Dietary composition of wildebeest (Connochaetes taurinus) kongoni (Alcephalus buselaphus) and cattle (Bos indicus), grazing on a common ranch in south-central Kenya
Abstract
enThis paper gives the results of a study conducted at Game Ranching Ltd, situated at the Athi Kapiti Plains, Kenya, to determine the dietary composition of cattle (Bos indicus L), kongoni (Alcephalus buselaphus Pallas) and wildebeest (Connochaetes taurinus Burchell), through two forage growing seasons (wet and dry). The dietary preferences and overlaps between the species were also determined.
The diet preference of the three herbivores was determined using a microhistological analysis technique. The three dominant grasses in the ranch: Themeda triandra Fork, Digitaria macroblephara (Hack.) Stapf and Penisetum mezianum Leeke, formed the major diets of the animals. The browse component of the diets increased during the dry season by about 100% for all the animal species, with cattle always having twice as much browse as the wild herbivores. However, the animals selected similar diets in terms of plant species during both seasons but were more selective during the wet season. Dietary overlaps were always above 75%, but more than this during the dry season. The dietary overlaps were lower between cattle and wild herbivores than between the wild herbivores. The diet preference index for the animals differed from season to season, and from plant to plant.
Résumé
frCet article donne les résultats d'une étude réalisée à Game Ranching Ltd, dans la plaine d'Athi Kapiti, au Kenya, pour déterminer la composition du régime alimentaire du bétail (Bos indicus L), des bubales (Alcephalus buselaphus Pallas) et des gnous (Connochaetes taurinus Burchell) pendant deux saisons de pousse du fourrage (saison des pluies et saison sèche). On a aussi déterminé les préférences alimentaires et les recouvrements entre les espèces.
Les préférences alimentaires des trois herbivores ont été déterminées en utilisant une technique d'analyse microhystologique. Les trois graminées dominantes dans le ranch : Themeda triandra Fork, Digitaria macroblephara (Hack.) Stapf et Penisetum mezianum Leeke, composaient le menu principal des animaux. Les composants broutés des régimes augmentaient de près de 100% pendant la saison sèche pour toutes les espèces animales, le bétail ayant toujours deux fois plus de fourrage que les animaux sauvages. Cependant, les animaux choisissaient des régimes similaires en ce qui concerne les espèces végétales pendant les deux saisons, et étaient plus sélectifs pendant la saison des pluies. Les recouvrements alimentaires dépassaient toujours 75%, mais ils étaient plus élevés que cela pendant la saison sèche, comparé avec la saison des pluies. Les recouvrements alimentaires étaient moindres entre le bétail et les herbivores sauvages qu'entre les différents herbivores sauvages. L'indice de préférence alimentaire des animaux différait d'une saison à l'autre et d'une plante à l'autre.
Introduction
Maximum livestock production is dependent upon proper management of the available resources. The most fundamental of these is stocking the range with the correct kinds/class and numbers of animals (Heady, 1975). Unlike stall-fed animals that receive their rations in amounts and proportions dictated by the livestock owners, freely ranging animals choose their diets from the complex variety of available forage plant species in the plant communities they utilize. Man, therefore, exerts only a limited managerial control through decisions such as stocking rates, herd composition and size, and location of grazing areas.
The relatively broad muzzles and efficient use of tongues in wildebeest and cattle allow rapid and efficient harvesting of grass leaves from dense leafy swards. However in tall grass communities, kongoni which have a long, narrow, flat muzzle are more capable of selecting for grass leaves than cattle (Jarman & Sinclair, 1979). Jarman (1974) described kongoni and wildebeest as being rather unselective for grass species but more selective for plant parts or growth stages. Kongoni select for maximum intake of grass leaves in the wet season, but in the dry season grass sheath is selected over grass stem (Stanley-Price, 1977). Kongoni appear to be able to select for grass leaf in tall grass vegetation types (Talbot & Talbot, 1962; Stewart & Stewart, 1970). Wildebeest show a preference for short grass vegetation types (Mentis & Duke, 1976). Unlike kongoni, wildebeest do not seem to be capable of selecting for grass leaf in tall grass vegetation types. Instead, they maximize their intake of grass leaves by migration or association with less selective ungulates in grazing succession (Bell, 1971).
