Niche Overlap of Congeneric Invaders Supports a Single-Species Hypothesis and Provides Insight into Future Invasion Risk: Implications for Global Management of the Bactrocera dorsalis Complex
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{"title"=>"Niche overlap of congeneric invaders supports a single-species hypothesis and provides insight into future invasion risk: Implications for global management of the Bactrocera dorsalis complex", "type"=>"journal", "authors"=>[{"first_name"=>"Matthew P.", "last_name"=>"Hill", "scopus_author_id"=>"37018159800"}, {"first_name"=>"John S.", "last_name"=>"Terblanche", "scopus_author_id"=>"7101911429"}], "year"=>2014, "source"=>"PLoS ONE", "identifiers"=>{"scopus"=>"2-s2.0-84896349713", "pui"=>"372630001", "pmid"=>"24587234", "issn"=>"19326203", "isbn"=>"1932-6203", "doi"=>"10.1371/journal.pone.0090121", "sgr"=>"84896349713"}, "id"=>"1b4c8749-7222-3099-b0bc-9422775dcf66", "abstract"=>"BACKGROUND The invasive fruit fly, Bactrocera invadens, has expanded its range rapidly over the past 10 years. Here we aimed to determine if the recent range expansion of Bactrocera invadens into southern Africa can be better understood through niche exploration tools, ecological niche models (ENMs), and through incorporating information about Bactrocera dorsalis s.s., a putative conspecific species from Asia. We test for niche overlap of environmental variables between Bactrocera invadens and Bactrocera dorsalis s.s. as well as two other putative conspecific species, Bactrocera philippinensis and B. papayae. We examine overlap and similarity in the geographical expression of each species' realised niche through reciprocal distribution models between Africa and Asia. We explore different geographical backgrounds, environmental variables and model complexity with multiple and single Bactrocera species hypotheses in an attempt to predict the recent range expansion of B. invadens into northern parts of South Africa. PRINCIPAL FINDINGS Bactrocera invadens has a high degree of niche overlap with B. dorsalis s.s. (and B. philippinensis and B. papayae). Ecological niche models built for Bactrocera dorsalis s.s. have high transferability to describe the range of B. invadens, and B. invadens is able to project to the core range of B. dorsalis s.s. The ENMs of both Bactrocera dorsalis and B. dorsalis combined with B. philipenesis and B. papayae have significantly higher predictive ability to capture the distribution points in South Africa than for B. invadens alone. CONCLUSIONS/SIGNIFICANCE Consistent with other studies proposing these Bactrocera species as conspecific, niche similarity and overlap between these species is high. Considering these other Bactrocera dorsalis complex species simultaneously better describes the range expansion and invasion potential of B. invadens in South Africa. We suggest that these species should be considered the same-at least functionally-and global quarantine and management strategies applied equally to these Bactrocera species.", "link"=>"http://www.mendeley.com/research/niche-overlap-congeneric-invaders-supports-singlespecies-hypothesis-provides-insight-future-invasion", "reader_count"=>65, "reader_count_by_academic_status"=>{"Unspecified"=>3, "Professor > Associate Professor"=>4, "Researcher"=>16, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>17, "Student > Postgraduate"=>2, "Student > Master"=>9, "Other"=>3, "Student > Bachelor"=>1, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>3, "Professor > Associate Professor"=>4, "Researcher"=>16, "Student > Doctoral Student"=>4, "Student > Ph. D. Student"=>17, "Student > Postgraduate"=>2, "Student > Master"=>9, "Other"=>3, "Student > Bachelor"=>1, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Environmental Science"=>14, "Biochemistry, Genetics and Molecular Biology"=>1, "Agricultural and Biological Sciences"=>40, "Medicine and Dentistry"=>1, "Physics and Astronomy"=>1, "Social Sciences"=>1, "Economics, Econometrics and Finance"=>1}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>1}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>40}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>1}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>14}}, "reader_count_by_country"=>{"Poland"=>1, "Brazil"=>3, "Chile"=>1, "France"=>1, "Spain"=>1}, "group_count"=>3}

Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/1400719"], "description"=>"<p>DPP = <i>B. dorsalis</i> + <i>B. philippinensis</i> + <i>B. papayae</i>, All = <i>B. dorsalis</i> + <i>B. invadens</i> + <i>B. papaya</i> + <i>B. philippinensis</i> AICc = sample size corrected Akaike information criteria across 10 replicates, bold values represent significantly lowest AICc score (<i>p</i><0.05); AUC<sub>TEST</sub> = area under the receiver operating characteristic curve; mean across 10 cross-validated replicates. <i>β</i> = regularization parameter.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "niche"], "article_id"=>946453, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.t003", "stats"=>{"downloads"=>2, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Ecological_Niche_Model_ENM_performance_for_different_Bactrocera_dorsalis_complex_datasets_/946453", "title"=>"Ecological Niche Model (ENM) performance for different <i>Bactrocera dorsalis</i> complex datasets.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400718"], "description"=>"<p>The ENFA derived parameters are determined separately for each of the species boundary hypotheses and for all four species combined. The scores calculated across the Köppen-Geiger background are on the left and the GEnS scores on the right. The total marginality score will increase above 1 when considering all predictor variable marginality scores. Bio02 =  Mean diurnal temperature range (mean(period max-min)) (°C); Bio03 =  Isothermality (Bio02 ÷ Bio07); Bio04 =  Temperature seasonality (C of V); Bio06 =  Min temperature of coldest week (°C); Bio07 =  Temperature annual range (Max temperature of warmest week - Bio06) (°C); Bio11 =  Mean temperature of coldest quarter (°C); Bio12 =  Annual precipitation (mm); Bio14 =  Precipitation of driest week (mm); Bio17 =  Precipitation of driest quarter (mm); Bio18 =  Precipitation of warmest quarter (mm); Bio21 =  Highest weekly radiation (W m<sup>−2</sup>); Bio26 =  Radiation of warmest quarter (W m<sup>−2</sup>); Bio27 =  Radiation of coldest quarter (W m<sup>−2</sup>); Bio28 =  Annual mean moisture index; Bio29 =  Highest weekly moisture index; Bio30 =  Lowest weekly moisture index; Bio32 =  Mean moisture index of wettest quarter; Bio33 =  Mean moisture index of driest quarter; Bio34 =  Mean moisture index of warmest quarter; Bio35 =  Mean moisture index of coldest quarter.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "enfa", "predictor"], "article_id"=>946452, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.t001", "stats"=>{"downloads"=>2, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Variables_selected_for_ENFA_predictor_sets_/946452", "title"=>"Variables selected for ENFA predictor sets.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400715"], "description"=>"<p>Ecological Niche Models shown here were constructed on ENFA-derived predictor sets as they had higher AUC<sub>TEST</sub> and <i>D</i> scores than did those built on expert-driven predictor sets (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090121#pone-0090121-t002\" target=\"_blank\">Table 2</a>). Shading indicates suitability and solid grey areas are those that fall outside Asia and Africa. a) RDM trained on <i>B. dorsalis</i> + <i>B. papayae</i> + <i>B. philippinensis</i> distribution projected to the background of <i>B. invadens</i>, Model H (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090121#pone-0090121-t002\" target=\"_blank\">Table 2</a>). b) RDM trained on <i>B. invadens</i> distribution projected to the background of <i>B. dorsalis</i> s.s. + <i>B. philippinensis</i> + <i>B. papayae</i>, Model E (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090121#pone-0090121-t002\" target=\"_blank\">Table 2</a>).</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "rdm", "philippinensis"], "article_id"=>946449, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.g003", "stats"=>{"downloads"=>1, "page_views"=>109, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Reciprocal_distribution_models_RDM_for_B_dorsalis_s_s_B_philippinensis_B_papayae_blue_dots_and_B_invadens_red_dots_/946449", "title"=>"Reciprocal distribution models RDM for <i>B. dorsalis</i> s.s. + <i>B. philippinensis + B. papayae</i> (blue dots) and <i>B. invadens</i> (red dots).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400713"], "description"=>"<p>Light grey points represent 1000 random background points across the range of <i>B. dorsalis</i> s.s. and dark grey, <i>B. invadens</i>. <b>a)</b> PCA for “expert” predictor set. Proportion of variance for PC1 = 88.8% and for PC2 = 6.4%. <b>b)</b> PCA for ENFA driven predictor set (note: eight variables were loaded, most informative across the 4 “species”) Proportion of variance for PC1 = 68.4% and for PC2 = 24.6%.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "components", "predictor"], "article_id"=>946447, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.g002", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Principal_components_analysis_PCA_of_four_different_Bactrocera_spp_across_different_predictor_variable_sets_/946447", "title"=>"Principal components analysis (PCA) of four different <i>Bactrocera</i> spp. across different predictor variable sets.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400712"], "description"=>"<p>Grey area represents area not used for background selection. Colours refer to Köppen-Geiger classifications for presence records of each species investigated. Af = tropical rainforest; Am = tropical monsoon; tropical wet and dry or savannah climate; BSh = arid steppe climate; BWh = arid desert climate; Cfa = humid, subtropical; Cfb = Oceanic, highlands; Cwa = humid, subtropical; Cwb = temperate highland climate. Black outlines represent administrative boundaries selected prior to climate zone selection. b) Species occupation of different GEnS strata classifications (see <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090121#pone.0090121-Metzger1\" target=\"_blank\">[52]</a>). All = all four species combined.