest at 44% amongst all the other cultural services i.e., recreational at 23%, cultural practices at 20% and spiritual services at 13%. Results in Table 1 shows that nearly half of the ecotourism assessments were done in Kenya. Reports by the Kenya Tourism Board indicate that the country had over 2 million visitors pre-COVID-19 and 1.5 million of them were non-resident who primarily visited for holiday and ecotourism purposes, which directly contributed over USD 5 billion to the country’s GDP (Tourism Research Institute (TRI), 2023). Moreover, the tourism performance increased by 70.45% post -COVID-19 which registered a growth of 83% according to the annual report by Tourism Research Institute (Ministry of Tourism, 2022; Tourism Research Institute (TRI), 2023).

In terms of cultural tourism, both Kenya and Tanzania have the Maasai tribe who live in the border-region and are nomadic between the Maasai-Mara National Reserve and Serengeti National Park (Snyder and Sulle, 2011; Brinks, 2016). The unique cultural niche offered by the Maasai is their preservation of indigenous way of life i.e., beliefs system, arts, food, and customs (Ngaruiya, 2015; Oduor, 2020). Uganda has remnants of the Baganda Kingdom and Kabaka palaces, which offer a perspective on the indigenous cultural practices of the Baganda people (Kasfir, 2020). However, there is still heavy reliance on wildlife-based tourism since Uganda is landlocked and prioritizes marketing its national parks since touristic earnings from them account for approximately 9% of the national GDP (Ayorekire et al., 2019). Similarly, Tanzania’s tourism sector contributes about 10.7% to the national GDP (Kweka et al., 2003).

Ethiopia exhibited a diverse portfolio of cultural services: studies frequently assessed the spiritual and recreational sites such as the churches of Lalibela, the site of true Holy Cross of Christ, Ethiopian Tewahedo Orthodox churches (Gessese et al., 2021) and Tiya stones (Karbo, 2013). Moreover, the county has a religious history as amongst the oldest to accept Christianity and Islam (Aerts et al., 2016). However, the country’s tourism sector underperforms (Ali, 2016) when compared to countries like Tanzania and Kenya, resulting from touristic preference towards game drives and beaches as well as low marketing campaign to attract tourist from the relevant authorities (Norton, 1996; O’Halloran, 2016).

3.2 Methods and approaches of ES valuation in East Africa

Both the direct valuation methods and indirect approaches (Markanday et al., 2024) were applied in the studies reviewed, and the valuation methods depended on the ES identified and prioritized in each of the East African countries as detailed in Table 2. Amongst the direct ES valuation methods used, the market price approach under revealed preference category and contingent valuation method (CMV) under the stated preference category were preferred (Stenger et al., 2009; Acharya et al., 2019). For the indirect ES valuation approaches, interviews were preferred under the category of participatory approaches. Further, a variety of modelling and mapping approaches were used for ES assessment with Geographic Information Systems (GIS), Light Detection and Ranging (LiDAR) having more preference.

Table 2
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Table 2 Summary of methods and approaches of ecosystem valuation in East Africa.

3.2.1 Direct valuation methods

The production function approach under revealed preference category was used to assess supporting ES primarily associated with agricultural production i.e., soil fertility, nutrient cycling, and soil organic matter (Bekunda et al., 2005). Regionally, the African Development Bank (Salami et al., 2010) reported agriculture as one of the main economic activities in the East African region, primarily done by small holder farmers who occupied farmlands adjacent to forest ecosystems (Gelgo et al., 2023; Birkhofer et al., 2024). Further, the International Food Policy Research Institute affirms that agriculture contributes an average of 30% to the GDP of Kenya, Tanzania, Uganda, and Madagascar (Waithaka et al., 2013; Tambo et al., 2023). In Kenya, the land degradation surveillance network established indicators of productivity in Sasumua catchment and its capacity to deliver ES to the local farmers (Kyei, 2017). Similarly, sample plots in Usambara Mountains (Tanzania) determined the productivity of farms using soil organic carbon as an indicator. The studies enabled the improvement of crop productivity to small holder farmers (Winowiecki et al., 2016).

The rural communities in this review demonstrated overwhelming dependence on provisioning ES products such as wood fuel and raw materials (Miller et al., 2021). In Uganda, assessment on forest stock and household fuel choice established that the likelihood using biofuel significantly increased for households in rural areas near large forest stocks (Gebru and Elofsson, 2023). For wood and raw products, market price approaches determined demand and supply of wood fuels and the priority areas of wood energy use in Eastern Africa i.e., Rwanda, Kenya, Tanzania, Uganda, Egypt, Burundi, and DR Congo (Sulaiman et al., 2017). The study established a nexus between the use of wood fuels under the prevailing socioeconomic conditions within the region and suggested effective points of intervention (Drigo, 2005). Similarly, market price approaches were used to assess regulatory ES of two different catchment areas in Kenya (Elgeyo and Nyambane), and their estimated value was over USD 480 million (Eregae et al., 2022).

For cultural ES, the ecotourism and recreational value of Maasai Mara National Park in Kenya was estimated to be over US$ 70 million (Mulwa et al., 2018) per year, using the individual travel cost methods derived from modelling the visitor data logs and entrance fees (Márquez et al., 2023). Abdeta (2022) used a contingent valuation method (CVM) to assess household willingness to pay (WTP) for the conservation of spiritual and recreational values of forest sites in Ethiopia (Ramdas and Mohamed, 2014). The findings indicated that demographic and socio-economic factors influenced perceived ES benefits and highlighted the need for public participation to improve management of forest resources. Similarly, stated preference methods such as CVM were used estimate the WTP for the cultural ES in Wof-Washa Forest in Ethiopia (Getachew, 2018).

3.2.2 Indirect valuation methods

The global demand for accurate, verifiable, and cost-efficient forest inventory data, especially for the vast and unexplored tropical ecosystems in Africa, South America and Southeast Asia led to the adoption of the recent advancements in forest management i.e., use of satellites, drones, LiDAR, and GIS (Mitchell and Schaab, 2008; Tang and Shao, 2015; Li et al., 2019). This assisted to bridge conventional ecosystem management methods with remote sensing and GIS applications (Baban and Niţă, 2022; Diallo et al., 2024) in forest ecosystem valuation. Different studies (Breugel et al., 2011; Rodríguez-Veiga et al., 2017; Vorster et al., 2020) indicate a demand for accurate forest biomass data because of its significance in the estimation of carbon (Araujo Barbosa et al., 2015). Remote sensing techniques and GIS application were primarily used for the valuation of provisioning ES (Araujo Barbosa et al., 2015; Negese, 2024). In Eastern Africa, regulatory ES i.e., climate and weather variability too, were assessed to determine effect on agricultural output using remote sensed data from the period 1961 to 2016 (Luc et al., 2021).

The valuation of the provisioning ES in Central Ethiopia, Biratu et al. (2022) highly relied on spatial data derived from remote sensing techniques to get an estimate of the total ecosystem valuation for the timeframe 1986–2021. Similarly, remote- sensing and GIS approaches provided crucial data on water supply, which was used in the quantification of livelihood dependency of communities along the Omo River in Turkana Basin at the boarder of Kenya and Ethiopia (Kleinschroth et al., 2021). The data were crucial for the assessment of changes in ES benefits along River Omo Basin (Yigezu et al., 2018; Anose et al., 2021) and its implications on the culture of nomadic people in that region. The rise of interest in biomass and carbon storage estimates were incentivized by mechanisms such as REDD+ and carbon credit systems for developing countries (Scharlemann et al., 2010; Parrotta et al., 2012; Thangata and Hildebrand, 2012). For instance, USD 100 billion was pledged in the Africa Climate Summit towards climate adaptation on the continent (African Union (AU), 2023). In contrast, the priorities of the European countries towards quantification carbon are to reduce GHG emissions and reduce dependence on fossil fuels (Siddi, 2020; Allam et al., 2022). Further, the European Green Deal (Vela Almeida et al., 2023; Popielak et al., 2024) centres on assisting EU countries to become carbon neutral (European Union (EU), 2021).

The participatory approaches identified in this review (Langan et al., 2018; Ketema et al., 2021; Daw et al., 2023) i.e., interviews, focus groups discussions, and household surveys gave an overall perspective on the value attributed to the regulating ES. In the context of ES valuation, it was particularly important when assessing WTP for non-market ES i.e., temperature and coastal protection (Comte et al., 2016). In Kenya, interviews with open-ended questionnaires were the preferred method to assess and quantify the full value of ES benefits to livelihood of forest adjacent communities in Maasai Mau (Koech et al., 2009). Similarly, a series of household surveys and interviews in Uganda (Bush et al., 2005) were used to estimate the value of tropical high forest in protected areas to the livelihoods of communities surrounding them and determine contribution of the non-market ecosystem services to the GDP. This approach recognised the values communities hold, their priority towards ecosystem services and offered a more informed perspective for decision makers (Mawa et al., 2023).