Wildebeest and zebra are virtually pure grazers and select leaves which have the highest ratio of protein and soluble carbohydrates to cellulose (Gwynne & Bell, 1968). In the dry season there is a decrease in the intake of leaves, at the expenses of leave sheath and stem. Ben-Shahar (1991) showed that the wildebeest diet alternated with seasons, showing high preferences during the winter for grasses, which were rejected during the summer.
Field (1975) noted that cattle, buffalo, eland and oryx grazed within the grass/herb layer during the early growth period. He also noted that annual and drought tolerant grasses form the main diet of oryx, while buffalo and cattle feed on bulky perennial grasses. Field & Potere (1972) have documented that cattle prefer grazing to browsing. Holechek et al. (1982) showed that grasses, forbs and shrubs averaged 61%, 16% and 23% of the diet, respectively, and that composition of the diet differed with advancement of the season. Forbs were heavily used in the early part of the growing season, before maturation. Browse comprised as much as 47% of the diet when green grass was unavailable. Holechek et al. (1982) concluded that cattle were opportunistic grazers and did not limit their selection to grass species.
Materials and methods
Study area
Game Ranching Ltd (GRL), Athi River, is a privately owned, mixed game and cattle ranch. GRL was initiated to demonstrate the economic and environmental viability as well as the social acceptability of game ranching. The ranch occupies an area of 8100 ha, and is located 40 km south-east of Nairobi on the Athi Kapiti plains. Its elevation varies between 1600 and 1700 m above sea-level, latitude is 0.1°30′S, and longitude 37°02′E (MacDowell et al., 1988; Sinnary & Hebrard, 1991). The ranch is only 5 km to the north of Kajiado District, which is mainly used for pastoralism and is bordered by unfenced private ranches. It is separated from Nairobi National Park by the Portland Cement Ranch and the Nairobi–Namanga road.
Prior to 1981, GRL was operated as a cattle and sheep ranch. Following the findings of research by Hopcraft (1975) on productivity a comparison between Thomson Gazelle and cattle and their relation to the ecosystem, GRL applied to the Kenyan Government for a permit to operate it as a game ranch. To meet the government regulations, GRL had to complete several modifications including a 50 km chain-link fence, 2.6 m in height, along the perimeter to ensure the existence of a closed system. The later was used in this study to investigate the diet preferences and overlaps between cattle, kongoni and wildebeest.
GRL falls within eco-climatic zone four (IV), the semi-arid zone (Pratt, Greenway & Gwynne, 1966). The following six vegetation types (habitats) occur in the ranch; Themeda grassland, Balanites tree grassland, Balanites–Acacia tree grassland, Acacia drepanolobium dwarf tree grassland, Acacia woodland and Acacia xanthophloea bushland (MacDowell et al., 1988). The different habitat types did not have distinct boundaries, but the vegetation differences were obvious. Themeda grassland areas were restricted only to the ridge tops and characterized by an absence of woody plants. Balanites tree grassland occurred on the slopes and was characterized by widely spaced trees. A. drepanolobium dwarf tree grassland, Balanites–Acacia tree grassland and Acacia woodland occurred on the lower slopes and areas with depressed topography. A. xanthophloea bushland was associated with an area restricted to a seasonal stream bed at the northern part of the ranch.
Rainfall is bimodal, and exhibits considerable seasonal as well as year-to-year variation. The long rainy season falls between March and May, followed by a cool, cloudy and dry season from June to September The short rainy season extends from October to December and is followed by a hot and sunny dry period, which continues to the middle of March. The average annual rainfall for the 12 years starting from 1981 was 502 mm (Table 1). During the study period, January to August, the short rains extended into April. The usual long rains failed and as such, January to April, and May to August were considered the wet and dry seasons, respectively, in this study. Due to the elevation, temperatures are characterized by warm days and cool nights, with a maximum of 24.9°C and minimum of 13.7°C (MacDowell et al., 1988).
| Year | 1981 | 1982 | 1983 | 1984 | 1985 | 1986 | 1987 | 1988 | 1989 | 1990 | 1991 | 1992 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Rainfall | 422 | 473 | 435 | 349 | 698 | 468 | 345 | 702 | 627 | 687 | 449 | 372 |
Herb layer biomass sampling
During the 8-month study period, the sampling was carried out six times, once every month except, during the months of March and July. Herb layer standing biomass was obtained by clipping thirty 0.5 m2 circular quadrats along 300 m transects in each vegetation type. Quadrats were placed after every 10 m along the transects. This process was repeated each time clipping was done, but on a transect parallel and 4 m away from the previous one. The herb layer was clipped to the ground level and separated into species. Forbs were grouped together. The clipped samples of each plant species were weighed in the field and packed in paper bags. They were later dried to a constant weight at 60°C and weighed. Dry weights were determined for each habitat type and converted to kilogrammes per hectare.
