Pysek, P;
Bacher, S;
Kuhn, I;
Novoa, A;
Catford, J;
Hulme, P;
Pergl, J;
... Blackburn, T; + view all
(2020)
MAcroecological Framework for Invasive Aliens (MAFIA): disentangling large-scale context dependence in biological invasions.
NeoBiota
, 62
pp. 407-461.
10.3897/neobiota.62.52787.
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Abstract
Macroecology is the study of patterns, and the processes that determine those patterns, in the distribution and abundance of organisms at large scales, whether they be spatial (from hundreds of kilometres to global), temporal (from decades to centuries), and organismal (numbers of species or higher taxa). In the context of invasion ecology, macroecological studies include, for example, analyses of the richness, diversity, distribution, and abundance of alien species in regional floras and faunas, spatio-temporal dynamics of alien species across regions, and cross-taxonomic analyses of species traits among comparable native and alien species pools. However, macroecological studies aiming to explain and predict plant and animal naturalisations and invasions, and the resulting impacts, have, to date, rarely considered the joint effects of species traits, environment, and socioeconomic characteristics. To address this, we present the MAcroecological Framework for Invasive Aliens (MAFIA). The MAFIA explains the invasion phenomenon using three interacting classes of factors – alien species traits, location characteristics, and factors related to introduction events – and explicitly maps these interactions onto the invasion sequence from transport to naturalisation to invasion. The framework therefore helps both to identify how anthropogenic effects interact with species traits and environmental characteristics to determine observed patterns in alien distribution, abundance, and richness; and to clarify why neglecting anthropogenic effects can generate spurious conclusions. Event-related factors include propagule pressure, colonisation pressure, and residence time that are important for mediating the outcome of invasion processes. However, because of context dependence, they can bias analyses, for example those that seek to elucidate the role of alien species traits. In the same vein, failure to recognise and explicitly incorporate interactions among the main factors impedes our understanding of which macroecological invasion patterns are shaped by the environment, and of the importance of interactions between the species and their environment. The MAFIA is based largely on insights from studies of plants and birds, but we believe it can be applied to all taxa, and hope that it will stimulate comparative research on other groups and environments. By making the biases in macroecological analyses of biological invasions explicit, the MAFIA offers an opportunity to guide assessments of the context dependence of invasions at broad geographical scales.
Type: | Article |
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Title: | MAcroecological Framework for Invasive Aliens (MAFIA): disentangling large-scale context dependence in biological invasions |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.3897/neobiota.62.52787 |
Publisher version: | https://doi.org/10.3897/neobiota.62.52787 |
Language: | English |
Additional information: | This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | climate, colonisation pressure, geographic range, habitats, invasion stages, non-native, propagule pressure, residence time, species traits, vertebrates |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10103967 |
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