International Journal of Plant Biology & Research

Woody Species Diversity and Farmers’ Preference of Parkland Agroforestry System in Benishangul Gumuz, Western Ethiopia

Research Article | Open Access

  • 1. Forest and Rangeland Plant Biodiversity Directorate, Assosa Biodiversity Center, Benishangul Gumuz Regional State, Ethiopia
  • 2. Wondo Genet College of Forestry and Natural Resources, Hawassa University, Wondo Genet, Ethiopia
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Corresponding Authors
Addiselem Yasin Forest and Rangeland Plant Biodiversity Directorate, Assosa Biodiversity Center, Benishangul Gumuz Regional State, Ethiopia, Tel: 0913820304/0902

Although there is a wealth of indigenous knowledge on managing parkland woody species, understanding farmers’ strategies on woody species diversity, preference, and purpose of keeping scattered trees with annual crops were insufficiently documented yet. This study was conducted to investigate woody species diversity, farmers’ preferences, and the purpose of keeping scattered trees on farmlands in the Assosa district, Western Ethiopia. Three administrative kebeles were selected purposively. Multi-stage sampling technique was employed to collect the primary data from the sample households. A total of 114 households were randomly selected for species preference and the purpose of keeping trees; of which 59 households were randomly selected proportionally for woody species inventory. Both qualitative and quantitative data were analyzed by using Statistical Package for Social Sciences, Version 20.0, and Microsoft Excel 2010. A total of 31 plant species belonging to 30 genera and 19 families were recorded in the parkland of the study area. Shannon diversity was higher at Selga -22 Ketena-1 than Ketena-2. Selga -20 Ketena-1 has higher species diversity than that of Ketena-2, but with a non-significant difference at (p<0.05). On the contrary, species evenness at Selga -20 Ketena-1 was significantly higher than that of Selga -21 Ketena-2 at (p<0.05). The study revealed that parkland agroforestry practice plays an important role in conserving native woody species and by providing food, income, and a wide range of other products such as fuel wood, construction, fodder, food, and medicinal plants.


Woody species, Shannon diversity, Farmers’ preference, Parkland agroforestry


ADANRMO: Assosa District Agriculture and Natural Resource Management Office; DAs: Development Agents; FGD: Focus Group Discussion; HHs: House Holds; KAs: Kebele Administrations; KI: Key Informants;


Yasin A, Ashine T, Asfaw Z (2022) Woody Species Diversity and Farmers’ Preference of Parkland Agroforestry System in Benishangul Gumuz, Western Ethiopia. Int J Plant Biol Res 10(1): 1131.


Agroforestry is a land use that has been practiced for a long time in many parts of the world [1]. However, the type, composition, and extent vary from place to place because of varied topography, biophysical attributes, and socioeconomic settings [2]. There are many types of traditional agroforestry practices found in different parts of Ethiopia [3]. Based on this, Parkland agroforestry, hedgerow intercropping, multi-strata home gardens, and riparian vegetation are the most noticeable traditional practices across most agroecosystems of the country [4].Woody species in parkland agroforestry practices favor the survival of native woody plants. Consequently, overall woody species diversity in parkland agroforestry is strongly linked to the quality of parkland tree structure [5].

In parkland agroforestry practice, specific characteristics of tree species are very important for the selection of species to be planted on the farmland following certain criteria ranging between the utility, drought resistance nature of the species, compatibility with crop elements, and potential for improvement of soil fertility[6]. Moreover, understanding the roles of trees on farms and diversification of the farm in terms of species richness, as well as evenness through increasing the number of trees of rare species, or through replacement of more indigenous species, are the best options for preventing the degradation of agroforest ecosystems on farms [7].

Some studies have been carried out in different parts of the country about parkland woody species diversity [8]. Framers in the Assosa district of Western Ethiopia have a wealth of indigenous knowledge on the management of parkland agroforestry systems particularly woody and non-woody plant diversity. Despite this, understanding farmers’ strategies in the woody species diversity and farmers’ preference for parkland agroforestry systems are insufficiently documented. Therefore, this study investigated woody species diversity and farmers’ preference in parkland agroforestry practice in the Assosa district, Western Ethiopia.


The study was carried out in Assosa District, Benishangul Gumuz Regional State, Western Ethiopia. The district is geographically located from 9º 42’ 0’’ to 10º 12’ 0’’ N latitude and 34º 12’ 0’’ to 34º 42’ 0’’ E longitude (Figure 1) and at a distance of 687km from the capital Addis Ababa. Assosa district has 74 kebeles; 66.22 % (49 kebeles) of the kebele practice parkland agroforestry while, the other 33.78% (25 kebeles) depend on daily labors, shifting cultivation, monoculture, trade, traditional mining, etc [9].

