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The Spatial Distribution of Chacma Baboon (Papio Ursinus) Habitat Based on an Environmental Envelope Model

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The Spatial Distribution of Chacma Baboon (Papio Ursinus) Habitat Based on an Environmental Envelope Model Int J Primatol DOI 10.1007/s10764-013-9669-9 The Spatial Distribution of Chacma Baboon (Papio ursinus) Habitat Based on an Environmental Envelope Model Olivia M. L. Stone & Shawn W. Laffan & Darren Curnoe & Andy I. R. Herries Received: 26 September 2012 /Accepted: 30 January 2013 # Springer Science+Business Media New York 2013 Abstract Predictive spatial modeling has become a key research tool for species distribution modeling where actual data are limited. Although qualitative maps and distribution descriptions for chacma baboons (Papio ursinus) are freely available, quantitative data are limited and do not provide the empirical information required to make informed decisions about issues such as population assessment, conservation, and management. Here we present the first quantitative, repeatable, and detailed predicted spatial distribution of the chacma baboon across southern Africa. Our distribution is at a finer level of detail than has previously been available. We used an environmental envelope model implemented within a geographic information system to achieve this. The model used environmental layers representing water availability, temperature and altitude, and model parameters determined from geore- ferenced observational data. The data extracted from the environmental layers sug- gest chacma baboons inhabit areas with mean minimum temperatures of the coolest month as low as −6.1 °C, mean maximum temperatures of the warmest month as high as 38.2 °C, mean annual rainfall up to 1,555 mm, and altitude up to 3,286 m. Our model demonstrates that the distribution of chacma baboons may be limited by temperature and rainfall, with the predicted northern extent of its range being temperature dependent. The model also implies that some areas well known for chacma baboon occupation today may in fact be marginal habitat. The resulting map highlights areas of suitable habitat in southern Africa. In addition, a linear “patchy” corridor was identified following the East African Rift Valley connecting Electronic supplementary material The online version of this article (doi:10.1007/s10764-013-9669-9) contains supplementary material, which is available to authorized users. O. M. L. Stone (*) : S. W. Laffan : D. Curnoe School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia e-mail: [email protected] A. I. R. Herries Archaeology Program, School of Historical and European Studies, Faculty of Humanities and Social Sciences, La Trobe University, Bundoora, Melbourne, VIC 3086, Australia O.M.L. Stone et al. the southern habitat with northeast Africa. We find the greatest proportion of suitable habitat to be located in South Africa. This modeling approach is generic and would be suitable to analyze other primate species across similar geographic extents. Keywords Chacma baboon . Distribution . Habitat . Papio . Southern Africa Introduction Population, distribution, and landscape models are becoming vital ecological tools in conservation and management (Dunning et al. 1995), providing ecological estimates both in the absence of, and in combination with, actual data. The rapid pace and widespread impacts of economic development in Africa have meant that in some regions conservation managers are turning their attention to non-threatened species in order to manage biodiversity (Ezemvelo KZN Wildlife 2008). Unfortunately, gaining basic ecological knowledge for common species is often overlooked in favor of protecting endangered or financially beneficial animals. This is despite the need for more information to provide insight into species distributions, habitat preferences, and potential migration patterns. Detailed distributions are needed to assess the effects of ecological change and species responses to anthropogenic and climatic effects, including the future impacts of global warming. Environmental envelope models (EEM) (Guisan and Zimmermann 2000) imple- mented within geographic information systems (GIS) can be used to predict species distributions. Both the environmental and the climatic limitations of the focal organ- ism constrain the EEMs. Many factors limit species distributions at a local scale, i.e., home ranges, day ranges, or foraging times (Altmann and Altmann 1970; Brain 1990; Hill 2005), but at a continental scale climatic effects are known to dominate species distributions (Pearson and Dawson 2003). Suitable habitat is considered to comprise the set of locations that fall within the defined envelopes for all environmental variables (Franklin 2009; Walker and Cocks 1991). This allows for an easily inter- preted model, as well as one that can be