More stories

  • in

    A life history model of the ecological and evolutionary dynamics of polyaneuploid cancer cells

    Housman, G. et al. Drug resistance in cancer: An overview. Cancers 6(3), 1769 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vasan, N. Baselga, J. & Hyman, D. M. A View on Drug Resistance in Cancer, 11 (2019).Casás-Selves, M. & Degregori, J. How cancer shapes evolution and how evolution shapes cancer (2011).Dujon, A. M. et al. Identifying key questions in the ecology and evolution of cancer. Evol. Appl. 14, 4 (2021).
    Google Scholar 
    Korolev, K. S., Xavier, J. B. & Gore, J. Turning ecology and evolution against cancer (2014).Merlo, L. M. F., Pepper, J. W., Reid, B. J. & Maley, C. C. Cancer as an evolutionary and ecological process. Nat. Rev. Cancer 6(12), 924–935 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ujvari, B., Roche, B. & Thomas, F. Ecology and Evolution of Cancer 1st edn. (Academic Press, 2017).
    Google Scholar 
    Brown, R. L. What evolvability really is. Brit. J. Philos. Sci. 65, 3 (2014).MathSciNet 
    Article 

    Google Scholar 
    Crother, B. I. & Murray, C. M. Early usage and meaning of evolvability. Ecol. Evol. 9, 7 (2019).Article 

    Google Scholar 
    Pigliucci, M. Is evolvability evolvable? (2008).Sniegowski, P. D. & Murphy, H. A. Evolvability (2006).Bukkuri, A. & Brown, J. S. Evolutionary game theory: Darwinian dynamics and the G function approach. MDPI Games 12(4), 1–19 (2021).MathSciNet 
    MATH 

    Google Scholar 
    Fisher, R. A. The Genetical Theory of Natural Selection (The Clarendon Press, 1930).MATH 
    Book 

    Google Scholar 
    Li, C. C. Fundamental theorem of natural selection. Nature 214(5087), 4 (1967).Article 

    Google Scholar 
    Vincent, T. L. & Brown, J. S. Evolutionary Game Theory, Natural Selection, and Darwinian Dynamics (Cambridge University Press, 2005).MATH 
    Book 

    Google Scholar 
    Hanahan, D. & Weinberg, R. A. The next generation. Leading edge review hallmarks of cancer. Cell 144, 646–674 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pienta, K. J. et al. Cancer cells employ an evolutionarily conserved polyploidization program to resist therapy. Semin. Cancer Biol. 20, 1–15 (2020).
    Google Scholar 
    Virchow, R. As based upon physiological and pathological histology: Cellular pathology. Nutr. Rev. 47(1), 23–25 (1989).CAS 
    PubMed 
    Article 

    Google Scholar 
    Razmik, M., Bonnie, A. & David, M. Roles of polyploid/multinucleated giant cancer cells in metastasis and disease relapse following anticancer treatment. Cancers 10(4), 4 (2018).
    Google Scholar 
    Amend, S. R. et al. Polyploid giant cancer cells: Unrecognized actuators of tumorigenesis, metastasis, and resistance. Prostate 79(13), 1489–1497 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kuczler, M. D., Olseen, A. M., Pienta, K. J. & Amend, S. R. ROS-induced cell cycle arrest as a mechanism of resistance in polyaneuploid cancer cells (PACCs). Prog. Biophys. Mol. Biol. 20, 3–7 (2021).Article 
    CAS 

    Google Scholar 
    Kostecka, L. G., Pienta, K. J. & Amend, S. R. Polyaneuploid cancer cell dormancy: Lessons from evolutionary phyla. Front. Ecol. Evol. 9, 439 (2021).Article 

    Google Scholar 
    Rajaraman, R., Rajaraman, M. M., Rajaraman, S. R. & Guernsey, D. L. Neosis—-a paradigm of self-renewal in cancer. Cell Biol. Int. 29(12), 1084–1097 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Rajaraman, R., Guernsey, D. L., Rajaraman, M. M. & Rajaraman, S. R. Neosis—a parasexual somatic reduction division in cancer. Int. J. Hum. Genet. 7(1), 29–48 (2007).CAS 
    Article 

    Google Scholar 
    Sundaram, M., Guernsey, D. L., Rajaraman, M. M. & Rajaraman, R. Neosis: A novel type of cell division in cancer. Cancer Biol. Ther. 3(2), 207–218 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Illidge, T. M., Cragg, M. S., Fringes, B., Olive, P. & Erenpreisa, J. A. Polyploid giant cells provide a survival mechanism for p53 mutant cells after DNA damage. Cell Biol. Int. 24(9), 621–633 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    Puig, P. E. et al. Tumor cells can escape DNA-damaging cisplatin through DNA endoreduplication and reversible polyploidy. Cell Biol. Int. 32(9), 1031–1043 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhang, S. et al. Generation of cancer stem-like cells through the formation of polyploid giant cancer cells. Oncogene 33(1), 116–128 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Comai, L. The advantages and disadvantages of being polyploid. Nat. Rev. Genet. 6(11), 836–846 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hassel, C., Zhang, B., Dixon, M. & Calvi, B. R. Induction of endocycles represses apoptosis independently of differentiation and predisposes cells to genome instability. Development (Cambridge) 141(1), 112–123 (2014).CAS 
    Article 

    Google Scholar 
    Lee, H. O., Davidson, J. M. & Duronio, R. J. Endoreplication: Polyploidy with purpose. Genes Dev. 23(21), 2461–2477 (2009).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Basener, W. F. & Sanford, J. C. The fundamental theorem of natural selection with mutations. J. Math. Biol. 76(7), 1589–1622 (2018).MathSciNet 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Frank, S. A. & Slatkin, M. Fisher’s fundamental theorem of natural selection. Trends Ecol. Evol. 7(3), 92–95 (1992).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lessard, S. Fisher’s fundamental theorem of natural selection revisited. Theor. Popul. Biol. 52(2), 119–136 (1997).MathSciNet 
    CAS 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Das, P., Mukherjee, S. & Das, P. An investigation on Michaelis–Menten kinetics based complex dynamics of tumor-immune interaction. Chaos Solitons Fractals 1, 28 (2019).MathSciNet 
    CAS 
    MATH 

