A conceptual map of invasion biology: Integrating hypotheses into a consensus network
Background and aims Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overla...
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| Published in | Global ecology and biogeography Vol. 29; no. 6; pp. 978 - 991 |
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| Main Authors | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Wiley Subscription Services, Inc
01.06.2020
John Wiley and Sons Inc |
| Subjects | |
| Online Access | Get full text |
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| Abstract | Background and aims
Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses.
Results
The resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections).
Significance
The network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography. |
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| AbstractList | Since its emergence in the mid-20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field's current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses.
The resulting network was analysed with a link-clustering algorithm that revealed five
(resource availability, biotic interaction, propagule, trait and Darwin's clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called
, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections).
The network visually synthesizes how invasion biology's predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure - a
- that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography. BACKGROUND AND AIMS: Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses. RESULTS: The resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections). SIGNIFICANCE: The network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography. Background and aims Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses. Results The resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections). Significance The network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography. Since its emergence in the mid-20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field's current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses.BACKGROUND AND AIMSSince its emergence in the mid-20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field's current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses.The resulting network was analysed with a link-clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin's clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections).RESULTSThe resulting network was analysed with a link-clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin's clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections).The network visually synthesizes how invasion biology's predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure - a conceptual map - that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography.SIGNIFICANCEThe network visually synthesizes how invasion biology's predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure - a conceptual map - that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography. Background and aimsSince its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied importance. Not only has the number of empirical studies increased through time, but also has the number of competing, overlapping and, in some cases, contradictory hypotheses about biological invasions. To make these contradictions and redundancies explicit, and to gain insight into the field’s current theoretical structure, we developed and applied a Delphi approach to create a consensus network of 39 existing invasion hypotheses.ResultsThe resulting network was analysed with a link‐clustering algorithm that revealed five concept clusters (resource availability, biotic interaction, propagule, trait and Darwin’s clusters) representing complementary areas in the theory of invasion biology. The network also displays hypotheses that link two or more clusters, called connecting hypotheses, which are important in determining network structure. The network indicates hypotheses that are logically linked either positively (77 connections of support) or negatively (that is, they contradict each other; 6 connections).SignificanceThe network visually synthesizes how invasion biology’s predominant hypotheses are conceptually related to each other, and thus, reveals an emergent structure – a conceptual map – that can serve as a navigation tool for scholars, practitioners and students, both inside and outside of the field of invasion biology, and guide the development of a more coherent foundation of theory. Additionally, the outlined approach can be more widely applied to create a conceptual map for the larger fields of ecology and biogeography. |
