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Article

Suitable Habitat Prediction for African Wild Ass (Equus africanus) in the Danakil Desert of the Afar Region, Ethiopia

by
Redwan Mohammed
1,*,
Redae T. Tesfai
2,
Patricia D. Moehlman
3,
Fanuel Kebede
4,
Afework Bekele
5,
Nicholas E. Young
2 and
Paul H. Evangelista
2
1
Department of Biology, Wollo University, Dessie P.O. Box 1145, Ethiopia
2
Natural Resource Ecology Laboratory, NESB, Colorado State University, Fort Collins, CO 80523, USA
3
IUCN/SSC Equid Specialist Group, Arusha P.O. Box 2031, Tanzania
4
Ethiopian Wildlife Conservation Authority, Addis Ababa P.O. Box 386, Ethiopia
5
Department of Biology, Addis Ababa University, Addis Ababa P.O. Box 1176, Ethiopia
*
Author to whom correspondence should be addressed.
Wild 2025, 2(4), 40; https://doi.org/10.3390/wild2040040
Submission received: 16 July 2025 / Revised: 22 August 2025 / Accepted: 1 October 2025 / Published: 6 October 2025
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Abstract

Simple Summary

The African wild ass (Equus africanus) is listed on the IUCN Red List as critically endangered. Previously, the major threats were hunting for food and medicinal purposes. These threats have been alleviated due to a long-term conservation effort. However, habitat loss and competition with livestock for access to drinking water and forage are the major threats currently. In this study, the presence location data of the African wild ass collected in the field were paired with habitat suitability determinant covariates (bioclimatic and topographic) to predict its suitable habitat and the seasonal habitat range in the Danakil Desert of the Afar Region, Ethiopia. Additionally, locations of water points, livestock, and settlements associating with the African wild ass in natural settings were recorded to support the ground assessment of a potential protecting site. These results are important to know the seasonal habitat range to guide future monitoring work and determine a protected area.

Abstract

The critically endangered African wild ass is found in low population densities and there may be as few as 600 individuals in the Danakil Desert of Ethiopia and Eritrea. An understanding of suitable habitats is important for prioritizing the conservation and management of the African wild ass. In this study, we recorded presence locations of the African wild ass and independently prepared environmental covariates to identify suitable habitats using the maximum entropy (Maxent) model. Model performances were high, with the area under the curve (AUC) values of 0.927 and 0.950 for wet and dry seasons, respectively. The predicted moderately suitable habitat area extent was greater during the wet season (15,223 km2) than during the dry season (6052 km2). Precipitation, temperature, and distance from water sources were vital variables for the wet season, while distance from water sources and distance from the settlements were important determinant covariates for the dry season. This information prioritizes where protected areas should be established for African wild ass conservation and also indicates potential new undocumented locations to guide surveys in the Danakil Desert of the Afar Region, Ethiopia.