    Google Scholar 
    Renee Fister, K. & Panetta, J. C. Optimal control applied to competing chemotherapeutic cell-kill strategies. SIAM J. Appl. Math. 63, 6 (2003).MathSciNet 
    MATH 

    Google Scholar 
    López, Á. G., Seoane, J. M. & Sanjuán, M. A. F. Decay dynamics of tumors. PLoS One 11, 6 (2016).
    Google Scholar 
    Pienta, K. J., Hammarlund, E. U., Brown, J. S., Amend, S. R. & Axelrod, R. M. Cancer recurrence and lethality are enabled by enhanced survival and reversible cell cycle arrest of polyaneuploid cells. Proc. Natl. Acad. Sci. U.S.A. 118(7), 2 (2021).Article 
    CAS 

    Google Scholar 
    Pienta, K. J., Hammarlund, E. U., Axelrod, R., Brown, J. S. & Amend, S. R. Poly-aneuploid cancer cells promote evolvability, generating lethal cancer. Evol. Appl. 13(7), 1626–1634 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mittal, K. et al. Multinucleated polyploidy drives resistance to Docetaxel chemotherapy in prostate cancer. Br. J. Cancer 116, 9 (2017).Article 
    CAS 

    Google Scholar 
    Cunningham, J. J., Bukkuri, A., Gatenby, R., Brown, J. S. & Gillies, R. J. Coupled source-sink habitats produce spatial and temporal variation of cancer cell molecular properties as an alternative to branched clonal evolution and stem cell paradigms. Front. Ecol. Evol. 9, 472 (2021).Article 

    Google Scholar 
    Fujiwara, M. & Diaz-Lopez, J. Constructing stage-structured matrix population models from life tables: Comparison of methods. PeerJ 5(10), 1–27 (2017).
    Google Scholar 
    Kendall, B. E. et al. Persistent problems in the construction of matrix population models. Ecol. Model. 406, 33–43 (2019).Article 

    Google Scholar 
    Law, R. & Edley, M. T. Transient dynamics of populations with age- and size-dependent vital rates. Ecology 71(5), 1863–1870 (1990).Article 

    Google Scholar 
    Velde, R. V. et al. Resistance to targeted therapies as a multifactorial, gradual adaptation to inhibitor specific selective pressures. Nat. Commun. 11(1), 1–13 (2020).Article 
    CAS 

    Google Scholar 
    Salmina, K. et al. The cancer aneuploidy paradox: In the light of evolution. Genes 10(2), 83 (2019).CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Turajlic, S., Sottoriva, A., Graham, T. & Swanton, C. Resolving genetic heterogeneity in cancer. Nat. Rev. Genet. 20(7), 404–416 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Miller, A. K., Brown, J. S., Enderling, H., Basanta, D. & Whelan, C. J. The evolutionary ecology of dormancy in nature and in cancer. Front. Ecol. Evol. 9, 5 (2021).Article 

    Google Scholar 
    Geiser, F. Hibernation. Curr. Biol. 23(5), R188–R193 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lyman, C. P. & Chatfield, P. O. Physiology of hibernation in mammals. Physiol. Rev. 35(2), 403–425 (1955).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lin, K. C. et al. The role of heterogeneous environment and docetaxel gradient in the emergence of polyploid, mesenchymal and resistant prostate cancer cells. Clin. Exp. Metas. 36(2), 97–108 (2019).Article 

    Google Scholar 
    Lin, K. C. et al. An: In vitro tumor swamp model of heterogeneous cellular and chemotherapeutic landscapes. Lab Chip 20(14), 2453–2464 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kawamura, E. et al. Identification of novel small molecule inhibitors of centrosome clustering in cancer cells. Oncotarget 4(10), 1763–1776 (2013).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kostecka, L. G. et al. High KIFC1 expression is associated with poor prognosis in prostate cancer. Med. Oncol. 38, 1–9 (2021).Article 
    CAS 

    Google Scholar 
    Sekino, Y. et al. KIFC1 induces resistance to docetaxel and is associated with survival of patients with prostate cancer. Urol. Oncol. Semin. Original Investig. 35(1), 1–8 (2017).Article 

    Google Scholar 
    Xiao, Y. X. & Yang, W. X. KIFC1: A promising chemotherapy target for cancer treatment?. Oncotarget 7(30), 1–9 (2016).
    Google Scholar 
    Law, M. E., Corsino, P. E., Narayan, S. & Law, B. K. Cyclin-dependent kinase inhibitors as anticancer therapeutics. Mol. Pharmacol. 88, 5 (2015).Article 
    CAS 

    Google Scholar 
    Tadesse, S., Caldon, E. C., Tilley, W. & Wang, S. Cyclin-Dependent Kinase 2 Inhibitors in Cancer Therapy: An Update (2019).Zhang, M. et al. CDK inhibitors in cancer therapy, an overview of recent development. Am. J. Cancer Res. 11, 5 (2021).CAS 

    Google Scholar 
    Kostecka, L. G., Pienta, K. J. & Amend, S. R. Lipid droplet evolution gives insight into polyaneuploid cancer cell lipid droplet functions. Med. Oncol. 38(11), 1–10 (2021).Article 
    CAS 

    Google Scholar 
    Strobl, M. A. R. et al. Turnover modulates the need for a cost of resistance in adaptive therapy. Can. Res. 81, 4 (2021).Article 

    Google Scholar 
    West, J., Ma, Y. & Newton, P. K. Capitalizing on competition: An evolutionary model of competitive release in metastatic castration resistant prostate cancer treatment. J. Theor. Biol. 4, 55 (2018).MathSciNet 
    MATH 

