Forest Structure and Carbon stock Dynamics under Traditional Coffee farming system in Diga District, Western Ethiopia

Present Address:

Abdi Geleta 1

Lijalem Hailu 1

Obsa Asefa 1

Emebet Asefa 1

Adugna Temesgen 2✉

Fekadu Gurmessa 1 Emailfekadugu@wollegauniversity.edu.et Emailfekadugurmessa.2020@gmail.com

Department of Biology Dambi Dollo University Dambi Dollo Ethiopia

2 Department of Biology Wollega University Nekemte Ethiopia

^aAbdi Geleta, ^aLijalem Hailu, ^aObsa Asefa, ^aEmebet Asefa, ^aAdugna Temesgen, ^b*Fekadu Gurmessa

^aDepartment of Biology, Dambi Dollo University, Dambi Dollo, Ethiopia, abdigalata@dadu.edu.et, abdigeleta96@gmail.com; ^bDepartment of Biology, Wollega University, Nekemte, Ethiopia, fekadugu@wollegauniversity.edu.et, fekadugurmessa.2020@gmail.com;

*Corresponding author

Abstract

Human-dominated landscapes are becoming more important for biodiversity conservation and climate change mitigation. As deforestation and forest degradation continue to reduce carbon stock density of the natural forest in the tropics, traditional coffee agroforestry systems, where Coffea arabica is cultivated under shade trees, are recognized for their structural complexity and capacity to store substantial biomass and soil carbon. However, the conversion of natural forests into simplified coffee systems through progressive thinning of shade trees can significantly diminish their ecological value. This study assessed forest structure and carbon stock dynamics in Natural Forest (NF) and Semi-Forest Coffee (SFC) systems in Diga District, western Ethiopia. To the people of this district, coffee forms a major source of livelihood. Forty sample plots (20 in each forest type) were systematically laid to record floristic composition, stand structure, basal area, and biomass of woody species. Species-specific and generalized allometric equations were used to estimate carbon stocks of trees and shrubs in both NF and SFC. Results revealed that NF had higher woody species richness (52 species) than SFC (25 species), asserting the impacts of traditional shade-tree management via selective removal of specific species and size classes. SFC had significantly lower basal area (8.41 m² ha⁻¹) and biomass carbon (41.59 t ha^-1) than NF (18.47 m² ha⁻¹) and 99.98 t ha^-1, respectively, demonstrating greater structural complexity. Albizia schimperiana was ecologically dominant in both systems, though with much larger basal area in NF. In both forest type, size-class distributions exhibited reverse J-shaped curves, suggesting active regeneration in NF but also selective removal of larger trees in SFC. Overall, forest structural integrity and carbon storage was markedly reduced due to traditional coffee management activities, emphasizing the need for improved shade-tree selection and retention strategies to improve ecosystem services in coffee-growing landscapes.

Keywords

/Phrases: Carbon stock density

Forest structure and biodiversity

Shade-tree management

Semi-Forest Coffee (SFC) systems

Introduction

Deforestation and forest degradation are becoming global environmental concerns; hence, protected areas alone are no longer sufficient for conserving biodiversity and mitigating the impact of climate change. As a result, Kremen & Merenlender (2018) suggested inclusion of human-dominated landscapes, predominantly those supporting tree-based crops such as coffee, rubber, cacao, etc., for their ecological value, including biodiversity conservation and carbon sequestration. Although agricultural landscapes have been overlooked in conservation planning, this view is changing as agroforestry systems demonstrate considerable potential for supporting biodiversity and ecosystem services, serving as refuge for other species. Agroforestry systems that incorporate trees, significantly contribute to biodiversity conservation and carbon sequestration.

Coffee-based traditional agroforestry is a long-established, ecologically complex production system in which Coffea arabica is cultivated under shade trees (Abebe, 2005; Waktola and Fekadu 2021). These systems retain multi-layered vegetation, including indigenous shade trees, and relatively complex canopy structures capable of storing substantial amounts of carbon in both biomass and soils. For instance, coffee agroforestry systems in southwestern Ethiopia store between 254.9 and 321.8 t C ha⁻¹ (biomass + soil), with coffee shrubs themselves contributing nearly 13% of total carbon (Niguse et al., 2022). Globally, high-shade, traditional coffee systems had higher soil organic carbon (SOC) than low-shade or full-sun systems (Molina-alvarado et al., 2025), asserting well-managed traditional coffee agroforests can serve as important carbon sinks, contributing to climate change mitigation while supporting biodiversity and rural livelihoods.

