# Woody Species Diversity in Traditional Agroforestry Practices of Dellomenna District, Southeastern Ethiopia: Implication for Maintaining Native Woody Species

Authors: Abiot Molla; Gonfa Kewessa
Journal: International Journal of Biodiversity
 (2015)

---

## Abstract

The major impact of humans on forest ecosystems including loss of forest area, habitat fragmentation, and soil degradation leads to losses of biodiversity. These problems can be addressed by integration of agriculture with forests and maintaining the existing forests. This study was initiated to assess woody species diversity of traditional agroforestry practices. Three study sites (Burkitu, Chire, and Erba) were selected based on the presence of agroforestry practice. Forty-eight (48) sample quadrants having an area of 20 m × 20 m, 16 sample quadrants in each study site, were systematically laid using four transect lines at different distance. The diversity of woody species was analyzed by using different diversity indices. A total of 55 woody species belonging to 31 families were identified and documented. There were significantly different (P
<
0.05) among the study Kebeles (peasant associations).Mangifera indica,Entada abyssinica, andCroton macrostachyus were found to have the highest Important Value Index. The results confirmed that traditional agroforestry plays a major role in the conservation of native woody species. However, threats to woody species were observed. Therefore, there is a need to undertake conservation practices before the loss of species.


---

## Body

## 1. Introduction

Agriculture is the main backbone of the economy but also the major occupation of Ethiopian population [1]. Rapid population growth and long history of sedentary agriculture have changed the land use/land cover systems and caused environmental degradation in many developing countries including Ethiopia [2]. Bishaw and Asfaw [3] indicated that population growth and environmental degradation on forest ecosystems lead to loss of forest area, habitat fragmentation, soil degradation, and biodiversity losses. International concern is to find alternative farming systems that are ecologically and economically sustainable as well as culturally acceptable to local communities.Agroforestry is a dynamic ecologically based natural resources management system through integration of trees on farms that diversifies agricultural landscapes and sustains production for increased social, economic, and environmental benefits [4]. Agroforestry systems are known to bring about changes in edaphic, microclimatic, floral, faunal, and other components of the ecosystem through biorecycling of mineral elements, environmental modifications, and changes in floral and faunal composition [5–7]. According to Schroth et al. [8], agroforestry also contributes to biodiversity conservation on a landscape scale in three ways. These are (i) the provision of supplementary secondary habitat for species that tolerate a certain level of disturbance, (ii) the reduction rates of conversion of natural habitat in certain cases, and (iii) the creation of a more benign and permeable “matrix” between habitat remnants compared with less tree-dominated land uses, which may support the integrity of these remnants and the conservation of their populations.There are several types of traditional agroforestry practices in different parts of Ethiopia. Some of the different agroforestry practices include coffee shade tree systems, scattered trees on the farm land, home gardens, woodlots, farm boundary practices, and trees on grazing lands [9, 10]. Adjoining habitats that are more similar to the remnants in terms of structure and floristic composition are the most beneficial to the long-term preservation of biodiversity [8]. In addition to supporting native species of plants and animals, agroforestry areas may contribute to the conservation of biodiversity by increasing the connectivity of populations, communities, and ecological processes in fragmented landscapes [11].Agroforestry systems may maintain considerable intraspecific genetic variation at the landscape level, and this variation is essential for adaptation to changes in environmental conditions [12]. Agroforestry systems serve as in situ conservation areas for many species that farmers value and therefore wish to conserve [13]. The mechanisms by which traditional agroforestry systems contribute to biodiversity have been examined by various authors [8, 14–16]. The same authors indicated that agroforestry plays five major roles in conserving biodiversity: (1) provides habitat for species that can tolerate a certain level of disturbance; (2) helps to preserve germ-plasm of sensitive species; (3) helps to reduce the rates of conversion of natural habitat by providing a more productive, sustainable alternative to traditional agricultural systems that may involve clearing natural habitats; (4) provides connectivity by creating corridors between habitat remnants which may support the integrity of these remnants and the conservation of area-sensitive floral and faunal species; and (5) helps to conserve biological diversity by providing other ecosystem services such as erosion control and water recharge, thereby preventing the degradation and loss of surrounding habitat. Agroforestry practices are the main option to reduce these problems. In the study area (Dellomenna District), farmers have been practicing different traditional agroforestry practices by integrating different woody perennials, crops, and livestock components in their lands. These traditional agroforestry practices constitute perennial and herbaceous plants that may promote biodiversity conservation and socioeconomic alternatives to local communities. However, the contribution of these traditional agroforestry practices on biodiversity conservation has not been studied so far in Dellomenna District. Therefore, this study was initiated to investigate status of woody species diversity in traditional agroforestry practices of Dellomenna District with particular emphasis on maintaining native woody species.