Preparation of slides from plant reference material and faecal samples
In this study, a microhistological technique was used in the dietary analysis of the study animals. Reference slides were prepared from plant species collected from the study area, following the procedures described by Cavender & Hansen (1970). For each of the animal species and for each month, faecal samples were collected for 3 days each week during a 3-week collection period from randomly selected fresh dung/faeces in the field. Faecal samples for each animal species were combined from the weekly samples to form one composite sample. Each composite sample was then crushed and washed over 600 µm and 212 µm sieves with running tap water. The sample retained by the 212 µm sieve was then dried and stored in sealed plastic bags. For each composite sample, five slides were made using the procedures described by Cavender & Hansen (1970).
Slide quantification
Faecal slides were quantified as described by Hansen et al. (1984) and Foppe (1984). Twenty identifiable fields were used in the quantification. A 100× magnification was used on a movable stage microscope. The recorded identifiable plant fragments were converted to percentage relative density (Sparks & Malechek, 1968; Foppe, 1984; Hansen et al., 1984). The percentage relative density gives an indication of the relative amount of different plant species consumed (Hansen et al., 1984). The frequency of different plant species in each of the faecal slides was determined and Relative Density (RD) was calculated using the formula (Hansen et al., 1984) below:
Data analysis
Seasonal diet preference . For each animal species and sampling period, the dietary components at species level were tabulated with their relative densities. This was compared with plant species available in the range so as to determine animal diet preference by calculating their preference indices. Diet preference indices were calculated using the following equation, adapted from Viljoen (1989 ).
Dietary overlaps . Dietary overlaps between animal species were calculated using a percentage similarity index ( Oosting, 1956 ). Comparisons were made between animals within seasons. The similarity index represents the percentage of the diets that was identical. It shows the potential for competition between two herbivores. Spearman's rank correlation coefficient was calculated from the relative densities of the plant species common to the diets of the two animals being compared ( Snedecor & Cochran 1967 ; Hansen et al. 1984 ). Comparisons were made between animals within seasons. A high R s value indicated a strong correlation for the order in which different plant species were selected by the animals. Using the above two methods, animal diets were compared two at a time for each season. Significant positive values were interpreted to mean strong correlations for the order in which any two herbivores selected the same plant species that constitute their diets. Trophic diversity indices were calculated using Shannon's diversity index (1948 ) to indicate food niche breadth.
Results
Diet composition by plant species
