Philippa Kaur

The pesticide hexachlorocyclohexane (HCH) is a toxic and persistent contaminant in the environment. Some bacteria and fungi can degrade HCH and its isomers under laboratory conditions. However, in heterogeneous environments, where many different factors are at play, the biodegradation capacity is challenged by the availability of nutrients to support degraders’ growth. As opposed to bacteria, fungi are more adapted to heterogeneous habitats, and in some cases mycelial fungi can facilitate the transport of organic substrates throughout the mycosphere, increasing their availability to promote bacterial contaminant biodegradation. However, how this occurs is not entirely understood. In this study, Khan et al. demonstrate that mycelial nutrients transferred from nutrient-rich to nutrient-deprived habitats promote co-metabolic degradation of HCH by bacteria. The authors incubated a non-HCH-degrading fungus (Fusarium equiseti K3) and a co-metabolically HCH-degrading bacterium (Sphingobium sp. S8) in a structured model ecosystem. Results from 13C isotope labelling and metaproteomics showed that fungal 13C was incorporated into bacterial proteins responsible for HCH degradation, thus illustrating the importance of synergistic fungal–bacterial interactions for contaminant biodegradation in nutrient-poor environments. More

UNDESA. World urbanization prospects. Demographic Research 12, 1–103 (2018).Oke, C. et al. Cities should respond to the biodiversity extinction crisis. npj Urban Sustain. 1, 11 (2021).Article 

Google Scholar 
World Bank. A catalogue of nature-based solutions for urban resilience. www.worldbank.org (2021).Elmqvist, T. et al. Benefits of restoring ecosystem services in urban areas. Curr. Opin. Environ. Sustain. 14, 101–108 (2015).Article 

Google Scholar 
Aerts, R., Honnay, O. & Van Nieuwenhuyse, A. Biodiversity and human health: Mechanisms and evidence of the positive health effects of diversity in nature and green spaces. Br. Med. Bull. 127, 5–22 (2018).Article 

Google Scholar 
Reyes-Riveros, R. et al. Linking public urban green spaces and human well-being: A systematic review. Urban For. Urban Green 61, 127105 (2021).Article 

Google Scholar 
Bardgett, R. D. & Van Der Putten, W. H. Belowground biodiversity and ecosystem functioning. Nature 515, 505–511 (2014).Article 
CAS 

Google Scholar 
Mehring, A. S. & Levin, L. A. Potential roles of soil fauna in improving the efficiency of rain gardens used as natural stormwater treatment systems. J. Appl. Ecol. 52, 1445–1454 (2015).Article 

Google Scholar 
Brevik, E. C. et al. Soil and human health: current status and future needs. Air, Soil Water Res. 13, 1–23 (2020).Article 

Google Scholar 
Silver, W. L., Perez, T., Mayer, A. & Jones, A. R. The role of soil in the contribution of food and feed. Philos. Trans. R. Soc. B Biol. Sci. 376, 20200181 (2021).Article 
CAS 

Google Scholar 
De Deyn, G. B. & Kooistra, L. The role of soils in habitat creation, maintenance and restoration. Philos. Trans. R. Soc. B Biol. Sci. 376, 20200170 (2021).Article 

Google Scholar 
Samaddar, S. et al. Role of soil in the regulation of human and plant pathogens: Soils’ contributions to people. Philos. Trans. R. Soc. B Biol. Sci. 376, 20200179 (2021).Article 

Google Scholar 
Thiele-Bruhn, S. The role of soils in provision of genetic, medicinal and biochemical resources. Philos. Trans. R. Soc. B Biol. Sci. 376, 20200183 (2021).Article 
CAS 

Google Scholar 
O’Riordan, R., Davies, J., Stevens, C., Quinton, J. N. & Boyko, C. The ecosystem services of urban soils: A review. Geoderma 395, 115076 (2021).Article 

Google Scholar 
Banerjee, S. & Heijden, M. G. A. Soil microbiomes and one health. Nat. Rev. Microbiol. https://doi.org/10.1038/s41579-022-00779-w (2022).Schmidt, D. J. et al. Urbanization erodes ectomycorrhizal fungal diversity and may cause microbial communities to converge. Nat. Ecol. Evol. 1, 0123 (2017).Article 

Google Scholar 
Geisen, S., Wall, D. H. & van der Putten, W. H. Challenges and opportunities for soil biodiversity in the Anthropocene. Curr. Biol. 29, R1036–R1044 (2019).Article 
CAS 

Google Scholar 
Fenoglio, M. S., Rossetti, M. R. & Videla, M. Negative effects of urbanization on terrestrial arthropod communities: A meta-analysis. Glob. Ecol. Biogeogr. 29, 1412–1429 (2020).Article 

Google Scholar 
Guilland, C., Maron, P. A., Damas, O. & Ranjard, L. Biodiversity of urban soils for sustainable cities. Environ. Chem. Lett. 16, 1267–1282 (2018).Article 
CAS 

Google Scholar 
Milano, V. et al. The effect of urban park landscapes on soil Collembola diversity: A Mediterranean case study. Landsc. Urban Plan. 180, 135–147 (2018).Article 

Google Scholar 
Merckx, T. et al. Body-size shifts in aquatic and terrestrial urban communities. Nature 558, 113–116 (2018).Article 
CAS 

Google Scholar 
Zhu, Y. G. et al. Soil biota, antimicrobial resistance and planetary health. Environ. Int. 131, 105059 (2019).Article 

Google Scholar 
Guerra, C. A. et al. Tracking, targeting, and conserving soil biodiversity: A monitoring and indicator system can inform policy. Science 371, 239–241 (2021).Article 
CAS 

Google Scholar 
Ramirez, K. S. et al. Biogeographic patterns in below-ground diversity in New York City’s Central Park are similar to those observed globally. Proc. R. Soc. B Biol. Sci. 281, 20141988 (2014).Article 

Google Scholar 
Delgado-Baquerizo, M. et al. Global homogenization of the structure and function in the soil microbiome of urban greenspaces. Sci. Adv. 7, eabg5809 (2021).Article 
CAS 

Google Scholar 
Braaker, S., Ghazoul, J., Obrist, M. K. & Moretti, M. Habitat connectivity shapes urban arthropod communities: the key role of green roofs. Ecology 95, 1010–1021 (2014).Article 
CAS 

Google Scholar 
Lin, B. B., Philpott, S. M. & Jha, S. The future of urban agriculture and biodiversity-ecosystem services: Challenges and next steps. Basic Appl. Ecol. 16, 189–201 (2015).Article 

Google Scholar 
Baruch, Z. et al. Increased plant species richness associates with greater soil bacterial diversity in urban green spaces. Environ. Res. 196, 110425 (2021).Article 
CAS 

Google Scholar 
Robinson, J. M. et al. Vertical stratification in urban green space aerobiomes. Environ. Health Perspect. 128, 1–12 (2020).Article 

Google Scholar 
Robinson, J. M. et al. Exposure to airborne bacteria depends upon vertical stratification and vegetation complexity. Sci. Rep. 11, 9516 (2021).Article 
CAS 

Google Scholar 
Nugent, A. & Allison, S. D. A framework for soil microbial ecology in urban ecosystems. Ecosphere 13, 1–20 (2022).Article 

Google Scholar 
Knop, E. Biotic homogenization of three insect groups due to urbanization. Glob. Chang. Biol. 22, 228–236 (2016).Article 

Google Scholar 
Li, X. et al. Management effects on soil nematode abundance differ among functional groups and land-use types at a global scale. J. Anim. Ecol. 91, 1770–1780 (2022).Article 

Google Scholar 
McKinney, M. L. Effects of urbanization on species richness: A review of plants and animals. Urban Ecosyst. 11, 161–176 (2008).Article 

Google Scholar 
Piano, E. et al. Urbanization drives cross-taxon declines in abundance and diversity at multiple spatial scales. Glob. Chang. Biol. 26, 1196–1211 (2020).Article 

Google Scholar 
Joimel, S. et al. Contrasting homogenization patterns of plant and collembolan communities in urban vegetable gardens. Urban Ecosyst. 22, 553–566 (2019).Article 

Google Scholar 
Ge, B., Mehring, A. S. & Levin, L. A. Urbanization alters belowground invertebrate community structure in semi-arid regions: A comparison of lawns, biofilters and sage scrub. Landsc. Urban Plan. 192, 103664 (2019).Article 

Google Scholar 
Tóth, Z. & Hornung, E. Taxonomic and functional response of millipedes (Diplopoda) to urban soil disturbance in a metropolitan area. Insects 11, 25 (2020).Article 

Google Scholar 
Selhorst, A. & Lal, R. Net carbon sequestration potential and emissions in home lawn turfgrasses of the United States. Environ. Manage. 51, 198–208 (2013).Article 

Google Scholar 
Cividini, S. & Montesanto, G. Aggregative behavior and intraspecific communication mediated by substrate-borne vibrations in terrestrial arthropods: An exploratory study in two species of woodlice. Behav. Process. 157, 422–430 (2018).Article 

Google Scholar 
Bray, N., Thompson, G. L., Fahey, T., Kao-Kniffin, J. & Wickings, K. Soil macroinvertebrates alter the fate of root and rhizosphere carbon and nitrogen in a turfgrass lawn. Soil Biol. Biochem. 148, 107903 (2020).Article 
CAS 

Google Scholar 
Barthod, J., Dignac, M. F. & Rumpel, C. Effect of decomposition products produced in the presence or absence of epigeic earthworms and minerals on soil carbon stabilization. Soil Biol. Biochem. 160, 108308 (2021).Article 
CAS 

Google Scholar 
Aquino, R. S. S. et al. Filamentous fungi vectored by ants (Hymenoptera: Formicidae) in a public hospital in north-eastern Brazil. J. Hosp. Infect. 83, 200–204 (2013).Article 
CAS 

Google Scholar 
Hodges, M. N. & McKinney, M. L. Urbanization impacts on land snail community composition. Urban Ecosyst. 21, 721–735 (2018).Article 

Google Scholar 
Saeki, I., Niwa, S., Osada, N., Azuma, W. & Hiura, T. Contrasting effects of urbanization on arboreal and ground-dwelling land snails: role of trophic interactions and habitat fragmentation. Urban Ecosyst. 23, 603–614 (2020).Article 

Google Scholar 
Buczkowski, G. & Bertelsmeier, C. Invasive termites in a changing climate: A global perspective. Ecol. Evol. 7, 974–985 (2017).Article 

Google Scholar 
Ford, A. E. S., Graham, H. & White, P. C. L. Integrating human and ecosystem health through ecosystem services frameworks. Ecohealth 12, 660–671 (2015).Article 

Google Scholar 
Wall, D. H., Nielsen, U. N. & Six, J. Soil biodiversity and human health. Nature 528, 69–76 (2015).Article 
CAS 

Google Scholar 
Wei, Z. et al. Initial soil microbiome composition and functioning predetermine future plant health. Sci. Adv. 5, 1–12 (2019).Article 

Google Scholar 
Song, C., Jin, K. & Raaijmakers, J. M. Designing a home for beneficial plant microbiomes. Curr. Opin. Plant Biol. 62, 102025 (2021).Article 
CAS 

Google Scholar 
Neiderud, C. J. How urbanization affects the epidemiology of emerging infectious diseases. African J. Disabil. 5, 27060 (2015).
Google Scholar 
Liddicoat, C. et al. Can bacterial indicators of a grassy woodland restoration inform ecosystem assessment and microbiota-mediated human health? Environ. Int. 129, 105–117 (2019).Article 

Google Scholar 
Baumgardner, D. J. Soil-related bacterial and fungal infections. J. Am. Board Fam. Med. 25, 734–744 (2012).Article 

Google Scholar 
Khan, N. A. Acanthamoeba: Biology and increasing importance in human health. FEMS Microbiol. Rev. 30, 564–595 (2006).Article 

Google Scholar 
Lindsay, R. G., Watters, G., Johnson, R., Ormonde, S. E. & Snibson, G. R. Acanthamoeba keratitis and contact lens wear. Clin. Exp. Optom. 90, 351–360 (2007).Article 

Google Scholar 
Fields, Barry, Robert, Benson & Besser, R. Legionella and Legionnaires’ Disease: 25 Years of Investigation – Comparative study of selective media for isolation of Legionella pneumophila from potable water. Clin. Microbiol. Rev. 15, 506 (2002).Article 

Google Scholar 
Van Elsas, J. D. et al. Microbial diversity determines the invasion of soil by a bacterial pathogen. Proc. Natl. Acad. Sci. USA 109, 1159–1164 (2012).Article 

Google Scholar 
Chen, X. D. et al. Soil biodiversity and biogeochemical function in managed ecosystems. Soil Res. 58, 1–20 (2019).Article 

Google Scholar 
Hernando-Amado, S., Coque, T. M., Baquero, F. & Martínez, J. L. Defining and combating antibiotic resistance from One Health and Global Health perspectives. Nat. Microbiol. 4, 1432–1442 (2019).Article 
CAS 

Google Scholar 
Wang, F. H. et al. High throughput profiling of antibiotic resistance genes in urban park soils with reclaimed water irrigation. Environ. Sci. Technol. 48, 9079–9085 (2014).Article 
CAS 

Google Scholar 
Cave, R., Cole, J. & Mkrtchyan, H. V. Surveillance and prevalence of antimicrobial resistant bacteria from public settings within urban built environments: Challenges and opportunities for hygiene and infection control. Environ. Int. 157, 106836 (2021).Article 
CAS 

