Density of wild animal populations and their conflicts with nearby farmers in southwest Ethiopia, Mankira Forest

doi:10.21203/rs.3.rs-4725148/v1

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Density of wild animal populations and their conflicts with nearby farmers in southwest Ethiopia, Mankira Forest

https://doi.org/10.21203/rs.3.rs-4725148/v1

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Farmers' survival is seriously threatened by wild animal species' coexistence and joint use of limited resources. A study on the density of wild animals and their conflicts with nearby farmers was conducted from December 2022 to May 2023 in southwest Ethiopia, Mankira Forest. Using the distance sampling technique, the densities of the wild animal population were estimated. The incidence of conflict between humans and wild animals was measured using a questionnaire given to 241 randomly selected household heads. The estimated densities of spotted hyenas (0.40 ± 0.54), Anubis baboons (11.83 ± 4.4), grivet monkeys (15.18 ± 5.12), black-backed jackals (0.60 ± 0.14), porcupines (0.70 ± 0.12), and warthogs (1.2 ± 0.20 individuals/km²) were recorded. Potatoes, wheat, and maize were the most severely damaged cereal crops. The most prevalent and top-ranked crop-raiding species was the Anubis baboon (N = 104, 43%), which was followed by the grivet monkey (N = 82), the warthog (N = 31), and the porcupine (N = 24). Depredated livestock were cattle, poultry, sheep, donkeys, dogs, horses, and mules. The spotted hyena (N = 118), black-backed jackal (N = 65), primates (N = 39), and leopard (N = 19) were the most commonly recorded predators. Various human activities that impact wildlife include deforestation, charcoal production, livestock grazing, agricultural expansion, and settlement. Guarding was the primary mitigating strategy. Locals living near forest boundaries were particularly susceptible to the impact of wild animals. Reducing livestock damage and crop loss can be achieved through continuous ecological surveying of wild animals and raising community awareness.

Conflict mitigation

Crop damage

Livestock predation

Population estimation

Resolving conflicts between humans and animals and keeping an eye on the state of animal conservation depend on an understanding of the size of mammalian populations and their habitat requirements (Travers et al. 2019). Wildlife experts need to have a solid understanding of the dynamics and population status of the species in question (Plumptre and Cox 2006). Human-wildlife conflict (HWC) is an increasingly prevalent phenomenon in developing and industrialised countries alike, including Africa (Teshome and Girmay 2017; Gemeda and Meles 2018; Tesfaye 2016). It happens when human populations' needs and those of wildlife populations overlap, harming both (Messmer 2000). There will be conflict between animals and the growing human population over scarce resources and space (Madden 2008; Addil et al. 2015). However, since agriculture and livestock are so essential to rural livelihoods in developing countries like Ethiopia, whose economies primarily rely on the subsistence use of natural resources, these countries are more susceptible to conflict (Fairet 2012; Fenta 2014).

Mortality or injury, crop damage, livestock loss, disease transmission, and other intangible social costs surrounding the conserved area are a few instances of the variable nature and extent of HWC (Merkebu and Yazezew 2021). Among the documented wild animals that were categorised as potential domestic animal predators were the spotted hyena (Yirga and Bauer 2010; Ogara et al. 2010; Kebede et al. 2022), leopard (Teshome and Girmay 2017), jackal (Atickem et al. 2017; Mekonen 2020), and lion (Acha and Temesgen 2015). Depending on the species and area, the frequency of predation changes throughout the season (Megaze et al. 2017).

Ethiopia's highlands and some of its lowlands have been turned into pastoral and agricultural fields; in addition, the vegetation has been cleared for agriculture, construction, and fuel wood (Datiko and Bekele 2013). Consequently, wildlife resources typically relocate from their natural habitats to regions of settlement where there is greater human-wildlife conflict (Kumsa and Bekele 2013). Farmers view leopards as one of the most dangerous wildlife species because they feed on livestock and endanger human life (Biset et al. 2019). People typically use poisoning, shooting, and trapping methods, which kill a lot of non-targeted animals and foster a negative attitude about the conservation of wild animals, to tackle this problem (Biset et al. 2019; Derebe et al. 2022).

There are no studies on the population density of wild animals in this forest, like in most other forest areas in the whole country or the coexistence or conflict between humans and wildlife in the Mankira Forest, which is located in the Southwest Regional State of Ethiopia. Data from this study describing the intensity of human-wildlife conflict and its effects, as well as the population density of different wild species, are useful to develop a successful conflict mitigation strategy. It is advantageous to lawmakers, wildlife managers, local communities, and other stakeholders in order to safeguard wildlife and the means of subsistence for farmers who reside near the forest environment. In order to improve the positive coexistence of the local population and wildlife for the benefit of humans and the natural environment, this study aimed to investigate the fundamental scientific information regarding the population density of some wild animals as well as the human-wildlife conflict mitigation strategies used by the local farmers.