The botanical composition of the animals', diets during the wet and dry seasons are shown in Tables 2 and 3. During the wet season, the three most prominent grass species in each animal species diet and their means were as follows:
| Species | Cattle | Kongoni | Wildebeest | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Jan | Feb | Mar | Apr | Jan | Feb | Mar | Apr | Jan | Feb | Mar | Apr | |
| Themeda triandra | 33.56 | 30.32 | 26.73 | 27.32 | 19.76 | 21.10 | 21.22 | 22.30 | 28.00 | 26.24 | 21.85 | 18.71 |
| Digitaria macroblephara | 25.79 | 27.59 | 27.44 | 18.17 | 26.13 | 18.21 | 16.37 | 22.60 | 20.38 | 15.74 | 20.62 | 27.48 |
| Penisetum mezianum | 13.00 | 14.39 | 15.03 | 21.31 | 19.57 | 23.61 | 16.80 | 17.73 | 21.65 | 17.82 | 21.24 | 13.92 |
| Penisetum stramineum Peter | 2.60 | 2.30 | 3.68 | 2.33 | 6.39 | 7.15 | 15.70 | 8.96 | 1.59 | 5.16 | 5.03 | 5.11 |
| Ischaemum afrum (J.F. Gmel) Dandy. | – | 1.64 | 2.08 | 8.05 | 6.58 | 6.51 | 4.46 | 5.44 | 1.25 | 3.68 | 7.40 | 10.47 |
| Cynodon dactylon (L) Pers. | 4.25 | 4.01 | 4.45 | 6.29 | 2.66 | 2.74 | 3.43 | 3.49 | 3.07 | 2.97 | 3.25 | 1.97 |
| Lintonia nutans Stapf | 0.08 | 1.67 | 1.49 | 1.61 | 4.25 | 4.65 | 4.28 | 5.35 | 1.96 | 2.70 | 6.37 | 3.88 |
| Bothriochloa inscupta (A.Rich) A.Camus | 3.34 | 2.17 | 1.58 | 0.70 | 2.35 | 3.31 | 0.73 | 1.03 | 1.07 | 2.19 | 1.60 | 2.63 |
| Aristida spp. | 3.45 | 2.76 | 0.80 | 0.49 | 1.78 | 0.86 | 1.21 | 0.60 | 1.27 | 1.67 | 0.75 | 1.17 |
| Chloris gayana | 1.65 | 0.74 | 0.93 | 0.78 | 1.85 | 1.01 | 0.69 | 0.18 | 3.09 | 0.85 | 2.90 | 0.60 |
| Brachiaria spp. | 2.42 | 1.39 | 2.26 | 0.59 | 1.81 | 0.70 | 2.08 | 0.32 | 0.56 | 1.37 | 0.44 | 0.88 |
| Hyperrhenia spp. | 0.67 | 0.46 | 0.25 | 0.41 | – | 0.19 | 0.98 | 1.15 | 1.72 | 0.49 | 0.90 | 4.51 |
| Penisetum masaicum Stapf | 0.34 | 0.33 | 0.90 | 0.25 | 1.02 | – | 2.55 | 3.05 | 0.00 | 1.47 | 0.46 | 1.27 |
| Heteropogon contortus (L) R & Rich | 0.50 | 0.60 | 1.72 | 0.18 | 0.18 | 0.46 | 1.15 | 0.62 | 0.67 | 2.56 | 2.16 | – |
| Harpachne schimperi A.Camus | 0.90 | 1.17 | 1.86 | 0.63 | 0.83 | 0.47 | 0.81 | 0.32 | 1.24 | 1.32 | 0.09 | 0.43 |
| Cenchrus ciliaris (L) | 1.14 | 0.60 | 0.95 | 0.69 | 1.34 | 0.42 | 1.48 | 0.52 | 0.89 | 0.51 | 0.37 | – |
| Sporobolus pellucides Hochst. | 1.19 | 1.59 | 0.46 | 0.95 | 0.08 | 0.74 | 0.36 | 0.22 | – | 0.22 | – | – |
| Panicum spp. | 0.23 | 0.53 | – | – | – | – | – | – | – | – | – | – |
| Browse | 2.80 | 2.39 | 5.20 | 5.76 | – | 1.18 | 1.78 | 1.90 | 2.93 | 0.98 | 0.86 | 2.83 |
| Unidentified grasses | 2.09 | 2.62 | 2.20 | 2.78 | 3.42 | 6.69 | 3.68 | 4.01 | 7.52 | 10.82 | 3.01 | 3.43 |
| Sedges | – | 0.74 | 0.71 | – | – | – | 0.23 | 0.23 | 0.45 | – | 0.74 | 0.72 |
| Species | Cattle | Kongoni | Wildebeest | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| May | Jun | Jul | Aug | May | Jun | Jul | Aug | May | Jun | Jul | Aug | |
| Digitaria macroblephara | 20.79 | 18.85 | 19.19 | 18.76 | 22.39 | 22.62 | 23.21 | 20.59 | 24.63 | 19.71 | 21.82 | 16.91 |
| Penisetum mezianum | 16.60 | 18.04 | 19.69 | 20.28 | 14.64 | 15.47 | 18.11 | 16.14 | 22.20 | 21.57 | 17.33 | 20.24 |
| Themeda triandra | 24.17 | 22.11 | 21.15 | 21.71 | 15.83 | 15.37 | 18.19 | 16.32 | 14.57 | 16.00 | 16.38 | 16.45 |
| Ischaemum afrum | 6.13 | 4.89 | 7.65 | 8.47 | 13.79 | 13.61 | 12.78 | 10.62 | 8.29 | 9.93 | 8.80 | 8.44 |