For cultural ES, participatory approaches such as interviews, focus group discussions and household surveys (Waruingi et al., 2021; Masselus and Fiala, 2024) highlight the effectiveness of non- monetary approaches in evaluating perception of non-market values of ES such as culture and recreational benefits (Zeppel, 2007; Márquez et al., 2023). In Kenya, Wangai et al. (2017) used household surveys to determine cultural ES indicators of well-being within the peri-urban areas of Nairobi and to develop suitable ES response models. Similarly, Mwakaje et al. (2013) used data from key informants and focus group discussions to assess the perceived cultural ES benefits from respondents living in Northern Tanzania on the value associated with living near the Serengeti National Park (Zeng et al., 2023).

4 Conclusions

Despite the fact that this study was limited to Kenya, Uganda, Tanzania and Ethiopia within the East African region and the data was exclusively obtained from open access indexed journals in the ISI Web of science platform, our analysis revealed a series of conclusions that are useful for further ES valuation research.

Provisioning services were the most assessed ES category amongst all the 4 countries. Their direct linkage to livelihoods necessitated relevance and priority in valuation because changes and impacts were more immediate and visible compared to other categories. Another contributing factor was the linkage between perceived benefits from tangible goods and motivation of communities to understand aspects of availability in quantity for ES goods like food, raw materials, and water. ES categories like regulating services were mainly linked to the rising interest in carbon sequestration and storage. The least evaluated ES was the supporting services, which were often intermediate and indistinguishable from final ES benefits. This indicated a gap in methodologies tailored specifically for evaluating supporting ES, highlighting the need for adaptable valuation techniques that can accommodate varying temporal and ecological complexities.

In the context of ES benefiting communities, provisioning ES were assessed using market price approaches in all the 4 countries and production function approaches only in Kenya, Tanzania and Ethiopia because of the direct reliance on tangible ES goods i.e., wood, cultivated plants and raw materials. Remote sensing and GIS applications in forestry were the most preferred method in Kenya and Ethiopia for modelling and mapping because of the available technological know-how, factors of cost and time efficiency in assessment of often large and remote tropical forest ecosystems. Participatory approaches such as interviews, household surveys and focus groups were extensively used in all the 4 countries which gave a perspective on the utility priorities that communities attach to the various ES. This reiterates the long-term benefits of community involvement in improving quality ES.

In many cases, ES valuation required a combination of different methods. For instance, cultural ES exhibited a diverse portfolio of services and perceived values amongst the 4 countries assessed, the variations necessitated application of two different techniques for valuation i.e., ecotourism evaluated using travel cost method in Kenya, Tanzania and Uganda, while spiritual values evaluated using participatory approaches in Ethiopia (Okello and Novelli, 2014). Moreover, this review has shed light on inequities inherent in carbon trading within PES schemes, in the payment for watershed with reference to water quality and the appreciation of genetic resources. Practitioners are better equipped to navigate the multifaceted challenges present in PES by incorporating integrated valuation methods that work towards implementing more equitable and sustainable PES mechanisms addressing various environmental and socio-economic concerns effectively. Our findings demonstrate how different regions prioritize ES benefits and inform further studies on temporal and contextual shifts in ES valuations. Moreover, the findings illustrate effective strategies for practitioners conducting ES valuation at country level and regional level.

Author contributions

EOO: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing. BP: Formal analysis, Methodology, Supervision, Validation, Writing – review & editing. HV: Data curation, Methodology, Validation, Writing – review & editing. IO: Visualization, Writing – review & editing. IVA: Funding acquisition, Project administration, Resources, Supervision, Validation, Writing – review & editing.

Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Transilvania University of Brasov, Interdisciplinary Doctoral School (grant number DGRIAE-111284/IN1/1/EC/03.09.2021).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

References

Abdeta D. (2022). Households’ Willingness to pay for forest conservation in Ethiopia: A review. J. For. Sci. doi: 10.17221/94/2022-JFS

CrossRef Full Text | Google Scholar

Abebaw D., Kassa H., Kassie G. T., Lemenih M., Campbell B., Teka W. (2012). Dry forest based livelihoods in resettlement areas of northwestern Ethiopia. For. Policy Economics 20, 72–77. doi: 10.1016/j.forpol.2012.02.002

CrossRef Full Text | Google Scholar

Acharya R. P., Maraseni T., Cockfield G. (2019). Global trend of forest ecosystem services valuation – an analysis of publications. Ecosyst. Serv. 39, 100979. doi: 10.1016/j.ecoser.2019.100979

CrossRef Full Text | Google Scholar

Adetoye A. M., Okojie L. O., Akerele D. (2018). Forest carbon sequestration supply function for African countries: an econometric modelling approach. For. Policy Economics 90, 59–66. doi: 10.1016/j.forpol.2018.01.007

CrossRef Full Text | Google Scholar

Aerts R., Overtveld K. V., November E., Wassie A., Abiyu A., Demissew S., et al. (2016). Conservation of the Ethiopian church forests: threats, opportunities and implications for their management. Sci. Total Environ. 551–552, 404–414. doi: 10.1016/j.scitotenv.2016.02.034

PubMed Abstract | CrossRef Full Text | Google Scholar

AFRICAN UNION (AU). (2023).The african leaders nairobi declaration on climate change and call to action preamble. Available online at: chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://au.int/sites/default/files/decisions/43124-Nairobi_Declaration_06092023.pdf.

Google Scholar

Aganyira K., Kabumbuli R., Muwanika V. B., Tabuti J. R. S., Sheil D. (2020). Determinants of participation in state and private PES projects in Uganda. Sci. Afr. 8, e00370. doi: 10.1016/j.sciaf.2020.e00370

CrossRef Full Text | Google Scholar

Ajwang’ Ondiek R., Kitaka N., Oduor S. O. (2016). Assessment of provisioning and cultural ecosystem services in natural wetlands and rice fields in Kano Floodplain, Kenya. Ecosyst. Serv. 21, 166–173. doi: 10.1016/j.ecoser.2016.08.008

CrossRef Full Text | Google Scholar

Ali Y. (2016). Challenge and prospect of Ethiopian tourism policy. J. Hotel Business Manage. 5. doi: 10.4172/2169-0286.1000134

CrossRef Full Text | Google Scholar

Allam Z., Sharifi A., Giurco D., Sharpe S. A. (2022). Green new deals could be the answer to COP26’s deep decarbonisation needs. Sustain. Horizons 1, 100006. doi: 10.1016/j.horiz.2022.100006

CrossRef Full Text | Google Scholar

Anley M. A., Minale A. S., Ayehu N. H., Gashaw T. (2022). Assessing the impacts of land use/cover changes on ecosystem service values in rib watershed, upper blue Nile Basin, Ethiopia. Trees Forests People 7, 100212. doi: 10.1016/j.tfp.2022.100212

CrossRef Full Text | Google Scholar

Anose F. A., Beketie K. T., Zeleke T. T., Ayal D. Y., Feyisa G. L. (2021). Spatio-temporal hydro-climate variability in Omo-Gibe River Basin, Ethiopia. Climate Serv. 24, 100277. doi: 10.1016/j.cliser.2021.100277

CrossRef Full Text | Google Scholar

Apsalyamova S. O., Khashir B. O., Khuazhev O. Z., Tkhagapso M. B., Bgane Y. K. (2015). The economic value of forest ecosystem services. J. Environ. Manage. Tourism 6, 291–965. doi: 10.14505/jemt.v6.2(12).01

CrossRef Full Text | Google Scholar

Araujo Barbosa C. C. D., Atkinson P. M., Dearing J. A. (2015). Remote sensing of ecosystem services: A systematic review. Ecol. Indic. 52, 430–443. doi: 10.1016/j.ecolind.2015.01.007

CrossRef Full Text | Google Scholar

Ayorekire J., Obua J., Byaruhanga M. B. (2019). “Broadening Uganda’s tourism product base through indigenous cultural resource utilisation,” in Positive Tourism in Africa (Taylor and Francis), 79–90. doi: 10.4324/9780429428685-7

CrossRef Full Text | Google Scholar

Baban G., Niţă M. D. (2022). Measuring forest height from space. Opportunities and limitations observed in natural forests. SSRN Electronic J. doi: 10.2139/ssrn.4305424

CrossRef Full Text | Google Scholar

Baker D. J., Richards G., Grainger A., Gonzalez P., Brown S., DeFries R., et al. (2010). Achieving forest carbon information with higher certainty: A five-part plan. Environ. Sci. Policy. doi: 10.1016/j.envsci.2010.03.004

CrossRef Full Text | Google Scholar

Baumgartner R. J. (2019). Sustainable development goals and the forest sector-A complex relationship. Forests 10. doi: 10.3390/f10020152

PubMed Abstract | CrossRef Full Text | Google Scholar

Bekunda M. A., Ebanyat P., Nkonya E., Mugendi D., Msaky J. J. (2005). Soil fertility status, management, and research in East Africa. Eastern Afr. J. Rural Dev. 20. doi: 10.4314/eajrd.v20i1.28362

CrossRef Full Text | Google Scholar

Biratu A. A., Bedadi B., Gebrehiwot S. G., Melesse A. M., Nebi T. H., Abera W., et al. (2022). Ecosystem service valuation along landscape transformation in central Ethiopia. Land 11. doi: 10.3390/land11040500