Description of the study area

Mankira Forest is located in the Kaffa Zone, Decha district, south-west Ethiopia (Fig. 1). The forest is located between 07^o6’ and 07^o10’N latitude and 36^o6’ and 36^o20’E longitude. The forest is located 12.5 kilometres from Bonga Town, the Kaffa Zone capital, and 461.5 kilometres from Addis Ababa. Six kebeles, or the smallest administrative units in Ethiopia, surround the about 840.88-hectare forest: Budi borders the south, Awasho Kofira lies to the west, Awasho Olla lies to the southwest, Modio Gonbera lies to the north, Gedam lies to the northwest, and Yanga lies to the east of the forest (Fig. 2). The forest is bordered by two rivers: the Atesho River in the northeast and the Gumi River in the west. The landscape of the research area is rugged, with lots of plains, hills, slopes, gorges, and plateaus (RDOKZ 2019).

Based on data collected over a 14-year period (from 2006 to 2019) by ENMA (2019), the study area's mean annual rainfall was around 1328.7 mm, with a range of 1043.4 mm to 1519.1 mm. A long rainy season (June to September) and a brief dry phase (March to May) with showers are the area's defining features. From June to September, the area experiences a unimodal yearly rainfall trend. August experienced a great deal of rainfall; however, December and January had the least amount. November to the end of February is considered to be the comparatively dry season. Data from ENMA (2019) covering 14 years, from 2006 to 2019, indicates that the research area's mean annual maximum and lowest temperature records are 21°C and 18°C, respectively. In March, the average yearly maximum temperature was 19.7°C, while in August; the average yearly minimum temperature was 15.60°C.

Mankira Forest is covered in a variety of flora. The most prevalent plant species in the forest include Juniperus procera, Syzygium guineense, Vernonia amygdalina, Olea welwitschii, Coffea arabica, Cordia africana, Phytolacca dodecandra, Rubuslogano baccus, and a few shrub species (Woldeyes 2000). The faunal species found in the forest area include Phacochoerus africanus, Panthera pardus, Potamochoerus larvatus, Civettictis civetta, Crocuta crocuta, Canis aures, Papio anubis, Hystrix cristata, Chlorocebus aethiops, raptors, and other mixed species of birds (DWAO 2018).

The majority of people in the area are employed in mixed farming, which involves raising both crops and livestock. Hordeum vulgare, Phaseolus vulgaris, Sorghum bicolor, Zea mays, Eragrostis tef, Coffea arabica, and Pisum sativum are the principal crops that are grown in the area. Furthermore, irrigation is used to grow Brassica oleracea, Allium cepa, Beta vulgaris, Solanum tuberosum, and Solanum lycopersicum. Among the common livestock in the area are Bos taurus, Ovis aries, Capra hircus, Equus africanus asinus, and Equus ferus caballus.

Methods

Site selection and sampling design

Mankira Forest was specifically chosen as the study's site because of the significant degree of conflict that exists there between wildlife and humans. Prior to formal data collection, we personally observed and discussed with a few key sources about conflicts between local wild animals and humans. Individual conflicts may occur among individuals who reside near the forest habitat. This study focused on four villages that were purposefully selected due to the forest's close vicinity.

The villages selected were Yetiti, Becha, Bahita, and Gola. A stratified random method of selection was carried out because the areas that were selected varied in terms of the intensity of the conflict and their proximity to the forest habitat. The stratification of the area into homogeneous groups was followed by the implementation of the random sampling approach. Every participant who was chosen at random in the study village was interviewed (Fenta 2014).

Sampling and sample size determination

The purposive sample method was used to choose the communities of respondents who participated in the data collection process. Using a systematic random sampling technique, every fifth person on the list of homes that participated in the questionnaires, interviews, and tangible information collection was selected. Systematic sampling in the study eliminated biassed samples and poor survey results.

The study area is surrounded by the seven villages of Gola, Yetiti, Bahita, Becha, Gechana, Chega, and Arida. However, the first four villages, which lie between 0.5 and 3 kilometres from the forest, were the study's target population. The sample size was established using the probability sampling technique formula (Cochran, 1977) after the total number of households in each of the four villages that were selected (Gola, 185 HH, Yetiti, 124 HH, Bahita, 183 HH, and Becha, 152 HH, totaling 644) was calculated (Table 1).

$$\:{\text{n}}_{\text{o}}=\:\frac{{\text{z}}^{2\:}\text{p}\text{q}}{{\text{d}}^{2}}{\:\:\:\:\:\:\:\:\:\:\:\:\:\text{n}}_{\text{o}}=\frac{{\left(1.96\right)}^{2}\left(0.5\text{*}0.5\right)}{({0.05)}^{2}}=384$$

A finite population adjustment formula was applied since the sample size was greater than 5% of the population size (5% of 644 = 33, which is less than 384).

$$\:{\text{n}}_{1}=\frac{{\text{n}}_{\text{o}}}{1+({\text{n}}_{\text{o}}/\text{N})}{\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\:\text{n}}_{1}=\:\frac{384}{1+(384/644)}\:=\:241$$

Where: $\:{\text{n}}_{\text{o}}$= desired sample size

$\:{\text{n}}_{1}$ = finite population correction factors less than 10,000

Z = standard normal deviation (1.96 for the 95% confidence interval).

