Seasonal variations in activity pattern and performance of sheep and goats in the semi-arid rangelands of Kenya

Introduction

Pastoralism is the main farming activity in the semi-arid rangelands of Kenya (Wasonga et al., 2010) [1] where more than 50% of total sheep and goats are kept as these species are highly adaptable to harsh environmental conditions (Nyariki & Amwata 2019) [2] . However, in recent years the semi-arid rangelands are faced with climate change, land degradation, vegetation loss, and overgrazing (Mganga et al., 2015) [3] , which have implications on sustainable rangeland systems and ruminant production. Goats are classified as browsers and sheep as grazers (Hofmann, 1989) [4] . Forage availability, chemical composition of available plant species and climate change tend to affect sheep and goats feeding activity pattern, forage intake and subsequently their performance ( [5,6,7] . It is well known that increased temperatures accelerate the rate of of plant maturity in the semi-arid rangelands, leading to increased fraction of cell wall constituents and hence poor forage quality (Krämer et al., 2012; Moore et al., 2020) [8,9] . Sampaio et al., (2010) [10] reported that rangeland forages have high cell wall contents and low crude protein (CP) levels during the dry season, limiting animal intake and performance, whereas during the rainy season, CP levels are higher and cell wall constituents are lower, favoring feed intake and, as a result, animals perform better. Studies (Schroeder et al., 2019; Samuels et al., 2016; Egea et al., 2014) [11,12,13] have found that sheep are able to browse in grazing areas with low presence of herbage; whereas goats are found to graze in areas with scarce browse species. These indicating feeding adaptation strategy by livestock to seasonal variations on plant species availability. Sheep and goats time partitioning to feeding and other nonfeeding activities (resting, ruminating, grooming, etc.) are found to differ between seasons (Castro & Fernandez, 2016) [5] . The performance of livestock in the semi-arid rangelands is a function of feed intake, forage quality and other factors. Feed intake is directly associated with time partitioning to feeding activity (O'Reagain, 2021; Edouard et al., 2010) [14,15] . In the semi-arid rangelands of Kenya, Leparmarai et al., (2018) [16] investigated time partitioning of cattle and camels to different activities and found these two species partitioning more than 80% of their daytime in the field to eating (grazing and browsing). On the contrary, there is no information available for seasonal forage intake, time partitioning to eating and performance of sheep and goats under pastoralism. Knowledge on seasonal effect on activity pattern, forage intake and performance in the semi-arid rangelands is important for the design of sustainable rangeland management. The aim of this study was to assess the seasonal variation in activity pattern, forage intake and live-weight gain (LWG) of sheep (Dorper and Red Maasai) and Galla goats foraging on a grassland habitat in the semi-arid rangeland of Machakos County, Kenya.

Materials and Methods

Statement of animal rights

The materials and methods of the study were approved by The Institutional Animal Care and Use Committee (IACUC) at the International Livestock Research Institute (ILRI) and the National Commission of Science and Technology of Kenya under License Number NACOSTI/P/22/17112.

Study site

This study was conducted in the semi-arid rangeland of Kapiti Research Station & Wildlife Conservancy of the International Livestock Research Institute (ILRI), located at Machakos County, Kenya. The area location is 37°08'00.68″ E: 1°37'18.15″ S, at an elevation of 1650-1900m, receiving an annual average rainfall of 550mm (ILRI, 2017) [17] . This study was carried out at end of both a dry season (September-October 2020) and rainy season (November-December 2020. Small ruminant animals in the ranch included 1200 sheep (Red Maasai, Dorper and their crossbreeds) and 250 Galla goats (ILRI 2017) [17] . The animals spend the night confined in corrals to prevent attack by predators and theft.

Experimental animals

The experiment involved six female animals from each of the Dorper and Red Maasai sheep breeds, as well as Galla goats, hereafter referred to as breeds. During each season, the animals were adult females aged 2-3yrs old, non-lactating, and non-pregnant, with weights averaging 53.2±1.8 kg for Dorper, 37.4±4.7 kg for Red Maasai, and 42.3±2.6 kg for Galla. All experimental animals, both sheep and goats, were managed as a single group integrated into a larger flock consisting of 88 animals (44 sheep and 44 goats). They were observed to be healthy and in good condition.