PubMed Abstract | CrossRef Full Text | Google Scholar

Birkhofer K., Bird T., Alfeus M., Arvidsson F., Buxton M., Djoudi E. A., et al. (2024). Smallholder agriculture in african dryland agroecosystems has limited impact on trophic group composition, but affects arthropod provision of ecosystem services. Agriculture Ecosyst. Environ. 363. doi: 10.1016/j.agee.2023.108860

CrossRef Full Text | Google Scholar

Boehnert J. (2016). The green economy: reconceptualizing the natural commons as natural capital. Environ. Commun. 10, 395–417. doi: 10.1080/17524032.2015.1018296

CrossRef Full Text | Google Scholar

Boerema A., Rebelo A. J., Bodi M. B., Esler K. J., Meire P. (2017). Are ecosystem services adequately quantified? J. Appl. Ecol. doi: 10.1111/1365-2664.12696

CrossRef Full Text | Google Scholar

Börner J., Mburu J., Guthiga P., Wambua S. (2009). Assessing opportunity costs of conservation: ingredients for protected area management in the Kakamega Forest, Western Kenya. For. Policy Economics 11, 459–675. doi: 10.1016/j.forpol.2009.05.004

CrossRef Full Text | Google Scholar

Breugel M. V., Ransijn J., Craven D., Bongers F., Hall J. S. (2011). Estimating carbon stock in secondary forests: decisions and uncertainties associated with allometric biomass models. For. Ecol. Manage. 262, 1648–1575. doi: 10.1016/j.foreco.2011.07.018

CrossRef Full Text | Google Scholar

Brinks R. J. (2016). The Impact of Tourism on the Maasai Culture A Case Study from Ole Keene, Narok County, Republic of Kenya. (Master thesis). Noorderdiep: University of Gronigen, The Netherlands.

Google Scholar

Bush G., Nampindo S., Aguti C., Plumptre A. (2005). The Value of Uganda’s Forests: A Livelihoods and Ecosystems Approach Rift Programme EU Forest Resources Management and Conservation Programme National Forest Authority. Kampala.

Google Scholar

Butchart S. H. M., Walpole M., Collen B., Strien A. V., Scharlemann J. P. W., Almond R. E. A., et al. (2010). Global biodiversity: indicators of recent declines. Science 328, 1164–1168. doi: 10.1126/science.1187512

PubMed Abstract | CrossRef Full Text | Google Scholar

Calderon-Aguilera L. E., Rivera-Monroy V. H., Porter-Bolland L., Martínez-Yrízar A., Ladah L. B., Martínez-Ramos M., et al. (2012). An assessment of natural and human disturbance effects on Mexican ecosystems: current trends and research gaps. Biodivers Conserv. 21, 589–617. doi: 10.1007/s10531-011-0218-6

CrossRef Full Text | Google Scholar

Call M., Mayer T., Sellers S., Ebanks D., Bertalan M., Nebie E., et al. (2017). Socio-environmental drivers of forest change in Rural Uganda. Land Use Policy 62, 49–58. doi: 10.1016/j.landusepol.2016.12.012

CrossRef Full Text | Google Scholar

Cavanagh C., Benjaminsen T. A. (2014). Virtual nature, violent accumulation: the ‘Spectacular failure’ of carbon offsetting at a Ugandan National Park. Geoforum 56, 55–65. doi: 10.1016/j.geoforum.2014.06.013

CrossRef Full Text | Google Scholar

Chama E., Shibru S., Gebre T., Demissew S., Woldu Z. (2023). Forest products monetary contribution to households’ Income: A means to improve the livelihood of a low-income rural community in South Ethiopia. Heliyon 9, e215535. doi: 10.1016/j.heliyon.2023.e21553

CrossRef Full Text | Google Scholar

Chapman C. A., Abernathy K., Chapman L. J., Downs C., Effiom E. O., Gogarten J. F., et al. (2022). The future of Sub-Saharan Africa’s biodiversity in the face of climate and societal change. Front. Ecol. Evol. 10. doi: 10.3389/fevo.2022.790552

CrossRef Full Text | Google Scholar

Charnley S. (2023). Livelihood investments as incentives for community forestry in Africa. World Dev. 168, 106260. doi: 10.1016/j.worlddev.2023.106260

CrossRef Full Text | Google Scholar

Chettri N., Aryal K., Thapa S., Uddin K., Kandel P., Karki S. (2021). Contribution of ecosystem services to rural livelihoods in a changing landscape: A case study from the Eastern Himalaya. Land Use Policy 109, 105643. doi: 10.1016/j.landusepol.2021.105643

CrossRef Full Text | Google Scholar

Coates D. J., Byrne M., Moritz C. (2018). Genetic diversity and conservation units: dealing with the species-population continuum in the age of genomics. Front. Ecol. Evol. 6. doi: 10.3389/fevo.2018.00165

CrossRef Full Text | Google Scholar

Comte J.-C., Cassidy R., Obando J., Robins N., Ibrahim K., Melchioly S., et al. (2016). Challenges in groundwater resource management in coastal aquifers of East Africa: investigations and lessons learnt in the Comoros islands, Kenya and Tanzania. J. Hydrology: Regional Stud. 5, 179–199. doi: 10.1016/j.ejrh.2015.12.065

CrossRef Full Text | Google Scholar

Corbeels M., Cardinael R., Powlson D., Chikowo R., Gerard B. (2020). Carbon sequestration potential through conservation agriculture in Africa has been largely overestimated. Soil Tillage Res. 196, 104300. doi: 10.1016/j.still.2019.104300

CrossRef Full Text | Google Scholar

Costanza R., Groot R. d., Sutton P., Ploeg S. v. d., Anderson S. J., Kubiszewski I., et al. (2014). Changes in the global value of ecosystem services. Global Environ. Change 26, 152–585. doi: 10.1016/j.gloenvcha.2014.04.002

CrossRef Full Text | Google Scholar

Daw T. M., Reid N. J., Coulthard S., Chaigneau T., António V. M., Cheupe C., et al. (2023). Life satisfaction in coastal Kenya and Mozambique reflects culture, gendered relationships and security of basic needs: implications for ecosystem services. Ecosyst. Serv. 62, 101532. doi: 10.1016/j.ecoser.2023.101532

CrossRef Full Text | Google Scholar

Diallo I. D., Tilioua A., Darraz C., Alali A., Sidibe D. (2024). Study and Evaluation of the Effects of Vegetation Cover Destruction on Soil Degradation in Middle Guinea through the Application of Remote Sensing and and Geotechnics. Heliyon 10, e235565. doi: 10.1016/j.heliyon.2023.e23556

CrossRef Full Text | Google Scholar

Drigo R. (2005). WISDOM-East Africa woodfuel integrated supply/demand overview mapping (WISDOM) methodology spatial woodfuel production and consumption analysis of selected african countries rudi drigo consultant-wood energy planning and forest resources monitoring. Available at: https//www.fao.org/4/j8227e/j8227e00.

Google Scholar

Duguma L., Atela J., Minang P., Ayana A., Gizachew B., Nzyoka J., et al. (2019). Deforestation and forest degradation as an environmental behavior: unpacking realities shaping community actions. Land 8, 265. doi: 10.3390/land8020026

CrossRef Full Text | Google Scholar

Durán A. P., Green J. M.H., West C. D., Visconti P., Burgess N. D., Virah-Sawmy M., et al. (2020). A practical approach to measuring the biodiversity impacts of land conversion. Methods Ecol. Evol. 11, 910–215. doi: 10.1111/2041-210X.13427

CrossRef Full Text | Google Scholar

Egoh B. N., O’Farrell P. J., Charef A., Josephine Gurney L., Koellner T., Nibam Abi H., et al. (2012). An African account of ecosystem service provision: Use, threats and policy options for sustainable livelihoods. Ecosyst. Serv. 2, 71–81. doi: 10.1016/j.ecoser.2012.09.004

CrossRef Full Text | Google Scholar

Engelbrecht H.-J. (2009). Natural capital, subjective well-being, and the new welfare economics of sustainability: some evidence from cross-country regressions. Ecol. Economics 69, 380–388. doi: 10.1016/j.ecolecon.2009.08.011

CrossRef Full Text | Google Scholar

Eregae J. E., Njogu P., Karanja R., Gichua M., Kenyatta J. (2022). Economic assessment of selected regulatory ecosystem services (RES) in the elgeyo and nyambene watersheds ecosystems in Kenya. doi: 10.21203/rs.3.rs-2238381/v1

CrossRef Full Text | Google Scholar

European Union (EU). (2021). “The European Green Deal and Cohesion Policy.” Brussels: European Parliament. A policy brief of the EU Parliament. Available at: https://www.europarl.europa.eu.

