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To enrich spatio-temporal information on the distribution of alien, cryptogenic, and neonative species in the Mediterranean and the Black Sea, a collective effort by 173 marine scientists was made to provide unpublished records and make them open access to the scientific community. Through this effort, we collected and harmonized a dataset of 12,649 records. It includes 247 taxa, of which 217 are Animalia, 25 Plantae and 5 Chromista, from 23 countries surrounding the Mediterranean and the Black Sea. Chordata was the most abundant taxonomic group, followed by Arthropoda, Mollusca, and Annelida. In terms of species records, Siganus luridus, Siganus rivulatus, Saurida lessepsianus, Pterois miles, Upeneus moluccensis, Charybdis (Archias) longicollis, and Caulerpa cylindracea were the most numerous. The temporal distribution of the records ranges from 1973 to 2022, with 44% of the records in 2020–2021. Lethrinus borbonicus is reported for the first time in the Mediterranean Sea, while Pomatoschistus quagga, Caulerpa cylindracea, Grateloupia turuturu, and Misophria pallida are first records for the Black Sea; Kapraunia schneideri is recorded for the second time in the Mediterranean and for the first time in Israel; Prionospio depauperata and Pseudonereis anomala are reported for the first time from the Sea of Marmara. Many first country records are also included, namely: Amathia verticillata (Montenegro), Ampithoe valida (Italy), Antithamnion amphigeneum (Greece), Clavelina oblonga (Tunisia and Slovenia), Dendostrea cf. folium (Syria), Epinephelus fasciatus (Tunisia), Ganonema farinosum (Montenegro), Macrorhynchia philippina (Tunisia), Marenzelleria neglecta (Romania), Paratapes textilis (Tunisia), and Botrylloides diegensis (Tunisia)., peer-reviewed

1. Natura 2000 network (N2000) and national protected areas (NPAs) are recognised as the most important core ‘units’ for biological conservation in Europe. 2. Species distribution models (SDMs) were developed to detect the potential distribution of the rare and threatened cerambycid beetle Rosalia alpina L. in Europe, and the amount of suitable habitat within the N2000 network [special areas of conservation (SACs) and special protection areas (SPAs)], NPAs (e.g. national parks, regional parks, state reserves, natural monuments and protected landscapes) and the overall European protected area network (EPAN) (N2000 + NPAs) was quantified. 3. According to this analysis, the suitable habitat for R. alpina in Europe amounts to c. 754 171 km2 and stretches across substantially uninterrupted areas from Portugal to Romania (west to east) and from Greece to Germany (south to north). The overlay between the existing system of conservation areas in Europe (N2000 and NPAs) and the binary map for R. alpina showed that only c. 42% of potential habitat is protected. SACs and SPAs protect c. 25% and 21% of potential habitat, respectively. However, because the two site types often spatially overlap, when taken together the entire N2000 network protects c. 31% of potential habitat. Instead, NPAs offer a degree of protection of c. 29%. Overall, almost 60% of the area potentially suitable for the species is unprotected by the EPAN, an aspect that should be considered carefully when planning the conservation of this beetle at a large scale. 4. These results may also help to focus field surveys in selected areas where greater chances of success are encountered to save resources and increase survey effectiveness.

