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Ciucci, P.

Publications and source records attributed to Ciucci, P..

7 recordsLinked to original sources

Misleading Success: Genomes Reveal Critical Risks to European Gray Wolves

Have European gray wolves recovered? Despite an increase to [~]21,000 wolves (Canis lupus), our genomic analyses reveal significant risks to their long-term viability. We analyzed over 200 whole-genomes spanning five major European populations. Rather than a single recovering population, European wolves form a mosaic of isolated, independently evolving lineages, mostly diverging in the late Pleistocene. All lineages have contemporary effective population sizes below the threshold for long-term viability (Ne [≥] 500) and show extensive inbreeding. Runs of homozygosity reveal population-specific inbreeding histories spanning recent to deep timeframes. Most lineages exhibit higher realized than masked genetic load, indicating emerging inbreeding depression. These findings challenge claims that downlisting European wolves is biologically warranted: none of these populations currently meets thresholds associated with favorable conservation status.

evolutionary biology↗

The population structure and genetic health of European wolves

Once nearly eradicated from Europe, grey wolves (Canis lupus) have recently undergone a remarkable demographic recovery, but their long-term survival remains precarious. By analyzing 1,001 genomes, we uncover a mosaic of distinct evolutionary lineages, not a single recovering population. Northern populations exhibit Asian wolf ancestry, while southern populations preserve ancient Holocene lineages, with dog introgression varying by region. Isolated wolves from the Scandinavian, Italian, and Iberian peninsulas harbored particularly high levels of inbreeding and fixed deleterious mutations. Signatures of genome erosion were widespread across Europe, with many populations falling well short of the minimum size recommended for long-term survival. Our study reveals the complex tapestry of wolf ancestry and variation across Europe, which calls for nuanced, regional conservation plans founded in genetic monitoring.

genomics↗

Coexisting with humans: genomic and behavioural consequences in a small and isolated bear population

Climate and land use change have increased human-wildlife interactions, potentially reducing wild species density and prompting behavioural adaptations to urbanised environments. It is still debated if behavioural responses are mainly the result of phenotypic plasticity or if they were driven by anthropic selective pressures, especially in small populations. Our study focused on the Apennine brown bear population (Ursus arctos marsicanus), which has coexisted with humans in Central Italy for millennia. We characterised genomic diversity and identified adaptation signals distinctive to this population by comparing whole genome resequencing data across the Holarctic species range. We show that Apennine brown bears possess a unique genomic diversity pattern including selective signatures at genes associated with reduced aggressiveness, possibly involving alternative splicing mechanism. Our findings suggest that even in small and long-isolated populations, selection may shape behavioural traits. We hypothesise that human-induced selection has influenced these changes, reducing conflicts and contributing to the long-term persistence of the Apennine bear and its coexistence with humans.

genomics↗

Human footprint and forest disturbance reduce space use of brown bears across Europe.

Three-quarters of the planets land surface has been altered by humans, with consequences for animal ecology, movements and related ecosystem functioning. Species often occupy wide geographical ranges with contrasting human disturbance and environmental conditions, yet, limited data availability across species ranges has constrained our understanding of how human impact and resource availability jointly shape intraspecific variation of animal space use. Leveraging a unique dataset of 752 annual GPS movement trajectories from 370 brown bears (Ursus arctos) across the species range in Europe, we investigated the effects of human impact (i.e., human footprint index), resource availability, forest cover and disturbance, and area-based conservation measures on brown bear space use. We quantified space use at different spatio-temporal scales during the growing season (May - September): home range size; representing general space requirements, 10-day long-distance displacement distances, and routine 1-day displacement distances. We found large intraspecific variation in brown bear space use across all scales, which was profoundly affected by human footprint index, vegetation productivity, and recent forest disturbances creating opportunity for resource pulses. Bears occupied smaller home ranges and moved less in more anthropized landscapes and in areas of higher resource availability. Forest disturbances reduced space use while contiguous forest cover promoted longer daily movements. The amount of strictly protected and roadless areas within bear home ranges were too small to affect space use. Anthropized landscapes may hinder the expansion of small and isolated populations, such as the Apennine and Pyrenean, and obstruct population connectivity, for example between the Alpine or Carpathian with the Dinaric Pindos populations. Our findings call for actions to maintain bear movements across landscapes with high human footprint, for example by maintaining forest integrity, to support viable bear populations and their ecosystem functions.