1. Introduction

The African wild ass (Equus africanus, Fitzinger, 1857), historically, was distributed throughout north-eastern Africa (Egypt, Sudan, Eritrea, Ethiopia, Djibouti, and Somalia) and was relatively abundant in the early 1970s with an estimated 18.6 individuals per 100 km2 in some areas [1,2]. Then, after some decades, surveys in the 2000s showed that the population declined to approximately 0.625 individuals per 100 km2, with reports indicating the local extirpation from the Yangudi–Rassa National Park [3,4]. Then, surveys in the 2020s stated that there were 0.81 individuals per 100 km2 in Ethiopia [5]. These reports illustrate the sharp decline of the population over time. Now, it is the most endangered wild equid in the world [6]. The range of African wild ass in Ethiopia and Eritrea has been reduced by approximately 90% according to surveys in the 1990s and afterward, and the remaining wild population is now mainly restricted to the Danakil Desert [3,7].
A major threat to the African wild ass in Ethiopia had been hunting for food and medicinal purposes [3,8]. Local pastoralists believed that diseases such as tuberculosis, backache, bone ache, constipation, and rheumatism could be cured by eating African wild ass meat and their bones in a soup [6]. This threat has been alleviated since 2002 due to a long-term conservation endeavor in the area. Significant support was given by the late religious elder, Sultan Alimirah Hanfere, who made a declaration not to kill African wild ass or use any part of its body for medicinal purposes [4,9]. The attitude of local people changed, and since then, they have developed sympathy for its low population status and adopted a more positive attitude towards African wild ass conservation [5]. Currently, the main threats to the species are habitat loss and competition with livestock for access to drinking water and forage [6,10]. Human activities and their livestock can negatively impact wildlife and their natural habitat by affecting the availability of resources and impacting the species’ activity, feeding, distribution, and habitat use [11,12]. The continued impact can result in habitat degradation and local extinction of some species [13].
Currently, the ranges of African wild ass in Ethiopia and Eritrea are occupied by human settlements and livestock [10,14]. In Ethiopia, field surveys from 1994 to 2014 reported a significant reduction in the African wild ass population (approximately 95%) and range (approximately 50%) since the 1970s [6]. Their historical ranges were from the Dire–Dawa to Yangudi–Rassa National Park and the Mille–Serdo Wild Ass Reserve [7]. Surveys conducted by Kebede et al. [14], reported that the African wild ass was extirpated from the Yangudi–Rassa National Park. Today, the known range is much reduced and restricted in the Afar Region from Serdo–Hillu in the south to Bidu–Afdera in the north. These two locations are 150 km apart, and the movements and connectivity of African wild ass populations in these locations need to be investigated further [8] (Figure 1). Both areas were selected for this study, since these African wild ass populations still inhabit the areas [14]. Conservationists and wildlife managers require scientific information on the species, its natural habitats, and the extent of suitability to identify and determine where it is appropriate to establish a protected area for securing conservation goals [15,16,17,18].
The local peoples in the study area are pastorals moving from one area to another in search of forage and water for their livestock [14]. According to the 2007 record from the CSA of Ethiopia, the local human population size of the Serdo–Hillu locations (65,342) were known to be double that of the Bidu–Afdera location (32,225); then, after 15 years, the 2022 CSA projection showed that the population for Serdo–Hillu increased more than twofold (122,641), whereas the population of Bidu–Afdera only showed slight increment (45,683) [19]. This high human population projection for the Serdo–Hillu area indicates that the area is more favorable and the influx of people and their livestock had increased through time [20]. By comparison, the Bidu–Afdera is hotter and a more challenging area for survival [21].
Species distribution models have been used to predict and identify suitable habitats for rare and cryptic wildlife species [22,23,24,25]. The maximum entropy (Maxent) model is one of the most widely used species distribution models [22,26,27]. The model uses the geographic coordinates of a species’ presence (e.g., observations, footprints, feces/droppings) and selected environmental variables to predict a suitable habitat through probability and spatially explicit model outputs [28,29,30,31]. Environmental covariates (e.g., precipitation, temperature, elevation, and slope) and biotic factors (like the settlements of local people and their livestock) are used to infer the probability model of the species’ potential suitable habitats [32,33,34,35,36,37]. Reliable and updated information on seasonal habitat requirements and species distribution is essential for conservation planning and species protection [38,39,40].
The main objective of this research was to predict the seasonal suitable habitat range of the critically endangered African wild ass, reassessing and refining upon the foundational work of Kebede et al. [14]. Moreover, this study investigated a more illustrative suitable habitat determination considering a larger dataset including factors of temporary water sources and the impact of livestock displacement. In addition, this evidence will be used to strengthen the community-based conservation strategy from the socio-ecological perspective. The Maxent model is employed to understand the potential range and guide future monitoring efforts to survey undocumented areas of the species’ occurrence. Additionally, the information will be used to determine what areas should be designated and protected for the long-term conservation of the African wild ass and other wildlife species in the Danakil Desert of the Afar Region, Ethiopia.

2. Materials and Methods

2.1. Study Area

This study was conducted in the Danakil Desert of northeastern Ethiopia, which is the hottest place on the African continent, and one of the hottest places in the world [41,42]. The area is characterized by an arid landscape with lava ridges [43,44]. The study area is located between 11°45′20″–13°05′40″ N latitude and 40°55′00″–41°55′15″ E longitude with an elevation ranging from c. 150 m below sea level in Bidu–Afdera up to c. 1500 m above sea level on the MinkileBera in Serdo–Hillu [45]. The potential range of the African wild ass is estimated to be 95,000 km2, while the study area was 12,300 km2. These two surveyed areas (Bidu–Afdera and Serdo–Hillu) constitute approximately 57 percent of the study area (12,300 km2) (Figure 1). There were six permanent water sources identified in the surveyed areas that are potentially used by the African wild ass (see Figure 1). Andeley is one of the permanent water sources located in Bidu–Afdera, which is critical for the survival of the species population occupying this area. This survey site is located in the northern part with an elevation ranging between 150 m below sea level and 50 m above sea level and covers approximately 2560 km2. The climate of this area is extremely hot and dry, with a monthly mean maximum temperature of 43.6 °C during June. The monthly mean minimum temperature was 26.9 °C in January. The monthly mean rainfall of this site ranged between 0.1 mm in February and 34.9 mm in August. The other five permanent water sources are located in Serdo–Hillu. This survey site is located in the southern part with an elevation ranging from 393 to 1045 m above sea level and covers an area of 4473 km2. The monthly mean maximum temperature was 42.5 °C in June, whereas the monthly mean minimum temperature was 17.5 °C in December. The monthly mean rainfall of this area ranged between a low of 0.6 mm in December and January to a high of 40.8 mm from mid-June to August [46].

