Refine
Document Type
- Article (3)
Language
- English (3)
Has Fulltext
- yes (3)
Is part of the Bibliography
- no (3)
Keywords
- Alliaria petiolata (1)
- Biogeographical comparisons (1)
- NeoBiota (1)
- alien species (1)
- biological invasions (1)
- citizen science (1)
- data publishing (1)
- functional traits (1)
- increased vigour (1)
- intrinsic vs extrinsic factors (1)
The Editorial presents the focus, scope, policies, and the inaugural issue of NeoBiota, a new open access peer-reviewed journal of biological invasions. The new journal NeoBiota is a continuation of the former NEOBIOTA publication series. The journal will deal with all aspects of invasion biology and impose no restrictions on manuscript size neither on use of color. NeoBiota implies an XML-based editorial workflow and several cutting-edge innovations in publishing and dissemination, such as semantic markup of and enhancements to published texts, data publication, and extensive cross-linking within the journal and to external sources.
To understand what makes some species successful invaders, it is critical to quantify performance differences between native and introduced regions, and among populations occupying a broad range of environmental conditions within each region. However, these data are not available even for the world’s most notorious invasive species. Here we introduce the Global Garlic Mustard Field Survey, a coordinated distributed field survey to collect performance data and germplasm from a single invasive species: garlic mustard (Alliaria petiolata) across its entire distribution using minimal resources. We chose this species for its ecological impacts, prominence in ecological studies of invasion success, simple life history, and several genetic and life history attributes that make it amenable to experimental study. We developed a standardised field survey protocol to estimate population size (area) and density, age structure, plant size and fecundity, as well as damage by herbivores and pathogens in each population, and to collect representative seed samples. Across four years and with contributions from 164 academic and non-academic participants from 16 countries in North America and Europe thus far, we have collected 45,788 measurements and counts of 137,811 plants from 383 populations and seeds from over 5,000 plants. All field data and seed resources will be curated for release to the scientific community. Our goal is to establish A. petiolata as a model species for plant invasion biology and to encourage large collaborative studies of other invasive species.
The success of invasive species has been explained by two contrasting but non-exclusive views: (i) intrinsic factors make some species inherently good invaders; (ii) species become invasive as a result of extrinsic ecological and genetic influences such as release from natural enemies, hybridization or other novel ecological and evolutionary interactions. These viewpoints are rarely distinguished but hinge on distinct mechanisms leading to different management scenarios. To improve tests of these hypotheses of invasion success we introduce a simple mathematical framework to quantify the invasiveness of species along two axes: (i) interspecific differences in performance among native and introduced species within a region, and (ii) intraspecific differences between populations of a species in its native and introduced ranges. Applying these equations to a sample dataset of occurrences of 1,416 plant species across Europe, Argentina, and South Africa, we found that many species are common in their native range but become rare following introduction; only a few introduced species become more common. Biogeographical factors limiting spread (e.g. biotic resistance, time of invasion) therefore appear more common than those promoting invasion (e.g. enemy release). Invasiveness, as measured by occurrence data, is better explained by inter-specific variation in invasion potential than biogeographical changes in performance. We discuss how applying these comparisons to more detailed performance data would improve hypothesis testing in invasion biology and potentially lead to more efficient management strategies.