## 2. Materials and Methods

### 2.1. The Study Area

Location. Dellomenna District is one of the districts found in Bale Zone, Southeast Ethiopia. Geographically, it lies between 6°40′–7°10′ N and 39°30′–40° E (Figure 1). The district comprises 14Kebeles with a total area of 461,665 hectares. It is bordered in the west by Harenna-Buluk District, in the east by Berbere and Guradamole Districts, in the North by Goba District, and in the South by Madda Walabu District [17].Figure 1
Map of the study sites in Dellomenna District, Southeastern Ethiopia.Topography and Climate. The area is characterized by flat lands and moderately steep rolling hills with valley bottoms. The altitude of the district ranges within 1000–2500 meters above sea level. It has two agroclimatic zones where 86.7% is“Kolla” (dry, hot tropical climate) while the remaining 13.3% is“Woina Dega” (moist to humid, warm subtropical climate). The rainfall pattern in the area is the bimodal type, that is, middle of March to end of May (short rain season) and September to October (the main rainy season). Annual rainfall ranges within 700–1200 mm. The average temperature for Dellomenna is 18°C [17].Population and Means of Livelihood. The total population of Dellomenna District is 96,161 with a population density of 21 persons/km2 [18]. There are various sources of livelihood and income for local communities living in the district. These includeCoffee arabica, honey,Catha edulis, crops, livestock production, timber, and other nontimber forest products. These products serve either for household consumption or for cash income or both. For example, honey,Catha edulis, and coffee are exclusively for income and field crops and livestock are mainly for household consumption.Land Use. The land use categories of this district are forest, agriculture, grazing land, and settlement [17]. According to Tadesse and Feyera [18], natural forest and woodlands still account for the largest share of the land use types in the district. Despite its large coverage, natural forest in Dellomenna District is under pressure by humans. Agricultural expansion, settlement, overgrazing, forest fire, and intensive management of coffee in the forest are the major threats to the natural forest. Tef (Eragrostis tef (Zucc.) Trotter), maize (Zea mays), sorghum (Sorghum bicolor L.), and haricot bean are the major field crops grown in the district. Fruits like mango (Mangifera indica), banana (Musa species), papaya (Carica papaya), avocado,Annona muricata, andPsidium guajava are common in the area. Vegetables including cabbage, carrot, pepper, onion, Irish potato, and sweet potato (Ipomoea batatas) are also grown in the area [18]. Various types of traditional agroforestry practices are also observed in the area. These include home garden and multipurpose trees on the farm land and farm boundary, agrosilvopastoral and silvopastoral [19].


### 2.2. Data Collection Methods

#### 2.2.1. Sampling Techniques

Systematic sampling methods were employed during the course of this study. The sampling procedures focused on identification of areas having traditional agroforestry practices. Accordingly three study sites were selected: Burkitu, Chire, and ErbaKebele were selected. Finally, based on the topography or the gradient land use systems, four transect lines were aligned at an interval of 500 m in each selected Kebele. On each transect, four quadrats were laid at an interval of 200 m. The first transect line and the first plot were systematically selected.A total of 48 quadrats, 16 quadrats in each selected Kebele, were used for vegetation assessment.Samples of all tree and shrub species encountered during this assessment were collected and recorded in their local names and later converted into scientific name by researchers themselves and by the use of agroforestry database: tree species reference and selection [20], useful trees and shrubs of Ethiopia [21, 22] and Flora of Ethiopia and Eritrea, Edwards et al. [23], Hedberg et al. [24], and Hedberg et al. [25]. For identification of the trees and shrubs that were not identified by researchers and by use of reference materials, expert field identification was made.


#### 2.2.2. Sampling Design

For the assessment of the diversity of woody species in traditional agroforestry practices, all woody species were recorded, and diameters at breast height (DBH, 1.3 m) for all woody species ≥5 cm were measured using a caliper or diameter tape except for coffee [26]. The diameter of coffee shrub was measured at 15 cm aboveground [27]. A quadrat size of 20 × 20 m (400 m2) was used for woody species assessment for diameter ≥5 cm [28]. Within this plot five subplots of 5 × 5 m, at four corners and in the center, were laid for sapling assessment for diameter of 1–5 cm. Within each subplot, again a small five plot of 2 × 2 m was laid in each corner and center for seedling assessment for diameter <1 cm [28]. The dimensions of the quadrats and sampling size coincide with recommended practice in the ecological literature and represent a compromise between recommended practice, accuracy, and practical considerations of time, resources, and effort [28].


### 2.3. Data Analysis

#### 2.3.1. Woody Species Diversity Indices

Woody species diversity was analyzed by using different diversity indices. Shannon diversity index (H
′), Shannon equitability/evenness index (E), species richness (S), and Simpson diversity index (D) were calculated and analyzed. These diversity indices provided important information about rarity and commonness of species in a community. Species richness is the total number of species in the community [29]. It is the oldest and the simplest concept of species diversity.


#### 2.3.2. Shannon-Wiener Diversity Index(
H
′
)

Shannon’s index accounts for both abundance and evenness of the species present. Two components of diversity are combined in the Shannon diversity index: (1) the number of species and (2) equitability or evenness portion of individuals among the species [29, 30]. The Shannon diversity index (H
′) is high when the relative abundance of the different species in the sample is even and is low when few species are more abundant. It is based on the theory that when there is a large number of species with even proportions, the uncertainty that a randomly selected individual belongs to a certain species increases and thus diversity increases. It relates proportional weight of the number of individuals per species to the total number of individuals for all species [31]. The Shannon diversity index is calculated as follows:(1)
H
′
=
-
∑
i
=
1
S
p
i
ln
⁡
p
i
,where H
′ is Shannon diversity index and p
i is proportion of individuals found in the ith species.Value of the index (H
′) usually lies between 1.5 and 3.5, although, in exceptional cases, the value can exceed 4.5 [31]. The larger the H
′ value, the higher the diversity.Evenness (Shannon equitability) index (E) was calculated as described by Kent and Coker [31] to estimate the homogeneous distribution of tree species on farms:(2)
E
=
H
1
H
max
⁡
=
H
1
ln
⁡
S
=
∑
i
=
1
S
p
i
ln
⁡
p
i
ln
⁡
S
with
H
max
⁡
=
=
ln
⁡
S
,where S is the number of species and p
i is proportion of individuals of the ith species or the proportion of the total species. E has values between 0 and 1, with 1 being complete evenness [31]. Usually, Shannon diversity index places most weight on the rare species in the sample [29] and hence Simpson’s diversity (D) was used to include the most abundant species.


