Impact of population pressure on forest resources depletion in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia

Fikru Mosisa Hunde; Adanech Asfaw Benti; Tefera Jegora Kapula

doi:10.1371/journal.pone.0324407

. 2026 Jan 5;21(1):e0324407. doi: 10.1371/journal.pone.0324407

Impact of population pressure on forest resources depletion in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia

Fikru Mosisa Hunde ^1,^*, Adanech Asfaw Benti ², Tefera Jegora Kapula ²

Editor: Dereje Oljira Donacho³

PMCID: PMC12768366 PMID: 41490348

Abstract

An increase in population density amplifies the demand for forest products, which in turn drives deforestation and the exhaustion of forest resource. The aim of the study was to assess the impact of population pressure on forest resource depletion in the Yayo Coffee Forest Biosphere Reserve, Southwest Ethiopia. A mixed-methods research design, integrating both quantitative and qualitative approaches. Data was collected from selected households, focus groups and key informant through semi-structured interview, group discussion and field observation. A systematic random sampling technique were used to collect the data. Data were analyzed quantitatively and qualitatively by SPSS and Microsoft office excels. Land-use and land-cover (LULC) changes over the past forty years were analyzed using satellite imagery to assess the impact of population growth on forest dynamics. Results indicated that the major livelihood strategies were contributed by the combination of crop production, livestock and forest product collection (36.2%) and followed by crop production and livestock (27.5%). Agricultural expansion (23.13%), overgrazing (17.9%), timber extraction (15.27%) and urbanization (14%) were the main direct drivers of forest loss. Satellite analysis revealed that forest cover declined from 120,087.2 hectares in 1982–100,772.9 hectares in 2024 an 11.6% reduction over four decades with a strong negative correlation (r = –0.998, p < 0.05) between population growth and forest area. Overall, both local practices and systemic pressures drive the conversion of forests to agricultural land in the Yayo Biosphere Reserve. This calls for district-specific interventions that engage indigenous institutions such as Shane, Xuxee, and Tuullaa in the management of coffee forests and enforcement of the law, encouraging alternative sources of energy, and ensuring that forest resources are not overexploited.

1 Introduction

Ethiopia has undergone serious demographic growth in recent decades: for instance, the national population is estimated to be about 114.96 million in 2022, with an annual growth rate of about 2.6% [1]. This demographic expansion has increased pressure on natural resources, mainly forests, for agricultural land, settlement, grazing, and fuelwood purposes [2,3]. Population growth, together with rural livelihood dependency on biomass energy, has accelerated forest conversion and degradation throughout the country [4,5]. Ethiopia’s forest cover was estimated at about 30–40% in the early 20th century, but it has declined dramatically to approximately 11–12% in recent decades [6,7]. Empirical studies have established the relationship between population growth and its corresponding percentage of agricultural expansion as the leading drivers of deforestation [8–10].

The Yayo Coffee Forest Biosphere Reserve (YCFBR), located in southwestern Ethiopia, is internationally recognized as one of the last remaining refuges of wild Coffea arabica and a vital center of Afromontane biodiversity [11,12]. Established under UNESCO’s Man and the Biosphere Programme, the reserve plays a critical role in conserving genetic resources, supporting community livelihoods, and promoting sustainable development and research [13]. However, YCFBR is facing growing socioecological pressures [14].

Land-use change and encroachment of agriculture, including smallholder farms expanding into coffee plantations and settlements, have been marked by widespread forest degradation and frequent conflicts over resource use and land rights between the communities and management authorities [15]. Coal mining explorations in the buffer zones, estimated at about 230 million tons of coal, have posed additional threats to forest integrity and Low productivity of smallholder coffee, ranging between 400 and 600 kg ha ⁻ ¹, against potential yields exceeding 1,000 kg ha ⁻ ¹, is also among the key drivers of conversion to expand cultivation areas [16].

The associated biodiversity and ecosystem service decline are evident, with highly simplified monocropping systems supporting significantly lower species diversity compared to more complex agroforestry mixtures [17]. Yayo Coffee Forest Biosphere Reserve is continuously experiencing increased deforestation, agricultural expansion, and socio-economic tensions [18]. Rapid population growth, accompanied by a decline in farm productivity due to land degradation and soil erosion, along with very limited livelihood diversification strategies, has increased local dependence on forest resources including timber, charcoal, and fuelwood [19].

Addressing these gaps is critical because YCFBR preserves the wild gene pool of Coffea arabica, vital for global coffee sustainability [20]. Understanding livelihood and forest interactions can offer guidance to how balanced management can provide basic needs to the local community, sustain biodiversity, and contribute to the wider debates on tropical forest governance and ecosystem-based livelihoods [21]. The study, therefore, intends to identify the effects caused by population pressure on forest resource depletions in the Yayo Coffee Forest Biosphere Reserve, Ilubabor Zone, Oromia Regional State, Southwest Ethiopia.

2 Methods and materials

2.1 Study area description

2.1.1. Location.

The Yayo Coffee Forest Biosphere Reserve is located in the Ilu Abba Bora Zone of the Oromia Regional State in southwestern Ethiopia. It is recognized as the center of origin for Coffea arabica, the world’s most widely consumed coffee, and Yayo is the largest and most significant forest for conserving wild coffee populations globally [22]. The reserve plays a crucial role in preserving both natural and cultural landscapes [23]. Situated in the southwestern part of the Oromia region, the Yayo Biosphere Reserve includes the Woredas of Hurumu, Yayo, Chora, Nopha, Alge Sachi, and Doreni, covering coordinates from 8°0’42“ to 8°44’23” N and 35°20’31” to 36°18’20” E [Fig. 1]. The district’s elevation ranges from 1,139.2 to 2,581.9 meters above sea level, with the lowest point located at Gaba River (1,100 meters) and the highest point at the summit of Sayi Mountain (2,581 meters) in Keresi.

2.1.2. Climate.

The area experiences a hot and humid climate, with an average annual temperature of around 23°C, ranging from a mean minimum of 18.59 ^°C to a mean maximum of 27.88 ^°C [24]. The varied physical conditions and altitudinal differences contribute to a rich diversity of climate, soil, and vegetation, fostering the development of numerous plant species with a high level of diversity [25]. The rainfall pattern of the districts varies annually from 1,191.6 to 1,960.7 mm, showing variations from year to year. It is a unimodal type of rainfall that increases from May to October and declines in November [26].

2.1.3. Ecology.

The study focuses on the Hurumu, Yayo, and Doreni districts located in the Yayo Coffee Forest Biosphere Reserve in southwestern Ethiopia, which is famous for its ecological importance and genetic diversity of wild Coffea arabica [27]. The biosphere reserve has a total surface area of 167,021 hectares and consists of three zones: a core zone (27,733 ha), a buffer zone (21,552 ha), and a transition zone (117,736 ha), balancing conservation and sustainable development [28]. Land in the study area comprises 3.5% highland (5,750.4 ha), 85% temperate zone (138,465.85 ha), and 11.47% lowland (18,684.75 ha), reflecting its heterogeneity and altitudinal gradients [29]. This diversity accounts for much of the biodiversity of the region and explains its status as a key location for environmental studies and resource management [30].

The diverse climatic conditions and habitats in these districts have contributed to a high level of species diversity in both plants and animals [31]. This biodiversity richness is one of the reasons why Ethiopia is considered one of the 20 most biodiverse countries in the world [32].

2.2 Study design

This researcher employs a mixed-methods research design, integrating both quantitative and qualitative approaches to comprehensively investigate the impacts of population dynamics on the Yayo Biosphere Reserve. The design is structured to systematically address the following objectives: assessing population growth, evaluating forest cover change, examining conservation practices, understanding community resource relationships, identifying stakeholder roles, and proposing sustainable management strategies.

2.3 Data collection tools

Following ethical approval, the study was conducted in several data collection waves between May 2024 and January 2025. The data for this study includes a sample household survey and land use/land cover change data. The research approach involves a consultative and interactive process, engaging respondents who are willing to provide essential information [33].

2.3.1. Key informant interviews (KIIs).

Key informant interviews were conducted with individuals who possessed in-depth knowledge and experience related to forest resource management and population dynamics in the area. These informants included community elders, local administrators, development agents, forestry experts. Interviews were conducted to collect data on the role of local communities in forest conservation, the impacts of human activities on the forest, and perceptions toward conservation efforts, as well as the challenges and consequences associated with these activities [34].