Despite their vital ecological role as biodiversity reservoir and carbon sink, shade-coffee systems face increasing threats. The conversion of natural forests into coffee agroforests, even shaded ones, and the simplification of existing coffee systems through excessive thinning, noticeably reduced shade-tree density, and removal of large remnant trees result in considerable carbon losses and diminished structural complexity (Aerts et al., 2011; Denu et al., 2016). Given the irreplaceable carbon storage capacity of mature trees, Pappo et al. (2025) indicated structural simplification of forests leads to net carbon emissions that even cannot be offset by mere plantation of new seedlings. In Ethiopia, transitions from closed-canopy forests to simplified coffee agroforests have been practiced, and altered species composition (Gurmessa et al., 2025), reduced canopy cover, and lowered biomass accumulation, ultimately decreasing carbon sequestration capacity. Although coffee agroforestry have been considered stable with little ecological impact, expansion of coffee plots into forest margins and intensification, by reducing shade cover, threaten its long-term carbon storage. Evidence from Indonesian coffee landscapes show wide variability, with some coffee agroforests with similar carbon stock to secondary forests, while others store as little as only 6.26 t C ha⁻¹, primarily due to low shade density and small tree sizes (Zekeng et al., 2025), indicating the impact of intensified coffee forest management practices on carbon sequestration potential of the system.

Conversion of high-carbon ecosystems into agriculture, including coffee plantations, results in large and often significant reductions in carbon stocks. Although coffee agroforestry may provide partial mitigation benefits, and maintain the carbon stock, its carbon sequestration potential remains low and insufficient to fully compensate the carbon losses caused by deforestation. Further intensification and declining vegetation cover, could shift shade-coffee landscapes from carbon sinks to carbon sources, with insignificant contribution to ecosystem stability and climate change mitigation (Ango et al., 2020; Laura et al., 2023). As coffee farming is widely practiced, and forms a major livelihood strategy in Diga District, understanding how traditional coffee management influences forest structure and carbon storage is critical. Local decisions regarding shade-tree retention, removal of remnant forest vegetation, and overall maintenance of canopy integrity determine whether coffee agroforests serve as effective carbon sinks or contribute to carbon loss. Hence, comprehensive evidence is required to guide sustainable forest management and policy recommendations. This study therefore was made to assess forest structure and carbon stock dynamics under traditional coffee farming systems in Diga District, Western Ethiopia.

Materials and Methods

Study area

The study was carried out in Diga District, situated in the East Wollega Zone of the Oromia Regional State, western Ethiopia. The district is located at ca. 12 and 346 km west Nekemte Town and Addis Ababa, respectively. Geographically, it extends between 8°56′–9°10′ N latitude and 36°9′–37°31′ E longitude (Fig. 1), covering a total area of 40,788 hectares.

Fig. 1

Location map of the study Area

(Source: Arc Map)

As per the climate data obtained from Nekemte Meteorological Station (2024), the district experiences humid and warm climate with a mean annual temperature and precipitation of 19.5°C and 1,866 mm, respectively (Fig. 2). Rainfall pattern is unimodal with peak precipitation occurring between June and September. Previously, Diga District was covered by Moist Afromontane forests (MAF) and Combretum–Terminalia woodland vegetation types. However, extensive deforestation driven by farmland expansion following the establishment of state farms particularly in the lowland areas has resulted in degradation of native forests, followed by severe soil erosion (Megersa, 2011).

Fig. 2

Climatic diagram of the study area

Diga District had a total population of 66,689, comprising 33,896 men and 32,793 women, of which approximately 12.56% were urban residents (CSA, 2007).The Oromo ethnic group forms the majority, with 96.75% of inhabitants, and the predominant religions is Protestant Christianity (56.06%) followed by Orthodox (36.53%) (CSA, 2007). Mixed farming, which integrates crop cultivation and livestock rearing, forms the main economic activity in the district. Coffee is widely grown in the mid highland areas as a cash crop and for household consumption. In addition, some residents engage in small-scale trade and handicrafts, reflecting a diversified livelihood structure. Land use in the area includes arable land, grazing land, coffee forests, natural forests, bush and shrub lands, construction areas, and other miscellaneous categories (Diga District Land, Agriculture, Forestry and Climate Change Office, 2024).

Data Collection

A preliminary survey was carried out within the study area to obtain preliminary information about vegetation type and forest coverage, to determine the appropriate sampling design. Data collection was conducted between April and May 2024 at two kebeles, namely Gudisa and Firomsa, in Diga District. These kebeles were purposively selected based on the presence of both natural forests (NF) and semi forest coffee (SFC). Semi forest coffee (SFC) is fully accessible and under the management of local coffee growers, whereas natural forest sites were those that are little accessible or not accessed by local communities. A total of 40 sample plots (20 per forest type) of 20 m × 20 m (400 m²) were established systematically following the sampling procedures outlined by Kent & Coker, (1992). Accordingly, 14 and 12 plots were established in NF and SFC of Gudisa kebele, while 6 and 8 plots were laid in NF and SFC of Firomsa kebele. Within each plot, juveniles (seedlings and saplings) with DBH between 2.5–5 cm were recorded in nested subplots of 5 m × 5 m (25 m²). To minimize edge effects, the first plot in each transect was established 50 m from the forest boundary, and subsequent plots and transects were spaced 100 m and 200 m apart, respectively following Senbeta & Teketay (2001). The number of plots required for adequate sampling was determined using a species–area curve. In each plot, species diversity, height, and diameter at breast height (DBH) were recorded for all woody species that attained a diameter at breast height (DBH) of 5 cm and height of 1.5 m and above. Plant specimens were collected from each plot, and taxonomic identification was made following the published volumes of Flora of Ethiopia and Eritrea books, and were verified by botanists in Wollega University teaching Herbarium. The full list of plant species included in this study will be obtained from the corresponding author upon the reasonable request. Voucher specimens are also stored in Wollega university teaching herbarium.