#### 2.3.3. Simpson’s Diversity Index(
D
)

Simpson’s diversity index is derived from a probability theory and it is the probability of picking two different species at random [29, 30, 32]. Simpson’s diversity (D) is calculated as (3)
D
=
1
-
∑
p
i
2
,where D is Simpson’s diversity index and p
i is proportion of individuals found in the ith species.Simpson’s diversity index gives relatively little weight to the rare species and more weight to the most abundant species. It ranges in value from 0 (low diversity) to a maximum of (1
-
1
/
S), where S is the number of species [29, 30]. The above indices, which are generally referred to as alpha diversity, indicate richness and evenness of species within a locality, but they do not indicate the identity of the species where it occurs. Hence, variation in composition of woody species among the different land use types (patch forests and agroforestry) was determined by computing Beta diversity. Beta diversity (β) is usually expressed in terms of a similarity index between different habitats in the same geographical area [32].


#### 2.3.4. Similarity Indices(
S
s
)

Similarity indices measure the degree to which the species compositions of different system are alike. Many measures exist for the assessment of similarity or dissimilarity between vegetation samples or quadrats. The Sorensen similarity coefficient is applied to qualitative data and is widely used because it gives more weight to the species that are common to the samples rather than to those that only occur in either sample [31].The Sorensen coefficient of similarity (S
s) is given by the following formula:(4)
S
s
=
2
a
2
a
+
b
+
c
,where S
s is Sorensen similarity coefficient, a is number of species common to both samples, b is number of species distinctive in sample 1, and c is number of species distinctive in sample 2.


#### 2.3.5. Important Value Index

The Important Value Index (IVI) is a composite index based on the relative measures of species frequency, abundance, and dominance [31]. It indicates the significance of species in the system. It is calculated as follows:(5)
IVI
%
=
Relative abundance
+
Relative dominance
+
Relative frequency
,
Relative abundance
=
Number of
individual
s
of woody species
Total number of woody
individual
s
∗
100
,
Relative dominance
=
Dominance of woody species
Total dominance of all woody species
∗
100
,
Relative frequency
=
Frequency of woody species
Frequency of all woody species
∗
100
.


### 2.4. Statistical Analysis

Variation in woody species diversity was tested using one-way ANOVA. Significant differences in mean values for woody species diversity were tested by least significance difference atP
<
0.05. All statistical computations were made using SAS statistical Software version 9.0 [33].


## 2.1. The Study Area

Location. Dellomenna District is one of the districts found in Bale Zone, Southeast Ethiopia. Geographically, it lies between 6°40′–7°10′ N and 39°30′–40° E (Figure 1). The district comprises 14Kebeles with a total area of 461,665 hectares. It is bordered in the west by Harenna-Buluk District, in the east by Berbere and Guradamole Districts, in the North by Goba District, and in the South by Madda Walabu District [17].Figure 1
Map of the study sites in Dellomenna District, Southeastern Ethiopia.Topography and Climate. The area is characterized by flat lands and moderately steep rolling hills with valley bottoms. The altitude of the district ranges within 1000–2500 meters above sea level. It has two agroclimatic zones where 86.7% is“Kolla” (dry, hot tropical climate) while the remaining 13.3% is“Woina Dega” (moist to humid, warm subtropical climate). The rainfall pattern in the area is the bimodal type, that is, middle of March to end of May (short rain season) and September to October (the main rainy season). Annual rainfall ranges within 700–1200 mm. The average temperature for Dellomenna is 18°C [17].Population and Means of Livelihood. The total population of Dellomenna District is 96,161 with a population density of 21 persons/km2 [18]. There are various sources of livelihood and income for local communities living in the district. These includeCoffee arabica, honey,Catha edulis, crops, livestock production, timber, and other nontimber forest products. These products serve either for household consumption or for cash income or both. For example, honey,Catha edulis, and coffee are exclusively for income and field crops and livestock are mainly for household consumption.Land Use. The land use categories of this district are forest, agriculture, grazing land, and settlement [17]. According to Tadesse and Feyera [18], natural forest and woodlands still account for the largest share of the land use types in the district. Despite its large coverage, natural forest in Dellomenna District is under pressure by humans. Agricultural expansion, settlement, overgrazing, forest fire, and intensive management of coffee in the forest are the major threats to the natural forest. Tef (Eragrostis tef (Zucc.) Trotter), maize (Zea mays), sorghum (Sorghum bicolor L.), and haricot bean are the major field crops grown in the district. Fruits like mango (Mangifera indica), banana (Musa species), papaya (Carica papaya), avocado,Annona muricata, andPsidium guajava are common in the area. Vegetables including cabbage, carrot, pepper, onion, Irish potato, and sweet potato (Ipomoea batatas) are also grown in the area [18]. Various types of traditional agroforestry practices are also observed in the area. These include home garden and multipurpose trees on the farm land and farm boundary, agrosilvopastoral and silvopastoral [19].


## 2.2. Data Collection Methods

### 2.2.1. Sampling Techniques

Systematic sampling methods were employed during the course of this study. The sampling procedures focused on identification of areas having traditional agroforestry practices. Accordingly three study sites were selected: Burkitu, Chire, and ErbaKebele were selected. Finally, based on the topography or the gradient land use systems, four transect lines were aligned at an interval of 500 m in each selected Kebele. On each transect, four quadrats were laid at an interval of 200 m. The first transect line and the first plot were systematically selected.A total of 48 quadrats, 16 quadrats in each selected Kebele, were used for vegetation assessment.Samples of all tree and shrub species encountered during this assessment were collected and recorded in their local names and later converted into scientific name by researchers themselves and by the use of agroforestry database: tree species reference and selection [20], useful trees and shrubs of Ethiopia [21, 22] and Flora of Ethiopia and Eritrea, Edwards et al. [23], Hedberg et al. [24], and Hedberg et al. [25]. For identification of the trees and shrubs that were not identified by researchers and by use of reference materials, expert field identification was made.