| Lintonia nutans | 4.41 | 7.70 | 5.57 | 7.73 | 9.90 | 10.25 | 7.28 | 9.35 | 6.30 | 6.18 | 5.88 | 6.62 |
| Penisetum stramineum | 7.33 | 8.72 | 4.36 | 3.88 | 4.08 | 9.30 | 6.08 | 8.04 | 3.19 | 6.93 | 8.59 | 7.32 |
| Cynodon dactylon | 3.94 | 2.23 | 3.79 | 3.29 | 8.60 | 5.11 | 5.91 | 6.33 | 6.30 | 8.11 | 6.41 | 12.06 |
| Hyperrhenia spp. | 1.58 | – | 1.78 | – | – | – | 0.21 | – | 1.22 | 0.20 | 1.56 | 1.13 |
| Brachiaria spp. | 0.54 | 0.18 | 1.54 | 0.73 | 0.30 | – | 0.42 | – | 0.17 | 0.79 | 0.16 | – |
| Chloris gayana | 0.63 | 0.55 | 0.19 | 0.72 | 0.08 | 0.36 | 0.42 | 0.26 | 0.45 | 0.49 | 0.63 | – |
| Bothriochloa inscupta | 0.26 | 0.45 | 0.29 | – | 0.14 | 0.19 | 1.37 | 0.27 | 0.45 | 0.80 | – | 0.09 |
| Cenchrus ciliaris | – | 0.47 | 0.92 | 0.55 | – | 0.09 | 0.10 | – | 0.35 | 0.45 | 0.17 | 0.72 |
| Sporobolus pellucides | 0.49 | 1.50 | – | – | 0.23 | – | 0.21 | – | 0.86 | 0.34 | – | – |
| Aristida spp. | 0.34 | – | – | – | 0.15 | – | 0.31 | – | 1.98 | – | 0.10 | 0.10 |
| Penisetum masaicum | – | – | – | – | 0.16 | – | 0.21 | 1.37 | 0.47 | – | 0.35 | 0.36 |
| Heteropogon contortus | – | 0.48 | – | – | 0.26 | 0.54 | – | – | – | – | 0.70 | 0.29 |
| Harpachne schimperi | 0.36 | – | – | – | – | 0.27 | 0.10 | 0.09 | 0.53 | 0.11 | – | – |
| Unidentified grasses | 3.52 | 3.60 | 4.83 | 4.57 | 2.69 | 4.57 | 3.05 | 4.29 | 2.94 | 4.25 | 6.70 | 5.64 |
| Browse | 8.42 | 9.21 | 5.33 | 9.33 | 6.62 | 1.70 | 2.05 | 3.09 | 3.61 | 3.73 | 4.43 | 3.50 |
| Sedges | 0.49 | 1.01 | 3.72 | – | 0.14 | 0.55 | – | 3.24 | 1.49 | 0.40 | – | 0.11 |
Cattle: T. triandra, D. macroblephara and P. mezianum , each contributed 29.5%, 24.7% and 15.9%, respectively. Their combined contribution was 70.2%. Other monocot species combined contributed 25.8%, while browse contribution was 4.0%.
Kongoni: D. macroblephara, T. triandra and P. mezianum were the prominent grass species. Each species made up 20.8%, 21.1% and 19.4%, respectively. Their combined contribution to the diet was 61.3%. Other grass species' combined diet contribution was 37.4%, whereas browse contributed only 1.2%.
Wildebeest: T. triandra, D. macroblephara and P. mezianum made up 23.7%, 21.1%, and 18.7% of the diet, respectively. Their combined contribution being 63.4%. Other grass species contributed 34.7%, while browse component of the diet was only 1.9%.
During the dry season the three most dominant grass species, other grasses and browse contribution to the diet and their means were as follows;
Cattle: T. triandra, D. macroblephara and P. mezianum were prominent grass species. Their contribution to diets were: 22.3%, 19.4% and 18.7%, respectively. The three made up 60.3% of the diet. Other grasses and browse species contributed 31.6% and 8.1%, respectively.
Kongoni: D. macroblephara, T. triandra and P. mezianum were the three most abundant plant species in the diet. These grasses contributed 22.2%, 16.4% and 16.1%, respectively, thus constituting 54.7% of the diet. Other grasses contributed 41.9%, whereas browse component was 3.4% of the diet.
Wildebeest: P. mezianum, D. macroblephara and T. triandra each contributed 20.3%, 20.8% and 15.8%, respectively to the diet, thus making up 57.0% of the diet. Again browse contributed only 3.8%, whereas other grasses contributed 39.2%.
