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    Life cycle of the cold-water coral Caryophyllia huinayensis

    The solitary cold-water scleractinian C. huinayensis is described here as a brooder. Although reproduction in scleractinian CWCs is still poorly known, no other temperate species has yet been described to brood larvae. The solitary temperate CWC D. dianthus12, as well as the temperate colonial CWC D. pertusum8,10,38, M. oculata8,10 and O. varicosa9 reproduce by broadcast spawning. Brooding has only been reported in subpolar and polar solitary CWCs from the Southern Ocean17,18.Although quantitative data on the number of larvae released in the four Southern Ocean brooders are lacking, a potential number of larvae released per polyp can be inferred from their maximum fecundity (Table 1). C. huinayensis appears to be in the lower range of larvae production (6.5 ± 11.4 month-1 larvae), when compared its larval size (750–1080 µm length) with Balanophyllia malouinensis larvae ( > 600 µm, Table 1).Table 1 Larval features of scleractinian CWC species.Full size tableThorson’s rule43,44 states that organisms at higher latitudes tend to produce larger and fewer offspring and are frequently brooders. However, the brooding C. huinayensis appears to defy this rule, as it occurs at mid-latitudes (36° and 48.5° S33,45). Though the phylogeography of C. huinayensis is not yet clear, six other solitary species of the genus Caryophyllia are endemic to Antarctica46, suggesting that the genus may have originated in the Southern Ocean, with the mid-latitude distribution of C. huinayensis making the downstream end dispersal via the cold Humboldt Current branching off the Southern Ocean. In our case, Thorson’s rule does not seem to be a good predictor of the macroevolutionary patterns and reproductive mode in Caryophyllia.A better explanation can be inferred from Kerr et al.47. Their phylogenetic study on scleractinians revealed that the change from spawning to brooding (or vice versa) is based on the sexuality of the corals (i.e., gonochoric or hermaphroditic) and not on latitudinal distribution. The main pathway is from gonochoric spawners to gonochoric brooders, then to hermaphroditic brooders, and finally hermaphroditic spawning, which is the dominant reproductive mode in shallow-water corals.The results of our study indicate that C. huinayensis reproduces throughout the year, albeit with large temporal variations in the number of larvae released. However, the fluctuations were not seasonal. This may be due to the fact that the aquarium for this experiment lacked external timing signals (zeitgebers) usually found in the field, i.e., there were no fluctuations e.g., in water temperature, food frequency, food quality, or salinity, which might otherwise have synchronized the corals’ internal clock. Although, it is not yet known if the local C. huinayensis population exhibits seasonality in their larval release, the lack of larvae in April 2021 could also be due to poor internal fertilisation success based on the quality and/or quantity of sperm released (which was never observed).If there is no seasonal release of larvae from the natural coral population, this may indicate that rapid recolonisation is possible throughout the year following a disturbance. Substrate alterations are usually observed in the Patagonian fjord region, where strong physical disturbances such as landslides occur48, due to precipitation and earthquakes49. Also, hypoxia events ( More

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    Impact of test, vaccinate or remove protocol on home ranges and nightly movements of badgers a medium density population

    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

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    Playing “hide and seek” with the Mediterranean monk seal: a citizen science dataset reveals its distribution from molecular traces (eDNA)

    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

    Adélie penguins north and east of the ‘Adélie gap’ continue to thrive in the face of dramatic declines elsewhere in the Antarctic Peninsula region

    Fraser, W., Trivelpiece, W., Ainley, D. & Trivelpiece, S. Increases in Antarctic penguin populations: Reduced competition with whales or a loss of sea ice due to environmental warming?. Polar Biol. 11, 525–531 (1992).Article 

    Google Scholar 
    Trivelpiece, W. et al. Variability in krill biomass links harvesting and climate warming to penguin population changes in Antarctica. PNAS 108, 7625–7628 (2011).Article 
    CAS 

    Google Scholar 
    Fraser, W. & Hofmann, E. A predator’s perspective on causal links between climate change, physical forcing and ecosystem response. Mar. Ecol. Prog. Ser. 265, 1–15 (2003).Article 

    Google Scholar 
    Hinke, J., Salwicka, K., Trivelpiece, S., Watters, G. & Trivelpiece, W. Divergent responses of Pygoscelis penguins reveal common environmental driver. Oecologia 153, 845–855 (2007).Article 

    Google Scholar 
    Poncet, S. & Poncet, J. Censuses of penguin populations of the Antarctic Peninsula, 1983–87. Br. Antarct. Surv. Bull. 77, 109–129 (1987).
    Google Scholar 
    Fraser, W. R. & Trivelpiece, W. Z. Factors controlling the distribution of seabirds: Winter-summer heterogeneity in the distribution of Adélie penguin populations. Found. For. Ecol. Res. West Antarct. Penins. 70, 257–272 (1996).Article 

    Google Scholar 
    Humphries, G. R. W. et al. Mapping application for penguin populations and projected dynamics (MAPPPD): Data and tools for dynamic management and decision support. Polar Rec. 53, 160–166 (2017).Article 

    Google Scholar 
    Lynch, H., Naveen, R., Trathan, P. N. & Fagan, W. F. Spatially integrated assessment reveals widespread changes in penguin populations on the Antarctic Peninsula. Ecology 93, 1367–1377 (2012).Article 

    Google Scholar 
    Elliot, D. H., Watts, D. R., Alley, R. B. & Gracanin, T. M. Bird and seal observations at Joinville Island and offshore islands. Antarct. J. USA 13, 154–155 (1978).
    Google Scholar 
    Bender, N. A., Crosbie, K. & Lynch, H. Patterns of tourism in the Antarctic Peninsula region: A twenty-year re-analysis. Antarct. Sci. 28, 194–203 (2016).Article 

    Google Scholar 
    Lynch, H. J. & Schwaller, M. R. Mapping the abundance and distribution of Adélie penguins using Landsat-7: First steps towards an integrated multi-sensor pipeline for tracking populations at the continental scale. PLoS ONE 9, 1–8 (2014).Article 

    Google Scholar 
    Lynch, H. J. & LaRue, M. A. First global census of the Adélie penguin. Auk 131, 457–466 (2014).Article 

    Google Scholar 
    Parkinson, C. L. & Cavalieri, D. J. Antarctic sea ice variability and trends, 1979–2010. Cryosphere 6, 871–880 (2012).Article 

    Google Scholar 
    Parkinson, C. L. Trends in the length of the Southern Ocean sea-ice season, 1979–99. Ann. Glaciol. 34, 435–440 (2002).Article 

    Google Scholar 
    Jena, B. et al. Record low sea ice extent in the Weddell Sea, Antarctica in April/May 2019 driven by intense and explosive polar cyclones. NPJ Clim. Atmos. Sci. 5, 1–15 (2022).Article 

    Google Scholar 
    Kumar, A., Yadav, J. & Mohan, R. Seasonal sea-ice variability and its trend in the Weddell Sea sector of West Antarctica. Environ. Res. Lett. 16, 024046 (2021).
    Google Scholar 
    Strass, V. H., Rohardt, G., Kanzow, T., Hoppema, M. & Boebel, O. Multidecadal warming and density loss in the deep Weddell Sea. Antarct. J. Clim. 33, 9863–9881 (2020).Article 

    Google Scholar 
    Morioka, Y. & Behera, S. K. Remote and local processes controlling decadal sea ice variability in the Weddell Sea. J. Geophys. Res. Ocean 126, e2020JC017036 (2021).Article 

    Google Scholar 
    Veytia, D. et al. Circumpolar projections of Antarctic krill growth potential. Nat. Clim. Chang. 10, 568–575 (2020).Article 

    Google Scholar 
    Humphries, G. R. et al. Predicting the future is hard and other lessons from a population time series data science competition. Ecol. Inf. 48, 1–11 (2018).Article 

    Google Scholar 
    Borowicz, A. et al. A multi-modal survey of Adèlie penguin megacolonies reveals the Danger Islands as a seabird hotspot. Sci. Rep. 8, 3926 (2018).Article 

    Google Scholar 
    Cimino, M., Lynch, H., Saba, V. & Oliver, M. Projected asymmetric response of Adèlie penguins to Antarctic climate change. Sci. Rep. 6, 28785 (2016).Article 
    CAS 

    Google Scholar 
    McClintock, J., Silva-Rodriguez, P. & Fraser, W. Southerly breeding in gentoo penguins for the eastern Antarctic Peninsula: Further evidence for unprecedented climate change. Antarct. Sci. 22, 285–286 (2010).Article 

    Google Scholar 
    Lynch, H. J., Naveen, R. & Fagan, W. F. Censuses of penguin, blue-eyed shag Phalacrocorax atriceps and southern giant petrel Macronectes giganteus populations on the Antarctic Peninsula, 2001–2007. Mar. Ornithol. 36, 83–97 (2008).
    Google Scholar 
    Dunn, M. J. et al. Population size and decadal trends of three penguin species nesting at Signy Island, South Orkney Islands. PLoS ONE 11, e0164025 (2016).Article 

    Google Scholar 
    Delegations of Argentina and Chile. Domain 1 Marine Protected Area Preliminary Proposal Part A-1, Priority Areas for Conservation. SC-CAMLR- XXXVI/17. Retrieved from https://meetings.ccamlr.org/en/sc-camlr-xxxvi/18 (2018).Delegations of Argentina and Chile. Domain 1 Marine Protected Area Preliminary Proposal Part A-2, Priority Areas for Conservation. SC-CAMLR- XXXVI/18. Retrieved from https://meetings.ccamlr.org/en/sc-camlr-xxxvi/18 (2018).Teschke, K. et al. Planning marine protected areas under the CCAMLR regime—the case of the Weddell Sea (Antarctica). Mar. Policy 124, 104370 (2021).Article 

