Resource selection, utilization and seasons influence spatial ...

Resource selection, utilization and seasons influence spatial distribution of ungulates in the western Serengeti National Park John Bukombe1*, Andrew Kittle2,3, Ramadhan Senzota4, Simon Mduma1, John Fryxell2 and Anthony R.E. Sinclair5 1 Tanzania Wildlife Research Institute, P.O Box 661, Arusha, Tanzania, 2Department of Integrative Biology, University of Guelph, 50 Stone Road East, Guelph, Ontario, N1G 2W1, Canada, 3Wilderness & Wildlife Conservation Trust, No.130, Reid Avenue, Colombo, Srilanka, 4Department of Zoology and Wildlife Conservation, University of Dar es Salaam, P.O Box 35064, Dar es Salaam, Tanzania and 5Center for Biodiversity Research, University of British Columbia, 6270 University Boulevard, Vancouver, British Columbia V6TIZ4, Canada

Abstract

Resume

Understanding herbivore selection and utilization of vegetation types is fundamental to conservation of multispecies communities. We tested three hypotheses for how ungulate species select their habitats and how this changes with season: first, resources are distributed as a mosaic of patches so that ungulates are also distributed patchily; this distribution reflects habitat selection, which changes with season, the different ungulates behaving differently. Second, resources become scarcer in the dry season relative to those in the wet season. If interspecific competition prevails, then all species should show a contraction of habitats chosen. Third, if predation is limiting, competition will be minimal, and hence, habitat selection by herbivores will not differ between seasons. We used frequencies of occurrence in four common vegetation types in western Serengeti National Park to determine selection coefficients and utilization patterns and Chisquare analysis to test the hypotheses. The results showed that selection changes differently in each species, agreeing with the first hypothesis. Herbivores did not all become more selective, as predicted by the competition hypothesis, nor did selection remain the same across seasons, as predicted by the predation hypothesis. These results can be useful in constructing habitat suitability maps for ungulate species with special conservation needs.

Il est fondamental de comprendre la selection et la frequentation des differents types de vegetation par les herbivores pour assurer la conservation des communautes comprenant plusieurs especes. Nous avons teste trois la facßon dont les especes d’ongules hypotheses quant a choisissent leurs habitats et comment cela change avec les saisons. Premierement, les ressources sont distribuees en une mosa€ıque de parcelles de sorte que les ongules sont aussi repartis de la même facßon ; cette distribution reflete la selection de l’habitat, qui change avec les saisons, les divers ongules se comportant differemment. Deuxiemement, les ressources deviennent plus rares en saison seche la saison des pluies. Si c’est la competition par rapport a interspecifique qui domine, toutes les especes devraient presenter une contraction des habitats choisis. Troisiemement, si c’est la predation qui est limitante, la competition sera minimale et donc la selection de l’habitat par les herbivores ne sera pas differente selon les saisons. Nous avons utilise la frequence des occurrences dans quatre types de vegetation courants dans l’ouest du parc National de Serengeti pour determiner les coefficients de selection et les schemas d’utilisation, ainsi qu’un test du v² pour verifier les hypotheses. Les resultats ont montre que la selection change differemment selon les especes, ce qui la premiere hypothese. Les herbivores ne correspond a devenaient pas tous plus selectifs, comme le predisait l’hypothese de competition, et la selection ne restait pas la même en toute saison, comme le predisait l’hypothese de predation. Ces resultats peuvent être utiles pour elaborer des cartes de l’adequation des habitats pour des especes d’ongules qui ont des besoins de conservation particuliers.

Key words: distribution of Serengeti ungulates, seasons, vegetation type selection

*Correspondence: E-mail: [email protected]

© 2017 John Wiley & Sons Ltd, Afr. J. Ecol., 56, 3–11

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4 John Bukombe et al.