Measurement of seasonal forage intake of sheep and goats

The grazing behaviour observation was carried out by a team of two people. One of them was dedicated to observation of the particular animal general and biting activities, while another person assisted with the operation of the stopwatch and sample labelling. The team members were trained on general activity determination (grazing, resting, ruminating, etc.), bite categorization, and bite size determination, of sheep and goats within a flock. The team was familiarized with the flock over a five-day period by being closer to the animals (Bonnet et al., 2015) [18] . This familiarization enabled the observers stay at around 2 m of distance from the observed animal (Leparmarai et al., 2018; Marquardt et al., 2010) [16,19] . The animals were observed for their grazing behaviour during the grazing period practiced at the farm (8:30am to 4:00 pm). Grazing behaviour was observed over 18 days. Only once, a single animal was randomly selected and monitored per day while alternating with respect to the breed and species. Forage biting (foraging) was monitored intermittently (during 1 min, every 5 min) and categorized into three bite sizes: small bite (a few leaves/flowers or small parts of leaves per bite), half bite (a cluster of leaves and small stem per bite), and full bite (sizable portion of leaves, or leaves and stems per bite) as per Leparmarai et al., (2018) [16] and Agreil & Meuret (2004) [20] . Rate of biting (bites/min) was counted once bite size was categorized (Leparmarai et al., 2018; Agreil & Meuret, 2004) [16,20] . When an animal encountered a patch of herbage, bite sizes were recorded as full, medium or small bites. Forage samples of the most selected plant species were collected by simulating the bite with a gloved hand and a knife in triplicate for each bite size. A mixed bite category (mixed plants species within a bite) was used for the less selected plant species, based on similarities in morphological characteristics (Leparmarai et al., 2018) [16] . Samples, at collection, were immediately put into paper bags and later air-dried until constant weight. After collection, samples were oven-dried for 12 hours at 105 o C and the data used to estimate various plant species contributions and total forage intake for the observation period (5-min intervals and n=90).

Measurement of seasonal activity pattern of sheep and goats

This data was extrapolated from the measurement of forage intake. Where, at each observation time the specific animal activity was recorded. Recorded activity categories included: drinking water, eating (browsing or grazing), grooming, panting, standing, ruminating and lying, running and walking (in search of forage or either coming back to or leaving corrals). The daily daylight (7 and ½ h) partitioning of time devoted to each activity was calculated by adding the categories observed at the 5-min intervals and then expressed as a percentage of the total number of observations (n=90).

Statistical analysis

Statistical test for seasonal difference in time spent on ingestion, standing, moving, lying and any other behavior was determined using mixed model of SAS (2002) where seasons (S), breed and interactions were independent variables affecting time spent in different activities. Means separation was conducted using Least Significant Difference (LSD) test at 0.05 level of significance. Means were considered statistically different from each other when p < 0.05. The statistical model is described below: where, Y ijkl = Overall observation; μ = Overall mean; A i = fixed effect due to ith seasons (Dry and rainy season); B j = fixed effect due to jth breed or animal type; AB= Interaction effect of i th season and j th breed; ε ijkl = random error Live weight data was analyzed using SAS (2002). Initial live weight was fitted as covariant to correct for unexplained variations in treatment means during mean comparisons. Means separation was conducted using least significant difference (LSD) test at 0.05 level of significance means were considered different if p < 0.05.

Results

From Table 1, shows that all breeds, in both seasons, spent a larger portion of their diurnal time (90.2 -91.2%) on feeding (grazing and browsing), then on walking without marked season effects (p > 0.05) on the partitioning of time to the measured activities. An exception to this was during the dry season, when a larger time proportion was devoted to water drinking (p < 0.0001) than during the rainy season (0.8 vs. 0.1%). In the dry season, Dorper were found to partition some running (mainly running in search of water).