### 2.2.2. Sampling Design

For the assessment of the diversity of woody species in traditional agroforestry practices, all woody species were recorded, and diameters at breast height (DBH, 1.3 m) for all woody species ≥5 cm were measured using a caliper or diameter tape except for coffee [26]. The diameter of coffee shrub was measured at 15 cm aboveground [27]. A quadrat size of 20 × 20 m (400 m2) was used for woody species assessment for diameter ≥5 cm [28]. Within this plot five subplots of 5 × 5 m, at four corners and in the center, were laid for sapling assessment for diameter of 1–5 cm. Within each subplot, again a small five plot of 2 × 2 m was laid in each corner and center for seedling assessment for diameter <1 cm [28]. The dimensions of the quadrats and sampling size coincide with recommended practice in the ecological literature and represent a compromise between recommended practice, accuracy, and practical considerations of time, resources, and effort [28].


## 2.2.1. Sampling Techniques

Systematic sampling methods were employed during the course of this study. The sampling procedures focused on identification of areas having traditional agroforestry practices. Accordingly three study sites were selected: Burkitu, Chire, and ErbaKebele were selected. Finally, based on the topography or the gradient land use systems, four transect lines were aligned at an interval of 500 m in each selected Kebele. On each transect, four quadrats were laid at an interval of 200 m. The first transect line and the first plot were systematically selected.A total of 48 quadrats, 16 quadrats in each selected Kebele, were used for vegetation assessment.Samples of all tree and shrub species encountered during this assessment were collected and recorded in their local names and later converted into scientific name by researchers themselves and by the use of agroforestry database: tree species reference and selection [20], useful trees and shrubs of Ethiopia [21, 22] and Flora of Ethiopia and Eritrea, Edwards et al. [23], Hedberg et al. [24], and Hedberg et al. [25]. For identification of the trees and shrubs that were not identified by researchers and by use of reference materials, expert field identification was made.


## 2.2.2. Sampling Design

For the assessment of the diversity of woody species in traditional agroforestry practices, all woody species were recorded, and diameters at breast height (DBH, 1.3 m) for all woody species ≥5 cm were measured using a caliper or diameter tape except for coffee [26]. The diameter of coffee shrub was measured at 15 cm aboveground [27]. A quadrat size of 20 × 20 m (400 m2) was used for woody species assessment for diameter ≥5 cm [28]. Within this plot five subplots of 5 × 5 m, at four corners and in the center, were laid for sapling assessment for diameter of 1–5 cm. Within each subplot, again a small five plot of 2 × 2 m was laid in each corner and center for seedling assessment for diameter <1 cm [28]. The dimensions of the quadrats and sampling size coincide with recommended practice in the ecological literature and represent a compromise between recommended practice, accuracy, and practical considerations of time, resources, and effort [28].


## 2.3. Data Analysis

### 2.3.1. Woody Species Diversity Indices

Woody species diversity was analyzed by using different diversity indices. Shannon diversity index (H
′), Shannon equitability/evenness index (E), species richness (S), and Simpson diversity index (D) were calculated and analyzed. These diversity indices provided important information about rarity and commonness of species in a community. Species richness is the total number of species in the community [29]. It is the oldest and the simplest concept of species diversity.


### 2.3.2. Shannon-Wiener Diversity Index(
H
′
)

Shannon’s index accounts for both abundance and evenness of the species present. Two components of diversity are combined in the Shannon diversity index: (1) the number of species and (2) equitability or evenness portion of individuals among the species [29, 30]. The Shannon diversity index (H
′) is high when the relative abundance of the different species in the sample is even and is low when few species are more abundant. It is based on the theory that when there is a large number of species with even proportions, the uncertainty that a randomly selected individual belongs to a certain species increases and thus diversity increases. It relates proportional weight of the number of individuals per species to the total number of individuals for all species [31]. The Shannon diversity index is calculated as follows:(1)
H
′
=
-
∑
i
=
1
S
p
i
ln
⁡
p
i
,where H
′ is Shannon diversity index and p
i is proportion of individuals found in the ith species.Value of the index (H
′) usually lies between 1.5 and 3.5, although, in exceptional cases, the value can exceed 4.5 [31]. The larger the H
′ value, the higher the diversity.Evenness (Shannon equitability) index (E) was calculated as described by Kent and Coker [31] to estimate the homogeneous distribution of tree species on farms:(2)
E
=
H
1
H
max
⁡
=
H
1
ln
⁡
S
=
∑
i
=
1
S
p
i
ln
⁡
p
i
ln
⁡
S
with
H
max
⁡
=
=
ln
⁡
S
,where S is the number of species and p
i is proportion of individuals of the ith species or the proportion of the total species. E has values between 0 and 1, with 1 being complete evenness [31]. Usually, Shannon diversity index places most weight on the rare species in the sample [29] and hence Simpson’s diversity (D) was used to include the most abundant species.


### 2.3.3. Simpson’s Diversity Index(
D
)

Simpson’s diversity index is derived from a probability theory and it is the probability of picking two different species at random [29, 30, 32]. Simpson’s diversity (D) is calculated as (3)
D
=
1
-
∑
p
i
2
,where D is Simpson’s diversity index and p
i is proportion of individuals found in the ith species.Simpson’s diversity index gives relatively little weight to the rare species and more weight to the most abundant species. It ranges in value from 0 (low diversity) to a maximum of (1
-
1
/
S), where S is the number of species [29, 30]. The above indices, which are generally referred to as alpha diversity, indicate richness and evenness of species within a locality, but they do not indicate the identity of the species where it occurs. Hence, variation in composition of woody species among the different land use types (patch forests and agroforestry) was determined by computing Beta diversity. Beta diversity (β) is usually expressed in terms of a similarity index between different habitats in the same geographical area [32].