    Google Scholar 
    Herman, R. et al. Update on the global abundance and distribution of breeding Gentoo Penguins (Pygoscelis papua). Polar Biol. 43, 1947–1956 (2020).Article 

    Google Scholar 
    Korczak-Abshire, M., Hinke, J. T., Milinevsky, G., Juáres, M. A. & Watters, G. M. Coastal regions of the northern Antarctic Peninsula are key for gentoo populations. Biol. Lett. 17, 20200708 (2021).Article 

    Google Scholar 
    Miller, A. K., Karnovsky, N. J. & Trivelpiece, W. Z. Flexible foraging strategies of gentoo penguins Pygoscelis papua over 5 years in the South Shetland Islands. Antarct. Mar. Biol. 156, 2527–2537 (2009).Article 

    Google Scholar 
    Herman, R. W. et al. Seasonal consistency and individual variation in foraging strategies differ among and within Pygoscelis penguin species in the Antarctic Peninsula region. Mar. Biol. 164, 1–13 (2017).Article 
    CAS 

    Google Scholar 
    Cimino, M. A., Fraser, W. R., Irwin, A. J. & Oliver, M. J. Satellite data identify decadal trends in the quality of Pygoscelis penguin chick-rearing habitat. Glob. Chang. Biol. 19, 136–148 (2013).Article 

    Google Scholar 
    Black, C. E. A comprehensive review of the phenology of Pygoscelis penguins. Polar Biol. 39, 405–432 (2016).Article 

    Google Scholar 
    Croxall, J. P. & Kirkwood, E. The Distribution of Penguins on the Antarctic Peninsula and Islands of the Scotia Sea (British Antarctic Survey, Cambridge, UK, 1979).
    Google Scholar 
    Naveen, R. et al. Censuses of penguin, blue-eyed shag, and southern giant petrel populations in the Antarctic Peninsula region, 1994–2000. Polar Rec. 36, 323–334 (2000).Article 

    Google Scholar 
    Woehler,E. J. The Distribution and Abundance of Antarctic and Subantarctic Penguins. In SCAR Comm. on Antarctic Res. Bird Biol. Subcomm. (Cambridge University Press, 1993).Naveen, R., Lynch, H. J., Forrest, S., Mueller, T. & Polito, M. First direct, site-wide penguin survey at Deception Island, Antarctica, suggests significant declines in breeding chinstrap penguins. Polar Biol. 35, 1879–1888 (2012).
    Google Scholar 
    Hallermann, N., Morgenthal, G. & Rodehorst, V. Unmanned aerial systems (UAS)–case studies of vision based monitoring of ageing structures. In Int. Symp. Non-Destructive Test. Civ. Eng. (NDT-CE) 15–17 (2015).Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen, J. L. & Carbonneau, P. E. Topographic structure from motion: A new development in photogrammetric measurement. Earth Surf. Process. Landf. 38, 421–430 (2013).Article 

    Google Scholar 
    Cavalieri, D. J., Germain, K. M. S. & Swift, C. T. Reduction of weather effects in the calculation of sea-ice concentration with the DMSP SSM/I. J. Glaciol. 41, 455–464 (1995).Article 

    Google Scholar 
    Fetterer, F., Knowles, K., Meier, W., Savoie, M. & Windnagel, A. Updated daily Sea Ice Index, Version 3. In Boulder, Colo.USA. NSIDC: Natl. Snow Ice Data Cent (2017).Iles, D. T. et al. Sea ice predicts long-term trends in Adélie penguin population growth, but not annual fluctuations: Results from a range-wide multiscale analysis. Glob. Change Biol. 26, 3788–3798 (2020).Article 

    Google Scholar 
    Plummer, M., Stukalov, A. & Denwood, M. rjags: Bayesian graphical models using mcmc. R package version 4. https://rdrr.io/cran/rjags/ (2016).Plummer, M. et al. Jags: A program for analysis of bayesian graphical models using gibbs sampling. In Proceedings of the 3rd International Workshop on Distributed Statistical Computing, vol. 124, 1–10 (Vienna, Austria., 2003).Brooks, S. P. & Gelman, A. General methods for monitoring convergence of iterative simulations. J. Comput. Graph. Stat. 7, 434–455 (1998).MathSciNet 

    Google Scholar 
    Youngflesh, C. MCMCvis: Tools to visualize, manipulate, and summarize MCMC output. J. Open Sourc. Softw. 3, 640 (2018).Article 

    Google Scholar 
    Wickham, H. ggplot2. Wiley Interdiscipl. Rev. Comput. Stat. 3, 180–185 (2011).Article 

    Google Scholar 
    Kellner,K. jagsUI: A wrapper around rjags to streamline JAGS analyses. R package version 1, 2015 (2015).Herman, R. & Lynch, H. Age-structured model reveals prolonged immigration is key for colony establishment in Gentoo Penguins. Ornithol. Appl. 124, duac04 (2022).
    Google Scholar 
    Polito, M. J., Lynch, H. J., Naveen, R. & Emslie, S. D. Stable isotopes reveal regional heterogeneity in the pre-breeding distribution and diets of sympatrically breeding Pygoscelis spp. penguins. Mar. Ecol. Prog. Ser. 421, 265–277 (2011).Article 

    Google Scholar 
    Ballerini, T., Tavecchia, G., Olmastroni, S., Pezzo, F. & Focardi, S. Nonlinear effects of winter sea ice on the survival probabilities of Adélie penguins. Oecologia 161, 253–265 (2009).Article 

    Google Scholar 
    Wilson, P. et al. Adélie penguin population change in the pacific sector of Antarctica: Relation to sea-ice extent and the Antarctic Circumpolar Current. Mar. Ecol. Prog. Ser. 213, 301–309 (2001).Article 

    Google Scholar 
    Wienecke, B. et al. Adélie penguin foraging behaviour and krill abundance along the Wilkes and Adélie land coasts, Antarctica. Deep. Sea Res. Part II Top. Stud. Oceanogr. 47, 2573–2587 (2000).Article 

    Google Scholar 
    Ainley, D. G. The Adélie Penguin: Bellwether of Climate Change (Columbia University Press, 2002).Book 

    Google Scholar 
    Cherel, Y. Isotopic niches of emperor and Adélie penguins in Adélie Land. Antarct. Mar. Biol. 154, 813–821 (2008).Article 

    Google Scholar 
    Ainley, D. G. et al. Post-fledging survival of Adélie penguins at multiple colonies: Chicks raised on fish do well. Mar. Ecol. Prog. Ser. 601, 239–251 (2018).Article 

    Google Scholar 
    Ashford, J., Zane, L., Torres, J. J., La Mesa, M. & Simms, A. R. Population structure and life history connectivity of Antarctic silverfish (Pleuragramma antarctica) in the Southern Ocean ecosystem. In The Antarctic Silverfish: A Keystone Species in a Changing Ecosystem 193–234 (Springer, 2017).Pakhomov, E. & Perissinotto, R. Antarctic neritic krill Euphausia crystallorophias: Spatio-temporal distribution, growth and grazing rates. Deep. Sea Res. Part I Oceanogr. Res. Pap. 43, 59–87 (1996).Article 

    Google Scholar 
    La Mesa, M. & Eastman, J. T. Antarctic silverfish: Life strategies of a key species in the high-Antarctic ecosystem. Fish Fish 13, 241–266 (2012).Article 

    Google Scholar 
    Davis, L. B., Hofmann, E. E., Klinck, J. M., Piñones, A. & Dinniman, M. S. Distributions of krill and Antarctic silverfish and correlations with environmental variables in the western Ross Sea. Antarct. Mar. Ecol. Prog. Ser. 584, 45–65 (2017).Article 
    CAS 

    Google Scholar 
    Chapman, E. W., Hofmann, E. E., Patterson, D. L., Ribic, C. A. & Fraser, W. R. Marine and terrestrial factors affecting Adélie penguin Pygoscelis adeliae chick growth and recruitment off the western Antarctic Peninsula. Mar. Ecol. Prog. Ser. 436, 273–289 (2011).Article 

    Google Scholar 
    La Mesa, M., Piñones, A., Catalano, B. & Ashford, J. Predicting early life connectivity of Antarctic silverfish, an important forage species along the Antarctic Peninsula. Fish. Oceanogr. 24, 150–161 (2015).Article 

    Google Scholar 
    La Mesa, M., Riginella, E., Mazzoldi, C. & Ashford, J. Reproductive resilience of ice-dependent Antarctic silverfish in a rapidly changing system along the Western Antarctic Peninsula. Mar. Ecol. 36, 235–245 (2015).Article 

    Google Scholar 
    Handley, J. et al. Marine important bird and biodiversity areas for penguins in Antarctica, targets for conservation action. Front. Mar. Sci. 7, 256 (2021).Article 

    Google Scholar 
    Brooks, C. et al. Workshop on identifying key biodiversity areas for the Southern Ocean using tracking data. In Tech.Rep. SC-CAMLR-41/BG/22, CCAMLR (2022).Lynch, H. J., Naveen, R. & Casanovas, P. Antarctic site inventory breeding bird survey data, 1994–2013: Ecological Archives E094–243. Ecology 94, 2653–2653 (2013).Article 

