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CAM-COAST: the database of bird and mammal fauna collected through camera traps in a Natura 2000 coastal site in Italy

2025/08/25 by Maria Carla de Francesco, Claudia Fiorella Huamaní Cahuas, Micaela del Valle Rasino +2 · 1 voice
Environmental Science · #Land Use and Ecosystem Services #Species Distribution and Climate Change #Wildlife Ecology and Conservation

paper · pdf · doi:10.3389/fevo.2025.1603295

openalex publication_date 2025/08/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/23

Abstract

Coastal dunes are dynamic ecosystems influenced by both natural and anthropogenic processes that shape vegetation zonation and faunal assemblages within dunes (Acosta et al., 2007;Bessa et al., 2013;Delgado-Fernandez et al., 2019). They are included in the European Habitat Directive (European Council Directive 92/43/EEC) as ecosystems of conservation interest, and they are largely considered in a bad (or inadequate) conservation status (Genovesi et al., 2014;Prisco et al., 2020). The maintenance of these environments is also essential for the ecosystem services they provide (Drius et al., 2019), such as climate regulation (Drius et al., 2016), protection from wind and aerosol (Bonari et al., 2017), control of coastal erosion (Drius et al., 2013), as reservoirs and shelter of biodiversity (Maiorano et al., 2015;Drius et al., 2016;Pellissier et al., 2020;Rasino et al., 2024), as well as recreation and tourist resources (Mastronardi et al., 2015;Petrosillo et al., 2007). However, wildlife may cause direct or indirect impacts due to consumption or trampling of vegetation and may alter the composition/structure of soil (Enquist et al., 2020;Warner & Cushman, 2002). Consequently, native plant communities may change as nitrophilous species and/or new generalist or alien species take advantage (Amori et al., 2016;Forbes et al., 2019;Kristensen et al., 2022;Mori et al., 2021). Coastal dune habitats are considered as transitional ecosystems, harboring important refugia for wildlife in human-dominated landscapes, but they are still understudied concerning their role as habitat for wildlife (Kissling et al., 2024;Rendall et al., 2019). Wildlife monitoring and inventory pose more challenges than vegetation monitoring due to animals' continuous movements and varying activity periods (Simo et al., 2023). The use of camera traps has become an excellent alternative to traditional field surveys of medium and large-size mammal species, and their use is increasing over time thanks to their effectiveness and non-invasiveness (Buxton et al., 2018;Kissling et al., 2024;Kleiven et al., 2023;van Meurs et al., 2024). Camera traps consist of automatically triggered cameras that allow collecting photographic records of species at a specific location (Rovero & Zimmermann, 2016;O'Connell et al., 2011). They represent a good alternative for detecting and monitoring animals in remote areas (van Meurs et al., 2024), and invasive and problematic species (Di Cerbo & Biancardi, 2013;Ferretti et al., 2021;Piscopo et al., 2023), and improving knowledge of species ecology and behavior (Wong & Kachel. 2024). The aim of our work is to describe the CAM-COAST database, which contains bird and mammal image records detected in coastal dune habitats of an Italian Natura 2000 Network site (N2K), across different seasons and daily phases using photo-trapping techniques. The study also provides a preliminary descriptive analysis of the collected data to outline the seasonal and daily distribution of the observed fauna, and determine the potential pressures and threats that may affect the conservation of EU habitats in the area. This study was part of the global research project called LIFEPLAN -A Planetary Inventory of Life, funded by the European Research Council (ERC) and coordinated by Helsinki University (Rogers et al., 2023), with around 200 globally distributed research sites, aiming at improving knowledge of biodiversity worldwide and using datasets for predictions and future scenarios (Rogers et al., 2023). LIFEPLAN is both running a global sampling biodiversity program and developing advanced bioinformatics and statistical approaches to make the best use of these data (Hardwick et al. 2024). Camera-trapping activity is still being conducted to implement international standards for data collection and analysis and promote collaborative, open data networks aimed at enhancing wildlife monitoring.The sampling site (Fig. 1) is located in the N2K SAC IT7228221 Foce Trigno-Marina di Petacciato (Italy), also included in the eLTER (integrated European Long-Term Ecosystem, critical zone and socio-ecological Research) network (Wohner et al., 2020), established to facilitate high-impact research and to catalyze new insights about the compounded impacts of climate change, biodiversity loss, soil degradation, pollution, and unsustainable resource use in terrestrial, freshwater, and transitional water ecosystems (Stoll et al., 2015;Mazzocchi et al., 