P = 0.5 (estimated proportion of the population to be included in the sample, i.e., 50%)

D = degree of desired accuracy (0.05) and q = 1-p (i.e., 0.5)

N = total population of households (644).

The percent of sample size in each village was computed by using C =$\:\:\:\frac{\mathbf{n}}{\mathbf{N}}\times\:100$%, where C = percent of sampled households, n = total number of selected sampled households, and N = total population in the four sample villages$\:.\:\:\mathbf{C}=\frac{241}{644}\times\:100\mathbf{\%}=37.42\mathbf{\%}$. A comparable sample size among the four villages was determined in proportion to their household numbers by using a simple proportion formula adopted from Cochran (1977): n_i = n×$\:\frac{\varvec{N}\varvec{i}}{\varvec{N}}$, I = 1, 2, 3..., n_i = sample size of each village, N_i = total population size in each village, n = total sample size, N = total population size of the four villages.

A sample of 241 respondents was chosen using the calculation mentioned above. After the sample sizes were determined, systematic random sampling techniques were used to choose the respondents from the 644 total populations. For this study, 69 HH from Bahita, 46 HH from Yetiti, 57 HH from Becha, and 69 HH from Gola were selected. Each village has a certain number of sample household heads assigned to it, based on the total number of household heads in each village that was chosen.

Table 1

Sample size from each village
Village	Number of households			The sample size			Percentage
Village	Male	Female	Total	Male	Female	Total	Percentage
Gola	172	13	185	64	5	69	28.63
Yetiti	110	14	124	41	5	46	19.09
Bahita	163	20	183	61	8	69	28.63
Becha	137	15	152	51	6	57	23.65
Total	582	62	644	217	24	241	100.00

Data collection method for population estimation

The study site was divided into two primary habitat sections, including farmland and forest. By employing distance sampling techniques, the study area's wild animal density was calculated. As Buckland et al. (2010) suggested, transect lines were established in each block. An extensive network of eighteen line transects has been established utilizing a stratified random sampling methodology across various habitat types and topographical features.

In some inaccessible areas, transects have been established along existing roads and paths. To estimate the population of wild animals, line transects have been established at random. Ten of the 18 transects were set up in forest habitat, and the remaining eight were in agricultural areas. Poles, natural indicators, and global positioning system (GPS) coordinates were used to draw the transect lines. It was discovered that each transects end locations were sufficiently far away from each forest habitat's margin to minimise the edge effect. The length of transect varied from 2 to 4 km, depending on the type of habitat and the topography of the area. To avoid double counting, consecutive transects were spaced 500 m to 1 km apart. With the villagers' help, they were carefully surveyed concurrently during the wet and dry seasons to maximise the likelihood of encountering seasoned and informed people on both sides of transects. When visibility was good, each transect was inspected twice in the same day, during their active hours of early morning (06:00 to 8:00 h) and late afternoon (17:00–19:00 h). Normal vision, GPS, and 7 × 35 magnifying binoculars were used for walking during the counting period. For walking transects, the average speed was 2 km/h. To reduce any disruptions, a silent detection technique was applied. For every detection, the following details were recorded: time, sighting angle, sighting distance, and observation of wild animals. Following the methods of Buckland et al. (2010), a laser metre was used to measure the distance and angle between the animals and the observer from the centre of the transect line. Group size, sighting angle (θ) between the transect line and the individual or group, and sighting distance (ri), which is the distance from each line transect to the geometric centre of the groups or individuals, were all noted on the data sheet whenever wild animals (individuals or groups) were sighted. Next, the formula x = ri sin (θ) was used to find the perpendicular distance between the animal and the transect line.

Data collection method for human-wild animal conflict

The structured questionnaires were developed in English using information gathered from the literature and the actual situation, and language experts (Kafinoonoo teachers) translated them into the language of the area. Trained data collectors, who were kebele agricultural experts and could both speak and listen to the participants' native tongue, conducted interviews with them in that language. The questionnaires also contained information on the individuals' sociodemographic characteristics.

The purpose of the questionnaire research was to gather information from participating households regarding the factors of human-wildlife conflict and the locals' attitudes towards wildlife conservation. Both closed-ended and open-ended questions were included in the questionnaire. In order to find out more about the wildlife in the area and whether it poses any problems for the people, open-ended questions were included. Prior to the distribution of the questionnaire, the participants were informed about the study's aim, how to fill it out, and how to obtain useful information on the subject.