Figure 1: Map of the study area

The total population of Benishangul Gumuz Region is 460,459 with a population density of 9 persons/Km2 . Assosa zone, one of the three zones and two special districts in the region, has a total area of 1,519 Km2 and a population of 28, 970 (population density of 19.1 persons/Km2 ) [10]. The topography of the area is characterized by undulating elevation, which decreases gradually towards the western part to an average altitude of 500m along Ethiopia -Sudanese border [11]. Assosa district is characterized by an elevation range of 1300 to 1470 m above sea level [12]. The climate of the area is sub-humid with mean minimum and maximum temperatures of 14.4 and 28.5o C, respectively. Assosa has a mono-modal rainfall pattern from the end of April to October with an average annual rainfall of approximately 1291.2 mm [12].

Soils of the study area are characterized by very low organic carbon and nitrogen Content, an indicator of low soil fertility status. The low nutrient status of the soils is constrained by the limited use of both organic and inorganic fertilizers and the loss of nutrients through leaching [12].Subsistence agriculture is the major economic activity, engaging approximately 80% of the population. Major crops are millet, sorghum, maize, sesame, cotton, soybean, coffee, and mango. These crops are produced by rain-fed and, to some extent in irrigated agriculture [11].

Sampling Techniques and Sample Size Determination

Multi-stage sampling technique was employed to collect the primary data from the sample households. In the first stage, to select sample kebeles out of all kebeles within the district, prior information (biophysical attributes and agroforestry practice) was collected from possible sources at the district level. In the next stage, out of 49 kebeles within the district, three kebeles were selected purposively based on the existence of parkland agroforestry practice [9], namely, Selga-20, Selga-21, and Selga-22. Finally, two villages were randomly selected from each kebele administration. In this study, the stratification of kebeles/villages was done for different reasons such as to increase the precision of population assessments, to avoid bias, to accommodate different sampling procedures, and to take accurate and reliable data from the field.

The number of sample households was determined by using proportionate random sampling to assess woody species diversity, and farmers’ preference of the local community following simplified formula provided by [13] at a 92 percent of Confident interval.


where, n=the sample size, N=the population size, e= allowed errors which are 8%.

Accordingly, from a total number of kebele households (N=422) Obtained from the Kebele agricultural development office and kebele administration, 114 HHs were randomly selected using a simple random sampling technique and a total number of households from which sample size determined in each KAs (villages) were from Selga-20 kebele 221 HHs (Ketena 1 = 112, Ketena 2= 109), Selga-21kebele 98HHs (Ketena 2= 48, Ketena 3=50) and Selga-22 kebele 103HHs (Ketena 1 =47, Ketena 2= 56). In this study, Ketena/Village is defined as the smallest sub-unit of kebele, which has many sub-units called ‘’Gots’’. 422 (N) households in sampled Kebeles were the target households of the study.

To determine the sample household size in each Kebele, the proportional sampling formula was used.


where, n1= sample household size in Kebele Administration (KA)1, N1= is the total household in KAs 1, n= is a total sampled household from the three KAs and N= is the total households in the three kebele. Hence, from Selga-20 kebele 59 (Ketena 1=30, Ketena 2 =29) HHs, from Selga- 21 kebele 27 (Ketena 2 = 13, Ketena 3 = 14) HHs, and from Selga-22 kebele 28 (Ketena 1=13, Ketena 2=15) HHs were randomly selected proportionally based on the number of households heads residing in each Kebeles.

Data Collection Methods

For this study, both primary and secondary data were used to achieve the desired objectives. Primary data were collected using household surveys, Key informant interviews, Focus group discussions, and field inventory of woody plants. Secondary data were collected from thesis inputs, books, journal articles, census records, literature reviews, and annual activity reports from relevant offices to supplement the information obtained from the primary sources.

In this study key informants (KIs) are defined as persons who are knowledgeable about woody species and changes in local conditions, and village households and who have continuously lived for a long period in the villages. The selection of the key informants was done following the snowball method [14]. To select individual household heads that could identify KIs, a village tour was made with development agents (DAs). During the village tour, knowledgeable five household heads were purposively requested to give the names of seven KIs at each KA, out of 35 KIs suggested, five top rankings were selected from each KAs. The purpose of selecting KIs was to classify households into those practicing parkland agroforestry or not.