2019). It is characterized by a natural vegetation zonation of sand coastal dunes (Prisco et al., 2016) of a great naturalistic value, with 11 habitats of European conservation concern (EU) (Stanisci et al., 2014;Prisco et al., 2015;Di Paola et al., 2022). The habitat zonation (following the sea-inland gradient) consists of embryonic and shifting dune habitats (EU habitats 1210, 2110, 2120), transition dunes with annual grassland (EU habitats 2230), well-preserved low Mediterranean maquis (EU habitats 2260), and back dunes with pine forest (EU habitat 2270*) (Del Vecchio et al., 2015) (Fig. 1). In dune habitats of this N2K site the following bird species are known (EEA; GBIF; Compagnone et al., 2023): Cettia cetti (Temminck, 1820), Buteo buteo (Linnaeus, 1758), Sturnus vulgaris (Linnaeus, 1758), Passer italiae (Vieillot, 1817), Hirundo rustica (Linnaeus, 1758) Corvus monedula (Linnaeus, 1758) Corvus cornix (Linnaeus, 1758), Cisticola juncidis (Rafinesque, 1810), Hirundo rustica (Linnaeus, 1758), Galerida cristata (Linnaeus, 1758),;Emberiza calandra (Linnaeus, 1758), and Pica pica (Linnaeus, 1758). These last three species are also included in our database while no mammal species was reported for this area before our study.[Place Figure 1 here] S1 Suppl. Mat.Five camera traps (model 4.0C from Wildlife Monitoring Solutions) were placed within a one-hectare natural area, according to the sampling design of the LIFEPLAN project (Hardwick et al. 2024) S1, Suppl. Mat). Each camera trap was fixed on a tree at 0.5 m from the ground and oriented downward and was motion activated by a passive infrared sensor, taking a series of 5 photographs approximately 1 s apart (5megapixel color CMOS) with 2560x1920 effective pixels and IR range of 20 m. Following the LIFEPLAN protocol, they were equipped with an access code to minimize the risks of tampering (Rogers et al., 2023) and were active for 233 days from February to December 2021. Camera trapping captured images of mammals and some occasional birds. Image records were previously analyzed through visual inspection image by image to eliminate repetitive images of the same specimen separated by fractions of a second both photographed by the same camera trap and by nearby camera traps, considering that the space separating the 5 camera traps is too small to identify them as completely independent from each other (Bowkett et al., 2008;Rovero & Zimmermann, 2016). A thorough examination of each individual photo sequence was conducted to identify separate photo-capture events. Subsequent images of the same species individuals captured within 30 minutes of each other were considered single events if the individuals could not be clearly recognized by particular signs related to sex, age group or body markings. Subsequently, images were analyzed with the aid of specialist literature and taxonomic manuals to identify the species (Amori & Nappi, 2011;Svensson et al., 2012;Corbet & Ovenden, 2012;Paolucci & Mauro, 2022). Camera traps produced a total of 2932 wildlife pictures in 233 days for a total of 766 occurrences (Table S2, Suppl. Mat.). CAM-COAST database included for each recorded image the following attributes, as requested by Darwin Core guidelines of GBIF repository: a) the ID number of image record; b) the number of occurrences; b) the taxonomic description at species and subspecies level with scientific name and authors (Festari & Castelli, 2011; Avibase; Mammal Diversity); c) English common name (Avibase; Mammal Diversity); d) date and time of records; e) daily phases (as for Desk Aeronautico; Time and Date AS. 1995-2025) and seasons (identification refers to ISTAT) of records; f) number of individuals per each camera image; g) total occurrences after aggregation of repetitive images. Moreover, the European Conservation Status of species listed in the CAM-COAST is reported in Table S3 (Suppl. Mat.).We performed exploratory analyses to examine the frequency of species observations, we calculated the Relative Abundance Index (RAI), using the following formula (Lim et al., 2023;O'Brien, 2021;Palmer et al., 2018): RAI = Di / N x 100 where Di represents the number of days with observations for a specific species and N the total number of observation days for all the camera traps.To analyze the seasonal and daily activity patterns of the recorded species, we employed two complementary abundance indices: the Monthly Relative Abundance Index (MRAI) and the Daily Phase Relative Abundance Index (DRAI) (Liu et al. (2013). MRAI was calculated as: MRAI = (DM / N) × 100 where DM is the number of days in which a species was recorded within a given month, and N is the total number of sampling days for all species. This index allowed us to quantify relative abundance across months and to group these monthly values into seasonal categories (spring, summer, autumn, winter). To explore diel activity, we used the DRAI, defined as: DRAI = (DD / N) × 100 where DD represents the number of days a given species was detected during a specific