Search

Context Urbanization and its associated impacts on biodiversity are increasing globally. There is a need to enhance our understanding of species responses to inform strategies for sustainable urbanization. Objectives Three extensive bird monitoring campaigns took place over the last three decades in the city of Naples, Italy, providing a comprehensive longitudinal dataset to analyse occurrence trends of urban birds. We aimed to assess both species-specific and assemblage-level changes in urban birds according to land cover dynamics. Methods We extracted bird data for the periods 1990–95, 2000–05, and 2014–18, and explored the spatial and temporal relationships between bird presence/avian assemblage composition, and land cover variation. Results The species richness of breeding birds remained stable over time, despite a notable species turnover, influenced by changes in the species’ key land cover classes. Species associated with forest and urban land cover tended to colonise the area, while those dependent on abandoned and cultivated areas decreased or went locally extinct. Birds changed their degree of dependence upon their key habitat type over time, as species from marginal and open habitat types needed larger amounts of habitat to persist within the area, while forest species showed an opposite trend. Conclusions Habitat-driven changes in avian assemblages within the urban landscape led to an increase in forest-associated species, and a decrease in birds associated with declining habitat types. Our findings may inform urban planning to promote more wildlife-friendly cities, which for our study area should prioritise open and marginal habitats.

Ailanthus altissima is an aggressive invasive tree worldwide, but the ecological factors that lead to the spread of this species in Mediterranean ecosystems are still unclear. Here we aim to identify such factors, focusing on the interaction of human activity with climatic conditions. We determined the occurrence and abundance of Ailanthus in 240 sites and studied their relationship with 20 variables representing climatic, geographic, and topographic factors, as well as land use, in the region of Campania (southern Italy). Overall, we found that temperature and rainfall in Campania are suitable for Ailanthus, with the only major constraint being the temperature at an altitude exceeding 900 m a.s.l.. We found that Ailanthus is unable to spread where the mean annual temperature is lower than 11.1 °C. By contrast, precipitation variables showed poor correlation with Ailanthus distribution, suggesting that rainfall in the selected study sites is suitable to sustain the growth of this tree. About land use variables, roads were the primary landscape feature along which this species spread and invaded new areas. Roads probably combine high propagule pressure and favorable growing conditions in terms of available resources i.e., light, water, and mineral nutrients, that allow Ailanthus to establish and spread along roadside edges in different ecosystems. In conclusion, we found that climate and human-associated variables are correlated with the current occurrence of Ailanthus, with the temperature being more influential at high elevation sites and road distance playing a prominent role in low elevation areas.

A methodological approach based on detailed land-use map, high-resolution LiDAR data and field surveys was developed to categorize productive and non-productive mixed forests, both in term of stand attributes and structural diversity. In 2011, leaf-off dedicated airborne LiDAR data were collected in a 20,000 ha inland patchy area which was representative of soil land use in the Apennines mountains of southern Italy. By combining field and LiDAR data in 5574 ha of forests with coexisting evergreen and deciduous species, we modelled common forest stand variables (height, diameter, volume and biomass) with high accuracy (0.60 ≤ Adj.R 2 ≤ 0.89). Moreover, a moderate correlation (0.425 ≤ τ ≤ 0.462) between field- and LiDAR-derived diversity indices was found. About 3393 ha of forests are enclosed in protected areas of the Natura 2000 network, which in turn possesses 77% (~ 576,286 Mg) of total aboveground dry biomass. Overall, eight forest types were identified, one of which, the European beech, is only found in the Natura 2000 sites, while other forest types are also found elsewhere. This is the first study to undertake a LiDAR analysis of Mediterranean forests in the Campania Region and might help better evaluate trade-off, especially in protected areas, in order to enhance multiple benefits and support sustainable management of forests.