    Google Scholar 
    Myrcha, A., Tatur, A. & Valle, R. D. V. Numbers of Adélie penguins breeding at Hope Bay and Seymour Island rookeries (West Antarctica) in 1985. Pol. Polar Res. 8, 411–422 (1987).
    Google Scholar 
    Montalti, D. & Soave, G. E. The birds of Seymour Island, Antarctica. Ornitol. Neotrop. 13, 267–271 (2002).
    Google Scholar 
    Perchivale, P. J. et al. Updated estimate of the Breeding Population of Adélie penguins (Pygoscelis adeliae) at Penguin Point, Marambio/Seymour Island within the proposed Weddell Sea Marine Protected Area (2022). https://www.researchsquare.com/article/rs-2117503/v1.Che-Castaldo, C. et al. Pan-Antarctic analysis aggregating spatial estimates of Adélie penguin abundance reveals robust dynamics despite stochastic noise. Nat. Commun. 8, 832 (2017).Article 

    Google Scholar 
    Hinke, J. T., Trivelpiece, S. G. & Trivelpiece, W. Z. Variable vital rates and the risk of population declines in Adélie penguins from the Antarctic Peninsula region. Ecosphere 8, e01666 (2017).Article 

    Google Scholar  More

  • in

    Evaluating red tide effects on the West Florida Shelf using a spatiotemporal ecosystem modeling framework

    Brown, A. R. et al. Assessing risks and mitigating impacts of harmful algal blooms on mariculture and marine fisheries. Rev. Aquac. 12, 1663–1688 (2020).
    Google Scholar 
    Bechard, A. Red tide at morning, tourists take warning? County-level economic effects of HABS on tourism dependent sectors. Harmful Algae 85, 101689–101689 (2019).Article 

    Google Scholar 
    Landsberg, J. H. The effects of harmful algal blooms on aquatic organisms. Rev. Fish. Sci. 10, 113–390 (2002).Article 

    Google Scholar 
    Flewelling, L. J. et al. Brevetoxicosis: Red tides and marine mammal mortalities. Nature 435, 755–756 (2005).Article 
    CAS 

    Google Scholar 
    Gannon, D. P. et al. Effects of Karenia brevis harmful algal blooms on nearshore fish communities in southwest Florida. Mar. Ecol. Prog. Ser. 378, 171–186 (2009).Article 
    CAS 

    Google Scholar 
    Driggers, W. B. et al. Environmental conditions and catch rates of predatory fishes associated with a mass mortality on the West Florida Shelf. Estuar. Coast. Shelf Sci. 168, 40–49 (2016).Article 
    CAS 

    Google Scholar 
    Hallett, C. S., Valesini, F. J., Clarke, K. R. & Hoeksema, S. D. Effects of a harmful algal bloom on the community ecology, movements and spatial distributions of fishes in a microtidal estuary. Hydrobiologia 763, 267–284 (2016).Article 

    Google Scholar 
    Anderson, D. M. et al. Marine harmful algal blooms (HABs) in the United States: History, current status and future trends. Harmful Algae 102, 101975–101975 (2021).Article 
    CAS 

    Google Scholar 
    Steidinger, K. A. & Haddad, K. Biologic and hydrographic aspects of red tides. Bioscience 31, 814–819 (1981).Article 

    Google Scholar 
    Soto, I. M. et al. Advection of Karenia brevis blooms from the Florida Panhandle towards Mississippi coastal waters. Harmful Algae 72, 46–64 (2018).Article 

    Google Scholar 
    Steidinger, K. A. & Ingle, R. M. Observations on the 1971 summer red tide in tampa bay, Florida1. Environ. Lett. 3, 271–278 (1972).Article 
    CAS 

    Google Scholar 
    Liu, Y. et al. Offshore forcing on the “pressure point” of the West Florida Shelf: Anomalous upwelling and its influence on harmful algal blooms. J. Geophys. Res. 121, 5501–5515 (2016).Article 

    Google Scholar 
    Liu, Y., Weisberg, R. H., Zheng, L., Heil, C. A. & Hubbard, K. A. Termination of the 2018 Florida red tide event: A tracer model perspective. Estuar. Coast. Shelf Sci. 272, 107901 (2022).Article 

    Google Scholar 
    Weisberg, R. H. & Liu, Y. Local and deep-ocean forcing effects on the West Florida continental shelf circulation and ecology. Front. Mar. Sci. https://doi.org/10.3389/fmars.2022.863227 (2022).Article 

    Google Scholar 
    Walsh, J. J. et al. Red tides in the Gulf of Mexico: Where, when, and why? Journal of Geophysical Research: Oceans 111, (2006).Lapointe, B. E., Herren, L. W., Debortoli, D. D. & Vogel, M. A. Evidence of sewage-driven eutrophication and harmful algal blooms in Florida’s Indian River Lagoon. Harmful Algae 43, 82–102 (2015).Article 
    CAS 

    Google Scholar 
    Medina, M. et al. Nitrogen-enriched discharges from a highly managed watershed intensify red tide (Karenia brevis) blooms in southwest Florida. Sci. Total Environ. 827, 154149–154149 (2022).Article 
    CAS 

    Google Scholar 
    Perkins, S. Ramping up the fight against Florida’s red tides. Proc. Natl. Acad. Sci. U.S.A. 116, 6510–6512 (2019).Article 
    CAS 

    Google Scholar 
    Skripnikov, A. et al. Using localized Twitter activity to assess harmful algal bloom impacts of Karenia brevis in Florida, USA. Harmful Algae 110, 102118–102118 (2021).Article 
    CAS 

    Google Scholar 
    SEDAR. SEDAR 33 Update – Gulf of Mexico gag grouper stock assessment report, 123. https://sedarweb.org/docs/suar/GagUpdateAssessReport_Final_0.pdf (2016).SEDAR. SEDAR 61 – Gulf of Mexico red grouper stock assessment report, 285. https://sedarweb.org/docs/sar/S61_Final_SAR.pdf (2019).SEDAR. SEDAR 10 Stock Assessment Report 2: Gulf of Mexico Gag Grouper, 250. www.sedarweb.org (2004).SEDAR. SEDAR 10 Update – Gulf of Mexico gag grouper stock assessment report. http://www.sedarweb.org (2009).SEDAR. SEDAR 72—Gulf of Mexico gag grouper stock assessment report, 318–318. https://sedarweb.org/docs/sar/S72_SAR_FINAL.pdf%0A (2021).Geary, W. L. et al. A guide to ecosystem models and their environmental applications. Nat. Ecol. Evol. 4, 1459–1471 (2020).Article 

    Google Scholar 
    Steenbeek, J. et al. Making spatial-temporal marine ecosystem modelling better—A perspective. Environ. Model. Softw. 145, 105209–105209 (2021).Article 

    Google Scholar 
    Gray DiLeone, A. M. & Ainsworth, C. H. Effects of Karenia brevis harmful algal blooms on fish community structure on the West Florida Shelf. Ecol. Model. 392, 250–267 (2019).Article 

    Google Scholar 
    Perryman, H. A. et al. A revised diet matrix to improve the parameterization of a West Florida Shelf Ecopath model for understanding harmful algal bloom impacts. Ecol. Model. 416, 108890–108890 (2020).Article 

    Google Scholar 
    Mayer-Pinto, M., Ledet, J., Crowe, T. P. & Johnston, E. L. Sublethal effects of contaminants on marine habitat-forming species: A review and meta-analysis. Biol. Rev. 95, 1554–1573 (2020).Article 

    Google Scholar 
    Reis Costa, P. Impact and effects of paralytic shellfish poisoning toxins derived from harmful algal blooms to marine fish. Fish Fish. 17, 226–248 (2016).Article 

    Google Scholar 
    Dahood, A., de Mutsert, K. & Watters, G. M. Evaluating Antarctic marine protected area scenarios using a dynamic food web model. Biol. Cons. 251, 108766–108766 (2020).Article 

    Google Scholar 
    de Mutsert, K. et al. Exploring effects of hypoxia on fish and fisheries in the northern Gulf of Mexico using a dynamic spatially explicit ecosystem model. Ecol. Model. 331, 142–150 (2016).Article 

    Google Scholar 
    de Mutsert, K., Lewis, K. A., White, E. D. & Buszowski, J. End-to-end modeling reveals species-specific effects of large-scale coastal restoration on living resources facing climate change. Front. Mar. Sci. 8, 104–104 (2021).Article 

    Google Scholar 
    Bauer, B. et al. Erratum: Reducing eutrophication increases spatial extent of communities supporting commercial fisheries: A model case study (ICES Journal of Marine Science (2018) DOI: https://doi.org/10.1093/icesjms/fsy003). ICES Journal of Marine Science, 75, 1155–1155 (2018).Sadchatheeswaran, S., Branch, G. M., Shannon, L. J., Coll, M. & Steenbeek, J. A novel approach to explicitly model the spatiotemporal impacts of structural complexity created by alien ecosystem engineers in a marine benthic environment. Ecol. Model. 459, 109731–109731 (2021).Article 

    Google Scholar 
    Coll, M. et al. Advancing global ecological modeling capabilities to simulate future trajectories of change in marine ecosystems. Front. Mar. Sci. 7, 741–741 (2020).Article 

    Google Scholar 
    Hernvann, P. Y. et al. The celtic sea through time and space: Ecosystem modeling to unravel fishing and climate change impacts on food-web structure and dynamics. Front. Mar. Sci. 7, 1018–1018 (2020).Article 