Google Scholar 
Alharbi, J. S., Alawadhi, Q. & Leather, S. R. Monomorium ant is a carrier for pathogenic and potentially pathogenic bacteria. BMC Res. Notes 12, 230 (2019).Article 

Google Scholar 
Guimaraes, A. J., Gomes, K. X., Cortines, J. R., Peralta, J. M. & Peralta, R. H. S. Acanthamoeba spp. as a universal host for pathogenic microorganisms: One bridge from environment to host virulence. Microbiol. Res. 193, 30–38 (2016).Article 

Google Scholar 
Vieira, A., Ramesh, A., Seddon, A. M. & Karlyshev, A. V. CmeABC multidrug efflux pump promotes Campylobacter jejuni survival and multiplication in Acanthamoeba polyphaga. Appl. Environ. Microbiol. 83, 1–13 (2017).Article 

Google Scholar 
Wyres, K. L. & Holt, K. E. Klebsiella pneumoniae as a key trafficker of drug resistance genes from environmental to clinically important bacteria. Curr. Opin. Microbiol. 45, 131–139 (2018).Article 
CAS 

Google Scholar 
Holt, K. E. et al. Genomic analysis of diversity, population structure, virulence, and antimicrobial resistance in Klebsiella pneumoniae, an urgent threat to public health. Proc. Natl. Acad. Sci. USA 112, E3574–E3581 (2015).Article 
CAS 

Google Scholar 
Bethony, J. et al. Soil-transmitted helminth infections: ascariasis, trichuriasis, and hookworm. Lancet 367, 1521–1532 (2006).Pullan, R. L., Smith, J. L., Jasrasaria, R. & Brooker, S. J. Global numbers of infection and disease burden of soil-transmitted helminth infections in 2010. Parasites and Vectors 7, 1–19 (2014).Article 

Google Scholar 
Kemp, S. F. et al. Expanding habitat of the imported fire ant (Solenopsis invicta): A public health concern. J. Allergy Clin. Immunol. 105, 683–691 (2000).Article 
CAS 

Google Scholar 
Estrada-Peña, A. & Jongejan, F. Ticks feeding on humans: a review of records on human-biting Ixodoidea with special reference to pathogen transmission Climate, niche, ticks, and models: what they are and how we should interpret them. Exp. Appl. Acarol. 23, 685–715 (1999).Article 

Google Scholar 
Nasir, S., Akram, W., Khan, R. R., Arshad, M. & Nasir, I. Paederusbeetles: The agent of human dermatitis. J. Venom. Anim. Toxins Incl. Trop. Dis. 21, 1–6 (2015).Article 

Google Scholar 
Santos, M. N. Research on termites in urban areas: approaches and gaps. https://doi.org/10.1007/s11252-020-00944-0 (2020).National Academies of Sciences, Engineering, and M. Advancing urban sustainability in China and the United States. (The National Academies Press, https://doi.org/10.17226/25794 2020).Crowther, T. W. et al. The global soil community and its influence on biogeochemistry. Science 365, eaav0550 (2019).Article 
CAS 

Google Scholar 
Velasco, E., Segovia, E., Choong, A. M. F., Lim, B. K. Y. & Vargas, R. Carbon dioxide dynamics in a residential lawn of a tropical city. J. Environ. Manage. 280, 111752 (2021).Article 
CAS 

Google Scholar 
Thakur, M. P. & Geisen, S. Trophic regulations of the soil microbiome. Trends Microbiol. 27, 771–780 (2019).Article 
CAS 

Google Scholar 
Delgado-Baquerizo, M. et al. Multiple elements of soil biodiversity drive ecosystem functions across biomes. Nat. Ecol. Evol. 4, 210–220 (2020).Article 

Google Scholar 
Jiao, S., Lu, Y. & Wei, G. Soil multitrophic network complexity enhances the link between biodiversity and multifunctionality in agricultural systems. Glob. Chang. Biol. 28, 140–153 (2022).Article 
CAS 

Google Scholar 
Hu, J. et al. Rhizosphere microbiome functional diversity and pathogen invasion resistance build up during plant development. Environ. Microbiol. 22, 5005–5018 (2020).Article 

Google Scholar 
Jayaraman, S. et al. Disease-suppressive soils—beyond food production: a critical review. J. Soil Sci. Plant Nutr. 21, 1437–1465 (2021).Article 

Google Scholar 
Chen, Q. L. et al. Loss of soil microbial diversity exacerbates spread of antibiotic resistance. Soil Ecol. Lett. 1, 3–13 (2019).Article 

Google Scholar 
Innocenti, G. & Sabatini, M. A. Collembola and plant pathogenic, antagonistic and arbuscular mycorrhizal fungi: a review. Bull. Insectology 71, 71–76 (2018).
Google Scholar 
Jones, M. S. et al. Organic farms conserve a dung beetle species capable of disrupting fly vectors of foodborne pathogens. Biol. Control 137, 104020 (2019).Huang, K. et al. Elimination of antibiotic resistance genes and human pathogenic bacteria by earthworms during vermicomposting of dewatered sludge by metagenomic analysis. Bioresour. Technol. 297, 122451 (2020).Article 
CAS 

Google Scholar 
Li, G., Sun, G. X., Ren, Y., Luo, X. S. & Zhu, Y. G. Urban soil and human health: a review. Eur. J. Soil Sci. 69, 196–215 (2018).Article 

Google Scholar 
Cachada, A., Pato, P., Rocha-Santos, T., da Silva, E. F. & Duarte, A. C. Levels, sources and potential human health risks of organic pollutants in urban soils. Sci. Total Environ. 430, 184–192 (2012).Article 
CAS 

Google Scholar 
Chen, M. et al. Bioremediation of soils contaminated with polycyclic aromatic hydrocarbons, petroleum, pesticides, chlorophenols, and heavy metals by composting: Applications, microbes and future research needs. Biotechnol. Adv. 33, 745–755 (2015).Article 
CAS 

Google Scholar 
González Henao, S. & Ghneim-Herrera, T. Heavy metals in soils and the remediation potential of bacteria associated With the plant microbiome. Front. Environ. Sci. 9, 1–17 (2021).Article 

Google Scholar 
Meynet, P. et al. Effect of activated carbon amendment on bacterial community structure and functions in a PAH impacted urban soil. Environ. Sci. Technol. 46, 5057–5066 (2012).Article 
CAS 

Google Scholar 
Xiong, W., Delgado-Baquerizo, M., Shen, Q. & Geisen, S. Pedogenesis shapes predator-prey relationships within soil microbiomes. Sci. Total Environ. 828, 154405 (2022).Article 
CAS 

Google Scholar 
Duan, G. et al. Interactions among soil biota and their applications in synergistic bioremediation of heavy-metal contaminated soils. Shengwu Gongcheng Xuebao/Chinese J. Biotechnol. 36, 455–470 (2020).CAS 

Google Scholar 
Beesley, L. & Dickinson, N. Carbon and trace element fluxes in the pore water of an urban soil following green waste compost, woody and biochar amendments, inoculated with the earthworm Lumbricus terrestris. Soil Biol. Biochem. 43, 188–196 (2011).Article 
CAS 

Google Scholar 
Zhu, D. et al. Deciphering potential roles of earthworms in mitigation of antibiotic resistance in the soils from diverse ecosystems. Environ. Sci. Technol. 55, 7445–7455 (2021).Article 
CAS 

Google Scholar 
Bowers, R. M., McLetchie, S., Knight, R. & Fierer, N. Spatial variability in airborne bacterial communities across land-use types and their relationship to the bacterial communities of potential source environments. ISME J. 5, 601–612 (2011).Article 
CAS 

Google Scholar 
Selway, C. A. et al. Transfer of environmental microbes to the skin and respiratory tract of humans after urban green space exposure. Environ. Int. 145, 106084 (2020).Article 

Google Scholar 
Ottman, N. et al. Soil exposure modifies the gut microbiota and supports immune tolerance in a mouse model. J. Allergy Clin. Immunol. 143, 1198–1206.e12 (2019).Article 
CAS 

Google Scholar 
Roslund, M. I. et al. Long-term biodiversity intervention shapes health-associated commensal microbiota among urban day-care children. Environ. Int. 157, 106811 (2021).Article 

Google Scholar 
Roslund, M. I. et al. A Placebo-controlled double-blinded test of the biodiversity hypothesis of immune-mediated diseases: Environmental microbial diversity elicits changes in cytokines and increase in T regulatory cells in young children. Ecotoxicol. Environ. Saf. 242, 113900 (2022).Rook, G., Bäckhed, F., Levin, B. R., McFall-Ngai, M. J. & McLean, A. R. Evolution, human-microbe interactions, and life history plasticity. Lancet 390, 521–530 (2017).Article 

Google Scholar 
Flandroy, L. et al. The impact of human activities and lifestyles on the interlinked microbiota and health of humans and of ecosystems. Sci. Total Environ. 627, 1018–1038 (2018).Article 
CAS 

Google Scholar 
Reber, S. O. et al. Immunization with a heat-killed preparation of the environmental bacterium Mycobacterium vaccae promotes stress resilience in mice. Proc. Natl. Acad. Sci. USA 113, E3130–E3139 (2016).Article 
CAS 

Google Scholar 
Ege, M. J. Exposure to environmental microorganisms and childhood asthma. N. Engl. J. Med. 364, 701–9 (2011).Article 
CAS 

Google Scholar 
Stein, M. M. et al. Innate immunity and asthma risk in amish and hutterite farm children. N. Engl. J. Med. 375, 411–421 (2016).Article 
CAS 

Google Scholar 
Roslund, M. I. et al. Environmental Studies biodiversity intervention enhances immune regulation and health-associated commensal microbiota among daycare children. Sci. Adv. 6, eaba2578 (2020).Article 
CAS 

Google Scholar 
Hanski, I. et al. Environmental biodiversity, human microbiota, and allergy are interrelated. Proc. Natl. Acad. Sci. USA 109, 8334–8339 (2012).Article 
CAS 

Google Scholar 
Franklin, P. J. Indoor air quality and respiratory health of children. Paediatr. Respir. Rev. 8, 281–286 (2007).Article 

Google Scholar 
Adams, R. I. et al. Microbial exposures in moisture-damaged schools and associations with respiratory symptoms in students: A multi-country environmental exposure study. Indoor Air 31, 1952–1966 (2021).Article 
CAS 

Google Scholar 
Dunn, R. R., Reese, A. T. & Eisenhauer, N. Biodiversity–ecosystem function relationships on bodies and in buildings. Nat. Ecol. Evol. 3, 7–9 (2019).Article 

Google Scholar 
Gilbert, J. A. & Stephens, B. Microbiology of the built environment. Nat. Rev. Microbiol. 16, 661–670 (2018).Article 
CAS 

Google Scholar 
Flies, E. J., Clarke, L. J., Brook, B. W. & Jones, P. Urbanisation reduces the abundance and diversity of airborne microbes – but what does that mean for our health? A systematic review. Sci. Total Environ. 738, 140337 (2020).Article 
CAS 

Google Scholar 
Berg, G., Mahnert, A. & Moissl-Eichinger, C. Beneficial effects of plant-associated microbes on indoor microbiomes and human health? Front. Microbiol. 5, 1–5 (2014).Article 

Google Scholar 
Parajuli, A. et al. Urbanization reduces transfer of diverse environmental microbiota indoors. Front. Microbiol. 9, 1–13 (2018).Article 

Google Scholar 
Kirjavainen, P. V. et al. Farm-like indoor microbiota in non-farm homes protects children from asthma development. Nat. Med. 25, 1089–1095 (2019).Article 
CAS 

Google Scholar 
Sonnenburg, E. D. & Sonnenburg, J. L. The ancestral and industrialized gut microbiota and implications for human health. Nat. Rev. Microbiol. 17, 383–390 (2019).Article 
CAS 

Google Scholar 
Fan, Y. & Pedersen, O. Gut microbiota in human metabolic health and disease. Nat. Rev. Microbiol. 19, 55–71 (2021).Article 
CAS 

Google Scholar 
Blum, W. E. H., Zechmeister-Boltenstern, S. & Keiblinger, K. M. Does soil contribute to the human gut microbiome? Microorganisms 7, 287 (2019).Article 

Google Scholar 
Liddicoat, C. et al. Naturally-diverse airborne environmental microbial exposures modulate the gut microbiome and may provide anxiolytic benefits in mice. Sci. Total Environ. 701, 134684 (2020).Article 
CAS 

Google Scholar 
Tun, H. M. et al. Exposure to household furry pets influences the gut microbiota of infants at 3-4 months following various birth scenarios. Microbiome 5, 1–14 (2017).Article 

Google Scholar 
Brame, J. E., Liddicoat, C., Abbott, C. A. & Breed, M. F. The potential of outdoor environments to supply beneficial butyrate-producing bacteria to humans. Sci. Total Environ. 777, 146063 (2021).Article 
CAS 

Google Scholar 
Elmqvist, T. et al. Urbanization, biodiversity and ecosystem services: challenges and opportunities: a global assessment. https://doi.org/10.1007/978-94-007-7088-1_23 (2013).Breed, M. F. et al. Ecosystem Restoration: A Public Health Intervention. Ecohealth 18, 269–271 (2021).Article 

Google Scholar 
Aronson, M. F. J. et al. Biodiversity in the city: key challenges for urban green space management. Front. Ecol. Environ. 15, 189–196 (2017).Article 