Diet preferences
The seasonal diet preference indices for cattle, kongoni and wildebeest in the ranch are shown in Table 4. Analysis of variance of mean diet preference indices of the plant species eaten by the animals revealed that the diet preference indices differed significantly between the animals (F2,18 = 8.39, df = 2, P < 0.05). Brachiaria species recorded the highest diet preference index, followed by Chloris gayana Kunth., while Hyperrhenia species had the lowest index. The diet preference indices for animals differed from one season to the next (F1,18 = 33.72, df = 1, P < 0.05). It tended to be high during the wet season and low during the dry season, indicating that the degree of selectivity was low during the dry season. Similarly, the diet preference indices varied significantly from one plant species to another (F17,18 = 30.30, df = 17, P < 0.05). The diet preferences seemed to be dependent on the interactions between season and plant species, and on the interactions between animals and plant species and not on animal–season interaction. This is supported by significant season–diet and animal–diet interaction terms (F10,18 = 6.66, df = 10, P = 0.05 and F33,18 = 2.62, df = 33, P < 0.05, respectively), while the animal–season interaction was non-significant.
| Plant species | Wet | Dry | ||||
|---|---|---|---|---|---|---|
| Cattle | Kongoni | Wildebeest | Cattle | Kongoni | Wildebeest | |
| Brachiaria spp. | 10.72 | 6.30 | 12.38 | – | – | – |
| Harpachne schimperi | 5.68 | 2.93 | 4.56 | 2.99 | 2.50 | 5.35 |
| Cynodon dactylon | 5.68 | 3.39 | 2.71 | 1.36 | 2.91 | 4.10 |
| Chloris gayana | 3.27 | 4.39 | – | 10.40 | – | – |
| Aristida spp. | 4.23 | 2.54 | 4.28 | 0.29 | 0.13 | 1.81 |
| Sedges | 3.79 | 0.31 | 3.64 | – | – | – |
| Digitaria macroblephara | 1.42 | 1.28 | 1.20 | 1.20 | 1.35 | 1.26 |
| Ischaemum afrum | 0.65 | 2.10 | 1.21 | 0.73 | 1.41 | 1.00 |
| Penisetum stramineum | 0.85 | 2.28 | 0.80 | 0.94 | 1.05 | 0.87 |
| Sporobolus pellucides | 5.18 | 1.37 | 0.20 | – | – | – |
| Themeda triandra | 1.21 | 0.84 | 0.96 | 1.12 | 0.78 | 0.77 |
| Bothriochloa inscupta | 0.87 | 1.07 | 1.62 | 0.34 | 0.37 | 0.66 |
| Penisetum mezianum | 0.77 | 1.00 | 0.89 | 0.71 | 0.60 | 0.84 |
| Panicum spp. | 1.14 | 0.00 | 3.08 | – | – | – |
| Browse | 0.43 | 0.11 | 0.28 | 1.31 | 0.54 | 0.53 |
| Lintonia nutans | – | – | – | 0.89 | 1.30 | 0.84 |
| Penisetum masaicum | 0.19 | 0.55 | 0.83 | – | – | – |
| Hyperrhenia spp. | – | – | – | 0.15 | 0.00 | 0.29 |
Seasonal dietary overlaps between animals
Dietary overlaps during the rainy season were all above 70% and significant (P < 0.05), as shown in Table 5. Cattle and kongoni diets had overlaps ranging from 72.59% to 79.56%, with a mean overlap of 76.06%. Correlation coefficients were significant (P < 0.05) and ranged from +0.46 to +0.87. Cattle and wildebeest diet overlaps ranged from 74.56% to 78.74%, with a mean overlap of 77.30%. All correlation coefficients were significant (P < 0.05) and ranged from +0.62 to +0.72. Diet overlaps between kongoni and wildebeest ranged from 77.24% to 82.97%, with a mean overlap of 80.83%. Correlation coefficients were significant during all periods and ranged from +0.64 to +0.90 (P < 0.05).