Data analysis

Data were analyzed by using DISTANCE (Version 6.0, Release 2) and SPSS version 21. DISTANCE Software was used for density and abundance estimation of wild animal populations. Density of primate within the area surveyed (D_g) was estimated as:

$$\:\text{D}\text{g}=\frac{nf\left(0\right)}{2L}$$

where ‘L’ denotes the aggregate length of the transects, ‘n’ is the number of wild animal individual observed and $\:f\left(0\right)$ is the probability density function of observed perpendicular distances evaluated at x = 0. Then, the perpendicular distance from the transect line to the animal is calculated as x = ri sin (θ) (Buckland et al. 2010). In order to compare the degree of conflict in different villages, SPSS software was also used. The impact of wild animals was examined using descriptive statistics, which were expressed as percentages and frequencies of the respondents' sociodemographic and socioeconomic characteristics. A chi-square test was used to determine the significant differences between the communities on attitudes towards wild animals, preventive measures, crop loss, and livestock depredation. The relationship between crop loss, wild animal depredation incidences, and the proximity of villages to forests was examined using Spearman's correlation coefficient.

Wild animal population estimation

The mean spotted hyena population estimates in the present study area were 57 ± 7.96. There were 134 ± 42.33 Anubis baboons, 768 ± 126.23 Grivet monkeys, 89 ± 17.20 porcupines, 58 ± 14.00 Spotted Hyenas, and 93.5 ± 17.23 Black-backed Jackals, respectively. Spotted hyena density estimations ranged from 0.40 ± 0.54 to 1.83 ± 0.40 for Anubis baboons, 5.18 ± 0.85 for grivet monkeys, 0.60 ± 0.14 for black-backed jackals, 0.70 ± 0.12 for porcupines, and 1.2 ± 0.2 for warthogs per km². Table 2 lists the effective strip width, detection probability, and other characteristics. Using different models, a minimal AIC value was determined for each species (Figs. 3–5).

Table 2

The wild animal’s density estimates in Mankira Forest Community Conserved Forest
Wild animal species	Parameter	Estimate	SE	%CV	95% CI	AIC	Model
Spotted hyena	p	0.36	0.35	9.59	0.30–0.44	891.36	HR/Cos
	ESW	36.26	3.4773	9.59	29.99–43.83
	D	0.40	0.54	13.97	0.29–0.51
	N	57.00	7.96	13.97	43.00–76.00
Anubis baboon	p	0.31	0.81	26.19	0.19–0.51	1060.92	HR/Cos
	ESW	18.00	4.7142	26.19	10.82–29.96
	D	1.83	0.40	30.59	0.73–2.45
	N	134.00	42.33	30.59	73.00-245
Grivet monkey	P	0.15	0.16	11.39	0.12–0.18	890.91	HN/Sps
	ESW	9.57	1.09	11.39	7.65–11.96
	D	5.18	0.85	16.44	3.73–7.19
	N	768.00	126.23	16.44	553.00-1068.0
Black-backed jackal	p	0.38	0.91	23.76	0.24–0.61	1616.97	HR/Sps
	ESW	18.43	4.38	23.76	11.61–29.25
	D	0.60	0.14	25.89	0.34–0.92
	N	55.00	14.24	25.89	34.00–92.00
Porcupine	p	0.55	0.23	4.29	0.50–0.59	1112.41	UF/Cos
	ESW	31.94	1.37	4.29	29.35–34.77
	D	0.70	0.12	17.60	0.49–0.99
	N	70.00	12.32	17.60	49.00–99.00
Warthog	p	0.37	0.38	10.28	0.29–0.45	1062.33	NE/Cos
	ESW	21.43	2.20	10.28	17.49–26.25
	D	1.2	0.20	17.49	0.82–1.64
	N	100.00	17.49	17.49	70.00–141.0
Note: Hr/SPs = hazard rate/simple polynomials; Hr/Cos: hazard rate/cosines; UF/Cos: uniform/cosines; Hn/Cos: half normal/cosines; Ne/Cos: negative polynomials/cosines; HN/Sps = half normal/simple polynomials. D = density; N = population; ESW = effective strip width; P = detection probability.

Demographic characteristics of the respondents

Ninety-one percent (N = 217) of the total 241 respondents were male. Of the responses, 9.96% (N = 24) were female. The sex groups of the respondents differ statistically significantly (χ2 = 64.00, df = 1, P < 0.05). The age range of 46–55 comprises the majority of responders (N = 70, 29.1%). 14 percent (N = 35) of the people surveyed had completed primary school, 2 percent (N = 7) had completed secondary school, 34.9% (N = 84) had received informal education and could read and write, and 47.7% (N = 115) were illiterate (Fig. 6).

