ORCID Profile
0000-0002-4951-2272
Current Organisations
University College London
,
University of Vienna
,
Universität Wien
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Publisher: Wiley
Date: 30-08-2022
DOI: 10.1111/ECOG.06227
Abstract: Islands are hotspots of plant endemism and are particularly vulnerable to the establishment (naturalization) of alien plant species. Naturalized species richness on islands depends on several biogeographical and socioeconomic factors, but especially on remoteness. One potential explanation for this is that the phylogenetically imbalanced composition of native floras on remote islands leaves unoccupied niche space for alien species to colonize. Here, we tested whether the species richness of naturalized seed plants on 249 islands worldwide is related to the phylogenetic composition of their native floras. To this end, we calculated standardized effect size (ses) accounting for species richness for three phylogenetic assemblage metrics (Faith's phylogenetic ersity (PD), PDses mean pairwise distance (MPD), MPDses and mean nearest taxon distance (MNTD), MNTDses) based on a phylogeny of 42 135 native island plant species and related them to naturalized species richness. As covariates in generalized linear mixed models, we included native species richness and biogeographical, climatic and socioeconomic island characteristics known to affect naturalized species richness. Our analysis showed an increase in naturalized species richness with increasing phylogenetic clustering of the native assemblages (i.e. native species more closely related than expected by chance), most prominently with MPDses. This effect, however, was smaller than the influence of native species richness and biogeographical factors, e.g. remoteness. Further, the effect of native phylogenetic structure (MPDses) on naturalized species richness was stronger for smaller islands, but this pattern was not consistent across all phylogenetic assemblage metrics. This finding suggests that the phylogenetic composition of native island floras may affect naturalized species richness, particularly on small islands where species are more likely to co‐occur locally. Overall, we conclude that the composition of native island assemblages affects their susceptibility to plant naturalizations in addition to other socioeconomic and biogeographical factors, and should be considered when assessing invasion risks on islands.
Publisher: Cold Spring Harbor Laboratory
Date: 19-10-2021
DOI: 10.1101/2021.10.18.464772
Abstract: The total impact of an alien species was conceptualised as the product of its range size, local abundance and per-unit effect in a seminal paper by Parker and colleagues in 1999, but a practical approach for estimating the three components has been lacking. Here, we generalise the impact formula and, through use of regression models, estimate the relationship between the three components of impact, an approach we term G-IRAE (Generalised Impact – Range size – Abundance – per-unit Effect). Moreover, we show that G-IRAE can also be applied to damage and management costs. We propose two methods for applying G-IRAE. The species-specific method computes the relationship for a given species across multiple invaded sites or regions, assuming a constant per-unit effect across the invaded area. The multi-species method combines data from multiple species across multiple sites or regions to calculate a per-unit effect for each species. While the species-specific method is more accurate, it requires a large amount of data for each species. The multi-species method is more easily applicable and data-parsimonious. We illustrate the multi-species method using data about money spent managing plant invasions in different biomes of South Africa. We found clear differences between species in terms of money spent per unit area invaded, with per-unit expenditures varying substantially between biomes for some species. G-IRAE offers a versatile and practical method which can be applied to many different types of data, to better understand and manage invasions.
Publisher: Pensoft Publishers
Date: 13-10-2021
DOI: 10.3897/NEOBIOTA.69.74121
Abstract: NA
Publisher: Wiley
Date: 23-03-2023
DOI: 10.1111/ELE.14196
Abstract: Human‐mediated changes in island vegetation are, among others, largely caused by the introduction and establishment of non‐native species. However, data on past changes in non‐native plant species abundance that predate historical documentation and censuses are scarce. Islands are among the few places where we can track human arrival in natural systems allowing us to reveal changes in vegetation dynamics with the arrival of non‐native species. We matched fossil pollen data with botanical status information (native, non‐native), and quantified the timing, trajectories and magnitude of non‐native plant vegetational change on 29 islands over the past 5000 years. We recorded a proportional increase in pollen of non‐native plant taxa within the last 1000 years. In idual island trajectories are context‐dependent and linked to island settlement histories. Our data show that non‐native plant introductions have a longer and more dynamic history than is generally recognized, with critical implications for bio ersity baselines and invasion biology.
Publisher: Elsevier BV
Date: 10-2021
Publisher: Wiley
Date: 30-08-2022
DOI: 10.1111/CONL.12918
Abstract: Monitoring the progress parties have made toward meeting global bio ersity targets requires appropriate indicators. The recognition of invasive alien species (IAS) as a bio ersity threat has led to the development of specific targets aiming at reducing their prevalence and impact. However, indicators for adequately monitoring and reporting on the status of biological invasions have been slow to emerge, with those that exist being arguably insufficient. We performed a systematic review of the peer‐reviewed literature to assess the adequacy of existing IAS indicators against a range of policy‐relevant and scientifically valid properties. We found that very few indicators have most of the desirable properties and that existing indicators are unevenly spread across the components of the Driver‐Pressure‐State‐Response and Theory of Change frameworks. We provide three possible reasons for this: (i) inadequate attention paid to the requirements of an effective IAS indicator, (ii) insufficient data required to populate and inform policy‐relevant, scientifically robust indicators, or (iii) deficient investment in the development and maintenance of IAS indicators. This review includes an analysis of where current inadequacies in IAS indicators exist and provides a roadmap for the future development of indicators capable of measuring progress made toward mitigating and halting biological invasions.
Publisher: Springer Science and Business Media LLC
Date: 11-06-2022
DOI: 10.1007/S10530-022-02836-0
Abstract: The total impact of an alien species was conceptualised as the product of its range size, local abundance and per-unit effect in a seminal paper by Parker et al. (Biol Invasions 1:3–19, 1999). However, a practical approach for estimating the three components has been lacking. Here, we generalise the impact formula and, through use of regression models, estimate the relationship between the three components of impact, an approach we term GIRAE (Generalised Impact = Range size × Abundance × per-unit Effect). We discuss how GIRAE can be applied to multiple types of impact, including environmental impacts, damage and management costs. We propose two methods for applying GIRAE. The species-specific method computes the relationship between impact, range size, abundance and per-unit effect for a given species across multiple invaded sites or regions of different sizes. The multi-species method combines data from multiple species across multiple sites or regions to calculate a per-unit effect for each species and is computed using a single regression model. The species-specific method is more accurate, but it requires a large amount of data for each species and assumes a constant per-unit effect for a species across the invaded area. The multi-species method is more easily applicable and data-parsimonious, but assumes the same relationship between impact, range size and abundance for all considered species. We illustrate these methods using data about money spent managing plant invasions in different biomes of South Africa. We found clear differences between species in terms of money spent per unit area invaded, with per-unit expenditure varying substantially between biomes for some species—insights that are useful for monitoring and evaluating management. GIRAE offers a versatile and practical method that can be applied to many different types of data to better understand and manage the impacts of biological invasions.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Cate Whittlesea.