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{"title"=>"Modeling the Potential Spread of the Recently Identified Non-Native Panther Grouper (Chromileptes altivelis) in the Atlantic Using a Cellular Automaton Approach", "type"=>"journal", "authors"=>[{"first_name"=>"Matthew W.", "last_name"=>"Johnston", "scopus_author_id"=>"37101629200"}, {"first_name"=>"Sam J.", "last_name"=>"Purkis", "scopus_author_id"=>"6507258668"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "isbn"=>"1932-6203", "pmid"=>"24009726", "scopus"=>"2-s2.0-84883247789", "doi"=>"10.1371/journal.pone.0073023", "sgr"=>"84883247789", "pui"=>"369700116"}, "id"=>"f4ffc52f-8102-3379-ad59-112228276fb9", "abstract"=>"The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species.", "link"=>"http://www.mendeley.com/research/modeling-potential-spread-recently-identified-nonnative-panther-grouper-chromileptes-altivelis-atlan", "reader_count"=>25, "reader_count_by_academic_status"=>{"Unspecified"=>1, "Librarian"=>1, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>7, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>1, "Librarian"=>1, "Researcher"=>7, "Student > Doctoral Student"=>2, "Student > Ph. D. Student"=>3, "Student > Master"=>7, "Student > Bachelor"=>2, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>1, "Environmental Science"=>7, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>15, "Decision Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Decision Sciences"=>{"Decision Sciences"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>15}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>1}, "Environmental Science"=>{"Environmental Science"=>7}}, "reader_count_by_country"=>{"United States"=>1}, "group_count"=>2}

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• http://doi.org/10.1007/s00227-014-2595-3
• http://doi.org/10.1111/maec.12249
• http://doi.org/10.1111/gcb.12874
• http://doi.org/10.1007/s00227-015-2777-7
• http://doi.org/10.1002/dneu.22686
• http://doi.org/10.1007/s00442-015-3368-5
• http://doi.org/10.1016/j.marpolbul.2014.09.013

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/1185076"], "description"=>"<p>Process flow of the enhanced ISM.</p>", "links"=>[], "tags"=>["Computational biology", "Ecosystem modeling", "Population modeling", "Marine biology", "Marine ecology", "Marine technology", "algorithms", "Computer modeling", "Computerized simulations", "Computing methods", "Computer animation", "geoinformatics", "Environmental systems modeling", "Geocomputation", "Remote sensing imagery", "software engineering", "Software design", "enhanced"], "article_id"=>784320, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Matthew W. Johnston", "Sam J. Purkis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0073023.g002", "stats"=>{"downloads"=>4, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Process_flow_of_the_enhanced_ISM_/784320", "title"=>"Process flow of the enhanced ISM.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-29 06:45:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1185074"], "description"=>"<p>Records from the USGS NAS indicating locations of panther grouper captures or sightings.</p>", "links"=>[], "tags"=>["Computational biology", "Ecosystem modeling", "Population modeling", "Marine biology", "Marine ecology", "Marine technology", "algorithms", "Computer modeling", "Computerized simulations", "Computing methods", "Computer animation", "geoinformatics", "Environmental systems modeling", "Geocomputation", "Remote sensing imagery", "software engineering", "Software design", "grouper"], "article_id"=>784318, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Matthew W. Johnston", "Sam J. Purkis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0073023.g001", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Panther_grouper_records_/784318", "title"=>"Panther grouper records.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-29 06:45:50"}
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• {"files"=>["https://ndownloader.figshare.com/files/1185082"], "description"=>"<p>Settlement rates of adult breeding populations for panther grouper on a ‘hot’ (red) to ‘cold’ (blue) scale using Jenks' natural breaks as class divisions. CS_FK with a larval mortality rate of 0.22 d ⁻¹ (A), 0.18 d ⁻¹ (B). CS_BC with a larval mortality rate of 0.22 d ⁻¹ (C), 0.18 d ⁻¹ (D).</p>", "links"=>[], "tags"=>["Computational biology", "Ecosystem modeling", "Population modeling", "Marine biology", "Marine ecology", "Marine technology", "algorithms", "Computer modeling", "Computerized simulations", "Computing methods", "Computer animation", "geoinformatics", "Environmental systems modeling", "Geocomputation", "Remote sensing imagery", "software engineering", "Software design", "larval"], "article_id"=>784326, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Matthew W. Johnston", "Sam J. Purkis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0073023.g006", "stats"=>{"downloads"=>6, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Sensitivity_Analysis_to_Larval_Mortality_/784326", "title"=>"Sensitivity Analysis to Larval Mortality.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-29 06:45:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1185079"], "description"=>"<p>Settlement rates of adult breeding populations for panther grouper on a ‘hot’ (red) to ‘cold’ (blue) scale using Jenks' natural breaks as class divisions (a method that reduces inter-class variance and maximizes variance between distinct classes) for CS_FK (A), CS_BC (B) and composite study (C) simulations for a duration of 78 months. Focus areas for early detection are indicated for the Jupiter Florida/Vero Beach (red), Cape Hatteras Tropical Limit/Myrtle Beach (orange), and Florida Keys/Ten Thousand Islands (green) locations.</p>", "links"=>[], "tags"=>["Computational biology", "Ecosystem modeling", "Population modeling", "Marine biology", "Marine ecology", "Marine technology", "algorithms", "Computer modeling", "Computerized simulations", "Computing methods", "Computer animation", "geoinformatics", "Environmental systems modeling", "Geocomputation", "Remote sensing imagery", "software engineering", "Software design"], "article_id"=>784323, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Matthew W. Johnston", "Sam J. Purkis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0073023.g003", "stats"=>{"downloads"=>2, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Settlement_and_focus_area_maps_/784323", "title"=>"Settlement and focus area maps.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-29 06:45:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1185081"], "description"=>"<p>SRCC calculation with a ρ = 0.80 for CS_BC when comparing 20 individual model runs (y-axis) to the RM (A), and ρ = 0.49 when comparing the RM (y-axis) to H_o (B). SRCC with a ρ = 0.67 for CS_FK when comparing 20 individual model runs (y-axis) to the RM (C), and ρ = 0.49 when comparing the RM (y-axis) to H_o (D). X-axis indicates the sequential order of establishment for the RM, and the y-axis indicates the order of establishment for each comparative simulation. Perfect correlation (SRCC of 1.0) is indicated by a point lying precisely on the diagonal from bottom-left to top-right.</p>", "links"=>[], "tags"=>["Computational biology", "Ecosystem modeling", "Population modeling", "Marine biology", "Marine ecology", "Marine technology", "algorithms", "Computer modeling", "Computerized simulations", "Computing methods", "Computer animation", "geoinformatics", "Environmental systems modeling", "Geocomputation", "Remote sensing imagery", "software engineering", "Software design", "coefficient"], "article_id"=>784325, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Matthew W. Johnston", "Sam J. Purkis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0073023.g005", "stats"=>{"downloads"=>0, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Spearman_s_Rank_Correlation_Coefficient_SRCC_calculations_/784325", "title"=>"Spearman's Rank Correlation Coefficient (SRCC) calculations.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-29 06:45:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1185080"], "description"=>"<p>Map indicating the sequence and relative month [sequence(month)] for the first 10 steps for a Broward County origin (A) and a 12 steps for a Florida Keys origin (B).</p>", "links"=>[], "tags"=>["Computational biology", "Ecosystem modeling", "Population modeling", "Marine biology", "Marine ecology", "Marine technology", "algorithms", "Computer modeling", "Computerized simulations", "Computing methods", "Computer animation", "geoinformatics", "Environmental systems modeling", "Geocomputation", "Remote sensing imagery", "software engineering", "Software design", "progression"], "article_id"=>784324, "categories"=>["Information And Computing Sciences", "Biological Sciences"], "users"=>["Matthew W. Johnston", "Sam J. Purkis"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0073023.g004", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Temporal_spatial_progression_map_/784324", "title"=>"Temporal-spatial progression map.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-08-29 06:45:50"}