2.3.2. Household surveys.

Household surveys were used to collect quantitative data from a representative sample of households within the Yayo Coffee Forest Biosphere Reserve. Structured questionnaires were administered to gather information on demographic characteristics, household size, landholding, livelihood activities, fuelwood consumption, and perceptions regarding forest resource use and conservation. This tool enabled statistical analysis and comparison across different groups and areas [35].

2.3.3. Focus group discussions (FGDs).

Focus group discussions and interviews were conducted to collect primarily qualitative data. Satellite imagery was utilized to generate land use land cover change data [36]. These informants included village elders, kebele administration, development agents (DAs). Three FGDs were also organized to garner community-level perspectives regarding forest management and socio-economic issues [37]. These interviews enriched the qualitative data through the locally grounded knowledge and lived experience [38].

2.3.4. Observations.

Field observations were carried out to supplement data obtained through surveys and interviews. These observations focused on land-use patterns, forest cover conditions, agricultural expansion, and evidence of forest degradation. Observation checklists were used to ensure systematic recording of data. This method helped verify and validate information gathered from other sources and provided a practical understanding of the extent of forest resource depletion in the study area.

2.4 Target populations

The population of interest for this study comprised rural households and key stakeholders residing in and around the Yayo Coffee Forest Biosphere Reserve, specifically within the selected woredas of Yayo, Hurumu, and Doreni. During the study time, there were a total of 91,694 households; 89,039 were males and 2,659 were females, with a total population of 458,472 individuals. These communities were chosen due to their direct dependence on forest resources for their livelihoods and their proximity to the core and buffer zones of the biosphere reserve [39,40].

The sampling frame included residents from nine kebeles, three from each of the selected woredas, identified based on geographic location, accessibility, and relevance to forest conservation activities [41]. Households were selected using purposive sampling techniques to ensure the inclusion of individuals with lived experience in forest resource use and conservation [42]. Criteria such as length of residence in the area, proximity to the forest, and knowledge of local forest management practices were considered during the selection process [43].

2.5 Sampling methods and techniques

To ensure a comprehensive understanding of the study area, a combination of preliminary assessments and quantitative and qualitative surveys was employed [44]. An initial exploratory survey was conducted to gain an overview of the spatial distribution of the Yayo Coffee Forest Biosphere Reserve and to facilitate the selection of appropriate study sites [27]. From a total of 91,694 households residing in the study woredas comprising 89,039 male-headed and 2,659 female-headed households a sample of 156 households was selected for the survey. A systematic random sampling technique was employed to ensure that the selected sample was both representative and unbiased.

The Yayo Coffee Forest Biosphere Reserve, which spans six woredas of the Ilubabor and Buno Bedele zones namely Yayo, Hurumu, Chora, Bilo Nopha, Alge Sachi, and Doreni served as the general study area. For this particular study, Yayo, Hurumu, and Doreni woredas were selected as representative sites. Within these woredas, nine rural kebeles were purposively chosen based on their proximity to the forest zone and relevance to forest resource use: Haro, Gaba, and Wangegne from Hurumu woreda; Waboo, Geci, and Wixete from Yayo woreda; and Bocho, Badesa, and Henna from Doreni woreda. These kebeles were chosen on purposively since they are nearest to forest, residence in the biosphere reserve for years, and knowledge on forest resource use and conservation methods [45].

To gather quantitative information, a systematic household survey was conducted with 156 respondents from the chosen kebeles. The survey collected baseline data on household characteristics, land use, livelihood strategies, and perceptions towards forest conservation [46,47]. At the same time, qualitative information was gathered through key informant interviews and FGDs. 18 key informants, two from each kebele, were interviewed Three FGDs were made, each containing six members, one from each woreda, resulting in a total of 18 participants.

2.6 Data analysis

The quantitative data collected through household surveys were first cleaned, validated, and coded in Microsoft Excel to promote consistency and accuracy [48]. The cleaned data were then exported into IBM SPSS version 20 for analysis. Besides, tables, graphs and charts were implemented using descriptive statistics; frequencies, percentages and other statistical analyses. Descriptive statistics were used in summarizing key variables such as household characteristics, forest resource use, and conservation knowledge [49].

To analyze causal relationships linear regression and logistic regression tests were used. These methods allowed the assessment of the impact of independent variables, i.e., household size, income level, and education, on dependent variables like dependency on forest resources and conservation behavior [50]. The validity of the regression models was checked by using diagnostic tests [51].

For the qualitative data collected through key informant interviews and focus group discussions, thematic analysis was applied [52]. The data were coded, transcribed, and categorized into local perceptions, emerging themes, traditional knowledge, forest governance, and livelihood strategies. Representative statements of the participants were utilized to elaborate on these themes [53]. Through this mixed-methods approach with regression-based quantitative analysis complemented by rich qualitative feedback, there was a guaranteed holistic understanding of the drivers, effects, and community perspectives about the use and preservation of forest resources [54].

2.7. Ethical considerations

Ethical approval was granted by the Mattu University Institutional Review Board (IRB) prior to participant recruitment and data collection. The ethical clearance was issued under Reference Number 258/MaU/2024 on May 12, 2024. The purpose and procedures of the interviews were clearly explained to all study participants before obtaining their consent to participate. Verbal informed consent was obtained from all stakeholders, each of whom retained a copy of the consent form for reference. Participation was entirely voluntary, and participants were free to withdraw at any time without penalty. All collected data were securely handled and stored to ensure participant privacy, with access restricted solely to the research team.

3 Results and discussion

3.1 Socio-economic characteristics

The majority of the households, 89,039 (97.1%), were male-headed, while only 2,659 (2.9%) were female-headed. The ages of the respondents ranged from 20 to 80 years, with a mean age of 48 years. The family size varied between 1 and 12 members, with an average of 5.18, which is consistent with the national average family size. Regarding education, 15.9% of the respondents were illiterate (unable to read or write), 30.4% had attended grades 1–5, 42% had completed grades 6–12, and 11.6% had completed secondary. On income, 14.2% of the households did not have any regular earnings or financial inflow (they were dependent on others), 39.8% of the households were low-income or below median household income (<10,000–15,000 ETB/year), 35.1% middle-income or, around median (15,000–50,000 ETB/year) and only 10.8% high-income or well above median (>50,000 ETB/year) [Central Statistical Agency of Ethiopia (CSA), Household Income and Expenditure Survey, 2015/16]. In terms of household size, the largest share (55.4%) included 4–5 members, then 23.6% included 6–7 members, and 12.8% included over 7 [Table 1]. Similarly, the family’s socioeconomic status includes the household income, earners’ education and occupation, as well as combined income when their own attributes are assessed [55]. In fact, the socio-economic status can be measured in a number of different ways, and most commonly, it is measured by education, occupation, and income [56]. Family illiteracy drastically restricts economic opportunities via limited availability of well-paying employment, resulting in poverty; affects the health services; and is unlikely to possess the capacity to aid their education [57,58].

Table 1. Socio-demographic and economic characteristics of the participants among households in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024.

Variables	Category	Frequency	Percent (%)
Sex	Male	144	97.2
	Female	4	2.8
	Total	148	100.0
Age	20-30	4	2.9
	31-40	58	39.1
	41-50	34	23.2
	51-60	22	14.5
	>61	30	20.3
	Total	148	100.0
Educational status	Illiterate (no formal education)	24	15.9
	Grade 1–5	45	30.4
	Grade 6–12	62	42.0
	Diploma & above	17	11.6
	Total	148	100.0
Income level	No income	21	14.2
	Low income	59	39.8
	Middle income	52	35.1
	High income	16	10.8
	Total	148	100
Family size	≤ 3	12	8.0
	4–5	82	55.4
	6–7	35	23.6
	> 7	19	12.8
	Total	148	100.0

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3.2. Livelihood strategies

In this study, among the sample households that participated in the survey, 36.2% of respondents indicated that their income came from crop, livestock and forest product, 27.5% from crop production and livestock rearing, and 15.2% from forest product collection and off farm activities. Additionally, 10.2% reported that their income sources were from crop production only. 6.9% of respondents indicated that their income relied on livelihood activities and 4% depends on off farm activities [Fig 2]. Against the above result, 73% of forest dwellers depend on these products as a source of revenue in the Bale Zone, southern Ethiopia [59]. The value of income sources like forest products, crop production, livestock production, and off-farm activities depends on each other [60]. Research conducted in the adjacent district of Yayo, included under one National Forest Priority Area (NFPA) with Gabba-Dogi, i.e., Yayo NFPA [61], revealed that 92.6 percent of the population in the study area have coffee in the forest, from which 57.3 kg of honey on average is harvested per household per year [62].