| Author | Ruland, Florian Belmaker, Jonathan Kühn, Ingolf Meyerson, Laura A. Enders, Martin Strayer, David L. Lockwood, Julie L. Bernard‐Verdier, Maud Kueffer, Christoph Saul, Wolf‐Christian Mabey, Abigail L. Jeschke, Jonathan M. Catford, Jane A. Musseau, Camille Haider, Sylvia Essl, Franz Pyšek, Petr Ricciardi, Anthony Heger, Tina McGeoch, Melodie A. Schittko, Conrad Vilà, Montserrat Sagouis, Alban Kleunen, Mark Hulme, Philip E. Kumschick, Sabrina Novoa, Ana Havemann, Frank Gómez‐Aparicio, Lorena Yannelli, Florencia A. Palma, Estíbaliz |
| AuthorAffiliation | 16 The University of Rhode Island Department of Natural Resources Science Kingston Rhode Island 25 Ecology, Department of Biology University of Konstanz Konstanz Germany 11 Biodiversity Research/Systematic Botany University of Potsdam Potsdam Germany 28 Ecology, Evolution and Natural Resources Rutgers University New Brunswick New Jersey 4 Philosophische Fakultät Institut für Bibliotheks‐ und Informationswissenschaft Humboldt‐Universität zu Berlin Berlin Germany 6 School of BioSciences The University of Melbourne Parkville Victoria Australia 3 Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) Berlin Germany 27 South African National Biodiversity Institute Kirstenbosch National Botanical Gardens Claremont South Africa 20 Graham Sustainability Institute University of Michigan Ann Arbor Michigan United States 21 Estación Biológica de Doñana (EBD‐CSIC) Seville Spain 17 Czech Academy of Sciences Institute of Botany Department of Invasion Ecology Průhonice Czech Republic 18 Redpath M |
| AuthorAffiliation_xml | – name: 9 Martin Luther University Halle‐Wittenberg Institute of Biology/Geobotany and Botanical Garden Halle (Saale) Germany – name: 24 Bio‐Protection Research Centre Lincoln University Lincoln, Canterbury New Zealand – name: 19 Cary Institute of Ecosystem Studies Millbrook New York United States – name: 3 Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) Berlin Germany – name: 13 Institute of Integrative Biology, Department of Environmental Systems Science ETH Zurich Zurich Switzerland – name: 15 Helmholtz Centre for Environmental Research – UFZ Department Community Ecology Halle (Saale) Germany – name: 25 Ecology, Department of Biology University of Konstanz Konstanz Germany – name: 16 The University of Rhode Island Department of Natural Resources Science Kingston Rhode Island – name: 20 Graham Sustainability Institute University of Michigan Ann Arbor Michigan United States – name: 7 Biological Sciences University of Southampton Southampton United Kingdom – name: 26 Zhejiang Provincial Key Laboratory of Plant Evolutionary Ecology and Conservation Taizhou University Taizhou China – name: 29 Ocean and Earth Science National Oceanography Centre University of Southampton Southampton United Kingdom – name: 31 Department of Ecology Faculty of Science Charles University Prague Czech Republic – name: 6 School of BioSciences The University of Melbourne Parkville Victoria Australia – name: 11 Biodiversity Research/Systematic Botany University of Potsdam Potsdam Germany – name: 27 South African National Biodiversity Institute Kirstenbosch National Botanical Gardens Claremont South Africa – name: 30 School of Biological Sciences Monash University Clayton Victoria Australia – name: 14 Centre for Invasion Biology Department of Botany and Zoology Stellenbosch University Matieland South Africa – name: 2 Leibniz‐Institute of Freshwater Ecology and Inland Fisheries (IGB) Berlin Germany – name: 22 Department of Plant Biology and Ecology University of Seville Seville Spain – name: 17 Czech Academy of Sciences Institute of Botany Department of Invasion Ecology Průhonice Czech Republic – name: 12 Technical University of Munich Freising Germany – name: 1 Department of Biology, Chemistry, Pharmacy Institute of Biology Freie Universität Berlin Berlin Germany – name: 5 Department of Geography King’s College London London United Kingdom – name: 10 German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig Germany – name: 28 Ecology, Evolution and Natural Resources Rutgers University New Brunswick New Jersey – name: 23 Department of Botany and Biodiversity Research University of Vienna Vienna Austria – name: 21 Estación Biológica de Doñana (EBD‐CSIC) Seville Spain – name: 8 Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC Seville Spain – name: 4 Philosophische Fakultät Institut für Bibliotheks‐ und Informationswissenschaft Humboldt‐Universität zu Berlin Berlin Germany – name: 18 Redpath Museum McGill University Montreal Quebec Canada – name: 32 Centre for Invasion Biology Department of Mathematical Sciences Stellenbosch University Matieland South Africa |
