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A conceptual map of invasion biology: Integrating hypotheses into a consensus network

Enders, M.; Havemann, F.; Ruland, F.; Bernard-Verdier, M.; Catford, J.A.; Gómez-Aparicio, L.; Haider, S.; Heger, T.; Kueffer, C.; Kühn, I.; Meyerson, L.A.; Musseau, C.; Novoa, A.; Ricciardi, A.; Sagouis, A.; Schittko, C.; Strayer, D.L.; Vilà, M.; Ess – 2020

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.

Titel
A conceptual map of invasion biology: Integrating hypotheses into a consensus network
Verfasser
Enders, M.; Havemann, F.; Ruland, F.; Bernard-Verdier, M.; Catford, J.A.; Gómez-Aparicio, L.; Haider, S.; Heger, T.; Kueffer, C.; Kühn, I.; Meyerson, L.A.; Musseau, C.; Novoa, A.; Ricciardi, A.; Sagouis, A.; Schittko, C.; Strayer, D.L.; Vilà, M.; Ess
Verlag
Wiley-Blackwell
Datum
2020-03
Kennung
https://doi.org/10.1111/geb.13082
Erschienen in
Global Ecology and Biogeography 29, 978-991
Zitierweise
Enders, M.; Havemann, F.; Ruland, F.; Bernard-Verdier, M.; Catford, J.A.; Gómez-Aparicio, L.; Haider, S.; Heger, T.; Kueffer, C.; Kühn, I.; Meyerson, L.A.; Musseau, C.; Novoa, A.; Ricciardi, A.; Sagouis, A.; Schittko, C.; Strayer, D.L.; Vilà, M.; Essl, F.; Hulme, P.E.; van Kleunen, M.; Kumschick, S.; Lockwood, J.L.; Mabey, A.L.; McGeoch, M.; Palma, E.; Pyšek, P.; Saul, W.-C.; Yannelli, F.A.; Jeschke, J.M. 2020. A conceptual map of invasion biology: integrating hypotheses into a consensus network. Global Ecology and Biogeography 29, 978-991. https://onlinelibrary.wiley.com/doi/full/10.1111/geb.13082
Sprache
eng
Art
Text
BibTeX Code
@article{doi:10.1111/geb.13082,
author = {Enders, Martin and Havemann, Frank and Ruland, Florian and Bernard-Verdier, Maud and Catford, Jane A. and Gómez-Aparicio, Lorena and Haider, Sylvia and Heger, Tina and Kueffer, Christoph and Kühn, Ingolf and Meyerson, Laura A. and Musseau, Camille and Novoa, Ana and Ricciardi, Anthony and Sagouis, Alban and Schittko, Conrad and Strayer, David L. and Vilà, Montserrat and Essl, Franz and Hulme, Philip E. and van Kleunen, Mark and Kumschick, Sabrina and Lockwood, Julie L. and Mabey, Abigail L. and McGeoch, Melodie A. and Palma, Estíbaliz and Pyšek, Petr and Saul, Wolf-Christian and Yannelli, Florencia A. and Jeschke, Jonathan M.},
title = {A conceptual map of invasion biology: Integrating hypotheses into a consensus network},
journal = {Global Ecology and Biogeography},
volume = {29},
number = {6},
pages = {978-991},
keywords = {biological invasions, concepts, consensus map, Delphi method, invasion science, invasion theory, navigation tools, network analysis},
doi = {10.1111/geb.13082},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/geb.13082},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/geb.13082},
abstract = {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.},
year = {2020}
}