Google Scholar 
Contos, P., Wood, J. L., Murphy, N. P. & Gibb, H. Rewilding with invertebrates and microbes to restore ecosystems: Present trends and future directions. Ecol. Evol. 11, 7187–7200 (2021).Article 

Google Scholar 
Auclerc, A. et al. Fostering the use of soil invertebrate traits to restore ecosystem functioning. Geoderma 424, 116019 (2022).Article 

Google Scholar 
Mills, J. G. et al. Revegetation of urban green space rewilds soil microbiotas with implications for human health and urban design. Restor. Ecol. 28, S322–S334 (2020).Article 

Google Scholar  More

Ferretti, F., Worm, B., Britten, G., Heithaus, M. & Lotze, H. Patterns and ecosystem consequences of shark declines in the ocean. Ecol. Lett. 13, 1055–1071 (2010).PubMed 

Google Scholar 
Heithaus, M. et al. Seagrasses in the age of sea turtle conservation and shark overfishing. Front. Mar. Sci. 1, 1–6 (2014).Article 

Google Scholar 
Estes, J. et al. Megafaunal impacts on structure and function of ocean ecosystems. Annu. Rev. Env. Resour. 41, 83–116 (2016).Article 

Google Scholar 
Anderson, O. et al. Global seabird bycatch in longline fisheries. Endanger. Species Res. 14, 91–106 (2011).Article 

Google Scholar 
Dias, M. et al. Threats to seabirds: A global assessment. Biol. Conserv. 237, 525–537 (2019).Article 

Google Scholar 
Phillips, R. et al. The conservation status and priorities for albatrosses and large petrels. Biol. Conserv. 201, 169–183 (2016).Article 

Google Scholar 
Werner, T., Kraus, S., Read, A. & Zollett, E. Fishing techniques to reduce the bycatch of threatened marine animals. Mar. Technol. Soc. J. 40, 50–68 (2006).Article 

Google Scholar 
Hall, M., Gilman, E., Minami, H., Mituhasi, T. & Carruthers, E. Mitigating bycatch in tuna fisheries. Rev. Fish Biol. Fish. 27, 881–908 (2017).Article 

Google Scholar 
Gilman, E., Brothers, N. & Kobayashi, D. Principles and approaches to abate seabird bycatch in longline fisheries. Fish Fish. 6, 35–49 (2005).Article 

Google Scholar 
Gilman, E., Chaloupka, M., Wiedoff, B. & Willson, J. Mitigating seabird bycatch during hauling by pelagic longline vessels. PLoS ONE 9, e84499 (2014).Article 
ADS 
PubMed 
PubMed Central 

Google Scholar 
Juan-Jorda, M., Murua, H., Arrizabalaga, H., Dulvy, N. & Restrepo, V. Report card on ecosystem-based fisheries management in tuna regional fisheries management organizations. Fish Fish. 19, 321–339 (2018).Article 

Google Scholar 
ACAP. Review and best practice advice for reducing the impact of pelagic longline fisheries on seabirds. Agreement on the Conservation of Albatrosses and Petrels, Hobart, Australia (2019).Crespo, P. & Crawford, R. Bycatch and the Marine Stewardship Council (MSC): A Review of the Efficacy of the MSC Certification Scheme in Tackling the Bycatch of Non-target Species (Birdlife International, 2019).
Google Scholar 
Nakano, H., Okazaki, M. & Okamoto, H. Analysis of catch depth by species for tuna longline fishery based on catch by branch lines. Bull. Nat. Res. Inst. Far Seas Fish. 34, 43–62 (1997).
Google Scholar 
Musyl, M. et al. Postrelease survival, vertical and horizontal movements, and thermal habitats of five species of pelagic sharks in the central Pacific Ocean. Fish. Bull. 109, 341–368 (2011).
Google Scholar 
Gabr, M. & El-Haweet, A. Pelagic longline fishery for albacore in the Mediterranean Sea off Egypt. Turk. J. Fish. Aquat. Sci. 12, 735–741 (2012).Article 

Google Scholar 
MEC. Marine Stewardship Council Public Certification Report. French Polynesia Albacore and Yellowfin Longline Fishery. ME Certification Ltd., Lymington, UK (2018).Gilman, E. et al. Robbing Peter to pay Paul: Replacing unintended cross-taxa conflicts with intentional tradeoffs by moving from piecemeal to integrated fisheries bycatch management. Rev. Fish Biol. Fish. 29, 93–123 (2019).Article 

Google Scholar 
SCS. Tri Marine Atlantic albacore (Thunnus alalunga) Longline Fishery. MSC Fishery Assessment Report. SCS Global Services, Emeryville, USA (2022).Gilman, E. et al. Phylogeny explains capture mortality of sharks and rays in pelagic longline fisheries: A global meta-analytic synthesis. Sci. Rep. https://doi.org/10.1038/s41598-022-21976-w (2022).Article 
PubMed 
PubMed Central 

Google Scholar 
WCPFC. Conservation and Management Measure to Mitigate the Impact of Fishing for Highly Migratory Fish Stocks on Seabirds. CMM 2018-03. Western and Central Pacific Fisheries Commission, Kolonia, Federated States of Micronesia (2018).IATTC. Resolution to Mitigate the Impact on Seabirds of Fishing for Species Covered by the IATTC. Resolution C-11-02. Inter-American Tropical Tuna Commission, La Jolla, USA (2011).Melvin, E., Guy, T. & Read, L. Best practice seabird bycatch mitigation for pelagic longline fisheries targeting tuna and related species. Fish. Res. 149, 5–18 (2014).Article 

Google Scholar 
Huang, H. Incidental catch of seabirds and sea turtles by Taiwanese longline fleets in the Pacific Ocean. Fish. Res. 170, 179–189 (2015).Article 

Google Scholar 
Jimenez, S. et al. Towards mitigation of seabird bycatch: Large-scale effectiveness of night setting and tori lines across multiple pelagic longline fleets. Bio. Cons. 247, 108642 (2020).Article 

Google Scholar 
IUCN. The IUCN Red List of Threatened Species. Version 2022–1. Online resource www.iucnredlist.org. ISSN 2307–8235. International Union for the Conservation of Nature, Gland, Switzerland (2022).Gilman, E., Castejon, V., Loganimoce, E. & Chaloupka, M. Capability of a pilot fisheries electronic monitoring system to meet scientific and compliance monitoring objectives. Mar. Policy 113, 103792 (2020).Article 

Google Scholar 
Gilman, E., Chaloupka, M. & Sieben, C. Ecological risk assessment of a data-limited fishery using an ensemble of approaches. Mar. Policy 133, 104752 (2021).Article 

Google Scholar 
WPRFMC. Appendix 5. Fact Sheets on Seabird Bycatch Mitigation Methods for Pelagic Longline Fisheries. Report of the Workshop to Review Seabird Bycatch Mitigation Measures for Hawaii’s Pelagic Longline Fisheries. ISBN: 978–1–944827–37–3. Western Pacific Regional Fishery Management Council, Honolulu (2019).Melvin, E., Dietrich, K., Suryan, R. & Fitzgerald, S. Lessons from seabird conservation in Alaskan longline fisheries. Cons. Biol. 33, 842–852 (2019).Article 

Google Scholar 
Ward, P. & Myers, R. Inferring the depth distribution of catchability for pelagic fishes and correcting for variations in the depth of longline fishing gear. Can. J. Fish. Aquat. Sci. 62, 1130–1142 (2005).Article 

Google Scholar 
Rice, P., Goodyear, C., Prince, E., Snodgrass, D. & Serafy, J. Use of catenary geometry to estimate hook depth during near-surface pelagic longline fishing: Theory versus practice. N. Am. J. Fish. Manag. 27, 1148–1161 (2007).Article 

Google Scholar 
Zhou, C. & Brothers, N. Interaction frequency of seabirds with longline fisheries: Risk factors and implications for management. ICES J. Mar. Sci. 78, 1278–1287 (2021).Article 

Google Scholar 
Childers, J., Snyder, S. & Kohin, S. Migration and behavior of juvenile North Pacific albacore (Thunnus alalunga). Fish. Oceanogr. 20, 157–173 (2011).Article 

Google Scholar 
Cosgrove, R., Arregui, I., Arrizabalaga, H., Goni, N. & Sheridan, M. New insights to behavior of North Atlantic albacore tuna (Thunnus alalunga) observed with pop-up satellite archival tags. Fish. Res. 150, 89–99 (2014).Article 

Google Scholar 
Williams, et al. Vertical behavior and diet of albacore tuna (Thunnus alalunga) vary with latitude in the South Pacific Ocean. Deep -Sea Res. II 113, 154–169 (2015).Punt, A., Butterworth, D., de Moor, C., De Oliveira, J. & Haddon, M. Management strategy evaluation: Best practices. Fish Fish. 17, 303–334 (2016).Article 

Google Scholar 
Gabry, J., Simpson, D., Vehtari, A., Betancourt, M. & Gelman, A. Visualization in Bayesian workflow. J. R. Soc. Ser. A 182, 1–14 (2019).MathSciNet 

Google Scholar 
Gelman, A., et al. Bayesian Workflow. arXiv:2011.01808v1 (2020).Fahrmeir, L. & Lang, S. Bayesian inference for generalised additive mixed models based on Markov random field priors. Appl. Stat. 50, 201–220 (2001).
Google Scholar 
Yao, Y., Vehtari, A., Simpson, D. & Gelman, A. Using stacking to average Bayesian predictive distributions (with Discussion). Bayesian Anal. 13, 917–1003 (2018).Article 
MathSciNet 
MATH 

Google Scholar 
Fávero, L., Hair, J., Souza, R., Albergaria, M. & Brugni, T. Zero-inflated generalized linear mixed models: a better way to understand data relationships. Mathematics 9, 1100 (2021).Article 

Google Scholar 
Gilman, E. et al. Tori lines mitigate seabird bycatch in a pelagic longline fishery. Rev. Fish Biol. Fish. 31, 653–666 (2021).Article 

Google Scholar 
Makowski, D., Ben-Shachar, M. & Lüdecke, D. bayestestR: Describing effects and their uncertainty, existence and significance within the Bayesian framework. J. Open Source Softw. 4, 1541 (2019).Article 
ADS 

Google Scholar 
Yau, K., Wang, K. & Lee, A. Zero-Inflated negative binomial mixed regression modeling of over-dispersed count data with extra zeros. Biom. J. 45, 437–452 (2003).Article 
MathSciNet 
MATH 

Google Scholar 
Congdon, P. Applied Bayesian Modelling. Wiley and Sons Ltd, UK. (2003).Günhan, B., Röver, C. & Friede, T. Random-effects meta-analysis of few studies involving rare events. Res. Synth. Methods 11, 74–90 (2020).Article 
PubMed 

Google Scholar 
Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Bürkner, P. brms: An R Package for Bayesian multilevel models using Stan. J. Stat. Softw. 81, 1–28 (2017).
Google Scholar 
Ott, M., Plummer, M. & Roos, M. How vague is vague? How informative is informative? Reference analysis for Bayesian meta-analysis. Stat. Med. 40, 4505–4521 (2021).Article 
MathSciNet 
PubMed 
PubMed Central 

Google Scholar 
Vehtari, A., Gelman, A., Simpson, D., Carpenter, B. & Bürkner, P. Rank-normalization, folding, and localization: an improved Rhat for assessing convergence of MCMC (with Discussion). Bayesian Anal. 16, 667–718 (2021).Article 
ADS 
MathSciNet 
MATH 

Google Scholar 
Vehtari, A., Gelman, A. & Gabry, J. Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. Stat. Comput. 27, 1413–1432 (2017).Article 
MathSciNet 
MATH 

Google Scholar 
Kruschke, J. & Liddell, T. The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective. Psychon. Bull. Rev. 25, 178–206 (2018).Article 
PubMed 

Google Scholar 
Lenth, R. Least-squares means: the R package lsmeans. J. Stat. Softw. 69, 1–33 (2016).Article 

Google Scholar 
Lenth R (2020) emmeans: Estimated Marginal Means, aka Least-Squares Means. R package version 1.5.2-1. https://CRAN.R-project.org/package=emmeans More

Myers, N., Mittermeier, R. A., Mittermeier, C. G., Fonseca, G. & Kent, J. M. Biodiversity hotspots for conservation priorities. Nature 403, 853–858 (2000).Article 
CAS 
PubMed 

Google Scholar 
Cuttelod, A., García, V., Abdul Malak, D., Temple, H. & Katariya, V. The Mediterranean: A biodiversity hotspot under threat. In Wildl. a Chang. World an Anal. 2008 IUCN Red List Threat. Species 89–101 (2008).Coll, M. et al. The biodiversity of the Mediterranean Sea: Estimates, patterns, and threats. PLoS ONE 5, e11842–e11842 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Coll, M. et al. The Mediterranean Sea under siege: Spatial overlap between marine biodiversity, cumulative threats and marine reserves. Glob. Ecol. Biogeogr. 21, 465–480 (2012).Article 

Google Scholar 
Micheli, F. et al. Cumulative human impacts on mediterranean and black sea marine ecosystems: Assessing current pressures and opportunities. PLoS ONE 8, e79889 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Lejeusne, C., Chevaldonné, P., Pergent-Martini, C., Boudouresque, C. F. & Pérez, T. Climate change effects on a miniature ocean: The highly diverse, highly impacted Mediterranean Sea. Trends Ecol. Evol. 25, 250–260 (2010).Article 
PubMed 