Knowing species distribution is essential to understand a species’ ecology and conservation needs. Species distribution models (SDMs) adopt a correlative approach to infer the ecological requirements of species from field observations based on statistically or theoretically derived response surfaces. SDMs have become a widely used technique and an increasingly important tool in many fields of natural and biological sciences to address various issues in applied ecology and conservation biology. The most basic of such aims is to understand the relationships between a species and its abiotic and biotic environment and to identify areas where a given species is likely to occur. The aim of this thesis was to evaluate the effectiveness of SDMs for supporting conservation actions. In particular, we used SDMs to focus on important but less handled issues and present three case studies. In the first case, we analysed the influence of spatial scale on SDMs’ ability to detect niche differences for two sympatric species of high conservation value, the bat Barbastella barbastellus and the cerambycid beetle Rosalia alpina, which apparently share the same habitat and ecological requirements. Broad scale SDMs revealed limited differences in preferred environmental predictor variables while failed to detect differences in microhabitats occupied. Only a small-scale niche analyses provided detailed ecological differences characterizing the two species and gave information on the type of management that such species need. In the second case, we evaluated the effectiveness of SDMs in managing the conservation of a mammal species reintroduced to Serbia and Bosnia-Herzegovina, the Eurasian beaver Castor fiber, during the post-release phase. We were able to predict suitable areas that beavers might colonize in the near future and to evaluate the potential risk posed to the expanding population by the very low degree of protection offered by the national reserve network. Finally, in the third case we focused on the importance of considering species’ phenology in presence record datasets to develop SDMs. We demonstrated that SDMs developed using different seasonal data separately, i.e. records of sites used by six European bat species for hibernation or reproduction may predict only partial species’ ecological niches. Then, we suggested a more valuable method for data collection to obtain a dataset featuring equally represented seasonal records for SDMs that take into account the potential ecological requirements of the species during its complete life cycle and predict a more realistic potential geographical range. My thesis offers important guidance in the development of conservation plans, e.g. by allowing more exhaustive gap analyses, helping detect corridors or low-suitability areas in need of restoration to improve the conservation status of management-dependent species.

Fagus sylvatica is one of the most representative trees of the European deciduous broadleaved forests, yet the impact of changing climatic conditions and anthropogenic pressures (anthromes) on its presence and distribution in the coastal and lowland areas of the Mediterranean Basin has long been overlooked. Here, we first analysed the local forest composition in two different time intervals (350–300 Before Current Era, BCE and 150–100 BCE) using charred wood remains from the Etruscan site of Cetamura (Tuscany, central Italy). Additionally, we reviewed all the relevant publications and the wood/charcoal data obtained from anthracological analysis in F. sylvatica, focusing on samples that date back to 4000 years before present, to better understand the drivers of beech presence and distribution during the Late Holocene (LH) in the Italian Peninsula. Then, we combined charcoal and spatial analyses to test the distribution of beech woodland at low elevation during LH in Italy and to evaluate the effect of climate change and/or anthrome on the disappearance of F. sylvatica from the lowlands. We collected 1383 charcoal fragments in Cetamura belonging to 21 woody taxa, with F. sylvatica being the most abundant species (28 %), followed by other broadleaved trees. We identified 25 sites in the Italian Peninsula with beech charcoals in the last 4000 years. Our spatial analyses showed a marked decrease in habitat suitability of F. sylvatica from LH to the present (ca. 48 %), particularly in the lowlands (0–300m above sea level, a.s.l.) and at higher altitudes (>900 m a.s.l). In the lowland areas, where F. sylvatica has disappeared, climate had a more uniform effect on beech distribution patterns across the entire elevation range analysed, whereas climate+anthrome and anthrome alone influenced 69 % and 84 % of the lowland areas, respectively.

Simple Summary Bioindicators are organisms that react to the quality or characteristics of the environment and their changes. They are vitally important to track environmental alterations and take action to mitigate them. As choosing the right bioindicators has important policy implications, it is crucial to select them to tackle clear goals rather than selling specific organisms as bioindicators for other reasons, such as for improving their public profile and encourage species conservation. Bats are a species-rich mammal group that provide key services such as pest suppression, pollination of plants of economic importance or seed dispersal. Bats show clear reactions to environmental alterations and as such have been proposed as potentially useful bioindicators. Based on the relatively limited number of studies available, bats are likely excellent indicators in habitats such as rivers, forests, and urban sites. However, more testing across broad geographic areas is needed, and establishing research networks is fundamental to reach this goal. Some limitations to using bats as bioindicators exist, such as difficulties in separating cryptic species and identifying bats in flight from their calls. It is often also problematic to establish the environmental factors that influence the distribution and behaviour of bats. Abstract Bats show responses to anthropogenic stressors linked to changes in other ecosystem components such as insects, and as K-selected mammals, exhibit fast population declines. This speciose, widespread mammal group shows an impressive trophic diversity and provides key ecosystem services. For these and other reasons, bats might act as suitable bioindicators in many environmental contexts. However, few studies have explicitly tested this potential, and in some cases, stating that bats are useful bioindicators more closely resembles a slogan to support conservation than a well-grounded piece of scientific evidence. Here, we review the available information and highlight the limitations that arise in using bats as bioindicators. Based on the limited number of studies available, the use of bats as bioindicators is highly promising and warrants further investigation in specific contexts such as river quality, urbanisation, farming practices, forestry, bioaccumulation, and climate change. Whether bats may also serve as surrogate taxa remains a controversial yet highly interesting matter. Some limitations to using bats as bioindicators include taxonomical issues, sampling problems, difficulties in associating responses with specific stressors, and geographically biased or delayed responses. Overall, we urge the scientific community to test bat responses to specific stressors in selected ecosystem types and develop research networks to explore the geographic consistency of such responses. The high cost of sampling equipment (ultrasound detectors) is being greatly reduced by technological advances, and the legal obligation to monitor bat populations already existing in many countries such as those in the EU offers an important opportunity to accomplish two objectives (conservation and bioindication) with one action.