    Google Scholar 
    Walters, C. Ecospace: Prediction of mesoscale spatial patterns in trophic relationships of exploited ecosystems, with emphasis on the impacts of marine protected areas. Ecosystems 2, 539–554 (1999).Article 

    Google Scholar 
    Christensen, V., Walters, C. J., Pauly, D. & Forrest, R. Ecopath with Ecosim version 6 user guide. Fish. Cent. Univ. Br. Columbia Vanc. Can. 281, 1–235 (2008).
    Google Scholar 
    Okey, T. A., Mahmoudi, B., Mackinson, S., Vasconcellos, M. & Vidal-Hernandez, L. An ecosystem model of the West Florida Shelf for use in fisheries management and ecological research: Volume II. Model construction. Fish. Manag. II, 163–163 (2002).
    Google Scholar 
    Liu, Y. & Weisberg, R. H. Seasonal variability on the West Florida Shelf. Prog. Oceanogr. 104, 80–98 (2012).Article 

    Google Scholar 
    Moretzsohn, F., Chávez-Sánchez, J. A. & J.W. Tunnell, Jr. GulfBase: Resource Database for Gulf of Mexico Research. World Wide Web electronic publication (2016).Murawski, S. A., Peebles, E. B., Gracia, A., Tunnell, J. W. & Armenteros, M. Comparative abundance, species composition, and demographics of continental shelf fish assemblages throughout the Gulf of Mexico. Mar. Coast. Fish. 10, 325–346 (2018).Article 

    Google Scholar 
    Darnell, R. M. The American sea: A natural history of the gulf of Mexico. The American Sea: A Natural History of the Gulf of Mexico, 557, https://doi.org/10.5860/choice.193769 (2015).Brochure, I. Marine recreational information program: Implementation plan (2008).Florida Fish and Wildlife Conservation Commission. Commercial fisheries landings summaries (2021).Murawski, S. A. et al. How did the deepwater horizon oil spill affect coastal and continental shelf ecosystems of the Gulf of Mexico?. Oceanography 29, 160–173 (2016).Article 

    Google Scholar 
    Chagaris, D. D., Patterson, W. F. & Allen, M. S. Relative effects of multiple stressors on reef food webs in the Northern Gulf of Mexico revealed via ecosystem modeling. Front. Mar. Sci. 7, 513–513 (2020).Article 

    Google Scholar 
    South, A. rnaturalearth: world map data from Natural Earth. R package version 0.1.0. The R Foundation. https://CRAN.R-project.org/package=rnaturalearth (2017).Colleter, M. et al. Global overview of the applications of the Ecopath with Ecosim modeling approach using the EcoBase models repository. Ecol. Model. 302, 42–53 (2015).Article 

    Google Scholar 
    Ahrens, R. N., Walters, C. J. & Christensen, V. Foraging arena theory. Fish fish. 13, 41–59 (2012).Article 

    Google Scholar 
    Christensen, V. et al. Representing variable habitat quality in a spatial food web model. Ecosystems 17, 1397–1412 (2014).Article 
    CAS 

    Google Scholar 
    Steenbeek, J. et al. Bridging the gap between ecosystem modeling tools and geographic information systems: Driving a food web model with external spatial–temporal data. Ecol. Model. 263, 139–151 (2013).Article 

    Google Scholar 
    Walters, C., Christensen, V., Walters, W. & Rose, K. Representation of multistanza life histories in Ecospace models for spatial organization of ecosystem trophic interaction patterns. Bull. Mar. Sci. 86, 439–459 (2010).
    Google Scholar 
    Heymans, J. J. et al. Best practice in Ecopath with Ecosim food-web models for ecosystem-based management. Ecol. Model. 331, 173–184 (2016).Article 

    Google Scholar 
    Okey, T. Simulating community effects of sea floor shading by plankton blooms over the West Florida Shelf. Ecol. Model. 172, 339–359 (2004).Article 

    Google Scholar 
    Chagaris, D. D. Ecosystem-based Evaluation of Fishery Policies and Tradeoffs on the West Florida Shelf Vol. 53, 1699 (University of Florida, 2013).
    Google Scholar 
    Chagaris, D. D., Mahmoudi, B., Walters, C. J. & Allen, M. S. Simulating the trophic impacts of fishery policy options on the west florida shelf using ecopath with ecosim. Mar. Coast. Fish. 7, 44–58 (2015).Article 

    Google Scholar 
    Chagaris, D. et al. An ecosystem-based approach to evaluating impacts and management of invasive lionfish. Fisheries 42, 421–431 (2017).Article 

    Google Scholar 
    Chagaris, D. West Florida Shelf Ecosystem Model. University of Florida. https://ufdc.ufl.edu/IR00011604/00001%0A West Florida Shelf Ecosystem Model (2021).Vilas, D. Spatiotemporal Ecosystem Dynamics on the West Florida Shelf: Prediction, Validation, and Application to Red Tides and Stock Assessment (University of Florida, 2022).
    Google Scholar 
    Chassignet, E. P. et al. The HYCOM (HYbrid Coordinate Ocean Model) data assimilative system. J. Mar. Syst. 65, 60–83 (2007).Article 

    Google Scholar 
    NOAA National Geophysical Data Center. U.S. Coastal Relief Model Vol. 3—Florida and East Gulf of Mexico. https://doi.org/10.7289/V5W66HP (2001).NASA. Goddard Space Flight Center, Ocean Ecology Laboratory, Ocean Biology Processing Group. Earth Data (2018).Casey, L. Nutrient and pesticide data collected from the USGS National Water Quality Network and previous networks, 1950–2020: U.S. Geological Survey, https://doi.org/10.5066/P9P2PF1N (2021).Chagaris, D. & Vilas, D. NOAA RESTORE Science Program: Ecosystem modeling to improve fisheries management in the Gulf of Mexico: model inputs and outputs for the West Florida Shelf, 1985–01–01 to 2018–12–31 (NCEI Accession 0242339), https://doi.org/10.25921/t26e-wj91. (2022).Püts, M. et al. Insights on integrating habitat preferences in process-oriented ecological models—A case study of the southern North Sea. Ecol. Model. 431, 109189–109189 (2020).Article 

    Google Scholar 
    Vilas, D., Fletcher, R. J. Jr., Siders, Z. A. & Chagaris, D. Understanding the temporal dynamics of estimated environmental niche hypervolumes for marine fishes. Ecol. Evol. 12, e9604 (2022).Article 

    Google Scholar 
    Grubbs, R. D., Musick, J. A., Conrath, C. L. & Romine, J. G. Long-term movements, migration, and temporal delineation of a summer nursery for Juvenile Sandbar Sharks in the Chesapeake Bay region. In Shark Nursery Grounds of the Gulf of Mexico and the East Coast Waters of the United States. American Fisheries Society Symposium 50 Vol. 50 (eds Grubbs, R. D. et al.) 87–107 (American Fisheries Society, 2007).
    Google Scholar 
    Addis, D. T., Patterson, W. F., Dance, M. A. & Ingram, G. W. Implications of reef fish movement from unreported artificial reef sites in the northern Gulf of Mexico. Fish. Res. 147, 349–358 (2013).Article 

    Google Scholar 
    Akins, J. L., Morris, J. A. & Green, S. J. In situ tagging technique for fishes provides insight into growth and movement of invasive lionfish. Ecol. Evol. 4, 3768–3777 (2014).Article 

    Google Scholar 
    Chen, Z., Xu, S., Qiu, Y., Lin, Z. & Jia, X. Modeling the effects of fishery management and marine protected areas on the Beibu Gulf using spatial ecosystem simulation. Fish. Res. 100, 222–229 (2009).Article 

    Google Scholar 
    Steenbeek, J. et al. Ecopath with ecosim as a model-building toolbox: Source code capabilities, extensions, and variations. Ecol. Model. 319, 178–189 (2016).Article 

    Google Scholar 
    Moriasi, D. N. et al. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans. ASABE 50, 885–900 (2007).Article 

    Google Scholar 
    Hu, C. et al. Red tide detection and tracing using MODIS fluorescence data: A regional example in SW Florida coastal waters. Remote Sens. Environ. 97, 311–321 (2005).Article 

    Google Scholar 
    Chagaris, D., Vilas, D., Siders, Z. A. & Sinnickson, D. Monthly maps of red tide on the West Florida Shelf 2002–2021: A simple approach combining remote sensing and in situ measurements (in prep).Florida Fish and Wildlife Conservation Commission-Fish and Wildlife Research Institute. Statewide harmful algal bloom karenia brevis current status map (2022).Wickham, H. et al. ggplot2: Create elegant data visualisations using the grammar of graphics (2016).Landsberg, J. H., Flewelling, L. J. & Naar, J. Karenia brevis red tides, brevetoxins in the food web, and impacts on natural resources: Decadal advancements. Harmful Algae 8, 598–607 (2009).Article 
    CAS 

    Google Scholar 
    Gianelli, I., Ortega, L. & Defeo, O. Modeling short-term fishing dynamics in a small-scale intertidal shellfishery. Fish. Res. 209, 242–250 (2019).Article 

    Google Scholar 
    Moore, S. K. et al. An index of fisheries closures due to harmful algal blooms and a framework for identifying vulnerable fishing communities on the U.S. West Coast. Mar. Policy 110, 103543–103543 (2019).Article 