### 2.3.4. Similarity Indices(
S
s
)

Similarity indices measure the degree to which the species compositions of different system are alike. Many measures exist for the assessment of similarity or dissimilarity between vegetation samples or quadrats. The Sorensen similarity coefficient is applied to qualitative data and is widely used because it gives more weight to the species that are common to the samples rather than to those that only occur in either sample [31].The Sorensen coefficient of similarity (S
s) is given by the following formula:(4)
S
s
=
2
a
2
a
+
b
+
c
,where S
s is Sorensen similarity coefficient, a is number of species common to both samples, b is number of species distinctive in sample 1, and c is number of species distinctive in sample 2.


### 2.3.5. Important Value Index

The Important Value Index (IVI) is a composite index based on the relative measures of species frequency, abundance, and dominance [31]. It indicates the significance of species in the system. It is calculated as follows:(5)
IVI
%
=
Relative abundance
+
Relative dominance
+
Relative frequency
,
Relative abundance
=
Number of
individual
s
of woody species
Total number of woody
individual
s
∗
100
,
Relative dominance
=
Dominance of woody species
Total dominance of all woody species
∗
100
,
Relative frequency
=
Frequency of woody species
Frequency of all woody species
∗
100
.


## 2.3.1. Woody Species Diversity Indices

Woody species diversity was analyzed by using different diversity indices. Shannon diversity index (H
′), Shannon equitability/evenness index (E), species richness (S), and Simpson diversity index (D) were calculated and analyzed. These diversity indices provided important information about rarity and commonness of species in a community. Species richness is the total number of species in the community [29]. It is the oldest and the simplest concept of species diversity.


## 2.3.2. Shannon-Wiener Diversity Index(
H
′
)

Shannon’s index accounts for both abundance and evenness of the species present. Two components of diversity are combined in the Shannon diversity index: (1) the number of species and (2) equitability or evenness portion of individuals among the species [29, 30]. The Shannon diversity index (H
′) is high when the relative abundance of the different species in the sample is even and is low when few species are more abundant. It is based on the theory that when there is a large number of species with even proportions, the uncertainty that a randomly selected individual belongs to a certain species increases and thus diversity increases. It relates proportional weight of the number of individuals per species to the total number of individuals for all species [31]. The Shannon diversity index is calculated as follows:(1)
H
′
=
-
∑
i
=
1
S
p
i
ln
⁡
p
i
,where H
′ is Shannon diversity index and p
i is proportion of individuals found in the ith species.Value of the index (H
′) usually lies between 1.5 and 3.5, although, in exceptional cases, the value can exceed 4.5 [31]. The larger the H
′ value, the higher the diversity.Evenness (Shannon equitability) index (E) was calculated as described by Kent and Coker [31] to estimate the homogeneous distribution of tree species on farms:(2)
E
=
H
1
H
max
⁡
=
H
1
ln
⁡
S
=
∑
i
=
1
S
p
i
ln
⁡
p
i
ln
⁡
S
with
H
max
⁡
=
=
ln
⁡
S
,where S is the number of species and p
i is proportion of individuals of the ith species or the proportion of the total species. E has values between 0 and 1, with 1 being complete evenness [31]. Usually, Shannon diversity index places most weight on the rare species in the sample [29] and hence Simpson’s diversity (D) was used to include the most abundant species.


## 2.3.3. Simpson’s Diversity Index(
D
)

Simpson’s diversity index is derived from a probability theory and it is the probability of picking two different species at random [29, 30, 32]. Simpson’s diversity (D) is calculated as (3)
D
=
1
-
∑
p
i
2
,where D is Simpson’s diversity index and p
i is proportion of individuals found in the ith species.Simpson’s diversity index gives relatively little weight to the rare species and more weight to the most abundant species. It ranges in value from 0 (low diversity) to a maximum of (1
-
1
/
S), where S is the number of species [29, 30]. The above indices, which are generally referred to as alpha diversity, indicate richness and evenness of species within a locality, but they do not indicate the identity of the species where it occurs. Hence, variation in composition of woody species among the different land use types (patch forests and agroforestry) was determined by computing Beta diversity. Beta diversity (β) is usually expressed in terms of a similarity index between different habitats in the same geographical area [32].


## 2.3.4. Similarity Indices(
S
s
)

Similarity indices measure the degree to which the species compositions of different system are alike. Many measures exist for the assessment of similarity or dissimilarity between vegetation samples or quadrats. The Sorensen similarity coefficient is applied to qualitative data and is widely used because it gives more weight to the species that are common to the samples rather than to those that only occur in either sample [31].The Sorensen coefficient of similarity (S
s) is given by the following formula:(4)
S
s
=
2
a
2
a
+
b
+
c
,where S
s is Sorensen similarity coefficient, a is number of species common to both samples, b is number of species distinctive in sample 1, and c is number of species distinctive in sample 2.


## 2.3.5. Important Value Index

The Important Value Index (IVI) is a composite index based on the relative measures of species frequency, abundance, and dominance [31]. It indicates the significance of species in the system. It is calculated as follows:(5)
IVI
%
=
Relative abundance
+
Relative dominance
+
Relative frequency
,
Relative abundance
=
Number of
individual
s
of woody species
Total number of woody
individual
s
∗
100
,
Relative dominance
=
Dominance of woody species
Total dominance of all woody species
∗
100
,
Relative frequency
=
Frequency of woody species
Frequency of all woody species
∗
100
.


## 2.4. Statistical Analysis

Variation in woody species diversity was tested using one-way ANOVA. Significant differences in mean values for woody species diversity were tested by least significance difference atP
<
0.05. All statistical computations were made using SAS statistical Software version 9.0 [33].


