Indicators of biodiversity in an intensively cultivated and heavily human modified landscape

Abstract Nowadays, the loss of biodiversity in agroecosystems due to the intensification of farming practices is happening very fast, and therefore, stopping or slowing it down should be a priority for conservation. To detect changes in these environmental contexts, one approach contemplates focusing on a limited set of indicator species that can alert us to ongoing changes in progress. In this research, we aimed to measure the biodiversity of vertebrates using a multi-taxa approach in an intensively cultivated and highly inhabited area located in northern Italy. We investigated the relationships between biodiversity and environmental characteristics and we identified the taxonomic groups that can be used as indicators of biodiversity. Data collection was carried out in 2016 with different methods depending on the taxonomic group, in 131 sampling units chosen using a Tessellation Stratified Sampling. Then we calculated for each sampling unit a standardized Biodiversity Index, which was related to environmental variables concerning the land use and the landscape configuration using Multiple Linear Regression Analysis and Information-Theoretic approach. We used correlation analyses and the Indicator Species Analysis (IndVal) to identify the taxonomic groups and species that can be used as indicators of biodiversity. Biodiversity was positively related to the number of patches of natural vegetation, whereas it was negatively affected by the number of patches of artificial surfaces and by habitat diversity. Our findings agree with those obtained by many other researchers, which pointed out that agroecosystems provide adequate shelters, suitable foraging habitats and nesting sites. The negative effect of habitat diversity was explained by the area-heterogeneity trade-off. Therefore, sites with high heterogeneity will not contain enough cover of residual natural vegetation, essential to maintain high biodiversity, because increasing compositional heterogeneity within a fixed area simultaneously reduces the surface of each cover type. The analyses showed that birds and reptiles might be used as biodiversity indicators of vertebrates. Eurasian Magpie and Green Whip Snake, both generalist species, were associated with sites of low biodiversity, whereas seven birds, both generalists and farmland specialists, were associated with sites of medium biodiversity. In high biodiversity sites there were not indicator species. To conclude, in less natural environments, such as urban and agricultural landscapes, a combination of specialist and generalist indicator species seems adequate to monitor biodiversity changes. Our findings increase the knowledge of these very dynamic ecosystems, being important both to plan strategies for biodiversity conservation and to guarantee ecosystems services useful for humans

First assessment of habitat suitability and connectivity for the golden jackal in north-eastern Italy

AbstractCompared with the rapid expansion across Europe, the golden jackal colonization of Italy is still limited and slow. No study focused on the habitat selection or landscape connectivity for this species was performed in Italy; thus, the potential distribution and dispersal patterns in the country remain unknown. Our objectives were to evaluate the suitability of the Friuli-Venezia Giulia region (north-eastern Italy) for the golden jackal, as well as to identify the ecological corridors connecting the areas currently occupied by the species. Corridors modelling allowed us both to hypothesize the dispersal dynamics occurring in the study region and to identify possible obstacles to future range expansion. We surveyed golden jackal presence in two study areas, covering an area of 500 km2, from March 2017 to February 2018. Using collected data, we modelled the species home-range scale habitat suitability based on an ensemble modelling approach. Subsequently, a habitat suitability prediction at a finer scale was used to estimate landscape resistance, starting from which, we modelled dispersal corridors among areas currently occupied by the species using a factorial least cost path and a cumulative resistant kernel approach. Our results indicated a moderate potential for large parts of the study region to support the occurrence of golden jackal family groups, whose presence seems to be mainly driven by the presence of wide areas covered by broadleaved forests and shrublands and by the absence of wide intensive agricultural areas. The predicted connectivity networks showed that three main permeable corridors are likely to connect golden jackal occurrence areas within the study region, while all the other corridors are characterized by a very low path density. Both the habitat selection and connectivity analyses showed a strong negative impact of the intensive cultivated plain on species stable presence and movement providing critical information for the conservation of the golden jackal in Italy

Changes in Wolf Occupancy and Feeding Habits in the Northern Apennines: Results of Long-Term Predator–Prey Monitoring

The comprehension of the factors that have influenced the recent changes in wolf (Canis lupus) range and diet that have occurred in our study area, characterized by a highly heterogeneous landscape, can shed light on their current process of expansion toward the plain. Wolf presence was monitored using a standardized protocol from 2007 to 2022 by carrying out eight monitoring sessions organized in seasonal surveys, during which, we collected wolf presence data. To model wolf range dynamics, we used dynamic occupancy models considering land cover types and wild ungulate abundances as covariates. Moreover, we studied the wolf diet through scat analysis, identifying the consumed items from undigested remains. Wolf occupancy in the study area progressed from mountains to lower hills gradually; the observed range dynamics were driven by prey abundance and human presence: in particular, the probability of colonization increased with roe deer (Capreolus capreolus) abundance, whereas the probability of extinction increased with urban areas. The wolf diet showed a gradual shift from the prevalent consumption of wild boar (2007–2008 and 2011–2012) to the prevalent consumption of roe deer (continuously increasing from 2015 onward). Our results might be related to a specific adaptation of the predator to the local ecology of the most consumed species: the roe deer