2.2. Data Collection

Collecting data on the African wild ass was demanding due to the harsh arid climate and rugged terrain of the study area [47]. The African wild ass in the Danakil Desert appears in very low density in scattered, small, and isolated groups, which makes it impractical to use conventional methods of data collection like line transects [9,10,48]. Some of the areas could be surveyed using a 4-wheel drive vehicle. However, most of the area was not accessible to vehicles. As a result, most of the fieldwork was conducted on foot using survey routes that made it possible to scan hilltops, water points, valleys, and gorges (Figure 1) [49,50]. These foot survey routes cover 963 km (279 km in Bidu–Afdera, and 684 km in Serdo–Hillu) during the survey periods of 126 days, quarterly for two consecutive years. The presence of African wild ass was documented based on direct observations (within a radius of 1000 m and sometimes can be approached up to 400 m after slow habituation), footprints, and fecal droppings (distinguished by their bigger size and patterns) [51], and these points were recorded with a global positioning system (GPS) [38]. Data were collected every three months for at least seven days at each site from December 2017 through February 2020. Surveys were usually carried out when the African wild asses were most active, i.e., in the morning from 06:00 to 11:00 h and in the late afternoon from 15:00 to 18:00 h. Surveys documented data on the presence of African wild ass (seen, camera trapped, foot print or droppings), and settlements (permanent or temporary), livestock, and all permanent and temporary water sources. Then, all coordinates for presence data were combined for the data analysis using Maxent. In total, we collected 411 GPS locations of African wild ass, of which 242 were for the dry seasons and 169 were for the wet seasons. We limited occurrence records to a single point for each 90 m2 pixel so that each pixel would represent an occurrence point to avoid weighting. This reduced the number of recorded occurrence points from (242 and 169) to (116 and 87) for dry and wet seasons, respectively (Figure 2).