Introduction Early studies demonstrated that ungulate species differ in their use of different habitats in different seasons (Lamprey, 1963; Jarman, 1972). Suitable vegetation types are often strong indicators of herbivore movement and habitat use (Chynoweth et al., 2015). In tropical savannahs, seasonal variation in habitat preferences can be determined by several different processes. Vegetation commonly occurs as a mosaic of patches, and this mosaic determines the distribution of herbivores that prefer specific vegetation types (Cromsigt & Olff, 2006). In savannah landscapes, such as those of Serengeti, the different seasons of wet and dry periods alter the mosaic and this affects animal movement patterns (Fryxell, Greever & Sinclair, 1988; Sinclair, 1989; McCune & Mefford, 1995; Wilmshurst et al., 1999). Habitat selection theory predicts that animals should become less selective and accordingly broaden their use of different food and vegetation types in the dry season when food is scarce (Rosenzweig, 1981; Sinclair, 1985). This process would allow individuals of a single species to take advantage of a broader range of food and vegetation types (Mduma, Sinclair & Hilborn, 1999). In contrast, interspecific competition theory predicts that different species should narrow their range of vegetation types in the dry season (Sinclair, 1985), resulting in a reduction in species overlap in resources. This implies that each herbivore species should become more selective during the dry season to avoid competition with other species. Finally, if predation severely limits ungulate population abundance below the level determined by food supply, then both competition within and among species would be minimal, obviating the need for any habitat response (Sinclair & Arcese, 1995; Sinclair, Mduma & Brashares, 2003). The predator limitation hypothesis predicts that choices of vegetation types by different ungulate species should not change between wet and dry seasons. In this study, we use seasonal changes in selection for different vegetation types in the Serengeti ecosystem to test the predictions from these three hypotheses (habitat selection, interspecific competition and predator limitation).

Materials and methods Study area The study area of 2490 km2 is located between latitude 2° and 2°30″S and longitude 34° and 34°30″E

(Figure 1), in the western Serengeti ecosystem (Bukombe et al., 2015). The elevation ranges from 1140 m west of Lake Victoria to 2000 m at the top of the Nyaroboro plateau (Jager, 1982). The vegetation is a mix of grasslands and woodlands which is highly patchy (Reed et al., 2009). The maximum rainfall is 1100 mm per year and most of that rainfall occurs in two distinct seasons (November-December and March-May) with a dry season in July-October. There is marked interannual variation in rainfall which is influenced by climate change (Le Mar, 2002). The western Serengeti corridor lies between two main rivers, the Mbalageti River to the south and Grumeti River to the north; both drain the area towards Lake Victoria. Throughout the dry season, sporadic thunderstorms near Lake Victoria produce enough rain to keep certain parts of the area green. The two rivers dry up into a series of pools by the late dry season, thus allowing resident ungulates to remain in the area in small groups. Although fire in the dry season is often an important cause of vegetation patchiness in African savannahs, where it influences sward structure, forage composition and quality (Higgins et al., 1999), it was not considered here.

Transect surveys Animal surveys were conducted in 2010 and 2011 with two observers on each side of a vehicle travelling at an average speed of ≤20 kmh1 along the transect so that animals were not disturbed by the vehicle. Observations were made with a Bushnell rangefinder. Five ungulate species were observed, including three resident species (buffalo [Syncerus caffer caffer (Sparrman, 1979)], topi [Damaliscus korrigum jimela (Matschie, 1892)] and impala [Aepyceros melampus (Lichtenstein, 1812)]) and two migratory species (zebra [Equus quagga, (Boddaert, 1785)] and wildebeest [Connochaetes taurinus (Burchell, 1823)]). Species were recorded within a search radius of 500 m from the transect line. The vegetation was made up of a mosaic of patches of a scale of approximately 100 m across. Thus, vegetation was sampled within a one-hectare area around each animal observation using the physiognomic classification of Pratt & Gwynne (1977). Vegetation types at each animal observation were categorized as grassland (sites without or with woody vegetation not exceeding 5%), bushed grassland (sites with woody vegetation ranging between 5% and 20%), bushland (sites with trees and shrubs but dominated by shrubby habit not


Patch selection influence ungulate distribution

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Fig 1 Map showing location of the western Serengeti National Park, transects and vegetation types [Colour figure can be viewed at wileyonlinelibrary.com]

exceeding 20%) or woodland (sites with woody vegetation cover exceeding 20%). The spatial location of animals sighted along transects was recorded using the vehicle’s odometer (zeroed at the commencement of each transect), with odometer readings later geographically calibrated using GPS.