Google Scholar

Fan S., He M., Zhang T., Huo Y., Fan D. (2022). Credibility measurement as a tool for conserving nature: Chinese herders’ Livelihood capitals and payment for grassland ecosystem services. Land Use Policy 115, 106032. doi: 10.1016/j.landusepol.2022.106032

CrossRef Full Text | Google Scholar

Fashing P. J., Nguyen N., Demissew S., Gizaw A., Atickem A., Mekonnen A., et al. (2022). Ecology, evolution, and conservation of Ethiopia’s biodiversity. Proc. Natl. Acad. Sci. 119 (50). doi: 10.1073/pnas.2206635119

CrossRef Full Text | Google Scholar

Fischer R., Ensslin A., Rutten G., Fischer M., Costa D. S., Kleyer M., et al. (2015). Simulating carbon stocks and fluxes of an African tropical montane forest with an individual-based forest model. PloS One 10, e01233005. doi: 10.1371/journal.pone.0123300

CrossRef Full Text | Google Scholar

Fitter A., Elmqvist T., Haines-Young R., Potschin M., Rinaldo A., Setala H., et al. (2010). An assessment of ecosystem services and biodiversity in Europe. Issues Environ. Sci. Technol. 30, 1–28. doi: 10.1039/9781849731058-00001

CrossRef Full Text | Google Scholar

Food Agriculture Organisation (FAO). (2016). Mainstreaming Ecosystem Services and Biodiversity into Agricultural Production and Management in East Africa. Available online at: www.fao.org/publications.

Google Scholar

Furo G., Tifo K., Feng M. (2022). Socio-economic factors influencing household dependency on forest resources: A case of the Munessa-Shashemene Forest, Ethiopia. SN Soc. Sci. 3, 75. doi: 10.1007/s43545-022-00594-3

CrossRef Full Text | Google Scholar

Gebru B., Elofsson K. (2023). The role of forest status in households’ Fuel choice in Uganda. Energy Policy 173, 113390. doi: 10.1016/j.enpol.2022.113390

CrossRef Full Text | Google Scholar

Gelgo B., Gemechu A., Bedemo A. (2023). The effect of institutional quality on agricultural value added in East Africa. Heliyon 9, e209645. doi: 10.1016/j.heliyon.2023.e20964

CrossRef Full Text | Google Scholar

Gessese N., Gebru A., Nigatu B. (2021). Mediatization of development in Sub Saharan Africa: insights from Ethiopian orthodox tewahedo church (EOTC), ‘Mahibere kidusan’ Magazine, Ethiopia. Heliyon 7, e079835. doi: 10.1016/j.heliyon.2021.e07983

CrossRef Full Text | Google Scholar

Getachew T. (2018). Estimating willingness to pay for forest ecosystem conservation. The case of Wof-Washa Forest, North Shewa Zone, Amhara National Regional State, Ethiopia. Int. Peer-Reviewed J. 46. Available at: www.iiste.org.

Google Scholar

Girma G., Shimeles A., Abate T., Seyoum G., Alemu M. (2022). The urge for just transition: evidence from understanding of wood fuel producers’ Livelihoods and vulnerability in the drylands of Ethiopia. Front. Sustain. Food Syst. 6. doi: 10.3389/fsufs.2022.966137

CrossRef Full Text | Google Scholar

Gogo A. F. C., Masaki E. (2022). “Sustainability of cultural tourism in east african community,” in Advances in Science, Technology and Innovation (Springer Nature), 187–194. doi: 10.1007/978-3-031-07819-4_16

CrossRef Full Text | Google Scholar

Gould W. A., Álvarez-Berríos N. L., Parrotta J. A., McGinley K. (2024). “Climate change and tropical forests,” in Chapter 10 in Future Forests (Elsevier), 203–219. doi: 10.1016/B978-0-323-90430-8.00012-5

CrossRef Full Text | Google Scholar

Grima N., Jutras-Perreault M.-C., Gobakken T., Ørka H. O., Vacik H. (2023). Systematic review for a set of indicators supporting the common international classification of ecosystem services. Ecol. Indic. 147, 109978. doi: 10.1016/j.ecolind.2023.109978

CrossRef Full Text | Google Scholar

Haddaway N. R., Macura B., Whaley P., Pullin A. S. (2018). ROSES reporting standards for systematic evidence syntheses: pro forma, flow-diagram and descriptive summary of the plan and conduct of environmental systematic reviews and systematic maps. Environ. Evidence 7. doi: 10.1186/s13750-018-0121-7

CrossRef Full Text | Google Scholar

Haile K. K., Tirivayi N., Tesfaye W. (2019). Farmers’ Willingness to accept payments for ecosystem services on agricultural land: the case of climate-smart agroforestry in Ethiopia. Ecosyst. Serv. 39, 100964. doi: 10.1016/j.ecoser.2019.100964

CrossRef Full Text | Google Scholar

Heubach K., Wittig R., Nuppenau E.-A., Hahn K. (2011). The economic importance of non-timber forest products (NTFPs) for livelihood maintenance of Rural West African communities: A case study from northern Benin. Ecol. Economics 70, 1991–20015. doi: 10.1016/j.ecolecon.2011.05.015

CrossRef Full Text | Google Scholar

Hooper D. U., Adair E.C., Cardinale B. J., Byrnes J. E. K., Hungate B. A., Matulich K. L., et al. (2012). A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108. doi: 10.1038/nature11118

PubMed Abstract | CrossRef Full Text | Google Scholar

Ingram S., Belcher K., Hesseln H. (2023). Policy development to support ecosystem services on pasture systems in saskatchewan: A case study. Land Use Policy 134, 106885. doi: 10.1016/j.landusepol.2023.106885

CrossRef Full Text | Google Scholar

Isbell F., Calcagno V., Hector A., Connolly J., Harpole W.S., Reich P. B., et al. (2011). High plant diversity is needed to maintain ecosystem services. Nature 477, 199–202. doi: 10.1038/nature10282

PubMed Abstract | CrossRef Full Text | Google Scholar

Jamouli A., Allali K. (2020). “Economic valuation of ecosystem services in africa,” in E3S Web of Conferences. Eds. El Youssfi L., Cherkaoui S. I., Aghzar A., Farissi M., Godoy Faundez A., Rivera Salazar D., et al. (EDP Sciences) 183, 01002. doi: 10.1051/e3sconf/202018301002

CrossRef Full Text | Google Scholar

Jensen A. (2009). Valuation of non-timber forest products value chains. For. Policy Economics 11, 34–41. doi: 10.1016/j.forpol.2008.08.002

CrossRef Full Text | Google Scholar

Jhariya M. K., Singh L., Toppo S. (2024). Wildfires and carbon budget of certain seasonally dry forests in India. Land Degradation Dev. doi: 10.1002/ldr.5166

CrossRef Full Text | Google Scholar

Jindal R., Swallow B., Kerr J. (2008). Forestry-based carbon sequestration projects in Africa: potential benefits and challenges. Nat. Resour. Forum 32, 116–305. doi: 10.1111/j.1477-8947.2008.00176.x

CrossRef Full Text | Google Scholar

Kadykalo A. N., Kelly L. A., Berberi A., Reid J. L., Findlay C.S. (2021). Research effort devoted to regulating and supporting ecosystem services by environmental scientists and economists. PloS One 16, e02524635. doi: 10.1371/journal.pone.0252463

CrossRef Full Text | Google Scholar

Kansiime M. K., Asten P. v., Sneyers K. (2018). Farm diversity and resource use efficiency: targeting agricultural policy interventions in East Africa farming systems. NJAS: Wageningen J. Life Sci. 85, 32–415. doi: 10.1016/j.njas.2017.12.001

CrossRef Full Text | Google Scholar

Karbo T. (2013). Religion and social cohesion in Ethiopia. Int. J. Peace Dev. Stud. 4, 43–52. doi: 10.5897/IJPDS

CrossRef Full Text | Google Scholar

Kasfir N. (2020). The restoration of the Buganda kingdom government 1986-2014: culture, contingencies, constraints. J. Modern Afr. Stud. doi: 10.1017/S0022278X1900048X

CrossRef Full Text | Google Scholar

Kassa H., Abiyu A., Hagazi N., Mokria M., Kassawmar T., Gitz V. (2022). Forest landscape restoration in Ethiopia: progress and challenges. Front. Forests Global Change 5. doi: 10.3389/ffgc.2022.796106

CrossRef Full Text | Google Scholar

Kassun B. W., Kallio A.M. I., Trømborg E., Rannestad M. M. (2024). Vegetation density and altitude determine the supply of dry afromontane forest ecosystem services: evidence from Ethiopia. For. Ecol. Manage. 552, 121561. doi: 10.1016/j.foreco.2023.121561

CrossRef Full Text | Google Scholar

Keenan R. J., Reams G. A., Achard F., Freitas J. V.d., Grainger A., Lindquist E. (2015). Dynamics of global forest area: results from the FAO global forest resources assessment 2015. For. Ecol. Manage. 352, 9–20. doi: 10.1016/j.foreco.2015.06.014

CrossRef Full Text | Google Scholar

Ketema H., Wei W., Legesse A., Wolde Z., Endalamaw T. (2021). Quantifying ecosystem service supply-demand relationship and its link with smallholder farmers’ Well-being in contrasting agro-ecological zones of the East African rift. Global Ecol. Conserv. 31, e01829. doi: 10.1016/j.gecco.2021.e01829