Besides, they were also provided information based on a checklist prepared about the historical background of households, species use, and farmers’ preference for parkland trees and on local names of woody species in smallholder parkland agroforestry systems in the study area. This information was later used for developing a questionnaire for verification, to conduct a household questionnaire survey, the total number of households in each selected kebeles was obtained from the kebele administration office and crosschecked with KIs at each kebele for its inclusiveness. Then households were classified into those practicing parkland agroforestry by using KIs and individual household heads from each kebele were selected by using a proportionally random sampling technique on sample size determined by [13].

A questionnaire on woody species preferences and uses of parkland agroforestry was developed and pre-tested on 12 randomly selected farmers from each KA. To verify the information that was collected during the discussion with KIs and to verify the quality of the questionnaire. The data collection was done by employing six enumerators before the survey work. The enumerators were trained to provide them with skills on how to approach individual households during the interview and handle information based on the questionnaires. Finally, the survey questionnaire sheets from the households and the data from the field inventory were checked and collected from each study kebele and made ready for analysis.

Focus group discussion was held to supplement and confirm information generated in the household questionnaire and indepth interviews were conducted with knowledgeable people about the ground situation. During information gathering, focus group discussion was carried out with 8-10 members per study area.

Woody species inventory was performed in May 2021; data were recorded on the farmers’ preferences, plant use, and number and abundance of woody species from the parklands of sampled households. Inventory of woody species was conducted by using quadrats with 50m*100m sample plot sizes on selected households’ parklands as being more suitable for minimum density of woody species in those areas following [15]. The sample plots were established on 59 randomly selected households practicing parklands in the study area. All tree/shrub species found in sample plots were counted for species abundance. Plant identification was carried out and the nomenclature of species was according to [16].

Data Analysis

Both qualitative and quantitative data were analyzed. The quantitative data were first summarized, tallied and coded, and processed, and were analyzed using Statistical Package for Social Sciences, Version 20.0 and Microsoft Excel 2010. The data obtained from the diversity indices were compared using oneway ANOVA. When the ANOVA showed significant differences, Tukey’s test was used to compare whether there was a significant mean difference in tree species diversity among villages. Descriptive statistics were also used to present the results.

The Shannon-diversity index (H’) was calculated, to analyze the diversity of tree/shrub species per parkland and it was calculated as follows:


where, H’=Shannon-Wiener diversity index, S=number of species, i=1, 2, 3…s, pi=Proportion of individuals or the abundance of the i th species expressed as a proportion of the total cover and ln is the natural logarithm (log to the base of e). Values of the index (H’) usually lie between 1.5 and 3.5, although in exceptional cases, the value can exceed 4.5 [17].

The evenness index (E) is calculated to estimate the homogeneous distribution of woody species on parklands. The evenness (Shannon equitability) index (E) was calculated as follows:

E=\frac{H^{'}}{H max}=\frac{H^{'}}{In(s)}=-\frac{\sum_{i=1}^{s}pilnpi}{In(s)}

with Hmax=InS (species diversity under maximum equitability conditions).

Where, S=the number of species, pi=proportion of individuals of the ith species or the abundance of the ith species expressed as a proportion of the total abundance. Thus, the measure of evenness (E) is the ratio of observed diversity to the maximum possible diversity. Evenness has values between 0 and 1, where 1 represents a situation in which all species are equally abundant [18].Simpson’s diversity index (D) is the probability of picking two organisms at random which are of different species [19].

Simpson’s diversity (D) was calculated as follows:

D=1-D=1-\left ( \frac{\sum n(n-1)}{N(N-1)} \right )

where D = Simpson’s index, n = the total number of organisms of a particular species

N = the total number of organisms of all species

In the end, the diversity index was converted to true diversity (effective number of species in the parklands) were calculated as follows:


where, TD = true diversity, e = base of natural logarithm (e =2.718), H= Shannon diversity index.



Floristic Composition of Plant Species

A total of 31 plant species belonging to 30 genera and 19 families were recorded in the parkland of the study area.

Where, Local names: Amharic; Establishment methods: P-planted, NR-Naturally Regenerated; Life form/habit: T- Tree, S- Shrub; Origin: Ind- Indigenous, Ex - Exotic; Uses: BH=bee hive, Ch=charcoal, Cm=construction material, Fo=fodder, F=food, Fr=fruit, Fw=fuel wood, Is=income source, M=medicine, Lf=live fence, Sf=soil fertility, Sc= Soil conservation, Sh=shade; Source: For life forms and Origin [16].