    Google Scholar  More

  • in

    Spatial autocorrelation signatures of ecological determinants on plant community characteristics in high Andean wetlands

    Rudnick, D. A. et al. The role of landscape connectivity in planning and implementing conservation and restoration priorities. Issues Ecol. 16, 1–23 (2012).
    Google Scholar 
    Brudvig, L. A. Interpreting the effects of landscape connectivity on community diversity. J. Veg. Sci. 27, 4–5 (2016).Article 

    Google Scholar 
    Socolar, J. B., Gilroy, J. J., Kunin, W. E. & Edwards, D. P. How should beta-diversity inform biodiversity conservation?. Trends Ecol. Evol. 31, 67–80 (2016).PubMed 
    Article 

    Google Scholar 
    Leibold, M. A., Chase, J. M. & Ernest, S. K. M. Community assembly and the functioning of ecosystems: how metacommunity processes alter ecosystems attributes. Ecology 98, 909–919 (2017).PubMed 
    Article 

    Google Scholar 
    Kuczynski, L. & Grenouillet, G. Community disassembly under global change: Evidence in favor of the stress-dominance hypothesis. Global Change Biol. 24, 4417–4427 (2018).ADS 
    Article 

    Google Scholar 
    Münkemüller, T. et al. From diversity indices to community assembly processes: A test with simulated data. Ecography 35, 468–480 (2012).Article 

    Google Scholar 
    Seabloom, E. W., BJørnstad, O. N., Bolker, B. M. & Reichman, O. J. Spatial signature of environmental heterogeneity, dispersal, and competition in successional grasslands. Ecol. Monogr. 75, 199–214 (2005).Article 

    Google Scholar 
    Vellend, M. Conceptual synthesis in community ecology. Q. Rev. Biol. 85, 183–206 (2010).PubMed 
    Article 

    Google Scholar 
    Fortin, M. J. & Dale, M. Spatial Analysis: A Guide for Ecologist (Cambridge Univ. Press., 2005).McIntire, E. J. B. & Fajardo, A. Beyond description: the active and effective way to infer processes from spatial patterns. Ecology 90, 46–56 (2009).PubMed 
    Article 

    Google Scholar 
    Smith, T. W. & Lundholm, J. T. Variation partitioning as a tool to distinguish between niche and neutral processes. Ecography 33, 648–655 (2010).Article 

    Google Scholar 
    Dray, S. et al. Community ecology in the age of multivariate multiscale spatial analysis. Ecol. Monogr. 82, 257–275 (2012).Article 

    Google Scholar 
    Dray, S. A new perspective about moran’s coefficient: Spatial autocorrelation as a linear regression problem. Geogr. Anal. 43, 127–141 (2011).Article 

    Google Scholar 
    Biswas, S. R., Mallik, A. U., Braithwaite, N. T. & Wagner, H. H. A conceptual framework for the spatial analysis of functional trait diversity. Oikos 125, 192–200 (2016).Article 

    Google Scholar 
    Biswas, S. R., MacDonald, R. L. & Chen, H. Y. H. Disturbance increases negative spatial autocorrelation in species diversity. Landsc. Ecol. 32, 823–834 (2017).Article 

    Google Scholar 
    Legendre, P. & Legendre, L. Numerical Ecology (Elsevier, 2012).Legendre, P. Spatial autocorrelation: Trouble or new paradigm?. Ecology 74, 1659–1673 (1993).Article 

    Google Scholar 
    Biswas, S. R., Xiang, J. & Li, H. Disturbance effects on spatial autocorrelation in biodiversity: An overview and a call for study. Diversity 13, 167 (2021).Article 

    Google Scholar 
    Bertin, A. et al. Effects of wind-driven spatial structure and environmental heterogeneity on high-altitude wetland macroinvertebrate assemblages with contrasting dispersal modes. Freshw. Biol. 60, 297–310 (2015).Article 

    Google Scholar 
    Bertin, A. et al. Genetic variation of loci potentially under selection confounds species-genetic diversity correlations in a fragmented habitat. Mol. Ecol. 26, 431–443 (2017).PubMed 
    Article 

    Google Scholar 
    Souvignet, M., Oyarzún, R., Verbist, K. M. J., Gaese, H. & Heinrich, J. Hydro-meteorological trends in semi-arid north-central Chile (29–32°S): Water resources implications for a fragile Andean region. Hydrol. Sci. J. 57, 479–495 (2012).Article 

    Google Scholar 
    Montecinos, S., Gutiérrez, J. R., López-Cortés, F. & López, D. Climatic characteristics of the semi-arid Coquimbo Region in Chile. J. Arid Environ. 126, 7–11 (2016).ADS 
    Article 

    Google Scholar 
    Gilbert, B. & Levine, J. M. Ecological drift and the distribution of species diversity. Proc. Biol. Sci. 284, 1–10 (2017).
    Google Scholar 
    Ruzzier, E. et al. From island biogeography to conservation: A multi-taxon and multi-taxonomic rank approach in the Tuscan archipelago. Land 10, 486 (2021).Article 

    Google Scholar 
    Siqueira, T. et al. Community size can affect the signals of ecological drift and niche selection on biodiversity. Ecology 101, e03014 (2020).PubMed 
    Article 

    Google Scholar 
    Anthelme, F. & Dangles, O. Plant–plant interactions in tropical alpine environments. Perspect. Plant Ecol. 14, 363–372 (2012).Article 

    Google Scholar 
    Gavini, S. S., Ezcurra, C. & Aizen, M. A. Plant–plant interactions promote alpine diversification. Evol. Ecol. 33, 195–209 (2019).Article 

    Google Scholar 
    Callaway, R. M. et al. Positive interactions among alpine plants increase with stress. Nature 417, 844–848 (2002).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Cavieres, L. A. et al. Facilitative plant interactions and climate simultaneously drive alpine plant diversity. Ecol. Lett. 17, 193–202 (2014).ADS 
    PubMed 
    Article 

