Characteristics of Human-Wildlife Conflicts in Kenya: Examples of Tsavo and Maasai Mara Regions

Mukeka, Joseph M.; Ogutu, Joseph O.; Kanga, Erustus

doi:10.5539/enrr.v8n3p148

Cited by 21 publications

(18 citation statements)

References 36 publications

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“…African savanna elephants were most commonly reported as damage-causing-a finding consistent with other studies in Africa and Asia (Acharya et al, 2016;Gubbi, 2012;Long et al, 2020). Here we show that the severity of conflict is influenced by a variety of factors, including the type of agriculture, the stage of crop production and the presence of wildlife species known to cause such damage (Mukeka et al, 2018;Ravenelle & Nyhus, 2017).…”

Section: Discussionsupporting

confidence: 90%

“…Similarly, infrastructure damage was predicted to peak in the dry season or after prolonged droughts when elephants are more likely to break water pipes and damage water storage facilities that sustain both domestic livestock and humans. By contrast, crop raiding was predicted to intensify during the summer months after rainfall when crops are well established (Mukeka et al, 2018). We discuss these and other predictors in the context of a national‐level understanding of potential HWI drivers on communal conservancies in Namibia.…”

Section: Introductionmentioning

confidence: 99%

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Multispecies study of patterns and drivers of wildlife impacts on human livelihoods in communal conservancies

Tavolaro

Woodgate

Brown³

et al. 2022

Conservat Sci and Prac

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Farmers in developing countries often work in challenging environments with poor infrastructure, marginal agricultural potential, and limited economic opportunities. These challenges are exacerbated when wildlife impact human livelihoods. Here, we analyze data quantifying the type and frequency of human‐wildlife impacts within communal conservancies across Namibia and explore possible drivers of temporal and spatial variation of these data. A total of 112,165 human‐wildlife impacts were reported between 2001 and 2019 at the national level, with livestock depredation the most common. Marked regional variation was however evident with crop raiding and attacks on humans more prevalent in the mesic North‐East, and both livestock depredation and infrastructure damage highest in the arid north‐western regions. Elephant, jackal, hyena, cheetah, and leopard (in descending order) were the species most frequently linked to reported damage. Distance to the nearest protected area and river, terrain ruggedness, conservancy size, and annual rainfall (amongst others) all had a significant impact on both the distribution and extent of human‐wildlife impact reports. Reports did not vary significantly with years but were significantly influenced by average monthly rainfall. Understanding spatial and temporal patterns of human‐wildlife impacts at a national scale, in addition to their potential drivers, allows for the identification of conflict hotspots and the allocation of resources and expertise to mitigate them. Ultimately, mitigating negative interactions between people and wildlife will allow for the continued sharing of space and with that the sustainability of a model that has seen a dramatic increase in both the distribution and abundance of wildlife in Namibia.

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Section: Discussionsupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Multispecies study of patterns and drivers of wildlife impacts on human livelihoods in communal conservancies

Tavolaro

Woodgate

Brown³

et al. 2022

Conservat Sci and Prac

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“…Land management type: We hypothesize that National Parks and Reserves will have larger lion group sizes compared to the other land management types since land that is under an official wildlife protection status is associated with higher protection from human activities (John Mining activities, illegal livestock grazing, increasing human population along park and conservancy boundaries increase in public infrastructure, that is, road and railway Cattle ranching and agriculture (Elliot et al, 2021;Mukeka et al, 2020) group at any one time, (2) subgroup size-the number of individuals present at each observation. To explore large-scale differences across land management type and between sites we used group size, whereas to explore the influence of variables at a finer scale and on fission-fusion dynamics, we used subgroup size.…”

Section: Lion Group Sizementioning

confidence: 99%

Effect of ecological and anthropogenic factors on grouping patterns in African lions across Kenya

