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Evaluating The Effectiveness Of Wildlife Underpassess Of The SGR At Nairobi National Park

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Wildlife underpasses facilitate animal movement under linear infrastructures and are generally located where railways cross watercourses, roads and natural resource areas. However, underpasses can be specifically designed to be used by animals (Glista et al. 2009; Jackson and Griffin 2000). Therefore, underpasses show considerable differences in size, and provide variable crossing facilities. Underpasses can be very large (i.e., viaducts, expanded bridges), where railways cross large watercourses and extensive valleys, in which it is assumed that passage for wildlife is limited, or they can be relatively small when, for example, they are only meant to allow the access of local vehicles between agricultural fields. Small underpasses may provide limited use for wildlife crossing if they are associated with roads with considerable traffic, or when they are completely flooded by the watercourse.

Exclusion fences are currently considered to be the most effective means to restrict wildlife access to railways (Ito et al. 2013; van der Grift 1999) being, probably, the best cost-effective measure to mitigate wildlife mortality in the long run (Dorsey et al. 2015). However, fences may be less effective for species capable of climbing, jumping over, or digging under them (Jackson and Griffin 2000). When fencing is used, it is crucial to provide escapes to avoid animals becoming trapped between fences on both sides of the railway (Jackson and Griffin 2000).

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Habitat connectivity denotes the functional connection between habitat patches. It is a vital, species-specific property of landscapes, which enables the movement of an animal within a landscape mosaic (Baudry and Merriam 1988; Taylor et al. 1993). Connectivity is achieved when the distances between neighboring habitat patches are short enough to allow individuals to cross easily on a daily basis. Animal movements are an important consideration in wildlife management and conservation. Knowledge about the type and the extent of animal movement may help to increase traffic safety, reduce road and rail mortality and/or find adequate places for mitigation measures such as fences and fauna passages (Putman 1997; Finder et al. 1999; Keller and Pfister 1997).

More recently, the protection of the habitats crossed by railways and their wildlife has become a main factor to be taken into consideration when designing new railways or maintaining existing ones (Clauzel et al. 2013; Profillidis 2014), associated with an increased societal awareness of the importance of biodiversity (Pereira et al. 2012). However, compared to other transportation systems, such as roads, less is known about the impact of railways on wildlife, as well as its specificities. Whereas there is a large body of research on road ecology, much less exists on railway ecology (Popp and Boyle 2017). Therefore, as the global railway network increases, and more countries promote railways over road or air transportation of people and goods, a review of the state-of-knowledge in railway ecology is needed. Railway ecology is an emerging field, but with scarce (and scattered) information about its effects on biodiversity (e.g., Dorsey et al. 2015; Popp and Boyle 2017). Empirical data on animal movement is still limited and this study seeks to generate data and information to understand where, and how, artificial or semi-natural structures can be used to lead animals safely across infrastructure barriers.

Nairobi National Park which is 117km2 is a major and the oldest National Park which was established in 1946. It’s the only close capital- metropolitan National Park in the world and ranks 5th in respect to visitation and income generation within the network in the Country. It’s one of Kenya’s most successful black rhinoceros sanctuaries, the migrating herbivores that gather in the Park during dry seasons. Wildlife migrating reach their southern pastures by migrating through the Athi Plains in Kitengela. However due to developments and growth of human population and the need for more land for settlement due to urbanization pose a threat to cut off and block the traditional migration routes. The parks wildlife species are also threatened by changing settlement patterns, fencing and infrastructure developments of Standard Gauge Railway and Roads. The ecosystem of wildlife is fragmented as their habitats is occupied by many activities occurring at the moment. The SGRs current re-aligned route encroaches on 87.29 ha of land of the NNP, which is a significant portion of the wildlife habitat (Habitat-Planners, 2016). Impacts related to the construction of SGR activities include vegetation clearance, land burrowing and filling, noise and air pollution. Phase 2A of the SGR is being aligned and it cuts the park along a 6km stretch and 15m single track way leave (Habitat-Planners, 2016).

According to Seiler and Folkerson (2006), new habitat edges are created by the physical construction of railways and roads in the landscape. Apart from infrastructure inflicting movement barriers to most of the terrestrial animals, it also results in the death of millions of individual animals every year (Seiler, 2006). The causing driver of the decline are not well understood, but it has been hypothesized that the causes of decline include habitat loss, habitat fragmentation and habitat constriction, human disturbance caused by land use changes in the landscape through encroachment and destruction. In particular the SGR will interfere with wildlife distribution and migration corridors that animals have been using for the longest time. The design of the SGR proposes to incorporate the culverts and underpass bridges in order to maintain the ecosystem connectivity and allow wildlife movement, but that does not seem to be realistic since wildlife are not easy to train like domestic ones (Murithi, 2015). This study therefore seeks to fill the knowledge deficit by looking at the effectiveness of the wildlife underpasses constructed under SGR on wildlife movements and distribution in NNP.

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