Data Analysis

Structural Data Analysis

Vegetation structure was determined using tree density (number of trees ha^− 1), basal area (m² ha^− 1), IVI, and size class distribution along DBH and height of trees. Basal area (BA) is the cross-sectional area of a tree estimated at breast height (1.3 m), usually expressed in m². Basal area was calculated using the following formula.

$\:BA={\uppi\:}\text{*}\frac{DB{H}^{2}}{4}$

Where: BA = is a basal area (m²) and DBH = is the diameter at breast height of a tree.

Importance value index (IVI) is used as a measure of woody species composition that combines frequency, abundance, and dominance importance values. The ecological importance of woody species (IVI) was computed for dominant woody species based on their relative density (RD), relative dominance (RDO) and relative frequency (RF) to determine their ecological importance, as follows (Kent & Coker, 1992)

$\:IVI=RD+RDO+RF$

Where:

$\:\text{R}\text{D}=\frac{\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{i}\text{n}\text{d}\text{i}\text{v}\text{i}\text{d}\text{u}\text{a}\text{l}\text{s}\:\text{o}\text{f}\:\text{a}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{e}\text{s}}{\text{t}\text{o}\text{t}\text{a}\text{l}\:\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{i}\text{n}\text{d}\text{i}\text{v}\text{i}\text{d}\text{u}\text{a}\text{l}\text{s}\:\text{o}\text{f}\:\text{a}\text{l}\text{l}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{e}\text{s}}*100$

$\:\text{R}\text{F}=\frac{\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{p}\text{l}\text{o}\text{t}\text{s}\:\text{w}\text{h}\text{e}\text{r}\text{e}\:\text{a}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{e}\text{s}\:\text{o}\text{c}\text{c}\text{u}\text{r}\text{s}}{\text{t}\text{o}\text{t}\text{a}\text{l}\:\text{o}\text{c}\text{c}\text{u}\text{r}\text{r}\text{e}\text{n}\text{c}\text{e}\:\text{o}\text{f}\:\text{a}\text{l}\text{l}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{e}\text{s}\:\text{i}\text{n}\:\text{a}\text{l}\text{l}\:\text{o}\text{f}\:\text{t}\text{h}\text{e}\:\text{p}\text{l}\text{o}\text{t}\text{s}}*100$

$\:\text{R}\text{D}\text{O}=\frac{\text{D}\text{o}\text{m}\text{i}\text{n}\text{a}\text{n}\text{c}\text{e}\:\text{o}\text{f}\:\text{a}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{e}\text{s}}{\text{D}\text{o}\text{m}\text{i}\text{n}\text{a}\text{n}\text{c}\text{e}\:\text{o}\text{f}\:\text{a}\text{l}\text{l}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{e}\text{s}}*100$

Carbon Stock Data Analysis

The data obtained from tree measurement was recorded and organized on the excel data sheet. As site-specific multi species equations were hardly available, aboveground biomass of trees with dbh ≥ 5 cm in NF was estimated using the biomass equation formulated by Chave et al. (2014).

Y = 0.0673 × (ƍD²H) ^0.976

Where: Y is aboveground biomass (Kg), ƍ: wood specific density (g/cm³), D: Diameter at breast Height (cm) and H: height (m)

Estimates of wood specific density were obtained from (FDRE, 2016). According to this source, the average wood density for woody species in Ethiopia was 0.612 g cm^− 3. This is comparable with the global average value and that of tropical Africa (Andalo et al., 2005; Henry et al., 2010; Reyes, 1992). For a species whose wood specific density is missing, the genus average was used.

Belowground biomass estimation is difficult, time consuming and destructive(Geider et al., 2001). Hence, it was estimated based on the root to shoot ratio, assuming BGB constitutes 20% of the aboveground biomass of trees in NF(Macdicken, 1997), and total carbon was estimated as 50% of total biomass(IPCC, 2006).

BGB = AGB × 0.2

Where, BGB: Belowground biomass, AGB: Aboveground biomass, 0.2: conversion factor (or 20% of AGB).

The aboveground biomass of shade trees was estimated using allometric models developed by (Kuyah et al., 2012) as follows.