3.3. Formal institutions in forest management

Based on the information gathered from interviews and focus group discussions, various institutions at the federal, regional, and local levels were identified, along with their interlinkages concerning the management of the coffee forest resource under investigation [63].

Changes in the institutional structure of the Ministry of Agriculture (MoA) since the early 1990s have failed to establish a dedicated government body for the management, conservation, and sustainable use of coffee forests [22]. This gap has contributed, to some extent, to the increasing lack of effective institutions for the sustainable management of coffee forests. Federal institutions, mainly under the Institution for Biodiversity Conservation (IBC), provide technical support for Yayo Coffee Forest Biosphere Reserve conservation [64].

At the regional level, two institutions with potential connections to the coffee forest are examined: the Oromia Forest and Wildlife Enterprise Supervising Agency and the regional agriculture and rural development bureaus established in 1999 under proclamation 90/1999 as parts of decentralization [55]. The primary issues identified within these organizations include a lack of technical and direct focus on forest coffee biodiversity conservation, insufficient budget and technical personnel at the agricultural and rural development bureaus, inadequate decentralization of the budget, and limited community involvement in planning and execution at the Forest Enterprise Supervising Agency [65]. Another gap noted in the State Forest Enterprise is the absence of incentives to motivate local communities to conserve specific forests [66]. The study confirms that local indigenous institutions have been gradually marginalized due to the increasing control of the state, which enforced formal institutions under various regimes in the past [67].

At the local level, the institutions involved in the use, conservation, and management of the coffee forest include the Yayo Coffee Forest Biosphere Reserve Conservation Project, the district administration (comprising the kebele and development team), and the district [68].

3.4. Informal institutions contributing for forest management

The study examines various informal institutions in terms of their structure and role in the livelihoods of the community in the study area. These institutions are categorized into four groups, with particular emphasis placed on two clusters [69,70]. The territorial-based administrative indigenous/customary institutions are further divided into four groups: Tuullaa, Xuxee, Shane, and Jaarsa Biyya, along with Muchoo. The study conducted by Tulu and Getahun revealed the same result with current study. The first cluster consists of territorial-based administrative indigenous/customary institutions, while the second includes a variety of self-help work organizations [70].

Shane, Xuxee, and Tuullaa make two important contributions to the management of coffee forests. A fundamental role in bringing local governance systems into alignment is played by Tuullaa, which organizes, leads, and enforces the work, norms, and regulations of various local customary institutions and self-help labor associations. By controlling coffee harvesting and enforcing customary regulations to stop overexploitation and resource degradation, for example, these organizations manage coffee forests both directly and indirectly [69]. This finding aligns with the broader literature on common-pool resource management, which emphasizes that strong social norms, particularly those founded on reciprocity and generalized trust, are instrumental for the sustainable management and conservation of collective natural resources. The result highlights the central role of Tuullaa as a culturally grounded institution that governs not only the social and economic existence of the community in the coffee forest zone but also exercises a significant influence over governing the environment [71].

The ability to govern conduct among community members and facilitate the crafting and enforcement of local rules situates it as a significant mechanism for maintaining collective action for sustainable forest use. This is in harmony with common-pool resource governance theory, which praises the effectiveness of locally crafted institutions in shared ecosystem management [71,72].

Jaarsa Biyya and Muchoo, as customary Oromo institutions, play a crucial role in the sustainable management of the coffee forest and other natural resources by being local enforcers of customary law and mediators in resource disputes. Their authority, which has its foundation in respect by the community, allows them to enforce existing rules and, if supported by the locals, create, and implement new rules. This aligns with the contention that locally embedded institutions are more effective and legitimate in the governance of resources than externally introduced formal institutions [72]. Similarly, it contends for the importance of facilitating resource users to participate in rule-making, a function these institutions are strategically positioned to undertake [73]. This is also supported by who adds that local self-help associations among the Oromo have traditionally worked to improve food security and economic resilience [74,75]. Interpreted through the theory of institutional bricolage, Jaarsa Biyya and Muchoo demonstrate how traditional authority can be reshaped to contemporary challenges, blending cultural practice with evolving governance imperatives for promoting sustainability [76].

3.5. Conservation policies and its drawbacks

As indicated by various informants in the coffee forest study area, different forms of ownership rights existed prior to the demarcation process. The publicly owned and strictly conserved portion of 50,000 hectares of the Yayo Coffee Forest Biosphere Reserve is the most significant. The remaining 117,000 hectares fall under a mix of community, cooperative, and private regimes, which work to strengthen traditional forest coffee production. Such sites support over 150,000 people, with 40–50% of the reserve in mixed regimes [77]. Federal Forest Development, Conservation, and Utilization Proclamation no. (5, 6) has a sure implication for natural resource management, even though in the practical implementation they have faced their own limitation [78].

3.6. The contributions of the biosphere reserve to the local communities

In this study, the collection of forest products was identified as the primary source of household income. Approximately 43.9% of respondents stated that they are highly dependent on forest products to support their households. Additionally, 37.8% of the households surveyed indicated that collecting forest products is their top priority for sustaining their livelihoods, While 16.2% of the respondents said forest product collections are serving my household as a second income source, and 12.8% of them have ranked forest products as the third option for their livelihood [Table 2]. This finding is similar with many studies conducted in different areas in Ethiopia [79]. For instance, in the Yayo district, the same study area, in the Sheka zone, and in the Bale Mountains, forest products were revealed as the primary source of income, with contributions of 54%, 49%, and 44.7%, followed by crop production [80]. In contrast, other studies have indicated that forest products contribute as the fourth most important source of livelihood for households. For instance, at Liban Woreda, Borena, southern Ethiopia (32%), and at Gore District, southwest Ethiopia, similar agro-ecology (23%) [81].

Table 2. Forest products priority to support the household’s livelihood among study participants in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024.

Preference category	No. of respondents	Percentage (%)	Rank
General dependency on forest products	65	43.9%	1
Forest products as 1st priority	36	37.8%	2
Forest products as 2nd priority	24	16.2%	3
Forest products as 3rd priority	19	12.8%	4
Not engaged in forest products	4	2.7%	5
Total	148	100.0%

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3.7. The major factors of forest depletion

The analysis of the household survey results highlighted several factors contributing to the depletion of forest stocks in the Yayo Coffee Forest Biosphere Reserve. Among the households surveyed, approximately 23.13% of respondents identified agricultural expansion as a major factor in the depletion of forest resources due to the local population’s reliance on primary activities such as wood logging, non-timber forest product collection, and farming. The findings in the Yayo Coffee Forest Biosphere Reserve from the survey identify three major causes of forest degradation: lack of indigenous community participation (21.95%), Timber extraction (15.27%) and Urbanization (14%). The Yayo Fertilizer Factory, which has removed about 115 hectares of forestland from the buffer zone of Yayo Biosphere Reserve, is a poor example of industrial investment, which 12.2% of respondents cited as one of the primary causes of forest degradation. This is consistent with research showing that industrial operations significantly speed up deforestation and pose serious risks to biodiversity [Fig 3]. These are strongly supported by findings in some well-accredited studies in comparable environmental and socio-economic contexts. For instance, it is projected that urban expansion would account for the conversion of over 2.5 million hectares of forests globally by 2030, primarily in developing nations, as a testament to the impact of urban spread on forest degradation [82].

The respondents’ high agreement with the statement that “the lack of indigenous involvement results in forest depletion” indicates that 73.9% of respondents strongly agree with this statement, which has been confirmed [83]. Similarly, the 75.7% who identified timber extraction as a major cause aligns with previous studies and reports, which rank unsustainable and illegal logging among the leading drivers of forest loss [84,85].

These trends emphasize the pressing need for more stringent environmental regulation and more environmentally friendly development practices. Moreover, the residents reported that the Yayo Fertilizer Factory displaced a high number of farmers from their farms, and they resorted to daily work as a source of survival [84,86]. The research revealed that approximately 2,200 farming families were physically displaced, losing their farms, houses, and wild coffee farms as sources of livelihood to accommodate the factory’s production [87].