    Google Scholar 
    Kikvidze, Z. et al. The effects of foundation species on community assembly: A global study on alpine cushion plant communities. Ecology 96, 2064–2069 (2015).PubMed 
    Article 

    Google Scholar 
    Zhao, R. M., Zhang, H. & An, L. Z. Spatial patterns and interspecific relationships of two dominant cushion plants at three elevations on the Kunlun Mountain, China. Environ. Sci. Pollut. Res. 27, 17339–17349 (2020).CAS 
    Article 

    Google Scholar 
    Pugnaire, F. I., Losapio, G. & Schöb, C. Interacciones entre especies y el papel de las plantas cojín en ecosistemas de alta montaña bajo un clima cambiante. Ecosistemas 30, 2186 (2021).Article 

    Google Scholar 
    Cadotte, M. W. Dispersal and species diversity: A meta-analysis. Am. Nat. 167, 913–924 (2006).PubMed 
    Article 

    Google Scholar 
    Vellend, M. et al. Drawing ecological inferences from coincident patterns of population- and community-level biodiversity. Mol. Ecol. 23, 2890–2901 (2014).PubMed 
    Article 

    Google Scholar 
    Legendre, P. & De Cáceres, M. Beta diversity as the variance of community data: Dissimilarity coefficients and partitioning. Ecol. Lett. 16, 951–963 (2013).PubMed 
    Article 

    Google Scholar 
    Leibold, M. A. & Chase, J. M. Metacommunity Ecology (Princeton University Press, 2018).Wilsey, B. & Stirling, G. Species richness and evenness respond in a different manner to propagule density in developing prairie microcosm communities. Plant Ecol. 190, 259–273 (2007).Article 

    Google Scholar 
    Schamp, B. S., Arnott, S. E. & Joslin, K. L. Dispersal strength influences zooplankton co-occurrence patterns in experimental mesocosms. Ecology 96, 1074–1083 (2015).PubMed 
    Article 

    Google Scholar 
    Troncoso, A. J., Bertin, A., Osorio, R., Arancio, G. & Gouin, N. Comparative population genetics of two dominant plant species of high Andean wetlands reveals complex evolutionary histories and conservation perspectives in Chile’s Norte Chico. Conserv. Genet. 18, 1047–1060 (2017).Article 

    Google Scholar 
    Pfeiffer, V. W. et al. Partitioning genetic and species diversity refines our understanding of species–genetic diversity relationships. Ecol. Evol. 8, 12351–12364 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bello, F. D. et al. Hierarchical effects of environmental filters on the functional structure of plant communities: A case study in the French Alps. Ecography 36, 393–402 (2013).Article 

    Google Scholar 
    Moritz, C. et al. Disentangling the role of connectivity, environmental filtering, and spatial structure on metacommunity dynamics. Oikos 122, 1401–1410 (2013).
    Google Scholar 
    Wilsey, B. J. & Potvin, C. Biodiversity and ecosystem functioning: Importance of species evenness in an old field. Ecology 81, 887–892 (2000).Article 

    Google Scholar 
    Stirling, G. & Wilsey, B. Empirical relationships between species richness, evenness, and proportional diversity. Am. Nat. 158, 286–299 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Stevens, R. D. & Willig, M. R. Geographical ecology at the community level: Perspectives on the diversity of new world bats. Ecology 83, 545–560 (2002).Article 

    Google Scholar 
    Wilsey, B. J. & Polley, H. W. Effects of seed additions and grazing history on diversity and productivity of subhumid grasslands. Ecology 84, 920–931 (2003).Article 

    Google Scholar 
    Ma, M. Species richness vs evenness: Independent relationship and different responses to edaphic factors. Oikos 111, 192–198 (2005).Article 

    Google Scholar 
    Schmitz, O. J. Effects of predator hunting mode on grassland ecosystem function. Science 319, 952–954 (2008).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Stomp, M., Huisman, J., Mittelbach, G. G., Litchman, E. & Klausmeier, C. A. Large-scale biodiversity patterns in freshwater phytoplankton. Ecology 92, 2096–2107 (2011).PubMed 
    Article 

    Google Scholar 
    Zhang, H. et al. The relationship between species richness and evenness in plant communities along a successional gradient: A study from sub-alpine meadows of the eastern Qinghai-Tibetan plateau, China. PLoS ONE 7, e49024 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hubbell, S. P. The Unified Neutral Theory of Biodiversity and Biogeography (Princeton University Press, 2001).
    Google Scholar 
    Young, K. R. in Climate Change and Biodiversity in the Tropical Andes (eds Herzog, S. K., Martinez, R., Jørgensen, P. M. & Tiessen, H.) Ch. 8, 128–140 (Inter-American Institute for Global Change Research, 2011).López-Angulo, J. et al. Determinants of high mountain plant diversity in the Chilean Andes: From regional to local spatial scales. PLoS ONE 13, e0200216 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    MacArthur, R. H. & Wilson, E. O. The Theory of Island Biogeography (Princeton University Press, 1967).
    Google Scholar 
    Hanski, I. Metapopulation Ecology (Oxford University Press, 1999).
    Google Scholar 
    Blanchet, F. G., Cazelles, K. & Gravel, D. Co-occurrence is not evidence of ecological interactions. Ecol. Lett. 23, 1050–1063 (2020).PubMed 
    Article 

    Google Scholar 
    Kunte, K. Competition and species diversity: Removal of dominant species increases diversity in Costa Rican butterfly communities. Oikos 117, 69–76 (2008).Article 

    Google Scholar 
    Dray, S., Legendre, P. & Peres-Neto, P. R. Spatial modelling: A comprehensive framework for principal coordinate analysis of neighbour matrices (PCNM). Ecol. Model. 196, 483–493 (2006).Article 

    Google Scholar 
    Kikvidze, Z. et al. Linking patterns and processes in alpine plant communities: A global study. Ecology 86, 1395–1400 (2005).Article 