extrapolated to unsampled locations as a prediction. Researchers have used GIS-based approaches successfully to analyze primate habitats including habitat association, prediction, selection, ranging patterns, and zoonotic disease transfer (Harcourt 2000; Hoffman and O’Riain 2012; Hopkins and Nunn 2007; Junker et al. 2012; Ostro et al. 2000; Sleeman 2005; Stickler and Southworth 2008; Zinner and Torkler 1996). Chacma baboons are a widespread species, inhabiting much of southern Africa, though detailed distribution data are limited. Geographically, chacma baboons are the southernmost of five to six commonly recognized species (Groves 2001; Grubb et al. 2003; Zinner et al. 2009), inhabiting an area from immediately north of the Zambezi River to the Cape of Good Hope (Jolly 1993). For the most part, chacma baboon distribution maps are generalized, with the finer details of its distribution being poorly understood. As a result, published estimates are spatially general, qualitative, and based mostly on nonrepeatable methods (Anderson 1982; Henzi and Barrett 2003; Hoffman and Hilton-Taylor 2008; Skinner and Chimimba 2005; Zinner et al. 2009). This is surprising considering the genus Papio is one of the most intensively studied of non-human primate taxa (Newman et al. 2004). Spatial Modeling for Distribution of Chacma Baboons The published literature suggests temperature, availability of water, and altitude are likely to be the main environmental variables affecting habitat selection for Papio (Altmann 1974; Biquand et al. 1992; Dunbar 1992; Henzi et al. 1992; Hill 2005). This is consistent with findings from a wide range of organisms (Cavagnaro 1988; Engelbrecht et al. 2007; Guisan and Thuiller 2005). Chacma baboons inhabit areas with temperatures ranging from <−10 °C to >40 °C (Anderson 1982; Cowlishaw 1997; Gaynor 1994; Henzi et al. 1992; McQualter 2005; Noser and Byrne 2007;Van der Weyde 2004). Extreme cold restricts baboon home ranges, with baboons avoiding areas until the ground temperature returns to >0 °C (Henzi et al. 1992). Although resting time —which is directly influenced by temperature variation— is an important determinant of primate distribution, Papio and another African genus, Chlorocebus, are exceptions to this rule (Korstjens et al. 2010). Further, although high temperatures led to a decrease in foraging activity and the pursuit of shade to reduce the impact of solar radiation (Hill 2005, 2006), this held true only for locations where day length allowed the primates to rest without adversely affecting foraging. Baboons continued to forage regardless of temperature variation in areas with shorter day lengths. Interestingly, locations with longer summer day lengths were those with lower temperatures that, in theory, would be less detrimental to foraging. Although primate populations are known to suffer in drought conditions (Lemur catta: Gould et al. 1999; Cercopithecus aethiops: Struhsaker 1973; Semnopithecus entellus: Waite et al. 2007), Papio demonstrates marked interspecies variation in its responses to rainfall and water availability, ranging from more arid regions in Saudi Arabia (Biquand et al. 1992) to high rainfall regions in Kenya and Ethiopia (Dunbar and Dunbar, 1974; Popp 1979). Published data indicate that chacma baboons inhabit areas with annual rainfall ranging from <20 to >1,400 mm (Barrett and Henzi 1997; Hamilton et al. 1976). Both water availability and the distribution of drinking sites affect the day range and home range of Papio (Altmann and Altmann 1970; Barton et al. 1992; Hall 1963; Stoltz and Saayman 1970). The amount of time elapsed without water, and the distribution of water itself, appear to limit baboon distribution. Chacma baboons have been recorded to abstain from drinking for between 1 and >90 days, demon- strating a partial independence from drinking water (Brain 1988, 1990; Brain and Bohrmann 1992; Brain and Mitchell 1999). However, if food substitutes are not available, a single water source within a day range is required (Brain 1988; Hamilton 1985). Eight kilometers appears to be the farthest reported distance from which a troop may reside from a water source (Brain 1988). Overall, the distance from a water supply appears to restrict how far baboon troops traveled, with areas reportedly rich in food left unoccupied as they were beyond range from permanent water sources (Altmann 1974; Hamilton et al. 1976). A negative association exists between the altitude of the home range and group size for chacma baboons (Hall 1963), unlike hamadryas baboons, which tend to have larger groups at higher altitudes (Zinner et al. 2001). Dunbar (1992) suggested that Papio would not inhabit an altitude >3,000 m. However, olive baboons have been found at altitudes ranging from 3,200 to 3,600 m (Stephens et al. 2001)where conditions are less restrictive than in southern Africa. The highest
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