Plant invasions in Italy: An integrative approach using the European LifeWatch infrastructure database

Malavasi, Marco; Acosta, Alicia Teresa Rosario; Carranza, María Laura; Bartolozzi, Luca; Basset, Alberto; Bassignana, M.; Campanaro, Alessandro; Canullo, Roberto; Carruggio, Francesca; Cavallaro, Viviana; Cianferoni, Fabio; Cindolo, Claudia; Cocciuffa, Cristiana; Corriero, Giuseppe; D’Amico, Francesco S.; Forte, Luigi; Freppaz, Michèle; Mantino, Francesca; Matteucci, Giorgio; Pierri, Cataldo; Stanisci, Angela; Colangelo, Paolo

doi:10.1016/j.ecolind.2018.03.038

Cited by 18 publications

(14 citation statements)

References 56 publications

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“…We selected generalized linear models (GLM; Nelder andBaker 1972, Oksanen andMinchin 2002) as a presence/ absence method and MaxEnt (Phillips et al 2006) as a presence-background method that are often adopted in ecological studies (Moudrý and Šímová 2013, Linda et al 2016, Malavasi et al 2018, Gábor et al 2019, Watts et al 2019). In addition, Graham et al (2008) showed that these two approaches were among the better performing modelling techniques when the data was affected by positional errors.…”

Section: Model Fitting and Evaluationmentioning

confidence: 99%

The effect of positional error on fine scale species distribution models increases for specialist species

et al. 2019

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Species occurrences inherently include positional error. Such error can be problematic for species distribution models (SDMs), especially those based on fine-resolution environmental data. It has been suggested that there could be a link between the influence of positional error and the width of the species ecological niche. Although positional errors in species occurrence data may imply serious limitations, especially for modelling species with narrow ecological niche, it has never been thoroughly explored. We used a virtual species approach to assess the effects of the positional error on fine-scale SDMs for species with environmental niches of different widths. We simulated three virtual species with varying niche breadth, from specialist to generalist. The true distribution of these virtual species was then altered by introducing different levels of positional error (from 5 to 500 m). We built generalized linear models and MaxEnt models using the distribution of the three virtual species (unaltered and altered) and a combination of environmental data at 5 m resolution. The models' performance and niche overlap were compared to assess the effect of positional error with varying niche breadth in the geographical and environmental space. The positional error negatively impacted performance and niche overlap metrics. The amplitude of the influence of positional error depended on the species niche, with models for specialist species being more affected than those for generalist species. The positional error had the same effect on both modelling techniques. Finally, increasing sample size did not mitigate the negative influence of positional error. We showed that fine-scale SDMs are considerably affected by positional error, even when such error is low. Therefore, where new surveys are undertaken, we recommend paying attention to data collection techniques to minimize the positional error in occurrence data and thus to avoid its negative effect on SDMs, especially when studying specialist species.

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Section: Model Fitting and Evaluationmentioning

confidence: 99%

The effect of positional error on fine scale species distribution models increases for specialist species

et al. 2019

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“…Similarly to that observed by Malavasi et al (2018) using the LifeWatch biological database, the utilisation of the LTER network constitutes a sound tool for modelling biological invasions, promoting the sharing of unprecedented amounts of data amongst ecologists. Furthermore, the multi-temporal nature of LTER data offers a unique opportunity to monitor variations and environmental conditions over time and also to identify, through multi-temporal iSDMs (e.g.…”

Section: Discussionmentioning

confidence: 98%

“…The intense and rapid land use change (Malavasi et al 2013(Malavasi et al , 2016 and the introduction of exotic species are amongst the main threats affecting native communities of Adriatic coastal ecosystems (Romano and Zullo 2014, Calabrese et al 2017, Malavasi et al 2018. Nonetheless, the coastal dunes of Molise still host many ecosystems of conservation concern in Europe (the so-called EU habitat types according to the European Directive 92/43/EEC; Stanisci et al 2014).…”

Section: Study Areamentioning

confidence: 99%

“…The considered cover categories in the study area are linked with habitats of European conservation concern: wooded dunes with Pinus pinea and/or Pinus pinaster (EC-2270) and herbaceous dune vegetation, that includes the embryonic shifting dunes (EC-2110), shifting dunes along the shoreline with Ammophila arenaria (EC -2120) and Malcolmietalia dune grasslands (EC -2230). All the variables were reported into raster layers with 5 m resolution, which is an adequate spatial resolution for analysing the coastal dune environments in the Mediterranean basin (Bazzichetto et al 2018a, Malavasi et al 2018).…”