## 3. Results

### 3.1. Characterizing of the Study Area

The types of traditional agroforestry practices found in the study area included scattered trees, parkland agroforestry, home gardens agroforestry practices, and live fences.In Chire Kebele, home gardens and parkland agroforestry were more common than in Erba and Burkitu. Live fence types of agroforestry were more common in Erba than the other two Kebeles. In Burkitu Kebele, Mango based home garden and scattered trees types of agroforestry practices were common. In each study site, fruit trees likeMangifera indica are dominantly found.


### 3.2. Woody Species Diversity

#### 3.2.1. Woody Species Richness, Abundance, and Frequency

A total of 55 woody species belonging to 31 families were gathered, identified, and recorded in the traditional agroforestry practices of the study sites (see Appendix). Forty-seven (47) (85%) of these species were indigenous while the remaining 8 species (15%) were exotic. Anacardiaceae, Bignoniaceae, and Myrtaceae family had the highest number of woody species (7 each), while Apocynaceae, Cupressaceae, Flacourtiaceae, Meliaceae, Papilionoideae, Proteaceae, Rhamnaceae, Santalaceae, and Sapotaceae families had the lowest number of woody species (2 each). Highest numbers of woody species were recorded at Chire while lowest numbers of species were recorded at Erba (Table1).Table 1
Woody species richness in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Kebele
Number of species (richness)
Rank
Burkitu
33
2
Chire
38
1
Erba
28
3The woody species richness for Chire was significantly (P
=
0.0202) higher than Burkitu and Erba (Table 2). However, there was no significant difference in woody species abundance per plot (P
=
0.7586) among the three Kebeles.Table 2
Mean woody species richness and abundance per plot of traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia.
Kebeles/site
Richness
Abundance
Means (± STD)
Means (± STD)
Burkitu
6.13 ± 1.03ab
34.13 ± 4.84a
Chire
8.75 ± 0.76a
32.13 ± 2.79a
Erba
5.94 ± 0.31b
30.06 ± 3.64a
Overall mean
6.94 ± 1.7
32.1 ± 3.89
Note. Different letter(s) ordered vertically on mean values show a significant difference at P
<
0.05 among the three Kebeles.Out of the total 55 woody species found in the area, the dominantly observed species wereCroton macrostachyus(68.75%) followed byMangifera indica(60.42%) followed byPersea americana(35.42) while 20 species had the lowest frequency (2.08%) (Figure 2).Figure 2
Frequency occurrences of woody species across traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia (for more details see Table10).


#### 3.2.2. Diversity Indices

Shannon-Wiener’s diversity index indicated that Chire Kebele was more diverse than the other two Kebeles (Table3). A similar trend was noticed in terms of Simpson’s diversity index. Shannon evenness (99%) indicated that the highest homogeneity of woody species was found in Chire Kebele compared with the other two Kebeles. The lowest Shannon diversity index, Simpson diversity index, and evenness were recorded in Burkitu Kebele.Table 3
Woody species diversity indices in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Diversity indices
Kebele
Shannon
Simpson
Evenness
Burkitu
2.53
0.90
0.91
Chire
2.73
0.93
0.99
Erba
2.66
0.92
0.96


#### 3.2.3. Sorensen’s Similarity Index of Woody Species

The similarity of woody species maintained in the three study Kebeles was summarized by Sorensen’s similarity index (Table4). Based on the presence and absence of woody species in the sampled plots, the highest similarity in woody species composition was recorded between Burkitu and Erba while the lowest woody species similarity was recorded between Burkitu and Chire.Table 4
Sorensen’s similarity index of woody species in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Kebele
Sorensen’s similarity index (%) land use/site name
Burkitu
Chire
Erba
Burkitu
50.7
55.8
Chire
52.1
ErbaThe Important Value Index (IVI) of all woody species in the study Kebeles is listed in Appendix. The five woody species with the highest IVIs in each study Kebele are given in descending order in Table5. The species with the highest IVI wereCroton macrostachyus andAnnona reticulata in Burkitu,Mangifera indica andCatha edulis in Chire, andM. indica andC. macrostachyus in Erba.Table 5
The five woody species with the highest IVIs in traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia.
Kebele
Scientific name
Important Value Index (IVI in %)
Burkitu
Croton macrostachyus
28.18
Annona reticulata
25.11
Calpurnia aurea
23.1
Mangifera indica
22.00
Casimiroa edulis
20.01
Chire
Mangifera indica
26.38
Catha edulis
22.04
Croton macrostachyus
21.92
Syzygium guineense
19.52
Rhus natalensis
18.69
Erba
Mangifera indica
33.07
Croton macrostachyus
31.61
Entada abyssinica
30.14
Catha edulis
24.05
Rhus natalensis
20.27


## 3.1. Characterizing of the Study Area

The types of traditional agroforestry practices found in the study area included scattered trees, parkland agroforestry, home gardens agroforestry practices, and live fences.In Chire Kebele, home gardens and parkland agroforestry were more common than in Erba and Burkitu. Live fence types of agroforestry were more common in Erba than the other two Kebeles. In Burkitu Kebele, Mango based home garden and scattered trees types of agroforestry practices were common. In each study site, fruit trees likeMangifera indica are dominantly found.