    Google Scholar 
    Hill, M. O. Diversity and evenness: A unifying notation and its consequences. Ecology 54, 427–432 (1973).Article 

    Google Scholar 
    Heip, C. H. R., Herman, P. M. J. & Soetaert, K. Indices of diversity and evenness. Océanis 4, 61–87 (1998).
    Google Scholar 
    Jost, L. Entropy and diversity. Oikos 113, 363–375 (2006).Article 

    Google Scholar 
    Jost, L. Partitioning diversity into independent alpha and beta components. Ecology 88, 2427–2439 (2007).PubMed 
    Article 

    Google Scholar 
    Jost, L. The relation between evenness and diversity. Diversity 2, 207–232 (2010).Article 

    Google Scholar 
    Pallmann, P. et al. Assessing group differences in biodiversity by simultaneously testing a user-defined selection of diversity indices. Mol. Ecol. Resour. 12, 1068–1078 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chao, A. et al. Rarefaction and extrapolation with Hill numbers: A framework for sampling and estimation in species diversity studies. Ecol. Monogr. 84, 45–67 (2014).Article 

    Google Scholar 
    Morris, E. K. et al. Choosing and using diversity indices: Insights for ecological applications from the german biodiversity exploratories. Ecol. Evol. 4, 3514–3524 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Beisel, J.-N., Usseglio-Polatera, P., Bachmann, V. & Moreteau, J.-C. A comparative analysis of evenness index sensitivity. Int. Rev. Hydrobiol. 88, 3–15 (2003).Article 

    Google Scholar 
    Fedor, P. & Zvaríková, M. in Encyclopedia of Ecology (ed Brian Fath) 337–346 (2019).Gatti, R. C., Amoroso, N. & Monaco, A. Estimating and comparing biodiversity with a single universal metric. Ecol. Model. 424, 8 (2020).
    Google Scholar 
    Lin, L., Deng, W., Huang, X. & Kang, B. Fish taxonomic, functional, and phylogenetic diversity and their vulnerabilities in the largest river in southeastern China. Ecol. Evol. 11, 11533–11548 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Squeo, F. A., Warner, B. G., Aravena, R. & Espinoza, D. Bofedales: High altitude peatlands of the central Andes. Rev. Chil. Hist. Nat. 79, 245–255 (2006).Article 

    Google Scholar 
    Villagrán-Mella, R., Aguayo, M., Parra, L. E. & González, A. Relación entre características del hábitat y estructura del ensamble de insectos en humedales palustres urbanos del centro-sur de Chile. Rev. Chil. Hist. Nat. 79, 195–211 (2006).Article 

    Google Scholar 
    Coronel, J. S., Declerck, S., Maldonado, M., Ollevier, F. & Brendonck, L. Temporary shallow pools in high-Andes ‘bofedal’ peatlands. Arch. Sci. 57, 85–96 (2004).CAS 

    Google Scholar 
    Wakeling, I. N. & Morris, J. J. A test of significance for partial least squares regression. J. Chemom. 7, 291–304 (1993).CAS 
    Article 

    Google Scholar 
    Foltête, J.-C., Clauzel, C. & Vuidel, G. A software tool dedicated to the modelling of landscape networks. Environ. Modell. Softw. 38, 316–327 (2012).Article 

    Google Scholar 
    Ricotta, C., Stanisci, A., Avena, G. C. & Blasi, C. Quantifying the network connectivity of landscape mosaics: a graph-theoretical approach. Community Ecol. 1, 89–94 (2000).Article 

    Google Scholar 
    Freeman, L. C. Centrality in social networks conceptual clarification. Soc. Netw. 1, 215–239 (1979).Article 

    Google Scholar 
    Urban, D. & Keitt, T. Landscape connectivity: A graph-theoretic perspective. Ecology 82, 1205–1218 (2001).Article 

    Google Scholar 
    Bodin, Ö. & Saura, S. Ranking individual habitat patches as connectivity providers: Integrating network analysis and patch removal experiments. Ecol. Model. 221, 2393–2405 (2010).Article 

    Google Scholar 
    Gotelli, N. J., Hart, E. M. & Ellison, A. M. EcoSimR: Null model analysis for ecological data. R package version 0.1.0. (R Foundation for Statistical Computing, 2015).Bivand, R. S. & Wong, D. W. S. Comparing implementations of global and local indicators of spatial association. TEST 27, 716–748 (2018).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Dray, S. et al. adespatial: multivariate multiscale spatial analysis. R package version 0.3-8. (R Foundation for Statistical Computing, 2020)Wagner, H. H. & Dray, S. Generating spatially constrained null models for irregularly spaced data using Moran spectral randomization methods. Methods Ecol. Evol. 6, 1169–1178 (2015).Article 

    Google Scholar 
    Monecke, A. & Leisch, F. semPLS: Structural equation modeling using partial least squares. J. Stat. Softw. 48, 1–32 (2012).Article 

    Google Scholar 
    Zhao, X., Li, Y., Song, H., Jia, Y. & Liu, J. Agents affecting the productivity of pine plantations on the Loess Plateau in China: A study based on structural equation modeling. Forests 11, 1328 (2020).Article 

    Google Scholar 
    Tenenhaus, M., Vinzi, V. E., Chatelin, Y.-M. & Lauro, C. PLS path modeling. Comput. Stat. Data Anal. 48, 159–205 (2005).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Gower, J. C. & Legendre, P. Metric and euclidean properties of dissimilarity coefficients. J. Classif. 3, 5–48 (1986).MathSciNet 
    MATH 
    Article 

    Google Scholar 
    Goslee, S. C. & Urban, D. L. The ecodist package for dissimilarity-based analysis of ecological data. J. Stat. Softw. 22, 1–19 (2007).Article 