Artificial light at night (ALAN) is a pervasive form of pollution largely affecting wildlife, from individual behaviour to community structure and dynamics. As nocturnal mammals, bats are often adversely affected by ALAN, yet some "light-opportunistic" species exploit it by hunting insects swarming near lights. Here we used two potentially competing pipistrelle species as models, Kuhl's (Pipistrellus kuhlii) and common (Pipistrellus pipistrellus) pipistrelles, both known to forage in artificially illuminated areas. We set our study in a mountainous area of central Italy, where only recently did the two species become syntopic. We applied spatial modelling and radiotracking to contrast potential vs. actual environmental preferences by the two pipistrelles. Species distribution models and niche analysis showed a large interspecific niche overlap, including a preference for illuminated areas, presenting a potential competition scenario. Pipistrellus pipistrellus association with ALAN, however, was weakened by adding P.kuhlii as a biotic variable to the model. Radiotracking showed that the two species segregated habitats at a small spatial scale and that P.kuhlii used artificially illuminated sites much more frequently than P.pipistrellus, despite both species potentially being streetlamp foragers. We demonstrate that ALAN influences niche segregation between two potentially competing species, confirming its pervasive effects on species and community dynamics, and provide an example of how light pollution and species' habitat preferences may weave a tapestry of complex ecological interactions.

Fire is a major disturbance that affects ecological communities, and when fire events increase in frequency or extent, they may jeopardise biodiversity. Although long-term studies are irreplaceable to understand how biological communities respond to wildfires, a rapid, efficient assessment of the consequences of wildfire is paramount to inform habitat management and restoration. Although Species Distribution Models (SDMs) may be applied to achieve this goal, they have not yet been used in that way. In summer 2017, during an extended drought that affected Italy, a severe wildfire occurred in the Vesuvius National Park (southern Italy). We applied SDMs to assess how much potential habitat was lost by the 12 bat species occurring in the area because of the wildfire, and whether habitat fragmentation increased following the event. Our analysis supported the hypotheses we tested (i.e. that the fire event potentially affected all species through habitat reduction and fragmentation) and that the bat species potentially most affected were those adapted to foraging in cluttered habitat (forest). We show that SDMs are a valuable tool for a first, rapid assessment of the effects of large-scale wildfires, and that they may help identify the areas that need to be monitored for animal activity and phenology, and to assist in saving human and financial resources.

Phenology is a key feature in the description of species niches to capture seasonality in resource use and climate requirements. Species distribution models (SDMs) are widespread tools to evaluate a species’ potential distribution and identify its large-scale habitat preferences. Despite its chief importance, data phenology is often neglected in SDM development. Non-migratory bats of temperate regions are good model species to test the effect of data seasonality on SDM outputs because of their different roosting preferences between hibernation and reproduction. We hypothesized that (1) the output of SDMs developed for six non-migratory European bat species will differ between hibernation and reproduction; (2) models built from datasets encompassing both ecological stages will perform better than seasonal models. We employed a dataset of 470 independent occurrences of bat hibernacula and 400 independent records of nursery roosts of selected species and for each species we developed separate winter, summer and mixed (i.e. generated from both winter and summer occurrences) models. Seasonal and mixed potential ranges differed from each other and the direction of this difference was species-specific. Mixed models outperformed seasonal models in representing species niches. Our work highlights the importance of considering data seasonality in the development of SDMs for bats as well as many other organisms, including non-migratory species, otherwise the analysis will lead to significant biases whose consequences for conservation planning and landscape management may be detrimental.

