Search

Bats are major consumers of arthropods, and there is ever growing evidence that they play a pivotal role in the fight against agricultural pests. However, relatively little research has addressed explicitly this important topic, and studies in temperate regions (especially European case studies) are infrequent. In the last few years, state-of-art molecular methods to identify prey remains in droppings and new experimental approaches to assess the actual magnitude of this ecosystem service have opened new perspectives in research. In this review, we discuss such aspects with an emphasis on temperate regions, and identify new research frontiers. These comprise: (1) detecting new bat species that consume pests, and further pest insects that bats might eat; (2) exploring sublethal effects of bat echolocation calls on tympanate moth pests; (3) getting a better understanding of bat predation over blood-sucking arthropods that parasitize livestock; (4) unveiling indirect effects of bat predation on plant pathogens; (5) implementing models to map the occurrence of bat insectivory and the potential to promote it; and (6) analyse bat droppings for active surveillance of arthropod pests and the diseases they carry. We also highlight that so-called “common” bat species, often neglected in conservation actions, are likely to provide the bulk of pest suppression in agroecosystems. All such aspects merit investigation and may lead to novel management practices aimed at conjugating bat conservation with economic and social sustainability of farming.

Bats are often unfairly depicted as the direct culprit in the current COVID-19 pandemic, yet the real causes of this and other zoonotic spillover events should be sought in the human impact on the environment, including the spread of domestic animals. Here, we discuss bat predation by cats as a phenomenon bringing about zoonotic risks and illustrate cases of observed, suspected or hypothesized pathogen transmission from bats to cats, certainly or likely following predation episodes. In addition to well-known cases of bat rabies, we review other diseases that affect humans and might eventually reach them through cats that prey on bats. We also examine the potential transmission of SARS-CoV-2, the causal agent of COVID-19, from domestic cats to bats, which, although unlikely, might generate a novel wildlife reservoir in these mammals, and identify research and management directions to achieve more effective risk assessment, mitigation or prevention. Overall, not only does bat killing by cats represent a potentially serious threat to biodiversity conservation, but it also bears zoonotic implications that can no longer be neglected.

Wildfires shape ecosystems globally, yet little is known on their effects on wildlife distribution and spatial behaviour. We used bats as models to test the effects of fire on ecosystems because they are multi-habitat specialists and feature ecological and life traits such as behavioural plasticity and longevity that make them able to respond to both short- and long-term environmental changes. We aimed at testing the effects of a severe wildfire on a Mediterranean bat assemblage in terms of occupancy, activity and individual fitness. Here, we measure the effects of fire on activity levels and occupancy by a Mediterranean bat assemblage at the Vesuvius National Park, in Southern Italy, over 4 years, encompassing a year when a severe wildfire occurred. By comparing bat occurrence and activity at burnt versus unburnt sites with a Before-After/Control-Impact approach, we found that bat responses to wildfires are species specific and depend on the time elapsed since the fire. Species that rely more strongly on forest areas showed a strong short-term adverse response in terms of occupancy and activity, while species adapted to open habitats showed no response 1 year after the wildfire. However, most species showed a general positive effect due to the passage of fire 2 years after its occurrence, probably because of vegetation regrowth. The wildfire event was also associated with reduced reproduction in at least one species, and to worse individual body conditions 1 year after the wildfire. Our results show that most bats in a Mediterranean ecosystem show resilience to the occurrence of fire, yet many species show negative short-term responses by altering their spatial behaviour and decreasing their investment in reproduction. Future increases in fire occurrence and intensity due to climate change may alter bat assemblages and impair population viability in the long term, hampering the fundamental ecosystem services provided by structured bat communities.

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.

