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How different biodiversity components underpin ecosystem resistance and recovery and thus stability under extreme climatic events is a timely question in Ecology. To date, most studies have focused on the role of taxonomic diversity, neglecting how community functional composition and diversity beget stability under exceptional climatic conditions. In addition, land use potentially modulates how biodiversity and ecosystem functions respond to extreme climatic conditions. Using an 11-year time-series of plant biomass from 150 permanent grassland plots spanning a gradient of land-use intensity, we examined how different biodiversity components affected resistance and recovery of biomass production under extreme drought. The association between biodiversity, land use, and biomass production varied across years, especially in the driest years. Species rich and functionally diverse communities buffered extreme droughts better, while species poor communities dominated by fast-growing species had higher recovery capabilities after a moderate to extreme drought. Our results show that plant community functional and taxonomic components determine grasslands resistance and recovery under severe drought. In turn, this points to the importance of designing landscapes with both extensively and intensively managed grasslands. Functionally and taxonomically rich communities (favoured under low land-use intensity) would preserve biomass production under extreme droughts, whereas species-poor, fast-growing communities (favoured by high land-use intensity) would restore biomass production after extreme droughts.

Aim: In species distribution models (SDMs), the quality and quantity of data describing the species distribution determine the quality of the estimate of the species-environment relationship. However, SDMs usually rely on opportunistic datasets sampled from existing projects/repositories with different purposes than modelling the distribution of the target species. Here, we assessed how different sampling strategies affect the accuracy and precision of species response curves estimated by parametric SDMs.Major taxa studied: Virtual plant species.Location: Abruzzo (Italy).Time period: Timeless (simulated data).Methods: We simulated the occurrence of two virtual species: one generalist and one specialist. These were similarly affected by precipitation, but the generalist had a wider thermal tolerance and, thus, a wider distribution extent. We sampled their occurrence following different sampling strategies: random, stratified, systematic, topographic, uniform within the environmental space, and close to roads. For each sampling design and species, we ran 500 simulations at increasing sampling efforts (total: 42,000 replicates). For each replicate, we fitted a binomial generalised linear model, extracted model coefficients for precipitation and temperature, and compared them with true coefficients from the known virtual species’ equation. We evaluated the quality of the estimated response curves by computing bias, variance, and root mean squared error. Also, we simulated two virtual subspecies to assess the impact of missing covariates on the performance of the different sampling approaches. Finally, we evaluated the effect of incompletely sampling the environmental space on the performance of the approach that uniformly samples within the environmental space.Results: For the generalist species, we found the lowest root mean squared error when uniformly sampling the environmental space, while sampling occurrence data close to roads provided the worst performance. For the specialist species, all sampling designs showed comparable outcomes. Excluding important predictors from fitted SDMs similarly affected all sampling strategies. Sampling only portions of the environmental space reduced the performance of the approach that uniformly samples within the environmental space, regardless of the portion surveyed. Main conclusions: Our results suggest that a proper estimate of the species response curve can be obtained when the choice of the sampling strategy is guided by the species’ ecology. Overall, uniformly sampling the environmental space seems more efficient for species with wide environmental tolerances. The advantage of seeking the most appropriate sampling strategy vanishes when modelling species with narrow realised niches.

Predicting the occurrence probability of species is intrinsically dependent on the quality of the training dataset and, in particular, on the sample prevalence (i.e., the ratio between presences and absences). Whenever the number of presences and absences is not equal within the training dataset, the predictions deviate towards higher values as the sample prevalence increases and vice versa. As a result, probability models of species occurrence with different sample prevalence cannot be directly compared. The favourability concept was introduced to amend this limitation. Indeed, the favourability - i.e., the variation in the probability of occurrence regardless the sample prevalence - could reduce the degree of uncertainty when comparing species distributions despite different sample prevalences. To test this hypothesis, we simulated 50 virtual species and compared the predictive performance of four probability-based and favourability-based Species Distribution Models (GLM, GAM, RF, BRT) under a set of different prevalence values and sampling strategies (i.e, random and stratified sampling). Favourability-based models performed slightly better than probability-based models in predicting the species distribution over geographic space, confirming also their capability to reduce the variability of the predictions across different degrees of sample prevalence.