    Google Scholar 
    GSMFC. SEAMAP: Environmental and Biological Atlas of the Gulf of Mexico. www.seamap.org (2020).Bechard, A. Harmful algal blooms and tourism: The economic impact to counties in Southwest Florida. Rev. Reg. Stud. 50, 170–188 (2020).
    Google Scholar 
    Foley, A. M. et al. Effects of Karenia brevis harmful algal blooms on nearshore fish communities in southwest Florida. Mar. Ecol. Prog. Ser. 378, 171–186 (2009).Article 

    Google Scholar 
    Karnauskas, M. et al. Timeline of severe red tide events on the West Florida Shelf: insights from oral histories. http://sedarweb.org/docs/wpapers/S61_WP_20_Karnauskasetal_red_tide.pdf (2019).Sagarese, S. R., Gruss, A., Karnauskas, M. & Walter, J. F. Ontogenetic spatial distributions of red grouper (Epinephelus morio) within the northeastern Gulf of Mexico and spatio‐ temporal overlap with red tide events, 35–35. http://sedarweb.org/docs/wpapers/S42_DW_04_Red_tide_distribution.pdf (2014).Sagarese, S. R., Vaughan, N. R., Walter, J. F. & Karnauskas, M. Enhancing single-species stock assessments with diverse ecosystem perspectives: A case study for gulf of mexico red grouper (epinephelus morio) and red tides. Can. J. Fish. Aquat. Sci. 78, 1168–1180 (2021).Article 

    Google Scholar 
    Sagarese, S. R. & Harford, W. J. Evaluating the risks of red tide mortality misspecification when modeling stock dynamics. Fish. Res. 250, 106271–106271 (2022).Article 

    Google Scholar 
    Whitehouse, G. A. & Aydin, K. Y. Assessing the sensitivity of three Alaska marine food webs to perturbations: An example of Ecosim simulations using Rpath. Ecol. Model. 429, 109074–109074 (2020).Article 

    Google Scholar 
    Walter, J. F. et al. Satellite derived indices of red tide severity for input for Gulf of Mexico Gag grouper stock assessment. SEDAR33-DW08 SEDAR. North Charlest. S. C. 43, 40–40 (2013).
    Google Scholar 
    Jackson, M. C., Pawar, S. & Woodward, G. The temporal dynamics of multiple stressor effects: From individuals to ecosystems. Trends Ecol. Evol. 36, 402–410 (2021).Article 

    Google Scholar 
    Walters, S., Lowerre-Barbieri, S., Bickford, J., Tustison, J. & Landsberg, J. H. Effects of Karenia brevis red tide on the spatial distribution of spawning aggregations of sand seatrout Cynoscion arenarius in Tampa Bay Florida. Mar. Ecol. Prog. Ser. 479, 191–202 (2013).Article 

    Google Scholar 
    Reynolds, D. A., Yoo, M. J., Dixson, D. L. & Ross, C. Exposure to the Florida red tide dinoflagellate, Karenia brevis, and its associated brevetoxins induces ecophysiological and proteomic alterations in Porites astreoides. PLoS One 15, e0228414–e0228414 (2020).Article 
    CAS 

    Google Scholar 
    Bornman, E., Cowley, P. D., Adams, J. B. & Strydom, N. A. Daytime intra-estuary movements and harmful algal bloom avoidance by Mugil cephalus (family Mugilidae). Estuar. Coast. Shelf Sci. 260, 107492–107492 (2021).Article 
    CAS 

    Google Scholar 
    Moreira-Santos, M., Ribeiro, R. & Araújo, C. V. M. What if aquatic animals move away from pesticide-contaminated habitats before suffering adverse physiological effects? A critical review. Crit. Rev. Environ. Sci. Technol. 49, 989–1025 (2019).Article 
    CAS 

    Google Scholar 
    Schreck, C. B. & Tort, L. The concept of stress in fish. In Fish Physiology Vol. 35 (eds Schreck, C. B. & Tort, L.) 1–34 (Elsevier, 2016).
    Google Scholar 
    Madin, E. M. P., Dill, L. M., Ridlon, A. D., Heithaus, M. R. & Warner, R. R. Human activities change marine ecosystems by altering predation risk. Glob. Change Biol. 22, 44–60 (2016).Article 

    Google Scholar 
    Walsh, J. R., Carpenter, S. R. & Van Der Zanden, M. J. Invasive species triggers a massive loss of ecosystem services through a trophic cascade. Proc. Natl. Acad. Sci. U.S.A. 113, 4081–4085 (2016).Article 
    CAS 

    Google Scholar 
    Short, J. W. et al. Evidence for ecosystem-level trophic cascade effects involving gulf menhaden (Brevoortia patronus) triggered by the Deepwater horizon blowout. J. Mar. Sci. Eng. 9, 1–20 (2021).Article 

    Google Scholar 
    Zohdi, E. & Abbaspour, M. Harmful algal blooms (red tide): A review of causes, impacts and approaches to monitoring and prediction. Int. J. Environ. Sci. Technol. 16, 1789–1806 (2019).Article 

    Google Scholar 
    Weisberg, R. H., Barth, A., Alvera-Azcarate, A. & Zheng, L. A coordinated coastal ocean observing and modeling system for the West Florida Continental Shelf. Harmful Algae 8, 585–597 (2009).Article 

    Google Scholar 
    Turley, B. D., Karnauskas, M., Campbell, M. D., Hanisko, D. S. & Kelble, C. R. Relationships between blooms of Karenia brevis and hypoxia across the West Florida Shelf. Harmful Algae 114, 102223 (2022).Article 

    Google Scholar 
    Fulton, E. A., Smith, A. D., Smith, D. C. & Johnson, P. An integrated approach is needed for ecosystem based fisheries management: Insights from ecosystem-level management strategy evaluation. PLoS One 9, e84242 (2014).Article 

    Google Scholar 
    Flynn, K. J. & McGillicuddy, D. J. Modeling marine harmful algal blooms: Current status and future prospects. Harmful Algal Blooms https://doi.org/10.1002/9781118994672.ch3 (2018).Article 

    Google Scholar 
    Thorson, J. T. Guidance for decisions using the Vector Autoregressive Spatio-Temporal (VAST) package in stock, ecosystem, habitat and climate assessments. Fish. Res. 210, 143–161 (2019).Article 

    Google Scholar 
    Fossum, T. O., Travelletti, C., Eidsvik, J., Ginsbourger, D. & Rajan, K. Learning excursion sets of vector-valued gaussian random fields for autonomous ocean sampling. Ann. Appl. Stat. 15, 597–618 (2021).Article 
    MathSciNet 
    MATH 

    Google Scholar 
    Fu, F. X., Place, A. R., Garcia, N. S. & Hutchins, D. A. CO2 and phosphate availability control the toxicity of the harmful bloom dinoflagellate Karlodinium veneficum. Aquat. Microb. Ecol. 59, 55–65 (2010).Article 

    Google Scholar 
    Hardison, D. R., Sunda, W. G., Shea, D. & Litaker, R. W. Increased toxicity of Karenia brevis during phosphate limited growth: Ecological and evolutionary implications. PLoS One 8, e58545–e58545 (2013).Article 
    CAS 

    Google Scholar 
    Errera, R. M., Yvon-Lewis, S., Kessler, J. D. & Campbell, L. Reponses of the dinoflagellate Karenia brevis to climate change: PCO2 and sea surface temperatures. Harmful Algae 37, 110–116 (2014).Article 
    CAS 

    Google Scholar 
    Wells, M. L. et al. Future HAB science: Directions and challenges in a changing climate. Harmful Algae 91, 101632–101632 (2020).Article 

    Google Scholar 
    Wolny, J. L. et al. Current and future remote sensing of harmful algal blooms in the chesapeake bay to support the shellfish industry. Front. Mar. Sci. 7, 337–337 (2020).Article 

    Google Scholar 
    Reum, J. C. P. et al. It’s not the destination, It’s the journey: Multispecies model ensembles for ecosystem approaches to fisheries management. Front. Mar. Sci. 8, 75–75 (2021).Article 

    Google Scholar 
    Howell, D. et al. Combining ecosystem and single-species modeling to provide ecosystem-based fisheries management advice within current management systems. Front. Mar. Sci. 7, 607831 (2021).Article 

    Google Scholar 
    McPherson, W. C. and J. C. and J. A. and Y. X. and J. shiny: Web application framework for R. R package version 1.4.0, 115–115 (2019). More

  • in

    The changing climate could lead to carbon losses in the tropics

    Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.This is a summary of: Uribe, M. R. et al. Net loss of biomass predicted for tropical biomes in a changing climate. Nat. Clim. Change https://doi.org/10.1038/s41558-023-01600-z (2023). More

  • in

    Gut microbiome composition associates with corticosteroid treatment, morbidity, and senescence in Chinook salmon (Oncorhynchus tshawytscha)

    Jerez-Cepa, I., Gorissen, M., Mancera, J. M. & Ruiz-Jarabo, I. What can we learn from glucocorticoid administration in fish? Effects of cortisol and dexamethasone on intermediary metabolism of gilthead seabream (Sparus aurata L.). Comp. Biochem. Physiol. A Mol. Integr. Physiol. 231, 1–10 (2019).Article 
    CAS 

    Google Scholar 
    Brown, C. L., Urbinati, E. C., Zhang, W., Brown, S. B. & McComb-Kobza, M. Maternal thyroid and glucocorticoid hormone interactions in larval fish development, and their applications in aquaculture. Rev. fish. Sci. Aquac. 22, 207–220 (2014).Article 