phase of the day (sunrise, daylight, sunset, or night), and N is the total number of observations per daily phase across all species. We then visualized these indices using boxplots, to display the data distribution with minimum and maximum scores and median, and barplots, to illustrate the relationship between a numeric and a qualitative variable, by season (spring, summer, autumn, winter) and daily phases (sunshine, daylight, sunset, night). These graphical approaches were chosen to summarize the variation in species activity patterns over time. For consistency in temporal reference, the 15th day of each month was used as the standard midpoint for monthly grouping. In addition, we calculated the RAI for each species separately for EU habitat 2270* and for EU habitat mosaic 2230/2260. The identification of daily phases (sunrise, daylight, sunset, and night) for 2021 was based on a calendar specific to the study area (Desk Aeronautico; Time and Date AS. 1995AS. -2025)). We used the timings of sunrise and sunset to calculate the duration of each daily phase on a weekly basis. Each camera trap photograph is time-stamped, allowing us to classify occurrences into their respective daily phases. Descriptive analyses were conducted using R Statistical Software (v4.3.0; R Core Team 2023), using the "ggplot2" package (Wickham 2016) for donut chart, bar chart, and boxplot; "dplyr" (Wickham et al. 2023), "networkD3" (Gandrud et al. 2017) package for Sankey diagram.We collected a total of 2932 records of images, with 2191 records of Mammalia class (74.7% of the total) and 741 records of Aves class (25.3% of the total) in 233 days (Fig. 2A); after aggregation of repetitive images of the same individual, we detected a total of 766 individual occurrences, 586 of mammals (76.5% of the total) and 180 occurrences of birds (23.5% of the total) (Fig. 2), corresponding to7 mammal species and 13 bird species (Table S2, Suppl. Mat.).Most records and occurrences (as shown in Fig. 2) refer to mammals rather than birds, and in particular to the families Suidae (Sus scrofa, Linnaeus, 1758), Canidae (Vulpes vulpes, Linnaeus, 1758) and Felidae (Felis catus, Linnaeus, 1758); among birds, most records and occurrences concern the family Columbidae (Columba palumbus, Linnaeus, 1758).[Place Figure 2 CAM-COAST provided new fauna data for the Adriatic coast, and updated data on rare species of conservation interest, as well as problematic mammal species, for which specific conservation and management measures should be implemented within the N2K (Rovero & Zimmermann, 2016). CAM-COAST represents the first organized database related to a coastal N2K site in Italy and despite some critical gaps, such as the short time span of data collection and the small sampling area, we think that it is a first step to be implemented in the future with other data. Results may provide some important assessments for the management and conservation of EU coastal habitats. Furthermore, the database shows the potential for studying, researching, and managing species and habitats that are of conservation importance (Kissling et al., 2024). The photographic dataset can be used to train automated species recognition algorithms (e.g., convolutional neural networks) and facilitate their application in automated biodiversity monitoring, such as through camera traps or drone surveys.The dataset fills a gap in mammal-bird co-occurrence patterns and temporal activity rhythms in a coastal Mediterranean habitats, which are underrepresented in current ecological datasets. We emphasize its value for long-term ecological monitoring, conservation management within N2K and eLTER networks, and as a baseline for evaluating anthropogenic pressures and climate-driven changes in wildlife. RAI values calculated for all species (Table S4, Suppl. Mat.) showed a high relative abundance of mammal species. The most frequent was wild boar (Sus scrofa Linnaeus, 1758) (44.2 % RAI), followed by red fox (Vulpes vulpes Linnaeus, 1758) (33.5 % RAI), and domestic cat (Felis catus Linnaeus, 1758) (28.7 % RAI). Other species detected at lower frequency were the Western European hedgehog (Erinaceus europaeus Linnaeus, 1758) and the European badger (Meles meles Linnaeus, 1758).Bird species with good representativeness in the study site are common wood pigeon Columba palumbus (14.6 % RAI), the Eurasian magpie Pica pica (6.0 % RAI) and Eurasian jay Garrulus glandarius (3.4 % RAI); RAI values of these species were significantly higher than RAI of other bird species.Although with minimal relative abundances, two mammal species of EU conservation importance, the gray wolf (Canis lupus lupus Linnaeus, 1758) and the crested porcupine (Hystrix cristata Linnaeus, 1758), were also recorded, respectively with one and four occurrences. The distribution of mammals' total occurrences by seasons and daily phases are reported in Table S5 and Figure S6 (Suppl. Mat.). In terms of mammal occurrences by season, the highest rate was observed in spring (35.1 %), followed