[Question]: Vegetation around the alpine–treeline ecotone faces changes in both climate and land use (i.e. grazing abandonment). Broad-scale shrub encroachment is considered an effect of these changes, but it remains unclear how this process is mediated by local-scale environmental heterogeneity. Our goal is to determine which local-scale environmental factors shape the spatial distribution and temporal trends of alpine dwarf shrub vegetation dominated by Juniperus communis in Mediterranean mountains. [Location]: Three sites in the Central Apennine Mountain Range (Italy): Mt. Terminillo, Mt. Duchessa and Mt. Ernici. [Methods]: Combining a set of environmental variables obtained at a fine scale (25-m resolution) from multi-year remote sensing imagery and field-collected vegetation data, we modelled the occurrence and cover of Juniperus communis-dominated dwarf shrubland, as well as its change over time, as a function of local climate, topography and land use, using linear and generalized mixed effects models. [Results]: Over a period of almost 60 years (1954–2012) shrubland occurrence increased by 12% and shrubland cover by 10% in our study sites. Its current distribution and change over time appear to be strongly shaped by the joint influences of fine-scale topography, above-ground biomass, land use and microclimate. Shrublands have been favoured locally in areas with harsher alpine environmental constraints and stronger resource limitations. [Conclusions]: Our study shows that in the Mediterranean high-mountain environment J. communis dwarf shrubland acts as a stress-tolerant pioneer vegetation, occurring in areas that are otherwise sparsely vegetated. Contrary to our expectations, at fine scales, warmer temperatures and the regional decline in grazing did not favour shrub encroachment. Despite increasing overall, J. communis shrubs have little competitive ability to successfully encroach grasslands, and remain restricted to less-productive areas. Our results confirm that fine-scale environmental heterogeneity can strongly influence shrub distribution and dynamics, thereby modulating future responses in evolving alpine ecosystems., Grant to the Department of Science Roma Tre University, Grant/Award Number: MIURItaly, Dipartimenti di Eccellenza,Articolo 1. Commi 314-337 Legge 232/2016

Analysing temporal patterns in plant communities is extremely important to quantify the extent and the consequences of ecological changes, especially considering the current biodiversity crisis. Long-term data collected through the regular sampling of permanent plots represent the most accurate resource to study ecological succession, analyse the stability of a community over time and understand the mechanisms driving vegetation change. We hereby present the LOng-Term Vegetation Sampling (LOTVS) initiative, a global collection of vegetation time-series derived from the regular monitoring of plant species in permanent plots. With 79 data sets from five continents and 7,789 vegetation time-series monitored for at least 6 years and mostly on an annual basis, LOTVS possibly represents the largest collection of temporally fine-grained vegetation time-series derived from permanent plots and made accessible to the research community. As such, it has an outstanding potential to support innovative research in the fields of vegetation science, plant ecology and temporal ecology., The authors acknowledge institutional support as follows. Nicola J. Day: Te Apārangi Royal Society of New Zealand (Rutherford Postdoctoral Fellowship). Jiří Danihelka: Czech Science Foundation (project no. 19-28491X) and Czech Academy of Sciences (project no. RVO 67985939). Francesco de Bello: Spanish Plan Nacional de I+D+i (project PGC2018-099027-B-I00). Eric Garnier: La Fage INRA experimental station. Tomáš Herben: GAČR grant 20-02901S. Anke Jentsch: German Federal Ministry of Education and Research (grant 031B0516C - SUSALPS) and Oberfrankenstiftung (grant OFS FP00237). Norbert Juergens: German Federal Ministry of Education and Research (grant 01LG1201N - SASSCAL ABC). Frédérique Louault and Katja Klumpp: AnaEE-France (ANR-11-INBS-0001). Robin J. Pakeman: Strategic Research Programme of the Scottish Government's Rural and Environment Science and Analytical Services Division. Meelis Pärtel: Estonian Research Council (PRG609) and European Regional Development Fund (Centre of Excellence EcolChange). Josep Peñuelas: Spanish Government (grant PID2019-110521GB-I00), Fundación Ramon Areces (grant ELEMENTAL-CLIMATE), Catalan Government (grant SGR 2017-1005), and European Research Council (Synergy grant ERC-SyG-2013-610028, IMBALANCE-P). Ute Schmiedel: German Federal Ministry of Education and Research (Promotion numbers 01LC0024, 01LC0024A, 01LC0624A2, 01LG1201A, 01LG1201N). Hana Skálová: GAČR grant 20-02901S. Karsten Wesche: International Institute Zittau, Technische Universität Dresden. Susan K. Wiser: New Zealand Ministry for Business, Innovation and Employment’s Strategic Science Investment Fund. Ben A. Woodcock: NERC and BBSRC (NE/N018125/1 LTS-M ASSIST - Achieving Sustainable Agricultural Systems). Enrique Valencia: Program for attracting and retaining talent of Comunidad de Madrid (no. 2017-T2/AMB-5406) and Community of Madrid and Rey Juan Carlos University (Young Researchers R&D Project. Ref. M2165 – INTRANESTI). Truman P. Young: National Science Foundation (LTREB DEB 19-31224).