CrossRef Full Text | Google Scholar

Khalifa S. A. M., Elshafiey E. H., Shetaia A. A., El-Wahed A. A., Algethami A. F., Musharraf S. G., et al. (2021). Overview of bee pollination and its economic value for crop production. Insects 12. doi: 10.3390/insects12080688

CrossRef Full Text | Google Scholar

Khan M. S. I. (2020). “Supporting Ecosystem Services: Concepts and Linkages to Sustainability,” In: Leal Filho, W., Azul, A., Brandli, L., Lange Salvia, A., Wall, T. (eds) Life on Land. Encyclopedia of the UN Sustainable Development Goals. Springer, Cham. 1–21. doi: 10.1007/978-3-319-71065-5_34-1

CrossRef Full Text | Google Scholar

Kieslich M., Salles J.-M. (2021). Implementation context and science-Policy interfaces: implications for the economic valuation of ecosystem services. Ecol. Economics 179, 106857. doi: 10.1016/j.ecolecon.2020.106857

CrossRef Full Text | Google Scholar

Kimeli A., Cherono S., Mutisya B., Tamooh F., Okello J., Westphal H., et al. (2021). Tracing organic matter sources in the estuarine sediments of Vanga, Kenya, and provenance implications. Estuarine Coast. Shelf Sci. 263, 107636. doi: 10.1016/j.ecss.2021.107636

CrossRef Full Text | Google Scholar

Kimengsi J. N., Owusu R., Djenontin I. N. S., Pretzsch J., Giessen L., Buchenrieder G., et al. (2022). What do we (Not) know on forest management institutions in Sub-Saharan Africa? A regional comparative review. Land Use Policy 114, 105931. doi: 10.1016/j.landusepol.2021.105931

CrossRef Full Text | Google Scholar

Kindu M., Mai T. L. N., Bingham L. R., Borges J. G., Abildtrup J., Knoke T. (2022). Auctioning approaches for ecosystem services – evidence and applications. Sci. Total Environ. 853. doi: 10.1016/j.scitotenv.2022.158534

PubMed Abstract | CrossRef Full Text | Google Scholar

King S., Obst C. (2017). Experimental ecosystem accounts for Uganda biodiversity impacts of trade view project diversity, community ecology and distribution of herpetofauna in the Albertine Rift (Africa) view project. doi: 10.13140/RG.2.2.34640.51201

CrossRef Full Text | Google Scholar

Kleinschroth F., Mekuria W., Schwatke C., McCartney M. (2021). “Ecosystem services in changing social-ecological systems,” in The Omo-Turkana Basin (Routledge, London), 78–101. doi: 10.4324/9781003169338-5

CrossRef Full Text | Google Scholar

Koech C. K., Ongugo P. O., Mbuvi M. T. E., Maua J. O. (2009). “Community forest associations in Kenya: challenges and opportunities,” in Paper presented at the annual conference proceedings of the Kenya Forest Research Institute in January 1–9, Nairobi.

Google Scholar

Kolinjivadi V., Hecken G. V., Merlet P. (2023). Fifteen years of research on payments for ecosystem services (PES): piercing the bubble of success as defined by a northern-driven agenda. Global Environ. Change 83, 102758. doi: 10.1016/j.gloenvcha.2023.102758

CrossRef Full Text | Google Scholar

Kumar P., United Nations Environment Programme, University of Liverpool, Indian Institute of Forest Management. (2010). Guidance Manual for the Valuation of Regulating Services (Nairobi: United Nations Environment Programme).

Google Scholar

Kweka J., Morrissey O., Blake A. (2003). The economic potential of tourism in Tanzania. J. Int. Dev. 15, 335–515. doi: 10.1002/jid.990

CrossRef Full Text | Google Scholar

Kyei E. (2017). Using the land degradation surveillance framework (LDSF) and farmers’ Perceptions to assess how land degradation has changed over a nine-year period in the Sasumua Catchment, Kenya. doi: 10.13140/RG.2.2.27462.83527

CrossRef Full Text | Google Scholar

Langan C., Farmer J., Rivington M., Smith J. (2018). Tropical wetland ecosystem service assessments in East Africa; A review of approaches and challenges. Environ. Model. Software 102, 260–273. doi: 10.1016/j.envsoft.2018.01.022

CrossRef Full Text | Google Scholar

Langat D. K., Maranga E. K., Aboud A. A., Cheboiwo J. K. (2018). The value of selected ecosystem services: A case study of East Mau Forest Ecosystem, Kenya. J. Forests 5, 1–10. doi: 10.18488/journal.101.2018.51.1.10

CrossRef Full Text | Google Scholar

Lee J., Ingalls M., Erickson J. D., Wollenberg E. (2016). Bridging organizations in agricultural carbon markets and poverty alleviation: an analysis of pro-Poor carbon market projects in East Africa. Global Environ. Change 39, 98–107. doi: 10.1016/j.gloenvcha.2016.04.015

CrossRef Full Text | Google Scholar

Li J., Huang X., Gong J. (2019). Deep neural network for remote-sensing image interpretation: status and perspectives. Natl. Sci. Rev. 6, 1082–1865. doi: 10.1093/nsr/nwz058

PubMed Abstract | CrossRef Full Text | Google Scholar

Locatelli B. (2016). “Ecosystem services and climate change,” in Routledge Handbook of Ecosystem Services. (New York, NY: Routledge), 481–490. doi: 10.4324/9781315775302-42

CrossRef Full Text | Google Scholar

Logsdon R. A., Chaubey I. (2013). A quantitative approach to evaluating ecosystem services. Ecol. Model. 257, 57–65. doi: 10.1016/j.ecolmodel.2013.02.009

CrossRef Full Text | Google Scholar

Luc J., Mwamba M., Mubenga-Tshitaka J.-L., Dikgang J., Muteba Mwamba J. W., Gelo D. (2021). Munich personal rePEc archive climate variability impacts on agricultural output in East Africa climate variability impacts on agricultural output in East Africa. Available at: https://mpra.ub.uni-muenchen.de/110771/.

Google Scholar

Manoj K. J., Meena R. S., Banerjee A., Kumar S., Raj A. (2024). “Index,” in Agroforestry for Carbon and Ecosystem Management. (Elsevier) 4, 429–434. doi: 10.1016/B978-0-323-95393-1.20001-8

CrossRef Full Text | Google Scholar

Manoj K. J., Meena R. S., Banerjee A., Meena S. N. (2022). Natural Resources Conservation and Advances for Sustainability, 44th ed. Eds. Meena R. S., Banerjee A., Kumar S., and Raj A., Jhariya M. K. (Haryana: Elsevier). doi: 10.1016/C2019-0-03763-6

CrossRef Full Text | Google Scholar

Markanday A., Lliso B., Sorman A. H. (2024). Investing in nature: assessing the effects of monetary and non-Monetary valuations on decision-Making. Ecol. Economics 219, 108135. doi: 10.1016/j.ecolecon.2024.108135

CrossRef Full Text | Google Scholar

Márquez L. A. M., Rezende E. C. N., MaChado K. B., Nascimento E. L. M. d., Castro J. D. B., Nabout J. C. (2023). Trends in valuation approaches for cultural ecosystem services: A systematic literature review. Ecosyst. Serv. 64, 101572. doi: 10.1016/j.ecoser.2023.101572

CrossRef Full Text | Google Scholar

Martin D. M., Mazzotta M. (2018). Non-monetary valuation using multi-criteria decision analysis: sensitivity of additive aggregation methods to scaling and compensation assumptions. Ecosyst. Serv. 29, 13–22. doi: 10.1016/j.ecoser.2017.10.022

PubMed Abstract | CrossRef Full Text | Google Scholar

Masiga M., Mwima P., Kiguli L. (2012). Trees for Global Benefit Program: Environmental Conservation Trust (ECOTRUST) of Uganda. Available online at: https://cgspace.cgiar.org/handle/10568/21218.