The primary source of income for the people living close to the Mankira forest was subsistence farming. Approximately 88% (N = 212) of the respondents work in mixed agriculture, which combines beekeeping, crop production, and animal rearing; 6.2% (N = 15) only produce crops; and the other 5.8% (N = 14) combine labour-intensive employment and agriculture (χ2 = 134.48, df = 2, P < 0.05). With a mean of 1.09 ha, the respondents' farmland ranges in size from 0.25 to 3 hectares. Most of the respondents (N = 115, 47.7%) only had one to 1.5 hectares under cultivation. Conversely, 33.6% (N = 81) of the respondents possess less than one hectare of farmland. Others have 1.75–2 ha (N = 28, 11.6%) and > 2 ha (N = 17, 7.1%) of farmland.

Farmlands located less than one kilometre from the forest's edge were owned by the majority of respondents (N = 147, 61%). Conversely, 34.9% (N = 84) of the respondents had agriculture between 1 and 2 km from the forest boundary, while 4.1% (N = 10) of the respondents had farmland farther away. A statistically significant difference was observed between the respondents' farms and the forest (χ2 = 48.86, df = 2, P < 0.05).

The crop varieties most commonly cultivated in this study area were teff, maize, potatoes, wheat, and barley. Around the forest boundary, maize and teff are grown by most respondents (N = 118, 49%); additional crops grown by others include potatoes (18.2%; N = 44), wheat (13.7%); barley (10.4%); and different crops and vegetables (8.7%; N = 21). Statistical significance was not observed for extensively grown crops (χ2 = 14.12, df = 5, p > 0.05).

The community in the study area raised cattle (cow and ox), goats, sheep, and pack animals (donkey and horse). Respondents' animal ownership counts vary from two to sixteen. The main types of cattle raised did not differ statistically significantly across the four villages (χ2 = 138, df = 9, p > 0.05). The overall number of animals held by each household did, however, differ significantly (χ2 = 8, df = 3, p < 0.05).

Wild animals involved in crop raiding and livestock predation

Those who responded stated that black-backed jackals, primates, spotted hyenas and leopards are among the wild animals that prey on livestock. Cattle, poultry, sheep, donkeys, dogs, horses, and mules were among the animals impacted. Among the wild animals involved in crop-raiding are grivet monkeys, porcupines, warthogs, and Anubis baboons. Crop raiders had an impact on the following crops: teff, barely, sorghum, potatoes, and maize. In the current study area, spotted hyenas (N = 118, 49%), black-backed jackals (N = 65, 27%), leopards (N = 19, 8%), and primates (N = 39, 16%) were the animals that preyed on livestock, based on the responses of the respondents. Predators varied significantly in how much livestock they preyed on (χ² = 38.00, df = 3, P < 0.05) (Fig. 7).

The Anubis baboon (N = 104, 43%) was the most common crop raider that damaged crops in all of the villages. The grivet monkey (N = 82, 34%), the warthog (N = 31, 13%), and the porcupine (N = 24, 10%), which are known to raid crops, were some other significant conflict-causing species. Crop damage varied significantly amongst crop raiders (χ² = 30.96, df = 3, P < 0.05). Anubis baboons and grivet monkeys cause damage to crops throughout the growing season, whereas porcupines and warthogs only damage crops early in the ripening stage (Fig. 8).

People who responded from the four villages mentioned different types of impacts caused by people on wildlife. According to the respondents’ responses, deforestation (26.1%), charcoal burning (25.0%), and agricultural expansion (22.4%) are the three major impacts of people on the wildlife in the study area. People's effects on wildlife differed significantly between villages (χ² = 22.76, df = 5, p < 0.05) (Table 3).

Table 3

Impacts of the local people on the wildlife and their forest habitat around the village
	Villages				Frequency	Percent (%)
Anthropogenic impact	Gola	Yetiti	Bahita	Becha
Agricultural expansion	19	11	10	14	54	22.4
Deforestation	15	11	24	13	63	26.1
Charcoal burning	16	10	20	14	60	25.0
Livestock grazing	9	7	5	7	28	11.6
Settlement	10	5	0	6	21	8.7
No response	0	2	10	3	15	6.2
Total	69	46	69	57	241	100

The local farmers are utilizing various crop raiding and livestock predation mitigation techniques to protect the wild animals attack. These were guarding, fencing, chemicals (common for the rodent pests), chasing, smoking, and scarecrow (Table 5, Fig. 9). The four villages' strategies for mitigating the attack by wild animals differed significantly (χ2 = 73.76, df = 5, p < 0.05). The respondents also reported that chasing the wild animals by using dogs, ‘kokeloo’ (the traditional tool used by the community to protect their crops from damage), and stones was another method that prevented the crop and livestock from damage.