With the aim to identify future challenges and opportunities in vegetation science, we brought together a group of 22 early career vegetation scientists from diverse backgrounds to perform a horizon scan. In this contribution, we present a selection of 15 topics that were ranked by participants as the most emergent and impactful for vegetation science in the face of global change. We highlight methodological tools that we expect will play a critical role in resolving emerging issues by providing ways to unveil new aspects of plant community dynamics and structure. These tools include next generation sequencing, plant spectral imaging, process-based species distribution models, resurveying studies and permanent plots. Further, we stress the need to integrate long-term monitoring, the study of novel ecosystems, below-ground traits, pollination interactions and global networks of near-surface microclimate data at fine spatio-temporal resolutions to fully understand and predict the impacts of climate change on vegetation dynamics. We also emphasize the need to integrate traditional forms of knowledge and a diversity of stakeholders into research, teaching, management and policy-making to advance the field of vegetation science. The conclusions reached by this horizon scan naturally reflect the background, expertise and interests of a representative pool of early career vegetation scientists, which should serve as basis for future developments in the field., We would like to thank the IAVS for their support in organizing the workshop in October. FAY is grateful to J. Jeschke for his suggestions and advice on logistics for the horizon scan. FAY would like to thank the support of the Rising Star Junior Fellowship in the Department of Biology, Chemistry and Pharmacy of the Freie Universität and specially the women’s representative office at the Department of Biology, Chemistry and Pharmacy of the Freie Universität (Frauenbeauftragte BCP) for providing financial support for childcare during Germany’s COVID-19 lockdowns. Without this help, working on this manuscript would have not been possible during these hard times. We acknowledge PhD grants from Fundação de Amparo à Pesquisa do Estado de São Paulo - FAPESP (2018/09054-0) to GD, from Conselho Nacional do Desenvolvimento Científico e Tecnológico- CNPq (141715/2018-9) to JT, from an Indonesia Endowment Fund for Education (LPDP) Scholarship to MJMH, from the Ministry of Education, Science and Technological Development of the Republic of Serbia granted to TŠ, from the Slovenian Research Agency (ARRS) to FK and from Mexico’s CONACyT (CVU: 348078) to CXPV

International audience; Secondary dry grasslands in Europe can host high levels of vascular plant richness at small spatial scales. However, in Southern Europe their biodiversity patterns are largely unexplored. In this work, we aim at: (i) estimating plant species richness patterns at very fine scales in montane dry grasslands, on limestone bedrock, in Abruzzo Lazio and Molise National Park (Central Apennines, Italy); (ii) assessing the most important physical and edaphic drivers of biodiversity patterns at multiple plot sizes. We used randomly placed nested-plot series where we measured alpha-diversity at three different plot sizes (1 m2, 0.1 m2 and 0.01 m2) and within-plot beta-diversity (as expressed by the slope of the species-area curve across plot sizes). Variable selection was performed by means of Random Forests. Relationships between selected variables and diversity measures were then assessed using Regression Trees, Linear and Generalized Linear Models. Overall, results pointed to topographically-controlled edaphic factors (soil pH and silt fraction) as the main drivers positively influencing alpha-diversity at all spatial scales, with a positive effect of rock cover and slope inclination at smaller spatial grains. Beta-diversity was positively influenced by rock cover. We suggest that high-pH, steep and/or rocky sites feature higher species richness because they lack competitive grass species. Our results are in agreement with previous works underlining the importance of less productive habitats for the conservation of secondary grassland biodiversity.