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "african", "distributions"], "article_id"=>946446, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.g001", "stats"=>{"downloads"=>0, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Asian_and_African_distributions_of_Bactrocera_spp_a_Bactrocera_dorsalis_s_s_grey_circles_Bactrocera_invadens_white_circles_Bactrocera_philippinensis_grey_squares_Bactrocera_papayae_white_squares_/946446", "title"=>"Asian and African distributions of <i>Bactrocera</i> spp. a) <i>Bactrocera dorsalis</i> s.s (grey circles), <i>Bactrocera invadens</i> (white circles), <i>Bactrocera philippinensis</i> (grey squares), <i>Bactrocera papayae</i> (white squares).", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400720"], "description"=>"<p>Models were assessed on their ability to predict the distribution of the other species with the AUC<sub>TEST</sub> (area under the receiver operating characteristic curve) score (independent dataset not included in model construction). DPP = <i>B. dorsalis</i> + <i>B. philippinensis</i> + <i>B. papayae</i>. True Skill Statistic (TSS) values were calculated to evaluate model performance at the threshold of maximum training sensitivity plus specificity. Schoener’s <i>D</i> values are the overlap of the given model in the <i>projected</i> range where the reciprocal model was calibrated.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography"], "article_id"=>946454, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.t002", "stats"=>{"downloads"=>0, "page_views"=>5, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_RDM_performance_/946454", "title"=>"RDM performance.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400717"], "description"=>"<p>Hatched area = area affected by recent <i>B. invadens</i> incursions. Red points are known localities of trapped flies. Models displayed at a binary presence/absence threshold set at maximum training sensitivity plus specificity. <b>b)</b> Final ENMs projected to show global invasion potential of <i>Bactrocera invadens</i> and when considered as a single species with <i>B. dorsalis</i>, <i>B. philippinensis</i> and <i>B. papayae</i>. Shading indicates variables outside training range and extrapolation (calculated with the multivariate environmental similarity surface (MESS) analysis in Maxent <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090121#pone.0090121-Elith3\" target=\"_blank\">[26]</a>). Models displayed at a binary presence/absence threshold set at maximum training sensitivity plus specificity.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "niche", "projected", "spatially", "enms", "africa"], "article_id"=>946451, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.g005", "stats"=>{"downloads"=>0, "page_views"=>39, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Final_Bactrocera_spp_Ecological_Niche_Models_ENMs_projected_spatially_a_Final_ENMs_projected_to_southern_Africa_to_predict_the_range_expansion_of_B_invadens_/946451", "title"=>"Final <i>Bactrocera</i> spp. Ecological Niche Models (ENMs) projected spatially a) Final ENMs projected to southern Africa to predict the range expansion of <i>B. invadens</i>.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-27 02:50:43"}
  • {"files"=>["https://ndownloader.figshare.com/files/1400716"], "description"=>"<p><b>a)</b> Niche breadth (Levin’s B) for 10 replicates of each final ENM projected to mainland southern Africa (see Fig. 5a). Note: DPP = <i>B. dorsalis</i> + <i>B. philippinensis</i> + <i>B. papayae. </i><b>b)</b> Niche overlap (Schoener’s <i>D</i>) between ENMs projected to mainland southern Africa (see Fig. 5a): A = <i>B. invadens</i> & <i>B. invadens</i> De Meyer <i>et al.</i> (2010); B = <i>B. invadens</i> & <i>B. dorsalis</i>; C = <i>B. invadens</i> & <i>B. dorsalis</i> + <i>B. philippinensis</i> + <i>B. papayae</i> (DPP); D = <i>B. invadens</i> & All four species combined.</p>", "links"=>[], "tags"=>["Pest control", "Computational biology", "Ecosystem modeling", "ecology", "Community Ecology", "Niche construction", "ecosystems", "biogeography", "Spatial and landscape ecology", "theoretical ecology", "Plant science", "Plant pathology", "Plant pests", "Zoology", "Entomology", "geography", "metrics", "calculated", "niche"], "article_id"=>946450, "categories"=>["Biological Sciences", "Medicine"], "users"=>["Matthew P. Hill", "John S. Terblanche"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0090121.g004", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Niche_metrics_calculated_for_Bactrocera_spp_Ecological_Niche_Models_/946450", "title"=>"Niche metrics calculated for <i>Bactrocera</i> spp. Ecological Niche Models.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2014-02-27 02:50:43"}

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