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"gazelles"
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Gazelles
Introduces the gazelle, discussing their physical characteristics, life cycle, and eating habits.
Book
Rigorous home range estimation with movement data: a new autocorrelated kernel density estimator
Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.
Journal Article
Lumpy Skin Disease Virus Infection in Free-Ranging Indian Gazelles ( Gazella bennettii ), Rajasthan, India
Near a zoo in Bikaner, India, 2 free-ranging Indian gazelles (Gazella bennettii) displayed nodular skin lesions. Molecular testing revealed lumpy skin disease virus (LSDV) infection. Subsequent genome analyses revealed LSDV wild-type strain of Middle Eastern lineage. Evidence of natural LSDV infection in wild gazelles in this area indicates a broadening host range.
Journal Article
Gazelle optimization algorithm: a novel nature-inspired metaheuristic optimizer
This study proposes a novel population-based metaheuristic algorithm called the Gazelle Optimization Algorithm (GOA), inspired by the gazelles’ survival ability in their predator-dominated environment. Every day, the gazelle knows that if it does not outrun and outmaneuver its predators, it becomes meat for the day, and to survive, the gazelles have to escape from their predators consistently. This information is vital to proposing a new metaheuristic algorithm that uses the gazelle’s survival abilities to solve real-world optimization problems. The exploitation phase of the algorithm simulates the gazelles grazing peacefully in the absence of the predator or while the predator is stalking it. The GOA goes into the exploration phase once a predator is spotted. The exploration phase consists of the gazelle outrunning and outmaneuvering the predator to a safe haven. These two phases are iteratively repeated, subject to the termination criteria, and finding optimal solutions to the optimization problems. The robustness and efficiency of the developed algorithm as an optimization tool were tested using benchmark optimization test functions and selected engineering design problems (fifteen classical, ten composited functions, and four mechanical engineering design problems). The results of the GOA are compared with nine other state-of-the-art algorithms. The simulation results obtained confirm the superiority and competitiveness of the GOA algorithm over nine state-of-the-art algorithms available in the literature. Also, the standard statistical analysis test carried out on the results further confirmed the ability of GOA to find solutions to the selected optimization problems. It also showed that GOA performed better or, in some cases, was very competitive with some state-of-the-art algorithms. Also, the results show that GOA is a potent tool for optimization that can be adapted to solve problems in different optimization domains.
Journal Article
Combined Effects of Clime, Vegetation, Human-Related Land Use and Livestock on the Distribution of the Three Indigenous Species of Gazelle in Eritrea
The status and habitat selection of the three species of gazelle indigenous to Eritrea, i.e., Nanger soemmerringii, Gazella dorcas and Eudorcas tilonura, are not well known. In this study, we analyzed the present distribution of the three species in the country in order to identify preferred habitats and assess the effect of human disturbance (land use for agricultural purposes and livestock) on species occurrence. These data represent baseline information for evidence-based strategies for conservation of the three species in Eritrea. Presence/absence data of the three species in each of the 67 administrative subregions (Sub Zoba) composing the country were collected using direct (field surveys) and indirect methods (questionnaires). For each sampling unit, we collected fifteen environmental variables, of which three are associated with climatic features, eight with vegetation structure and four with human disturbance (human-related land use and livestock). The occurrence probability of each species was modeled through Generalized Linear Models (GLM). The analyses showed that Dorcas gazelle occurred more frequently in warmer conditions and in a wide range of natural vegetation types. Heuglin’s gazelle occurred in warmer regions with higher seasonality in both temperature and precipitation with a preference for closed woody and open grassland areas. In the case of Soemmerring’s gazelle, the GLM with climatic variables predicted a preference for warmer conditions but with lower seasonality of temperature and precipitation. The species also seemed to prefer arid and semi-arid open vegetation. Human disturbance is the variable with the strongest, negative, effect on the species occurrence. Indeed, the occurrence probability of each species decreased with increasing livestock density and agricultural land use. Most of these gazelle occurred in unprotected areas, thus the human-related activities are undoubtedly the most important threat for the three species of gazelle in Eritrea. Therefore, the establishment of protected areas that preserve the potential optimal habitats for gazelle and reduce the impact of livestock ranching are essential to ensure a future for these gazelle in Eritrea.
Journal Article
XO, OX : a love story
\"The hilarious tale of an ox who is in love with a gazelle, told in correspondence\"-- Provided by publisher.
Book
Estimating where and how animals travel: An optimal framework for path reconstruction from autocorrelated tracking data
An animal's trajectory is a fundamental object of interest in movement ecology, as it directly informs a range of topics from resource selection to energy expenditure and behavioral states. Optimally inferring the mostly unobserved movement path and its dynamics from a limited sample of telemetry observations is a key unsolved problem, however. The field of geostatistics has focused significant attention on a mathematically analogous problem that has a statistically optimal solution coined after its inventor, Krige. Kriging revolutionized geostatistics and is now the gold standard for interpolating between a limited number of autocorrelated spatial point observations. Here we translate Kriging for use with animal movement data. Our Kriging formalism encompasses previous methods to estimate animal's trajectories—the Brownian bridge and continuous‐time correlated random walk library—as special cases, informs users as to when these previous methods are appropriate, and provides a more general method when they are not. We demonstrate the capabilities of Kriging on a case study with Mongolian gazelles where, compared to the Brownian bridge, Kriging with a more optimal model was 10% more precise in interpolating locations and 500% more precise in estimating occurrence areas.
Journal Article