Section: Environmental Datamentioning

confidence: 99%

“…The establishment, growth and expansion of invasive alien species depend on a combination of mechanisms related to both ecology of the species and the assembly of environmental factors (Lockwood et al 2005, Richardson and Pyšek 2006, Malavasi et al 2018. Indeed, biological invasions are promoted by a wide range of drivers that can be schematically grouped into three main components, the so called PAB factors: Propagule pressure (P), Abiotic characteristics of the invaded ecosystem (A) and Biotic interaction between invasive species and recipient community (B) (Catford et al 2009).…”

Section: Introductionmentioning

confidence: 99%

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Modelling Acacia saligna invasion on the Adriatic coastal landscape: An integrative approach using LTER data

Marzialetti¹,

Bazzichetto²,

Giulio³

et al. 2019

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Invasive Alien Species (IAS) pose a major threat to biodiversity and ecosystem services worldwide. Even if preventing biological invasions should be the most cost-effective way to minimise the impact of IAS on biodiversity, new efforts are necessary to identify early signs of invasion and to assess invasion risk. In this context, the implementation of invasive Species Distribution Models (iSDMs) could represent a sound instrument that merits further research. Acaciasaligna is an Australian vascular plant introduced into Europe during the last half century and is one of the most aggressive IAS in the Mediterranean basin. In this work, we model the occurrence of A.saligna in the coastal landscapes of central Italy (Adriatic coast) while accounting for the simultaneous effect of multiple factors (propagule pressure, abiotic, biotic factors). The iSDM for A.saligna was implemented on a representative tract of the Adriatic coast in central Italy (Molise region), largely included in two Long-Term Ecological Research (LTER) sites which actively contribute to the description of the considered ecosystem status and possible future trends. By using a Generalised Linear Model (GLM) with a binomial distribution of errors based on field and cartographic geo-referenced data, we examined the statistical relationship between the occurrence of A.saligna and a comprehensive set of environmental factors. The iSDM effectively captured the role of the different variables in determining the occurrence of A.saligna in the coastal dunes. Its occurrence is primarily related to Wooded dunes with Pinuspinea and/or P.pinaster (EU Habitat 2270) and distance from the sea and, to a lesser extent, with distance from roads and rivers. This research provides a first exploratory analysis of the environmental characteristics that promote the rapid growth and development of A.saligna in Italian dune ecosystems, identifying the habitats that are mainly affected by the invasive process in coastal areas and, by doing so, contributing to filling the gap between theory and practice in conservation decision-making. Finally, the LTER network benefitted from this research, confirming its relevance in providing useful information for modelling and monitoring invasion processes.

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The invasion history of Elodea canadensis and E. nuttallii (Hydrocharitaceae) in Italy from herbarium accessions, field records and historical literature

et al. 2022

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We analysed the invasion history of two North American macrophytes (Elodea canadensis and E. nuttallii) in Italy, through an accurate census of all available herbarium and field records, dating between 1850 and 2019, and a rich literature collection describing the initial introduction and naturalisation phase that supports the results obtained by the occurrence records. Elodea canadensis arrived in Italy before 1866 and had two invasion phases, between the 1890s and 1920s and between the 1990s and 2000s; E. nuttallii, probably arrived in the 1970s, started invading in 2000 and the invasion is still ongoing. Botanical gardens and fish farming played a crucial role in dispersal and naturalisation of both species. The current invasion range of both species is centred in northern Italy, with scattered occurrences of E. canadensis in central and southern regions. River Po represents a dispersal barrier to the Mediterranean region and a strategic monitoring site to prevent the invasion in the peninsula. The study detects differences in the niches of the two species during the introduction and naturalisation phase and a habitat switch occurred after 1980 in E. canadensis and after 2000 in E. nuttallii, during their expansion phases. For E. canadensis the switch corresponds to the second invasion round. Further research can clarify whether the second invasion round is due to confusion of the recently introduced E. nuttallii with E. canadensis, to a cryptic introduction of a new genotype, to post-introduction evolution, or just to an increased scientific interest in biological invasions.

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Plant invasions in Italy: An integrative approach using the European LifeWatch infrastructure database

Cited by 18 publications

References 56 publications

The effect of positional error on fine scale species distribution models increases for specialist species

The effect of positional error on fine scale species distribution models increases for specialist species

Modelling Acacia saligna invasion on the Adriatic coastal landscape: An integrative approach using LTER data

The invasion history of Elodea canadensis and E. nuttallii (Hydrocharitaceae) in Italy from herbarium accessions, field records and historical literature

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