Determination of available habitat as a proportion of the total landscape We estimated the area of each of the three vegetation types as a proportion of the total available along each transect at intervals of 200 m. Each 200 m point was the centre of a rectangle


200 m (100 m in front and 100 m behind) along the transect and 1000 m wide (500 m on each side of the track), and within this rectangle, the proportion of each vegetation type was estimated. The total area of each vegetation type (pi) along each transect was obtained by summing the area of each vegetation type over all rectangles measured.

v2 ¼

X ðuþj Veij Þ2 =Veij :

(4)

A large Chi-squared value is indicative of poor agreement between observed and expected frequencies, with extreme values leading to rejection of the null hypothesis.

Results

Data analysis

Selection of vegetation types by ungulate species Determining selection ratios of vegetation types by ungulates. We used Manly et al. (2002) equation 1 to calculate the selection ratio by an ungulate species for a vegetation type in each season: xij ¼

uij =uþj pi

(1)

where xij is the selection ratio of vegetation type i by animal j, uij is the frequency of observations (termed the observed utilization) of animal species j in a vegetation type, u+j is the total frequency of observations (termed the total observed utilization) of the same animal species in all vegetation types, and pi is the proportion of habitat type i across the landscape. Preferential selection of a given vegetation type is indicated when xi > 1, but avoidance is indicated when xi < 1.

Vegetation selection ratios indicated that different vegetation types were typically selected by different ungulate species (Table 1, Fig. 2). While both impala and topi ^ ij \1), it was avoided bush grassland in the wet season (w ^ ij [ 1). During preferred by buffalo, wildebeest and zebra (w the wet season, woodland was avoided by buffalo, impala and topi, but was preferred by wildebeest and zebra. Patterns of habitat selection were markedly different in the dry season. In the dry season, buffalo and wildebeest avoided bush grassland, whereas impala and zebra avoided grassland. All species, except for topi, preferentially used woodland. The degree of selection of bush grassland habitat by impala and grassland habitat by topi changed little between seasons.

Utilization of vegetation types by ungulates Estimating the proportion of utilization of vegetation types. The approach used by Manly et al. (2002) in equation 2 below was used to estimate the proportion of utilization of vegetation type i (pij) of by ungulate species j in each season: pij ¼

uij : uþj

(2)

The proportions of utilization for each vegetation type were estimated for each animal species and season. Chi square analysis, with no association representing the null hypothesis (Zar, 1999), was used to test whether availability and utilization of vegetation types were independent. Assuming that the availability and utilization of vegetation types are independent, we predicted an expected utilization Veij for each cell in the contingency table using equation 3: Veij ¼ pij pi :

(3)

We then computed a Chi-square test statistic v2 by comparing each cell’s observed utilization frequency to its respective expected value Veij as shown in equation 4:

Utilization of bushland was not random during the wet season for all five ungulates (Table 2, Fig. 2). Utilization of grassland was also not random for topi, buffalo and impala. However, utilization of bushed grassland and woodland was typically random for all species, with the exception of topi in bushed grassland and impala and buffalo in woodland. In contrast, in the dry season, both bushland and woodland were used nonrandomly by all species. However, bushed grassland and grassland were used randomly by most species, the exceptions being topi in the former and topi and zebra in the latter.

Discussion The three hypotheses laid out in the introduction make different predictions. The habitat mosaic hypothesis states that resources are distributed as a mosaic of patches, leading consequently to a patchy distribution of ungulates. The competition hypothesis states that if resources become



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^ ij ) of vegetation types by ungulates in western Serengeti in the wet and dry seasons of 2010–2011 Table 1 Selection coefficients (w Vegetation Type Bush grassland

Bushland

Grassland

Woodland

Wet season

Dry season

Species

^ ij w

Direction of selectivity

^ ij w

Direction of selectivity

Buffalo Impala Topi Wildebeest Zebra Buffalo Impala Topi Wildebeest Zebra Buffalo Impala Topi Wildebeest Zebra Buffalo Impala Topi Wildebeest Zebra