PMC Usage Stats | Further Information

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• {"unique-ip"=>"10", "full-text"=>"12", "pdf"=>"4", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"2", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"10"}
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• {"unique-ip"=>"4", "full-text"=>"4", "pdf"=>"0", "abstract"=>"0", "scanned-summary"=>"0", "scanned-page-browse"=>"0", "figure"=>"0", "supp-data"=>"0", "cited-by"=>"0", "year"=>"2016", "month"=>"12"}
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Relative Metric

{"start_date"=>"2013-01-01T00:00:00Z", "end_date"=>"2013-12-31T00:00:00Z", "subject_areas"=>[{"subject_area"=>"/Biology and life sciences", "average_usage"=>[269, 466, 588, 697, 800, 896, 988, 1076, 1165, 1254, 1340, 1417]}, {"subject_area"=>"/Biology and life sciences/Organisms", "average_usage"=>[281, 484, 611, 728, 835, 934, 1030, 1123, 1214, 1299, 1383, 1464]}, {"subject_area"=>"/Earth sciences", "average_usage"=>[296, 488, 620, 717, 828, 938, 1038, 1130, 1230, 1328, 1414, 1502, 1592]}, {"subject_area"=>"/Earth sciences/Geomorphology", "average_usage"=>[317, 502, 627, 717, 810, 905, 982, 1057, 1140, 1227, 1336, 1413, 1464]}, {"subject_area"=>"/Ecology and environmental sciences", "average_usage"=>[284, 475, 603, 722, 826, 928, 1026, 1129, 1225, 1310, 1390, 1468, 1549]}, {"subject_area"=>"/Ecology and environmental sciences/Invasive species", "average_usage"=>[275]}, {"subject_area"=>"/People and places/Demography", "average_usage"=>[253, 440, 552, 650, 735, 820, 902, 976, 1042, 1112, 1192, 1271, 1337]}, {"subject_area"=>"/Physical sciences", "average_usage"=>[254, 431, 547, 651, 748, 842, 932, 1017, 1098, 1178, 1259, 1336, 1404]}, {"subject_area"=>"/Physical sciences/Mathematics", "average_usage"=>[259, 431, 541, 639, 727, 816, 898, 980, 1061, 1136, 1214, 1294, 1356]}]}

F1000Prime