$\:AGB=0.091*{d}^{2.472}$

Where: AGB is above ground biomass; d is diameter at breast height.

The aboveground carbon stock of shade tree was estimated by multiplying AGB with 48%.

Belowground biomass was estimated from shoot: root ratio of 26% which is commonly used and the product was multiplied by 50% to obtain belowground biomass carbon (IPCC, 2006). For each plot, a biomass C stock (Mg C ha-1) was calculated as the product of biomass and C content.

The aboveground biomass (AGB) of coffee shrubs was estimated using the model developed by Negash et al. (2013). This model use basal diameter (d) as a single independent variable (Negash et al., 2013).

$\:AGB\:coffee=0.147*{d}^{4.02}$

Where: AGB coffee is aboveground biomass of coffee shrubs (kg); d is the diameter of coffee shrubs at 40 cm above ground.

Coffee AGB was multiplied by 49% to obtain aboveground biomass carbon stock of coffee shrubs (Negash et al., 2013), and the AGC was multiplied by 26% to get BGC stock. Moreover, biomass carbon was converted to Carbon dioxide Equivalent by multiplying it by 3.67 (Pearson & Brown, 2005).

Tree parameter, including biomass and carbon stock data were recorded and organized on Microsoft Excel and analyzed using R statistical software (ver. 3.4.2.) ( R Foundation Core Team, 2017). Initial comparisons were made using descriptive statistics, including percentage, tables and graphs. Moreover, independent two-sampled t-test was performed to determine whether NF and SFC were significantly different with respect to basal area and carbon stock density. The impacts of traditional coffee farming practices on woody species richness, basal area and carbon stock were summarized and supported with concise discussion. Box plots were used for visualizations. In order to understand the preferences of shade tree species and the management techniques influencing forest structure and carbon, qualitative data were analyzed using a qualitative approach.

Results and Discussion

Woody Species Composition and Structural Attributes

A total of 52 woody plant species belonging to 48 genera and 32 families were recorded from the Natural Forest (NF) of Diga District, including 25 species in the Semi- Forest Coffee (SFC) systems (Fig. 3). Woody species richness obtained in this study is much lower than that of Abe Dongoro district (Gurmessa et al., 2025), which could be attributed to deforestation and overexploitation of woody species in the natural vegetation and intensive coffee management activities in the SFC. The significantly lower number of woody species in the SFC highlights the impact of coffee cultivation on woody species richness, supporting the findings of Gurmessa et al. (2025), and Hundera et al. (2013). Other studies, such as Schmitt et al. (2009) and Geeraert (2019), also stated the negative impact of coffee cultivation on woody species diversity, leading to less diverse tree communities. Hence, the reduction in woody species richness of the SFC is attributed to practices like slashing, hoeing, and selective tree removal, aimed at maximizing coffee yield. The natural forest in Diga District had comparable woody species richness with Bale ecoregion (47 species), Yayo District (54 species), and Belete Gera (55 species). SFC species richness was much lower than Belete Gera Forest (44 species), Abe Dongoro district (40 species), Bale ecoregion (39 species) and Yayo District (38 species) (Fekadu, 2019; Gurmessa et al., 2025; Nigatu et al., 2017, Gamachu & Jegora, 2019). These variations in species richness across regions could be due to differences in disturbance levels, sampling intensity, and varying topographic and climatic factors.

Trees constituted the dominant growth form in both land-use types, contributing 51.92% in the NF and 64% in the SFC. This compositional pattern aligns with observations from similar Afromontane forest–coffee systems in Ethiopia, where trees form the primary structural component followed by shrubs and lianas (Fole, 2022; Gole et al., 2008; Gurmessa et al., 2025),

Fig. 3

Number of woody species in different Growth form

Fabaceae family was the most species-rich in both land-use systems, with 6 species in the NF and 4 species in SFC areas. This is followed by Euphorbiaceae (three species in both NF and SFC), Moraceae, Rubiaceae, and Rutaceae (3 species each) in the NF. The dominance of these families is consistent with findings from Ethiopian montane forests and traditional coffee agroforestry systems, which are characterized by high representation of Fabaceae and Euphorbiaceae due to their ecological adaptability and role in nitrogen cycling and shade provision (Aerts et al., 2011; Hundera et al., 2013; Gurmessa et al., 2025).

Stand structure analysis revealed comparable stem densities across the two land-use systems, with 313.75 stems ha⁻¹ in the NF and 285 individuals ha⁻¹ in the SFC. However, species dominance varied markedly. In SFC, Coffea arabica exhibited exceptionally high stem density (203.75 individuals ha⁻¹), reflecting deliberate management practices favoring coffee cultivation. This was followed by Albizia schimperiana (25 individuals ha⁻¹), a widely preferred shade tree in traditional coffee production systems in the area and elsewhere in southwest Ethiopia (Senbeta & Denich, 2006; Muleta et al., 2011).