2.3. Predictor Variables

The selection of predictor variables is a fundamental step that can impact the quality and usefulness of habitat suitability models [52]. Predictor variable selections were based on expert opinion with an emphasis on the spatial conditions that were conducive or limiting to African wild ass distribution in the Danakil [53]. We used 19 bioclimatic variables from the CHELSA climate database (http://chelsa-climate.org/, accessed on 1 December 2024) (see Supplementary Table S1), land cover type (tree cover, shrub cover, herbaceous grassland, cropland, bare ground areas, and built-up areas), and topographic variables (elevation, aspect, and slope) from the European Space Agency (ESA) World Cover (https://esa-worldcover.org, accessed on 1 December 2024). The user-generated distance from water and the distance from settlement variables have been used as additional predictors. These variables were produced for wet and dry seasons separately using the Euclidean distance tool in ArcGIS v. 10.8 [54] (Table 1). We resampled all the predictor variables at the resolution of 90 m using the resample tool in Arc Map, aligning with the species ecology and the amount of occurrence data to avoid over-fitting to improve the identification of suitable habitats for the African wild ass using Maxent modeling. Finally, we calculated the 20-year mean (2000–2019) of the enhanced vegetation index in Google Earth Engine [55]. We selected major predictor variables that could influence the distribution of the African wild ass in the Danakil Desert and had higher percent of contribution on the initial model iterations after we ran a covariate correlation matrix test for each dataset (bioclimatic and environmental variables) and developed the model by removing one of each pair of highly correlated predictor variables (Spearman correlation coefficient |r|> 0.7) (see Supplementary Tables S2 and S3) [56].
Consequently, based on the number of occurrence points, we included seven variables (precipitation, i.e., average mean precipitation of coldest quarter for the wet season, average mean precipitation of driest quarter for the dry season, temperature, i.e., average mean temperature of wettest quarter for wet season, average mean maximum temperature of warmest month for dry season, herbaceous grassland cover, elevation, slope, distance from water, and distance from settlements) in the models following the recommendation to use no more than one predictor for every 10 occurrence points [57] (Table 1). Precipitation is an important source of water and essential for the growth of forage (grasses and herbs), which plays a fundamental role in the survival of the species in an arid environment like the Danakil [58,59,60,61]. Climatic variables (average mean precipitation of the coldest quarter for the wet season, average mean precipitation of the driest quarter for the dry season) were selected based on their high contributions and low co-linearity. Even though the vegetation cover of the study area is sparse, the herbaceous grassland cover is an important determining factor indicating forage availability for African wild ass, other wildlife, and livestock [62,63,64].
Average mean temperature of the wettest quarter for the wet season, average mean maximum temperature of the warmest month for dry season, elevation, and slope, were assumed important due to their level of influence on the species distribution in the surveyed area. The other determinant covariate was distance variable classified as distance from water, which is a critical resource for the survival of the African wild ass. Permanent water points can persist throughout the year, whereas temporary water points (ponds) only stay for a few months after the rain. All pertinent information on temporary water points was collected for the wet season during the wet season survey (March–August). The rainwater may sometimes persist longer after the rain and attract the species to utilize larger areas compared to the dry season. As Danakil is a very arid environment, and there are only a few known permanent water points, it was not difficult to monitor available water sources in the survey area. Distances from permanent and temporary settlements were also categorized as wet and dry seasons, which are an important covariate as the distribution and movement of the African wild ass is negatively influenced by people and settlements. Permanent settlements include towns, highways, and roads, whereas temporary settlements were villages that persisted for less than six months These village huts, locally called “Ribora Afar Ari” can be assembled easily at the destination point during mobility and dismantled quickly and moved to areas of better grazing sites for livestock.

2.4. Data Analysis

The maximum entropy model (Maxent) is an established and frequently used tool to predict the suitable habitat of a given species [65]. The model has been shown to perform well with small datasets using presence-only data [28]. Previously, it has been widely used with default settings, including all bioclimatic and many environmental variables, allowing the Maxent algorithm to make decisions. Recently, researchers highlighted the importance of inputs and settings, particularly background extent, feature classes, and regularization tuning [66]. This indicated that careful pre-modelling decisions and developing clear hypotheses for predictors is needed, rather than just including everything [67]. The Maxent model had limitations from the point of data incompleteness, variable distribution constraints, and models’ performance for species, so the models should be treated with validation and the model iteration process to avoid pitfalls [57]. Habitat suitability for the African wild ass was modeled using Maxent version 3.4.4 with 10 replicates of selected variables using k-fold cross-validation for the dry and wet seasons, which holds 10% of the data for testing in each iteration, and results are averaged across all iterations. We used the default value of 10,000 locations to generate background samples from the surveyed areas within the study area, making sure these areas were accessible and represented the available environment [57]. The default (10,000) value was used considering that our vast study area as these background points provide sufficient coverage for the large environmental variability of the Danakil. Also, using a finer resolution (90 m) of predictor variables can help to capture the complex environmental conditions (e.g., mountainous terrain and diverse vegetation) [53,67] (Figure 3).
Model results were evaluated by AUC (area under the receiver operating characteristics (ROC) curve) values, which are automatically generated by Maxent [68]. The AUC value provides a measure of model performance with a range from 0 to 1 with values closer to 1 indicating better model performance, and values at or below 0.5 being no better than random [27,28]. We adjusted the regularization multiplier by increasing the value until the difference between the training and test area under the receiver operating characteristics curve (AUC) < 0.05 to control over-fitting and set the maximum iteration to 5000 [69]. The seasonal model output was reclassified into unsuitable, moderately suitable, and optimally suitable based on the minimum training presence logistic threshold and maximum test sensitivity plus specificity logistic threshold values, i.e., pixel values lower than minimum were considered as unsuitable, pixel values between minimum and maximum were considered as moderately suitable, and pixel values higher than maximum were considered as optimally suitable [70].
The model result figure was constructed by reclassifying model output in Arc map toolsets based on the minimum and maximum threshold values [71]. The suitable and optimal areas were combined to determine and quantify the extent of suitability of the habitat for the African wild ass (Figure 4). All the other area and distance calculations, as well as figures, were constructed, and all predictor variables were projected to the WGS84 UTM zone 37N, and clipped to the extent of the Afar Region with a resolution of 90 m using ArcGIS version 10.8 [54].