Table 5

Crop damage and livestock predation mitigation techniques used by the local farmers
Control methods	Villages				Frequency	Percentage (%)
Control methods	Gola	Yetiti	Bahita	Becha	Frequency	Percentage (%)
Guarding	32	21	33	27	113	46.9
Fencing	12	9	11	10	42	17.4
Chemical	2	0	5	1	8	3.3
Chasing	10	11	8	8	37	15.4
Smoking	6	0	2	5	13	5.4
Scarecrows	7	5	10	6	28	11.6
Total	69	46	69	57	241	100

Estimates of population sizes are essential for understanding the ecology of the entire species, providing reliable data on size fluctuations, and facilitating the tracking of population trends (Wang et. al. 2016; Wang 2010). The type and amount of biotic and abiotic resources that are available to ungulates at different time scales affect their distribution and abundance patterns (Gautam 2013). Therefore, keeping track of the expenses associated with population management initiatives requires accurate population size calculations (Donini et al. 2021).

The current research area's spotted hyena density (0.40 hyenas/km²) was greater than estimates of similar densities elsewhere in Africa.. For instance, spotted hyena densities in Hwange National Park, Zimbabwe, and Etosha National Park, Namibia, were reported by Holekamp and Dloniak (2006) to be 0.07 individuals/km² and Trinkel (2009) to be 0.02 individuals/km², respectively. These densities were lower than those reported by Deneke et al. (2022), which were 1.34 in farmland and 0.55 in forest hyena/km² in Ethiopia. In southern Ethiopia, there was 0.61 and 0.55 hyena/km² (Mesfin et al. 2023). These densities could be affected by fluctuations in the distribution and abundance of prey within the study area. In the current study area, the high number of spotted hyenas may also be explained by the abundance of prey species, accidental or diseased livestock carcasses, and organic wastes originating from humans surrounding the communities. In addition, spotted hyenas consume domestic animals for food. There is a positive correlation between carnivore density and prey abundance (Carbone et al. 2021; Karanth et al. 2004). As litter size and offspring survival rise, the relationship gets stronger (Fuller 2001). Many reasons, such as an abundance of food, a high birth rate, reduced competition for food and space, and less human pressure in the area, may be responsible for the spotted hyena population's great size.

Anubis baboon density was 11.83 individuals/km² for the present study area, which was considerably higher than those estimated by Mesfin et al. (2023) at 3.66 and 5.35 individuals/km² in Ethiopia; Se´gniagbeto et al. (2018) at 0.81 individuals/km² in Togo; and Ajayi et al. (2020) at 0.042 ± 0.000 individuals/km² in Nigeria, but considerably lower than those of Kifner et al. (2022) at 132.5 individuals/km² in Lake Manyara National Park Tanzania. Grivet monkey densities estimated at 15.18 individuals/km² in the current research area are significantly lower than those estimated by Menbere and Balakrishnan (2016) in Ethiopia, which were 133.1 individuals/km², and higher than those of Mesfin et al. (2023) findings of 3.57 and 2.91 individuals/km² in Ethiopia. Grivet monkeys are well-known agricultural pest monkeys that are challenging for guarders to control during flowering times. This could be a result of the farm fields being close to forest and the abundance of trees that give monkeys shelter and help them escape from the guards. They also impose serious harm by hiding among weeds and maize plants. According to the study, Anubis baboons caused the most damage to maize across all study sites, followed by grivet monkeys, and the least amount was damaged by other wild animals. This could be a result of the primates' high intelligence and capacity for social organization, which allowed them to recognize that there were no crop guards on the farm. Additionally, because of their large number in the group, they are difficult to chase and quickly escape into the farm fields, severely damaging the area. This result coincided with Hill's (2000) study conducted in Uganda.

In the present study area, the density estimate of black-backed jackal was 0.6 individuals/km², which is higher than the density estimates of 34–40 individuals/100 km² in South Africa (Rowe–Rowe 1982). Nature reserves in the country's center have recorded densities of 33–43 individuals/100 km² (Klare et al. 2010), while our result was lower than the findings in Zimbabwe 53.9 to 79.1 per 100 km² Loveridge et al. (2010) and Nel et al. (2013) observed jackal concentrations ranging from 0.1 to 13.1 individuals/ km² of shoreline along the Namib Desert coast, depending on the availability of resources, black backed jackal density varied from 0.02 to 1.20 individuals/ km² and density (0.31–9.80 jackals/km²) wasn't aware of and closely correlated with the distance to the food source were estimated in Namibia (Jenner et al. 2011)

Porcupine densities are now estimated to be 0.7 individuals/km², which is less than those found in central Italy by Franchini et al. (2022) and Mesfin et al. (2023) in Ethiopia. Due to its damage to fields and abuse by nearby farmers, the porcupine is regarded as a "potentially problematic species." Within the research region, the porcupine's basic food consists of seeds, fruits, roots, epigeal portions, and other underground stems like enset. On the other hand, because porcupines eat potatoes, haricot beans, and maize, local farmers may be less tolerant of them. Due to their widespread reputation as crop raiders in the study area and the traditional medicinal value of their meat, porcupines are killed. To determine the proper course of conservation and management, determining its density is even more crucial.