AimHere, we aim to: (i) investigate the local effect of environmental and human-related factors on alien plant invasion in sub-Antarctic islands; (ii) explore the relationship between alien species features and their dependence on anthropogenic propagule pressure; and (iii) unravel key traits conferring invasiveness in the sub-Antarctic.LocationPossession Island, Crozet archipelago (French sub-Antarctic islands).TaxonNon-native vascular plants (Poaceae, Caryophyllaceae, Juncaceae).MethodsSingle-species distribution models were used to explore the effect of high-resolution topoclimatic and human-related variables on the occurrence of six of the most aggressive alien plants colonizing French sub-Antarctic islands. Furthermore, the interaction between alien species traits and their response to anthropogenic propagule pressure was analysed by means of a multi-species distribution model. This allowed identifying the features of species that were associated to low dependence on human-assisted introductions, and were thus potentially more invasive.ResultsWe observed two main invasion patterns: low-spread species strongly dependent on anthropogenic propagule pressure and high-spread species limited mainly by harsh climatic conditions. Differences in invasiveness across species mostly related to their residence time, life history and plant height, with older introductions, perennial and low-stature species being more invasive.Main conclusionsThe availability of high-resolution data improved our understanding of the role of environmental and human-related factors in driving alien species distribution on sub-Antarctic islands. At the same time, the identification of alien species features conferring invasiveness may help anticipating future problematic invasions.

International audience; Question: Does spectral diversity captured by unmanned aerial systems (UAS) provide reliable information for monitoring the eco-geomorphological integrity of Mediterranean coastal dune ecosystems? Can this information discriminate between two coastal areas with low (LP) and high (HP) human pressure? Location: Tyrrhenian coast, Central Italy. Methods: By processing UAS images, we derived the normalized difference vegetation index (NDVI) and topographic variables at high spatial resolution (0.5 m) for 150 m wide strips starting from the coastline inland on two representative coastal tracts under low and high human pressure. We mapped the sea–inland heterogeneity applying Rao's Q index to the plant biomass (NDVI) and geomorphology variables (elevation and slope). Since Rao's Q index can be calculated in a multidimensional space, we summarized the variability of these three variables into a single eco-geomorphological layer. We then inspected and compared how the Rao's Q index values for plant biomass, geomorphology and eco-geomorphology change as a func-tion of the distance from the sea between the two coastal sites. Results: Rao's Q heterogeneity values vary along the sea–inland gradient of well-preserved sites (LP). The maximum eco-geomorphological heterogeneity was found at intermediate distances from the sea and decreased toward the inner sector where the dune geomorphology was more stable and vegetation more homogeneously dis-tributed. Instead, Rao's Q heterogeneity values featured constant low values along the gradient on the HP site, highlighting a simplified eco-geomorphological gradient related to the high human pressure. Conclusions: Using UAS, the eco-geomorphological gradient of coastal dunes can be quantified at a very fine spatial resolution over management-relevant extents. Rao's Q index applied to sensing imagery successfully captured the differences in the eco-geomorphological heterogeneity along the sea–inland dune gradient and among sites with different levels of anthropic pressure. This approach supports frequent surveys and is particularly suitable for spatial monitoring of key coastal functions and services. © 2021 International Association for Vegetation Science.

Although many hypotheses explaining invasion success have been formulated, invasion drivers are usually tested in isolation. This work aims to analyze the combined influence of propagule pressure (P), abiotic (A) and biotic (B) factors (PAB) on determining the invasion process of an exotic plant taxon (Carpobrotus sp.) in Mediterranean coastal landscapes. Specifically, we used a binomial Generalized Additive Model for exploring the relation between the occurrence of the invasive species and a set of PAB proxy variables derived from high-resolution remote sensed imagery (LiDAR – Light Detection and Ranging – and orthophotos). We evaluated the predictive power of the model by computing the mean of the AUC scores obtained through a 5-fold cross-validation and visual inspection of the Hosmer-Lemeshow plot. The integrated PAB approach efficiently captured the different roles played by the drivers of invasion in affecting the presence of the species. Invasion does not proceed homogeneously across the coastal landscape, but is promoted wherever the combined action of the PAB factors is favorable for establishment of the invader. Moreover, the use of remotely sensed data allowed us to model the invader-landscape relationship on a large geographic extent and to highlight the coastal sectors that are most likely to be invaded in the future.