3. Results

Maxent model results showed average test AUC values of 0.927 and 0.950 for wet and dry seasons, respectively. The minimum training presence logistic threshold and maximum test sensitivity plus specificity logistic threshold values were 0.008 and 0.437 for the wet season and 0.005 and 0.273 for the dry season. The model results of habitat suitability indicated that there is a difference in the size of suitable habitats for the African wild ass between seasons. The extent of suitability (moderately suitable and optimally suitable) of habitats for the wet season was 15,517 km2, whereas for the dry season it was 6259 km2. This result indicated that for the wet season, the suitable habitat is much bigger (more than twofold) compared with the dry season. Similarly, the size of optimum habitats for the wet season (294 km2) showed a 87 km2 increase compared with the dry season (207 km2), which indicated that the prevalence of more grassland vegetation cover during the wet season is due to moisture availability (Figure 4).
Distance from water, distance from settlement, and precipitation of the driest quarter were the most important predictor variables showing the highest percentage contribution during the dry season (Figure 5). Whereas, in the wet season, precipitation of the coldest quarter, mean temperature of the wettest quarter, and the distance from water scored a higher percentage contribution. Conversely, herbaceous cover and slope scored a lower percentage contribution to both seasons’ modeling (Figure 5).

4. Discussion

The habitat suitability model results for the African wild ass (Equus africanus) achieved strong predictive performance, with AUC values of 0.927 and 0.950 for the wet and dry seasons, respectively. These high AUC values are a promising sign of the effectiveness of the models in predicting the extent of suitability of a habitat for a species under study [72]. The results revealed significant seasonal variations between wet and dry seasons, emphasizing the complex interplay between environmental variables and species response in arid environments of the Danakil Depression. The model analysis also reflected the dynamic nature of the habitat selection of the African wild ass, driven mainly by environmental conditions. The model result indicated that the African wild ass has more suitable areas and a greater potential distribution range during the wet season compared to the dry season (Figure 4). This is possibly due to widely available water points and forage in the wet season [14,73]. The suitable habitat in the wet season covered a total of 15,517 km2, which is significantly larger than the 6259 km2 of the dry season. This is a typical feature of an arid environment which happened due to rainwater availability, allowing vegetation cover to increase during the wet season [74]. This situation allows the species to expand its range and occupy a bigger area. Similar seasonal expansion was observed by Tesfai et al. [74] in Eritrea. This seasonal shift underscores the critical importance of water availability and precipitation in determining habitat use.
The model showed the importance of environmental variables in determining habitat suitability variability between seasons. During the dry season, the distance from the water was the most important predictor variable. This finding aligns with previous studies. As Klingel [1] noted, the African wild ass often congregates around water points during the dry season, which is a focal area for survival and emphasizes the importance of permanent water sources in arid landscapes [14,73]. Water sources are scarce during dry seasons, and permanent water is critical for survival. Even though African wild ass are physiologically well adapted to arid ecosystems, they still need access to surface water [3]. Adult males and non-reproductive females can drink at five-day intervals, but adult females with foals drink daily [10]. The African wild ass in the Serdo–Hillu area has better access to water compared to Bidu–Afdera area, because the water sources in Edgilo, Aila Manda, and Lake Gamary are nearby (10–25 km) their location [14]. Water dependent species like the African wild ass are known to be constrained by proximity to water during dry periods when surface water becomes scarce, influencing their spatial distribution [75]. Despite this seasonal contraction in overall suitable habitat, the area of optimum habitat did not show a huge difference between seasons (294 km2 in the wet season and 207 km2 in the dry season). This suggests that core areas may remain optimally suitable for the species throughout the year. These areas likely represent critical refuges for the species due to the availability of critical resources to support the species during both seasons.
In the wet season, precipitation in the coldest quarter, average mean temperature of the wettest quarter, and distance from the water become the dominant variables. Rainfall during the wet season reduces the dependency of the species on permanent water sources since temporary water sources allow the African wild ass to disperse more widely [76]. The high percent of contribution for climatic variables, such as precipitation and temperature, reflects the direct influence of these factors on forage production, creating a favorable situation during the wet season [61] (Figure 5). During this period, African wild asses were observed closer (2–3 km) to temporary water sources where forage and water were available (R. Mohammed, pers. Obs, 2020). These temporary water holes dug by the Afar Region tourism office supply water to the community, livestock, and wildlife, including the African wild ass, which helps to reduce competition for water.