In contrast, the NF exhibited more even species distribution, with Syzygium guineense showing the highest density (38.75 individuals ha⁻¹), followed by Maytenus arbutifolia (25 individuals ha⁻¹) and Albizia schimperiana, Flacourtia indica, and Teclea nobilis (each 18.75 individuals ha⁻¹). The more uniform stem density among woody species in the NF reflects expected heterogeneity, typical of less-disturbed Afromontane forests (Beenhouwer et al., 2016).

Diameter at breast height (DBH) analysis indicated considerable variation across species and land-use types. The highest DBH recorded was 121 cm for Albizia schimperiana, followed by Syzygium guineense subsp. afromontanum, and Ficu sur (each 95 cm) in NF. In the SFC system, the highest DBH (127.39 cm) was still registered for Albizia schimperiana, with subsequent DBH values of 98, 79, and 79 cm for the same species. The dominance of large-diameter individuals of A. schimperiana in both systems highlights its ecological importance and selective retention by farmers as a priority shade tree, consistent with previous findings in Ethiopian coffee agroforestry landscapes (Senbeta & Denich, 2006; Gole et al., 2008).

The size-class distribution pattern of woody species in both systems followed a typical reverse J-shaped curve (Fig. 4), characterized by high frequencies of small-diameter individuals with progressively declining stem density in successive larger size classes. Approximately 60% of stems in the NF and 81% in the SFC were with a DBH of ≤ 10 cm, indicating active recruitment and sustainable population dynamics ((Lamprecht, 1989; Kent, 2012). As DBH increased, stem density declined sharply from 188.75 and 231.25 stems ha⁻¹ in the smallest size class to only 13.75 and 10 stems ha⁻¹ in the largest size class in the NF and SFC systems, respectively. Such trend of diameter class distribution shows selective cutting of larger trees for fuel, construction, timber, or to reduce canopy cover so as to let sunlight reach the understory coffee shrub, which is characteristic of secondary forest, and is commonly reported in coffee-based agroforestry systems in Ethiopia (Hundera et al., 2013; Beenhouwer et al., 2016)

Fig. 4

Size class distribution of woody species in Natural Forest (NF) and Semi Forest Coffee (SFC) systems of Diga District.

Basal Area

The basal area measurements revealed a substantial difference between the Natural Forest (NF) and Semi-Forest Coffee (SFC) systems in Diga district, with values of 18.47 m² ha⁻¹ and 8.41 m² ha⁻¹, respectively (Fig. 5).

Fig. 5

Boxplot showing Basal area (BA) of NF and SFC

The independent t-test (Table 1) showed that the basal area of SFC was significantly lower than that of the natural forest at p = 0.05, indicating that management practices associated with traditional coffee cultivation reduce overall stand density and tree size structure. These findings align with earlier studies that identified reduced basal area in coffee-managed forests due to selective thinning, pruning, and removal of competing species to optimize light for Coffea arabica (Senbeta & Denich, 2006; Aerts et al., 2011).

Table 1

Mean difference in Basal area between SFC and NF
Forest type	Mean BA (m² ha^− 1)	t-value	Df	p-value	95% confidence interval
					Lower	Upper
SFC	8.41	-2.02	38	0.05	-20.15	0.03
NF	18.47

Basal area distribution across species showed dominance by a few large canopy species such as Albizia schimperiana (16.99 m² ha^− 1) and Syzygium guineense subsp. afromontanum (6.79 m² ha^− 1) in the natural forest. These species contribute greatly to biomass accumulation, nutrient cycling, and microclimate regulation, attributes typical of mature Afromontane forest ecosystems (Friis et al., 2010). Medium-basal-area species such as Celtis africana, Albizia gummifera, Ficus sur, and Apodytes dimidiata further enhance habitat heterogeneity. Conversely, species exhibiting very low basal area, including Galiniera saxifraga and Brucea antidysenterica, likely represent either suppressed individuals with low DBH or species confined to understory roles, consistent with multi-layered forest systems.

In the SFC system, Albizia schimperiana (3.45 m² ha^− 1) remained an important shade tree, but at markedly reduced basal area compared to the NF, reflecting selective retention by farmers. The increased basal area of Coffea arabica (2.10 m² ha^− 1) and Croton macrostachyus (1.64 m² ha^− 1) also indicates management-driven species composition, where economically important species dominate. Other trees such as Dracaena afromontana and Millettia ferruginea are retained in the SFC, primarily for agro ecological benefits such as soil fertility improvement and moderation of understory microclimate, attributes widely reported for traditional coffee systems in Ethiopia (Gole, 2003; Fole, 2022). Overall, the natural forest represents a structurally complex ecosystem with higher biomass and ecological stability, while the SFC system represents an anthropogenic regulated landscape balancing ecological function with livelihood needs.

