GPS database of 26 tagged gulls used to perform spatial and statistical analyses related to the title: “Evil and allies: opportunistic gulls as both spreaders and sentinels of antibiotic-resistant bacteria in human-transformed landscapes” [Dataset]
Human-transformed residuals, especially those derived from human waste (dumps), farmland and livestock are involved in the emergence of antibiotic-resistant bacteria (ARB) in the environment. Wildlife can act as vectors of ARB dispersal through different environments, but also as sentinels to detect...
| Autores: | , , , , , , , , , |
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| Tipo de documento: | conjunto de datos |
| Data de publicação: | 2024 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositório: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/367361 |
| Acesso em linha: | http://hdl.handle.net/10261/367361 https://doi.org/10.20350/digitalCSIC/16538 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Agriculture AMR ARB Connectivity One Heath Risk maps Wildlife Yellow-legged gull |
| Resumo: | Human-transformed residuals, especially those derived from human waste (dumps), farmland and livestock are involved in the emergence of antibiotic-resistant bacteria (ARB) in the environment. Wildlife can act as vectors of ARB dispersal through different environments, but also as sentinels to detect the early spread and determine ARB sources. The development of integrated monitoring programs focused on wildlife would help to anticipate the risks of ARB to humans and livestock. We used the yellow-legged gull (Larus michahellis) as a model species to investigate and monitor the spatial patterns of ARB dispersal across an extensive farmland region located in north-eastern Spain (Lleida). By integrating GPS tracking data and ARB clinical testing for 26 individuals within a network analysis framework, we modelled the risk of spatial pathogen spread through faeces during the bacteria-transmission latency period (16 days after sample collection). Additionally, we created a connectivity network to determine the main sources of ARB in the area, focusing on three main habitats of special risk for infection: dumps, livestock facilities and irrigation ponds. Seven individuals were infected by Escherichia coli, with one also co-infected with Listeria monocytogenes and Salmonella spp. Potential pathogen dispersal distances ranged from 1.13 km to 23.13 km from the breeding colony. Our network analyses revealed 54 main nodes (i.e., high-risk habitats recurrently visited by tracked gulls) and 1,182 links among them. Our findings revealed a high degree of connectivity between the breeding area, located in a shallow lake and nearby dumps, highlighting them as significant contributors to ARB dispersal. The integration of GPS data, pathogen testing and network analyses can shed further light on pathogen dynamics by creating spatial risk maps and identifying ARB sources. In combination with complementary molecular epidemiology techniques within a One Health framework, our approach can emerge as an important tool for monitoring ARB dynamics within highly human-transformed ecosystems. This may empower managers for the development of targeted ARB monitoring programmes and effective mitigation strategies, ultimately improving both animal and public health. |
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