Google Scholar 
Tsirintanis, K. et al. Bioinvasion impacts on biodiversity, ecosystem services, and human health in the Mediterranean Sea. Aquatic Invasions, 17(3), 308–352 (2022).Article 

Google Scholar 
Sanderson, C. E. & Alexander, K. A. Unchartered waters: Climate change likely to intensify infectious disease outbreaks causing mass mortality events in marine mammals. Glob. Chang. Biol. 26, 4284–4301 (2020).Article 
PubMed 

Google Scholar 
EEC, 1992. European Commission. In EU Council Directive 92/43/EEC on the Conservationof Natural Habitats and of Wild Fauna and Flora. Orkesterjournalen L 7–50 206 (1992).Bearzi, G. Interactions between cetacean and fisheries in the Mediterranean Sea. In: G. Notarbartolo di Sciara (Ed.), Cetaceans of the Mediterranean and Black Seas: state of knowledge and conservation strategies. A report to the ACCOBAMS Secretariat, Monaco, 9, 20 (2002). Reeves, R. R., Smith, B. D., Crespo, E. A. & Notarbartolo di Sciara, G. Dolphins, Whales and Porpoises : 2002–2010 Conservation Action Plan for the world’s Cetaceans (2003).Dolman, S., Evans, P., Ritter, F., Simmonds, M. & Swabe, J. Implications of new technical measures regulation for cetacean bycatch in European waters. Mar. Policy 124, 1043 (2020).
Google Scholar 
Carlucci, R. et al. Managing multiple pressures for cetaceans’ conservation with an Ecosystem-Based Marine Spatial Planning approach. J. Environ. Manage. 287, 112240 (2021).Article 
PubMed 

Google Scholar 
Carlucci, R. et al. Assessment of cetacean–fishery interactions in the marine food web of the Gulf of Taranto (Northern Ionian Sea, Central Mediterranean Sea). Rev. Fish Biol. Fish. 31, 135–156 (2020).Article 

Google Scholar 
Fossi, C. & Lauriano, G. Impacts of shipping on the biodiversity of large marine vertebrates: Persistent organic pollutants, sewage and debris. Marit. Traffic Eff. Biodivers. Mediterr. Sea Rev Impacts Prior. Areas Mitig. Meas. 3, 65–73 (2008).
Google Scholar 
Cardellicchio, N. Persistent contaminants in dolphins: An indication of chemical pollution in the mediterranean sea. Water Sci. Technol. 32, 331–340 (1995).Article 
CAS 

Google Scholar 
Fossi, M. C., Panti, C., Baini, M. & Lavers, J. L. A review of plastic-associated pressures: Cetaceans of the Mediterranean Sea and Eastern Australian Shearwaters as case studies. Front. Mar. Sci. 5, 125 (2018).Article 

Google Scholar 
Marsili, L., Jiménez, B. & Borrell, A. Persistent Organic Pollutants in Cetaceans Living in a Hotspot Area (Elsevier, 2018).Book 

Google Scholar 
Dolman, S. J., Evans, P. G. H., Notarbartolo-di-Sciara, G. & Frisch, H. Active sonar, beaked whales and European regional policy. Mar. Pollut. Bull. 63, 27–34 (2011).Article 
CAS 
PubMed 

Google Scholar 
di Sciara, G. N. et al. Place-based approaches to marine mammal conservation. Aquat. Conserv. Mar. Freshw. Ecosyst. 26, 85–100 (2016).Article 

Google Scholar 
Holcer, D., Fortuna, C. M., Mackelworth, P., Cebrian, D. & Requena Moreno, S. Adriatic Sea: Important Areas for Conservation of Cetaceans, Sea Turtles and Giant Devil Rays (2015).Carlucci, R. et al. Modeling the spatial distribution of the striped dolphin (Stenella coeruleoalba) and common bottlenose dolphin (Tursiops truncatus) in the Gulf of Taranto (Northern Ionian Sea, Central-eastern Mediterranean Sea). Ecol. Indic. 69, 707–721 (2016).Article 

Google Scholar 
Carlucci, R., Ricci, P., Cipriano, G. & Fanizza, C. Abundance, activity and critical habitat of the striped dolphin Stenella coeruleoalba in the Gulf of Taranto (northern Ionian Sea, central Mediterranean Sea). Aquat. Conserv. Freshw. Ecosyst. 28, 324–336 (2018).Article 

Google Scholar 
Carlucci, R. et al. Random Forest population modelling of striped and common-bottlenose dolphins in the Gulf of Taranto (Northern Ionian Sea, Central-eastern Mediterranean Sea). Estuar. Coast. Shelf Sci. 204, 177–192 (2018).Article 

Google Scholar 
Arcangeli, A., Campana, I. & Bologna, M. A. Influence of seasonality on cetacean diversity, abundance, distribution and habitat use in the western Mediterranean Sea: Implications for conservation. Aquat. Conserv. Mar. Freshw. Ecosyst. 27, 995–1010 (2017).Article 

Google Scholar 
Panigada, S. et al. Estimating cetacean density and abundance in the Central and Western Mediterranean Sea through aerial surveys: Implications for Management. Deep. Res. Part II-Top. Stud. Oceanogr. 141, 41–58 (2017).Article 

Google Scholar 
Mannocci, L. et al. Assessing cetacean surveys throughout the Mediterranean Sea: A gap analysis in environmental space. Sci. Rep. 8, 1 (2018).Article 
CAS 

Google Scholar 
Panigada, S. et al. Estimates of Abundance and Distribution of Cetaceans, Marine Mega-Fauna and Marine Litter in the Mediterranean Sea from 2018–2019 surveys. ACCOBAMS vol. ACCOBAMS S (2021).Paiu, R.-M. et al. Estimates of abundance and distribution of cetaceans in the Black Sea from 2019 surveys. ACCOBAMS 54, 45 (2021).
Google Scholar 
Azzolin, M. et al. Spatial distribution modelling of striped dolphin (Stenella coeruleoalba) at different geographical scales within the EU Adriatic and Ionian Sea Region, central-eastern Mediterranean Sea. Aquat. Conserv. Freshw. Ecosyst. 30, 1194–1207 (2020).Article 

Google Scholar 
Renò, V. et al. A SIFT-based software system for the photo-identification of the Risso’s dolphin. Ecol. Inform. 50, 95–101 (2019).Article 

Google Scholar 
Maglietta, R. et al. DolFin: an innovative digital platform for studying Risso’s dolphins in the Northern Ionian Sea (North-eastern Central Mediterranean). Sci. Rep. 8, 17185 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Hammond, P. S. et al. Estimating the abundance of marine mammal populations. Front. Mar. Sci. 8, 96 (2021).Article 

Google Scholar 
Fontaine, M. C. et al. History of expansion and anthropogenic collapse in a top marine predator of the Black Sea estimated from genetic data. Proc. Natl. Acad. Sci. 109, E2569–E2576 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Alter, S. E., Rynes, E. & Palumbi, S. R. DNA evidence for historic population size and past ecosystem impacts of gray whales. Proc. Natl. Acad. Sci. 104, 15162–15167 (2007).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Chavez-Rosales, S., Palka, D. L., Garrison, L. P. & Josephson, E. A. Environmental predictors of habitat suitability and occurrence of cetaceans in the western North Atlantic Ocean. Sci. Rep. 9, 5833 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Buckland, S. et al. Introduction to Distance Sampling: Estimating Abundance of Biological Populations (Oxford University Press, 2001).MATH 

Google Scholar 
Buckland, S. T. et al. Advanced Distance Sampling: Estimating Abundance of Biological Populations (OUP Oxford, 2004).MATH 

Google Scholar 
Laake, J. S. T., Buckland, E. A., Rexstad, T. A., Marques, C. S. & Oedekoven, F. Distance sampling: Methods and applications. Biometrics 72, 1389–1390 (2016).Article 

Google Scholar 
Hammond, P. S., Mizroch, S. A. & Donovan, G. P. Individual recognition of cetaceans: Use of photo-identification and other techniques to estimate population parameters. In Incorporating the Proceedings of the Symposium and Workshop on Individual Recognition and the Estimation of Cetacean Population Parameters (1990).Sandercock, B. K. Handbook of capture-recapture analysis. Biometrics 62, 1276–1277 (2006).Article 

Google Scholar 
Hammond, P. S. Mark-Recapture. In Encyclopedia of Marine Mammals (Third Edition) (eds Würsig, B. et al.) 580–584 (Academic Press, 2018).Pless, E., Saarman, N. P., Powell, J. R., Caccone, A. & Amatulli, G. A machine-learning approach to map landscape connectivity in Aedes aegypti with genetic and environmental data. Proc. Natl. Acad. Sci. 118, 9 (2021).Article 

Google Scholar 
Belanger, C. L. et al. Global environmental predictors of benthic marine biogeographic structure. Proc. Natl. Acad. Sci. 109, 14046–14051 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Frainer, A. et al. Climate-driven changes in functional biogeography of Arctic marine fish communities. Proc. Natl. Acad. Sci. USA 114, 12202–12207 (2017).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Miller, D. L., Burt, M. L., Rexstad, E. A. & Thomas, L. Spatial models for distance sampling data: Recent developments and future directions. Methods Ecol. Evol. 4, 1001–1010 (2013).Article 

Google Scholar 
Zurell, D. et al. A standard protocol for reporting species distribution models. Ecography (Cop.) 43, 1261–1277 (2020).Article 

Google Scholar 
Redfern, J. V. et al. Techniques for cetacean-habitat modeling. Mar. Ecol. Prog. Ser. 310, 271–295 (2006).Article 

Google Scholar 
Hastie, T. J. & Tibshirani, R. J. Generalized Additive Models (Taylor & Francis, 1990).MATH 

Google Scholar 
Goodfellow, I., Bengio, Y. & Courville, A. Deep Learning (MIT Press, 2016).MATH 

Google Scholar 
Friedman, J. H. Greedy function approximation: A gradient boosting machine. Ann. Stat. 29, 1189–1232 (2001).Article 
MathSciNet 
MATH 

Google Scholar 
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).Article 
MATH 

Google Scholar 
Vapnik, N.V. Statistical Learning Theory (1998).Culley, C., Vijayakumar, S., Zampieri, G. & Angione, C. A mechanism-aware and multiomic machine-learning pipeline characterizes yeast cell growth. Proc. Natl. Acad. Sci. 117, 18869–18879 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Moore, B. M. et al. Robust predictions of specialized metabolism genes through machine learning. Proc. Natl. Acad. Sci. 116, 2344–2353 (2019).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Renò, V. et al. Combined color semantics and deep learning for the automatic detection of dolphin dorsal fins. Electronics 9, 75 (2020).Article 

Google Scholar 
Maglietta, R., Milella, A., Caccia, M. & Bruzzone, G. A vision-based system for robotic inspection of marine vessels. Signal Image Video Process. 12, 471–478 (2018).Article 

Google Scholar 
Maglietta, R. et al. Automated hippocampal segmentation in 3D MRI using random undersampling with boosting algorithm. Pattern Anal. Appl. 19, 579–591 (2016).Article 
MathSciNet 
PubMed 

Google Scholar 
Ancona, N., Maglietta, R. & Stella, E. Data representations and generalization error in kernel based learning machines. Pattern Recognit. 39, 1588–1603 (2006).Article 
MATH 

Google Scholar 
Martín, B., González-Arias, J. & Vicente-Virseda, J. A. Machine learning as a successful approach for predicting complex spatial temporal patterns in animal species abundance. Anim. Biodivers. Conserv. 2021, 25 (2021).
Google Scholar 
Dimauro, G. et al. A novel approach for biofilm detection based on a convolutional neural network. Electronics 9, 88 (2020).Article 

Google Scholar 
Inglese, P. et al. Multiple RF classifier for the hippocampus segmentation: Method and validation on EADC-ADNI Harmonized Hippocampal Protocol. Phys. Med. 31(8), 1085–1091 (2015).Article 
CAS 
PubMed 

Google Scholar 
Maglietta, R. et al. Convolutional neural networks for Risso’s Dolphins identification. IEEE Access 8, 80195–80206 (2020).Article 

Google Scholar 
Conference on Biological Diversity—Nagoya 2010 European Parliament resolution of 7 October 2010 on the EU strategic objectives for the 10th Meeting of the Conference of the Parties to the Convention on Biological Diversity (CBD), to be held in Nagoya (2010).EU. In Commission Decision (EU) 2017/848 of 17 May 2017 Laying Down Criteria and Methodological Standards on Good Environmental Status of Marine Waters and Specifications and Standardised Methods for Monitoring and Assessment, and Repealing Decision 2 (2017).European Commission. Directive 2014/89/EU of the European Parliament and of the Council of 23 July 2014 establishing a framework for maritime spatial planning. In Off. J. Eur. Union 2014, L 257, 135; MSFD (2008/56/EC) (2014).Muckenhirn, A., Baş, A. A. & Richard, F.-J. Assessing the influence of environmental and physiographic parameters on common bottlenose dolphin (Tusiops truncatus) distribution in the southern Adriatic Sea. In Proc. 1st Int. Electron. Conf. Biol. Divers. Ecol. Evol. (2021).Correia, A. et al. Predicting Cetacean Distributions in the Eastern North Atlantic to Support Marine Management. Front. Mar. Sci. 8, 256 (2021).Article 