Current strategies for conservation reportedly suffer from an inadequate awareness of the drivers affecting lichen diversity, pointing to the need to fully develop a functional approach to lichen ecology. This study is an attempt to detect the drivers affecting functional diversity in the lichen flora of a volcanic Mediterranean area. Data on epiphytic lichen distribution were correlated with information coming from a GIS analysis. Species richness, functional diversity and indicator values of lichens species were analyzed as a function of altitude, bioclimatic patterns and land use patterns. Both taxonomic and functional diversity were found to increase with altitude, peaking at 600 m a.s.l. and slightly decreasing at higher elevations. A filtering effect of altitude on lichen growth-forms was detected at increasing altitude, with foliose isidiate lichens replacing crustose lichens with sexual reproduction, cyanobacteria replacing Trentepohlia as photobiont, and oligotrophic species linked to partially shaded environments gradually replacing species indicating eutrophic conditions. Forest stations impacted by low impact traditional agriculture tended to express higher lichen diversity compared to either undisturbed broadleaved forests or intensive orchards. These data demonstrate the need to integrate traditional low-impact agricultural practices in protected areas. Moreover, they provide the evidence that reanalyzing past and recent lichenological censuses with the proposed analytical tools may help previewing and driving the evolution of endangered ecosystems.

Recent advances in fire management led landscape managers to adopt an integrated fire fighting strategy in which fire suppression is supported by prevention actions and by knowledge of local fire history and ecology. In this framework, an accurate evaluation of fire ignition risk and its environmental drivers constitutes a basic step toward the optimization of fire management measures. In this paper, we propose a multivariate method for identifying and spatially portraying fire ignition risk across a complex and heterogeneous landscape such as the National Park of Cilento, Vallo di Diano, and Alburni (southern Italy). The proposed approach consists first in calculating the fire selectivity of several landscape features that are usually related to fire ignition, such as land cover or topography. Next, the fire selectivity values of single landscape features are combined with multivariate segmentation tools. The resulting fire risk map may constitute a valuable tool for optimizing fire prevention strategies and for efficiently allocating fire fighting resources.

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.

Decomposition of plant debris is a critical process during the filling phase of water reservoir. Here we investigated the impact of decomposition of the plant species (Cytisus scoparius, Pteridium aquilinum and Juncus effusus) in the Alaco reservoir (southern Italy). To simulate lake ecological conditions, a microcosm experiment was carried-out for 100 days with litters incubated in water lake in aerobic conditions in the light at two temperatures (+12 °C and +24 °C). Litter types were characterized by classic proximate chemical analyses (total C and N, labile C, cellulose and lignin content, C/N and lignin/N ratios) and, at molecular level, by solid-state 13C CPMAS NMR. Water quality was monitored through pH, electrolytic conductivity, DOC, BOD5 and dissolved oxygen. Decomposition was more rapid for C. scoparius, intermediate for J. effusus and slower for P. aquilinum. After 100 days of decomposition for all litter type the O-alkyl-C region, associated with sugars and polysaccharides, decreased and the aliphatic alkyl-C region increased for C. scoparius and P. aquilinum. Immediately after litter submergence, DOC and BOD5 dramatically increased, reaching high values for P. aquilinum and C. scoparius. However, after 100 days of incubation, DOC concentration sharply decreased reaching values usually below 50 mg l−1, and after 10 days of incubation BOD5 values dropped to values close to zero. Although carried out in laboratory, the experiment showed that submerged plant litter during decomposition produces a short-term changes of water quality that rapidly returns to background level.