Woody Species Abundance, Richness, and Diversity

Note: Small letters following vertical mean values indicate a significant difference (P<0.05) between villages.

Woody Species Preference and Purpose of keeping

Concerning tree species preference, farmers in the study area grow trees for different purposes and no particular tree species can be regarded as being best for all requirements of the household. The choice of tree species depends on the benefits that can be drawn from keeping the trees on farmlands [20, 21].

Note:- Relative score was calculated by multiplying the number of respondents in each rank by its proportion e.g. (3*(3/114)).


Floristic Composition of Plant Species

Among the 31 plant species recorded, trees constituted 70.97% while 29.03% were shrubs. Of the recorded plant species, 74.19% were native species and the remaining 25.81% were exotic species (Table 1). This result indicates the effectiveness of parkland agroforestry practices for conserving native flora. HH respondents stated that about 48.39% of the woody species were naturally regenerated or retained while 38.7% were artificially planted and 12.9% were both planted and naturally regenerated/ retained on the parklands (Table 1).

Table 1. List of the recorded species and uses in the Assosa district.
Scientific Name Local Name (Amharic) Family Source Habit Origin Uses
Acacia abyssinica Hochst. Gerar Fabaceae NR T Ind Fw, Sh, Ch
Albizia gummifera (J. F. Gmel.) C. A. Sm. Sesa Fabaceae NR T Ind Bh, Cm, Sh, Is
Casimiroa edulis La Llave Kazmier Rutaceae P T Ex Fr, Fw, Is
Catha edulis (Vahl) Forssk. ex Endl. Chat Celastraceae P S Ind Is, M
Citrus aurantifolia (Christm.) Swingle Lomi Rutaceae P S Ex Fr,Is, M
Coffea arabica L. Buna Rubiaceae P S Ind Is, Fw,M
Combretum aculeatum Vent. Zenfok Combretaceae NR/R T Ind Fw, Sh, Ch
Combretum molle R. Br. ex G. Don Baguri/Abalo Combretaceae NR T Ind Ch, Is, Fw, Sh, Fo
Cordia africana Lam. Wanza Boraginaceae P &NR T Ind Bh,Cm,Fw, Sh,Sc,Sf,Is
Croton macrostachyus Del. Besana Euphorbiaceae R T Ind Bh, Cm, Ch, Fw, Sh
Discopodium penninervium Hochst Ameraro Solanaceae P&NR T Ind Fw,Ch,Cm,Is,Sc
Dombeya torrida (J.F.Gmel.) Bamps Wulkeffa Sterculiaceae NR T Ind Cm,Fw,Sf, Sh
Eucalyptus camaldulensis Dehnh. Key-baher zaf Myrtaceae P T Ex Fw,Cm,Is
Ficus sycomorus L. Shola Moraceae NR T Ind Sh, Bh, Sf,Sc,Fr
Gardenia volkensii K.Schum. Gambelo Rubiaceae NR T Ind Fw
Grevillea robusta R. Br. Geravila Proteaceae P T Ex Cm,Fw,Is,Sc,Sh
Grewia ferruginea Hochst. Ex. A. Rich. Lenquwata Tiliaceae NR S Ind Fw,Sf,Sc
Jatropha curcas L. Ye-ferenji Gulo Euphorbiaceae P S Ex Lf,Sf,Sc
Mangifera indica L. Mango Anacardiaceae P T Ex Fr, Fw, Is, Sh,Sf,Sc
Melia azedarach L. Mimi Meliaceae P T Ex Fw,Cm,M,Fo,Sh, Bh
Oxytenanthera abyssinica (A.Rich.) Kerkha Poaceae P T Ind Cm,F,Fw, Is
Piliostigma thonningii (Schumach.) Milne-Redh. Redh. Y-kola Wanza Fabaceae NR T Ind Fw, Sh,Sf,Sc
Psidium guajava L. Zeituna Myrtaceae P T Ex Fr, Fw, Is
Rhamnus prinoides L’Herit. Gesho Rhamnaceae P S Ind Is, Fw,M
Senna didymobotrya (Fresen.) Irwin & Barneby Digta Fabaceae NR S Ind Fw,Sf,Sc,
Sesbania sesban (L.) Merr. Sesbania Fabaceae P&NR S Ind Fo,Fw,Cm,Sf,Sc
Stereospermum kunthianum Cham Washint/ Zana Bignoniaceae NR T Ind Fw,Sh,Cm,Sf
Syzygium guineense (Willd.) DC. Dokma Myrtaceae NR T Ind Fr, Fw, Sh,Sf
Terminalia brownii Fresen. Korasuma/Weyeba Combretaceae NR T Ind Fo,Fw,CH,Sh,Sc
Vernonia amygdalina Del Gerawa Gerawa P S Ind Fw, Fo, Lf, M
Ziziphus mucronata Willd. Kurkura Rhamnaceae NR T Ind Bh,Ch,Fw,Fr,Sh