    Google Scholar 
    Lumley, T. & Miller, A. leaps: Regression subset selection. R package version 2.7. http://CRAN.R-project.org/package=leaps (2004).AICcmodavg: Model Selection and Multimodel Inference Based on (Q)AIC(c). R package version 2.3-1. (2019).Freestone, A. L. & Inouye, B. D. Dispersal limitation and environmental heterogeneity shape scale-dependent diversity patterns in plant communities. Ecology 87, 2425–2432 (2006).PubMed 
    Article 

    Google Scholar 
    Li, F., Tonkin, J. D. & Haase, P. Local contribution to beta diversity is negatively linked with community-wide dispersal capacity in stream invertebrate communities. Ecol. Indic. 108, 105715 (2020).Article 

    Google Scholar 
    Vilmi, A., Karjalainen, S. M. & Heino, J. Ecological uniqueness of stream and lake diatom communities shows different macroecological patterns. Divers. Distrib. 23, 1042–1053 (2017).Article 

    Google Scholar 
    Baldeck, C. A., Tupayachi, R., Sinca, F., Jaramillo, N. J. E. & Asner, G. P. Environmental drivers of tree community turnover in western Amazonian forests. Ecography 39, 1089–1099 (2016).Article 

    Google Scholar 
    Chase, J. M. Stochastic community assembly causes higher biodiversity in more productive environments. Science 328, 1388–1391 (2010).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Chase, J. M. & Myers, J. A. Disentangling the importance of ecological niches from stochastic processes across scales. Philos. Trans. R. Soc. B. 366, 2351–2363 (2011).Article 

    Google Scholar 
    Segre, H. et al. Competitive exclusion, beta diversity, and deterministic vs. stochastic drivers of community assembly. Ecol. Lett. 17, 1400–1408 (2014).PubMed 
    Article 

    Google Scholar 
    Ceschin, F., Bini, L. M. & Padial, A. A. Correlates of fish and aquatic macrophyte beta diversity in the Upper Paraná River floodplain. Hydrobiologia 805, 377–389 (2018).CAS 
    Article 

    Google Scholar 
    Heino, J. et al. Unravelling the correlates of species richness and ecological uniqueness in a metacommunity of urban pond insects. Ecol. Indic. 73, 422–431 (2017).Article 

    Google Scholar 
    Leão, H., Siqueira, T., Torres, N. R. & Montag, L. F. D. A. Ecological uniqueness of fish communities from streams in modified landscapes of Eastern Amazonia. Ecol. Indic. 111, 106039 (2020).Article 

    Google Scholar 
    Vega-Álvarez, J., García-Rodríguez, J. A. & Cayuela, L. Facilitation beyond species richness. J. Ecol. 107, 722–734 (2019).Article 

    Google Scholar  More

  • in

    Effects of decadal climate variability on spatiotemporal distribution of Indo-Pacific yellowfin tuna population

    Burrows, M. T. et al. The pace of shifting climate in marine and terrestrial ecosystems. Science 334, 652–655 (2011).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Cheung, W. W. L., Dunne, J., Sarmiento, J. L. & Pauly, D. Integrating ecophysiology and plankton dynamics into projected maximum fisheries catch potential under climate change in the Northeast Atlantic. ICES J. Mar. Sci. 68, 1008–1018 (2011).Article 

    Google Scholar 
    Muhling, B. A. et al. Potential impact of climate change on the Intra-Americas Sea: Part 2. Implications for Atlantic bluefin tuna and skipjack tuna adult and larval habitats. J. Mar. Syst. 148, 1–13 (2015).Article 

    Google Scholar 
    Erauskin-Extramiana, M. et al. Large-scale distribution of tuna species in a warming ocean. Glob. Change Biol. 25, 2043–2060 (2019).ADS 
    Article 

    Google Scholar 
    Cheung, W. W. et al. Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Glob. Change Biol. 16, 24–35 (2010).ADS 
    Article 

    Google Scholar 
    Townhill, B. L., Couce, E., Bell, J., Reeves, S. & Yates, O. Climate change impacts on Atlantic oceanic island tuna fisheries. Front. Mar. Sci. 8, 140 (2021).Article 

    Google Scholar 
    Wu, Y. L., Lan, K. W. & Tian, Y. J. Determining the effect of multiscale climate indices on the global yellowfin tuna (Thunnus albacares) population using a time series analysis. Deep Sea Res. Part II Top. Stud. Oceanogr. 175, 104808 (2020).Article 

    Google Scholar 
    Faillettaz, R., Beaugrand, G., Goberville, E. & Kirby, R. R. Atlantic Multidecadal Oscillations drive the basin-scale distribution of Atlantic bluefin tuna. Sci. Adv. 5(1), eaar6993 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lan, K. W., Evans, K. & Lee, M. A. Effects of climate variability on the distribution and fishing conditions of yellowfin tuna (Thunnus albacares) in the western Indian Ocean. Clim. Change 119, 63–77 (2013).ADS 
    Article 

    Google Scholar 
    Lan, K. W., Chang, Y. J. & Wu, Y. L. Influence of oceanographic and climatic variability on the catch rate of yellowfin tuna (Thunnus albacares) cohorts in the Indian Ocean. Deep Sea Res. Part II Top. Stud. Oceanogr. 175, 104681 (2019).Article 

    Google Scholar 
    Drinkwater, K. et al. Climate forcing on marine ecosystems. In Marine Ecosystems and Global Change 11–39 (2010).Lan, K. W., Wu, Y. L., Chen, L. C., Naimullah, M. & Lin, T. H. Effects of climate change in marine ecosystems based on the spatiotemporal age structure of top predators: A case study of bigeye tuna in the Pacific Ocean. Front. Mar. Sci. 8, 352 (2021).Article 

    Google Scholar 
    Li, S. et al. The Pacific Decadal Oscillation less predictable under greenhouse warming. Nat. Clim. Chang. 10, 30–34 (2020).ADS 
    CAS 
    Article 