Seasonal average feed intake and live weight gain of sheep breeds (Dorper and Red Maasai) and Galla goats in a dry and rainy seasons

In both dry and rainy seasons, the average initial LW, final LW, LWG, and intake along with the corresponding standard deviation, are shown in Table 3 for the Dorper and Red Maasai sheep breeds and the Galla goat breed. Breed x season interactions had no effect on initial LW, final LW, or LWG however, a significant effect was found on intake (P = 0.0041). Seasons had a significant impact on LWG, final LW and intake (p < 0.05), but initial and final LW varied significantly across breeds (Table 3). 88.5±8.9 ab a, b, c means in a row followed by different letter superscripts differ (p < 0.05), LWG = Live weight change (g/day); IW= initial weight (kg); FW=final weight (kg); intake g/90 minutes Table 4 shows significant differences in initial and final LW between the Dorper, Red Maasai, and Galla breeds (p < 0.0001). Dorper had the highest average initial and final LW, followed by Red Maasai and Galla. Furthermore, there were seasonal variations in intake and live weight gain (LWG). The Rainy season had a significantly higher mean intake and LWG than the Dry season (p < 0.0001), suggesting better conditions favoring intake and subsequent weight gain during this period. In contrast, LWG in the Dry season shows no significant deviation from zero, indicating that weight gain is minimal during this time (P = 0.6). From figure 1, the regression model explained 46% of the variation in weight change (R² = 0.46, P = 0.019). Season had a significant effect on weight change (p < 0.01), with animals in the rainy season gaining more weight than those in the dry season, in contrast, intake was not a significant predictor of weight change (P= 0.39) and its interaction was not significant. This indicates that seasonal conditions, rather than the level of feed intake, were the main drivers of weight change in the study.