Additionally, the crew saw firsthand how more than 26 low-income families depended on daily wage labor to make ends meet. The Community Forest Coffee Project’s (COFCOP) arrival was considered noteworthy in this context because it provided some alternative livelihood support [88].

The coal mining initiative, launched in 2010, aimed to generate employment for thousands of jobless locals in the region. Between 2012 and 2013, over 6,000 skilled and unskilled workers were hired by the Yayo Fertilizer Factory, with most resettled in heavily forested villages such as Achebo and Wutete. However, starting in 2018, coal mining at the Achebo site came under the control of organized youth from displaced families. As a result of the project’s strict security measures, hundreds of villagers were physically displaced and denied access to their coffee farms, forest lands, and water sources. While compensation was provided, it was limited to losses of seasonal crops (like maize, sorghum, and barley), perennial crops (such as mango, pawpaw, and oranges), garden trees, and village homes and structures. The study also revealed that compensation was calculated for only 420 of the 2,200 displaced individuals. For example, compensation for a coffee stand was estimated at just 6.50 birr, and for one hectare of farmland, it was only 400 birr [88].

Other study results indicated a lack of economic opportunities and social amenities in rural areas; rural-urban migration has resulted in a considerable population increase in many sub-Saharan African cities [89].

3.8. Population growth and forest cover change

According to the statistical findings from the household survey, the main drivers of this activity were identified as farmland expansion (40.5%), forest product collection (29.6%), settlement (12%), and overgrazing (17.9%), with these factors emerging as the most significant contributors. Ethiopia continues to have one of the highest population growth rates in sub-Saharan Africa, 2.5% to 3% annually, which adds pressure to land and other natural resources [90]. Over the past few decades, the region has been a big hub for migrants, with both rising numbers and rising ethnic diversity. Other groups who settled in the area include people from the Southern Nations, Nationalities, and Peoples’ Region (SNNPR), Amhara, Tigray, and eastern Oromia [91]. Such movements relate to broader national patterns of domestic migration, often predicated on voluntary migration as well as government-sponsored resettlement programs aimed toward relatively sparsely populated forest zones [92]. Household survey reports that forest product collection, mainly firewood and forest coffee, as a leading cause of forest degradation. Hurumu Woreda informants report widespread overexploitation of tree species like Cordia africana for illegal timber [Fig 4]. This aligns with general trends in Ethiopia and sub-Saharan Africa, where wood fuel and timber overextraction drive deforestation [93]. Cordia africana, of economic value for timber and shade, is most susceptible, threatening biodiversity and agroforestry. Despite its importance for livelihood, forest product collection accelerates degradation, particularly when combined with agricultural encroachment and settlement [90].

Farmland expansion, identified by 35.8% of respondents, is a leading cause of forest degradation in the area, while settlement activities contribute to 18.9% of the degradation [Table 3]. Overgrazing, however, is not as prominent since it entails the use of certain grazing fields (kaloo) that are different from forests. Similar findings in the Ethiopian highlands show that spatial land-use management, like exclosures, can avert degradation [94,95]. In contrast, regions lacking these management systems, such as Afar and Borana, are facing severe soil degradation and loss of biodiversity, largely driven by uncontrolled overgrazing and the absence of sustainable land-use practices [96,97].

Table 3. Satellite images results of land use land cover in the Yayo coffee forest Biosphere reserve from 1984 to 2024 (S1 Fig).

Districts	Land use land cover	1984		2004		2024
Districts	Land use land cover	Area (Ha)	%	Area (Ha)	%	Area (Ha)	%
Doreni	Forest	29030.1	63.1	25395.59	55.2	24889.52	54.1
	Agriculture & Settlement	16976.4	36.9	20610.91	44.8	21116.98	45.9
	Total	46006.5	100	46006.5	100	46006.5	100
Hurumu	Forest	30848.4	66.3	29638.65	63.7	24241.35	52.1
	Agriculture & Settlement	15680.1	33.7	16889.85	36.3	22287.15	47.9
	Total	46528.5	100	46528.5	100	46528.5	100
Yayo	Forest	60208.67	74.5	57703.34	71.4	51642.06	63.9
	Agriculture & Settlement	20608.34	25.5	23113.66	28.6	29174.94	36.1
	Total	80817	100	80817	100	80817	100
Grand total Forest land		120087.17	69.3	112737.58	65	100772.93	58.1

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3.9. Demographic trends from 1984 to 2024 and forest cover change satellite image result

Population data for the past 40 years were obtained from the Central Statistical Agency (CSA), Jimma Branch, based on the Ethiopian Population Censuses conducted in 1984 and 1994, as well as projections from the 2007 census. According to the census data, the population of Ilubabor Zone was over 847,048 in 1984, over 970,243 in 1994, 1,271,609 in 2007 and 2,301,242 in 2024.The population of Yayo district increased from 29,837 in 1984–52,851 in 1994, then to 83,579 in 2007, and further to 139,001 by 2024. Similarly, the population of Hurumu district was 27,586 in 1984, rising to 42,667 in 1994, 106,294 in 2007, and 165,143 by 2024. In Dorani district, the population was 20,015 in 1984, increased to 36,705 in 1994, reached 58,938 in 2007, and grew to 97,491 by 2024 [Fig 5]. The forest cover change in Yayo Biosphere Reserve over the past 40 years (from 1984 to 2024) is presented as a satellite image comparison. Landsat 5 TM for 1984, Landsat 5 TM and ETM for 1994, and Landsat 7 TM and ETM+ for 2024, each with a 30-meter resolution satellite image cover, showed Forest coverage decreased from 120087.2 hectares to 100772.9 hectares, or by 11.6%, over the 40-year period [Table 3]. Forest coverage is replaced by agricultural land, and settlement land is the dominant land use type in the study area, which is divided into three compartments: core, buffer, and transitional zones, within the Yayo Biosphere Reserve, and LANDSAT/TM satellite images from 1986 to 1990 show that Ethiopia’s forest cover had since then been reduced to 3.93%, or 45,055 sq km [98].

The Yayo Coffee Forest Biosphere Reserve is a significant ecological location that sequesters carbon and mitigates climate change, which makes it both a national and global priority [99]. Agroforestry systems in the region, particularly those for coffee grown under shade, are a sustainable land use practice that conserves the environment and promotes local development and illustration of a climate-resilient approach in that they enhance carbon sequestration and sustain rural livelihoods [100].

The identification of these land use changes as significant contributors to the region’s forest degradation further supported the findings of statistical analysis and satellite imaging, and it makes it exceedingly dangerous for the biosphere reserve to maintain the biodiversity that made it possible for it to be identified and About 15 households have unlawfully established on 8 hectares of the biosphere reserve’s core zone, according to data acquired from focus groups and key informant interviews with farmers in Yayo District, particularly in the Kori area close to Sayi Forest [105]. Similarly, in Ilu Abba Dinka Kebele, Janeh area, about 28 households have settled on 14 hectares of the core zone. In total, approximately 22 hectares of forest in the core zone have been cleared due to agricultural expansion and coffee production. Additionally, in some areas, particularly in Gechi Kebele, local people have raised concerns about the planting of exotic tree species, which they believe could rapidly threaten and negatively affect the indigenous species by clearing the native vegetation [101].

The present results align with a study conducted in the Hawa Galan district of Kelem Wollega, Ethiopia, which found that forest cover in the district was negatively correlated with both the district’s overall population and the population within the forest area [102]. Another study reported that population growth has intensified pressure on scarce natural resources, leading to the degradation and destruction of forests and woodlands [103].

3.10. Socio-economic determinants of forest dependency and conservation behavior

The Pearson Correlation analysis results indicate a strong negative correlation between forest cover and population growth rate over the past 40 years in the surveyed forest biosphere reserve, with a coefficient value of −0.998. This negative value confirms an inverse relationship between population growth and forest cover, meaning that as population growth increases, forest area decreases, and vice versa [104]. The statistical analysis also shows that this correlation is significant at the 0.05 confidence level (P < 0.05) [Table 4]. In line with the above findings, the impact and pressure of population on land use and land cover (LULC) changes are strongly influenced by population density. Pearson correlation analysis showed that forest cover (P = −0.006) is negatively associated with population pressure on forests [104].

Table 4. Pearson correlation analysis: Population growth Vs Forest cover change, Yayo coffee forest biosphere reserve from 1984 to 2024, Southwest Ethiopia, Supplementary Table (S1 Table).

