Dynamic Approach to Space and Habitat Use Based on Biased Random Bridges
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{"title"=>"Dynamic approach to space and habitat use based on biased random bridges", "type"=>"journal", "authors"=>[{"first_name"=>"Simon", "last_name"=>"Benhamou", "scopus_author_id"=>"24400948100"}], "year"=>2011, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"361174328", "sgr"=>"79251492717", "issn"=>"19326203", "pmid"=>"21297869", "scopus"=>"2-s2.0-79251492717", "doi"=>"10.1371/journal.pone.0014592", "isbn"=>"1932-6203"}, "id"=>"cb4a7218-0d74-300e-b191-687b7fc027b9", "abstract"=>"Although habitat use reflects a dynamic process, most studies assess habitat use statically as if an animal's successively recorded locations reflected a point rather than a movement process. By relying on the activity time between successive locations instead of the local density of individual locations, movement-based methods can substantially improve the biological relevance of utilization distribution (UD) estimates (i.e. the relative frequencies with which an animal uses the various areas of its home range, HR). One such method rests on Brownian bridges (BBs). Its theoretical foundation (purely and constantly diffusive movements) is paradoxically inconsistent with both HR settlement and habitat selection. An alternative involves movement-based kernel density estimation (MKDE) through location interpolation, which may be applied to various movement behaviours but lacks a sound theoretical basis.", "link"=>"http://www.mendeley.com/research/dynamic-approach-space-habitat-based-biased-random-bridges", "reader_count"=>317, "reader_count_by_academic_status"=>{"Unspecified"=>11, "Professor > Associate Professor"=>9, "Researcher"=>83, "Student > Doctoral Student"=>14, "Student > Ph. D. Student"=>85, "Student > Postgraduate"=>14, "Student > Master"=>70, "Other"=>10, "Student > Bachelor"=>12, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>4}, "reader_count_by_user_role"=>{"Unspecified"=>11, "Professor > Associate Professor"=>9, "Researcher"=>83, "Student > Doctoral Student"=>14, "Student > Ph. D. Student"=>85, "Student > Postgraduate"=>14, "Student > Master"=>70, "Other"=>10, "Student > Bachelor"=>12, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>4}, "reader_count_by_subject_area"=>{"Unspecified"=>17, "Agricultural and Biological Sciences"=>194, "Veterinary Science and Veterinary Medicine"=>2, "Chemistry"=>1, "Computer Science"=>6, "Earth and Planetary Sciences"=>9, "Engineering"=>3, "Environmental Science"=>71, "Biochemistry, Genetics and Molecular Biology"=>1, "Materials Science"=>1, "Mathematics"=>3, "Medicine and Dentistry"=>1, "Design"=>1, "Physics and Astronomy"=>3, "Psychology"=>1, "Social Sciences"=>3}, "reader_count_by_subdiscipline"=>{"Materials Science"=>{"Materials Science"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>3}, "Physics and Astronomy"=>{"Physics and Astronomy"=>3}, "Psychology"=>{"Psychology"=>1}, "Mathematics"=>{"Mathematics"=>3}, "Unspecified"=>{"Unspecified"=>17}, "Environmental Science"=>{"Environmental Science"=>71}, "Design"=>{"Design"=>1}, "Engineering"=>{"Engineering"=>3}, "Chemistry"=>{"Chemistry"=>1}, "Earth and Planetary Sciences"=>{"Earth and Planetary Sciences"=>9}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>194}, "Computer Science"=>{"Computer Science"=>6}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Veterinary Science and Veterinary Medicine"=>{"Veterinary Science and Veterinary Medicine"=>2}}, "reader_count_by_country"=>{"United States"=>3, "United Kingdom"=>5, "Portugal"=>4, "Switzerland"=>1, "Spain"=>5, "Canada"=>2, "Austria"=>1, "Czech Republic"=>1, "Finland"=>1, "Brazil"=>3, "South Africa"=>3, "Mexico"=>2, "France"=>8, "Chile"=>1, "Germany"=>5}, "group_count"=>16}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/803106"], "description"=>"<p>Most habitat-specific diffusion coefficients (expressed in m<sup>2</sup>/min) were computed from too few couples of consecutive track segments (sample sizes between parentheses) to be reliable. Both habitat availability (non-weighted proportion of each habitat type) and use (UD-weighted proportion of each habitat type) were computed on the areas encompassed within 95% isopleths (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0014592#pone-0014592-g001\" target=\"_blank\">Fig. 1</a>). Normalised preferences correspond to habitat use/availability ratios subject to unit-sum constraint. Drift speeds values (expressed in m/min) should be considered with extreme caution when computed from only a few track segments.</p>", "links"=>[], "tags"=>["diffusion", "preferences"], "article_id"=>473483, "categories"=>["Infectious Diseases", "Ecology"], "users"=>["Simon Benhamou"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0014592.t001", "stats"=>{"downloads"=>5, "page_views"=>2, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Habitat_specific_diffusion_coefficients_preferences_and_drift_speeds_/473483", "title"=>"Habitat-specific diffusion coefficients, preferences and drift speeds.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 20:59:50"}
  • {"files"=>["https://ndownloader.figshare.com/files/802978"], "description"=>"<p>The top panel shows how the period considered (early wet season, indicated by the white background) was delineated by marked and durable changes in mean or variance of longitude or latitude (computed over a few days in a sliding window). The bottom left panel shows the herd movement (big dots represent GPS relocations recorded at 30-min intervals and tiny dots locations interpolated along track segments at 1-min activity intervals) and the different habitat types available within 95% UD cumulative frequency isopleths (R: Rocky grounds, G: Forest galleries, P: Perennial grasses, A: Annual grasses). The bottom right panel shows the GPS relocations (black dots) and UD cumulative frequencies up to 95% (the colour attributed to a given percentage <i>p</i> applies to areas comprised between <i>p</i> and <i>p</i>–5% isopleths).</p>", "links"=>[], "tags"=>["african", "buffalo", "herd", "4-week", "stationary", "computed", "simplified", "brbs", "mkde"], "article_id"=>473340, "categories"=>["Infectious Diseases", "Ecology"], "users"=>["Simon Benhamou"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0014592.g001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Utilization_Distribution_UD_of_an_African_buffalo_herd_for_a_4_week_stationary_period_computed_using_simplified_BRBs_min__100_m_D_440_m_2_min_and_T_max_30_min_through_the_MKDE_method_h_min__min_and_h_max__2_min_DT_max_2_0_5_/473340", "title"=>"Utilization Distribution (UD) of an African buffalo herd for a 4-week stationary period computed using simplified BRBs (σ<i><sub>min</sub></i> = 100 m, <i>D</i> = 440 m<sup>2</sup>/min and <i>T<sub>max</sub></i>>30 min) through the MKDE method (<i>h<sub>min</sub></i> = σ<i><sub>min</sub></i> and <i>h<sub>max</sub></i> = (σ<sup>2</sup><i><sub>min</sub></i>+<i>DT<sub>max</sub></i>/2)<sup>0.5</sup>).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 20:59:00"}

PMC Usage Stats | Further Information

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Relative Metric

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