Google Scholar 
Redfern, J. V., Barlow, J., Ballance, L. T., Gerrodette, T. & Becker, E. A. Absence of scale dependence in dolphin-habitat models for the eastern tropical Pacific Ocean. Mar. Ecol. Prog. Ser. 363, 1–14 (2008).Article 

Google Scholar 
Kruse, S. L. Aspects of the Biology, Ecology, and Behavior of Risso’s dolphins (Grampus griseus) off the California Coast (University of California, Santa Cruz, 1989).Kruse, S., Caldwell, D. K., Caldwell, M. C., Ridgway, S. H. & Harrison, R. Risso’s dolphin Grampus griseus (G. Cuvier, 1812). Handb. Mar. Mamm. Sec. B Dolphins Porpoises 6, 12 (1999).
Google Scholar 
Gómez-de-Segura, A., Hammond, P. S. & Raga, J. A. Influence of environmental factors on small cetacean distribution in the Spanish Mediterranean. J. Mar. Biol. Assoc. UK 88, 1185–1192 (2008).Article 

Google Scholar 
Pitchford, J. et al. Predictive spatial modelling of seasonal bottlenose dolphin (Tursiops truncatus) distributions in the Mississippi Sound: Seasonal spatial distributions of bottlenose dolphins. Aquat. Conserv. Mar. Freshw. Ecosyst. 26, 289–306 (2015).Article 

Google Scholar 
La Manna, G., Ronchetti, F. & Sarà, G. Predicting common bottlenose dolphin habitat preference to dynamically adapt management measures from a Marine Spatial Planning perspective. Ocean Coast. Manag. 130, 317–327 (2016).Article 

Google Scholar 
Becker, E. A. et al. Predicting cetacean abundance and distribution in a changing climate. Divers. Distrib. 25, 626–643 (2019).Article 

Google Scholar 
Cañadas, A. & Hammond, P. S. Abundance and habitat preferences of the short-beaked common dolphin Delphinus delphis in the southwestern Mediterranean: Implications for conservation. Endanger. Spec. Res. 4, 309–331 (2008).Article 

Google Scholar 
Mannocci, L. et al. Predicting cetacean and seabird habitats across a productivity gradient in the South Pacific gyre. Prog. Oceanogr. 120, 383–398 (2014).Article 

Google Scholar 
Carretta, J. V. Estimates of Marine Mammal, Sea Turtle, and Seabird Bycatch in the California Large-Mesh Drift Gillnet Fishery: 1990–2019 U.S. Department of Commerce, NOAA Technical Memorandum NMFS-SWFSC-654.
https://doi.org/10.25923/7emj-za90 (2021).Rustam, F. et al. A performance comparison of supervised machine learning models for Covid-19 tweets sentiment analysis. PLoS ONE 16, e0245909 (2021).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
D’Addabbo, A. & Maglietta, R. Parallel selective sampling method for imbalanced and large data classification. Pattern Recognit. Lett. 62, 61–67 (2015).Article 

Google Scholar 
Dimauro, G. et al. An intelligent non-invasive system for automated diagnosis of anemia exploiting a novel dataset. Artif. Intell. Med. 136, 102477 (2023).Article 
PubMed 

Google Scholar 
Spooner, A. et al. A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction. Sci. Rep. 10, 20410 (2020).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Becker, E. A. et al. Performance evaluation of cetacean species distribution models developed using generalized additive models and boosted regression trees. Ecol. Evol. 10, 5759–5784 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Kosicki, J. Z. Generalised additive models and random forest approach as effective methods for predictive species density and functional species richness. Environ. Ecol. Stat. 27, 273–292 (2020).Article 
CAS 

Google Scholar 
Barreto, J. et al. Drone-monitoring: Improving the detectability of threatened marine megafauna. Drones 5, 14 (2021).Article 

Google Scholar 
Sarr, J.-M.A. et al. Complex data labeling with deep learning methods: Lessons from fisheries acoustics. ISA Trans. 109, 113–125 (2021).Article 
PubMed 

Google Scholar 
Capezzuto, F. et al. The bathyal benthopelagic fauna in the north-western Ionian Sea: Structure, patterns and interactions. Chem. Ecol. 26, 199–217 (2010).Article 

Google Scholar 
Harris, P. & Whiteway, T. Global distribution of large submarine canyons: Geomorphic differences between active and passive continental margins. Mar. Geol. 285, 69–86 (2011).Article 

Google Scholar 
Pescatore, T. & Senatore, M. R. A comparison between a present.day (Taranto Gulf) and a Miocene (Irpinian Basin) foredeep of the Southern Apennine (Italy). Spec. Publ. 1986, 169–182 (1986).
Google Scholar 
Rossi, S. & Gabbianelli, G. Geomorfologia del Golfo di Taranto. Ital. J. Geosci. 97, 423–437 (1978).
Google Scholar 
Federico, I. et al. Observational evidence of the basin-wide gyre reversal in the Gulf of Taranto. Geophys. Res. Lett. 47, 1030 (2020).Article 

Google Scholar 
Carlucci, R., Battista-Capezzuto, F., Serena, F. & Sion, L. Occurrence of the basking shark Cetorhinus maximus (Gunnerus, 1765) (Lamniformes: Cetorhinidae) in the central-eastern Mediterranean Sea. Ital. J. Zool. 81, 280–286 (2014).Article 

Google Scholar 
Matarrese, R., Chiaradia, M. T., Tijani, K., Morea, A. & Carlucci, R. Chlorophyll A multi-temporal analysis in coastal waters with MODIS data. Eur. J. Remote Sens. 2011, 39–48 (2011).
Google Scholar 
Civitarese, G., Gačić, M., Lipizer, M. & Eusebi-Borzelli, G. L. On the impact of the Bimodal Oscillating System (BiOS) on the biogeochemistry and biology of the Adriatic and Ionian Seas (Eastern Mediterranean). Biogeosciences 7, 3987–3997 (2010).Article 
CAS 

Google Scholar 
Pinardi, N. et al. Marine rapid environmental assessment in the hack{newline} Gulf of Taranto: A multiscale approach. Nat. Hazards Earth Syst. Sci. 16, 2623–2639 (2016).Article 

Google Scholar 
Ciancia, E. et al. Investigating the chlorophyll-a variability in the Gulf of Taranto (North-western Ionian Sea) by a multi-temporal analysis of MODIS-Aqua Level 3/Level 2 data. Cont. Shelf Res. 155, 34–44 (2018).Article 

Google Scholar 
Trotta, F., Pinardi, N., Fenu, E., Grandi, A. & Lyubartsev, V. Multi-nest high-resolution model of submesoscale circulation features in the Gulf of Taranto. Ocean Dyn. 67, 1609–1625 (2017).Article 

Google Scholar 
Federico, I. et al. Coastal ocean forecasting with an unstructured grid model in the southern Adriatic and northern Ionian seas. Nat. Hazards Earth Syst. Sci. 17, 45–59 (2017).Article 

Google Scholar 
Trotta, F. et al. A relocatable ocean modeling platform for downscaling to shelf-coastal areas to support disaster risk reduction. Front. Mar. Sci. 8, 103 (2021).Article 

Google Scholar 
Artegiani, A. et al. The Adriatic Sea general circulation. Part I: Air-sea interactions and water mass structure. J. Phys. Oceanogr. 27, 1492–1514 (1997).Article 

Google Scholar 
Artegiani, A. et al. The Adriatic Sea general circulation. Part II: Baroclinic circulation structure. J. Phys. Oceanogr. 27, 1515–1532 (1997).Article 

Google Scholar 
Cushman-Roisin, B., Gacić, M., Poulain, P. M. & Artegiani, A. Physical Oceanography of the Adriatic Sea (2001).Escudier, R. et al. Mediterranean sea production centre MEDSEA_MULTIYEAR_PHY_006_004 (2021).Clementi, E. et al. Mediterranean sea physical analysis and forecast (CMEMS MED-Currents, EAS6 system) (Version 1) set. In Copernicus Monitoring Environment Marine Service (CMEMS) (2021).Madec, G. NEMO Ocean Engine (2008).Dobricic, S. & Nadia, P. An oceanographic three-dimensional variational data assimilation scheme. Ocean Model 22, 89–105 (2008).Article 

Google Scholar 
Roquet, F., Madec, G., McDougall, T. J. & Barker, P. M. Accurate polynomial expressions for the density and specific volume of seawater using the TEOS-10 standard. Ocean Model 90, 29–43 (2015).Article 

Google Scholar 
IOC, SCOR & IAPSO. In The International Thermodynamic Equation of Seawater—2010: Calculation and Use of Thermodynamic Properties 196 (2010).MEDSEA_MULTIYEAR_BGC_006_008 (2020).Mediterranean Sea Monthly and Daily Reprocessed Surface Chlorophyll Concentration from Multi Satellite observations + SeaWiFS daily climatology (2020).Volpe, G. et al. Mediterranean ocean colour Level 3 operational multi-sensor processing. Ocean Sci. 25, 1527–1532 (2019).
Google Scholar 
Berthon, J.-F. & Zibordi, G. Bio-optical relationships for the northern Adriatic Sea. Int. J. Remote Sens. 25, 1527–1532 (2004).Article 

Google Scholar 
De Dominicis, M. et al. A relocatable ocean model in support of environmental emergencies. Ocean Dyn. 64, 667–688 (2014).Article 

Google Scholar 
Freund, Y. & Schapire, R. E. A decision-theoretic generalization of on-line learning and an application to boosting. J. Comput. Syst. Sci. 55, 119–139 (1997).Article 
MathSciNet 
MATH 

Google Scholar 
Wu, J. et al. Hyperparameter optimization for machine learning models based on bayesian optimizationb. J. Electron. Sci. Technol. 17, 26–40 (2019).
Google Scholar 
Yang, L. & Shami, A. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing 415, 295–316 (2020).Article 

Google Scholar  More

Shaw, J., Weyrich, L. & Cooper, A. Using environmental (e)DNA sequencing for aquatic biodiversity surveys: A beginner’s guide. Mar. Freshw. Res. 68, 68 (2016).
Google Scholar 
Smith, K. J. et al. Stable isotope analysis of specimens of opportunity reveals ocean-scale site fidelity in an elusive whale species. Front. Conserv. Sci. 2, 1–11 (2021).Article 

Google Scholar 
Coll, M. et al. The biodiversity of the Mediterranean Sea: Estimates, patterns, and threats. PLoS One 5, (2010).Cavanagh, R. D. & Gibson, C. Overview of the conservation status of cartilaginous fishes (Chondrichthyans) in the Mediterranean Sea. https://doi.org/10.2305/iucn.ch.2007.mra.3.en (2007).Pace, D. S., Tizzi, R. & Mussi, B. Cetaceans value and conservation in the Mediterranean Sea. Journal Biodivers. Endanger. Species S1:
S1.004 (2015).Carlucci, R. et al. Modeling the spatial distribution of the striped dolphin (Stenella coeruleoalba) and common bottlenose dolphin (Tursiops truncatus) in the Gulf of Taranto (Northern Ionian Sea, Central-eastern Mediterranean Sea). Ecol. Indic. 69, 707–721 (2016).Article 

Google Scholar 
Boldrocchi, G. et al. Distribution, ecology, and status of the white shark, Carcharodon carcharias, in the Mediterranean Sea. Rev. Fish Biol. Fish. 27, 515–534 (2017).Article 

Google Scholar 
Karamanlidis, A. A. et al. The Mediterranean monk seal Monachus monachus: Status, biology, threats, and conservation priorities. Mammal Review 46, 92–105. https://doi.org/10.1111/mam.12053 (2016).Article 

Google Scholar 
Johnson, W. M. The role of the Mediterranean monk seal (Monachus monachus) in European history and culture, from the fall of Rome to the 20th century Monk Seals in Post-Classical History. (2004).Johnson, W. M. & Lavigne, D. M. The Mediterranean Monk Seal (Monachus monachus) in Ancient History and Literature Monk Seals in Antiquity. (1999).Israëls, l. D. Thirty Years of Mediterranean Monk Seal Protection – A Review. Netherlands Com- Mission Int. Nat. Prot. Inst. voor Taxon. Zoölogie/Zoölogische Museum, Univ. van Amsterdam, Amsterdam, Netherlands. Meded. No. 281–65. (1992).Stringer, C. B. et al. Neanderthal exploitation of marine mammals in Gibraltar. Proc. Natl. Acad. Sci. U. S. A. 105, 14319–14324 (2008).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
La Mesa, G., Lauriano, G., Mo, G., Paglialonga, A. & Tunesi, L. Assessment of the conservation status of marine species of the Habitats Directive (92/43/EEC) in Italy: results, drawbacks and perspectives of the fourth national report (2013–2018). Biodivers Conserv (2021).Adamantopoulou, S., Karamanlidis, A. A., Dendrinos, P. & Gimenez, O. Citizen science indicates significant range recovery and defines new conservation priorities for Earth’s most endangered pinniped in Greece. Anim. Conserv. https://doi.org/10.1111/acv.12806 (2022).Article 

Google Scholar 
Nicolaou, H., Dendrinos, P., Marcou, M., Michaelides, S. & Karamanlidis, A. A. Re-establishment of the Mediterranean monk seal Monachus monachus in Cyprus: Priorities for conservation. Oryx 55, 526–528 (2021).Article 