Discussion

All breeds and seasons spent more than 80% of their time eating. This observation concurs with other studies in which sheep and goats were found to spend most of their daytime eating with a grazing time allowance of 5 to 9 hours (Kam et al., 2020; Kam & Degen, 2012) [21,22]: Safari et al., 2011) [6] . The latter is a consequence of husbandry practice of enclosing animals in corrals for more than two-thirds of their daily time without access to feed or water. Similar behaviors have been observed in cattle and camels (Leparmarai et al., 2018) [16] . During the experiment at Kapiti Research Ranch Station and Wildlife Conservancy, grazing was planned to match stocking capacity. This grazing strategy takes into account seasonal changes and new forage data, to rehabilitate severely degraded grassland ecosystems affected by bush encroachment, particularly by unpalatable shrubs such as Acacia drepanolobium, Solanum incanum, and Aspilia spp (Sircely et al., 2020) [23] Thus, in situations where allowance for grazing is severely limited and/or forage availability and quality are reduced, animals prioritize their time to eating activity in order to maintain forage intake (Miguel et al., 2014) [24] . In both dry and rainy seasons, Galla goats spent most of their time browsing (eating shrubs and trees), which is what other studies have reported with goats when free ranging in areas with readily available browse species (Schroeder et al.,2019; Yayneshet et al.,2008) [11,25] . On the other hand, Dorper and Red Maasai sheep were found to spend more time grazing (eating grasses and herbs). Kam & Degen, (2012) [22] investigated the foraging behavior of sheep and goats in Israel and found that where plant species is diverse sheep tend to prefer grasses and herbs (grazing) while goats prefer shrubs and trees (browsing). Ferreira et al., (2013) [26] investigated the foraging behavior of sheep and goats in improved pasture rangelands and found that sheep are primarily grazers switching to browsing only when forage availability is limiting, whereas goats are primarily browsers switching to grazing only when forage availability is limited. Mohammed et al., (2020) [27] studied grazing behavior of co-grazing sheep, goats, cattle, and camels in Ethiopian pastoral and agro pastoral areas. Their observations were that sheep and cattle spend more than half of their time grazing while goats and camels spend a similar amount of time browsing. In general, the grazing habits of sheep and goats were different in this study because the sheep were observed to wander in groups, eating numerous bites at one area before slowly moving on to the next, whereas the goats browsed individually, spending less time on a single plant before rapidly moving on to the next. Both sheep and goat breeds were found to spend more time drinking water in the dry season than in the rainy season, which is an observation consistent with those of other studies (Safari et al., 2011) [6] . The more water intake during the dry season can be attributed to a higher ambient temperature during the dry season. Ruminating is an important activity for reduction of particle size enabling digestion. in this study, this behavior did not change with seasons or with breeds and was in overall less than one percent of the diurnal activity. Marcone et al. (2021) [28] suggested that reduced rumination time in ruminants is associated with heat stress. In the present study, however, the relatively short rumination time may not be attributed to heat stress alone. The animals were allowed to free-range for only a limited period each day, which may have encouraged them to prioritize forage intake over rumination. Consequently, rumination was likely postponed to subsequent resting periods after grazing. Similar behavioral adaptations have been reported in grazing ruminants, where restricted grazing time reduced rumination during grazing but increased rumination during later resting periods, enabling animals to maximize forage intake (Gregorini et al., 2012) [29] . This behavioral pattern is consistent with the natural feeding strategy of ruminants, in which grazing is typically followed by rumination during periods of rest, particularly at night (Sun et al., 2023) [30] . It is established that rumination time is strongly related to fiber intake, particularly NDF intake, with forages containing more than 65% NDF classified as lowquality (Elgersma & Søegaard, 2018) [31] . According to Van Soest (1994) [32] , increased NDF promotes increased rumination time due to the increased need for fiber digestion. Nevertheless, the lack of significant differences in rumination time across seasons and breeds could be attributed to not achieving voluntary feed intake able to trigger clearance of large particles from the rumen throughout rumination. All breeds spent a portion of their day standing mostly in the shade, with sheep breeds (Dorper and red Massai) spending more time doing so than goat breeds (Galla) Seasons had an effect on both intake and the performance of sheep (Dorper and Red Maasai) and Galla goats. This could be attributed to seasonal influence on forage availability and quality. For example, Mburu, (2015) [33] reported that forage availability in the coastal semi-arid rangelands of Kenya was higher and of better quality in the rainy season than in the dry season. In turn, Safari et al., (2011) [6] , based on studies carried out in semi-arid rangelands of Tanzania, reported higher quality forages during the rainy season compared to dry season. It is also well known that increased temperatures accelerate the rate of plant maturity in the semi-arid rangelands, leading to increased fraction of cell wall constituents and hence poor forage quality (Krämer et al.,2012; Moore et al., 2020) [8,9] . Sampaio et al., (2010) [10] reported that rangeland forages have high cell wall contents and low crude protein (CP) levels during the dry season, limiting animal intake and performance, whereas during the rainy season, CP levels are higher and cell wall constituents are lower, favoring feed intake and, as a result, animals perform better. The findings of this study provide important information for the sustainable management of semi-arid rangelands and the improvement of small ruminant production systems. The differences in forage selection among Galla goats, Dorper sheep, and Red Maasai sheep suggest that these breeds use rangeland vegetation differently. Therefore, grazing these species together can improve the utilization of grasses, shrubs, and browse species. This complementary use of forage resources can reduce grazing pressure on individual plant species. Consequently, mixed-species grazing can help maintain plant species diversity and overall sustainable utilization of the rangelands. Furthermore, due to increased heat stress, both sheep and goat breeds require adequate water availability during the dry season. High-quality forage provision or supplementation is critical for maximizing rumination and nutrient utilization while species-specific behaviors such as standing times should inform grazing management strategies. Integrating these insights into rangeland management improves animal welfare and productivity under different rangeland environmental conditions.