by autumn, while winter had the lowest value (4.9 %) (Fig. S6A). Mammals detected in all seasons are wild boar, common red fox, and domestic cat (Fig. S6A). Wild boar was the most observed species in spring and summer (17.9 %). The red fox was more frequent in autumn (15.1 %), while the domestic cat mainly visited the target site in spring and autumn (13.2 %).All the following descriptive data analysis was conducted exclusively for mammals. Seasonal RAI calculated per EU habitats mosaic 2230-2260 and 2270* (Table S5, Suppl. Mat.) showed statistical differences only for autumn season, with a preference for the habitats with annual vegetation and maquis (EU habitats 2230/2260) (Fig. S7, Suppl. Mat.).Concerning the daily phases, mammal occurrence was highest during the night, and subordinately in the daylight phase, while the lowest occurrence was recorded at sunrise (Table S5, Suppl. Mat.; Fig. S6B DRAI values significantly differed among seasons (Fig. S9, Suppl. Mat.). In spring, daylight had the highest value, while sunrise had the lowest. During summer, DRAI values were generally low, with a significant increase at sunset. In autumn, DRAI values were significantly higher during both daylight and night. In winter, the values remained very low, with a slight increase during daylight and night.The high number of wild boar and domestic cat occurrences may represent a threat for biodiversity conservation in the analyzed N2K site, as recorded in other natural areas (Chadwick et al., 2022). Two mammal species of EU conservation interest are to be highlighted, the gray wolf (priority species of II and IV Annexes -HD92/43/EEC) and the crested porcupine (priority species of IV Annex -HD92/43/EEC), even if they are rare. The gray wolf trophic niche is centered on available wild/domestic ungulates and Central Italy hosts one of the highest densities of wild ungulates in Europe (Apollonio et al., 2010), especially roe deer (Capreolus capreolus Linnaeus, 1758) and wild boar (Cerri et al., 2023). This latter was the most abundant species in our study area, likely attracting the wolf in this most unsuitable area (Mattioli et al., 1995, Nores et al., 2008). According to Ercole et al. (2021), the study area is located outside of the traditional Italian range of the gray wolf. However, in the last decade, an extension of the gray wolf's range toward the coastal habitats was detected (La Morgia et al., 2022). The crested porcupine is experiencing a range expansion in various Italian territories, but it was rarely detected in the coastal area (Mori et al., 2013). Climate change and the abandonment of agricultural practices have favored the colonization of residual coastal woody areas, where new records have been collected in recent years (Mori et al., 2021).As far as the most recorded species, the wild boar, it worth to note that it has been listed among the "World's Worst Invaders" (Toso & Pedrotti, 2001), because it may cause a loss of plant diversity, the damage to crops and forestry, disease transmission to livestock, and habitat changes for other species (Carpio et al., 2021;Valente et al., 2020). In Italy, in the first half of the last century, wild boars were reduced to some fragmented and small populations; conversely, in the last decades, the Italian range of the species has rapidly increased, (Boitani et al., 1994;Massei et al., 1997;Meriggi & Sacchi, 2001;Merli & Meriggi, 2006), with a high in the due to the abandonment of agricultural of areas, and increase in areas to These areas as a for the species, using these as and/or areas & 2022). The wild boar has on the of the soil due to its behavior (Mori et al., 2020), trampling (Mori et al., & 2020). This behavior the of soil and the of the which also the erosion plant plant species and may affect wildlife communities and and species et al., & et et al., in which are common in areas, wild boars damage by in of or trampling and agricultural et al., & 2020). Moreover, the continuous across different habitats the wild boar a of or of alien and plant species, which in environments et al., et al., A significant in plant species and plant species of conservation concern was observed after 20 years of a wild boar in a Mediterranean forest & 2020). Other that the of wild boar great differences in the and abundance of species in the of Mediterranean et al., et al., and in coastal in in our study area, the domestic cat was It is an and generalist et al., et al., and is considered among the threats to global biodiversity et al., et al., et al., et al., In and areas, domestic have a great on especially on birds and small mammals et al., ecological disease and et al., et al., to the the of this mammal in the area could be to the biodiversity that hosts this N2K the recognized ecological value of the site, for mammals and birds, are The CAM-COAST database provides essential data for improving our of Mediterranean coastal dunes as habitats for wildlife and the threats native

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