    Google Scholar 
    Tort, L. Stress and immune modulation in fish. Dev. Comp. Immunol. 35, 1366–1375 (2011).Article 
    CAS 

    Google Scholar 
    Schreck, C. B. & Tort, L. In Fish Physiology (eds Schreck, C. B. et al.) vol. 35, 1–34 (Elsevier, 2016).Sternberg, E. M., Chrousos, G. P., Wilder, R. L. & Gold, P. W. The stress response and the regulation of inflammatory disease. Ann. Intern. Med. 117, 854–866 (1992).Article 
    CAS 

    Google Scholar 
    Staufenbiel, S. M., Penninx, B. W. J. H., Spijker, A. T., Elzinga, B. M. & van Rossum, E. F. C. Hair cortisol, stress exposure, and mental health in humans: A systematic review. Psychoneuroendocrinology 38, 1220–1235 (2013).Article 
    CAS 

    Google Scholar 
    Pickering, A. D. & Pottinger, T. G. Cortisol can increase the susceptibility of brown trout, Salmo trutta L., to disease without reducing the white blood cell count. J. Fish Biol. 27, 611–619 (1985).Article 
    CAS 

    Google Scholar 
    McCormick, S. D. et al. Repeated acute stress reduces growth rate of Atlantic salmon parr and alters plasma levels of growth hormone, insulin-like growth factor I and cortisol. Aquaculture 168, 221–235 (1998).Article 
    CAS 

    Google Scholar 
    McConnachie, S. H. et al. Consequences of acute stress and cortisol manipulation on the physiology, behavior, and reproductive outcome of female Pacific salmon on spawning grounds. Horm. Behav. 62, 67–76 (2012).Article 
    CAS 

    Google Scholar 
    Moffat, S. D., An, Y., Resnick, S. M., Diamond, M. P. & Ferrucci, L. Longitudinal change in cortisol levels across the adult life span. J. Gerontol. A Biol. Sci. Med. Sci. 75, 394–400 (2020).Article 
    CAS 

    Google Scholar 
    Oh, H.-J. et al. Age-related decrease in stress responsiveness and proactive coping in male mice. Front. Aging Neurosci. 10, 128 (2018).Article 
    PubMed Central 

    Google Scholar 
    Woods, H. A. 2nd. & Hellgren, E. C. Seasonal changes in the physiology of male Virginia opossums (Didelphis virginiana): Signs of the Dasyurid semelparity syndrome?. Physiol. Biochem. Zool. 76, 406–417 (2003).Article 

    Google Scholar 
    Barry, T. P., Unwin, M. J., Malison, J. A. & Quinn, T. P. Free and total cortisol levels in semelparous and iteroparous Chinook salmon. J. Fish Biol. 59, 1673–1676 (2001).Article 
    CAS 

    Google Scholar 
    Petrosus, E., Silva, E. B., Lay, D. Jr. & Eicher, S. D. Effects of orally administered cortisol and norepinephrine on weanling piglet gut microbial populations and Salmonella passage. J. Anim. Sci. 96, 4543–4551 (2018).PubMed Central 

    Google Scholar 
    Shi, D. et al. Impact of gut microbiota structure in heat-stressed broilers. Poult. Sci. 98, 2405–2413 (2019).Article 

    Google Scholar 
    Uren Webster, T. M., Rodriguez-Barreto, D., Consuegra, S. & Garcia de Leaniz, C. Cortisol-related signatures of stress in the fish microbiome. Front. Microbiol. 11, 1621 (2020).Article 
    PubMed Central 

    Google Scholar 
    Ridlon, J. M. et al. Clostridium scindens: A human gut microbe with a high potential to convert glucocorticoids into androgens. J. Lipid Res. 54, 2437–2449 (2013).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    UrenWebster, T. M., Consuegra, S. & Garcia de Leaniz, C. Early life stress causes persistent impacts on the microbiome of Atlantic salmon. Comp. Biochem. Physiol. Part D Genomics Proteomics 40, 100888 (2021).Article 
    CAS 

    Google Scholar 
    Bozzi, D. et al. Salmon gut microbiota correlates with disease infection status: Potential for monitoring health in farmed animals. Anim. Microbiome 3, 30 (2021).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Xiong, J.-B., Nie, L. & Chen, J. Current understanding on the roles of gut microbiota in fish disease and immunity. Zool. Res. 40, 70–76 (2019).
    Google Scholar 
    Williams, C. L., Garcia-Reyero, N., Martyniuk, C. J., Tubbs, C. W. & Bisesi, J. H. Jr. Regulation of endocrine systems by the microbiome: Perspectives from comparative animal models. Gen. Comp. Endocrinol. 292, 113437 (2020).Article 
    CAS 

    Google Scholar 
    Schmidt, K. et al. Prebiotic intake reduces the waking cortisol response and alters emotional bias in healthy volunteers. Psychopharmacology 232, 1793–1801 (2015).Article 
    CAS 

    Google Scholar 
    Crumeyrolle-Arias, M. et al. Absence of the gut microbiota enhances anxiety-like behavior and neuroendocrine response to acute stress in rats. Psychoneuroendocrinology 42, 207–217 (2014).Article 
    CAS 

    Google Scholar 
    Bell, E. A., Ball, A. G., Deprey, K. L. & Uno, J. K. The impact of antibiotics on the intestinal microbiome and the gut-brain axis in zebrafish. FASEB J. 32, 765–771 (2018).Article 

    Google Scholar 
    Björnsson, B. T., Stefansson, S. O. & McCormick, S. D. Environmental endocrinology of salmon smoltification. Gen. Comp. Endocrinol. 170, 290–298 (2011).Article 

    Google Scholar 
    Carruth, L. L., Jones, R. E. & Norris, D. O. Cortisol and Pacific Salmon: A new look at the role of stress hormones in olfaction and home-stream migration. Integr. Comp. Biol. 42, 574–581 (2002).Article 
    CAS 

    Google Scholar 
    Donaldson, E. M. & Fagerlund, U. H. M. Effect of sexual maturation and gonadectomy at sexual maturity on cortisol secretion rate in sockeye salmon (Oncorhynchus nerka). J. Fish. Res. Board Can. 27, 2287–2296 (1970).Article 

    Google Scholar 
    Dickhoff, W. W. Development, Maturation, and Senescence of Neuroendocrine Systems 253–266 (Elsevier, 1989).Book 

    Google Scholar 
    Maule, A. G., Schreck, C. B. & Kaattari, S. L. Changes in the immune system of coho salmon (Oncorhynchus kisutch) during the parr-to-smolt transformation and after implantation of cortisol. Can. J. Fish. Aquat. Sci. 44, 161–166 (1987).Article 
    CAS 

    Google Scholar 
    Llewellyn, M. S. et al. Parasitism perturbs the mucosal microbiome of Atlantic Salmon. Sci. Rep. 7, 1–10 (2017).Article 

    Google Scholar 
    Vasemägi, A., Visse, M. & Kisand, V. Effect of environmental factors and an emerging parasitic disease on gut microbiome of wild Salmonid fish. mSphere 2, e00418-17 (2017).Article 
    PubMed Central 

    Google Scholar 
    Kelly, C. & Salinas, I. Under pressure: Interactions between commensal microbiota and the teleost immune system. Front. Immunol. 8, 559 (2017).Article 
    PubMed Central 

    Google Scholar 
    Fast, M. D., Hosoya, S., Johnson, S. C. & Afonso, L. O. B. Cortisol response and immune-related effects of Atlantic salmon (Salmo salar Linnaeus) subjected to short- and long-term stress. Fish Shellfish Immunol. 24, 194–204 (2008).Article 
    CAS 

    Google Scholar 
    Carrizo, V. et al. Effect of cortisol on the immune-like response of rainbow trout (Oncorhynchus mykiss) myotubes challenged with Piscirickettsia salmonis. Vet. Immunol. Immunopathol. 237, 110240 (2021).Article 
    CAS 

    Google Scholar 
    Nervino, S. Intestinal lesions and parasites associated with prespawn mortality in Chinook salmon (Oncorhynchus tshawytscha). (2022).Couch, C. E. et al. Enterocytozoon schreckii n. sp. infects the enterocytes of adult chinook salmon (Oncorhynchus tshawytscha) and may be a sentinel of immunosenescence. mSphere 7, e0090821 (2022).Article 

    Google Scholar 
    Redding, J. M., Schreck, C. B., Birks, E. K. & Ewing, R. D. Cortisol and its effects on plasma thyroid hormone and electrolyte concentrations in fresh water and during seawater acclimation in yearling coho salmon, Oncorhynchus kisutch. Gen. Comp. Endocrinol. 56, 146–155 (1984).Article 
    CAS 

    Google Scholar 
    Marotz, C. et al. DNA extraction for streamlined metagenomics of diverse environmental samples. Biotechniques 62, 290–293 (2017).Article 
    CAS 

    Google Scholar 
    Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA. 108(Suppl 1), 4516–4522 (2011).Article 
    CAS 

    Google Scholar 
    Minich, J. J. et al. High-throughput miniaturized 16S rRNA amplicon library preparation reduces costs while preserving microbiome integrity. mSystems 3, e00166-18 (2018).Article 
    PubMed Central 

    Google Scholar 
    Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Escalas, A. et al. Ecological specialization within a carnivorous fish family is supported by a herbivorous microbiome shaped by a combination of gut traits and specific diet. Front. Mar. Sci. 8, 622883 (2021).Article 