Google Scholar

Masselus L., Fiala N. (2024). Whom to ask? Testing respondent effects in household surveys. J. Dev. Economics , 103265. doi: 10.1016/j.jdeveco.2024.103265

CrossRef Full Text | Google Scholar

Mawa C., Babweteera F., Tumusiime D. M. (2022). Livelihood outcomes after two decades of co-Managing a state forest in Uganda. For. Policy Economics 135, 102644. doi: 10.1016/j.forpol.2021.102644

CrossRef Full Text | Google Scholar

Mawa C., Tumusiime D. M., Babweteera F., Okwir E., Tabuti J. R. S. (2023). Community-based forest management promotes survival-led livelihood diversification among forest-fringe communities in Uganda. Front. Forests Global Change 6. doi: 10.3389/ffgc.2023.1125247

CrossRef Full Text | Google Scholar

McIntosh M. G., Zhang D. (2024). Faustmann formula and its use in forest asset valuation: A review and a suggestion. For. Policy Economics 160, 103158. doi: 10.1016/j.forpol.2024.103158

CrossRef Full Text | Google Scholar

Mekuria W., Wondie M., Amare T., Wubet A., Feyisa T., Yitaferu B. (2018). Restoration of degraded landscapes for ecosystem services in north-western Ethiopia. Heliyon 4, e007645. doi: 10.1016/j.heliyon.2018.e00764

CrossRef Full Text | Google Scholar

Mengist W., Soromessa T., Feyisa G. L. (2022). Estimating the total ecosystem services value of eastern afromontane biodiversity hotspots in response to landscape dynamics. Environ. Sustainability Indic. 14, 100178. doi: 10.1016/j.indic.2022.100178

CrossRef Full Text | Google Scholar

Mgaya E. (2021). Forest and forestry in Tanzania: changes and continuities in policies and practices from colonial times to the present. J. OF THE GEOGRAPHICAL Assoc. OF TANZANIA 36, 45–58. doi: 10.56279/jgat.v36i2.149

CrossRef Full Text | Google Scholar

Midega C. A. O., Bruce T. J. A., Pickett J. A., Pittchar J. O., Murage A., Khan Z. R. (2015). Climate-adapted companion cropping increases agricultural productivity in East Africa. Field Crops Res. 180, 118–125. doi: 10.1016/j.fcr.2015.05.022

CrossRef Full Text | Google Scholar

Miller E. F., Doolittle A. A., Cerutti P. O., Naimark J., Rufino M. C., Ashton M. S., et al. (2021). Spatial distribution and perceived drivers of provisioning service values across an East African montane forest landscape. Landscape Urban Plann. 207, 103995. doi: 10.1016/j.landurbplan.2020.103995

CrossRef Full Text | Google Scholar

Ministry of Tourism (2022). Ministry of Tourism, Wildlife and Heritage- Strategy Report for Kenya 2021-2025 (NAIROBI).

Google Scholar

Mitchell N., Schaab G. (2008). Developing a disturbance index for five East African forests using GIS to analyse historical forest use as an important driver of current land use/cover. Afr. J. Ecol. 46, 572–584. doi: 10.1111/j.1365-2028.2007.00901.x

CrossRef Full Text | Google Scholar

Mombo F., Lusambo L., Speelman S., Buysse J., Munishi P., Huylenbroeck G. v. (2014). Scope for introducing payments for ecosystem services as a strategy to reduce deforestation in the kilombero wetlands catchment area. For. Policy Economics 38, 81–89. doi: 10.1016/j.forpol.2013.04.004

CrossRef Full Text | Google Scholar

Mooney H. A., Cropper A., Reid W. (2004). The millennium ecosystem assessment: what is it all about? Trends Ecol. Evol. 19, 221–245. doi: 10.1016/j.tree.2004.03.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Mukherjee N., Sutherland W. J., Dicks L., Hugé J., Koedam N., Dahdouh-Guebas F. (2014). Ecosystem service valuations of mangrove ecosystems to inform decision making and future valuation exercises. PloS One 9, e1077065. doi: 10.1371/journal.pone.0107706

CrossRef Full Text | Google Scholar

Müller D., Mburu J. (2009). Forecasting hotspots of forest clearing in Kakamega forest, Western Kenya. For. Ecol. Manage. 257, 968–775. doi: 10.1016/j.foreco.2008.10.032

CrossRef Full Text | Google Scholar

Mulwa R., Kabubo-Mariara J., Nyangena W. (2018). Recreational value and optimal pricing of national parks: lessons from Maasai Mara in Kenya. J. Environ. Economics Policy 7, 204–225. doi: 10.1080/21606544.2017.1391716

CrossRef Full Text | Google Scholar

Mutoko M. C., Hein L., Shisanya C. A. (2015). Tropical forest conservation versus conversion trade-offs: insights from analysis of ecosystem services provided by Kakamega rainforest in Kenya. Ecosyst. Serv. 14, 1–11. doi: 10.1016/j.ecoser.2015.03.003

CrossRef Full Text | Google Scholar

Mwakaje A. G., Manyasa E., Wawire N., Muchai M., Ongare D., Mugoya C., et al. (2013). Community-based conservation, income governance, and poverty alleviation in Tanzania: the case of serengeti ecosystem. J. Environ. Dev. 22, 51–735. doi: 10.1177/1070496512471949

CrossRef Full Text | Google Scholar

Næsset E., McRoberts R. E., Pekkarinen A., Saatchi S., Santoro M., Trier Ø. D., et al. (2020). Use of local and global maps of forest canopy height and aboveground biomass to enhance local estimates of biomass in miombo woodlands in Tanzania. Int. J. Appl. Earth Observation Geoinformation 89, 102109. doi: 10.1016/j.jag.2020.102109

CrossRef Full Text | Google Scholar

Naidoo G. (2023). The mangroves of Africa: A review. Mar. pollut. Bull. 190, 114859. doi: 10.1016/j.marpolbul.2023.114859

PubMed Abstract | CrossRef Full Text | Google Scholar

Negese A. (2024). Critical oversights of remote sensing-based RUSLE cover and management (C) factor estimation in Ethiopia: A review. Remote Sens. Applications: Soc. Environ. 33, 101089. doi: 10.1016/j.rsase.2023.101089

CrossRef Full Text | Google Scholar

Ngaruiya G. W. (2015). Reweaving stakeholder networks: promoting climate mitigation and maasai culture using medicinal plants in Kenya. Ecosyst. Serv. 15, 103–112. doi: 10.1016/j.ecoser.2015.05.010

CrossRef Full Text | Google Scholar

Njana M. A. (2020). Structure, growth, and sustainability of mangrove forests of mainland Tanzania. Global Ecol. Conserv. 24, e01394. doi: 10.1016/j.gecco.2020.e01394

CrossRef Full Text | Google Scholar

Norton A. (1996). Experiencing nature: the reproduction of environmental discourse through safari tourism in East Africa. Geoforum 27, 355–373. doi: 10.1016/S0016-7185(96)00021-8

CrossRef Full Text | Google Scholar

Notte A. L., D’Amato D., Mäkinen H., Paracchini M. L., Liquete C., Egoh B., et al. (2017). Ecosystem services classification: A systems ecology perspective of the cascade framework. Ecol. Indic. 74, 392–402. doi: 10.1016/j.ecolind.2016.11.030

PubMed Abstract | CrossRef Full Text | Google Scholar

Ntibona L. N., Shalli M. S., Mangora M. M. (2022). Incentives and disincentives of mangrove conservation on local livelihoods in the RuFiji Delta, Tanzania. Trees Forests People 10, 100326. doi: 10.1016/j.tfp.2022.100326

CrossRef Full Text | Google Scholar

Ntiyakunze M. S., Stage J. (2022). Forest dependence in Tanzania: analysis of the determinants of perceived forest dependence. Trees Forests People 8, 100277. doi: 10.1016/j.tfp.2022.100277

CrossRef Full Text | Google Scholar

Nyangoko B. P., Berg H., Mangora M. M., Shalli M. S., Gullström M. (2022). Local perceptions of changes in mangrove ecosystem services and their implications for livelihoods and management in the RuFiji Delta, Tanzania. Ocean Coast. Manage. 219, 106065. doi: 10.1016/j.ocecoaman.2022.106065

CrossRef Full Text | Google Scholar

Nyongesa J. M., Bett H. K., Lagat J. K., Ayuya O. I. (2016). Estimating farmers’ Stated willingness to accept pay for ecosystem services: case of lake naivasha watershed payment for ecosystem services scheme-Kenya. Ecol. Processes 5, 15. doi: 10.1186/s13717-016-0059-z

CrossRef Full Text | Google Scholar

Nyongesa K. W., Pucher C., Poletti C., Vacik H. (2023). Evaluation of the relationship between spatio-Temporal variability of vegetation condition index (VCI), fire occurrence and burnt area in Mount Kenya forest reserve and national park. Fire 6, 2825. doi: 10.3390/fire6080282

CrossRef Full Text | Google Scholar

O’Halloran R. M. (2016). BOOK REVIEW. Ann. Tourism Res. 60, 177–178. doi: 10.1016/j.annals.2016.05.006

CrossRef Full Text | Google Scholar

Obua J., Agea J. G., Ogwal J. J. (2010). Status of forests in Uganda. Afr. J. Ecol. 48, 853–595. doi: 10.1111/j.1365-2028.2010.01217.x

CrossRef Full Text | Google Scholar

Oduor A. M. O. (2020). Livelihood impacts and governance processes of community-based wildlife conservation in Maasai Mara ecosystem, Kenya. J. Environ. Manage. 260, 110133. doi: 10.1016/j.jenvman.2020.110133

PubMed Abstract | CrossRef Full Text | Google Scholar

Okello M. M., Novelli M. (2014). Tourism in the East African community (EAC): challenges, opportunities, and ways forward. Tourism Hospitality Res. 14 (2), 53–66. doi: 10.1177/1467358414529580

