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      No room to roam: King Cobras reduce movement in agriculture

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          Abstract

          Background

          Studying animal movement provides insights into how animals react to land-use changes. As agriculture expands, we can use animal movement to examine how animals change their behaviour in response. Recent reviews show a tendency for mammalian species to reduce movements in response to increased human landscape modification, but reptile movements have not been as extensively studied.

          Methods

          We examined movements of a large reptilian predator, the King Cobra ( Ophiophagus hannah), in Northeast Thailand. We used a consistent regime of radio telemetry tracking to document movements across protected forest and adjacent agricultural areas. Using dynamic Brownian Bridge Movement Model derived motion variance, Integrated Step-Selection Functions, and metrics of site reuse, we examined how King Cobra movements changed in agricultural areas.

          Results

          Motion variance values indicated that King Cobra movements increased in forested areas and tended to decrease in agricultural areas. Our Integrated Step-Selection Functions revealed that when moving in agricultural areas King Cobras restricted their movements to remain within vegetated semi-natural areas, often located along the banks of irrigation canals. Site reuse metrics of residency time and number of revisits appeared unaffected by distance to landscape features (forests, semi-natural areas, settlements, water bodies, and roads). Neither motion variance nor reuse metrics were consistently affected by the presence of threatening landscape features (e.g. roads, human settlements), suggesting that King Cobras will remain in close proximity to threats, provided habitat patches are available.

          Conclusions

          Although King Cobras displayed individual heterogeneity in their response to agricultural landscapes, the overall trend suggested reduced movements when faced with fragmented habitat patches embedded in an otherwise inhospitable land-use matrix. Movement reductions are consistent with findings for mammals and forest specialist species.

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          Most cited references73

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          Multiple causes of high extinction risk in large mammal species.

          Many large animal species have a high risk of extinction. This is usually thought to result simply from the way that species traits associated with vulnerability, such as low reproductive rates, scale with body size. In a broad-scale analysis of extinction risk in mammals, we find two additional patterns in the size selectivity of extinction risk. First, impacts of both intrinsic and environmental factors increase sharply above a threshold body mass around 3 kilograms. Second, whereas extinction risk in smaller species is driven by environmental factors, in larger species it is driven by a combination of environmental factors and intrinsic traits. Thus, the disadvantages of large size are greater than generally recognized, and future loss of large mammal biodiversity could be far more rapid than expected.
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            Analyzing animal movements using Brownian bridges.

            By studying animal movements, researchers can gain insight into many of the ecological characteristics and processes important for understanding population-level dynamics. We developed a Brownian bridge movement model (BBMM) for estimating the expected movement path of an animal, using discrete location data obtained at relatively short time intervals. The BBMM is based on the properties of a conditional random walk between successive pairs of locations, dependent on the time between locations, the distance between locations, and the Brownian motion variance that is related to the animal's mobility. We describe two critical developments that enable widespread use of the BBMM, including a derivation of the model when location data are measured with error and a maximum likelihood approach for estimating the Brownian motion variance. After the BBMM is fitted to location data, an estimate of the animal's probability of occurrence can be generated for an area during the time of observation. To illustrate potential applications, we provide three examples: estimating animal home ranges, estimating animal migration routes, and evaluating the influence of fine-scale resource selection on animal movement patterns.
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              Eliminating autocorrelation reduces biological relevance of home range estimates

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                Author and article information

                Contributors
                benjaminmichaelmarshall@gmail.com
                strine.conservation@gmail.com
                Journal
                Mov Ecol
                Mov Ecol
                Movement Ecology
                BioMed Central (London )
                2051-3933
                3 August 2020
                3 August 2020
                2020
                : 8
                : 33
                Affiliations
                [1 ]GRID grid.6357.7, ISNI 0000 0001 0739 3220, Suranaree University of Technology, ; Nakhon Ratchasima, Thailand
                [2 ]GRID grid.412151.2, ISNI 0000 0000 8921 9789, King Mongkut’s University of Technology Thonburi, ; Bangkok, Thailand
                [3 ]Population and Community Development Association, Bangkok, Thailand
                [4 ]Sakaerat Environmental Research Station, Nakhon Ratchasima, Thailand
                [5 ]GRID grid.134563.6, ISNI 0000 0001 2168 186X, School of Natural Resources and Environment, , University of Arizona, ; Tucson, AZ USA
                Author information
                http://orcid.org/0000-0001-5614-292X
                Article
                219
                10.1186/s40462-020-00219-5
                7397683
                31921423
                16b02a8e-c730-4e1a-92aa-a10ec5725021
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 10 April 2020
                : 7 July 2020
                Funding
                Funded by: National Science and Technological Development Agency, Thailand
                Funded by: FundRef http://dx.doi.org/10.13039/501100009082, Wildlife Reserves Singapore Conservation Fund;
                Funded by: Herpetofauna Foundation
                Funded by: FundRef http://dx.doi.org/10.13039/501100004352, Suranaree University of Technology;
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                snake,reptile,ophiophagus hannah,elapid,space-use,step-selection,dbbmm,site fidelity,tropical

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