Behind wolf predation on wild ungulates: environmental factors influencing the distribution of kill sites in Northern Italy

Predation is a hierarchical process whereby predators are constrained to kill prey within the area they select while hunting. Therefore kill sites are not randomly distributed, rather where kill sites occur is a function of prey distribution and predictability and environmental factors that influence prey detection, access, or the success of an attack [1]. Wolves (Canis lupus) are considered generalist apex predators, preying mainly on wild ungulates. Being socially organized in packs, usually consisting of the breeding pair and their offspring, wolves roam within their exclusive territory and cooperate during the hunt. Wolves are well adapted for cursorial predation with chases ranging from 100 m to more than 5 km [2]. The aim of this research is to identify the main environmental factors influencing the distribution of wolf kill sites, so at the same time determine which factors influenced the vulnerability of prey once the hunt began. The study was carried out in Liguria (5343 km2 region in Northern Italy; Fig. 1) The wild ungulate community includes the wild boar (Sus scrofa) and the roe deer (Capreolus capreolus), widely distributed with high densities, the fallow deer (Dama dama) and the chamois (Rupicapra rupicapra) more localized. Moreover, the red deer (Cervus elaphus) has a sporadic presence along the boundaries of the region. Wolves reached the Ligurian Apennines in the late 1980s (the first illegally killed wolf was found in 1990) and the Ligurian Alps in the late 1990s (the first illegally killed wolf was found in 1997). The most recent research estimated the presence of minimum five wolf packs by non-invasive genetic sampling [3]. Using data collected through a monitoring project carried out between 2007-2014 [3], we delineated wolf range using the sampled wolf genotypes by a fixed kernel estimator. We considered all claimed and verified cases of wolf predation upon wild ungulates recorded during 2007-2016, reporting the preyed species and possibly some related information (sex, age, proportion of consumption). Around each kill site we defined a buffer corresponding to the potential hunting area of wolves. We used a width of 13 km, corresponding to the average travel distance of wolves during the night to go from dens or resting sites to hunting sites in Italy [4]. We compared the plots where kill sites were recorded and an equal number of random plots within the estimated wolf range. We formulated a habitat suitability model following an approach presence vs. availability by binary logistic regression analysis (BLRA, forward stepwise method); we tested the hypothesis that wolf choice of kill sites is influenced by the morphology and the land use of the area. In each plot, we measured from the Corine Land Cover III level and the Digital Elevation Models (DEM) the environmental variables used as covariates: four slope classes (range between 0° and >60°), road density, path density, forests (broad-leaved, coniferous, and mixed forests), urban and cultivated areas, scrublands, open areas (pastures and grasslands), and bare ground (rocks and areas with little or no vegetation cover). We considered even two-way interactions between covariates. We tested the model performance by the percentage of correct classifications of original cases, Nagelkerke’s R2, and receiver operating characteristic (ROC) curve analysis. We identified 74 distinct wolf genotypes, corresponding to 189 non-invasive DNA samples (98% faeces, 1% urines and 1% hairs), collected in the study area from 2007 to 2014. Wolf range had a total extent of 5068 km2. We mapped and digitized 62 wolf kill sites; among the preyed wild ungulates, we identified 23 roe deer, 18 fallow deer, 16 wild boars, and 5 chamois (Fig. 1). BLRA showed a negative effect of the road density, the urban areas, the mixed forests, and the medium slopes (20-40°), a positive effect of steep slopes (>60°), open areas, and bare ground, the latter without statistical significance (Tab. 1). The logistic model explained 56.4% of the variance of the response variable and correctly classified 78.2% of original cases, 82.3% of kill sites and 74.2% of control ones. The area under the ROC curve was significantly greater than that of a model that randomly classifies the cases (AUC=0.883±0.029; P<0.001). Wolves kill sites in Liguria were steep, open habitats (pastures and grasslands) far from roads and urban areas. Wolves tend to avoid areas with high road and human settlement densities, as they may be barriers to wolf movements and a cause of direct mortality both from vehicle collisions and illegal killing. Moreover, human disturbance associated with roads and urban areas may deter or interfere with wolves when attempting to kill prey, or afterward during carcass consumption. Wolves seemed to select steep slopes, probably because they may find a suitable habitat in terms of advantage during hunting activities. We found that hiding-cover levels were lower at kill sites than at random sites. Indeed, dense cover can affect the prey capacity to exploit refuges, thus enhance its chances of escaping an attack, and can increase the chance of detection the predator, 394 because of its noisier approach. From the predator point of view, in open habitats prey were easier to locate and catch. Wild ungulates mainly use open habitats during the night as feeding areas, because of the higher quality resources, and more closed habitats during the day, with less forage but a higher degree of shelter. Wild ungulates have to face a constant trade-off between the choice of better food patches and predation risk. This trade-off is mediated by the vigilance behaviour, which requires exclusive visual attention to scan the environment, thereby interrupting or slowing down foraging activity. Wolves usually take advantage of this wavering behaviour to start the rush. Moreover, wolves are mainly active from dawn to dusk and this is probably closely related to their hunting pattern, which matches with the activity patterns of wild ungulates. Overall, the environmental factors of the kill sites identified in this study are consistent with the cursorial hunting strategy of wolves