The present estimated density of warthogs is lower, which is 1.2 individual/km² compared to typical cluster densities investigated by Edossa et al. (2022) in Ethiopia (5.18/km² and 2.37/km²), Creel et al. (2018) in Tanzania (1.7/km²), Marchal et al. (2012) in Burkina Faso (2.5 individuals/km²), and Cunningham (2016) in Namibia (4.05/km² and 1.95/km²). The common warthog density estimate in the present area was in line with that found in central Kenyan protected areas (1–10 animals/km²) (De Jong et al. 2016). However, the current study's findings are higher than the warthog density estimates of 0.19/km² (Augustine, 2010) and 0.25/km² (Apio et al. 2015) found in the habitat of Acacia bushlands at Kenya's. The current research, however, was much less than the values (77 animals/km²) previously recorded in the South Africa (De Jong et al., 2016), and in the short grass of Kenya (22.8/km², Swanepoel et al. 2016; 26.0/km², White 2010). This variation of density might be due to the competition for resources and human activities.

Olive baboons were the most damaging crop-foraging species, according to local farmers, while the study area's grivet monkeys were the next most common animals to complain about when they visited farms. Apex carnivores were shown to be the most damaging small livestock pest, after crop foraging, in terms of economic impacts. In the current study area, the lack of wild food, habitat degradation, and constriction most likely enhance olive baboons' ability to predate small livestock. To verify the respondents' assessment of olive baboons as the leading livestock predator in the area, additional observational research is necessary. In a comparable manner, additional research revealed that baboons are known to outcompete small livestock in Ethiopia (Kifle and Bekele 2020) and Benin (Sogbohossou et al. 2011). This includes juvenile goats and sheep. In addition to causing crop damage, grivet monkeys also hunt chickens and steal and snatch human food and eggs from children and elderly people (Ejigu and Bekele 2010; Chapman and Peres 2001).

Most respondents agreed that the expansion of agriculture and deforestation for the purpose of harvesting firewood and expanding farmlands were the primary causes contributing to the impact of wildlife on the local community. This result is in line with a study by Hill (2000), which discovered that competition for resources between people and wild animal’s cause’s conflict between wildlife species and humans in forests. Similarly, a study conducted in south-western Ethiopia in Gera district reported that agricultural expansion around the forest edge was the main cause of wildlife impacts on the people (Gobosh et al. 2016).

The current study found that agricultural loss was greater in villages near the forest, including Bahita and Gola, than it was in areas further from the forest boundary. The farther cropland is from the forest boundary, the more damage crop raider’s cause to crops (Nibret et al. 2016). Costs associated with farming close to forests include crop loss, livestock predation, and the time and resources needed to protect the crops and livestock. This result agrees with the finding of Mackenzie (2012), in which, in many parts of Africa, the wildlife species in the forest are the most serious problems in the villages located adjacent to the natural forest or protected area. According to Nibret et al. (2016), a study conducted in Choke Mountain, Ethiopia, indicated that the crop damage caused by wildlife species was severe near the forest. The absence of a buffer zone between the farmlands and the park, according to Biset et al. (2019), is probably responsible for the highest crop damage incidence among the surrounding households. They emphasised that the absence of a buffer zone may result in increased interactions between agricultural areas and wildlife, hence increasing crop vulnerability to damage.

The majority of respondents agreed that the primary cause of olive baboon raids and the subsequent escalation of conflict was the tasty nature of cereal crops. Easy-to-digest human harvesting crops offer monkeys an alternative food supply and nutritional benefits in times of low natural food supplies (Wallace and Hill 2012; Kifle 2021; Kifle and Bekele 2020). Research has also shown that when habitat productivity in the surrounding areas declined, baboons' agricultural foraging increased (Kagoro-Rugunda 2004; Findlay and Hill 2020). Similarly, there's a greater chance of crop damage in the area due to intense farming practices and a lack of natural food in the habitats of olive baboons. According to Wallace and Hill (2012), primates experiencing habitat loss in Uganda could rely on field crops as a dependable and easily available source of food. According to Seiler and Robbins (2020), primates are compelled to go into marginal habitats and become crop foragers as their habitats diminish and human settlements encircle them more and more. Similar to this, the boundaries of protected areas, the separation between farms, and the proximity of crop fields all have a significant impact on the occurrence of crop damage (Matseketsa et al. 2019; Mamo et al. 2021).