Google Scholar 
Tenan, S. et al. Evaluating mortality rates with a novel integrated framework for nonmonogamous species. Conserv. Biol. 30, 1307–1319 (2016).Article 
PubMed 

Google Scholar 
Vanpe, C. et al. Estimating abundance of a recovering transboundary brown bear population with capture- recapture models. Peer Community Journal, 2, e71. (2022).Lecaudey, L. A., Schletterer, M., Kuzovlev, V. V., Hahn, C. & Weiss, S. J. Fish diversity assessment in the headwaters of the Volga River using environmental DNA metabarcoding. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 1785–1800 (2019).Article 

Google Scholar 
Itakura, H. et al. Environmental DNA analysis reveals the spatial distribution, abundance, and biomass of Japanese eels at the river-basin scale. Aquat. Conserv. Mar. Freshw. Ecosyst. 29, 361–373 (2019).Article 

Google Scholar 
Closek, C. J. et al. Marine vertebrate biodiversity and distribution within the central California current using environmental DNA (eDNA) metabarcoding and ecosystem surveys. Front. Mar. Sci. Vol. 6. (2019).Boldrocchi, G. & Storai, T. Data-mining social media platforms highlights conservation action for the Mediterranean Critically Endangered blue shark Prionace glauca. Aquat. Conserv. Mar. Freshw. Ecosyst. 31, 3087–3099 (2021).Article 

Google Scholar 
Thiel, M. et al. Citizen scientists and marine research: Volunteer participants, their contributions, and projection for the future. Oceanogr. Mar. Biol. An Annu. Rev. 52, 257–314 (2014).
Google Scholar 
Araujo, G. et al. Citizen science sheds light on the cryptic ornate eagle ray Aetomylaeus vespertilio. Aquat. Conserv. Mar. Freshw. Ecosyst. 30, 2012–2018 (2020).Article 

Google Scholar 
Silvertown, J. A new dawn for citizen science. Trends Ecol. Evol. 24, 467–471 (2009).Article 
PubMed 

Google Scholar 
Dickinson, J. L., Zuckerberg, B. & Bonter, D. N. Citizen science as an ecological research tool: Challenges and benefits. Annu. Rev. Ecol. Evol. Syst. 41, 149–172 (2010).Article 

Google Scholar 
Barnes, M. A. et al. Environmental conditions influence eDNA persistence in aquatic systems. Environ. Sci. Technol. 48, (2014).Strickler, K. M., Fremier, A. K. & Goldberg, C. S. Quantifying effects of UV-B, temperature, and pH on eDNA degradation in aquatic microcosms. Biol. Conserv. 183, 85–92 (2015).Article 

Google Scholar 
Eichmiller, J., Best, S. E. & Sorensen, P. W. Effects of temperature and trophic state on degradation of environmental DNA in lake water. Environ. Sci. Technol. https://doi.org/10.1021/acs.est.5b05672 (2016).Article 
PubMed 

Google Scholar 
Mächler, E., Osathanunkul, M. & Altermatt, F. Shedding light on eDNA: neither natural levels of UV radiation nor the presence of a filter feeder affect eDNA-based detection of aquatic organisms. PLoS ONE 13, 1–15 (2018).Article 

Google Scholar 
Jo, T., Murakami, H., Yamamoto, S., Masuda, R. & Minamoto, T. Effect of water temperature and fish biomass on environmental DNA shedding, degradation, and size distribution. Ecol. Evol. 9, 1135–1146 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Mauvisseau, Q. et al. The multiple states of environmental DNA and what is known about their persistence in aquatic environments. Environ. Sci. Technol. 56, 5322–5333 (2022).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Valsecchi, E. et al. A species – specific qPCR assay provides novel insight into range expansion of the Mediterranean monk seal (Monachus monachus ) by means of eDNA analysis. Biodivers. Conserv. 31, 1175–1196 (2022).Article 

Google Scholar 
Collins, R. A. et al. Persistence of environmental DNA in marine systems. Commun. Biol. https://doi.org/10.1038/s42003-018-0192-6 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Zhao, B., P.M., B. & Timbros, K. The particle size distribution of environmental DNA varies with species and degradation. Sci. Total Environ. 797, 149175 (2021).Würtz, M. Mediterranean submarine canyons. in Ecology and Governance (ed. IUCN) 192 (2012).Valsecchi, E. et al. Ferries and environmental DNA: Underway sampling from commercial vessels provides new opportunities for systematic genetic surveys of marine biodiversity. Front. Mar. Sci. 8, 1–17 (2021).Article 

Google Scholar 
Bustin, S. A. et al. The MIQE guidelines: Minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 622, 611–622 (2009).Article 

Google Scholar 
Klymus, K. E. et al. Reporting the limits of detection and quantification for environmental DNA assays. Environ. DNA 1–12. https://doi.org/10.1002/edn3.29 (2019).Goldberg, G. et al. Critical considerations for the application of environmental DNA methods to detect aquatic species. Methods Ecol. Evol. 1299–1307. https://doi.org/10.1111/2041-210X.12595 (2016).Farrell, J. A. et al. Detection and population genomics of sea turtle species via noninvasive environmental DNA analysis of nesting beach sand tracks and oceanic water. Mol. Ecol. Resour. (2022).Shamblin, B. M. et al. Loggerhead turtle eggshells as a source of maternal nuclear genomic DNA for population genetic studies. Mol. Ecol. Resour. 11, 110–115 (2011).Article 
PubMed 

Google Scholar 
MacKenzie, D. I. et al. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83, 2248–2255 (2002).Article 

Google Scholar 
White, G. C. & Burnham, K. P. Program MARK: survival estimation from populations of marked animals. Bird Study 37–41 (1999).Akaike, H. Information theory and an extension of the maximum likelihood principle in Breakthroughs in Statistics, Vol.I, Foundations and Basic Theory, (eds. Kotz, S. and Johnson, N.L.) 610–624 (Springer-Verlag, New York, 1992).Adamantopoulou, S. et al. Movements of Mediterranean Monk Seals (Monachus monachus) in the Eastern Mediterranean Sea. Aquat. Mamm. 37, 256–261 (2011).Article 

Google Scholar  More

In this study, we provide the first description of the bacterial communities of cryoconite holes from South American glaciers, in particular from both small high-elevation glaciers of the Central Andes in the Santiago Metropolitan Region (Chile), and from the tongues of two large glaciers in Patagonian Andes that reach low altitudes. These pieces of information fill a large geographical gap in our knowledge of glacier environments because this is the first description of the microbial communities of supraglacial environments in South America, a continent with about 30,000 km2 covered by ice29. Results showed that the large Patagonian glaciers (Exploradores and Perito Moreno) had the highest oxygen concentrations, while Iver and East Iver had the lowest ones and Morado an intermediate value. This pattern could be related to the different altitudes of the glaciers. Indeed, since water temperature in cryoconite holes is always quite low and stable at all altitudes, oxygen solubility in these environments is related to the atmospheric partial pressure of oxygen that decreases at increasing altitude30. This result is consistent with [O2] values we found in our samples. Indeed, Exploradores and Perito Moreno are located in Patagonia at low altitudes ( 40%), whereas mining is also an additional important black carbon source50. Their similarity can therefore derive also from being exposed to the same general ecological conditions, including high UV radiation, oxidative stress, anthropic pressures, and probably, also from similar sources of bacteria. These results therefore highlight that correlative studies like the present ones can hardly disentangle the effects of geographical positions and ecological conditions on the structure of cryoconite hole bacterial communities, and further studies should be designed to add insight into this still open question.Analyses of alpha diversity indices indicated that cryoconite holes on Exploradores glacier showed the highest richness and evenness. Samples on the Exploradores were collected close to the glacier terminus, surrounded by a rich evergreen broadleaf vegetation, and in an area with abundant supraglacial debris and frequented by tourists. The higher biodiversity of this large, low-altitude glacier, compared to that of the small, high-altitude Iver and East Iver glaciers is not surprising, as the rich evergreen broadleaf forest that surrounds the tongue of the first glacier can be the source of a richer and more diverse bacterial community than the bare ground surrounding the other ones. However, it is more surprising that the alpha biodiversity of the large, low-altitude Perito Moreno was intermediate and similar to that of the Morado glacier. Interestingly, Perito Moreno was the southernmost glacier among those we collected, and was surrounded by a less diverse forest, dominated by southern beeches, Nothofagus ssp. than that of Exploradores, while Morado was the glacier where samples were collected at the lowest altitude among the three glaciers near Santiago. We may therefore speculate that a broad gradient related to altitude and general climate conditions of the area surrounding the glacier may somehow affect its biodiversity. For instance, among the most abundant orders, Cytophagales were more abundant on high than on low-elevation glaciers (Fig. 5b). A similar pattern was observed for the Micrococcales and Chitinophagales (Fig. 5c–k) with the only exception of Iver.In summary, we provide the first-ever description of the bacterial communities of cryoconite holes of glaciers in South America, specifically in the Southern Andes. This study thus fills an important gap of knowledge as almost no information was previously available on the cryoconite holes of this continent, and opens the possibility of future biogeography analyses including samples from almost every important glacial area of the world. The five glaciers we investigated are still a too small sample for thoroughly assessing the ecological processes that control cryoconite hole bacterial communities, and a larger set of environmental variables should also be considered, but we hope this study can be the basis for further investigations aiming at a deeper understanding of these extreme environments. More

Bradshaw, W. E. & Holzapfel, C. M. Evolution of animal photoperiodism. Annu. Rev. Ecol. Evol. System. 2007, 1–25 (2007).Article 

Google Scholar 
Way, M., Hopkins, B. & Smith, P. Photoperiodism and diapause in insects. Nature 164, 615–615 (1949).Article 
ADS 
CAS 
PubMed 

Google Scholar 
Bromage, N., Porter, M. & Randall, C. Reproductive Biotechnology in Finfish Aquaculture 63–98 (Elsevier, 2001).Book 

Google Scholar 
Weil, Z. M. & Crews, D. Photoperiodism in Amphibians and Reptiles (ed. Nelson, R. J. et al.) 399–419 (Oxford University Press, 2010).Vera, L., Davie, A., Taylor, J. & Migaud, H. Differential light intensity and spectral sensitivities of Atlantic salmon, European sea bass and Atlantic cod pineal glands ex vivo. Gen. Comp. Endocrinol. 165, 25–33 (2010).Article 
CAS 
PubMed 

Google Scholar 
Smith, K. A., Schoen, M. W. & Czeisler, C. A. Adaptation of human pineal melatonin suppression by recent photic history. J. Clin. Endocrinol. Metabol. 89, 3610–3614 (2004).Article 
CAS 

Google Scholar 
Refinetti, R. Enhanced circadian photoresponsiveness after prolonged dark adaptation in seven species of diurnal and nocturnal rodents. Physiol. Behav. 90, 431–437 (2007).Article 
CAS 
PubMed 

Google Scholar 
Chang, A.-M., Scheer, F. A. & Czeisler, C. A. The human circadian system adapts to prior photic history. J. Physiol. 589, 1095–1102 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Aschoff, J. & Daan, S. Human time perception in temporal isolation: Effects of illumination intensity. Chronobiol. Int. 14, 585–596 (1997).Article 
CAS 
PubMed 

Google Scholar 
Tast, A. et al. The photophase light intensity does not affect the scotophase melatonin response in the domestic pig. Anim. Reprod. Sci. 65, 283–290 (2001).Article 
CAS 
PubMed 

Google Scholar 
Migaud, H. et al. A comparative ex vivo and in vivo study of day and night perception in teleosts species using the melatonin rhythm. J. Pineal Res. 41, 42–52 (2006).Article 
CAS 
PubMed 

Google Scholar 
Nisembaum, L. G., Martin, P., Lecomte, F. & Falcón, J. Melatonin and osmoregulation in fish: A focus on Atlantic salmon Salmo salar smoltification. J. Neuroendocrinol. 33, e12955 (2021).Article 
CAS 
PubMed 

Google Scholar 
Iigo, M. et al. Lack of circadian regulation of in vitro melatonin release from the pineal organ of salmonid teleosts. Gen. Comp. Endocrinol. 154, 91–97 (2007).Article 
CAS 
PubMed 

Google Scholar 
Iigo, M., Azuma, T. & Iwata, M. Lack of circadian regulation of melatonin rhythms in the sockeye salmon (Oncorhynchus nerka) in vivo and in vitro. Zool. Sci. 24, 67–70 (2007).Article 
CAS 

Google Scholar 
Huang, T., Ruoff, P. & Fjelldal, P. G. Diurnal expression of clock genes in pineal gland and brain and plasma levels of melatonin and cortisol in Atlantic salmon parr and smolts. Chronobiol. Int. 27, 1697–1714 (2010).Article 
CAS 
PubMed 

Google Scholar 
Fjelldal, P. G., Hansen, T. & Huang, T. Continuous light and elevated temperature can trigger maturation both during and immediately after smoltification in male Atlantic salmon (Salmo salar). Aquaculture 321, 93–100 (2011).Article 

Google Scholar 
Leclercq, E., Taylor, J., Sprague, M. & Migaud, H. The potential of alternative lighting-systems to suppress pre-harvest sexual maturation of 1+ Atlantic salmon (Salmo salar) post-smolts reared in commercial sea-cages. Aquacult. Eng. 44, 35–47 (2011).Article 

Google Scholar 
Fjelldal, P. G. et al. Development of supermale and all-male Atlantic salmon to research the vgll3 allele-puberty link. BMC Genet. 21, 1–13 (2020).Article 