Wolf predation on wild ungulates: How slope and habitat cover influence the localization of kill sites

Based on data collected along the Ligurian Apennines and Alps (N-W Italy), we analysed the main environmental and human-related factors influencing the distribution of kill sites of the wolf Canis lupus. We mapped and digitized 62 kill sites collected during 2007-2016. Around each kill site, we defined a buffer corresponding to the potential hunting area of wolves. We compared kill site plots and an equal number of random plots. We formulated a model of kill site distribution following an approach presence versus availability by binary logistic regression analysis; we tested the hypothesis that wolf choice of kill sites is influenced by the physiography and the land use of the area. Among the preyed wild ungulates, we identified 23 roe deer Capreolus capreolus, 18 fallow deer Dama dama, 16 wild boars Sus scrofa, and 5 chamois Rupicapra rupicapra. Binary logistic regression analysis showed a negative effect of the road density, the urban areas, the mixed forests, and a positive effect of steep slopes and open habitats. Prey are more vulnerable to predators under certain conditions and predators are capable of selecting for these conditions. Wolves achieved this by selecting particular habitats in which to kill their prey: they preferred steep, open habitats far from human presence, where wild ungulates are more easily detectable and chasable

Wolves and wild ungulates in the Ligurian Alps (Western Italy): prey selection and spatial-temporal interactions

We propose the integration of different noninvasive sampling methods to the study of predator-prey interactions. We analyzed the diet of the wolf (Canis lupus) to point out its elective prey and we investigated its spatial and temporal interactions with prey species from December 2012 to November 2014 in the Ligurian Alps (Southern Alps, Italy). In this area, the wolf is the only large predator, and there is a rich wild ungulate community consisting of four species. Our analyses showed that the most consumed species by wolves were the wild boar (Sus scrofa) and the roe deer (Capreolus capreolus). To successfully hunt these species, wolves need to share their spatial range, searching for them in the most suitable habitat types and in the periods of the diel cycle during which they are mainly active. Fallow deer (Dama dama) and chamois (Rupicapra rupicapra) consumption was low, and wolves showed also relatively low overlap with these species. Our results suggest that wolves might be firstly specialized on wild boar predation, as they showed substantial spatial and temporal overlap with this species, and secondly on roe deer predation, especially during the denning season when they probably take advantage of the presence of fawns

Combining ensemble models and connectivity analyses to predict wolf expected dispersal routes through a lowland corridor.

The Italian wolf (Canis lupus italicus) population has remained isolated South of the Alps for the last few thousand years. After a strong decline, the species has recolonized the Apennines and the Western Alps, while it is currently struggling to colonize the Eastern Alps. Recently, the species was detected in a lowland park connecting the Northern Apennines to the Central Alps. If the park was able to sustain a net wolf dispersal flow, this could significantly boost the connection with the Eastern Alps and the Dinaric-Balkan population. We investigated the suitability of the park as a functional ecological corridor for the wolf through the unhospitable lowland of Northern Italy. We collected wolf occurrence data in two study areas. We modeled species distribution running a separate ensemble model for each study area and then merging the output of the models to obtain an integrated suitability map. We used this map to identify corridors for the wolf adopting a factorial least-cost path and a cumulative resistant kernel approach. The connectivity models showed that only two corridors exist in the lowland areas between the Northern Apennines and the Central Alps. The Western corridor is a blind route, while the eastern corridor passes through the park and has a continuous course. However, the models also revealed a scarce resilience of corridor connectivity in the passageways between the park and the Apennines and the Prealps, which suggests that urgent management actions are necessary to ensure the future functionality of this important corridor