Factors	Population growth	Forest cover change	Year of change
Population growth	1	−0.998*	0.999*
Sig. value		0.043	0.020

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Based on the Data from 148 households in the Yayo Coffee Forest Biosphere Reserve identified key socio-economic factors influencing forest dependence. Multiple linear regression analysis showed that household size (β = −0.32), income (β = −0.0011), and education (β = −0.21) were all significantly and negatively associated with forest dependency (p < 0.001 for all). Larger families, higher income, and better education were linked to reduced reliance on forest resources, likely due to diversified livelihoods and greater access to alternatives. These findings support previous research on the socio-economic drivers of forest use and conservation [105,106]. The inverse relationship between education and forest dependency (β = −0.21, p < 0.001), and its positive contribution to conservation behavior (β = 0.31, p < 0.001), the environmental awareness is enhanced and pressure on forest resources is reduced through education [105,106]. Conservation behavior was analyzed using a logistic regression model, with a binary variable indicating whether households participated in conservation. Education had a positive and significant effect (β = 0.31, p < 0.001), suggesting that higher education promotes environmental awareness. Income also showed a positive association (β = 0.0017, p = 0.005), implying that wealthier households are more likely to engage in sustainable practices. Similarly, household size was positively linked to conservation behavior (β = 0.28, p = 0.002), possibly due to greater labor availability for community forest management activities [Table 5].

Table 5. Socio-economic determinants of forest dependency and conservation behavior in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024, Supplementary Table (S2 Table).

Variable	LR on forest resources		LR conservation behavior
Variable	Coefficient (A)	p-value	Coefficient (B)	p-value
Family Size	−0.32	0.000	0.28	0.002
Income Level (ETB)	−0.0011	0.000	0.0017	0.005
Education status (Years)	−0.21	0.000	0.31	0.000

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LR* - Linear Regression, LR- Logistic Regression.

Similarly, income’s role in decreasing forest dependency (β = −0.0011, p < 0.001) and increasing conservation participation (β = 0.0017, p = 0.005) aligns with the finding that income diversification enables households to meet their demands without over-exploiting forests [107]. Although it appears contradictory to assume that family size would be positively associated with conservation conduct, this study found that larger families were less dependent on the forest (β = −0.32, p < 0.001) and more involved in conservation activities (β = 0.28, p = 0.002), consistent with those who argued that larger families are capable of rendering more effort and labor towards conservation [108].

4. Conclusion and policy implications

The Yayo Coffee Forest Biosphere Reserve is crucial for local livelihoods, despite the growing threat of increasing population, expansion of farmlands, and the weak coordination at the institutional level. Traditional systems of governance, such as Tuullaa and Jaarsa Biyya, work to regulate resource use, while formal institutions face the problem of limited capacity and community engagement. A strong negative correlation between population growth and forest cover results in an 11.6% loss over four decades, and this indicates pressure on natural resources. It requires the integration of indigenous governance into formal systems, environmental awareness, diversified income, and the enforcement of land-use policy that balances ecological protection with community needs. The study also suggests revision in land allocation policy by adopting a “Comprehensive-to-Detail” approach: First, by undertaking a detailed survey of the available land and creating flexible standards that allow efficient and effective use of the land; and second, by continual research on this approach and other complementary strategies to minimize land consumption.

Supporting information

S1 Fig. Satellite Images Results of Land Use Land Cover in the Yayo coffee forest Biosphere Reserve from 1984 to 2024, Southwest Ethiopia [Hurumu, Doreni and Yayo districts].

(DOCX)

pone.0324407.s001.docx^{(725.9KB, docx)}

S1 Table. Pearson Correlation analysis Data: Population growth Vs Forest cover change, Yayo coffee forest Biosphere Reserve from 1984 to 2024, Southwest Ethiopia.

(DOCX)

pone.0324407.s002.docx^{(16.9KB, docx)}

S2 Table. Socio-Economic Determinants Data: Forest Dependency and Conservation Behavior in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024.

(DOCX)

pone.0324407.s003.docx^{(16.1KB, docx)}

Abbreviations

CBOs: Community Based Organization
DAs: Developmental Agents
EARO: Ethiopian Agricultural Research Organization
FAO: Food and Agricultural Organization
IUCN: International Union for Conservation of Nature and Natural Resources
m.a.s.l.: Meter above sea level
MAB: Program on Man and the Biosphere
NGOs: Non-Governmental Organizations
SPSS: Statistical Package for Social Sciences
STCP: Sustainable Tree Crops Program
UNESCO: United Nations Educational, Scientific and Cultural Organization
ZEF: Zentrum fur Entwicklungsforschung (Center for Development Research)

Data Availability

The dataset supporting the findings of this study is publicly available in Dryad at https://doi.org/10.5061/dryad.66t1g1kfb. The data are fully anonymized and contain only the variables necessary to replicate the results reported in this study.

Funding Statement

The author(s) received no specific funding for this work.

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PLoS One. doi: 10.1371/journal.pone.0324407.r001

Decision Letter 0

Dereje Donacho

9 Jun 2025

Dear Dr. Hunde,

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Additional Editor Comments:

The study highlighted the impact of population pressure on forest resource depletion in the Yayo Coffee Forest Biosphere Reserve, Ilubabor Zone, Oromia Regional State, and Southwest Ethiopia. The topic is important and interesting; however, it needs major revision to improve the quality and novelty of research. More importantly, the authors may benefit from intensive revision focusing on the following points:

• The introduction should be clear and show the research gap and attempts done so far by local implementers, particularly government, local community, and non-governmental organizations.

• The methodology also lacks some clarities that should be addressed in the revision.

• The results should be rechecked with consistency, and the grammar and logical coherence should be clear for the readers.

• The discussion sections need additional comparison with the domain knowledge, and the discrepancy should be discussed well.

• The limitation and strength of the study should be clearly stated.

• The implication of the finding and the recommendations lack clarity that needs revision.

• Finally, the individual photos attached in the document need legal documents such as consent, but nothing is explained about the issue in the manuscript. Therefore, I recommend to remove.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Partly

Reviewer #2: Yes

**********

2. Has the statistical analysis been performed appropriately and rigorously? -->?>

Reviewer #1: Yes

Reviewer #2: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available??>

The PLOS Data policy

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English??>

Reviewer #1: No

Reviewer #2: Yes

**********

Reviewer #1: Dear authors your study topic is interesting but it needs major revisions, especial grammar and lack of citations are the major problems of the study, please solve this problem and related ones. Also make the mape legevisible for readers!

Reviewer #2: Critical Review of the Manuscript

1. Nobility of the Study

• Strengths: The manuscript focuses on a critical environmental issue in a globally significant biosphere reserve. It addresses the pressing need for sustainable forest management amidst growing population pressures.

• Weaknesses: The manuscript does not highlight the global implications of its findings. For instance, the impact of forest loss in the Yayo Coffee Forest Biosphere Reserve on carbon sequestration and global biodiversity hotspots could be better contextualized.

• Recommendation: Explicitly link the study's implications to global environmental challenges, such as climate change and biodiversity loss.

2. Statement of the Problem and Knowledge Gap

• Strengths: The problem is articulated in the context of population pressure and forest degradation.

• Weaknesses: The knowledge gap lacks specificity. While the manuscript states that population growth affects forest resources, it does not critically assess why current solutions are insufficient or how this study provides a novel perspective.

• Recommendation: Expand the introduction to include a critical review of existing solutions and their shortcomings. Clearly articulate how this research addresses those gaps.

3. Objective

• Strengths: Objectives are clear and focused.

• Weaknesses: The objectives could be more concise and aligned directly with the problem statement.

• Recommendation: Reframe the objectives to reflect measurable outcomes. For example, "Quantify the impact of population growth on forest cover using satellite imagery from 1984 to 2024."

4. Method of Data Collection

• Strengths: The mixed-methods approach adds depth and breadth to the analysis.

• Weaknesses: The manuscript fails to justify the selection of methods, particularly the use of satellite imagery spanning specific years and the choice of SPSS for analysis.

• Recommendation: Provide citations for methodological protocols. For instance, why were 1984, 1994, and 2007 chosen for satellite imagery? What validation steps were taken to ensure accuracy in satellite data interpretation? Include a clear rationale for the statistical tools employed.

5. Method of Data Analysis

• Strengths: The use of SPSS and Pearson correlation is appropriate for quantitative data.