Conclusion

To meet their nutritional requirements, both sheep and goats partition almost all their time to eating whereas goats mostly partition time to browsing and sheep mostly to grazing. Both sheep and goats spend more time drinking water during the dry season than during the rainy season, likely as a response to higher temperatures and the high dry matter content of their dietsSeasons has an effect on both intake and performance of sheep (Dorper and Red Maasai) and Galla goats. Both sheep and goats had a higher intake and performed better in the rainy season than the dry season. With climate change, knowledge and regular assessments of how sheep and goats respond to seasonal temperature increases and the amount of dry matter in their dietary preferences are critical because they guide decisions about rangeland sustainability, water provision, overnight housing, and grazing management. By considering these factors, farmers and ranchers can improve the adaptability of their livestock systems and mitigate the negative effects of changing climate conditions.

References

1. Wasonga VO, van de Steeg J, Ouma R, Mude A. Risk management and adaptation options for pastoral and agropastoral systems in East and Central Africa: A review paper on uncertainty in current seasonal rainfall and future climate variability and change. Nairobi: International Livestock Research Institute; 2010.
2. Nyariki DM, Amwata DA. The value of pastoralism in Kenya: Application of total economic value approach. Pastoralism. 2019;9(1):1-13.
3. Mganga KZ, Musimba NKR, Nyariki DM, Nyangito MM, Mwang'ombe AW. The choice of grass species to combat desertification in semi-arid Kenyan rangelands is greatly influenced by their forage value for livestock. Grass and Forage Science. 2015;70(1):161-169.
4. Hofmann RR. Evolutionary steps of ecophysiological adaptation and diversification of ruminants: A comparative view of their digestive system. Oecologia. 1989;78(4):443-457.
5. Castro M, Fernandez-Nuñez E. Seasonal grazing of goats and sheep on Mediterranean mountain rangelands of northeast Portugal. Livestock Research for Rural Development. 2016;28.
6. Safari J, Mushi DE, Kifaro GC, Mtenga LA, Eik LO. Seasonal variation in chemical composition of native forages, grazing behaviour and some blood metabolites of Small East African goats in a semi-arid area of Tanzania. Animal Feed Science and Technology. 2011;164(1-2):62-70.
7. Schlecht E, Hiernaux P, Kadaouré I, Hülsebusch C, Mahler F. A spatio-temporal analysis of forage availability and grazing and excretion behaviour of herded and free grazing cattle, sheep and goats in Western Niger. Agriculture, Ecosystems & Environment. 2006;113(1-4):226-242.
8. Krämer M, Weisbjerg MR, Lund P, Jensen CS, Pedersen MG. Estimation of indigestible NDF in forages and concentrates from cell wall composition. Animal Feed Science and Technology. 2012;177(1-2):40-51.
9. Moore KJ, Lenssen AW, Fales SL. Factors affecting forage quality. In: Forages: The Science of Grassland Agriculture. Vol. 2; 2020. p. 701-717.
10. Sampaio CB, Detmann E, Paulino MF, Valadares Filho SC, de Souza MA, Lazzarini I, et al. Intake and digestibility in cattle fed low-quality tropical forage and supplemented with nitrogenous compounds. Tropical Animal Health and Production. 2010;42(7):1471-1479.
11. Schroeder A, Samuels MI, Swarts M, Morris C, Cupido CF, Engelbrecht A. Diet selection and preference of small ruminants during drought conditions in a dryland pastoral system in South Africa. Small Ruminant Research. 2019;176:17-23.
12. Samuels I, Cupido C, Swarts MB, Palmer AR, Paulse JW. Feeding ecology of four livestock species under different management in a semi-arid pastoral system in South Africa. African Journal of Range & Forage Science. 2016;33(1):1-9.
13. Egea AV, Allegretti L, Lama SP, Grilli D, Sartor C, Fucili M, et al. Selective behavior of Creole goats in response to the functional heterogeneity of native forage species in the central Monte desert, Argentina. Small Ruminant Research. 2014;120(1):90-99.