| Animal combination | Period | SI | R s | n | t |
|---|---|---|---|---|---|
| Cattle vs. kongoni | Jan | 76.14 | 0.46 | 20 | 2.218* |
| Feb | 72.59 | 0.87 | 21 | 7.683* | |
| Mar | 75.99 | 0.78 | 20 | 5.253* | |
| Apr | 79.56 | 0.66 | 20 | 3.699* | |
| Mean | 76.06 ± 2.46 | ||||
| Cattle vs. wildebeest | Jan | 78.74 | 0.62 | 21 | 3.405* |
| Feb | 78.30 | 0.72 | 21 | 4.507* | |
| Mar | 77.64 | 0.62 | 20 | 3.383* | |
| Apr | 74.56 | 0.68 | 20 | 3.940* | |
| Mean | 77.30 ± 1.63 | ||||
| Kongoni vs. wildebeest | Jan | 77.24 | 0.64 | 21 | 3.669* |
| Feb | 82.97 | 0.80 | 20 | 5.726* | |
| Mar | 81.08 | 0.76 | 20 | 5.031* | |
| Apr | 82.06 | 0.90 | 20 | 8.890* | |
| Mean | 80.83 ± 2.18 |
- * Significant ( P < 0.05).
Dietary overlaps exhibited during the dry season were all above 79% (Table 6) cattle and kongoni diets had overlaps ranging from 80.18% to 83.16%, with a mean of 81.44%. Correlation coefficients were positive and ranged from +0.78 to +0.86, and were significant (P < 0.05). Cattle and wildebeest diets overlaps ranged from 79.96% to 85.60%, with a mean of 83.19%. Correlation coefficients were significantly high (P < 0.05) and ranged from +0.78 to +0.84. Kongoni and wildebeest diet overlaps ranged from 83.06% to 88.49%, with a mean of 85.84%. Correlation coefficients were significantly high (P < 0.05) and ranged between +0.78 and +0.83.
| Animal combination | Period | SI | R s | n | t |
|---|---|---|---|---|---|
| Cattle vs. kongoni | May | 80.18 | 0.78 | 19 | 5.139* |
| Jun | 80.2 | 0.86 | 17 | 6.444* | |
| Jul | 83.16 | 0.83 | 19 | 6.020* | |
| Aug | 82.22 | 0.79 | 16 | 4.877* | |
| Mean | 81.44 ± 1.292 | ||||
| Cattle vs. wildebeest | May | 79.96 | 0.84 | 19 | 6.403* |
| Jun | 82.77 | 0.82 | 18 | 5.751* | |
| Jul | 85.60 | 0.81 | 18 | 5.622* | |
| Aug | 84.45 | 0.78 | 18 | 5.042* | |
| Mean | 83.19 ± 2.124 | ||||
| Kongoni vs. wildebeest | May | 83.06 | 0.78 | 20 | 5.331* |
| Jun | 85.80 | 0.83 | 18 | 6.013* | |
| Jul | 88.49 | 0.81 | 19 | 5.836* | |
| Aug | 86.04 | 0.80 | 18 | 5.448* | |
| Mean | 85.84 ± 1.92 |
- * Significant ( P < 0.05).
Generally, all the animals in this study had high trophic diversity, indicating that they were not dependent on any one particular plant species, but rather selected from a wide spectrum of plants. Cattle had the lowest trophic diversity (2.12 ± 0.06) while wildebeest had the highest (2.20 ± 0.05). That of the kongoni was intermediate (2.16 ± 0.05). Overall, wildlife had a higher trophic diversity than cattle, but the difference was not statistically significant (P = 0.05).
Discussion
All the study animal species had very similar plant varieties in their diets during both the wet and dry seasons. This observation however, contradicted the results of Casebeer & Koss (1970) in the same general area. They found that the diets of the animals had a greater variety during the dry season than during the wet season. This is explained in two ways. First, this study was carried out in a closed system. This may have resulted in the animals being limited in their preferred habitats and home ranges and therefore limited in the plant varieties they could select from. Secondly, the high abundance of forage in the ranch during the study period may not have necessitated a shift in the diets of the animals.