Google Scholar 
Ricker, W. E. Computation and interpretation of biological statistics of fish populations. Bull. Fisher. Res. 191, 1–382 (1975).
Google Scholar 
Fjelldal, P. G. et al. Sexual maturation and smoltification in domesticated Atlantic salmon (Salmo salar L.)-is there a developmental conflict?. Physiol. Rep. 6, e13809 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for. R J. 9, 378–400 (2017).Article 

Google Scholar 
Lenth, R. emmeans: Estimated Marginal Means, Aka Least-Squares Means. R package version 1. 4. 3. 01 (2019).Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
Huang, T., Ruoff, P. & Fjelldal, P. G. Effect of continuous light on daily levels of plasma melatonin and cortisol and expression of clock genes in pineal gland, brain, and liver in Atlantic salmon postsmolts. Chronobiol. Int. 27, 1715–1734 (2010).Article 
CAS 
PubMed 

Google Scholar 
Davie, A., Minghetti, M. & Migaud, H. Seasonal variations in clock-gene expression in Atlantic salmon (Salmo salar). Chronobiol. Int. 26, 379–395 (2009).Article 
CAS 
PubMed 

Google Scholar 
Max, M. & Menaker, M. Regulation of melatonin production by light, darkness, and temperature in the trout pineal. J. Comp. Physiol. Part A 170, 479–489 (1992).CAS 

Google Scholar 
Randall, C. & Bromage, N. Photoperiodic history determines the reproductive response of rainbow trout to changes in daylength. J. Comp. Physiol. Part A 183, 651–660 (1998).Article 

Google Scholar 
Randall, C., Bromage, N., Duston, J. & Symes, J. Photoperiod-induced phase-shifts of the endogenous clock controlling reproduction in the rainbow trout: A circannual phase-response curve. Reproduction 112, 399–405 (1998).Article 
CAS 

Google Scholar 
Duston, J. & Bromage, N. Photoperiodic mechanisms and rhythms of reproduction in the female rainbow trout. Fish Physiol. Biochem. 2, 35–51 (1986).Article 
CAS 
PubMed 

Google Scholar 
Duston, J. & Bromage, N. Circannual rhythms of gonadal maturation in female rainbow trout (Oncorhynchus mykiss). J. Biol. Rhythms 6, 49–53 (1991).Article 
CAS 
PubMed 

Google Scholar 
Taranger, G. L. et al. Abrupt changes in photoperiod affect age at maturity, timing of ovulation and plasma testosterone and oestradiol-17β profiles in Atlantic salmon, Salmo salar. Aquaculture 162, 85–98 (1998).Article 

Google Scholar 
Melo, M. C. et al. Salinity and photoperiod modulate pubertal development in Atlantic salmon (Salmo salar). J. Endocrinol. 220, 319–332 (2014).Article 
CAS 
PubMed 

Google Scholar 
Hansen, T. J., Fjelldal, P. G., Folkedal, O., Vågseth, T. & Oppedal, F. Effects of light source and intensity on sexual maturation, growth and swimming behaviour of Atlantic salmon in sea cages. Aquac. Environ. Interact. 9, 193–204 (2017).Article 

Google Scholar 
Oppedal, F., Taranger, G. L., Juell, J.-E., Fosseidengen, J. E. & Hansen, T. Light intensity affects growth and sexual maturation of Atlantic salmon (Salmo salar) postsmolts in sea cages. Aquat. Living Resour. 10, 351–357 (1997).Article 

Google Scholar 
Harvey, A. C. et al. Inferring Atlantic salmon post-smolt migration patterns using genetic assignment. R. Soc. Open Sci. 6, 190426 (2019).Article 
ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Anderson, J. J., Gurarie, E., Bracis, C., Burke, B. J. & Laidre, K. L. Modeling climate change impacts on phenology and population dynamics of migratory marine species. Ecol. Model. 264, 83–97 (2013).Article 

Google Scholar 
Ljungstrӧm, G., Langbehn, T. J. & Jørgensen, C. Light and energetics at seasonal extremes limit poleward range shifts. Nat. Clim. Chang. 11, 530–536 (2021).Article 
ADS 

Google Scholar 
Naish, K. A. & Hard, J. J. Bridging the gap between the genotype and the phenotype: Linking genetic variation, selection and adaptation in fishes. Fish Fish. 9, 396–422 (2008).Article 

Google Scholar 
Lehnert, S. J. et al. Genomic signatures and correlates of widespread population declines in salmon. Nat. Commun. 10, 1–10 (2019).Article 
CAS 

Google Scholar  More

DEFRA. Strategy for Achieving Officially Bovine Tuberculosis Free Status for England: The ‘edge area’ strategy. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/300447/pb14088-bovine-tb-strategy-140328.pdf (2014).Campbell, E. L. et al. Interspecific visitation of cattle and badgers to fomites: A transmission risk for bovine tuberculosis?. Ecol. Evol. 9(15), 8479–8489 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Roberts, T., O’Connor, C., Nuñez-Garcia, J., De La Rua-Domenech, R. & Smith, N. H. Unusual cluster of Mycobacterium bovis infection in cats. Vet. Rec. 174(13), 326–326 (2014).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Phipps, E. et al. Bovine tuberculosis in working foxhounds: Lessons learned from a complex public health investigation. Epidemiol. Infect. 147, 1–6 (2019).Article 

Google Scholar 
Delahay, R. J., De Leeuw, A. N. S., Barlow, A. M., Clifton-Hadley, R. S. & Cheeseman, C. L. The status of Mycobacterium bovis infection in UK wild mammals: A review. Vet. J. 164(2), 90–105 (2002).Article 
CAS 
PubMed 

Google Scholar 
Fitzgerald, S. D. & Kaneene, J. B. Wildlife reservoirs of bovine tuberculosis worldwide: Hosts, pathology, surveillance, and control. Vet. Pathol. 50(3), 488–499 (2013).Article 
CAS 
PubMed 

Google Scholar 
Skuce, R. A., Allen, A. R. & McDowell, S. W. J. Herd-level risk factors for bovine tuberculosis: A literature review. Vet Med Int 2012, 621210 (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Ayele, W. Y., Neill, S. D., Zinsstag, J., Weiss, M. G. & Pavlik, I. Bovine tuberculosis: An old disease but a new threat to Africa. Int. J. Tuberc. Lung Dis. 8(8), 924–937 (2004).CAS 
PubMed 

Google Scholar 
Gallagher, J. & Clifton-Hadley, R. S. Tuberculosis in badgers; a review of the disease and its significance for other animals. Res. Vet. 69(3), 203–217 (2000).Article 
CAS 

Google Scholar 
Allen, A. et al. Genome epidemiology of Mycobacterium bovis infection in contemporaneous, sympatric badger and cattle populations in Northern Ireland. Access Microbiol. 1(1A), 385 (2019).Article 

Google Scholar 
APHA. Bovine Tuberculosis in England in 2020—Epidemiological analysis of the 2020 data and historical trends. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1027591/tb-epidemiological-report-2020.pdf (2021).DAERA. Tuberculosis disease statistics in Northern Ireland 2022. https://www.daera-ni.gov.uk/publications/tuberculosis-disease-statistics-northern-ireland-2022 (2022).Woodroffe, R. et al. Effects of culling on badger Meles meles spatial organization: Implications for the control of bovine tuberculosis. J. Appl. Ecol. 43(1), 1–10 (2006).Article 

Google Scholar 
Byrne, A. W., Paddy Sleeman, D., O’Keeffe, J. & Davenport, J. The ecology of the European badger (Meles meles) in Ireland: A review. Biol. Environ. 112, 105–132 (2012).Article 

Google Scholar 
McDonald, J., Robertson, A. & Silk, M. Wildlife disease ecology from the individual to the population: Insights from a long-term study of a naturally infected European badger population. J. Anim. Ecol. 87(1), 101–112 (2017).Article 
PubMed 

Google Scholar 
Macdonald, D. W., Newman, C. & Buesching, C. D. Badgers in the rural landscape—conservation paragon or farmland pariah? Lessons from the Wytham Badger Project. Wildlife conservation on farmland 2, 65–95 (2015).
Google Scholar 
Judge, J., Wilson, G. J., Macarthur, R., McDonald, R. A. & Delahay, R. J. Abundance of badgers (Meles meles) in England and Wales. Sci. Rep. 7(1), 1–8 (2017).Article 
CAS 

Google Scholar 
Feore, S. & Montgomery, W. I. Habitat effects on the spatial ecology of the European badger (Meles meles). J. Zool. 247(4), 537–549 (1999).Article 

Google Scholar 
Reid, N., Etherington, T. R., Wilson, G. J., Montgomery, W. I. & McDonald, R. A. Monitoring and population estimation of the European badger Meles meles in Northern Ireland. Wildlife Biol. 18(1), 46–57 (2012).Article 

Google Scholar 
DAERA. Farm animal populations: Cattle populations in Northern Ireland from 1981 to 2019. https://www.daera-ni.gov.uk/publications/farm-animal-population-data (2019).DEFRA. Livestock numbers in the UK (data to December 2019). https://www.gov.uk/government/statistical-data-sets/structure-of-the-livestock-industry-in-england-at-december.39 (2020).DEFRA. Setting the minimum and maximum numbers in badger cull areas in 2021—Advice to Natural England. https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1015421/tb-min-max-numbers-2021.pdf (2021).Griffin, J. M. et al. The impact of badger removal on the control of tuberculosis in cattle herds in Ireland. Prev. Vet. Med. 67(4), 237–266 (2005).Article 
CAS 
PubMed 

Google Scholar 
Ham, C., Donnelly, C. A., Astley, K. L., Jackson, S. Y. B. & Woodroffe, R. Effect of culling on individual badger Meles meles behaviour: Potential implications for bovine tuberculosis transmission. J. Appl. Ecol. 56(11), 2390–2399 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Olea-Popelka, F. J. et al. Targeted badger removal and the subsequent risk of bovine tuberculosis in cattle herds in county Laois, Ireland. Prev. Vet. Med. 88(3), 178–184 (2009).Article 
CAS 
PubMed 

Google Scholar 
Donnelly, C. A. et al. Positive and negative effects of widespread badger culling on tuberculosis in cattle. Nature 439(7078), 843–846 (2006).Article 
CAS 
PubMed 

Google Scholar 
Byrne, A. W., White, P. W., McGrath, G., O’Keeffe, J. & Martin, S. W. Risk of tuberculosis cattle herd breakdowns in Ireland: Effects of badger culling effort, density and historic large-scale interventions. Vet. Res. 45(1), 1–10 (2014).Article 

Google Scholar 
Wright, D. M. et al. Herd-level bovine tuberculosis risk factors: Assessing the role of low-level badger population disturbance. Sci. Rep. 5, 1–11 (2015).Article 

Google Scholar 
Jenkins, H. E., Woodroffe, R. & Donnelly, C. A. The duration of the effects of repeated widespread badger culling on cattle tuberculosis following the cessation of culling. PLoS ONE 5(2), e9090 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Tuyttens, F. A. M. et al. Spatial perturbation caused by a badger (Meles meles) culling operation: Implications for the function of territoriality and the control of bovine tuberculosis (Mycobacterium bovis). J. Anim. Ecol. 69(5), 815–828 (2000).Article 
CAS 
PubMed 

Google Scholar 
Carter, S. P. et al. Culling-induced social perturbation in Eurasian badgers Meles meles and the management of TB in cattle: An analysis of a critical problem in applied ecology. Proc. R. Soc. B. 274(1626), 2769–2777 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
Donnelly, C. A. et al. Impact of localized badger culling on tuberculosis incidence in British cattle. Nature 426(6968), 834–837 (2003).Article 
CAS 
PubMed 

Google Scholar 
Vicente, J., Delahay, R. J., Walker, N. J. & Cheeseman, C. L. Social organization and movement influence the incidence of bovine tuberculosis in an undisturbed high-density badger Meles meles population. J Anim Ecol. 76(2), 348–360 (2007).Article 
CAS 
PubMed 

Google Scholar 
Riordan, P., Delahay, R. J., Cheeseman, C., Johnson, P. J. & Macdonald, D. W. Culling-induced changes in badger (Meles meles) behaviour, social organisation and the epidemiology of bovine tuberculosis. PLoS ONE 6(12), e28904 (2011).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Kowalczyk, R., Jȩdrzejewska, B. & Zalewski, A. Annual and circadian activity patterns of badgers (Meles meles) in Białowieża Primeval Forest (eastern Poland) compared with other palaearctic populations. J. Biogeogr. 30(3), 463–472 (2003).Article 

Google Scholar 
Smith, G. C., Delahay, R. J., McDonald, R. A. & Budgey, R. Model of selective and non-selective management of badgers (Meles meles) to control bovine tuberculosis in badgers and cattle. PLoS ONE 11(11), e0167206 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Garnett, B. T., Delahay, R. J. & Roper, T. J. Ranging behaviour of European badgers (Meles meles) in relation to bovine tuberculosis (Mycobacterium bovis) infection. Appl. Anim. Behav. Sci. 94(3–4), 331–340 (2005).Article 

Google Scholar 
Weber, N. et al. Badger social networks correlate with tuberculosis infection. Curr. 23(20), 915–916 (2013).Article 

Google Scholar 
Ellwood, S. A. et al. An active-radio-frequency-identification system capable of identifying co-locations and social-structure: Validation with a wild free-ranging animal. Methods Ecol. Evol. 8(12), 1822–1831 (2017).Article 