14. O'Reagain P. Foraging strategies on rangeland: Effects on intake and animal performance. 2021.
15. Edouard N, Duncan P, Dumont B, Baumont R, Fleurance G. Foraging in a heterogeneous environment-An experimental study of the trade-off between intake rate and diet quality. Applied Animal Behaviour Science. 2010;126(1-2):27-36.
16. Leparmarai PT, Mwangi DM, Gluecks I, Mutie FM, Marquardt S. Plant selection and performance of two cattle types and camels on semi-arid rangelands in Kenya. Rangeland Ecology & Management. 2018;71(6):798-806.
17. International Livestock Research Institute. Kapiti Plains Ranch: Farmhouse and Research Centre. Project brochure. Nairobi: International Livestock Research Institute; 2017.
18. Bonnet OJ, Meuret M, Tischler MR, Cezimbra IM, Azambuja JC, Carvalho PC. Continuous bite monitoring: A method to assess the foraging dynamics of herbivores in natural grazing conditions. Animal Production Science. 2015;55(3):339-349.
19. Marquardt S, Beck SG, Encinas FD, Alzérreca H, Kreuzer M, Mayer AC. Plant species selection by freeranging cattle in southern Bolivian tropical montane forests. Journal of Tropical Ecology. 2010;26(6):583593.
20. Agreil C, Meuret M. An improved method for quantifying intake rate and ingestive behavior of ruminants in diverse and variable habitats using direct observation. Small Ruminant Research. 2004;54(1-2):99113.
21. Kam M, El-Meccawi S, Brosh A, Degen AA. Resting and field metabolic rates of Awassi sheep and Baladi goats raised by Negev Bedouin. The Journal of Agricultural Science. 2020;158(5):431-437.
22. Kam M, El-Meccawi S, Degen AA. Foraging behaviour and diet selection of free-ranging sheep and goats in the Negev Desert, Israel. The Journal of Agricultural Science. 2012;150(3):379-387.
23. Sircely JA, Gluecks IV, Kimengich N. ILRI Kapiti Plains Research Station: Grazing plan for early 2020. Nairobi: International Livestock Research Institute; 2020.
24. Miguel MF, Ribeiro-Filho HMN, de Andrade EA, Genro TCM, Delagarde R. Pasture intake and milk production of dairy cows grazing annual ryegrass with or without corn silage supplementation. Animal Production Science. 2014;54(10):1810-1816.
25. Yayneshet T, Eik LO, Moe SR. Influences of fallow age and season on the foraging behavior and diet selection pattern of goats (Capra hircus L.). Small Ruminant Research. 2008;77(1):25-37.
26. Ferreira LMM, Celaya R, Benavides R, Jáuregui BM, García U, Santos AS, et al. Foraging behaviour of domestic herbivore species grazing on heathlands associated with improved pasture areas. Livestock Science. 2013;155(2-3):373-383.
27. Mohammed AS, Animut G, Urge M, Assefa G. Grazing behavior, dietary value and performance of sheep, goats, cattle and camels co-grazing range with mixed species of grazing and browsing plants. Veterinary and Animal Science. 2020;10:100154.
28. Marcone G, Kaart T, Piirsalu P, Arney DR. Panting scores as a measure of heat stress evaluation in sheep with access and with no access to shade. Applied Animal Behaviour Science. 2021;240:105350.
29. Gregorini P, DelaRue B, McLeod K, Clark CEF, Glassey CB, Jago J. Rumination behavior of grazing dairy cows in response to restricted time at pasture. Livestock Science. 2012;146(1):95-98.
30. Sun D. Decoding calf patterns: Advancing automated health monitoring with algorithmic insights. Wageningen: Wageningen University and Research; 2023.
31. Elgersma A, Søegaard K. Changes in nutritive value and herbage yield during extended growth intervals in grasslegume mixtures: Effects of species, maturity at harvest, and relationships between productivity and components of feed quality. Grass and Forage Science. 2018;73(1):78-93.
32. Van Soest PJ. Nutritional ecology of the ruminant. 2 nd ed. Ithaca: Cornell University Press; 1994.
33. Mburu LM. Effect of seasonality of feed resources on dairy cattle production in coastal lowlands of Kenya. Nairobi: University of Nairobi; 2015.