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{"title"=>"Adaptive Lévy Processes and Area-Restricted Search in Human Foraging", "type"=>"journal", "authors"=>[{"first_name"=>"Thomas T.", "last_name"=>"Hills", "scopus_author_id"=>"6701562138"}, {"first_name"=>"Christopher", "last_name"=>"Kalff", "scopus_author_id"=>"33567846900"}, {"first_name"=>"Jan M.", "last_name"=>"Wiener", "scopus_author_id"=>"8886011800"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"arxiv"=>"1203.2655", "sgr"=>"84875964928", "pmid"=>"1000090690", "isbn"=>"0011-3891", "pui"=>"368686563", "issn"=>"19326203", "scopus"=>"2-s2.0-84875964928", "doi"=>"10.1371/journal.pone.0060488"}, "id"=>"91d295d6-708b-3170-86b3-0a793adfc846", "abstract"=>"A considerable amount of research has claimed that animals' foraging behaviors display movement lengths with power-law distributed tails, characteristic of Lévy flights and Lévy walks. Though these claims have recently come into question, the proposal that many animals forage using Lévy processes nonetheless remains. A Lévy process does not consider when or where resources are encountered, and samples movement lengths independently of past experience. However, Lévy processes too have come into question based on the observation that in patchy resource environments resource-sensitive foraging strategies, like area-restricted search, perform better than Lévy flights yet can still generate heavy-tailed distributions of movement lengths. To investigate these questions further, we tracked humans as they searched for hidden resources in an open-field virtual environment, with either patchy or dispersed resource distributions. Supporting previous research, for both conditions logarithmic binning methods were consistent with Lévy flights and rank-frequency methods-comparing alternative distributions using maximum likelihood methods-showed the strongest support for bounded power-law distributions (truncated Lévy flights). However, goodness-of-fit tests found that even bounded power-law distributions only accurately characterized movement behavior for 4 (out of 32) participants. Moreover, paths in the patchy environment (but not the dispersed environment) showed a transition to intensive search following resource encounters, characteristic of area-restricted search. Transferring paths between environments revealed that paths generated in the patchy environment were adapted to that environment. Our results suggest that though power-law distributions do not accurately reflect human search, Lévy processes may still describe movement in dispersed environments, but not in patchy environments-where search was area-restricted. Furthermore, our results indicate that search strategies cannot be inferred without knowing how organisms respond to resources-as both patched and dispersed conditions led to similar Lévy-like movement distributions.", "link"=>"http://www.mendeley.com/research/adaptive-l%C3%A9vy-processes-arearestricted-search-human-foraging", "reader_count"=>23, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>4, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>7, "Student > Master"=>3, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Professor > Associate Professor"=>1, "Librarian"=>1, "Researcher"=>4, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>7, "Student > Master"=>3, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>2, "Environmental Science"=>1, "Mathematics"=>1, "Agricultural and Biological Sciences"=>9, "Neuroscience"=>1, "Design"=>1, "Arts and Humanities"=>1, "Psychology"=>6, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Design"=>{"Design"=>1}, "Neuroscience"=>{"Neuroscience"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Psychology"=>{"Psychology"=>6}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>9}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>2}, "Environmental Science"=>{"Environmental Science"=>1}, "Arts and Humanities"=>{"Arts and Humanities"=>1}}, "reader_count_by_country"=>{"Japan"=>1, "South Africa"=>1, "Germany"=>1}, "group_count"=>0}