We examined the relationship between coastal habitats (sensu European Union Habitats Directive) and local dune morphology along a Mediterranean coastal dune system by integrating field collected vegetation data and remotely sensed imagery. Specifically, we described the morphological profile of each EC habitat based on the morphological variables that are most likely to affect their occurrence, including elevation, slope, curvature, northness, eastness and sea distance. In addition, we assessed the role and strength of each morphological variable in determining the occurrence of EC habitats. We used 394 random vegetation plots representative of six EC habitats (Habitat 1210: “Annual vegetation of drift lines”; Habitat 2110: “Embryonic shifting dunes”; Habitat 2120: “Shifting dunes along the shoreline with Ammophila arenaria ”; Habitat 2210 and 2230: “ Crucianellion maritimae fixed beach dunes” and “ Malcolmietalia dune grasslands”; Habitat 2250: “Coastal dunes with Juniperus spp.”; Habitat 2260: “ Cisto-Lavanduletalia dune sclerophyllous scrubs”) found along the Tyrrhenian coast of central Italy. We derived each morphological variable from a DTM (Digital Terrain Model) obtained from 2-m resolution LiDAR (Light Detection And Range) images. The mean value of each variable was calculated at different spatial scales using buffer areas of increasing radius (2 m, 4 m, 8 m) around each vegetation plot. Mean morphological values for each EC habitat were compared using Kruskal-Wallis rank test. The role and strength of the relationship between habitat type and the morphological variables were assessed using Generalized Linear Models. EC habitats occur differentially across dune morphology, and the role and strength of each morphological variable define habitat specificity. Dune elevation and sea distance were determined to be the key factors in shaping EC habitat occurrence along this section of the Mediterranean coast. Identification of the close relationship between habitat type and morphological variables deriving from airborne LiDAR imagery points to the high potential of such remote sensing tool for analyzing and monitoring the integrity of coastal dune ecosystems. As airborne LiDAR enables the rapid collection of extremely accurate topographic data over large areas, it also offers useful information for the management of these threatened and fragile ecosystems.

International audience; Coastal erosion, in combination with sea-level rise and extreme meteorological events, is globally threatening the biodiversity and functioning of dune ecosystems, along with the essential ecosystem services they provide. In this study, by quantifying the intensity of erosion and accretion processes occurred over two decades in a wide Mediterranean dune system, we explore the influence of sand processes on dune plant communities focusing on a large portion of the sea-inland gradient. In particular, using different regression techniques, we assess how erosion and accretion processes affect richness, cover and diversity of Mediterranean coastal dune plant communities. Results show that the influence of coastal erosion and accretion varies along the sea-inland gradient, with foreseeable consequences on the integrity of dune systems. The negative effect of erosion seems to be particularly marked on foredunes, which play a key role in dune formation, while decreasing in landward communities. On the other hand, accretion features an opposite trend, unexpectedly influencing only Mediterranean shrubs. We highlight the importance of monitoring the effects of erosion and accretion processes on coastal vegetation in order to support the conservation of dune habitats and preserve the associated ecosystem services, especially in the context of climate and human-induced changes.

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.

Resurveying studies are commonly appreciated as a means to monitoring temporal changes in plant diversity. However, most of them still rely on phytosociological plots, which, although representing an invaluable source of data, can lead to biased estimates of vegetation changes. At the community-level, temporal changes can be quantified by means of beta-diversity measures. However, compositional variation can be the result of two different, often contrasting, processes: turnover and nestedness. In this context we test the effectiveness of resurveying approaches based on quasi-permanent plots in revealing temporal changes in herbaceous communities of Mediterranean coastal dune systems. Indeed, due to their being highly dynamic, coastal dunes can be considered ideal habitats for implementing such tools. In particular, we quantified temporal changes in species composition occurred over 10–15 years by calculating Sorensen index of dissimilarity and, in order to determine whether the change was really driven by species turnover, we partitioned Sorensen index into its two components of turnover and nestedness. At the same time, since diagnostic species are considered to be particularly sensitive to habitat modifications and helpful in assessing changes in the ecological structure of a community, we analyzed temporal changes in the occurrence and cover of diagnostic species of the investigated habitats. Results show that coastal dune communities of our study area underwent consistent changes during the analyzed time-span. Almost 25% of the historical plots disappeared. Major transformations, mainly driven by species turnover, involved upper beach communities, embryonic and mobile dunes, as revealed by the parallel analysis of beta diversity and diagnostic species. This work shows how resurveying approaches can efficiently reveal useful insights on vegetation dynamics, therefore providing a solid basis for the implementation of effective conservation strategies, especially in endangered habitats.