This study shows how conflicts between wildlife and human populations get worse when wild animals damage crops and livestock. Predation of livestock and crop raiding by wild animals is a major cause of conflict between humans and wild animals, putting human-wild animal coexistence at risk globally (Jayson 2016). According to Wang et al. (2019), the act of wild animals preying on cattle and the subsequent retaliatory reactions can have detrimental effects on both humans and carnivores. Humans and wild animals are negatively impacted by conflicts between them (Mekonen 2020). Conflicts involving crop loss and livestock harm were the most prevalent (Pisa and Katsande 2021). Major obstacles face both wild animal management and rural lifestyles as a consequence of the conflict between the local people and wild animals (Tamrat et al. 2020). According to Dhakal et al. (2019), interactions between animals for food, shelter, and other needs might be advantageous or disadvantageous. Conflicts between humans and wild animals are highly dangerous due to crop raiding and livestock predation (Meena 2021; Neelakantan et al. 2019). A related study indicated that chickens, goats, sheep, dogs, and cats were among the animals that lost the most (Blair and Meredith 2018). Kilcullen (2015) and Gervasi et al. (2020) have noted that crop raiding and the killing of young goats and lambs are the primary causes of conflicts between farmers, semi-pastoralists, and wild animals. Other scholars have also suggested that crop raiding, livestock predation, and deforestation for different purposes are causes of human-wild animal conflict (Bond and Mkutu 2018; Gervasi et al. 2020).

The locals' means of livelihood were significantly impacted by the loss of crops and cattle as a result of wild animals. Farmers who made their living from livestock and farming reported greater losses from crops and animals. In a related survey, Biset et al. (2019) discovered that the majority of participants (85.6%) thought that people's interaction with wild animals harmed crops and livestock. The settlement distance was also associated with crop and animal losses caused by wild animals (Horgan and Kudavidanage 2020; Pisa and Katsande 2021; Dunnink et al. 2020).

This study shows that only a limited number of traditional practices were used in the nearby villages of the Mankira Forest to prevent and mitigate conflicts between humans and wild animals. The most widely used strategies for reducing crop damage and cattle depredation were guarding, fencing, chemicals, chasing, smoking, and throwing stones to repel wild animals, as well as having farmers and their families stand vigil and smoke on the edges of their fields and keep a constant eye on their livestock and crops. According to research conducted in the in Benin, which is similar to current findings, guarding crops was found to be the most efficient technique of crop protection by most farmers (Nyhus, 2016). In actuality, most households' farmland is located closer to the Mankira forest boundary. More harm by wild animals occurs when they are near forests, which is in line with research done in Nigeria (Eniang et al. 2011).

Since larger animal populations have a greater impact on livestock and crops, population density information is crucial to the management of wildlife. Crop raiding and livestock depredation by wild animals were seen as serious risks to the local farmers' livelihoods in the study area. Farmers who resided at the edge of the forest were particularly at risk from the wild animals. Farmers used traditional approaches to deter crop raiding and animal predation. The most common and efficient way of defending their livestock and crops was guarding. In order to ensure that strategies for mitigating human-wild animal conflict are sustainable over the long term, it is imperative to establish community-based wildlife conservation programmes and encourage awareness-raising efforts among nearby farmers.

Consent for publication

All authors agreed to make public this original research work.

Competing interests

The authors declare that they have no conflicts of interest.

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki, which provides guidance for researchers to protect research subjects. The study was approved by the Institutional Research Review Board (IRB) of Wolaita Sodo University, Ethiopia. Consent to participation isn’t applicable to the present article.

Funding

The authors declare that there is no specific funding from any fundraising organizations.

Author Contribution

"B.A. conceptualized the study, prepared the methodology, validated the study, and wrote the original and final draft and W.T. and T.D. conceptualized the study, validated the study, supervised it, and reviewed the draft of the paper."

Acknowledgments

We sincerely thank Kaffa Zone, Decha District and Wolaita Sodo University for their logistic support. We also want to thank the people in the surrounding area of the forest for their kindness and hospitality in sharing their knowledge about our inquiry.

Availability of data and materials

The data used to support the findings of this study are available in the manuscript.

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Density of wild animal populations and their conflicts with nearby farmers in southwest Ethiopia, Mankira Forest

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Abstract

Figures

Introduction

Materials and methods

Description of the study area

Methods

Site selection and sampling design

Sampling and sample size determination

Data collection method for population estimation

Data collection method for human-wild animal conflict

Data analysis

Results

Wild animal population estimation

Demographic characteristics of the respondents

Wild animals involved in crop raiding and livestock predation

Discussion

Conclusion

Declarations

Consent for publication

Competing interests

Ethics approval and consent to participate

Funding

Author Contribution

Acknowledgments

Availability of data and materials

References

Additional Declarations

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