    Google Scholar 
    Debertin, A. J., Irvine, J. R., Holt, C. A., Oka, G. & Trudel, M. Marine growth patterns of southern British Columbia chum salmon explained by interactions between density-dependent competition and changing climate. Can. J. Fish. Aquat. Sci. 74(7), 1077–1087 (2017).Article 

    Google Scholar 
    Di Lorenzo, E. et al. North Pacific Gyre Oscillation links ocean climate and ecosystem change. Geophys. Res. Lett. https://doi.org/10.1029/2007GL032838 (2008).Article 

    Google Scholar 
    Oceanic Fisheries Programme Pacific Community. Western and central Pacific fisheries commission tuna fishery yearbook (2020).IOTC. Report of the Twelfth Session of the Scientific Committee of the Indian Ocean Tuna Commsion. Victoria, Seychelles, 190 (2009).Pecoraro, C. et al. Putting all the pieces together: Integrating current knowledge of the biology, ecology, fisheries status, stock structure and management of yellowfin tuna (Thunnus albacares). Rev. Fish. Biol. Fish. 27(4), 811–841 (2017).Article 

    Google Scholar 
    Lee, Y. C., Nishida, T. & Mohri, M. Separation of the Taiwanese regular and deep tuna longliners in the Indian Ocean using bigeye tuna catch ratios. Fish. Sci. 71(6), 1256–1263 (2005).CAS 
    Article 

    Google Scholar 
    Marsac, F. Outlook of ocean climate variability in the west tropical Indian Ocean, 1997–2008. Working document for IOTC Indian Ocean Tuna Commission (2008).Lehodey, P., Chai, F. & Hampton, J. Modelling climate-related variability of tuna populations from a coupled ocean–biogeochemical-populations dynamics model. Fish Oceanogr. 12(4–5), 483–494 (2003).Article 

    Google Scholar 
    Torres-Faurrieta, L. K., Dreyfus-León, M. J. & Rivas, D. Recruitment forecasting of yellowfin tuna in the eastern Pacific Ocean with artificial neuronal networks. Ecol. Inform. 36, 106–113 (2016).Article 

    Google Scholar 
    Planque, B. et al. How does fishing alter marine populations and ecosystems sensitivity to climate?. J. Mar. Syst. 79(3–4), 403–417 (2010).Article 

    Google Scholar 
    Perry, R. I. et al. Sensitivity of marine systems to climate and fishing: Concepts, issues and management responses. J. Mar. Syst. 79(3–4), 427–435 (2010).Article 

    Google Scholar 
    Sen Gupta, A. & McNeil, B. Variability and change in the ocean. In The Future of the World’s Climate 141–165 (2012).Welch, H., Pressey, R. L. & Reside, A. E. Using temporally explicit habitat suitability models to assess threats to mobile species and evaluate the effectiveness of marine protected areas. J. Nat. Conserv. 41, 106–115 (2018).Article 

    Google Scholar 
    Shin, A., Yoon, S. C., Lee, S. I., Park, H. W. & Kim, S. The relationship between fishing characteristics of Pacific bluefin tuna (Thunnus orientalis) and ocean conditions around Jeju Island. Fish. Quat. Sci. 21, 1–12 (2018).
    Google Scholar 
    Monllor-Hurtado, A., Pennino, M. G. & Sanchez-Lizaso, J. L. Shift in tuna catches due to ocean warming. PLoS ONE 12, e0178196 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Arrizabalaga, H. et al. Global habitat preferences of commercially valuable tuna. Deep Sea Res. Part II Top. Stud. Oceanogr. 113, 102–112 (2015).ADS 
    Article 

    Google Scholar 
    Yen, K. W. et al. Using remote-sensing data to detect habitat suitability for yellowfin tuna in the Western and Central Pacific Ocean. Int. J. Remote Sens. 33(23), 7507–7522 (2012).Article 

    Google Scholar 
    Liu, Q. et al. Seasonal and intraseasonal thermocline variability in the central South China Sea. Geophys. Res. Lett. 28(23), 4467–4470 (2001).ADS 
    Article 

    Google Scholar 
    Schaefer, K. M., Fuller, D. W. & Block, B. A. Movements, behavior, and habitat utilization of yellowfin tuna (Thunnus albacares) in the northeastern Pacific Ocean, ascertained through archival tag data. Mar. Biol. 152, 503–525 (2007).Article 

    Google Scholar 
    Song, L. M. et al. Environmental preferences of longlining for yellowfin tuna (Thunnus albacares) in the tropical high seas of the Indian Ocean. Fish Oceanogr. 17, 239–253 (2008).Article 

    Google Scholar 
    Bismuto, E. et al. Molecular dynamics simulation of the acidic compact state of apomyoglobin from yellowfin tuna. Proteins 74, 273–290 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Galli, G. L. J., Shiels, H. A. & Brill, R. W. Temperature sensitivity of cardiac function in pelagic fishes with different vertical mobilities: yellowfin tuna (Thunnus albacares), bigeye tuna (Thunnus obesus), mahimahi (Coryphaena hippurus), and swordfish (Xiphias gladius). Physiol. Biochem. Zool. 82, 280–290 (2009).PubMed 
    Article 

    Google Scholar 
    Weng, K. C. et al. Habitat and behaviour of yellowfin tuna Thunnus albacares in the Gulf of Mexico determined using pop-up satellite archival tags. J. Fish Biol. 74, 1434–1449 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tseng, C. T. et al. Spatio-temporal distributions of tuna species and potential habitats in the Western and Central Pacific Ocean derived from multi-satellite data. Int. J. Remote Sens. 31, 4543–4558 (2010).Article 

    Google Scholar 
    Báez, J. C., Czerwinski, I. A. & Ramos, M. L. Climatic oscillations effect on the yellowfin tuna (Thunnus albacares) Spanish captures in the Indian Ocean. Fish Oceanogr. 29(6), 572–583 (2020).Article 