• Weaknesses: The analysis lacks depth in exploring causality. For example, while correlation is established, causation is not discussed.

• Recommendation: Include regression analysis or other advanced statistical methods to explore causality. For qualitative data, provide representative quotes or narratives to substantiate thematic findings.

6. Results

• Strengths: The results are comprehensive and supported by tables and figures.

• Weaknesses: The presentation is cluttered and lacks coherence. The socio-economic data is presented without linking it to the broader research question.

• Recommendation: Simplify tables and figures, ensuring each directly addresses a research objective. Use visual aids like trend lines or pie charts to make data more digestible.

7. Discussion

• Strengths: The discussion connects findings to conservation and socio-economic issues.

• Weaknesses: There is insufficient engagement with contemporary literature. Key findings are not critically analyzed against previous studies.

• Recommendation: Incorporate a comparative analysis with global studies on forest degradation. Critically evaluate the implications of key results, such as the role of local governance in conservation efforts.

8. Recommendations

• Strengths: The recommendations are actionable and community-oriented.

• Weaknesses: They are broad and lack prioritization.

• Recommendation: Categorize recommendations into immediate, medium-term, and long-term actions. Justify recommendations with data and evidence from the study.

9. Alignment of Research Problem, Objective, Methods, Results, and Discussion

• Strengths: The manuscript maintains alignment throughout its sections.

• Weaknesses: The linkage between objectives, findings, and recommendations is weak. For example, the methods section does not explain how the data supports specific recommendations.

• Recommendation: Create explicit connections between each section. For instance, demonstrate how the satellite imagery data directly informs the policy recommendations.

10. Suggestions for Authors

o Refine the introduction to frame the study within a global conservation context.

o Enhance methodological transparency by justifying data collection and analysis choices.

o Integrate more critical analysis in the discussion, contrasting findings with global studies.

**********

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Reviewer #1: Yes: Binega Derebe

Reviewer #2: No

**********

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Attachment

Submitted filename: PONE-D-25-21231 first reviewed.pdf

pone.0324407.s004.pdf^{(1.4MB, pdf)}

PLoS One. 2026 Jan 5;21(1):e0324407. doi: 10.1371/journal.pone.0324407.r002

Author response to Decision Letter 1

11 Oct 2025

Response to Reviewer Comments

Manuscript Title: Impact of Population Pressure on Forest Resources Depletion in Yayo Coffee Forest Biosphere Reserve, Ilubabor Zone, Oromia Regional State, Southwest Ethiopia

Manuscript ID: PONE-D-25-21231

Dear PLOS ONE Editorial Team,

We sincerely thank you for the opportunity to revise our manuscript and express our appreciation to the reviewers for their insightful comments and suggestions that have helped us to improve the quality and clarity of our paper.

We have carefully considered all the reviewer’s comments and revised the manuscript accordingly. Below we provide a detailed, point-by-point response to the reviewer’s remarks. For clarity, we have included each comment in bold followed by our responses in regular text. All changes made in the manuscript are highlighted for your convenience.

Reviewer #1:

Comment #1. Dear authors your study topic is interesting but it needs major revisions, especial grammar and lack of citations are the major problems of the study, please solve this problem and related ones. Also make the mape legevisible for readers!

Response #1. We sincerely thank the reviewer for the constructive feedback and appreciation of the study's topic. In response:

� We have thoroughly revised the manuscript for grammar, clarity, and academic writing quality. To ensure correctness, we conducted a full language edit and proofreading.

� We have reviewed the manuscript and added relevant and up-to-date citations to strengthen the literature support and properly credit prior research.

� The presentation of the Mean Absolute Percentage Error (MAPE) has been improved. Specifically, we have clarified its definition, usage, and interpretation in the methodology and results sections. We also ensured it is clearly labeled and easy to interpret in the tables and figures.

Reviewer #2:

Comment #1.

1. Nobility of the Study: Critical Review of the Manuscript

� Strengths: The manuscript focuses on a critical environmental issue in a globally significant biosphere reserve. It addresses the pressing need for sustainable forest management amidst growing population pressures.

� Weaknesses: The manuscript does not highlight the global implications of its findings. For instance, the impact of forest loss in the Yayo Coffee Forest Biosphere Reserve on carbon sequestration and global biodiversity hotspots could be better contextualized.

� Recommendation: Explicitly link the study's implications to global environmental challenges, such as climate change and biodiversity loss.

Response #1.

We sincerely thank the reviewer for the thoughtful evaluation and constructive suggestion. In response, we have revised the introduction, discussion and conclusion sections to better highlight the global significance of our findings. Specifically, we now discuss the broader implications of forest loss in the Yayo Coffee Forest Biosphere Reserve in terms of carbon sequestration, contributions to global biodiversity conservation, and relevance to international climate and sustainability goals. These additions help to clearly position our study within the context of global environmental challenges, such as climate change and biodiversity loss.

The revisions can be found on page2, paragraph 3; page 16, paragraph 2 and page 19, paragraph 2

Comment # 2. Statement of the Problem and Knowledge Gap

• Strengths: The problem is articulated in the context of population pressure and forest degradation.

• Recommendation: Expand the introduction to include a critical review of existing solutions and their shortcomings. Clearly articulate how this research addresses those gaps.

Response # 2

We thank the reviewer for this insightful observation. In response, we have revised the introduction to include a more detailed and critical review of existing interventions aimed at mitigating forest degradation under population pressure. We now discuss the limitations of current policy frameworks, enforcement mechanisms, and community-based management approaches, particularly in the context of the Yayo Coffee Forest Biosphere Reserve. Furthermore, we have clearly articulated how our study offers a novel contribution by integrating socio-ecological analysis with geospatial data to assess the effectiveness of existing measures. These revisions help clarify the specific knowledge gap and the unique perspective our study brings.

The revised content can be found on page 3, paragraph 3.

Comment #3: Objective

• Strengths: Objectives are clear and focused.

• Weaknesses: The objectives could be more concise and aligned directly with the problem statement.

• Recommendation: Reframe the objectives to reflect measurable outcomes. For example, "Quantify the impact of population growth on forest cover using satellite imagery from 1984 to 2024."

Response # 3

We appreciate the reviewer’s positive feedback and helpful recommendation. In response, we have revised the objectives to make them more concise and explicitly aligned with the problem statement. The updated objectives now clearly reflect measurable outcomes, including the quantification of forest cover change over time and the assessment of population growth impacts using geospatial data from 1984 to 2024. This reframing enhances the clarity and focus of the study and better communicates its purpose to the reader.

The revised objectives are presented in the introduction section on page 3 paragraph 4

Comment #4. Method of Data Collection

• Strengths: The mixed-methods approach adds depth and breadth to the analysis.

• Weaknesses: The manuscript fails to justify the selection of methods, particularly the use of satellite imagery spanning specific years and the choice of SPSS for analysis.

• Recommendation: Provide citations for methodological protocols. For instance, why were 1984, 1994, 2004 and 2024 chosen for satellite imagery? What validation steps were taken to ensure accuracy in satellite data interpretation? Include a clear rationale for the statistical tools employed.

Response #4

We thank the reviewer for this valuable feedback and for recognizing the strengths of our mixed-methods approach. In response to the concerns raised:

• We have now provided a detailed justification for the selection of satellite imagery years (1984, 1994, and 2024). These years were chosen based on data availability, major policy or demographic shifts in the region, and their relevance in capturing long-term trends in land cover change. We have added relevant references to support this temporal selection.

• We have also described the image classification and accuracy assessment procedures, including the use of ground truth data, historical Google Earth imagery, and confusion matrices to validate classification results. The methods and validation steps are now clearly stated in the revised methodology section.

• Furthermore, we have included a rationale for using SPSS, explaining its role in analyzing survey data and conducting descriptive and inferential statistical analyses, such as correlation and regression, to examine relationships between population dynamics and forest cover change. Supporting citations have been added where appropriate.

These revisions are included in the methodology section on pages 18 – 21.

Comment # 5: Method of Data Analysis

• Strengths: The use of SPSS and Pearson correlation is appropriate for quantitative data.

• Weaknesses: The analysis lacks depth in exploring causality. For example, while correlation is established, causation is not discussed.

