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      Spotted hyaena population density across habitat and land use types in southern Tanzania

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          Abstract

          Although the spotted hyaena ( Crocuta crocuta) has been widely considered to be resilient to human disturbance, the species is now thought to be undergoing widespread population declines. Nevertheless, only a handful of population density estimates are available for the species, despite the importance of this information for informing conservation management. This is a consequence of both a lack of surveys and logistical challenges associated with processing spotted hyaena data. In this study, we collaborated with a cohort of students to process camera trap data from the Ruaha‐Rungwa landscape initially collected to estimate lion ( Panthera leo) and leopard ( Panthera pardus) population density. By doing so, we provide the first spatially explicit population density estimates for spotted hyaena in Tanzania, via spatially explicit capture‐recapture (SECR) modelling. We also examine the relationship between population densities of spotted hyaena, lion and leopard at each site. Spotted hyaena densities varied from 3.55 ± 0.72 adults and sub‐adults per 100 km 2 in a miombo ( BrachystegiaJulbernardia) woodland area of Ruaha National Park, to 10.80 ± 1.08 per 100 km 2 in a prey‐rich open woodland savannah habitat in Ruaha National Park, with intermediate densities recorded in Rungwa Game Reserve and MBOMIPA Wildlife Management Area. Our results suggest that spotted hyaena density is influenced by prey availability and protection, and the species may be less resilient to human pressures than widely thought. Spotted hyaena densities were generally positively correlated with densities of lion and leopard, suggesting that prey availability and anthropogenic disturbance had a greater impact than interspecific effects in shaping large carnivore densities in this system. Overall, our study provides some of the first insights into an under‐studied species in an under‐researched part of its range, while shedding light into the impact of anthropogenic versus interspecific effects in shaping population status of spotted hyaena in human‐impacted African systems.

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              Spatially explicit maximum likelihood methods for capture-recapture studies.

              Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore straightforward. Additional (nonspatial) variation in capture probability may be modeled as in conventional capture-recapture. The method is tested by simulation, using a model in which capture probability depends only on location relative to traps. Point estimators are found to be unbiased and standard error estimators almost unbiased. The method is used to estimate the density of Red-eyed Vireos (Vireo olivaceus) from mist-netting data from the Patuxent Research Refuge, Maryland, U.S.A. Estimates agree well with those from an existing spatially explicit method based on inverse prediction. A variety of additional spatially explicit models are fitted; these include models with temporal stratification, behavioral response, and heterogeneous animal home ranges.
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                Author and article information

                Contributors
                Journal
                Journal of Zoology
                Journal of Zoology
                Wiley
                0952-8369
                1469-7998
                January 2024
                October 19 2023
                January 2024
                : 322
                : 1
                : 89-100
                Affiliations
                [1 ] Wildlife Conservation Research Unit, Department of Biology University of Oxford Tubney UK
                [2 ] Lion Landscapes Iringa Tanzania
                [3 ] Panthera New York NY USA
                [4 ] Southern Tanzania Elephant Program Iringa Tanzania
                [5 ] Department of Psychology University of Stirling Stirling UK
                [6 ] Tanzanian Elephant Foundation Kilimanjaro Tanzania
                [7 ] Department of Evolution, Behaviour and Environment University of Sussex Brighton UK
                [8 ] Tanzania National Parks Arusha Tanzania
                Article
                10.1111/jzo.13119
                a5d3675f-c941-40e9-aa49-a8ebee646c37
                © 2024

                http://creativecommons.org/licenses/by/4.0/

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