Distance from human settlements plays a crucial role, as the African wild ass tend to avoid areas with high human and livestock densities, possibly due to the risks of hunting and competition for resources [73]. Distance from the settlement had a lower contribution during the wet season. This may indicate that competition for water and forage is reduced as there is more widespread availability of water and forage so the African wild ass can maintain their distance (1–2 km) from livestock and (3–6 km) from local settlements (Figure 4a). Pastoralists and their livestock also utilize areas that the African wild ass inhabit [2], and may compete for forage as well as water [10]. Competition for water is high when people and livestock are more concentrated around the permanent water sites in the dry season [3,77]. The important contribution that distance from settlements makes in our dry season model indicates more competition with livestock for water as also reported in other studies [73] (Figure 4b). The prevalence of more water and forage could attract livestock and increase the competition during the wet season, which may lead to smaller optimum habitat for seasonal modeling [78,79]. Compared to the above predictor variables (e.g., distance from water, precipitation, and distance from settlement), herbaceous grassland cover and slope contributed minimally in both seasons. This relative minimal contribution could be due to the nature of scarce vegetation cover in the Danakil and the species’ ability to move across rugged terrain whenever required (Figure 5). This is also observed on other desert ungulates as their movement allows them to forage a vast area and this mobility reduces their dependency on the vegetation cover at a fixed location [80]. The other reason could be that access to water and avoidance of human disturbance is prioritized over forage abundance in habitat selection [81,82]. This result is consistent with findings by Kebede et al. [14], who also found that topography and vegetation type were less significant compared to water availability and human presence. The African wild ass is highly adaptable to various terrain types and can thrive in open plains or rugged terrain as long as water and forage are accessible [77]. Their ability to use a wide range of habitats due to physiological adaptation allows them to persist in a very arid ecosystem, such as the Danakil Depression [83,84].
The optimum habitat sizes of this study in wet and dry seasons are very small compared to the previous findings. This might be due to the growing number of settlements over time and the recent expansion of agricultural developments in the area (Aiela Manda and Lake Gamary). These expansions of mechanized agriculture and recent mining activity in the south near the permanent water location of Aila Manda and Lake Gamary pose a potential threat to the African wild ass in particular and to all wildlife in general. The northern study area is less susceptible to human activities due to inhospitable environmental factors, such as high temperature, poor forage cover, and scarcity of permanent water.
The seasonal variations in habitat suitability highlighted by this study have profound implications through a better understanding of the species’ habitat utilization in different seasons, enabling the delineation of the boundary of where to conserve the fragmented population and their habitat. The contraction of suitable habitats during the dry season means that the species is likely more vulnerable during this period, particularly as human and livestock activities intensify around remaining water sources. Tesfai et al. [74] similarly emphasized the need for targeted conservation efforts during the dry season when competition for resources is highest. One critical conservation strategy would be the protection of key water sources and optimally suitable habitats, especially those that remain suitable year-round through community-based conservation approaches. As indicated by other studies [14,73], the areas around permanent water sources represent core habitats that are crucial for the survival of the African wild ass. Following the current prediction model, effective management of these areas, including the reduction in human–wildlife conflict and the establishment of protected areas, could significantly enhance the African wild ass’s chances of survival and generate livelihood options benefiting locals.
Climate change affects the critically endangered African wild ass in the arid and semi-arid regions of the Danakil Desert, Ethiopia [14,85]. High temperatures, prolonged droughts, and erratic rainfall patterns are expected to exacerbate water scarcity and reduce forage availability, further fragmenting the species’ limited habitat [86]. As a result of these climate shifts, the wild ass may have to change its seasonal movement patterns and how it uses its habitat. Long-term habitat stability is crucial for the survival of the African wild ass, as the species relies on specific environmental conditions, such as proximity to permanent water sources and suitable forage [6]. However, climate change may disrupt these conditions, leading to habitat degradation and reduced suitability over time. For instance, prolonged droughts could dry up seasonal water sources, while increased temperatures might reduce the productivity of sparse vegetation [14]. To mitigate these impacts, conservation strategies must prioritize the protection of key habitats, such as areas near permanent water sources, and incorporate climate change into management plans.
The main limitation of the study is collecting actual presence data due to the difficulty in accessing the species habitat. Also, detecting the African wild ass was another constraint due to its shy behavior [87]. To alleviate this, we walked through gorges and hilltops to record the occurrence. The other limitation may be the potential for model bias due to the reliance on presence-only data, which may not fully capture the African wild ass’s true distribution, especially in areas where the species is rare or difficult to detect [88]. We decreased such effects by careful selection of background data, incorporating relevant predictors, and model calibration by using cross-validation to assess model performance. Additionally, the accuracy of predictor variables may be limited by the resolution of remote sensing data [89]. To minimize this kind of noise effect at such a fine scale, we have aligned the environmental data with the species’ actual habitat use.