We used a Cellular Automata (CA) modeling framework to simulate the evolution of two small-size wildland fires that broke up in Sardinia, Italy in the summer of 2010. The CA model is based on our established detailed model that has been shown to approximate adequately the evolution of large-scale wildfires in Greece. The modified simplified model takes into account the landscape characteristics, the distribution of flammability and detailed wind field data. Simulation results over an ensemble of lattice realizations show that the model captures qualitatively the actual data; however, significant quantitative differences between simulations and real patterns do exist for very small sizes of burned area. Comparing model results with data obtained from Greece, where simulations succeeded to approximate quite well the spatio-temporal evolution of the fires, we suggest that the obtained discrepancies are due to the small size of the fires.We used a Cellular Automata (CA) modeling framework to simulate the evolution of two small-size wildland fires that broke up in Sardinia, Italy in the summer of 2010. The CA model is based on our established detailed model that has been shown to approximate adequately the evolution of large-scale wildfires in Greece. The modified simplified model takes into account the landscape characteristics, the distribution of flammability and detailed wind field data. Simulation results over an ensemble of lattice realizations show that the model captures qualitatively the actual data; however, significant quantitative differences between simulations and real patterns do exist for very small sizes of burned area. Comparing model results with data obtained from Greece, where simulations succeeded to approximate quite well the spatio-temporal evolution of the fires, we suggest that the obtained discrepancies are due to the small size of the fires.

We studied habitat selection by Rhinolophus euryale in a rural area of southern Italy in 1998–2000 by radio-tracking. Two comparisons were carried out, one between habitat occurrence within individual home ranges and within the study area, the other between time spent in each foraging habitat and habitat occurrence within the home range. The first analysis showed that olive groves and conifer plantations were, respectively, the most and the least important habitats. The second analysis highlighted the importance of woodland for R.euryale , while urban sites, open areas and conifer plantations were avoided. We recommend that clearing of continuous, large areas of woodland for tree harvesting should be avoided. Conifers should not be used for reforestation. Urbanisation should be limited in the areas of greatest importance for the species, and linear landscape elements such as tree lines and hedgerows should be maintained. # 2002 Elsevier Science Ltd. All rights reserved.

Bio-monitoring of air pollution, i.e. monitoring environmental pollution through the use of living organisms (Nimis & Skert, 1999), may be based either on the tendency of some organism to accumulate pollutants in their tissues (bio-accumulation) or on the changes that occur in the composition of animal and plant communities after exposure to pollutants (bioindication). Compared to instrumental monitoring, the use of bio-monitors allows to measure as a whole the global effect that abiotic and biotic factors exert on biota, what is not possible by just analyzing the concentrations of single selected pollutants in the environment. Bio-monitoring provides useful information about the global conditions affecting the environment over a given area. Of course it should not be considered as a substitute of instrumental monitoring, but rather, a necessary complement of it. It may also be suited to screen areas subjected to any risk of contamination, so helping to plan landscape policies and to set land nets of air quality (ANPA, 2001). Bio-monitoring of air pollutants can be passive or active. Passive methods observe organisms growing naturally within the area of interest. Active methods detect the presence of air pollutants by placing test organisms of known response and genotype into the study area (Szczepaniak & Biziuk, 2003). In this study, lichen distribution was examined in a district of Campania region to monitor the evolution of air quality at landscape scale. A new methodological approach was tried by overlapping the results of bio-monitoring samplings to land cover maps, in order to highlight the relations between air pollution and land use patterns (Pinho et al., 2004; Paoli et al., 2006; Pinho et al., 2008). The main objectives of this work were the following: to evaluate air quality on the studied area with the aid of IBL index, and reporting geo-referenced data on a thematic map; to relate lichen distribution and biodiversity to land use spatial patterns; to put the basis for a comparative analysis focused on changes induced by the present socio-economic evolution of the plain, from agriculture to industrial and tertiary; to provide a reproducible protocol for monitoring air quality, identifying clusters of lichen species linked to particular land use models and formulating previsions about environmental quality on areas characterized by similar dynamics. measuring lichen biodiversity through the IBL index allowed us to characterize the state of environment on the studied area. This method put the basis for a wider study on the dynamic evolution of a district interested by a process of industrial reconversion very close to a natural reserve. A good responsiveness of statistical clustering towards geo-statistical features of lands was found, confirming the reliability of IBL index as an indicator of environmental quality has been confirmed by statistical clustering towards geostatistical features of LC/LU (Land cover/Land Use). Moreover, the arrangement of lichen species is indicative not only of the environmental quality on a local scale, but also of the complex set of variables related to land use patterns at landscape level.