CrossRef Full Text | Google Scholar

Omeja P. A., Chapman C. A., Obua J., Lwanga J. S., Jacob A. L., Wanyama F., et al. (2011). Intensive tree planting facilitates tropical forest biodiversity and biomass accumulation in Kibale National Park, Uganda. For. Ecol. Manage. 261, 703–795. doi: 10.1016/j.foreco.2010.11.029

CrossRef Full Text | Google Scholar

Osewe I., Hălălişan A.-F., Talpă N., Popa B. (2023a). Critical analysis of payments for ecosystem services: case studies in Kenya, Uganda and Tanzania. Forests 14, 12095. doi: 10.3390/f14061209

CrossRef Full Text | Google Scholar

Osewe E. O., Niţă M. D., Abrudan I. V. (2022). Assessing the fragmentation, canopy loss and spatial distribution of forest cover in Kakamega National Forest Reserve, Western Kenya. Forests 13. doi: 10.3390/f13122127

CrossRef Full Text | Google Scholar

Osewe I., Osewe E. O., Popa B. (2023b). “Interconnection between ecosystem services and local communities: knowledge gap identification in the area of kakamega forest,” in Bulletin of the Transilvania University of Brasov. Series II: Forestry • Wood Industry • Agricultural Food Engineering, 37–68. doi: 10.31926/but.fwiafe.2023.16.65.2.3

CrossRef Full Text | Google Scholar

Ototo G., Vlosky R. P. (2018). Overview of the forest sector in Kenya. For. Prod. J. 68, 6–145. doi: 10.13073/0015-7473.68.1.4

CrossRef Full Text | Google Scholar

Ouko C., Mulwa R., Kibugi R., Owuor M., Zaehringer J., Oguge N. (2018). Community perceptions of ecosystem services and the management of mt. Marsabit forest in northern Kenya. Environments 5, 1215. doi: 10.3390/environments5110121

CrossRef Full Text | Google Scholar

Parrotta J. A., Wildburger C., Mansourian S. (2012). Understanding Relationships between Biodiversity, Carbon, Forests and People: The Key to Achieving REDD+ Objectives. A Global Assessment Report Prepared by the Global Forest Expert Panel on Biodiversity, Forest Management and REDD+. IUFRO World Series.

Google Scholar

Popielak P., Majchrzak-Kucęba I., Wawrzyńczak D. (2024). Climate change mitigation with CCUS - A case study with benchmarking for selected countries in adapting the European Union’s green deal. Int. J. Greenhouse Gas Control 132, 104057. doi: 10.1016/j.ijggc.2023.104057

CrossRef Full Text | Google Scholar

Quijas S., Balvanera P. (2013). “Biodiversity and ecosystem services,” in Encyclopedia of Biodiversity: Second Edition (Elsevier Inc), 341–356. doi: 10.1016/B978-0-12-384719-5.00349-X

CrossRef Full Text | Google Scholar

Rahman M., Islam M., Islam R., Sobuj N. A. (2017). Towards sustainability of tropical forests: implications for enhanced carbon stock and climate change mitigation. J. For. Environ. Sci. 33, 281–945. doi: 10.7747/JFES.2017.33.4.281

CrossRef Full Text | Google Scholar

Rajpar M. N. (2018). “Tropical forests are an ideal habitat for wide array of wildlife species,” in Tropical Forests - New Edition. doi: 10.5772/INTECHOPEN.73315

CrossRef Full Text | Google Scholar

Ramdas M., Mohamed B. (2014). Impacts of tourism on environmental attributes, environmental literacy and willingness to pay: A conceptual and theoretical review. Proc. - Soc. Behav. Sci. 144, 378–391. doi: 10.1016/j.sbspro.2014.07.307

CrossRef Full Text | Google Scholar

Reid W. V., Mooney H. A. (2016). The millennium ecosystem assessment: testing the limits of interdisciplinary and multi-scale science. Curr. Opin. Environ. Sustainability 19, 40–46. doi: 10.1016/j.cosust.2015.11.009

CrossRef Full Text | Google Scholar

Rizos V., Egenhofer C., Elkerbout M. (2019). Circular economy for climate neutrality: setting the priorities for the EU. CEPS Policy Brief, 2019, 1–11. Available at: www.ceps.eu.

Google Scholar

Rodríguez-Veiga P., Wheeler J., Louis V., Tansey K., Balzter H. (2017). Quantifying forest biomass carbon stocks from space. Curr. Forestry Rep. 3, 1–18. doi: 10.1007/s40725-017-0052-5

CrossRef Full Text | Google Scholar

Roger F., Godhe A., Gamfeldt L. (2012). Genetic diversity and ecosystem functioning in the face of multiple stressors. PloS One 7, e450075. doi: 10.1371/journal.pone.0045007

CrossRef Full Text | Google Scholar

Roy H.-Y., Potschin M. (2018). Common International Classification of Ecosystem Services (CICES) V5.1 Guidance on the Application of the Revised Structure. Available online at: www.cices.eu.

Google Scholar

Salami A., Kamara A. B., Brixiova Z. (2010). Smallholder Agriculture in East Africa: Trends, Constraints and Opportunities. Available online at: www.afdb.org/.

Google Scholar

Samal R., Dash M. (2023). Ecotourism, biodiversity conservation and livelihoods: understanding the convergence and divergence. Int. J. Geoheritage Parks 11, 1–205. doi: 10.1016/j.ijgeop.2022.11.001

CrossRef Full Text | Google Scholar

Sangha K. K., Gordon I. J., Costanza R. (2023). Editorial: ecosystem services, policy, and human well-being. Front. Ecol. Evol. 11. doi: 10.3389/fevo.2023.1174160

CrossRef Full Text | Google Scholar

Scharlemann J. P. W., Kapos V., Campbell A., Lysenko I., Burgess N. D., Hansen M. C., et al. (2010). Securing tropical forest carbon: the contribution of protected areas to REDD. Oryx 44, 352–357. doi: 10.1017/S0030605310000542

CrossRef Full Text | Google Scholar

Sharma A., Patel S. K., Singh R., Tiwari A. K., Singh G. S. (2023). Valuation of provisioning ecosystem services and household dependency for livelihood: empirical evidence from a tropical dry forest, India. doi: 10.21203/rs.3.rs-2515857/v1

CrossRef Full Text | Google Scholar

Sharpe L. M., Harwell M. C., Phifer C., Gardner G., Newcomer-Johnson T. (2023). The final ecosystem goods and services voltron: the power of tools together. Front. Ecol. Evol. 11. doi: 10.3389/fevo.2023.1290662

CrossRef Full Text | Google Scholar

Siddi M. (2020). “The european green deal: assessing its current state and future implementation,” in FIIA Working Paper, 114.

Google Scholar

Snyder K. A., Sulle E. B. (2011). Tourism in maasai communities: A chance to improve livelihoods? J. Sustain. Tourism 19, 935–515. doi: 10.1080/09669582.2011.579617

CrossRef Full Text | Google Scholar

Solomon N., Segnon A. C., Birhane E. (2019). Ecosystem service values changes in response to land-use/land-cover dynamics in dry afromontane forest in Northern Ethiopia. Int. J. Environ. Res. Public Health 16. doi: 10.3390/ijerph16234653

PubMed Abstract | CrossRef Full Text | Google Scholar

Sourokou R., Vodouhe F. G., Tovignan S., Yabi J. A. (2023). Economic valuation of forest degradation through direct users’ Willingness to pay in Benin (West Africa). Trees Forests People 14, 100459. doi: 10.1016/j.tfp.2023.100459

CrossRef Full Text | Google Scholar

Stenger A., Harou P., Navrud S. (2009). Valuing environmental goods and services derived from the forests. J. For. Economics 15, 1–14. doi: 10.1016/j.jfe.2008.03.001

CrossRef Full Text | Google Scholar

Strauch A. M., Rurai M. T., Almedom A. M. (2016). Influence of forest management systems on natural resource use and provision of ecosystem services in Tanzania. J. Environ. Manage. 180, 35–44. doi: 10.1016/j.jenvman.2016.05.004

PubMed Abstract | CrossRef Full Text | Google Scholar

Sulaiman C., Abdul-Rahim A. S., Mohd-Shahwahid H. O., Chin L. (2017). Wood fuel consumption, institutional quality, and forest degradation in Sub-Saharan Africa: evidence from a dynamic panel framework. Ecol. Indic. 74, 414–419. doi: 10.1016/j.ecolind.2016.11.045

CrossRef Full Text | Google Scholar

Swallow B. M., Sang J. K., Nyabenge M., Bundotich D. K., Duraiappah A. K., Yatich T. B. (2009). Tradeoffs, synergies and traps among ecosystem services in the Lake Victoria Basin of East Africa. Environ. Sci. Policy 12, 504–195. doi: 10.1016/j.envsci.2008.11.003

CrossRef Full Text | Google Scholar

Tambo E., Zhang C.-S., Tazemda G. B., Fankep B., Tappa N. T., Bkamko C. F.B., et al. (2023). Triple-crises-induced food insecurity: systematic understanding and resilience building approaches in Africa. Sci. One Health 2, 100044. doi: 10.1016/j.soh.2023.100044