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• {"id"=>"320551076896071681", "text"=>"Our paper on human foraging behaviour is our: http://t.co/1Qg9S0IWP2", "created_at"=>"2013-04-06T14:58:26Z", "user"=>"Jan_Wiener", "user_name"=>"Jan Wiener", "user_profile_image"=>"http://a0.twimg.com/profile_images/3276905416/29be7234d6e072df5dc2c0f1d2fd59c3_normal.png"}
• {"id"=>"320555837082968066", "text"=>"Our paper on foraging strategies in humans is out: http://t.co/1Qg9S0IWP2", "created_at"=>"2013-04-06T15:17:21Z", "user"=>"Jan_Wiener", "user_name"=>"Jan Wiener", "user_profile_image"=>"http://a0.twimg.com/profile_images/3276905416/29be7234d6e072df5dc2c0f1d2fd59c3_normal.png"}
• {"id"=>"320557274928132097", "text"=>"Great analysis: “@Jan_Wiener: Our paper on foraging strategies in humans is out: http://t.co/pvGo9p93YY”", "created_at"=>"2013-04-06T15:23:04Z", "user"=>"hugospiers", "user_name"=>"Hugo Spiers", "user_profile_image"=>"http://a0.twimg.com/profile_images/1776546713/hugo2_normal.jpg"}
• {"id"=>"320562643381415936", "text"=>"#mustread \"@Jan_Wiener: Our paper on foraging strategies in humans is out: http://t.co/s7p2d2aEjz\"", "created_at"=>"2013-04-06T15:44:24Z", "user"=>"ant_newman", "user_name"=>"Ant Newman", "user_profile_image"=>"http://a0.twimg.com/profile_images/2728950980/637c8ad7f23cfeb6dd8eafad990c779b_normal.jpeg"}
• {"id"=>"320629442999353345", "text"=>"RT @hugospiers: Great analysis: “@Jan_Wiener: Our paper on foraging strategies in humans is out: http://t.co/pvGo9p93YY”", "created_at"=>"2013-04-06T20:09:50Z", "user"=>"LectorixEduca", "user_name"=>"Lectorix", "user_profile_image"=>"http://a0.twimg.com/profile_images/1668087444/LOGO_Lectorix_normal.png"}

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/1017551"], "description"=>"<p>Note: PL = power law, Exp = unbounded exponential, PLB = bounded power-law, ExpB = bounded exponential.</p>", "links"=>[], "tags"=>["comparisons"], "article_id"=>676999, "categories"=>["Physics", "Mathematics", "Neuroscience", "Mental Health", "Evolutionary Biology"], "users"=>["Thomas T. Hills", "Christopher Kalff", "Jan M. Wiener"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0060488.t002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_comparisons_for_individual_data_/676999", "title"=>"Model comparisons for individual data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-04-05 01:56:39"}
• {"files"=>["https://ndownloader.figshare.com/files/1017552"], "description"=>"<p>Note: PL = power law, Exp = unbounded exponential, PLB = bounded power-law, ExpB = bounded exponential.</p>", "links"=>[], "tags"=>["comparisons", "aggregated"], "article_id"=>677000, "categories"=>["Physics", "Mathematics", "Neuroscience", "Mental Health", "Evolutionary Biology"], "users"=>["Thomas T. Hills", "Christopher Kalff", "Jan M. Wiener"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0060488.t001", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_comparisons_for_aggregated_data_/677000", "title"=>"Model comparisons for aggregated data.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-04-05 01:56:40"}
• {"files"=>["https://ndownloader.figshare.com/files/1017550"], "description"=>"<p>We compared path performance by randomly simulating paths from the alternative environment using 100 simulated versions of each observed path in the alternative resource distribution. Paths from the patched condition simulated in the dispersed environment performed as well as dispersed paths in the dispersed environment (<i>t</i>(15) = 0.05, <i>P</i> = .97, two-tailed t-test). However, paths from the dispersed environment simulated in the patchy environment were outperformed by the original paths from the patchy environment (<i>t</i>(14) = −3.91, <i>P = </i>.002, two-tailed t-test).</p>", "links"=>[], "tags"=>["Mental health", "neuroscience", "Evolutionary biology", "physics", "mathematics"], "article_id"=>676998, "categories"=>["Physics", "Mathematics", "Neuroscience", "Mental Health", "Evolutionary Biology"], "users"=>["Thomas T. Hills", "Christopher Kalff", "Jan M. Wiener"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0060488.g004", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Comparing_path_performance_across_environments_/676998", "title"=>"Comparing path performance across environments.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-05 01:56:38"}