## 3.2. Woody Species Diversity

### 3.2.1. Woody Species Richness, Abundance, and Frequency

A total of 55 woody species belonging to 31 families were gathered, identified, and recorded in the traditional agroforestry practices of the study sites (see Appendix). Forty-seven (47) (85%) of these species were indigenous while the remaining 8 species (15%) were exotic. Anacardiaceae, Bignoniaceae, and Myrtaceae family had the highest number of woody species (7 each), while Apocynaceae, Cupressaceae, Flacourtiaceae, Meliaceae, Papilionoideae, Proteaceae, Rhamnaceae, Santalaceae, and Sapotaceae families had the lowest number of woody species (2 each). Highest numbers of woody species were recorded at Chire while lowest numbers of species were recorded at Erba (Table1).Table 1
Woody species richness in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Kebele
Number of species (richness)
Rank
Burkitu
33
2
Chire
38
1
Erba
28
3The woody species richness for Chire was significantly (P
=
0.0202) higher than Burkitu and Erba (Table 2). However, there was no significant difference in woody species abundance per plot (P
=
0.7586) among the three Kebeles.Table 2
Mean woody species richness and abundance per plot of traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia.
Kebeles/site
Richness
Abundance
Means (± STD)
Means (± STD)
Burkitu
6.13 ± 1.03ab
34.13 ± 4.84a
Chire
8.75 ± 0.76a
32.13 ± 2.79a
Erba
5.94 ± 0.31b
30.06 ± 3.64a
Overall mean
6.94 ± 1.7
32.1 ± 3.89
Note. Different letter(s) ordered vertically on mean values show a significant difference at P
<
0.05 among the three Kebeles.Out of the total 55 woody species found in the area, the dominantly observed species wereCroton macrostachyus(68.75%) followed byMangifera indica(60.42%) followed byPersea americana(35.42) while 20 species had the lowest frequency (2.08%) (Figure 2).Figure 2
Frequency occurrences of woody species across traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia (for more details see Table10).


### 3.2.2. Diversity Indices

Shannon-Wiener’s diversity index indicated that Chire Kebele was more diverse than the other two Kebeles (Table3). A similar trend was noticed in terms of Simpson’s diversity index. Shannon evenness (99%) indicated that the highest homogeneity of woody species was found in Chire Kebele compared with the other two Kebeles. The lowest Shannon diversity index, Simpson diversity index, and evenness were recorded in Burkitu Kebele.Table 3
Woody species diversity indices in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Diversity indices
Kebele
Shannon
Simpson
Evenness
Burkitu
2.53
0.90
0.91
Chire
2.73
0.93
0.99
Erba
2.66
0.92
0.96


### 3.2.3. Sorensen’s Similarity Index of Woody Species

The similarity of woody species maintained in the three study Kebeles was summarized by Sorensen’s similarity index (Table4). Based on the presence and absence of woody species in the sampled plots, the highest similarity in woody species composition was recorded between Burkitu and Erba while the lowest woody species similarity was recorded between Burkitu and Chire.Table 4
Sorensen’s similarity index of woody species in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Kebele
Sorensen’s similarity index (%) land use/site name
Burkitu
Chire
Erba
Burkitu
50.7
55.8
Chire
52.1
ErbaThe Important Value Index (IVI) of all woody species in the study Kebeles is listed in Appendix. The five woody species with the highest IVIs in each study Kebele are given in descending order in Table5. The species with the highest IVI wereCroton macrostachyus andAnnona reticulata in Burkitu,Mangifera indica andCatha edulis in Chire, andM. indica andC. macrostachyus in Erba.Table 5
The five woody species with the highest IVIs in traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia.
Kebele
Scientific name
Important Value Index (IVI in %)
Burkitu
Croton macrostachyus
28.18
Annona reticulata
25.11
Calpurnia aurea
23.1
Mangifera indica
22.00
Casimiroa edulis
20.01
Chire
Mangifera indica
26.38
Catha edulis
22.04
Croton macrostachyus
21.92
Syzygium guineense
19.52
Rhus natalensis
18.69
Erba
Mangifera indica
33.07
Croton macrostachyus
31.61
Entada abyssinica
30.14
Catha edulis
24.05
Rhus natalensis
20.27


## 3.2.1. Woody Species Richness, Abundance, and Frequency

A total of 55 woody species belonging to 31 families were gathered, identified, and recorded in the traditional agroforestry practices of the study sites (see Appendix). Forty-seven (47) (85%) of these species were indigenous while the remaining 8 species (15%) were exotic. Anacardiaceae, Bignoniaceae, and Myrtaceae family had the highest number of woody species (7 each), while Apocynaceae, Cupressaceae, Flacourtiaceae, Meliaceae, Papilionoideae, Proteaceae, Rhamnaceae, Santalaceae, and Sapotaceae families had the lowest number of woody species (2 each). Highest numbers of woody species were recorded at Chire while lowest numbers of species were recorded at Erba (Table1).Table 1
Woody species richness in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Kebele
Number of species (richness)
Rank
Burkitu
33
2
Chire
38
1
Erba
28
3The woody species richness for Chire was significantly (P
=
0.0202) higher than Burkitu and Erba (Table 2). However, there was no significant difference in woody species abundance per plot (P
=
0.7586) among the three Kebeles.Table 2
Mean woody species richness and abundance per plot of traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia.
Kebeles/site
Richness
Abundance
Means (± STD)
Means (± STD)
Burkitu
6.13 ± 1.03ab
34.13 ± 4.84a
Chire
8.75 ± 0.76a
32.13 ± 2.79a
Erba
5.94 ± 0.31b
30.06 ± 3.64a
Overall mean
6.94 ± 1.7
32.1 ± 3.89
Note. Different letter(s) ordered vertically on mean values show a significant difference at P
<
0.05 among the three Kebeles.Out of the total 55 woody species found in the area, the dominantly observed species wereCroton macrostachyus(68.75%) followed byMangifera indica(60.42%) followed byPersea americana(35.42) while 20 species had the lowest frequency (2.08%) (Figure 2).Figure 2
Frequency occurrences of woody species across traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia (for more details see Table10).