This finding is higher than that of [22] who reported 16 tree species in the parklands of Hawassa Zuria, Ethiopia; [23] who reported 15 tree species in croplands of Tigray Region, Ethiopia. In contrast, this result is lower than the finding of [24] who recorded 39 tree species on croplands of North Western Ethiopia. Among 19 plant families, Fabaceae (5) was the most dominant followed by Combretaceae (3), Myrtaceae (3), Euphorbiaceae (2), and Rhamnaceae (2), while the remaining were represented by a single species. This finding is in line with the finding of [25] who reported a similar result in the West Shoa Zone, Oromia Regional State, Ethiopia. Farmers in the study area planted or retained different plant species in their land holdings to fulfill the demands of various products and services such as construction material, food, shade, bee forage, soil fertility improvement, fuel wood, medicine, and income source (Table 1).

Woody Species Abundance, Richness, and Diversity

A comparison of mean values showed that the highest and the lowest species abundance were found at Selga-22 ketena-2 and Selga-20 ketena-1 respectively, but with a non-significant difference at (p<0.05) (Table 2). The mean value of species richness of parkland agroforestry woody species showed a slight difference among villages (Table 2). However, the highest and the lowest species richness were recorded in parklands of Selga -22 ketena-2 and Selga -20 ketena-1respectively, but With nonsignificant difference at (p<0.05) (Table 2).

Table 2. Mean (±Std) of species abundance, richness, and diversity indices of tree species in parkland agroforestry at village level (n=59).
Study Areas Villages Species Abundance Species Richness Diversity index value True Diversity
Simpson's Diversity Shannon Diversity Species Evenness
Selga-20 Ketena-1 15.80±12.35 5.13±1.41 0.73±0.16 1.31±0.35 0.54±0.17^{a} 3.92±1.32
Ketena-2 30.87±36.45 5.27±2.31 0.67±0.18 1.23±0.38 0.44±0.17 3.66±1.36^{a}
Selga-21 Ketena-2 39.43±23.77 5.14±1.86 0.58±0.23 1.12±0.47 0.33±0.15^{a} 3.36±1.43^{b}
Ketena-3 33.14±24.23 5.71±1.98 0.71±0.16 1.39±0.44 0.43±0.14 4.38±1.72
Selga-22 Ketena-1 34.86±17.36 6.43±2.15 0.82±0.06 1.67±0.44 0.50±0.04 5.65±1.74^{a}
Ketena-2 50.63±43.59 7.12±2.53 0.63±0.16 1.29±0.28 0.38±0.15 3.76±1.10
Overall mean 31.47±29.34 5.66±2.07 0.69±0.17 1.32±0.39 0.45±0.16 4.02±1.51

Woody species diversity also varies from village to village, for instance at Selga -22 Shannon diversity was higher at Ketena-1 than Ketena-2 and also in Selga -20 Ketena-1 has higher species diversity than that of Ketena-2, but it was non-significant (p0.05) (Table 2).

On contrary, species evenness at Selga -20 Ketena-1 was significantly higher than that of Selga -21 Ketena-2 at (p<0.05) (Table 2). True species diversity at Selga -22 Ketena-1 was significantly higher than that of Selga -20 Ketena-2 and Selga-21 ketena-2 (P<0.05) (Table 2). True species diversity in Selga -20 Ketena-2 also showed significantly higher than that of Selga -21 ketena-2 (P<0.05) (Table 2). The finding suggested that as species diversity increases the true species diversity also increases.

Woody Species Preference and Purpose of keeping

According to Household respondents, the choice of trees for the parkland agroforestry system depends upon the purpose of the farmer whether to grow them for economical or ecological use. This finding is consistent with the finding of [21] who reported farmers to have planting or protecting trees in a specific case, they nearly always fulfill several functions simultaneously in India [20] also reported woody species preference depends on the benefit that can be drawn from keeping the tree in parklands agroforestry in Ethiopia.