Response #5

We appreciate the reviewer’s thoughtful comments and suggestions to enhance the rigor of our data analysis. In response:

• We have extended our quantitative analysis by incorporating multiple linear regression models to better explore causal relationships between population growth variables and forest cover change. The regression results are now included and interpreted in the revised results section.

• In addition to Pearson correlation, the use of regression analysis enables us to assess the strength and direction of potential causal links while controlling for confounding variables.

• For the qualitative data, we have included representative quotes from key informant interviews and focus group discussions to support and illustrate the main themes identified. These narratives provide greater context and depth to the findings.

All additions and revisions are detailed in the results and conclusion sections on pages 21-22

Comment #6. Results

• Strengths: The results are comprehensive and supported by tables and figures.

• Weaknesses: The presentation is cluttered and lacks coherence. The socio-economic data is presented without linking it to the broader research question.

• Recommendation: Simplify tables and figures, ensuring each directly addresses a research objective. Use visual aids like trend lines or pie charts to make data more digestible.

Response #6

We thank the reviewer for acknowledging the comprehensiveness of our results and for the valuable suggestions to improve clarity and coherence. In response:

• We have simplified and reorganized the tables and figures to ensure each one directly corresponds to a specific research objective or key finding. Unnecessary or redundant visuals have been removed, and labels and captions have been improved for clarity.

• To enhance readability, we introduced more visual aids such as trend lines, pie charts, and bar graphs where appropriate—particularly for time-series and categorical socio-economic data. These revisions help highlight key trends and make the data more accessible to readers.

• Additionally, we revised the narrative surrounding the socio-economic data to better connect the findings with the main research question and theoretical framework. This strengthens the linkage between data and interpretation.

The revised figures and results are presented in the results section on pages Fig 1 on page 4, Figure 2 on page 10, figure 3 on page 15, and figure 4 on page 16, figure 5 on page 18, and Table 5 on page 21.

Comment #7. Discussion

• Strengths: The discussion connects findings to conservation and socio-economic issues.

• Weaknesses: There is insufficient engagement with contemporary literature. Key findings are not critically analyzed against previous studies.

Response # 7

We thank the reviewer for this important suggestion to deepen the analytical strength of the discussion. In response:

• We have substantially revised the discussion section to include a broader engagement with recent and relevant global literature on forest degradation, land use change, and population dynamics. Comparative insights from studies in other tropical biosphere reserves and conservation areas (e.g., Southeast Asia, Central Africa, and Latin America) have been incorporated to contextualize our findings.

• We have critically examined how our results align with or diverge from previous studies, particularly regarding the drivers of forest loss and the socio-economic dimensions of resource pressure.

• Moreover, we have expanded our evaluation of the role of local governance in forest conservation. This includes a discussion of community-based forest management, institutional challenges, and the effectiveness of local bylaws and stakeholder engagement, supported by recent studies and best practices from similar settings.

These additions provide a more nuanced understanding of our findings and better position them within the global discourse on forest conservation. The revised discussion is found on pages 7- 20

Comment # 8. Recommendations

� Strengths: The recommendations are actionable and community-oriented.

� Weaknesses: They are broad and lack prioritization.

� Recommendation: Categorize recommendations into immediate, medium-term, and long-term actions. Justify recommendations with data and evidence from the study.

Response # 8

We thank the reviewer for the constructive feedback and for recognizing the community-oriented nature of our recommendations. In response:

• We have revised the recommendations section to categorize proposed actions into immediate, medium-term, and long-term interventions. This prioritization provides a clearer implementation framework for stakeholders.

• Each recommendation is now more explicitly supported by data and findings from our study—for example, deforestation hotspots identified through satellite analysis and community perceptions gathered through surveys and interviews.

• We also clarified the linkage between the proposed actions and the underlying causes of forest degradation identified in the research, ensuring that each recommendation is both evidence-based and aligned with the study objectives.

These improvements are presented in the revised conclusion and recommendations sections on pages 23, and are highlighted accordingly in the updated manuscript.

Comment # 9: Alignment of Research Problem, Objective, Methods, Results, and Discussion

� Strengths: The manuscript maintains alignment throughout its sections.

� Weaknesses: The linkage between objectives, findings, and recommendations is weak. For example, the methods section does not explain how the data supports specific recommendations.

� Recommendation: Create explicit connections between each section. For instance, demonstrate how the satellite imagery data directly informs the policy recommendations.

Response # 9

We thank the reviewer for highlighting the importance of internal consistency and coherence across the manuscript. In response:

• We have revised the methods and discussion sections to more clearly explain how each type of data collected—particularly the satellite imagery and socio-economic survey results—contributes directly to the study’s objectives and informs the recommendations.

• The discussion now includes explicit references to how land cover change data (e.g., forest loss from 1984 to 2024) supports targeted policy interventions such as zoning, reforestation efforts, and land use planning.

• We have also refined the recommendations section to include cross-references to the specific findings they are based on. This creates a stronger narrative thread from research problem to objective, methods, results, and actionable solutions.

• Where applicable, we included a summary table that links each research objective with the corresponding data, key findings, and resulting recommendations to make these connections more transparent to the reader.

These improvements appear on pages 18 to 21

Comment # 10: Suggestions for Authors

o Refine the introduction to frame the study within a global conservation context.

o Enhance methodological transparency by justifying data collection and analysis choices.

o Integrate more critical analysis in the discussion, contrasting findings with global studies.

Response # 10

We sincerely thank the reviewer for these valuable and constructive suggestions. In response:

• We have refined the introduction to more clearly position the study within a global conservation context. This includes discussion of the relevance of biosphere reserves to global biodiversity conservation, climate change mitigation, and sustainable development goals. We have also added citations to recent international studies and frameworks to support this global framing.

• To enhance methodological transparency, we have added justifications for our choices in data collection (e.g., selection of satellite imagery years, survey tools) and data analysis (e.g., use of SPSS, regression analysis). Supporting literature has been cited to provide methodological ground

Attachment

Submitted filename: Response to Reviewers.docx

pone.0324407.s005.docx^{(24.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0324407.r003

Decision Letter 1

Dereje Donacho

27 Oct 2025

Dear Dr. Hunde,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Dec 11 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

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Comments to the Author

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Reviewer #3: All comments have been addressed

Reviewer #4: (No Response)

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Reviewer #1: Yes

Reviewer #3: Yes

Reviewer #4: No

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Reviewer #3: Yes

Reviewer #4: No

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Reviewer #3: Yes

Reviewer #4: No

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Reviewer #3: Yes

Reviewer #4: No

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Reviewer #1: Dear authors thank you for your corrections of my previous comments and now the manuscript needs only minor revisions as I track in the pdf. Please correct them and your manuscript will be ready to publish.

Reviewer #3: -Streamline some long paragraphs in the discussion for conciseness and improve the narrative flow.

-Ensure all citations are formatted consistently according to PLOS ONE style.

-The conclusions could be shortened to focus on key findings and their policy implications rather than restating results.

-If possible, include a clearer policy framework diagram linking population dynamics, land use, and conservation responses

Reviewer #4: Title:

Impact of Population Pressure on Forest Resource Depletion in Yayo Coffee Forest Biosphere Reserve, Ilubabor Zone, Oromia Regional State, Southwest Ethiopia

General Comments:

The manuscript presents a potentially important topic concerning the impact of population pressure on forest resource depletion within the Yayo Coffee Forest Biosphere Reserve. However, the overall quality of the paper does not meet the expected scientific and publication standards. The manuscript lacks organization, clarity, and scientific rigor in several sections. Below is a detailed evaluation of each component.

Technical Issue:

•The manuscript lacks continuous line numbering, making it difficult to provide specific comments or refer to precise sections of the text.

2. Major Issues

2.1 Title

•The title is appropriate and well formulated, clearly indicating the study area and the core issue of investigation.

2.2 Abstract

•The abstract is weakly constructed and lacks structure.

•The data collection process is confusing and incomplete. The author should specify how many respondents were included (key informants, kebele leaders, development agents, households), and clarify the roles of focus group discussions and field observations.

•The study design and analytical methods are not mentioned, leaving readers uncertain about how data were collected or analyzed.

•Inclusion of livelihood activities in the abstract is unnecessary and distracts from the research focus.

Recommendation:

The abstract should be revised to follow a clear and concise format:

1.Background and objective of the study

2.Methods and data (sample size, design, and analytical tools)

3.Key findings with quantitative evidence

4.Conclusions and implications

2.3 Introduction

•The introduction is poorly developed and lacks articulation.

•The study area is not properly contextualized, and the section fails to provide a strong background or justification for the research.

•The problem statement and research gap are missing or not explicitly defined.

•The justification for the study is weak, making it unclear why the research was necessary or how it contributes to existing literature.

•Only four citations are used throughout the section, which is insufficient to meet scientific and journal standards. The authors should consult recent and relevant studies to strengthen the background and demonstrate awareness of previous work.

Recommendation:

The introduction should:

1.Present the broader context of population growth and forest depletion in Ethiopia.

2.The specific issues in the Yayo Coffee Forest Biosphere Reserve.

3.Clearly state the research problem and objectives.

4.Identify the research gap and justify why this study is necessary.

5.Integrate at least 10–15 recent and relevant references to strengthen the academic foundation.

2.4 Materials and Methods:

•This section is not well organized and lacks coherence.

•It includes unnecessary sentences and paragraphs rather than clearly outlining the data collection process, sampling procedures, data sources, and analytical techniques.

•There is no clear description of how data were obtained from different respondents or how the qualitative and quantitative information was analyzed.

Recommendation:

The section should be restructured to include:

1.Description of the study area (location, population, ecology).

2.Sampling design and techniques (how respondents were selected).

3.Data sources (primary and secondary).

4.Data collection tools (household surveys, key informant interviews, FGDs, observations).

5.Data analysis (statistical methods, qualitative coding, GIS/remote sensing tools, etc.).

2.5 Results and Discussion

•The results and discussion are not scientifically presented and lack analytical interpretation.

•The content reads more like a descriptive report than a scientific discussion, focusing excessively on general socio-economic characteristics and institutional narratives.

•The subsection “Population Growth and Forest Cover Change” is weakly supported; it does not establish any statistical relationship between population pressure and forest cover dynamics.

•The “Satellite Image Results of Land Use Land Cover (1984–2007)” subsection contains potentially valuable information but lacks analysis linking observed land cover changes to the stated hypothesis.

Recommendation:

•Present results using quantitative evidence (tables, figures, statistical tests).

•Discuss findings in comparison with previous studies to provide scientific interpretation.

•Use appropriate statistical methods (e.g., correlation, regression, trend analysis) to demonstrate relationships between population growth and forest cover change.

2.6 Conclusion and Recommendations

•The conclusion does not effectively summarize key findings or their implications.

•The recommendations are generic and not derived from the study results.

Recommendation:

•Summarize the main findings succinctly, focusing on their implications for forest management, policy, and sustainable livelihoods.

•Ensure that recommendations are evidence-based, specific, and actionable, directly linked to the findings presented.

Overall Evaluation:

•The manuscript does not meet the required publication standards in its current form.

•Therefore, it is regrettably rejected for publication

**********

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Reviewer #1: Yes: Binega Derebe

Reviewer #3: No

Reviewer #4: No

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PLoS One. 2026 Jan 5;21(1):e0324407. doi: 10.1371/journal.pone.0324407.r004

Author response to Decision Letter 2

20 Nov 2025

Response to Reviewers comments,

Dear Editor,

We thank the reviewers for their constructive comments on our manuscript. We have carefully revised the paper and addressed all points raised. The abstract has been restructured; the introduction rewritten with clearer context, defined research gaps, and additional recent references; and the Materials and Methods section reorganized to clearly describe the study area, sampling procedures, data sources, and analytical methods.

The Results and Discussion section has been strengthened with quantitative evidence, statistical analyses, and clearer links between population pressure and forest cover change. The Conclusion and Recommendations have been rewritten to reflect the key findings and provide specific, evidence-based actions. Continuous line numbering has also been added.

We believe these revisions have significantly improved the clarity, rigor, and overall quality of the manuscript. We appreciate the opportunity to revise our work.

Sincerely,

Fikru Mosisa

Corresponding Author

Attachment

Submitted filename: Response to Reviewers_2.docx

pone.0324407.s008.docx^{(23.1KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0324407.r005

Decision Letter 2

Dereje Donacho

24 Nov 2025

IMPACT OF POPULATION PRESSURE ON FOREST RESOURCES DEPLETION IN YAYO COFFEE FOREST BIOSPHERE RESERVE, SOUTHWEST ETHIOPIA

PONE-D-25-21231R2

Dear Dr. Hunde,

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Dereje Oljira Donacho, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0324407.r006

Acceptance letter

Dereje Donacho

PONE-D-25-21231R2

PLOS One

Dear Dr. Hunde,

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Fig. Satellite Images Results of Land Use Land Cover in the Yayo coffee forest Biosphere Reserve from 1984 to 2024, Southwest Ethiopia [Hurumu, Doreni and Yayo districts].

(DOCX)

pone.0324407.s001.docx^{(725.9KB, docx)}

S1 Table. Pearson Correlation analysis Data: Population growth Vs Forest cover change, Yayo coffee forest Biosphere Reserve from 1984 to 2024, Southwest Ethiopia.

(DOCX)

pone.0324407.s002.docx^{(16.9KB, docx)}

S2 Table. Socio-Economic Determinants Data: Forest Dependency and Conservation Behavior in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024.

(DOCX)

pone.0324407.s003.docx^{(16.1KB, docx)}

Attachment

Submitted filename: PONE-D-25-21231 first reviewed.pdf

pone.0324407.s004.pdf^{(1.4MB, pdf)}

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Submitted filename: Response to Reviewers.docx

pone.0324407.s005.docx^{(24.1KB, docx)}

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Submitted filename: PONE-D-25-21231_R1.pdf

pone.0324407.s006.pdf^{(4.3MB, pdf)}

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Submitted filename: PLOS.docx

pone.0324407.s007.docx^{(19.2KB, docx)}

Attachment

Submitted filename: Response to Reviewers_2.docx

pone.0324407.s008.docx^{(23.1KB, docx)}

Data Availability Statement

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PERMALINK

Impact of population pressure on forest resources depletion in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia

Fikru Mosisa Hunde

Adanech Asfaw Benti

Tefera Jegora Kapula

Roles

Abstract

1 Introduction

2 Methods and materials

2.1 Study area description

2.1.1. Location.

Fig 1. Maps of the study area [Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024].

2.1.2. Climate.

2.1.3. Ecology.

2.2 Study design

2.3 Data collection tools

2.3.1. Key informant interviews (KIIs).

2.3.2. Household surveys.

2.3.3. Focus group discussions (FGDs).

2.3.4. Observations.

2.4 Target populations

2.5 Sampling methods and techniques

2.6 Data analysis

2.7. Ethical considerations

3 Results and discussion

3.1 Socio-economic characteristics

Table 1. Socio-demographic and economic characteristics of the participants among households in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024.

3.2. Livelihood strategies

Fig 2. Livelihood strategies among study participants [Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024].

3.3. Formal institutions in forest management

3.4. Informal institutions contributing for forest management

3.5. Conservation policies and its drawbacks

3.6. The contributions of the biosphere reserve to the local communities

Table 2. Forest products priority to support the household’s livelihood among study participants in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024.

3.7. The major factors of forest depletion

Fig 3. Factors contributing for the possible depletion of forest stocks [Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024].

3.8. Population growth and forest cover change

Fig 4. Forest land Conversion [Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024].

Table 3. Satellite images results of land use land cover in the Yayo coffee forest Biosphere reserve from 1984 to 2024 (S1 Fig).

3.9. Demographic trends from 1984 to 2024 and forest cover change satellite image result

Fig 5. Demographic Changes in the Yayo coffee forest Biosphere Reserve from 1984 to 2024, Southwest Ethiopia [Yayo, Hurumu, and Doreni Districts].

3.10. Socio-economic determinants of forest dependency and conservation behavior

Table 4. Pearson correlation analysis: Population growth Vs Forest cover change, Yayo coffee forest biosphere reserve from 1984 to 2024, Southwest Ethiopia, Supplementary Table (S1 Table).

Table 5. Socio-economic determinants of forest dependency and conservation behavior in Yayo coffee forest Biosphere Reserve, Southwest Ethiopia, 2024, Supplementary Table (S2 Table).

4. Conclusion and policy implications

Supporting information

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Dereje Donacho

Roles

Author response to Decision Letter 1

Decision Letter 1

Dereje Donacho

Roles

Author response to Decision Letter 2

Decision Letter 2

Dereje Donacho

Roles

Acceptance letter

Dereje Donacho

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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