Importance Value Index (IVI)

The IVI analysis provides deeper insight into species dominance, ecological roles, and distribution within the natural forest. Albizia schimperiana, with an IVI of 65.47, emerged as the most ecologically significant species. Its high dominance reflects its large basal area, widespread distribution, and considerable contribution to forest structure, which is also consistent with its role as a fast-growing canopy species capable of nitrogen fixation and enhancing soil fertility (Assefa et al., 2022).

The second most influential species, Syzygium guineense subsp. afromontanum (IVI = 40.74), is known for its ecological versatility, contribution to canopy cover, and significance in providing food resources for wildlife (Friis, 1992). Celtis africana (IVI = 19.49), another important species, plays a substantial role in habitat provisioning, and nutrient cycling, supporting overall forest biodiversity and functioning. Species such as Ficus sur, Apodytes dimidiata, and Euphorbia abyssinica exhibited moderate IVI values, suggesting that while they are not dominant, they maintain notable ecological roles in forest regeneration, understory structuring, and interactions with fauna. In contrast, species with low IVI values, including Galiniera saxifraga, Brucea antidysenterica, Maesa lanceolata, and Rytigynia neglecta, are likely to be either rare, have restricted niches, or exist primarily as small-diameter understory trees. Such variation demonstrates a heterogeneous forest with a mix of dominant, subdominant, and rare species, indicative of healthy successional dynamics, ecological balance, and resilience (Kent & Coker, 1992).

Together, the IVI and basal area results suggest that the natural forest is characterized by high structural and compositional complexity, whereas the SFC system exhibits modified ecological patterns shaped by human management practices. Understanding these structural patterns is essential for designing sustainable forest management strategies, especially in landscapes where traditional coffee production intersects with biodiversity conservation.

Carbon Stock Density

Carbon stock analysis reveals clear structural and functional differences in carbon storage capacity between the Natural Forest and the Semi-Forest Coffee (SFC) systems of Diga district. Unlike SFC systems, which are regularly subjected to human interventions such as pruning and selective cutting (Denu et al., 2016), natural forests accumulate significantly higher carbon stocks due to minimal disturbance (Dibaba et al., 2019). The Natural Forest exhibited an average carbon stock density (CSD) of 99.98 t ha⁻¹, more than twice that of the SFC system (41.59 t ha⁻¹). Although the t-test indicated no statistically significant difference (p = 0.08), the ecological difference remains substantial and meaningful (Table 2). This pattern is consistent with findings from other Afromontane regions, where undisturbed forests consistently store higher biomass and carbon owing to the presence of large, mature trees and structurally complex stands (Brown & Lugo, 1992; Tefera, 2015; Addisu et al., 2019).

Table 2

Mean difference in Carbon stock density (CSD) of SFC and NF
Forest type	Mean Carbon stock density in (t ha^− 1)	t-value	Df	p-value	95% confidence interval
					Lower	Upper
SFC	41.59	-1.79	38	0.08	-124.35	7.58
NF	99.98

The broad range of CSD observed in the Natural Forest (1.91–535.94 t ha⁻¹) reflects high structural heterogeneity, species diversity, and the presence of large biomass-accumulating individuals (Fig. 6). Mature tropical trees contribute disproportionately to carbon storage, and their removal greatly reduces forest carbon sequestration capacity (Andalo., 2005; Lewis et al., 2013). By contrast, the SFC system displayed a narrower range (0.46–234.10 t ha⁻¹), consistent with typical coffee-management practices such as selective thinning, pruning, and understory clearing (Senbeta & Denich, 2006; Aerts et al., 2011). These interventions reduce structural complexity and limit biomass accumulation, contributing to the lower mean CSD in SFC areas.

Fig. 6

Boxplot comparison of Carbon stock density between SFC and NF

Despite these reductions, the SFC system still functions as an important carbon sink because shade trees are retained, demonstrating the climate-mitigation potential of agroforestry systems (Negash & Starr, 2015). However, intact natural forests remain the most effective carbon reservoirs due to their abundance of large-diameter trees, stable microclimates, and lower levels of disturbance (Pan et al., 2011).

Species-specific variations in carbon storage were also evident in both forest types. In the Natural Forest, Syzygium guineense subsp. afromontanum (747.13 t ha⁻¹), Albizia schimperiana (525.24 t ha⁻¹), and Prunus africana (170.63 t ha⁻¹) were the largest carbon reservoirs. These species attain large diameters and heights, resulting in high biomass accumulation and underscoring the important role of canopy trees in Afromontane forest carbon dynamics (Friis et al., 2010; Girma & Soromessa, 2014). Consistent with Denu et al. (2016), who reported high carbon storage by Ficus sur in Jimma Highlands; such species-level differences highlight the significance of retaining large individuals in managed systems. In the SFC, Albizia schimperiana (553.00 t ha⁻¹) remained the dominant carbon-storing species due to deliberate retention by farmers as a preferred shade tree. Although Syzygium guineense subsp. afromontanum and Croton macrostachyus also contributed notably, their carbon storage was lower than in the Natural Forest. The consistently lower contribution of small-diameter species in both systems supports global findings that large trees disproportionately shape forest-level carbon budgets (Slik et al., 2013).