Chege,

Bertola,

De Snoo

et al. 2024

Ecology and Evolution

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Social carnivores frequently live in fission–fusion societies, where individuals that share a common territory or home range may be found alone, in subgroups, or altogether. Absolute group size and subgroup size is expected to vary according to resource distribution, but for species that are susceptible to anthropogenic pressures, other factors may be important drivers. African lions (Panthera leo) are the only truly social felid and lion prides are characterized by fission–fusion dynamics with social groups frequently splitting and reforming, and subgroup membership can change continuously and frequently. The number of individuals in a group can be reflective of social, ecological, and anthropogenic conditions. This dynamic behavior makes understanding lion grouping patterns crucial for tailoring conservation measures. The evolution of group living in lions has been the topic of numerous studies, and we drew on these to formulate hypotheses relating to group size and subgroup size variation. Based on data collected from 199 lion groups across eight sites in Kenya, we found that group sizes were smaller when lions were closer to human settlements, suggesting that edge effects are impacting lions at a national scale. Smaller groups were also more likely when they were far from water, and were associated with very low and very high levels of non‐tree vegetation. We found significant differences between the study sites, with the Maasai Mara having the largest groups (mean ± SD = 7.7 ± 4.7, range = 1–19), and Amboseli conservation area the smallest (4.3 ± 3.5, range = 1–14). While long‐term studies within a single site are well suited to thoroughly differentiate between absolute group size and subgroup size, our study provides unique insight into the correlates of grouping patterns in a vulnerable species at a national scale.

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“…stations (Figure 1) on a daily basis and transmitted to the Security Division through an elaborate radio network (Mukeka et al, 2018). Overall, the KWS operates over 265 security patrol bases in 38 of the 47 counties, outposts and park gates (not shown in Figure 1), for an average of seven bases per county, that feed wildlife-related data and information to the KWS headquarters.…”

Section: Hypotheses and Their Predictions Rationalementioning

confidence: 99%

Long-term trends in elephant mortality and their causes in Kenya

Mukeka¹,

Ogutu²,

Kanga³

et al. 2022

Front. Conserv. Sci.

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High mortality poses a serious threat to sustainable conservation of the African elephant (Loxodonta africana). Using detected carcass data collected by the Kenya Wildlife Service (KWS) during 1992-2017, we analyze temporal and spatial variation in elephant mortality in Kenya. We investigate the major mortality causes and means used to kill elephants, carcass category, tusk recovery status, variation in mortality with elephant age and sex classes, differences between inside and outside protected areas (PAs), the Proportion of Illegally Killed Elephants (PIKE) and the overall mortality rate (MR — the number of dead/number of live elephants in a given year). In total 9,182 elephant deaths were recorded during the 26 years. Elephant mortality increased over time and was attributed primarily to natural (33.1%) and human-related causes, particularly ivory poaching (31.5%) and human-elephant conflicts (19.9%). Elephant mortality varied across Kenya’s 47 counties in correspondence with variation in elephant population size and was the highest in the leading elephant range counties of Taita Taveta, Laikipia, Samburu and Meru. Mortality was higher for males and adults and outside the protected areas. Most elephant carcasses had tusks (75.1%) but a few did not (12.5%). Yearly PIKE values peaked in 2012, the year with the highest poaching levels in Kenya during 1992-2017. MR increased throughout 1992-2017. Temporal variation in elephant mortality probability was significantly influenced by human and livestock population densities, average annual maximum temperature and total annual rainfall and the strength of these influences varied across the seven leading elephant range counties of Kenya. Natural processes are increasingly contributing to elephant mortality likely due to climate change and the associated food and water stress, exacerbated by contracting range. Enhancing anti-poaching and strategies for mitigating climate change impacts and human-elephant conflict and reducing range contraction while sustaining habitat connectivity can help reduce mortality and promote elephant conservation. Strengthening enforcement of international wildlife laws can further reduce illegal trade in tusks and killing of elephants.

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Characteristics of Human-Wildlife Conflicts in Kenya: Examples of Tsavo and Maasai Mara Regions

Cited by 21 publications

References 36 publications

Multispecies study of patterns and drivers of wildlife impacts on human livelihoods in communal conservancies

Multispecies study of patterns and drivers of wildlife impacts on human livelihoods in communal conservancies

Effect of ecological and anthropogenic factors on grouping patterns in African lions across Kenya

Long-term trends in elephant mortality and their causes in Kenya

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