During the two seasons in 1993, three grass species, namely D. macroblephara, P. mezianum and T. triandra, dominated the diets of the three animals. The preference for these species were probably by virtue of being perennial and having greater standing biomass than other grass species. The browse component of the diets increased during the dry season by about 100%, irrespective of the animal species, with cattle always having twice as much browse as the wild herbivores. The results clearly show an increased use of browse in the dry season. This is in general agreement with earlier studies by Payne & MacFarlane (1963) and Kayongo Male (1986) who found that the browse component in cattle diets increased as the dry season progressed. These results, however, contradict those of Wangoi & Hansen (1987) who concluded that cattle are predominantly grass feeders and the browse component of their diet was higher during the wet season than in the dry. Whereas cattle in this study browsed more during the dry season, Wangoi (1984) observed that cattle browsed most during the wet season when browse shoots are most abundant. This difference is most likely to be due to differences in the vegetation in the two areas. Wangoi (1984) reported that most of the trees and shrubs were devoid of leaves in the dry season. In the study area (GRL) most trees and shrubs retained their leaves long into the dry season, thereby offering browse to the animals. Owaga (1975) observed that wildebeest browsed about 1–2% of browse during the wet season and almost none at other times. This was in contrast to the findings of this study, where wildebeest took more browse during the dry season but about the same amount during the wet. This difference can be attributed to management. Whereas Owaga did her study on animals whose movement was unrestricted, this study was carried out in a closed system, which did not allow for the migration of the animals. The increase in browse component of the diets during the dry season can be explained in four ways. During the wet season the animals utilized habitats which had less browse material than during the dry season. It seems clear therefore, that the locality of the animals in relation to plant availability will affect the proportion of browse in the diet. Secondly, during the wet season, the new growth from all plants is high in crude protein, digestibility, has less fibre, and forage is abundant in general. There would be no nutritional advantage in animals walking from one shrub/tree to another in search of browse, whereas the grass at ground level was more abundant, and accessible. The energy cost involved would outweigh the benefits. Thirdly this can also be viewed as a resource utilization strategy whereby these animals make maximum use of the grass when it is still growing and high in nutrient contents, before suddenly declining in quality with advancement of maturity. This results in browse preservations, which declines less in quality for the critical dry season. Fourth, it has also been reported (Van Soest, 1982) that young growing browse plants may contain high levels of secondary compounds, which may interfere with the digestive mechanisms of the animal, among other effects. It is possible then, that these animals could simply be avoiding much of the browse growth which may contain such compounds.
During the wet and dry seasons, the dietary overlaps and Spearman Rank Correlation Coefficients were high among all the animal species. The findings of this study clearly indicate that cattle, kongoni and wildebeest most likely compete with each other for forage resources. Do overlaps indicate competition? Not necessarily: Field (1972) documented that competition only occurs when the resources being shared are limited. Many researchers in East Africa have addressed the question of resource partitioning and the coexistence of East African ungulates. Some of the theories on how coexistence is achieved include: spatial and temporal distribution, grazing at different herb layers, grazing of different plant parts, differences in mouth structure and differences in body size. Thus, it is possible that the study animals, despite having high dietary overlaps, may have had a differential selectivity for plant parts. The study animals concentrated on those habitats where the grass was kept short and or in growing condition by trampling, mowing and grazing. The short grass was preferred, as it was leafy and nutritious. Thus, in the wet season, the animals were limited by the quality of the food rather than its quantity. There was super-abundance of forage resources during this study period and hence critical levels that trigger competition may not have been attained. This may be one of the reasons why the dietary overlaps were high. In conclusion, the dietary overlaps were lower between cattle and wildlife than among wild animals.
Diet preference index for the animals differed from season to season, and from plant to plant. The animals were more selective during the wet season. This could be explained in various ways. First, the presence of a higher standing biomass during the wet season gave the animals an opportunity to select diets that they prefer most. During the dry season, forage species that were not preferred by the animals during the wet season were also eaten, resulting in lower diet preference. Secondly, animals select plant parts that are more nutritious. It is possible therefore, that the animals selected for those plant parts that were more nutritious during the dry season from those plants that were not preferred during the wet season. Finally, different habitats had different proportions of standing biomass of each plant species. The seasonal changes in the habitat preferences of the animals (Ego, 1996) therefore exposed them to those plants that were not equally accessible during the wet season. These seasonal changes in habitat preference by the animals were reflected by the changes in diet preferences.
Acknowledgements
We acknowledge financial support from the European Union (EU), which was used in collecting the field data and field samples used in the publication of this paper. We are grateful to Dr David Hopcraft, the owner of Game Ranching Limited, Athi River, and the ranch management for allowing us unlimited access to their land and other resources. We also thank the Centre Director NRRC Kiboko who provided, support, transport and other facilities used in analysis of field samples and data. Finally we wish to thank Mr Kinyua. J.M and S.M Mwaura among others, who contributed by way of data collection and analysis of field samples.