We assessed whether the presence and abundance of plant pathogens and antagonists change in soil fungal communities along a land abandonment gradient. The study was carried out in the Cilento area (Southern Italy) at a site with three different habitats found along a land abandonment gradient: agricultural land, Mediterranean shrubland and woodland. For all microbiological substrates the colony forming units were about 3.1 × 106 g−1 soil for agricultural land and about 1.1 × 106 g−1 soil for Mediterranean shrubland and woodland. We found the following genera in all habitats: Cladosporium, Mortierella, Penicillium and Trichoderma. In agricultural land, the significantly most abundant fungus genera were Aspergillus, Fusarium, Cylindrocarpon and Nectria; in Mediterranean shrubland, Rhizopus and Trichoderma; and in woodland, Bionectria, Mortierella, Cladosporium, Diplodia, Paecilomyces, Penicillium and Trichoderma. We found a total of 8, 8 and 9 species of fungal antagonist, and 16, 6 and 6 species of fungal plant pathogens in agricultural land, Mediterranean shrubland and woodland respectively. Fungal plant pathogens decreased significantly over a land abandonment gradient, while we no found significant differences among fungal antagonists in the three habitats. We conclude that a decrease in the number of fungal pathogen species occurs when formerly cultivated areas are abandoned. On the other hand, fungal antagonists seem not to be affected by this process.

Human-induced alterations of ecosystems and environmental conditions often lead to changes in the geographical range of plants and animals. While modelling exercises may contribute to understanding such dynamics at large spatial scales, they rarely offer insights into the mechanisms that prompt the process at a local scale. Savi’s pipistrelle (Hypsugo savii) is a vespertilionid bat widespread throughout the Mediterranean region. The species’ recent range expansion towards northeastern Europe is thought to be induced by urbanization, yet no study actually tested this hypothesis, and climate change is a potential alternative driver. In this radio-telemetry study, set in the Vesuvius National Park (Campania region, Southern Italy) we provide insights into the species’ thermal physiology and foraging ecology and investigate their relationships with potential large-scale responses to climate, and land use changes. Specifically, we test whether H. savii i) exploits urbanisation by selecting urban areas for roosting and foraging, and ii) tolerates heatwaves (a proxy for thermophily) through a plastic use of thermoregulation. Tolerance to heatwaves would be consistent with the observation that the species’ geographic range is not shifting but expanding northwards. Tracked bats roosted mainly in buildings but avoided urban habitats while foraging, actively selecting non-intensive farmland and natural wooded areas. Hypsugo H. savii showed tolerance to heat, reaching the highest body temperature ever recorded for a free-ranging bat (46.5 °C), and performing long periods of overheating. We conclude that H. savii is not a strictly synurbic species because it exploits urban areas mainly for roosting, and avoids them for foraging: this questions the role of synurbization as a range expansion driver. On the other hand, the species’ extreme heat tolerance and plastic thermoregulatory behaviour represent winning traits to cope with heatwaves typical of climate change-related weather fluctuations.

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.

a b s t r a c t Presence-only models can aid conservation and management of threatened, elusive species. We devel- oped a Maxent model for the rare cerambycid beetle Rosalia longicorn Rosalia alpina L. in Italy and neighbouring regions and identified the variables best explaining the species' occurrence on a large scale. Once successfully validated, we used the model to (a) evaluate the current degree of fragmen- tation of R. alpina range in Italy; and (b) quantify the amount of the Italian territory with the highest probability of beetle presence within the existing national conservation areas (Natura 2000 network, parks and reserves). Low ( 0.9) covered only 2.5%. R. alpina was predicted to occur mostly in broadleaved deciduous forest at 1000-1700 m a.s.l. with warm maximum spring temperatures and May and November precipitation >80 mm. We found a high degree of fragmentation; gaps were mainly covered with farmland or other unsuitable habitat. Over 52% of potential habitat is unprotected. While the Natura 2000 network protects 42% of potential habitat, parks and reserve covers less than 29%. To preserve R. alpina, we urge to create, or restore, forest corridors to bridge the otherwise impermeable gaps our model detected and grant protection to the still largely unprotected area of the Italian territory e.g. by including it in further Natura 2000 sites. Models such as ours may also help focus field surveys in selected areas to save resources and increase survey success.