1.03 0.9 0.83 1.1 1.03 0.3 0.0 0.1 0.1 0.1 1.2 1.1 1.2 1.03 1.03 0.69 1.0 0.85 1.02 1.1

+ + + + + + + + + +

0.8 0.9 1 0.8 1 0 0.2 0.2 0.4 0 1 0.9 1.1 1 0.9 1.3 1.3 1 1.2 1.4

ns ns ns + ns + + ns + +

The symbols showing the direction of selectivity: ‘+’ indicates selection P < 0.05; ‘’ indicates avoidance P < 0.05 and ns = not significant P ≥ 0.05.

more scarce in the dry season, then interspecific competition will be intensified, leading to contraction of habitat chosen and hence increased selectivity. The predator limitation hypothesis states that if predators severely limit herbivore population abundance, then resources will not be limiting, competition will be weak, and hence, habitat selection will not differ between seasons. Comparing our measurements of habitat selection in the wet vs. dry seasons with these predictions, it appears that the habitat mosaic hypothesis was most consistent with the data. Selection for habitats differed between species, and each species changed its selection between seasons in a different way. They did not all become more selective during the dry season period of resource scarcity, as predicted by the interspecific competition hypothesis, nor did habitat selection remain the same across seasons as predicted by the predator limitation hypothesis. Shifts in vegetation selection between the dry and wet seasons cannot be explained by predator limitation, because hyaenas and lions maintain group territories year-round. These conclusions are consistent with some previous published work on wildebeest (Wilmshurst, 1998;


Wilmshurst et al., 1999; Boone, Thirgood & Hopcraft, 2006), zebra and topi (Anderson et al., 2010) and buffalo and impala (Seagle & McNaughton, 1992). These earlier studies suggested that within each season, patterns of habitat selection differed between species, suggesting that species-specific habitat preferences influence the distribution of each ungulate species across the Serengeti landscape. This occurs most prominently in three vegetation types: bush grassland, grassland and woodland (Anderson et al., 2010; Bukombe et al., 2015). Ndibalema (2007) reported that grasslands, bush grassland and open woodland were the most heavily used vegetation types in western Serengeti. In our study, each of the ungulate species avoided bushland. While the reason for this was not obvious, we speculate that it may reflect inadequate availability of forage in bushland vegetation types. Seasonal shifts in herbivore habitat selection were in agreement with previous studies for wildebeest and zebra (Voeten & Prins, 1999), impala, topi and buffalo (Jarman & Sinclair, 1979; Meissner, Pieterse & Potgieter, 1996). One explanation for such seasonal shifts could be fluctuations in forage abundance (Sinclair, 1985; Hopcraft, Olff & Sinclair, 2010), forage quality (Anderson et al., 2010) in


Fig 2 Seasonal utilization of vegetation types by buffalo, zebra and wildebeest relative to that available in 2011–2012 in western Serengeti. % available (grey), % use in wet season (black), % use in dry season (open), where B is Bushland, Bg is Bushed grassland, W is Woodland and G is Grassland

relation to species functional differences (Hopcraft et al., 2012) and predation risk. Food is often more abundant and uniformly distributed in the wet than in the dry season. Species functional differences have been used to explain species overlap or segregation in patch use (Bell, 1969; Jarman & Sinclair, 1979; Hanley & Hanley, 1982; Langvatn & Hanley, 1993; Coe et al., 2005). Overlap in patch use could stem from weak interspecific competition (Van Wieren & Van Langevelde, 2008). In our study, the two migrant species (wildebeest and zebra) used several vegetation types in the wet season, but each species restricted their habitat choices in the dry season, preferentially using woodland vegetation. This pattern among the migrants suggests the possibility for meaningful levels of interspecific competition in the dry season, as suggested by the earlier studies by Sinclair (1985). Although the shifts in habitat use from grassland to woodland in the wet and dry seasons, respectively, by buffalo and impala probably signify the influence of seasonal differences in forage abundance, they are also