In light of the global biodiversity loss, syntheses of the available knowledge about drivers of biodiversity are becoming increasingly important. However, despite the high number of studies analyzing patterns of plant species diversity, few attempts have been made to synthesize findings within different ecosystems. In this work, the relative role of a wide set of predictors imputable to three conceptual-methodological domains (abiotic, human-mediated disturbance and landscape domain, hereafter AD, DD and LD) was simultaneously analyzed in 644 random plots distributed along the coastal dunes of Central Italy. Native species richness and focal species cover, both field-recorded, were used as response variables. Predictors pertaining to the three domains were derived from both field surveys and high-resolution remotely sensed imagery (LiDAR and orthophotos). To test how AD, DD and LD affect native species richness and focal species cover, a GLM and a linear model were fitted respectively. The three domains were then ranked according to their relative importance. Although the role of the three domains was always significant, they turned out to unequally contribute to the explanation of native species richness and focal species cover patterns. For Mediterranean coastal dune ecosystems, AD appears to be the key biodiversity driver, followed by DD and LD. Our results suggest that as long as human disturbance is limited, plant diversity will distribute according to species abiotic tolerances, regardless of habitat loss and fragmentation per se. Representing a first effort towards a synthesis of plant diversity drivers in coastal dunes, this work points to the importance, in Mediterranean coastal dune ecosystems, of zonation dynamics, whose occurrence should be addressed as a priority issue by efficient conservations strategies.

Preventing biological invasions in areas of conservation concern represents the most cost-effective strategy to minimize the impact of Invasive Alien Species (IAS) on native communities. In this context, invasive Species Distribution Models (iSDMs) are a sound tool for predicting invasion risk in protected areas. Although their potential to support invasive species managers is widely acknowledged, evidence of iSDMs providing actual conservation solutions is still scarce. With this work, we propose an iSDM-based methodology that accounts for the role of multiple invasion drivers to assess the risk posed by IAS in protected areas. Using a binomial Generalized Additive Model, we predicted the occurrence of a highly invasive plant in Mediterranean dune systems. According to the predicted IAS occurrence, we quantified the invasibility of protected sites inside the study area, classified each site in low to medium-high invasibility categories, and identified site-specific management perspectives. Our results encourage the use of iSDMs as a means of evaluating the risk posed by IAS in protected areas, and, at the same time, represent an attempt to fill the gap between theory and practice in conservation decision-making.

Due to increasing worldwide anthropogenic pressure and in order to promote adequate environmental conservation strategies, quantification of non-biological diversity, such as considering marine and beach litter, is becoming increasingly useful. Information on beach litter in terms of richness and diversity may have a consistent influence regarding the evaluation of its pressure and impact on coastal ecosystems. Highlighted are strengths, weaknesses and caveats concerning the use of uni- and bi-variate diversity metrics applied to a class of man-made non-biological objects periodically accumulated on the beaches. Two case studies show evidence that the application of diversity metrics on non-biological objects may have different implications. In absence of a universal and standardized non-biological taxonomy, it is important to be cautious when comparing values obtained from non-living assemblages, in particular if different sites, time or operators are considered. Moreover, different indices provide different information. Therefore, users should pay particular attention on the application of diversity metrics, addressing specific research questions and avoiding automatic calculation of redundant and “magic” indices.

We assessed the annual accumulation rates of beach litter on the Tyrrhenian coast of central Italy, providing the characterization of litter following European standardized guidelines. Three different sites of a beach were sampled seasonally from spring 2014 to winter 2015. A total of 31,739 items were removed and classified into 103 categories. Plastic represented the majority (94.4%) of the collected items. We detected temporal and spatial differences in the abundance and composition of litter between seasons and between sites. Furthermore, we found that plastic cotton bud sticks composed > 30% of the total amount of litter and, together with plastic and polystyrene pieces, made up > 70% of the total items. Finally, our results led us to propose that the most effective strategy to reduce litter pollution is to devise specific management procedures focusing on the most abundant items.