Hide-and-Seek in a Highly Human-Dominated Landscape: Insights into Movement Patterns and Selection of Resting Sites of Rehabilitated Wolves (<i>Canis lupus</i>) in Northern Italy

Assessing the behavioural responses of floating wolves to human presence is crucial for investigating the chance of wolf populations expanding into urbanised landscapes. We studied the movement ecology of three rehabilitated wolves in a highly human-dominated landscape (Po Plain, Italy) to explore wolf’s plasticity amid widespread human pressure. To reach this aim, we estimated individual 95% utilisation distributions (UD) after the release and inspected both 95% UDs and net squared displacements to identify individual movement patterns; tested for differences in movement patterns during day and night; and analysed the selection of resting sites during dispersal movement in a highly human-altered environment. Both the 95% UDs and step lengths were smaller for wolves settling in suitable areas than for those settling in more urbanised areas. All wolves exhibited strong temporal segregation with humans during all movement phases, particularly while dispersing across highly urbanised areas. Main roads and proximity to built-up areas were shown to limit wolves’ dispersal, whereas small-wooded patches that provide shelter during rest facilitated long-distance movements. This study provides important insights into wolf movement and settling in urban and peri-urban areas, providing critical knowledge to promote human–carnivore coexistence

Niche partitioning between sympatric wild canids: the case of the golden jackal (Canis aureus) and the red fox (Vulpes vulpes) in north-eastern Italy

none6noBackground: Two coexisting species with similar ecological requirements avoid or reduce competition by changing the extent of their use of a given resource. Numerous coexistence mechanisms have been proposed, but species interactions can also be aggressive; thus, generally a subordinate species modifies its realized niche to limit the probability of direct encounters with the dominant species. We studied niche partitioning between two sympatric wild canids in north-eastern Italy: the golden jackal and the red fox, which, based on competition theories, have a high potential for competition. We considered four main niche dimensions: space, habitat, time, and diet. Results: We investigated three study areas monitoring target species populations from March 2017 to November 2018 using non-invasive monitoring techniques. Red fox presence was ascertained in every study area, while golden jackal presence was not ascertained in one study area, where we collected data regarding wolf presence. Considering the two target species, we observed partial diet partitioning based on prey size, with the golden jackal mainly feeding on wild ungulates and the red fox mainly feeding on small mammals. The two canids had an extensive temporal overlap along the diel cycle, having both predominant crepuscular and nocturnal activity patterns, but marked spatial partitioning and differential use of habitats. The golden jackal proved to be specialist concerning the habitat dimension, while the red fox resulted completely generalist: the former selected less human-modified habitats and avoided intensively cultivated lands, while the latter was present in all habitats, including intensively cultivated lands. Conclusions: The observed partitioning might be due partially to some ecological adaptations (e.g. specialist vs. generalist use of resources) and specific behaviours (e.g. cooperative vs. solitary hunting) and partially to the avoidance response of the red fox aimed at reducing the probability of direct encounters with the golden jackal.openTorretta, Elisa; Riboldi, Luca; Costa, Elena; Delfoco, Claudio; Frignani, Erica; Meriggi, AlbertoTorretta, Elisa; Riboldi, Luca; Costa, Elena; Delfoco, Claudio; Frignani, Erica; Meriggi, Albert

NUMERICAL MODEL FOR CHELATING AGENTS ENHANCED SOIL FLUSHING

“In situ” remediation technologies, if applied without careful evaluation of the process parameters, may themselves be a source of pollution. The soil flushing is a useful technology for in situ remediation of a heavy metal contaminated soil and is particularly effective when the washing solution is added with a chelating agent such as EDTA. Excessive use of chelating agent may, however, be harmful to the environment for several reasons: the chelating solution, if incompletely intercepted by extraction wells, can reach the water table; an excessive concentration of chelator can damage soil structure and finally the metal transported by the chelating solution can be reabsorbed into the deeper layers of the soil. This paper presents the results of a soil flushing treatment with a EDTA solution carried out on an experimental soil column that consists of a surface layer contaminated with lead and a not contaminated deeper layer. The purpose of the study is to determine whether a part of the metal contained into the superficial contaminated soil can be transferred, by the chelating solution, in the uncontaminated soil; furthermore the concentration of the chelating agent and the volume of the solution that minimizes the risk for the soil are determined by 1D model that simulates the chelation process. The experimental results confirm the possibility that a small amount of metal can be transferred and absorbed into the not contaminated soil. Operationally this information can be used to define the correct positioning of the extraction wells used in the soil flushing; at the same simulation model can be used to determine the concentration and volume of chelating solution that optimize the treatment