    Google Scholar 
    Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: Assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).Article 
    CAS 

    Google Scholar 
    Apprill, A., McNally, S., Parsons, R. & Weber, L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 75, 129–137 (2015).Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. (2020). https://www.R-project.org/.Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).Article 
    CAS 

    Google Scholar 
    Wright, E. Using DECIPHER v2.0 to analyze big biological sequence data in R. R. J. 8, 352 (2016).Article 

    Google Scholar 
    Schliep, K., Potts, A. J., Morrison, D. A. & Grimm, G. W. Intertwining phylogenetic trees and networks. Methods Ecol. Evol. 8, 1212–1220 (2017).Article 

    Google Scholar 
    Shannon, C. E. A mathematical theory of communication. Bell Syst. Tech. J. 27, 623–656 (1948).Article 
    MathSciNet 
    MATH 

    Google Scholar 
    Shepard, R. N. The analysis of proximities: Multidimensional scaling with an unknown distance function. II. Psychometrika 27, 219–246 (1962).Article 
    MathSciNet 
    MATH 

    Google Scholar 
    Oksanen, J. et al. The vegan package. Community Ecol. Packag. 10, 631–637 (2007).
    Google Scholar 
    Martinez Arbizu, P. pairwiseAdonis: Pairwise Multilevel Comparison using Adonis. Preprint at (2017)Zhang, Y. Likelihood-based and Bayesian methods for Tweedie compound Poisson linear mixed models. Stat. Comput. 23, 743–757 (2013).Article 
    MathSciNet 
    CAS 
    MATH 

    Google Scholar 
    Hassenrück, C., Reinwald, H., Kunzmann, A., Tiedemann, I. & Gärdes, A. Effects of thermal stress on the gut microbiome of juvenile milkfish (Chanos chanos). Microorganisms 9, 5 (2020).Article 
    PubMed Central 

    Google Scholar 
    Liu, Y. et al. Response mechanism of gut microbiome and metabolism of European seabass (Dicentrarchus labrax) to temperature stress. Sci. Total Environ. 813, 151786 (2022).Article 
    CAS 

    Google Scholar 
    Du, F. et al. Response of the gut microbiome of Megalobrama amblycephala to crowding stress. Aquaculture 500, 586–596 (2019).Article 
    CAS 

    Google Scholar 
    Stothart, M. R., Palme, R. & Newman, A. E. M. It’s what’s on the inside that counts: Stress physiology and the bacterial microbiome of a wild urban mammal. Proc. Biol. Sci. 286, 20192111 (2019).PubMed Central 

    Google Scholar 
    Michels, N. et al. Gut microbiome patterns depending on children’s psychosocial stress: Reports versus biomarkers. Brain Behav. Immun. 80, 751–762 (2019).Article 

    Google Scholar 
    Zhao, H., Jiang, X. & Chu, W. Shifts in the gut microbiota of mice in response to dexamethasone administration. Int. Microbiol. 23, 565–573 (2020).Article 
    CAS 

    Google Scholar 
    Zanuzzo, F. S., Sabioni, R. E., Marzocchi-Machado, C. M. & Urbinati, E. C. Modulation of stress and innate immune response by corticosteroids in pacu (Piaractus mesopotamicus). Comp. Biochem. Physiol. A Mol. Integr. Physiol. 231, 39–48 (2019).Article 
    CAS 

    Google Scholar 
    Timmermans, S., Souffriau, J. & Libert, C. A general introduction to glucocorticoid biology. Front. Immunol. 10, 1545 (2019).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Kugathas, S. & Sumpter, J. P. Synthetic glucocorticoids in the environment: First results on their potential impacts on fish. Environ. Sci. Technol. 45, 2377–2383 (2011).Article 
    CAS 

    Google Scholar 
    Schaal, P. et al. Links between host genetics, metabolism, gut microbiome and amoebic gill disease (AGD) in Atlantic salmon. Anim. Microbiome 4, 53 (2022).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Birlanga, V. B. et al. Dynamic gill and mucus microbiomes during a gill disease episode in farmed Atlantic salmon. Sci. Rep. 12, 16719 (2022).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Cipriano, R. C., Ford, L. A., Smith, D. R., Schachte, J. H. & Petrie, C. J. Differences in detection of Aeromonas salmonicida in covertly infected Salmonid fishes by the stress-inducible furunculosis test and culture-based assays. J. Aquat. Anim. Health 9, 108–113 (1997).Article 

    Google Scholar 
    Lovy, J., Speare, D. J., Stryhn, H. & Wright, G. M. Effects of dexamethasone on host innate and adaptive immune responses and parasite development in rainbow trout Oncorhynchus mykiss infected with Loma salmonae. Fish Shellfish Immunol. 24, 649–658 (2008).Article 
    CAS 

    Google Scholar 
    Bakhtiyar, Y., Yousuf, T. & Arafat, M. Y. Bacterial Fish Diseases 269–278 (Elsevier, 2022).Book 

    Google Scholar 
    Benda, S. E., Naughton, G. P., Caudill, C. C., Kent, M. L. & Schreck, C. B. Cool, pathogen-free refuge lowers pathogen-associated prespawn mortality of Willamette River Chinook salmon. Trans. Am. Fish. Soc. 144, 1159–1172 (2015).Article 

    Google Scholar 
    Barton, B. A. & Iwama, G. K. Physiological changes in fish from stress in aquaculture with emphasis on the response and effects of corticosteroids. Annu. Rev. Fish Dis. 1, 3–26 (1991).Article 

    Google Scholar 
    Dolan, B. P. et al. Innate and adaptive immune responses in migrating spring-run adult chinook salmon, Oncorhynchus tshawytscha. Fish Shellfish Immunol. 48, 136–144 (2016).Article 
    CAS 

    Google Scholar 
    Wedemeyer, G. A. Physiological response of juvenile coho salmon (Oncorhynchus kisutch) and rainbow trout (Salmo gairdneri) to handling and crowding stress in intensive fish culture. J. Fish. Res. Board Can. 33, 2699–2702 (1976).Article 

    Google Scholar 
    Suomalainen, L.-R., Tiirola, M. A. & Valtonen, E. T. Influence of rearing conditions on Flavobacterium columnare infection of rainbow trout, Oncorhynchus mykiss (Walbaum). J. Fish Dis. 28, 271–277 (2005).Article 

    Google Scholar 
    Schmidt-Posthaus, H., Bernet, D., Wahli, T. & Burkhardt-Holm, P. Morphological organ alterations and infectious diseases in brown trout Salmo trutta and rainbow trout Oncorhynchus mykiss exposed to polluted river water. Dis. Aquat. Organ. 44, 161–170 (2001).Article 
    CAS 

    Google Scholar 
    Shi, N., Li, N., Duan, X. & Niu, H. Interaction between the gut microbiome and mucosal immune system. Mil. Med. Res. 4, 1–7 (2017).CAS 

    Google Scholar 
    Mitchell, S. O. et al. “Candidatus Branchiomonas cysticola” is a common agent of epitheliocysts in seawater-farmed Atlantic salmon Salmo salar in Norway and Ireland. Dis. Aquat. Organ. 103, 35–43 (2013).Article 
    CAS 

    Google Scholar 
    Kormas, K. A., Meziti, A., Mente, E. & Frentzos, A. Dietary differences are reflected on the gut prokaryotic community structure of wild and commercially reared sea bream (Sparus aurata). Microbiologyopen 3, 718–728 (2014).Article 
    CAS 
    PubMed Central 

    Google Scholar 
    Engel, M. et al. Influence of lung CT changes in chronic obstructive pulmonary disease (COPD) on the human lung microbiome. PLoS ONE 12, e0180859 (2017).Article 
    PubMed Central 

    Google Scholar 
    Lucasson, A. et al. A core of functionally complementary bacteria colonizes oysters in Pacific Oyster Mortality Syndrome. bioRxiv https://doi.org/10.1101/2020.11.16.384644 (2020).Article 

    Google Scholar  More

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    House Sparrow (Passer domesticus) escape behavior is triggered faster in smaller settlements

    Sol, D., Lapiedra, O. & González-Lagos, C. Behavioural adjustments for a life in the city. Anim. Behav. 85, 1101–1112 (2013).Article 

    Google Scholar 
    Ritzel, K. & Gallo, T. Behavior change in urban mammals: A systematic review. Front. Ecol. Evol. 8, 393 (2020).Article 

    Google Scholar 
    Gil, D. & Brumm, H. Avian Urban Ecology: Behavioural and Physiological Adaptations (Oxford University Press, 2014).
    Google Scholar 
    Stankowich, T. & Blumstein, D. T. Fear in animals: A meta-analysis and review of risk assessment. Proc. R. Soc. B Biol. Sci. 272, 2627–2634 (2005).Article 

    Google Scholar 
    Ydenberg, R. C. & Dill, L. M. The economics of fleeing from predators. Adv. Study Behav. 16, 229–249 (1986).Article 

    Google Scholar 
    Blumstein, D. T. Flight-initiation distance in birds is dependent on intruder starting distance. J. Wildl. Manag. 67, 852–857 (2003).Article 

    Google Scholar 
    Cooper, W. E. & Frederick, W. G. Optimal flight initiation distance. J. Theor. Biol. 244, 59–67 (2007).Article 
    MathSciNet 
    MATH 

