Occurrence and Level of Elephant Damage to Farms Adjacent to Mount Kenya Forests: Implications for Conservation

Incidences of elephant’s crop raids in Mount Kenya area have escalated in the recent past causing considerable damage to the fragile local economy that is mainly peasant farming.  Studies on crop-raiding predisposing factors, nature and extent of the damage in this region are scanty. Thus, this was the aim of this study.  Data was obtained from questionnaires and occurrence books at Kenya Wildlife Service between 1997 – 2000.  Elephant movements were mapped in relationship to watering points and salt licks.  It was found that crop-raiding incidences by elephants were widely spread over the study area (80%, n = 487).  Crop damage severity was about 16.8 % of the expected yields.  Levels of crop damage were positively correlated to crop occurrence (r = 0.982, P = 0.01).  Thus, damage levels were substantive. Elephant’s crop-raids should stop.  Fencing off elephant from farmland will solve crop-raiding problems and enhance their conservation. Keywords: Elephants crop-raiding, human-wildlife conflict, forest fragmentation, conservation area barrier

How “science” can facilitate the politicization of charismatic megafauna counts

Ideally, the practice of science stays independent, informs policy in real time, and facilitates learning. However, when large uncertainties go unreported or are not effectively communicated, science can, inadvertently, facilitate inappropriate politics.http://www.pnas.orgam2023Mammal Research InstituteZoology and Entomolog

Movement Patterns of African Elephants (Loxodonta africana) in a Semi-arid Savanna Suggest That They Have Information on the Location of Dispersed Water Sources

Water is a scarce resource in semi-arid savannas where over half of the African elephants (Loxodonta africana) populations occur and may therefore influence their movement pattern. A random search is expected for an animal with no information on the location of the target resource, else, a direction-oriented walk is expected. We hypothesized that elephants movement patterns show a stronger directional orientation toward water sources in the dry season compared to the wet season. We investigated the movement paths of four male and four female elephants with hourly GPS fixes in Tsavo National Park, Kenya in 2012–2013. Consistent with our predictions, the movement paths of elephants had longer step lengths, longer squared net displacements, and were directed toward water sources in the dry season as compared to the wet season. We argue that African elephants know the location of dispersed water resources, enabling them to survive with scarce resources in dry savannas. These results can be used in conservation and management of wildlife, through for instance, protection of preferred water sources

Using Range Condition Assessment to Optimize Wildlife Stocking in Tindress Wildlife Sanctuary, Nakuru District, Kenya

Over 70% of Kenya’s wildlife resources occur outside protected areas, in areas where land use practices do not necessarily conform to wildlife conservation standards. Ensuring that land use practices in these areas accommodate wildlife conservation is vital in effectively conserving wildlife in this country. Tindress Farm in Rift Valley offers a good example of a place where economic activities and wildlife conservation can work harmoniously. The farm has set up a 320-ha wildlife sanctuary in the hilly parts of the property to provide a haven for wildlife displaced by human settlements in the surrounding environs. The Tindress Farm management needed to know the diversity and optimum number of wildlife species that the sanctuary could accommodate. This study set out to 1) outline a set of models for objectively calculating wildlife stocking levels and 2) demonstrate the practical use of these models in estimating optimum stocking levels for a specific wildlife sanctuary. After comparing models using forage inventory methods models and utilization-based methods (UM), we opted to use UM models because of their focus on ecological energetics. This study established that the range condition in Tindress Wildlife Sanctuary varied from poor to good (29-69%) and recommended a total stocking density of 158.9 grazer units and 201.4 browser units shared out by the various herbivore species. These estimates remain a best-case scenario. The effects of rainfall, range condition, and condition of the animals should be monitored continuously to allow for adjustments through active adaptive management.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202

African elephant (Loxodonta africana) select less fragmented landscapes to connect core habitats in human‐dominated landscapes

African elephants (Loxodonta africana) utilise corridors to access limited resources, that is forage and water scattered across heterogeneous habitats they roam. The existence of small elephant metapopulations depend on the intactness of these corridors to access the scarce resources. Due to the sedentarisation of the previously nomadic Maasai people, elephant corridors have been exposed to increased fragmentation from human-induced activities across the Amboseli ecosystem in Kenya. In this study, we sought to compare the scale of fragmentation between corridors and their immediate landscapes (noncorridors) in the Amboseli ecosystem, Kenya. We used a Brownian Bridge Movement Model (BBMM) to identify corridors used by elephants from global positioning system (GPS) collar data. The scale of fragmentation between corridors and noncorridors was determined using the effective mesh size fragmentation metric (m eff). Our results showed that elephant corridors were significantly less fragmented (Wilcoxon sum rank test: W = 6,121.5, p < 0.05) when compared to the noncorridors. The presence of fragmentation geometries in the corridors remains a major cause of concern for wildlife managers as they have the potential to invade and constrict the existing corridors. Our results underscore the need to extend management of elephant habitats to migration corridors outside protected areas

Elephants move faster in small fragments of low productivity in Amboseli ecosystems: Kenya

Understanding factors affecting the behaviour and movement patterns of the African elephant is important for wildlife conservation, especially in increasingly human-dominated savanna landscapes. Currently, knowledge on how landscape fragmentation and vegetation productivity affect elephant speed of movement remains poorly understood. In this study, we tested whether landscape fragmentation and vegetation productivity explains elephant speed of movement in the Amboseli ecosystem in Kenya. We used GPS collar data from five elephants to quantify elephant speed of movement for three seasons (wet, dry and transitional). We then used multiple regression to model the relationship between speed of movement and landscape fragmentation, as well as vegetation productivity for each season. Results of this study demonstrate that landscape fragmentation and vegetation productivity predicted elephant speed of movement poorly (R2 < 0.4) when used as solitary covariates. However, a combination of the covariates significantly (p < 0.05) explained variance in elephant speed of movement with improved R2 values of 0.69, 0.45, 0.47 for wet, transition and dry seasons, respectively

Assessing trends and seasonal changes in elephant poaching risk at the small area level using spatio-temporal Bayesian modeling

<p>Knowledge about changes in wildlife poaching risk at fine spatial scale can provide essential background intelligence for law enforcement and crime prevention. We assessed interannual trends and seasonal changes in elephant poaching risk for Kenya’s Greater Tsavo ecosystem for 2002 to 2012 using spatio-temporal Bayesian modeling. Poaching data were obtained from the Kenya Wildlife Service’s database on elephant mortality. The novelty of our paper is (1) combining space and time when defining poaching risk for elephant; (2) the inclusion of environmental risk factors to improve the accuracy of the spatio-temporal Bayesian model; and (3) the separate analysis of dry and wet seasons to understand season-dependent poaching patterns. Although Tsavo’s overall poaching level increased over time, the risk of poaching differed significantly across space. Three of the 34 spatial units had a consistently high poaching risk regardless of whether models included environmental risk factors. Adding risk factors enhanced the model’s predictive power. We found that highest poaching risk areas differed between the wet and dry season. The findings improve our understanding of elephant poaching and highlight high risk areas within Tsavo where action to reduce elephant poaching is required.</p