ecology↗

Including biotic interactions in species distribution models improves the understanding of species niche: a case of study with the brown bear in Europe

Biotic interactions are expected to influence species responses to climate change, but they are usually not included when predicting future range shifts. We assessed the importance of biotic interactions to understand future consequences of climate and land use change for biodiversity using as a model system the brown bear (Ursus arctos) in Europe. By including biotic interactions using the spatial variation of energy contribution and habitat models of each food species, we showed that the use of biotic factors considerably improves our understanding of the distribution of brown bears. Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, warning about future indirect climate change effects. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future scenarios of biodiversity change, which is key for conserving biodiversity and ecosystem services.

ecology↗

Genomes of the extinct Sicilian wolf reveal a complex history of isolation and admixture with ancient dogs

The Sicilian wolf represented the only population of wolves living on a Mediterranean island until the first half of the twentieth century (1930s-1960s) 1-7. Previous studies hypothesised that they remained isolated from mainland wolves from the end of the Last Glacial Maximum (LGM) 8,9, until human persecutions led them to extinction 1-7. There are only seven known Sicilian wolf specimens from the 19th and 20th century preserved in museums in Italy and recent morphometric analyses assigned them to the new subspecies Canis lupus cristaldii 10. To better understand the origins of the Sicilian wolf, and its relationship to other wolf populations, we sequenced four whole genomes (3.8x-11.6x) and five mitogenomes. We investigated the relationship between Sicilian wolves and other modern breeds to identify potential admixture. Furthermore, considering that the last land-bridge between Sicily and Italy disappeared after the LGM 11, around 17 kya, we explored the possibility that the Sicilian wolf retained ancestry from ancient wolf and dog lineages. Additionally, we explored whether the long-term isolation might have affected the genomic diversity, inbreeding levels and genetic load of the Sicilian wolf. Our findings show that the Sicilian wolves shared most ancestry with the modern Italian wolf population but are better modelled as admixed with European dog breeds, and shared traces of Eneolithic and Bronze age European dogs. We also find signatures of severe inbreeding and low genomic diversity at population and individual levels due to long-term isolation and drift, suggesting also low effective population size.

genomics↗

From individual behavior and pack dynamics to population responses: An individual-based approach to model the wolf social life cycle

The occurrence of wolf populations in human-dominated landscapes is challenging worldwide because of conflicts with human activities. Modeling is an important tool to predict wolf dynamics and expansion, and help in decision making concerning management and conservation. However, some individual behaviors and pack dynamics of the wolf life cycle are still unclear to ecologists. Here we present an individual-based model (IBM) to project wolf populations while exploring the lesser-known processes of the wolf life cycle. IBMs are bottom-up models that simulate the fate of individuals interacting with each other, with population-level properties emerging from the individual-level simulations. IBMs are particularly adapted to represent social species such as the wolf that exhibits complex individual interactions. Our IBM predicts wolf demography including fine-scale individual behavior and pack dynamics based on up-to-date scientific literature. We explore four processes of the wolf life cycle whose consequences on population dynamics are still poorly understood: the pack dissolution following the loss of a breeder, the adoption of young dispersers by packs, the establishment of new packs through budding, and the different types of breeder replacement. While running different versions of the IBM to explore these processes, we also illustrate the modularity and flexibility of our model, an asset to model wolf populations experiencing different ecological and demographic conditions. The different parameterization of pack dissolution, territory establishment by budding, and breeder replacement processes influence the most the projections of wolf populations. As such, these processes require further field investigation to be better understood. The adoption process has a lesser impact on model predictions. Being coded in R to facilitate its understanding, we expect that our model will be used and further adapted by ecologists for their own specific applications.

ecology↗