Species Distribution Models (SDMs) may provide important information for the follow-up phase of reintroduction operations by identifying the main areas most likely to be colonized by the reintroduced species. We used SDMs to identify the potential distribution of Eurasian beavers (Castor fiber) reintroduced to Serbia and Bosnia and Herzegovina in 2004–2006 after being historically driven to extinction by overhunting. Models were also used to carry out a gap analysis to assess the degree of protection granted by the national reserve networks to the potentially expanding population. Distances from hydrographic network, broadleaved forest, main watercourses and farmland were the main factors influencing model performance. We estimated that suitable habitat covers 14.0% (31,000 km2) of the whole study area. In Serbia, in 2004–2013 beavers expanded their range at a mean colonization speed of 70.9 ± 12.8 km/year (mean ± SD). Only 2.89% of and 9.72% of beaver’s suitable habitat lie within the national network of protected areas of Bosnia and Serbia respectively. We detected new potential areas where beavers will likely settle in the near future, advising on where further monitoring should be carried out. We also identified low suitability areas to be targeted with appropriate management to improve their conditions as well as important regions falling outside reserve boundaries to which protection should be granted.

Species distribution models (SDMs) provide realistic scenarios to explain the influence of bioclimatic variables on plant pathogen distribution. Diplodia sapinea is most harmful to plantations of both exotic and native pine species in Italy, causing economic consequences expecially to edible seed production. In this study, we developed maximum entropy models for D. sapinea in Italy to reach the following goals: (i) to carry out the pathogen’s first geographical distribution analysis in Italy and determine which eco-geographical variables (EGVs) may influence its outbreaks; (ii) to detect the effect of climate change on the potential occurrence of disease outbreaks by 2050 and 2070. We used Maxent ver. 3.4.0 to develop SDMs. We used six global climate models (BCC-CSM1-1, CCSM4, GISS-E2-R, MIROC5, HadGEM2-ES and MPI-ESM-LR) for two representative concentration pathways (4.5 and 8.5) and two time projections (2050 and 2070) to detect future climate projections of D. sapinea. The most important EGVs influencing outbreaks were land cover, altitude, mean temperature of driest and wettest quarter, precipitation of wettest quarter, precipitation seasonality and minimum temperature of coldest month. The distribution of D. sapinea mostly expanded in central and southern Italy and shifted in altitude upwards on average by ca. 93m a.s.l. Moreover the fungus expanded the range where disease outbreaks may be recorded in response to an increase in the mean temperature of wettest and driest quarter by ca. 1.9 °C and 5.8 °C, respectively in all climate change scenarios. Precipitation of wettest quarter did not differ between current and any of future models. Under different climate change scenarios D. sapinea's disease outbreaks will be likely to affect larger areas of pine forests in the country, probably causing heavy effects on the dynamics and evolution of these stands or perhaps constraining their survival.

Organisms sharing the same habitats may differ in small-scale microhabitat requirements or benefit from different management. In this study, set in Italy, we focused on two species of high conservation value, the cerambycid beetle Rosalia alpina and the bat Barbastella barbastellus, which often share the same forest areas and in several cases the same individual trees. We compared the potential distribution and, at two spatial scales, the niches between such species. The predicted distributions largely overlapped between the beetle and the bat. The niches proved to be similar on a broad scale, yet not on the plot one. Compared with B. barbastellus, R. alpina tends to occur at lower altitude in more irradiated sites with lower canopy closure and uses shorter trees with wider diameters. B. barbastellus occurred more often in trees within forest or along its edges, whereas R. alpina lays eggs in trees found in clearings. B. barbastellus plots were more frequent in forest, R. alpina plots in forested pasture and open-shredded forest. Overall, exposure to sun influenced more critically site and tree selection by R. alpina, as a warm microclimate is essential for larval development. Although B. barbastellus reproduction may be favored by warmer roosting conditions, bats may also find such conditions in dense forest and in strongly irradiated cavities high up in tall trees that project above the canopy. We emphasize that subtle differences in the ecological requirements of syntopic taxa could be missed at broad scales, so multiple-scale assessment is always advisable.