| Author_xml | – sequence: 1 givenname: Martin orcidid: 0000-0002-0681-852X surname: Enders fullname: Enders, Martin email: enders.martin@gmx.net organization: Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) – sequence: 2 givenname: Frank orcidid: 0000-0002-0485-2580 surname: Havemann fullname: Havemann, Frank organization: Humboldt‐Universität zu Berlin – sequence: 3 givenname: Florian orcidid: 0000-0002-5785-1733 surname: Ruland fullname: Ruland, Florian organization: Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) – sequence: 4 givenname: Maud surname: Bernard‐Verdier fullname: Bernard‐Verdier, Maud organization: Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) – sequence: 5 givenname: Jane A. orcidid: 0000-0003-0582-5960 surname: Catford fullname: Catford, Jane A. organization: University of Southampton – sequence: 6 givenname: Lorena surname: Gómez‐Aparicio fullname: Gómez‐Aparicio, Lorena organization: Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), CSIC – sequence: 7 givenname: Sylvia orcidid: 0000-0002-2966-0534 surname: Haider fullname: Haider, Sylvia organization: German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig – sequence: 8 givenname: Tina orcidid: 0000-0002-5522-5632 surname: Heger fullname: Heger, Tina organization: Technical University of Munich – sequence: 9 givenname: Christoph orcidid: 0000-0001-6701-0703 surname: Kueffer fullname: Kueffer, Christoph organization: Stellenbosch University – sequence: 10 givenname: Ingolf orcidid: 0000-0003-1691-8249 surname: Kühn fullname: Kühn, Ingolf organization: Helmholtz Centre for Environmental Research – UFZ – sequence: 11 givenname: Laura A. orcidid: 0000-0002-1283-3865 surname: Meyerson fullname: Meyerson, Laura A. organization: The University of Rhode Island – sequence: 12 givenname: Camille orcidid: 0000-0002-5633-2384 surname: Musseau fullname: Musseau, Camille organization: Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) – sequence: 13 givenname: Ana orcidid: 0000-0001-7092-3917 surname: Novoa fullname: Novoa, Ana organization: Czech Academy of Sciences – sequence: 14 givenname: Anthony surname: Ricciardi fullname: Ricciardi, Anthony organization: McGill University – sequence: 15 givenname: Alban surname: Sagouis fullname: Sagouis, Alban organization: Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) – sequence: 16 givenname: Conrad orcidid: 0000-0002-2200-8762 surname: Schittko fullname: Schittko, Conrad organization: University of Potsdam – sequence: 17 givenname: David L. surname: Strayer fullname: Strayer, David L. organization: University of Michigan – sequence: 18 givenname: Montserrat orcidid: 0000-0003-3171-8261 surname: Vilà fullname: Vilà, Montserrat organization: University of Seville – sequence: 19 givenname: Franz surname: Essl fullname: Essl, Franz organization: University of Vienna – sequence: 20 givenname: Philip E. surname: Hulme fullname: Hulme, Philip E. organization: Lincoln University – sequence: 21 givenname: Mark orcidid: 0000-0002-2861-3701 surname: Kleunen fullname: Kleunen, Mark organization: Taizhou University – sequence: 22 givenname: Sabrina surname: Kumschick fullname: Kumschick, Sabrina organization: Kirstenbosch National Botanical Gardens – sequence: 23 givenname: Julie L. orcidid: 0000-0003-0177-449X surname: Lockwood fullname: Lockwood, Julie L. organization: Rutgers University – sequence: 24 givenname: Abigail L. orcidid: 0000-0003-0156-1881 surname: Mabey fullname: Mabey, Abigail L. organization: University of Southampton – sequence: 25 givenname: Melodie A. orcidid: 0000-0003-3388-2241 surname: McGeoch fullname: McGeoch, Melodie A. organization: Monash University – sequence: 26 givenname: Estíbaliz orcidid: 0000-0002-4500-254X surname: Palma fullname: Palma, Estíbaliz organization: The University of Melbourne – sequence: 27 givenname: Petr orcidid: 0000-0001-8500-442X surname: Pyšek fullname: Pyšek, Petr organization: Charles University – sequence: 28 givenname: Wolf‐Christian orcidid: 0000-0002-3584-6159 surname: Saul fullname: Saul, Wolf‐Christian organization: Stellenbosch University – sequence: 29 givenname: Florencia A. orcidid: 0000-0003-1544-5312 surname: Yannelli fullname: Yannelli, Florencia A. organization: Stellenbosch University – sequence: 30 givenname: Jonathan M. orcidid: 0000-0003-3328-4217 surname: Jeschke fullname: Jeschke, Jonathan M. organization: Berlin‐Brandenburg Institute of Advanced Biodiversity Research (BBIB) – sequence: 31 givenname: Jonathan surname: Belmaker fullname: Belmaker, Jonathan |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34938151$$D View this record in MEDLINE/PubMed |
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Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of... Since its emergence in the mid-20th century, invasion biology has matured into a productive research field addressing questions of fundamental and applied... Background and aimsSince its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of... BACKGROUND AND AIMS: Since its emergence in the mid‐20th century, invasion biology has matured into a productive research field addressing questions of... |
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| SubjectTerms | Algorithms biocenosis Biogeography biological invasions Biology Clustering Concept Paper concepts consensus map Delphi method ecological invasion Empirical analysis empirical research Hypotheses invasion science invasion theory navigation tools network analysis Resource availability students |
| Title | A conceptual map of invasion biology: Integrating hypotheses into a consensus network |
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