Comparison of the Natural Forest CSD in Diga district with similar studies elsewhere in Ethiopia shows that the value obtained in this study (99.98 t ha⁻¹) falls within the range commonly reported for Afromontane forests (Table 3). Although lower than Tulu Lafto (261.89 t ha⁻¹) (Gurmessa et al., 2021), it is comparable to the Dorze Ayira forest (91.74 t ha⁻¹)(Dingamo & Takele, 2019). Likewise, comparison of the SFC CSD (41.59 t ha⁻¹) with other Ethiopian coffee forests shows moderate carbon storage potential (Table 3). The SFC in Diga stores more carbon than the Yirgacheffe coffee forest (Tesfay et al., 2022) but less than those in Mana district (63.1 t ha⁻¹), Jimma Highlands (61.5 t ha⁻¹), and Gera (58.27 t ha⁻¹), where coffee is grown under denser canopies with larger shade trees and reduced disturbances (Betemariyam et al., 2022; Denu et al., 2016; Mohammed & Bekele, 2014)

Table 3

Carbon stock comparison of Diga NF and SFC with other Forests in Ethiopia
S.N.	Forest type	Study area	CSD (Mg ha^− 1)	Source
1	Natural forest	Tulu Lafto forest	261.89	Gurmessa et al. (2021)
2	Natural forest	Sekele-Mariam forest	185.71	Mekonnen & Tolera (2019)
3	Natural forest	Sirso forest	384.44	Mewded & Lemessa (2020)
4	Natural forest	Babile Elephant Sanctuary	147.6	Sintayehu et al. (2020)
5	Natural forest	Dorze Ayira forest	91.74	Dingamo & Takele (2019)
6	Natural forest	Current Study	99.98
7	Coffee forest	Mana district, Jimma	63.1	Betemariyam et al. (2022)
8	Coffee forest	Jimma Highlands	61.5	Denu et al. (2016)
9	Coffee forest	Yirgacheffe district	11.07 to 27.48	Tesfay et al. (2022)
10	Coffee forest	Gera, SW Ethiopia	58.27	Mohammed & Bekele (2014)
11	SFC	Current Study	41.59

Overall, carbon storage among Ethiopia’s coffee forests is strongly influenced by differences in forest structure, management intensity, and levels of anthropogenic disturbance. Management practices typical of coffee systems, such as pruning, selective thinning, undergrowth removal, and occasional expansion of coffee plots, reduces stand density and basal area, ultimately lowering total biomass and carbon stocks (Denu et al., 2016).This pattern is reflected in the present study, where the Natural Forest stores more than twice the carbon of the SFC system. Despite its lower CSD, the SFC in Diga district still functions as an important carbon sink within the landscape. Improving management practices, particularly retention of large shade trees, reduced over-thinning, and the adoption of enrichment planting, can substantially enhance carbon sequestration while maintaining coffee productivity. Numerous studies highlight the long-term potential of coffee-based agroforestry systems to contribute to climate-change mitigation and sustainable forest management (Toru & Kibret, 2019; Sintayehu et al., 2020; Tesfay et al., 2022). Given the central role of coffee farming in local livelihoods, integrating carbon-sensitive management interventions offers important synergies between economic benefits and environmental conservation. In conclusion, although the SFC of Diga stores less carbon than many other Ethiopian forest systems, it remains ecologically significant and holds considerable potential for improvement through sustainable management. Safeguarding natural forests while promoting carbon-friendly practices in coffee agroforestry systems is essential for harmonizing livelihood needs with broader climate-mitigation commitments.

The CO₂-equivalent values show patterns similar to those observed in carbon stock density. In the Natural Forest, the highest CO₂-equivalent value (2,741.97 t CO₂ ha^− 1) was recorded for Syzygium guineense subsp. afromontanum, highlighting its exceptional role in long-term carbon storage. The average CO₂-equivalent across species (236.73 t CO₂ ha^− 1) reflects the presence of several high-biomass species. The lowest value (0.33 t CO₂ ha^− 1) from Galiniera saxifraga indicates its minor contribution to carbon sequestration due to small size or low abundance. This variation demonstrates that forest carbon storage is strongly skewed toward a few dominant tree species, a pattern commonly reported in tropical forests (Bastin et al., 2008).