5. Conclusions

The Maxent model prediction results demonstrate that the African wild ass’s suitable habitat depends on water availability and climatic factors, which vary significantly between wet and dry seasons. These prediction results indicate that the African wild ass could have more spatially distributed suitable habitats during the wet than the dry season, as water and forage are widely available. The stability of optimal habitats across seasons and the importance of water sources underscore the need for focused conservation efforts in key areas, particularly during the dry season. The differences that distance from settlement played in the wet and dry season models suggest that the African wild ass is less affected by settlements when resources are available, while dry season models indicate that they might compete for available forage and water resources with people and livestock. This research indicates that there are undocumented, potentially suitable areas that need to be surveyed. The extent of suitable habitats during the wet season indicates that the Bidu and Serdo survey areas are not fragmented and that the African wild ass should be able to move freely between these locations. The observed patterns of habitat use could provide insights applicable to other species facing similar ecological challenges. This research underlines the importance of integrating species-specific adaptations into conservation planning, particularly in regions where there are environmental extremes. Additionally, conservation management measures like rangeland management to improve pasture condition and promoting and creating local people and wildlife co-existence would have a meaningful outcome. Further research would provide needed information on the population size of the African wild ass and management of available suitable habitats through prioritizing which areas should be designated as protected habitats for the critically endangered African wild ass.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/wild2040040/s1, Table S1: Bioclimatic variables from CHELSA climate database (www.chelsa-climate.org); Table S2: Correlation matrix table of the dry season variables; Table S3: Correlation matrix table of the wet season variables.

Author Contributions

R.M.: Conceptualization, data curation, formal analysis, investigation, methodology, software, supervision, validation, visualization, writing—original draft, writing—review and editing. R.T.T.: Conceptualization, formal analysis, investigation, methodology, software, supervision, validation, visualization, writing—review and editing. P.D.M.: Conceptualization, formal analysis, funding acquisition, investigation, methodology, project administration, resources, supervision, validation, writing—review and editing. P.H.E.: Conceptualization, data curation, formal analysis, investigation, methodology, resources, software, supervision, validation, visualization, writing—review and editing. N.E.Y.: Conceptualization, data curation, formal analysis, investigation, methodology, software, supervision, validation, visualization, writing—review and editing. F.K.: formal analysis, investigation, methodology, project administration, software, supervision, validation, visualization, writing—review and editing. A.B.: Supervision, writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Dataset available on request from the authors.

Acknowledgments

The authors are grateful for the technical support of the Natural Resource Ecology Laboratory (NREL) at Colorado State University. We thank the Ethiopian Wildlife Conservation Authority and Afar Tourism office, the local villagers in Hillu and Bidu, as well as the local scouts Ali Wagaris, Ali Hamed, and Deto Nuru for their careful guidance during fieldwork in the Danakil. Funding for the field works was provided by the Basel Zoo, EcoHealth Alliance, the Government of the Federal Republic of Germany, through the Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (Bundesministerium für Umwelt, Naturschutz, Bau und Reaktorsicherheit; BMUB) via the Convention on Migratory Species, IUCN Save Our Species, and Little Rock Zoo. The authors kindly acknowledge their financial support.

Conflicts of Interest

The authors declare no conflicts of interest.