    Google Scholar 
    Blumstein, D. T. & Fernández-Juricic, E. A Primer of Conservation Behavior (Sinauer Associates, 2010).
    Google Scholar 
    Nunes, J. A. C. C. et al. Global trends on reef fishes’ ecology of fear: Flight initiation distance for conservation. Mar. Environ. Res. 136, 153–157 (2018).Article 
    CAS 

    Google Scholar 
    Haidt, A., Kamiński, T., Borowik, T. & Kowalczyk, R. Human and the beast—Flight and aggressive responses of European bison to human disturbance. PLoS ONE 13, e0200635 (2018).Article 

    Google Scholar 
    Breck, S. W., Poessel, S. A., Mahoney, P. & Young, J. K. The intrepid urban coyote: A comparison of bold and exploratory behavior in coyotes from urban and rural environments. Sci. Rep. 9, 2104 (2019).Article 

    Google Scholar 
    Andrade, M. & Blumstein, D. T. Anti-predator behavior along elevational and latitudinal gradients in dark-eyed juncos. Curr. Zool. 66, 239–245 (2020).Article 

    Google Scholar 
    Cooper, W. & Pérez-Mellado, V. Escape by the Balearic Lizard (Podarcis lilfordi) is affected by elevation of an approaching predator, but not by some other potential predation risk factors. Acta Herpetol. 6, 247–259 (2011).
    Google Scholar 
    Møller, A. P. Interspecific variation in fear responses predicts urbanization in birds. Behav. Ecol. 21, 365–371 (2010).Article 

    Google Scholar 
    Samia, D. S. M. et al. Rural–urban differences in escape behavior of European birds across a latitudinal gradient. Front. Ecol. Evol. 5, 66 (2017).Article 

    Google Scholar 
    Morelli, F. et al. Contagious fear: Escape behavior increases with flock size in European gregarious birds. Ecol. Evol. 9, 6096–6104 (2019).Article 

    Google Scholar 
    Tätte, K., Møller, A. P. & Mänd, R. Towards an integrated view of escape decisions in birds: Relation between flight initiation distance and distance fled. Anim. Behav. 136, 75–86 (2018).Article 

    Google Scholar 
    Bókony, V., Kulcsár, A., Tóth, Z. & Liker, A. Personality traits and behavioral syndromes in differently urbanized populations of house sparrows (Passer domesticus). PLoS ONE 7, e36639 (2012).Article 

    Google Scholar 
    Vincze, E. et al. Habituation to human disturbance is faster in urban than rural house sparrows. Behav. Ecol. 27, 1304–1313 (2016).Article 

    Google Scholar 
    Seress, G., Bókony, V., Heszberger, J. & Liker, A. Response to predation risk in urban and rural house sparrows: Response to predation risk in house sparrows. Ethology 117, 896–907 (2011).Article 

    Google Scholar 
    Metcalf, B. M., Davies, S. & Ladd, P. G. Adaptation of behaviour by two bird species as a result of habituation to humans. Aust. Field Ornithol. 18, 306–312 (2000).
    Google Scholar 
    Blumstein, D. T. Attention, habituation, and antipredator behaviour: Implications for urban birds. In Avian Urban Ecology: Behavioural and Physiological Adaptations (eds Gil, D. & Brumm, H.) 41–53 (Oxford University Press, 2014).
    Google Scholar 
    Cavalli, M., Baladrón, A. V., Isacch, J. P., Biondi, L. M. & Bó, M. S. The role of habituation in the adjustment to urban life: An experimental approach with burrowing owls. Behav. Process. 157, 250–255 (2018).Article 
    CAS 

    Google Scholar 
    Fossett, T. E. & Hyman, J. The effects of habituation on boldness of urban and rural song sparrows (Melospiza melodia). Behaviour 159, 243–257 (2021).Article 

    Google Scholar 
    Møller, A. P., Grim, T., Ibanez-Alamo, J. D., Marko, G. & Tryjanowski, P. Change in flight initiation distance between urban and rural habitats following a cold winter. Behav. Ecol. 24, 1211–1217 (2013).Article 

    Google Scholar 
    Møller, A. P. Reproductive behaviour. In Behavioural Responses to a Changing World (eds Candolin, U. & Wong, B. B. M.) 106–118 (Oxford University Press, 2012).Chapter 

    Google Scholar 
    Seress, G. & Liker, A. Habitat urbanization and its effects on birds. Acta Zool. Acad. Sci. Hung. 61, 373–408 (2015).Article 

    Google Scholar 
    Eötvös, C. B., Magura, T. & Lövei, G. L. A meta-analysis indicates reduced predation pressure with increasing urbanization. Landsc. Urban Plan. 180, 54–59 (2018).Article 

    Google Scholar 
    Fischer, J. D., Cleeton, S. H., Lyons, T. P. & Miller, J. R. Urbanization and the predation paradox: The role of trophic dynamics in structuring vertebrate communities. Bioscience 62, 809–818 (2012).Article 

    Google Scholar 
    Vincze, E. et al. Great tits take greater risk toward humans and sparrowhawks in urban habitats than in forests. Ethology 125, 686–701 (2019).Article 

    Google Scholar 
    Anderson, T. R. Biology of the Ubiquitous House Sparrow: From Genes to Populations (Oxford University Press, 2006).Book 

    Google Scholar 
    Santiago-Alarcon, D., Carbó-Ramírez, P., Macgregor-Fors, I., Chávez-Zichinelli, C. A. & Yeh, P. J. The prevalence of avian haemosporidian parasites in an invasive bird is lower in urban than in non-urban environments. Ibis 162, 201–214 (2020).Article 

    Google Scholar 
    García-Arroyo, M. & MacGregor-Fors, I. Tolerant to humans? Assessment of alert and flight initiation distances of two bird species in relation to sex, flock size, and environmental characteristics. Ethol. Ecol. Evol. 32, 445–456 (2020).Article 

    Google Scholar 
    Møller, A. P. Successful city dwellers: A comparative study of the ecological characteristics of urban birds in the Western Palearctic. Oecologia 159, 849–858 (2009).Article 

    Google Scholar 
    Cohen, S. B. & Dor, R. Phenotypic divergence despite low genetic differentiation in house sparrow populations. Sci. Rep. 8, 394 (2018).Article 

    Google Scholar 
    Martin, L. B. & Fitzgerald, L. A taste for novelty in invading house sparrows, Passer domesticus. Behav. Ecol. 16, 702–707 (2005).Article 

    Google Scholar 
    Quesada, J. et al. Bold or shy? Examining the risk-taking behavior and neophobia of invasive and non-invasive house sparrows. Anim. Biodivers. Conserv. 45, 97–106 (2022).Article 

    Google Scholar 
    Díaz, M. et al. The geography of fear: A latitudinal gradient in anti-predator escape distances of birds across Europe. PLoS ONE 8, e64634 (2013).Article 

    Google Scholar 
    Quesada, J. & Calderon, J. Pardal comú. In Atles Dels Ocells Nidificants De Catalunya: Distribució i Abundancia 2015–2018 i Canvi des de 1980 (eds Franch, M. et al.) (Institut Català d’Ornitologia/Cossetània Edicions, 2021).
    Google Scholar 
    Shochat, E. Credit or debit? Resource input changes population dynamics of city-slicker birds. Oikos 106, 622–626 (2004).Article 

    Google Scholar 
    Statistical Institute of Catalonia. The municipality in figures. Bages. gencat https://www.idescat.cat/emex/?id=07 (2020).Bellet Sanfeliu, C. The evolution of urban planning in medium-sized Catalan cities (1979–2019). Urban Sci. 5, 36 (2021).Article 

    Google Scholar 
    Borras, A. & Junyent, F. Vertebrats de la Catalunya Central (Edicions Intercomarcals, 1993).
    Google Scholar 
    Vangestel, C., Braeckman, B. P., Matheve, H. & Lens, L. Constraints on home range behaviour affect nutritional condition in urban house sparrows (Passer domesticus). Biol. J. Linn. Soc. 101, 41–50 (2010).Article 

    Google Scholar 
    Herrando, S., Brotons, L., Estrada, J., Guallar, S. & Anton, M. Atles dels Ocells de Catalunya a I’hivern 2006–2009: Catalan Winter Bird Atlas 2006–2009 (Lynx Ed, 2011).
    Google Scholar 
    MacGregor-Fors, I. How to measure the urban-wildland ecotone: Redefining ‘peri-urban’ areas. Ecol. Res. 25, 883–887 (2010).Article 

    Google Scholar 
    Lemoine-Rodríguez, R., MacGregor-Fors, I. & Muñoz-Robles, C. Six decades of urban green change in a neotropical city: A case study of Xalapa, Veracruz, Mexico. Urban Ecosyst. 22, 609–618 (2019).Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).
    Google Scholar 
    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).MATH 

    Google Scholar 
    Shochat, E. et al. Invasion, competition, and biodiversity loss in urban ecosystems. Bioscience 60, 199–208 (2010).Article 

    Google Scholar 
    Sol, D. et al. Risk-taking behavior, urbanization and the pace of life in birds. Behav. Ecol. Sociobiol. 72, 59 (2018).Article 

    Google Scholar 
    Geue, D. & Partecke, J. Reduced parasite infestation in urban Eurasian blackbirds (Turdus merula): A factor favoring urbanization?. Can. J. Zool. 86, 1419–1425 (2008).Article 

    Google Scholar 
    MacGregor-Fors, I., Quesada, J., Lee, J.G.-H. & Yeh, P. J. On the lookout for danger: House sparrow alert distance in three cities. Urban Ecosyst. 22, 955–960 (2019).Article 

    Google Scholar  More