• {"files"=>["https://ndownloader.figshare.com/files/1017547"], "description"=>"<p>Black circles are movement lengths ≥ <i>x</i>. The four model fits are power-law (blue-straight line), bounded power-law (curved blue-dashed line), unbounded exponential (curved red line), and bounded exponential (curved red-dashed line). <b>A.</b> The aggregated data for the dispersed condition. The inset shows the results of logarithmic binning with best fitting power-law. <b>B.</b> The aggregated data for the patched condition. The inset shows the results of logarithmic binning with best fitting power-law. <b>C.</b> Data for each individual in the dispersed condition. <b>D.</b> Data for each individual in the patched condition.</p>", "links"=>[], "tags"=>["aggregated", "fits", "logarithmic"], "article_id"=>676995, "categories"=>["Physics", "Mathematics", "Neuroscience", "Mental Health", "Evolutionary Biology"], "users"=>["Thomas T. Hills", "Christopher Kalff", "Jan M. Wiener"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0060488.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Rank_frequency_plots_of_aggregated_and_individual_data_along_with_model_fits_on_logarithmic_axes_/676995", "title"=>"Rank/frequency plots of aggregated and individual data along with model fits on logarithmic axes.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-05 01:56:35"}
• {"files"=>["https://ndownloader.figshare.com/files/1017546"], "description"=>"<p><b>A.</b> Participants’ perspective during the task. One of the global landmarks (a mountain) is visible in the distance. The number in the lower left hand corner is the number of resources collected so far. <b>B.</b> The resource distribution in the dispersed environment with a path generated by one participant. <b>C.</b> The resource distribution in the patchy environment with a path generated by one participant.</p>", "links"=>[], "tags"=>["foraging"], "article_id"=>676994, "categories"=>["Physics", "Mathematics", "Neuroscience", "Mental Health", "Evolutionary Biology"], "users"=>["Thomas T. Hills", "Christopher Kalff", "Jan M. Wiener"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0060488.g001", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_virtual_foraging_environment_resource_distributions_and_representative_paths_/676994", "title"=>"The virtual foraging environment, resource distributions, and representative paths.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-05 01:56:34"}
• {"files"=>["https://ndownloader.figshare.com/files/1017549"], "description"=>"<p>Participants in the patched condition significantly increased turning in response to resource encounters relative to both the dispersed condition (<i>F(1,30) = </i>5.31, <i>P = </i>.03, repeated measures analysis of variance) and ‘random’ baseline turning (<i>F(1,15) = </i>5.71, <i>P</i> = .03, repeated measures analysis of variance). Turning angles in the dispersed condition were not different from the ‘random’ baseline turning (<i>F(1,15) = </i>1.68, <i>P = </i>.21, repeated measures analysis of variance). Data show mean±sem.</p>", "links"=>[], "tags"=>["empirical", "locations", "trajectories"], "article_id"=>676997, "categories"=>["Physics", "Mathematics", "Neuroscience", "Mental Health", "Evolutionary Biology"], "users"=>["Thomas T. Hills", "Christopher Kalff", "Jan M. Wiener"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0060488.g003", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Turning_angle_as_a_function_of_distance_after_item_encounter_for_the_empirical_data_8220_Experiment_dispersed_8221_and_8220_Experiment_patched_8221_and_for_random_locations_along_the_trajectories_8220_Random_dispersed_8221_and_8220_Random_patched_8221_/676997", "title"=>"Turning angle as a function of distance after item encounter for the empirical data (“Experiment dispersed” and “Experiment patched”) and for random locations along the trajectories (“Random dispersed” and “Random patched”).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-04-05 01:56:37"}

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Relative Metric

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F1000Prime