## 3.2.2. Diversity Indices

Shannon-Wiener’s diversity index indicated that Chire Kebele was more diverse than the other two Kebeles (Table3). A similar trend was noticed in terms of Simpson’s diversity index. Shannon evenness (99%) indicated that the highest homogeneity of woody species was found in Chire Kebele compared with the other two Kebeles. The lowest Shannon diversity index, Simpson diversity index, and evenness were recorded in Burkitu Kebele.Table 3
Woody species diversity indices in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Diversity indices
Kebele
Shannon
Simpson
Evenness
Burkitu
2.53
0.90
0.91
Chire
2.73
0.93
0.99
Erba
2.66
0.92
0.96


## 3.2.3. Sorensen’s Similarity Index of Woody Species

The similarity of woody species maintained in the three study Kebeles was summarized by Sorensen’s similarity index (Table4). Based on the presence and absence of woody species in the sampled plots, the highest similarity in woody species composition was recorded between Burkitu and Erba while the lowest woody species similarity was recorded between Burkitu and Chire.Table 4
Sorensen’s similarity index of woody species in traditional agroforestry practice in Dellomenna District, Southeastern Ethiopia.
Kebele
Sorensen’s similarity index (%) land use/site name
Burkitu
Chire
Erba
Burkitu
50.7
55.8
Chire
52.1
ErbaThe Important Value Index (IVI) of all woody species in the study Kebeles is listed in Appendix. The five woody species with the highest IVIs in each study Kebele are given in descending order in Table5. The species with the highest IVI wereCroton macrostachyus andAnnona reticulata in Burkitu,Mangifera indica andCatha edulis in Chire, andM. indica andC. macrostachyus in Erba.Table 5
The five woody species with the highest IVIs in traditional agroforestry practices in Dellomenna District, Southeastern Ethiopia.
Kebele
Scientific name
Important Value Index (IVI in %)
Burkitu
Croton macrostachyus
28.18
Annona reticulata
25.11
Calpurnia aurea
23.1
Mangifera indica
22.00
Casimiroa edulis
20.01
Chire
Mangifera indica
26.38
Catha edulis
22.04
Croton macrostachyus
21.92
Syzygium guineense
19.52
Rhus natalensis
18.69
Erba
Mangifera indica
33.07
Croton macrostachyus
31.61
Entada abyssinica
30.14
Catha edulis
24.05
Rhus natalensis
20.27


## 4. Discussion

Woody Species Composition and Diversity. The highest woody species richness in the Chire traditional agroforestry could be due to its relatively well organized irrigation activities compared with the other study Kebeles. The woody species richness of the study area was comparable with another study in Ethiopia ([34]: 64 woody species from Beseku) and lower than a study in Nicaragua ([35]: 83 tree species). In addition, the woody species richness in this study was lower compared with several other studies: for example, 120 trees and shrubs from Sidama in Southern Ethiopia [10], 459 tree and shrub species around Mt. Kenya in central and eastern Kenya [36], 289 woody plants from suburban areas in Sri Lanka [37], and 122 trees and shrubs from Northeast India [38].The number of woody species per plot recorded in the present study is less when compared with the earlier report of Kindt [39] from Meru, Kenya, in which the average number of species per farm was 54, ranging from 28 to 97. The total and average number of individual woody species per plot recorded in the present study is also higher than similar studies reported from other locations. For example, Kindt et al. [40] reported 16.6 tree species per farm ranging from 15.7 to 17.5 for western Kenya. The higher woody species abundance per plot in the present study could be because woody species abundance largely depends on the planting pattern of the woody species as reported in home gardens of Sidama [10].The variation in woody species richness could be due to site characteristics, management strategy, socioeconomic factors [10], and farmers’ preferences for tree species and functions in different localities [41]. For example, farmers maintained many tree and shrub species for environmental services like soil and water conservation in the drier regions of the West African Sahel [41]. The frequency of distribution of tree species on farms in the present study was variable. As one would expect, tree species with a greater economic or ecological value or both were found to be frequently distributed across the farms.Mangifera indica was the most frequent species occurring in 97% of the sampled farms. It is followed byCroton macrostachyus, Entada abyssinica, and Annona reticulate. The low abundance species could indicate that the population size might be too low to sustain these species within the agroecosystem unless their abundance is increased, as reported by O’Neill et al. [42]. Since tree species diversity is required for the long-term survival of species, tree integration on farms could be one of the areas for conservation.Shannon’s diversity index of woody species in this study in traditional agroforestry systems was comparable to the study on Kerala garden in India, ranging from 1.12 to 3 [43], Tolera [44], who recorded Shannon diversity index, Simpson index, and evenness as 2.22, 0.83, and 0.64, respectively, also comparable to the present study. It is higher than the finding for Sidama home gardens by Abebe [10] and is comparable with the findings in the home gardens of Thailand, which ranges from 1.9 to 2.7 for Shannon index [45].The IVI is an aggregate index that summarizes the density, abundance, and distribution of a species. It measures the overall importance of a species and gives an indication of the ecological success of a species in a particular area. The tree species with the highest IVI recorded in traditional agroforestry wereM. indica, Entada abyssinica, andC. macrostachyus. The IVI values can also be used to prioritize species for conservation, and species with high IVI value need less conservation efforts, whereas those having low IVI value need high conservation effort.


## 5. Conclusion and Recommendations

The results of the present study confirm that traditional agroforestry practices play a major role in the conservation of native woody species likeSyzygium guineense andJuniperus procera which are endemic to Ethiopia and the critically endangered species likeCordia africana andC. macrostachyus. Based on the results obtained from the study, the following recommendations are offered: This study focused mainly on the assessment of the woody species diversity in traditional agroforestry practices; hence, in-depth assessment of all natural habitats is important to quantify the status of native woody species in the area. Creating awareness at the grass roots level about wise utilization of the woody species in the area is crucial in order to prevent the loss of valuable tree species. The governmental and nongovernmental organizations should promote different agroforestry practices to conserve indigenous woody species through circa situm conservation.



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*Source: 643031-2015-12-08.xml*