Google Scholar 
Noonan, M. et al. A new Magneto-Inductive tracking technique to uncover subterranean activity: what do animals do underground?. Methods Ecol. Evol. 6(5), 510–520 (2015).Article 

Google Scholar 
Schütz, K. et al. Behavioral and physiological responses of trap-induced stress in European badgers. J. Wildl. Manag. 70(3), 884–891 (2006).Article 

Google Scholar 
Clinchy, M. et al. Fear of the human “super predator” far exceeds the fear of large carnivores in a model mesocarnivore. Behav. Ecol. 27(6), 1826–1832 (2016).
Google Scholar 
Bidder, O. R. et al. Step by step: Reconstruction of terrestrial animal movement paths by dead-reckoning. Mov. Ecol. https://doi.org/10.1186/s40462-015-0055-4 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Gunner, R. M. et al. Dead-reckoning animal movements in R: a reappraisal using Gundog. Tracks. Anim. Biotelem. 9(1), 1–37 (2021).
Google Scholar 
McClune, D. W., Marks, N. J., Delahay, R. J., Montgomery, W. I. & Scantlebury, D. M. Behaviour-time budget and functional habitat use of a free-ranging European badger (Meles meles). Anim. Biotelem. 3(7), 1–7 (2015).
Google Scholar 
McClune, D. et al. Tri-axial accelerometers quantify behaviour in the Eurasian badger (Meles meles): towards an automated interpretation of field data. Anim. Biotelem. 2(1), 1–6 (2014).Article 

Google Scholar 
Gaughran, A. et al. Dispersal patterns in a medium-density Irish badger population: Implications for understanding the dynamics of tuberculosis transmission. Ecol. Evol. 9(23), 13142–13152 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Kelly, D. J. et al. Extra Territorial Excursions by European badgers are not limited by age, sex or season. Sci. Rep. 10(1), 1–2 (2020).Article 

Google Scholar 
Macdonald, D. W., Newman, C., Buesching, C. D. & Johnson, P. J. Male-biased movement in a high-density population of the Eurasian badger (Meles meles). J. Mammal. 89(5), 1077–1086 (2008).Article 

Google Scholar 
Courcier, E. A. et al. Evaluating the application of the dual path platform VetTB test for badgers (Meles meles) in the test and vaccinate or remove (TVR) wildlife research intervention project in Northern Ireland. Res. Vet. Sci. 130, 170–178 (2020).Article 
CAS 
PubMed 

Google Scholar 
Menzies, F. D. et al. Test and vaccinate or remove: Methodology and preliminary results from a badger intervention research project. Vet. Rec. 189, e248 (2021).Article 
PubMed 

Google Scholar 
O’Hagan, M. J. H. et al. Effect of selective removal of badgers (Meles meles) on ranging behaviour during a “test and Vaccinate or Remove” intervention in Northern Ireland. Epidemiol. Infect. 149(1), e125 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Roper, T. J. The structure and function of badger setts. J. Zool. 227(4), 691–698 (1992).Article 

Google Scholar 
DAERA. The Test and Vaccinate or Remove (TVR) Wildlife Intervention Research Project. Year 1 Report—2014. https://www.daera-ni.gov.uk/sites/default/files/publications/dard/tvr-year-1-report.pdf (2014).Brown, E., Cooney, R. & Rogers, F. Veterinary guidance on the practical use of the BadgerBCG tuberculosis vaccine. In Pract. 35(3), 143–146 (2013).Article 

Google Scholar 
Magowan, E. A. et al. Dead-reckoning elucidates fine-scale habitat use by European badgers Meles meles. Anim. Biotelem. 10(1), 1–11 (2022).Article 

Google Scholar 
McGill, K. et al. Seroconversion against antigen MPB83 in badgers (Meles meles) vaccinated with multiple doses of BCG strain Sofia. Res. Vet. Sci. 149, 119–124. https://doi.org/10.1016/j.rvsc.2022.06.011 (2022).Article 
CAS 
PubMed 

Google Scholar 
Gaughran, A. et al. Super-ranging. A new ranging strategy in European badgers. PLoS ONE 13(2), e0191818 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Williams, H. J. et al. Identification of animal movement patterns using tri-axial magnetometry. Mov. Ecol. 5(1), 6 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Brendel C, Helder R, Chevallier D, Zaytoon J, Georges JY, and Handrich Y. Testing a global positioning system on free ranging badgers Meles meles. Mammal Notes, The Mammal Society, Southampton. https://www.mammal.org.uk/wp-content/uploads/2016/04/Note–Brendel-MN-2012-1.pdf (2012).Börger, L. et al. Effects of sampling regime on the mean and variance of home range size estimates. J. Anim. Ecol. 75(6), 1393–1405 (2006).Article 
PubMed 

Google Scholar 
Calenge, C. The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals. Ecol. Modell. 197(3–4), 516–519 (2006).Article 

Google Scholar 
Calabrese, J. M., Fleming, C. H. & Gurarie, E. ctmm: An r package for analyzing animal relocation data as a continuous-time stochastic process. Methods Ecol. Evol. 7(9), 1124–1132 (2016).Article 

Google Scholar 
QGIS.org. QGIS Geographic Information System. QGIS Association. https://qgis.org/en/site/ (2021).Fleming, C. H. et al. Rigorous home range estimation with movement data: A new autocorrelated kernel density estimator. Ecology 96(5), 1182–1188 (2015).Article 
CAS 
PubMed 

Google Scholar 
Fleming, C. H. et al. Estimating where and how animals travel: An optimal framework for path reconstruction from autocorrelated tracking data. Ecology 97(3), 576–582 (2016).CAS 
PubMed 

Google Scholar 
Fleming, C. H. et al. Correcting for missing and irregular data in home-range estimation. Ecol. Appl. 28(4), 1003–1010 (2018).Article 
CAS 
PubMed 

Google Scholar 
Gula, R. & Theuerkauf, J. The need for standardization in wildlife science: Home range estimators as an example. Eur. J. Wildl. Res. 59, 713–718 (2013).Article 

Google Scholar 
Schuler, K. L., Schroeder, G. M., Jenks, J. A. & Kie, J. G. Ad hoc smoothing parameter performance in kernel estimates of GPS-derived home ranges. Wildl. Biol. 20(5), 259–266 (2014).Article 

Google Scholar 
Huck, M., Davison, J. & Roper, T. J. Comparison of two sampling protocols and four home-range estimators using radio-tracking data from urban badgers Meles meles. Wildl. Biol. 14(4), 467–477 (2008).Article 

Google Scholar 
Scull, P., Palmer, M., Frey, F. & Kraly, E. A comparison of two home range modeling methods using Ugandan mountain gorilla data. Int. J. Geogr. Inf. Sci. 26(11), 2111–2121 (2012).Article 

Google Scholar 
Woodroffe, R. et al. Ranging behaviour of badgers Meles meles vaccinated with Bacillus Calmette Guerin. J. Appl. Ecol. 54(3), 718–725 (2017).Article 

Google Scholar 
Signer, J. & Fieberg, J. R. A fresh look at an old concept: Home-range estimation in a tidy world. PeerJ 9, e11031 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Woodroffe, R. et al. Badgers prefer cattle pasture but avoid cattle: implications for bovine tuberculosis control. Ecology 19(10), 1201–1208 (2016).
Google Scholar 
Hijmans RJ. Introduction to the geosphere package (version 1 .5–10). Cran (2019).Dewhirst, O. P. et al. Improving the accuracy of estimates of animal path and travel distance using GPS drift-corrected dead reckoning. Ecol. Evol. 6(17), 6210–6222 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
QGIS.org. Working with vector data. QGIS Desktop 3.16 User Guide. pp 304. https://docs.qgis.org/3.22/en/docs/user_manual/index.html (2022).Qasem, L. et al. Tri-axial acceleration as a proxy for animal energy expenditure; should we be summing values or calculating the vector?. PLoS ONE 7(2), e31187 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Wilson, R. P. et al. Estimates for energy expenditure in free-living animals using acceleration proxies; a reappraisal. J anim Ecol. 89(1), 161–172 (2020).Article 
PubMed 

Google Scholar 
RStudio Team. RStudio: Integrated Development for R. RStudio, PBC, Boston, MA http://www.rstudio.com/ (2021).Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67(1), 1–48. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
Barton K. Package “MuMin”. Cran (2018).Rogers, L. M., Cheeseman, C. L., Mallinson, P. J. & Clifton-Hadley, R. The demography of a high-density badger (Meles meles) population in the west of England. J. Zool. 242(4), 705–728 (1997).Article 

Google Scholar 
Macdonald, D. W. & Newman, C. Population dynamics of badgers (Meles meles) in Oxfordshire, UK: Numbers, density and cohort life histories, and a possible role of climate change in population growth. J. Zool. 256(1), 121–138 (2002).Article 

Google Scholar 
Kruuk, H., & MacDonald, D. Group territories of carnivores: empires and enclaves. In 25th Symposium of the British Ecological Society (1985).Roper, T. J., Shepherdson, D. J. & Davies, J. M. Scent marking with faeces and anal secretion in the European badger (Meles meles): seasonal and spatial characteristics of latrine use in relation to territoriality. Behaviour 97(1–2), 94–117 (1986).
Google Scholar 
Sleeman, D. P. et al. How many Eurasian badgers Meles meles L. are there in the republic of Ireland?. Eur. J. Wildl. Res. 55(4), 333–344 (2009).Article 

Google Scholar 
Carter, S. P. et al. BCG vaccination reduces risk of tuberculosis infection in vaccinated badgers and unvaccinated badger cubs. PLoS ONE 7(12), e49833 (2012).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Byrne, A., Parnell, A., O’Keeffe, J. & Madden, J. The challenge of estimating wildlife populations at scale: the case of the European badger (Meles meles) in Ireland. Eur. J. Wildl. Res. 67(5), 1–10 (2021).Article 

Google Scholar 
Minta, S. C. Sexual differences in spatio-temporal interaction among badgers. Oecologia 96(3), 402–409 (1993).Article 
PubMed 

Google Scholar 
Annavi, G. et al. Neighbouring-group composition and within-group relatedness drive extra-group paternity rate in the European badger (Meles meles). J. Evol. Biol. 27(10), 2191–2203 (2014).Article 
CAS 
PubMed 
PubMed Central 

Google Scholar 
DEFRA. Monitoring regional changes in badger numbers. Research Project Final Report. http://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=None&ProjectID=14237. Accessed 07 February 2023 (2009).Johnson, D. D., Jetz, W. & Macdonald, D. W. Environmental correlates of badger social spacing across Europe. J. Biogeogr. 29(3), 411–425 (2002).Article 

Google Scholar 
Kruuk, H. Spatial organization and territorial behaviour of the European badger Meles meles. J Zool. 184(1), 1–19 (1978).Article 

Google Scholar 
Macdonald, D., Newman, C., Dean, J., Buesching, C. & Johnson, P. The distribution of Eurasian badger, Meles meles, setts in a high-density area: field observations contradict the sett dispersion hypothesis. Oikos 106(2), 295–307 (2004).Article 

Google Scholar 
Sleeman, D. P. & Mulcahy, M. F. Loss of territoriality in a local badger Meles meles population at Kilmurry, Co Cork, Irealnd. Irish Nat. J. 28(1), 11–19 (2005).
Google Scholar 
Byrne, A. W., O’Keeffe, J., Buesching, C. D. & Newman, C. Push and pull factors driving movement in a social mammal: Context dependent behavioral plasticity at the landscape scale. Curr. Zool. 65(5), 517–525 (2019).Article 
PubMed 

Google Scholar 
Cheeseman, C. L., Cresswell, W. J., Harris, S. & Mallinson, P. J. Comparison of dispersal and other movements in two Badger (Meles meles) populations. Mamm. Rev. 18(1), 51–59 (1988).Article 

Google Scholar 
Seebacher, F. & Krause, J. Epigenetics of social behaviour. TREE 34(9), 818–830 (2019).PubMed 

Google Scholar 
Allen, A. et al. European badger (Meles meles) responses to low-intensity, selective culling: Using mark–recapture and relatedness data to assess social perturbation. Ecol. Solut. Evid. 3(3), e12165 (2022).Article 

Google Scholar 
Loureiro, F., Rosalino, L. M., Macdonald, D. W. & Santos-Reis, M. Path tortuosity of Eurasian badgers (Meles meles) in a heterogeneous Mediterranean landscape. Ecol. Res. 22(5), 837–844 (2007).Article 

Google Scholar 
Sun, Q., Stevens, C., Newman, C., Buesching, C. & Macdonald, D. Cumulative experience, age-class, sex and season affect the behavioural responses of European badgers (Meles meles) to handling and sedation. Anim Welf. 24(4), 373–385 (2015).Article 

Google Scholar 
Conlan, A. et al. Potential benefits of cattle vaccination as a supplementary control for bovine tuberculosis. PLoS Comput. Biol. 11(2), e1004038 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Gormley, E. et al. Oral vaccination of free-living badgers (Meles meles) with Bacille Calmette Guérin (BCG) vaccine confers protection against tuberculosis. PLoS ONE 12(1), e0168851 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Benton, C. H. et al. Badger vaccination in England: Progress, operational effectiveness and participant motivations. People Nat. 2(3), 761–775 (2020).Article 

Google Scholar  More