consistent with the predator limitation hypothesis because selection did not change with season. In addition, the choice of grassland in the wet season, which is a more open vegetation than woodland, could represent a strategy to reduce the risk of predation because grassland has greater visibility and less need for vigilance (Pratt & Gwynne, 1977; Crawley, 2007). Reduction in predation risk could similarly be one reason why topi were more restricted to grassland in both seasons. Another possible reason for topi to choose grassland is their specialized use of grass leaves on long stems (Murray & Brown, 1993; Murray & Illius, 2000), which have high nutritional content (Murray, 1993). The results for buffalo from our study disagree with those of Hopcraft et al. (2012) that the distribution of large grazers such as buffalo is not constrained by predation but by food abundance. The reason for our different results could stem from the different spatial scales used to identify vegetation types in the two studies. Our study used a smaller scale (one-ha plots) compared to Hopcraft et al.



Buffalo Impala Topi Wildebeest Zebra Buffalo Impala Topi Wildebeest Zebra Buffalo Impala Topi Wildebeest Zebra Buffalo Impala Topi Wildebeest Zebra

Species 0.1 1.7 3.8 1.7 0.3 5.8 36 22 52 40 4.4 7 13 0.9 0.5 6.2 0.2 3.7 0.1 1.1

v2(df = 1)

The words ‘accept’ indicate P > 0.05 and ‘reject’ indicate P < 0.05.

Woodland

Grassland

Bushland

Bush grassland

Vegetation Type

Wet season

Accept Accept Reject Accept Accept Reject Reject Reject Reject Reject Reject Reject Reject Accept Accept Reject Accept Reject Accept Accept

H0: Availability and utilization of vegetation types are independent. 1.8 0.6 0.2 9.1 0.2 8.9 26 17 27 43 0 1.7 2 1.1 4.5 6.3 24 3.7 11 32

v2(df = 1)

Dry season

Accept Accept Accept Reject Accept Reject Reject Reject Reject Reject Accept Accept Reject Accept Reject Reject Reject Reject Reject Reject

H0 Availability and utilization of vegetation types are independent.

Table 2 Chi-square association coefficients indicating whether the seasonal utilization of vegetation types by ungulates differs from random in western Serengeti in 2010–2011

Patch selection influence ungulate distribution 9

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John Bukombe et al.

(2012), who used distribution maps of 5 9 5 km blocks. As the vegetation of Serengeti is patchy at a fine scale of 100 m diameter (Reed et al., 2009), the large scale of 5 km could obscure fine-scale habitat selectivity. Our results reveal surprisingly high levels of utilization of woodland vegetation by ungulate species in the dry season compared to other vegetation types. This may occur because in the dry season, woodland habitats are better at providing nutritious food species such as forbs and grasses such as Panicum maximum (Treydte et al., 2007, 2013), which grow in shade under trees (Vetaas, 1992; Scholes & Archer, 1997; Owen-Smith & Cooper, 2010). These plant species are highly palatable, especially in the dry season (Frank, McNaughton & Tracy, 1998; Fritz et al., 2002). Selection for certain habitats is critical for conservation purposes. However, it is often difficult to detect which factor is most responsible for herbivore spatial responses (Andrew, Bleich & August, 1999). For example, our data show that buffalo, wildebeest and zebra selected bush grassland in the wet season. It is not clear from our results whether they were selecting food type, visibility within the landscape or proximity to water. The multifaceted interactions among variables can be important in defining the way that ungulates use vegetation types and hence their distribution across landscapes (Andrew, Bleich & August, 1999).

Acknowledgements This work was funded by the Canadian Natural Sciences and Engineering Research Council grants to J. M. Fryxell and A. R. E Sinclair and the Commission for Science and Technology in Tanzania (COSTECH). We appreciate the assistance of Drs. Michael Anderson and Tom Morrison in R statistics. Thanks to Mr. Hamza Kija for helping in Map production and Mr. Deusdedit Lugemalila for offering R statistics software. We highly appreciate the assistance in data collection by Mr. Emilian Mayemba, Mr. Ally Nkwabi, Mr. John Mchetto and Mr. Joseph Masoy.

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