In the SFC system, the maximum CO₂-equivalent (2,029.51 t CO₂ ha^− 1) occurred in Albizia schimperiana, emphasizing its importance as the dominant shade tree. The mean CO₂-equivalent value (152.64 t CO₂ ha^− 1) was lower than that of the Natural Forest, consistent with reduced stand structure, biomass, and species diversity. The smallest contributor was Allophylus abyssinicus (0.44 t CO₂ ha^− 1), typical of understory or small-stature species. Although SFC systems store lower total amounts of CO₂, the presence and retention of large shade trees enable them to maintain meaningful levels of carbon sequestration. This highlights the climate-mitigation potential of traditional shade-grown coffee systems, consistent with evidence from other Ethiopian and global agroforestry landscape (Moges et al., 2010; Soto-pinto et al., 2000). Overall, the comparison between Natural Forest and SFC systems shows that Natural Forests function as far more effective carbon reservoirs due to their structural complexity, abundance of large-diameter trees, and limited human disturbance. On the other hand, SFC systems continue to play an important role in climate-change mitigation, particularly where high-biomass shade trees are preserved. These findings reinforce the need to conserve intact natural forests while simultaneously promoting sustainable, shade-based coffee management practices that support both ecological integrity and local livelihoods.

Conclusion and Recommendations

The dominance of Coffea arabica and the markedly lower basal area recorded in the SFC system reflect a simplified forest structure characterized by small-diameter trees, reduced stand density, and lower overall biomass. These structural features are largely the result of traditional coffee management practices, such as selective thinning, pruning, and undergrowth removal, accomplished to optimize coffee production. Although statistical analysis showed no significant difference in carbon stock between the Natural Forest and the SFC system, the findings clearly demonstrate that the shaded coffee (SFC) system stores substantially lower carbon and CO₂-equivalent compared to undisturbed natural forests. This decline in carbon stock is primarily due to the selective removal of large native trees, limited recruitment of high-biomass species, and the predominance of young or small-stature vegetation typical of managed coffee landscapes. While some high-carbon species, notably Albizia schimperiana and Syzygium guineense subsp. afromontanum, are retained as shade trees, their contribution to carbon storage remains far below that of natural forests where large canopy species such as Pouteria adolfi-friederici, Prunus africana, Croton macrostachyus, and Ficus sur play critical roles in biomass accumulation and carbon sequestration. Despite these limitations, however, the SFC system remains an important carbon sink. The deliberate retention of shade trees, maintenance of tree cover, and integration of native species provide meaningful carbon-sequestration potential. This underscores the ecological value of SFC systems and highlights the opportunity for enhancing carbon storage through targeted, sustainable management practices.

To improve carbon sequestration in the SFC system of Diga district, coffee growers should prioritize the preservation of high-biomass native species such as Albizia schimperiana, Syzygium guineense subsp. afromontanum, Prunus africana, and Croton macrostachyus. Promoting optimal thinning intensity to avoid over-removal of canopy trees is equally essential. Encouraging multi-species shade-tree systems, incorporating species with complementary ecological roles such as nitrogen fixation, deep rooting, and rapid growth, rather than relying on a few preferred species, will further strengthen system resilience and carbon storage. Additionally, supporting natural regeneration by minimizing understory clearing and establishing community nurseries to produce seedlings of priority carbon-dense species are vital measures for sustaining and enhancing long-term carbon sequestration.

Acknowledgement

Authors are grateful to Dembi Dolo university and Wollega university for providing material support to 1st author during data collection.

Author Contribution

Authors’ contribution: Abdi Geleta: Conceptualization, methodology, field data collection, data curation, formal analysis, and original draft preparation; Fekadu Gurmessa: Methodology, supervision, validation, review and editing of the manuscript; Lijalem Hailu: Biomass and carbon stock calculations, and statistical analysis; Obsa Asefa: Vegetation inventory, and data curation; Emebet Asefa: Validation of results, and data interpretation; and Adugna Temesgen: Literature review and manuscript editing and approved the final version of the manuscript.

Funding

declaration: This research received no funding from any institution.

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ethics statement

The research was ethically approved by the Ethics Committee of Wollega University. All participants were duly informed of their rights and responsibilities and provided explicit written consent prior to their participation.

Moreover, plant specimens were collected for taxonomic identification following the appropriate plant collection guidelines of Oromia Environment, Forest and Climate Change Authorities, and permission was obtained from East Wollega zone Environment, Forest and Climate Change office. Plant specimen identification was made by Fekadu Gurmessa (PhD), a botanist in Wollega University, and voucher specimens are stored in Wollega university teaching herbarium, with voucher number will be provided later.

Clinical Trial Number

Not applicable

Consent to publish

declaration: I, Fekadu Gurmessa, the corresponding author of this manuscript, along with other co-authors, hereby grant permission to Discover Environment Journal to publish the manuscript entitled “Forest Structure and Carbon stock Dynamics under Traditional Coffee farming system in Diga District, Western Ethiopia” upon acceptance.

Consent to participate

declaration: Key informants who participates in this study were informed about the study and voluntarily agreed to take part.

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