Linear infrastructures (e.g., roads, railways, pipelines, and powerlines) pose a serious threat to wildlife, due to the risk of wildlife-vehicle collisions (roadkills). The placement of mitigation measures, such as crossing structures, should consider species’ life cycles and ecological requirements. Such an assessment would require data collection over large areas, which may be possible by employing citizen science. In this study, we aimed to identify spatio-temporal trends of roadkill occurrence using citizen science data from one of the most urbanized and biodiversity-rich regions of Italy. Temporal trends were analyzed using generalized additive models, while landscape patterns were assessed by identifying significant thresholds over land cover gradients, related to increases in relative roadkill abundance, by employing threshold indicator taxa analysis. Our approach recorded a total of 529 roadkills, including 33 different species, comprising 13 mammal, 10 bird, 6 reptile, and 2 amphibian species. Statistical analysis indicated significant temporal trends for the red fox, the European hedgehog, the stone marten and the European badger, with peaks in roadkill occurrence between the winter and spring months. Relative roadkill abundance increased mostly in landscapes with anthropogenic land cover classes, such as complex cultivations, orchards, or urban surfaces. Our results allowed us to develop a map of potential roadkill risk that could assist in planning the placement of mitigation measures. Citizen science contributions from highly populated areas allowed data collection over a large area and a dense road network, and also directly led to the evaluation of management decisional options.
Environmental heterogeneity affects not only the distribution of a species but also its local abundance. High heterogeneity due to habitat alteration and fragmentation can influence the realized niche of a species, lowering habitat suitability as well as reducing local abundance. We investigate whether a relationship exists between habitat suitability and abundance and whether both are affected by fragmentation. Our aim was to assess the predictive power of such a relationship to derive advice for environmental management. As a model species we used a forest specialist, the short-toed treecreeper (Family: Certhiidae; Certhia brachydactyla Brehm, 1820), and sampled it in central Italy. Species distribution was modelled as a function of forest structure, productivity and fragmentation, while abundance was directly estimated in two central Italian forest stands. Different algorithms were implemented to model species distribution, employing 170 occurrence points provided mostly by the MITO2000 database: an artificial neural network, classification tree analysis, flexible discriminant analysis, generalized boosting models, generalized linear models, multivariate additive regression splines, maximum entropy and random forests. Abundance was estimated also considering detectability, through N-mixture models. Differences between forest stands in both abundance and habitat suitability were assessed as well as the existence of a relationship. Simpler algorithms resulted in higher goodness of fit than complex ones. Fragmentation was highly influential in determining potential distribution. Local abundance and habitat suitability differed significantly between the two forest stands, which were also significantly different in the degree of fragmentation. Regression showed that suitability has a weak significant effect in explaining increasing value of abundance. In particular, local abundances varied both at low and high suitability values. The study lends support to the concept that the degree of fragmentation can contribute to alter not only the suitability of an area for a species, but also its abundance. Even if the relationship between suitability and abundance can be used as an early warning of habitat deterioration, its weak predictive power needs further research. However, we define relationships between a species and some landscape features (i.e., fragmentation, extensive rejuvenation of forests and tree plantations) which could be easily controlled by appropriate forest management planning to enhance environmental suitability, at least in an area possessing high conservation and biodiversity values.
Reporting on uncommon wide animal movements could help in depicting potential carry-over effects at the population level, particularly in an era of rapid climate and environmental changes. The razorbill (Alca torda, Linnaeus 1758) is a regular passage migrant and winter visitor to Italian seas, but with sporadic presences usually involving small numbers of individuals. Irruptions have been occasionally documented, with the last records of an unusually large number dating back to 1982. However, in the past, irruptions have only been locally reported and poorly described. Here we report on an unprecedented massive irruption of hundreds of razorbills which occurred in the central Mediterranean Sea in November-December 2022. Using citizen science platforms and photos/videos shared on social networking sites (SNSs), we estimated the relative magnitude of the irruption and described the spatial distribution of birds at sea, as well as report cases of stranded individuals. We collected a total of 267 records, both from Italy and from neighboring countries. We also discuss the likely factors affecting razorbill irruption and stress the importance of open social platforms and data sharing to aid in the early detection and estimation of such events at a wide-scale, as well as for the monitoring of the mortality of the irrupted species.
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