References

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Figure 1. Topographical map of the study area with major landscape features like Hillu, a hill that is higher than the surrounding land, and surveying routes, temporary water points, permanent water points, 1 = Andeley, 2 = Dako, 3 = Edgilo, and 4 = Aila Manda, 5 = Tendaho dam, 6 = Gamary, Awash River and Salty Lakes (A = Lake Afdera and B = Lake Abbe), in the Danakil Desert, the Afar Region, Ethiopia. The representations of international boundaries on this map are not authoritative.
Figure 1. Topographical map of the study area with major landscape features like Hillu, a hill that is higher than the surrounding land, and surveying routes, temporary water points, permanent water points, 1 = Andeley, 2 = Dako, 3 = Edgilo, and 4 = Aila Manda, 5 = Tendaho dam, 6 = Gamary, Awash River and Salty Lakes (A = Lake Afdera and B = Lake Abbe), in the Danakil Desert, the Afar Region, Ethiopia. The representations of international boundaries on this map are not authoritative.
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Figure 2. Topographical map indicating African wild ass occurrence locations.
Figure 2. Topographical map indicating African wild ass occurrence locations.
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Figure 3. Schematic illustration of the methodology starting from data collection up to modeling.
Figure 3. Schematic illustration of the methodology starting from data collection up to modeling.
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Figure 4. African wild ass habitat suitability during the (a) wet season and (b) dry season, indicating Maxent model output extent of habitat suitability (unsuitable, moderately suitable, and optimally suitable areas) derived from wildlife field survey data from 2017 to 2020, where permanent water points, 1 = Andeley, 2 = Dako, 3 = Edgilo, 4 = Aila manda, 5 = Lake Tendaho dam, 6 = Lake Gamary, and salty water bodies, (A) = Lake Afdera and (B) = Lake Abbe, located in the Danakil Desert of the Afar Region, Ethiopia.
Figure 4. African wild ass habitat suitability during the (a) wet season and (b) dry season, indicating Maxent model output extent of habitat suitability (unsuitable, moderately suitable, and optimally suitable areas) derived from wildlife field survey data from 2017 to 2020, where permanent water points, 1 = Andeley, 2 = Dako, 3 = Edgilo, 4 = Aila manda, 5 = Lake Tendaho dam, 6 = Lake Gamary, and salty water bodies, (A) = Lake Afdera and (B) = Lake Abbe, located in the Danakil Desert of the Afar Region, Ethiopia.
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Figure 5. Maxent output of variables with their percentage contribution for wet and dry season’s habitat suitability models for African wild ass in the Danakil Desert of Ethiopia.
Figure 5. Maxent output of variables with their percentage contribution for wet and dry season’s habitat suitability models for African wild ass in the Danakil Desert of Ethiopia.
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Table 1. Predictor variables used for modeling.
Table 1. Predictor variables used for modeling.
Wet Season Predictor VariablesDry Season Predictor VariablesSource
Distance from water Distance from water Constructed using ArcGIS v. 10.8
Distance from settlement Distance from settlement Constructed using ArcGIS v. 10.8
Precipitation of coldest quarterPrecipitation of driest quarterDownloaded from CHELSA (www.chelsa-climate.org)
Temperature of wettest quarterMax-temperature of warmest monthDownloaded from CHELSA (www.chelsa-climate.org)
ElevationElevationDownloaded from ESA (https://esa-worldcover.org)
Herbaceous grassland cover of wetHerbaceous grassland cover of dryDownloaded from ESA (https://esa-worldcover.org)
SlopeSlopeDownloaded from ESA (https://esa-worldcover.org)
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Mohammed, R.; Tesfai, R.T.; Moehlman, P.D.; Kebede, F.; Bekele, A.; Young, N.E.; Evangelista, P.H. Suitable Habitat Prediction for African Wild Ass (Equus africanus) in the Danakil Desert of the Afar Region, Ethiopia. Wild 2025, 2, 40. https://doi.org/10.3390/wild2040040

AMA Style

Mohammed R, Tesfai RT, Moehlman PD, Kebede F, Bekele A, Young NE, Evangelista PH. Suitable Habitat Prediction for African Wild Ass (Equus africanus) in the Danakil Desert of the Afar Region, Ethiopia. Wild. 2025; 2(4):40. https://doi.org/10.3390/wild2040040

Chicago/Turabian Style

Mohammed, Redwan, Redae T. Tesfai, Patricia D. Moehlman, Fanuel Kebede, Afework Bekele, Nicholas E. Young, and Paul H. Evangelista. 2025. "Suitable Habitat Prediction for African Wild Ass (Equus africanus) in the Danakil Desert of the Afar Region, Ethiopia" Wild 2, no. 4: 40. https://doi.org/10.3390/wild2040040

APA Style

Mohammed, R., Tesfai, R. T., Moehlman, P. D., Kebede, F., Bekele, A., Young, N. E., & Evangelista, P. H. (2025). Suitable Habitat Prediction for African Wild Ass (Equus africanus) in the Danakil Desert of the Afar Region, Ethiopia. Wild, 2(4), 40. https://doi.org/10.3390/wild2040040

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