The retaining of woody species in parkland agroforestry practices depends on farmers’ preferences. To evaluate farmers’ species preferences, respondents were asked to rank the five most important woody species among the species found in their parklands, and then the total relative score was calculated. Farmers selected indigenous and multi-purpose woody species in the order of Accordingly, Cordia Africana Lam. Mangifera indica L., Oxytenanthera abyssinica (A.Rich.), Eucalyptus camaldulensis Dehnh., Grevillea robusta R. Br., Ziziphus mucronata Willd, Melia azedarach L., Sesbania sesban (L.) Merr. Albizia gummifera (J. F. Gmel.) C. A. Sm., Syzygium guineense (Willd.) DC, Terminalia brownii Fresen., Combretum molle R. Br. ex G. Don, Ficus sycomorus L., Dombeya torrida (J.F.Gmel.) Bamps and Stereospermum kunthianum Cham. were listed by the HH respondents (Table 3).

Table 3. Woody species preference ranking of parkland agroforestry practice in the study area (N=114).
Species Name Respondents Relative score Total Score Rank
1^{st} 2^{nd} 3^{rd} 4^{th} 5^{th} 1^{st} 2^{nd} 3^{rd} 4^{th} 5^{th}
Ziziphus mucronata 3 - - - 10 0.08 - - - 1.61 1.69 6
Cordia africana 56 8 2 7 - 27.51 0.69 0.06 0.55 - 28.81 1
Mangifera indica 22 17 21 23 - 4.25 3.14 6.3 5.94 - 19.63 2
Ficus sycomorus - 2 - - - - 0.04 - - - 0.04 13
Albizia gummifera 1 5 1 3 5 0.01 0.27 0.01 0.10 0.40 0.79 9
Terminalia brownie 4 - 2 1 4 0.14 - 0.06 0.01 0.26 0.47 11
Combretum molle - 4 - 3 1 - 0.17 - 0.10 0.02 0.29 12
Syzygium guineense - 1 - 1 6 - 0.01 - 0.01 0.58 0.60 10
Melia azedarach 3 2 6 8 3 0.08 0.04 0.51 0.72 0.15 1.50 7
Stereospermum kunthianum - 1 - - - - 0.011 - - - 0.011 15
Eucalyptus camaldulensis 5 26 11 9 4 0.22 7.35 1.73 0.91 0.26 10.46 4
Grevillea robusta 4 6 7 5 9 0.14 0.39 0.7 0.28 1.31 2.82 5
Oxytenanthera abyssinica 11 20 18 22 13 1.06 4.35 4.63 5.44 2.73 18.20 3
Sesbania sesban 5 - 2 7 6 0.22 - 0.06 0.55 0.58 1.41 8
Dombeya torrida - - - - 1 - - - - 0.02 0.02 14
Total 114 92 70 89 62              

This finding is in line with the findings of [26, 27, 28] who reported reasons for retaining/planting different woody species depend on the tangible uses and services that they render to the household.



This study found a total of 31 woody species belonging to 30 genera, and 19 families were identified in the parkland agroforestry practice of the study site. Parkland agroforestry in the study area plays a major role in the conservation of woody species. The mean value of the Shannon diversity index of parkland agroforestry woody species showed a slight difference among villages. However, the highest and the lowest Shannon diversity index were recorded in parklands of Selga -22 ketena-1 and Selga -2 ketena-2 respectively. There was significant variation in species evenness and true diversity indices among villages. The variation may be attributed to the interest of farmers, land size, agro-climatic conditions, and characteristics of the woody species. In the study area, woody species preference depends on the contribution to household livelihoods and compatibility with food crops. It is concluded that the parkland agroforestry system of the study area provides goods and services for local livelihoods, is essential for the conservation of woody species diversity which complements the natural forests; and helps to counteract the loss of woody species from the natural forest. Further studies should be examined in the study area concerning the role of parkland wood species in climate change adaptation and mitigation and interested donor agencies should be promoted in terms of carbon trading.


We are grateful to thank Mr. Dereje Mosissa from Ethiopian Biodiversity Institute Assosa Biodiversity Center who gave us unreserved technical support in the whole process of our research work especially during data collection, processing and analysis. Special thanks also goes to farmers of Assosa district and kebele experts who played a substantial role in providing information and for their unreserved support during data collection for this work.


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Received : 11 Nov 2022
Accepted : 12 Dec 2022
Published : 15 Dec 2022
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