    Google Scholar 
    Mantua, N. J., Hare, S. R., Zhang, Y., Wallace, J. M. & Francis, R. C. A Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Am. Meteorol. Soc. 78, 1069–1080 (1997).ADS 
    Article 

    Google Scholar 
    Messié, M. & Chavez, F. Global modes of sea surface temperature variability in relation to regional climate indices. J. Clim. 24, 4314–4331 (2011).ADS 
    Article 

    Google Scholar 
    Michael, P. E., Tuck, G. N., Strutton, P. & Hobday, A. Environmental associations with broad-scale Japanese and Taiwanese pelagic longline effort in the southern Indian and Atlantic Oceans. Fish. Oceanogr. 24(5), 478–493 (2015).Article 

    Google Scholar 
    Chavez, F. P., Ryan, J., Lluch-Cota, S. E. & Ñiquen, M. From anchovies to sardines and back: Multidecadal change in the Pacific Ocean. Science 299, 217–221 (2003).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Chiba, S. et al. Temperature and zooplankton size structure: climate control and basin-scale comparison in the North Pacific. Ecol. Evol. 5(4), 968–978 (2015).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Olson, R. J. et al. Decadal diet shift in yellowfin tuna (Thunnus albacares) suggests broad-scale food web changes in the eastern tropical Pacific Ocean. Mar. Ecol.-Prog. Ser. 497, 157–178 (2014).ADS 
    Article 

    Google Scholar 
    Deepa, J. S. et al. The tropical Indian Ocean decadal sea level response to the Pacific decadal oscillation forcing. Clim. Dyn. 52, 5045–5058 (2019).Article 

    Google Scholar 
    Vibhute, A. et al. Decadal variability of tropical Indian Ocean Sea surface temperature and its impact on the Indian summer monsoon. Theor. Appl. Climatol. 141, 551–566 (2020).ADS 
    Article 

    Google Scholar 
    Ummenhofer, C. C., Biastoch, A. & Böning, C. W. Multidecadal Indian Ocean variability linked to the Pacific and implications for preconditioning Indian Ocean dipole events. J. Clim. 30, 1739–1751 (2017).ADS 
    Article 

    Google Scholar 
    Latif, M. The ocean’s role in modeling and predicting decadal climate variations. In International Geophysics 645–665 (Academic Press, 2013).Sun, C. et al. Western tropical Pacific multidecadal variability forced by the Atlantic multidecadal oscillation. Nat. Commun. 8, 1–10 (2017).Article 
    CAS 

    Google Scholar 
    Xie, T., Li, J., Chen, K., Zhang, Y. & Sun, C. Origin of Indian Ocean multidecadal climate variability: Role of the North Atlantic Oscillation. Clim. Dyn. 56, 3277–3294 (2021).Article 

    Google Scholar 
    Myers, R. A. & Worm, B. Rapid worldwide depletion of predatory fish communities. Nature 423, 280–283 (2003).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Ciannelli, L. et al. Climate forcing, food web structure and community dynamics in pelagic marine ecosystems. In Aquatic Food Webs: An Ecosystem Approach 143–169 (Oxford University Press, Oxford, 2005).Enfield, D. B., Mestas-Nuñez, A. M. & Trimble, P. J. The Atlantic multidecadal oscillation and its relation to rainfall and river flows in the continental US. Geophys. Res. Lett. 28, 2077–2080 (2001).ADS 
    Article 

    Google Scholar 
    Zuo, H., Balmaseda, M., Tietsche, S., Mogensen, K. & Mayer, M. The ECMWF operational ensemble reanalysis-analysis system for ocean and sea-ice: A description of the system and assessment. Ocean Sci. 15(3), 779–808 (2019).ADS 
    Article 

    Google Scholar 
    Harley, S. J., Myers, R. A. & Dunn, A. Is catch-per-unit-effort proportional to abundance?. Can J. Fish. Aquat. Sci. 58, 1760–1772 (2001).Article 

    Google Scholar 
    Guyomard, D., Desruisseaux, M., Poisson, F., Taquet, M., Petit, M. GAM analysis of operational and environmental factors affecting swordfish (Xiphias gladius) catch and CPUE of the Reunion Island longline fishery, in the South Western Indian Ocean. IOTC-2004-WPB-08, 38 (2004).Su, N. J., Sun, C. L., Punt, A. E., Yeh, S. Z. & DiNardo, G. Modelling the impacts of environmental variation on the distribution of blue marlin, Makaira nigricans, in the Pacific Ocean. ICES J. Mar. Sci. 68, 1072–1080 (2011).Article 

    Google Scholar 
    Bonett, D. G. & Wright, T. A. Sample size requirements for estimating Pearson, Kendall and Spearman correlations. Psychometrika 65(1), 23–28 (2000).MATH 
    Article 

    Google Scholar 
    Weaver, B. & Koopman, R. An SPSS macro to compute confidence intervals for Pearson’s correlation. Quant. Methods Psychol. 10(1), 29–39 (2014).Article 

    Google Scholar 
    Naimullah, M. et al. Effect of the El Niño-Southern Oscillation (ENSO) cycle on the catches and habitat patterns of three swimming crabs in the Taiwan Strait. Front. Mar. Sci. https://doi.org/10.3389/fmars.2021.763543 (2021).Article 

    Google Scholar 
    Chen, X. J., Li, G., Feng, B. & Tian, S. Q. Habitat suitability index of Chub mackerel (Scomber japonicus) from July to September in the East China Sea. J. Oceanogr. 65, 93–102 (2009).Article 

    Google Scholar 
    Urich, D. L. & Graham, J. P. Applying habitat evaluation procedures (HEP) to wildlife area planning in Missouri. Wildl. Soc. Bull. 11(3), 215–222 (1983).
    Google Scholar 
    Chen, X. J., Tian, S. Q., Chen, Y. & Liu, B. L. A modeling approach to identify optimal habitat and suitable fishing grounds for neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean. Fish. Bull. 108, 1–14 (2010).
    Google Scholar 
    Tian, S. Q., