Alien plant invasion hotspots and invasion debt in European woodlands

Wagner, Viktória; Večeřa, Martin; Jíménez-Alfaro, Borja; Pergl, Jan; Lenoir, Jonathan; Svenning, Jens‐Christian; Pyšek, Petr; Agrillo, Emiliano; Biurrun, Idoia; Campos, Juan Antonio; Ewald, Jörg; Fernández‐González, Federico; Jandt, Ute; Rašomavičius, Valerijus; Šilc, Urban; Škvorc, Željko; Vassilev, Kiril; Wohlgemuth, Thomas; Chytrý, Milan

doi:10.1111/jvs.13014

Cited by 27 publications

(23 citation statements)

References 56 publications

(104 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The present research shows that invasive trees were more likely to be introduced, become established, and spread in tropical or subtropical areas [ 5 ]. Most of these 11 invasive tree species are native to tropical and subtropical areas of South America, southern Europe, East Asia, and South Asia.…”

Section: Discussionmentioning

confidence: 99%

“…For example, Hiptage benghalensis is a weed in the tropical rain forests of Australia and is highly invasive to Mauritius and Réunion, where it thrives in the dry lowland forests forming impenetrable stands of shrubs and suffocating the local vegetation [ 5 , 6 , 7 ]. Other studies have shown that some species may invade only a limited area but are likely to expand and cause further substantial damage [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions

Zhang

Wang

Wan

2022

Plants

View full text Add to dashboard Cite

Invasive tree species threaten ecosystems, natural resources, and managed land worldwide. Land cover has been widely used as an environmental variable for predicting global invasive tree species distributions. Recent studies have shown that consensus land cover data can be an effective tool for species distribution modelling. In this paper, consensus land cover data were used as prediction variables to predict the distribution of the 11 most aggressive invasive tree species globally. We found that consensus land cover data could indeed contribute to modelling the distribution of invasive tree species. According to the contribution rate of land cover to the distribution of invasive tree species, we inferred that the cover classes of open water and evergreen broadleaf trees have strong explanatory power regarding the distribution of invasive tree species. Under consensus land cover changes, invasive tree species were mainly distributed near equatorial, tropical, and subtropical areas. In order to limit the damage caused by invasive tree species to global biodiversity, human life, safety, and the economy, strong measures must be implemented to prevent the further expansion of invasive tree species. We suggest the use of consensus land cover data to model global invasive tree species distributions, as this approach has strong potential to enhance the performance of species distribution modelling. Our study provides new insights into the risk assessment and management of invasive tree species globally.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions

Zhang

Wang

Wan

2022

Plants

View full text Add to dashboard Cite

show abstract

“…A total of 15 contributions used fine‐grain plant community data to address macroecological questions at various extents: global (Kusumoto et al, 2021; Testolin et al, 2021), across the whole Palaearctic (Biurrun et al, 2021; Dembicz et al, 2021; Zhang et al, 2021), across Europe (Axmanová et al, 2021; Boonman et al, 2021; Padullés Cubino et al, 2021; Sporbert et al, 2021; Večera et al, 2021), larger parts of Europe (Cao Pinna et al, 2021; Wagner et al, 2021) or at state level (Bourgeois et al, 2021; Craven et al, 2021). Most of these studies rely on two large vegetation‐plot databases established and maintained by two working groups of the International Association for Vegetation Science (IAVS), the European Vegetation Archive (EVA; Chytrý et al, 2016) by the European Vegetation Survey (Axmanová et al, 2021; Boonman et al, 2021; Cao Pinna et al, 2021; Padullés Cubino et al, 2021; Sporbert et al, 2021; Večera et al, 2021; Wagner et al, 2021) and the GrassPlot database (Dengler et al, 2018) by the Eurasian Dry Grassland Group (Biurrun et al, 2021; Dembicz et al, 2021; Zhang et al, 2021). Testolin et al (2021) used data from the global vegetation‐plot database sPlot (Bruelheide et al, 2019), and four relied on regional data compilations (Bourgeois et al, 2021; Craven et al, 2021; Kusumoto et al, 2021; Tordoni et al, 2021).…”

Section: Contributions In the Special Issuementioning

confidence: 99%

Macroecology of vegetation — Lessons learnt from the Virtual Special Issue

Pärtel

Sabatini

Morueta‐Holme

et al. 2022

J Vegetation Science

View full text Add to dashboard Cite

Macroecology uses statistical tools and broad-scale data to understand general ecological principles. It has established itself as a solid research field over the past three decades (McGill, 2019). A central tenet is that emergent properties of large ecological systems can be tackled when analyzed as a whole, leaving aside much of contingency (Lawton, 1999). Macroecological principles have been used for centuries, but James Brown and Brian Maurer coined the term in their seminal paper in 1989 (Brown & Maurer, 1989). Initially restricted to body size, population density and geographical ranges, macroecology soon expanded to cover many more fields at the interface between ecology, geography and conservation science (Blackburn & Gaston, 1998). Modern macroecology is a very active discipline as indicated by a five-to six-fold increase in the number of scientific publications with the keyword 'macroecology' during the past two decades, corresponding to twice the rate of increase in ecological papers in general (keyword 'ecology'; source: webofknowledge.com, accessed Dec 2021).A decade ago, Beck et al. (2012) identified the lack of small-grain large-extent data as a major deficit in macroecology. For plants, this Special Issue demonstrates that many studies and large initiatives have addressed this gap since then. A total of 15 contributions used

show abstract

“…The storage and reuse of these data is now a fundamental source of information to address ecological and biogeographical questions, such as vegetation and habitat classification, ecological modeling, plant species invasions, understanding biodiversity patterns from a macroecological perspective or testing island biogeography theory (Chytrý et al 2020;Biurrun et al 2021;Chiarucci et al 2021;Wagner et al 2021). The large amount of available vegetation plots estimated for Europe by Schaminée et al (2009) underlines the great potential offered by these data and, therefore, the necessity of make them easily available.…”

Section: Introductionmentioning

confidence: 99%

AMS-VegBank: a new database of vegetation plots for the Italian territory

Alessi¹,

Bruzzaniti²,

Buldrini³

et al. 2022

VCS

View full text Add to dashboard Cite

The importance of collection, storage and exchange of georeferenced vegetation plot-based data has significantly grown in the recent decades, because of the new potentialities offered by ecoinformatics. In this article we introduce the Alma Mater Studiorum – University of Bologna vegetation database (AMS-VegBank; GIVD code EU-IT-021) compiling 17,505 georeferenced vegetation-plot observations within a time span of 90 years. This database includes 337,799 occurrence data of vascular plant species, belonging to many different habitat types. The historical relevance of the presented database is highlighted by the presence of some of the most ancient vegetation-plot observations in Europe (years 1930–1938). The geographic coverage of the database is mostly for Italian territory but it includes also data from other countries. The thematic focuses represented in the database are various, such as small Mediterranean islands, the Dolomite Mountains and the Italian National Parks. The large amount of historical plots available for the country not previously included in existing databases, combined with the constant action to improve the georeferencing of existing data and the addition of new data, highlight the uniqueness of this database. AMS-VegBank represents thus an important tool for studying plant biodiversity within the context of continental and global vegetation plot databases. Taxonomic reference: All plant names reported in this article follow the nomenclature by Pignatti et al. (2017–2019). Abbreviations: EVA = European Vegetation Archive; GIVD = Global Index of Vegetation-Plot Databases.

show abstract

Alien plant invasion hotspots and invasion debt in European woodlands

Cited by 27 publications

References 56 publications

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions

Macroecology of vegetation — Lessons learnt from the Virtual Special Issue

AMS-VegBank: a new database of vegetation plots for the Italian territory

Contact Info

Product

Resources

About

Alien plant invasion hotspots and invasion debt in European woodlands

Cited by 27 publications

References 56 publications

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions

Using Consensus Land Cover Data to Model Global Invasive Tree Species Distributions

Macroecology of vegetation — Lessons learnt from the Virtual Special Issue

﻿AMS-VegBank: a new database of vegetation plots for the Italian territory

Contact Info

Product

Resources

About

AMS-VegBank: a new database of vegetation plots for the Italian territory