CrossRef Full Text | Google Scholar

Tamire C., Elias E., Argaw M. (2023). A systematic review of ecosystem services assessments, trends, and challenges in Ethiopia. Watershed Ecol. Environ. 5, 38–45. doi: 10.1016/j.wsee.2022.12.002

CrossRef Full Text | Google Scholar

Tang L., Shao G. (2015). Drone remote sensing for forestry research and practices. J. Forestry Res. 26, 791–975. doi: 10.1007/s11676-015-0088-y

CrossRef Full Text | Google Scholar

Tebkew M., Atinkut H. B. (2022). Impact of forest decentralization on sustainable forest management and livelihoods in East Africa. Trees Forests People 10, 100346. doi: 10.1016/j.tfp.2022.100346

CrossRef Full Text | Google Scholar

Tekalign M., Flasse C., Frankl A., Rompaey A. V., Poesen J., Nyssen J., et al. (2018). Forest cover loss and recovery in an east African remnant forest area: understanding its context and drivers for conservation and sustainable ecosystem service provision. Appl. Geogr. 98, 133–142. doi: 10.1016/j.apgeog.2018.07.014

CrossRef Full Text | Google Scholar

Thangata P. H., Hildebrand P. E. (2012). Carbon stock and sequestration potential of agroforestry systems in smallholder agroecosystems of Sub-Saharan Africa: mechanisms for ‘Reducing emissions from deforestation and forest degradation’ (REDD+). Agriculture Ecosyst. Environ. 158, 172–183. doi: 10.1016/j.agee.2012.06.007

CrossRef Full Text | Google Scholar

Theuerkauff D., Rivera-Ingraham G. A., Mercky Y., Lejeune M., Lignot J.-H., Sucré E. (2018). Effects of domestic effluent discharges on mangrove crab physiology: integrated energetic, osmoregulatory and redox balances of a key engineer species. Aquat. Toxicol. 196, 90–103. doi: 10.1016/j.aquatox.2018.01.003

PubMed Abstract | CrossRef Full Text | Google Scholar

Tisdell C. (2014). Ecosystems functions and genetic diversity: TEEB raises challenges for the economics discipline. Economic Anal. Policy 44, 14–20. doi: 10.1016/j.eap.2014.02.004

CrossRef Full Text | Google Scholar

Tittonell P., Muriuki A., Shepherd K. D., Mugendi D., Kaizzi K. C., Okeyo J., et al. (2010). The diversity of rural livelihoods and their influence on soil fertility in agricultural systems of East Africa – A typology of smallholder farms. Agric. Syst. 103, 83–97. doi: 10.1016/j.agsy.2009.10.001

CrossRef Full Text | Google Scholar

Tompkins A. M., Caporaso L., Biondi R., Bell J. P. (2015). A generalized deforestation and land-use change scenario generator for use in climate modelling studies. PloS One 10, e01361545. doi: 10.1371/journal.pone.0136154

CrossRef Full Text | Google Scholar

Tourism Research Institute (TRI). (2023). REPUBLIC OF KENYA REPUBLIC OF KENYA Ministry of Tourism, Wildlife & Heritage. Available online at: www.tri.go.ke.

Google Scholar

Tranquilli S., Abedi-Lartey M., Abernethy K., Amsini F., ASamoah A., Balangtaa C., et al. (2014). Protected areas in tropical Africa: assessing threats and conservation activities. PloS One 9, e114154. doi: 10.1371/journal.pone.0114154

PubMed Abstract | CrossRef Full Text | Google Scholar

Vela Almeida D., Kolinjivadi V., Ferrando T., Roy B., Herrera H., Gonçalves M. V., et al. (2023). The ‘Greening’ of empire: the european green deal as the EU first agenda. Political Geogr. 105, 102925. doi: 10.1016/j.polgeo.2023.102925

CrossRef Full Text | Google Scholar

Vorster A. G., Evangelista P. H., Stovall A. E. L., Ex S. (2020). Variability and uncertainty in forest biomass estimates from the tree to landscape scale: the role of allometric equations. Carbon Balance Manage. 15, 1–205. doi: 10.1186/s13021-020-00143-6

CrossRef Full Text | Google Scholar

Wackernagel M., Rees W. E. (1997). Perceptual and structural barriers to investing in natural capital: economics from an ecological footprint perspective. Ecol. Economics 20, 3–245. doi: 10.1016/S0921-8009(96)00077-8

CrossRef Full Text | Google Scholar

Waithaka M., Nelson G. C., Thomas T. S., Kyotalimye M. (2013). East African Agriculture and Climate Change: A Comprehensive Analysis. (Washington DC: International Food Policy Research Institute). Available at: www.ifpri.org.

Google Scholar

Wale E., Nkoana M. A., Mkuna E. (2022). Climate change-induced livelihood adaptive strategies and perceptions of forest-dependent communities: the case of Inanda, KwaZulu-Natal, South Africa. Trees Forests People 8, 100250. doi: 10.1016/j.tfp.2022.100250

CrossRef Full Text | Google Scholar

Wangai P. W., Burkhard B., Kruse M., Müller F. (2017). Contributing to the cultural ecosystem services and human wellbeing debate: A case study application on indicators and linkages. Landscape Online 50, 1–275. doi: 10.3097/LO.201750

CrossRef Full Text | Google Scholar

Wangai P. W., Burkhard B., Müller F. (2016). A review of studies on ecosystem services in Africa. Int. J. Sustain. Built Environ. doi: 10.1016/j.ijsbe.2016.08.005

CrossRef Full Text | Google Scholar

Waruingi E., Mbeche R., Ateka J. (2021). Determinants of forest dependent household’s participation in payment for ecosystem services: evidence from plantation establishment livelihood improvement scheme (PELIS) in Kenya. Global Ecol. Conserv. 26, e01514. doi: 10.1016/j.gecco.2021.e01514

CrossRef Full Text | Google Scholar

Whitham C. E.L., Shi K., Riordan P. (2015). Ecosystem service valuation assessments for protected area management: A case study comparing methods using different land cover classification and valuation approaches. PloS One 10, e01297485. doi: 10.1371/journal.pone.0129748

CrossRef Full Text | Google Scholar

Winowiecki L., Vågen T. G., Massawe B., Jelinski N. A., Lyamchai C., Sayula G., et al. (2016). Landscape-scale variability of soil health indicators: effects of cultivation on soil organic carbon in the Usambara Mountains of Tanzania. Nutrient Cycling Agroecosystems 105, 263–745. doi: 10.1007/s10705-015-9750-1

CrossRef Full Text | Google Scholar

Xepapadeas A. (2011). The economics of ecosystems and biodiversity: ecological and economic foundations, edited by Pushpam Kumar 2010, London and Washington: Earthscan, ISBN 978-1-84971-212-5 (HB) price £49.99 [Earthscan have offered a 20% Discount off the book for EDE reade. Environ. Dev. Economics 16, 239–242. doi: 10.1017/s1355770x11000088

CrossRef Full Text | Google Scholar

Yeung A. W. K. (2023). A revisit to the specification of sub-datasets and corresponding coverage timespans when using web of science core collection. Heliyon 9, e21527. doi: 10.1016/j.heliyon.2023.e21527

PubMed Abstract | CrossRef Full Text | Google Scholar

Yigezu G., Mandefro B., Mengesha Y., Yewhalaw D., Beyene A., Ahmednur M., et al. (2018). Habitat suitability modelling for predicting potential habitats of freshwater snail intermediate hosts in Omo-Gibe River Basin, Southwest Ethiopia. Ecol. Inf. 45, 70–80. doi: 10.1016/j.ecoinf.2018.04.002

CrossRef Full Text | Google Scholar

Zeng Y., Zhong L., Yu H., Deng J., Wang L.-e. (2023). Impact of protected area management on local communities: A perspective of recreational ecosystem services. Environ. Dev. 45, 100804. doi: 10.1016/j.envdev.2023.100804

CrossRef Full Text | Google Scholar

Zeppel H. (2007). “Indigenous ecotourism: conservation and resource rights,” in Critical Issues in Ecotourism (New Zealand: Elsevier), 308–348. doi: 10.1016/B978-0-7506-6878-1.50020-7

CrossRef Full Text | Google Scholar

Keywords: ecosystem services, valuation methods, forest ecosystem benefits, livelihoods, biodiversity, community benefits, East Africa

Citation: Osewe EO, Popa B, Vacik H, Osewe I and Abrudan IV (2024) Review of forest ecosystem services evaluation studies in East Africa. Front. Ecol. Evol. 12:1385351. doi: 10.3389/fevo.2024.1385351

Received: 12 February 2024; Accepted: 20 June 2024;
Published: 09 July 2024.

Edited by:

Athanasios Kallimanis, Aristotle University of Thessaloniki, Greece

Reviewed by:

Manoj Kumar Jhariya, Sant Gahira Guru Vishwavidyalaya, India
Petros Ganatsas, Aristotle University of Thessaloniki, Greece

Copyright © 2024 Osewe, Popa, Vacik, Osewe and Abrudan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Erick O. Osewe, ZXJpY2sub3Nld2VAdW5pdGJ2LnJv

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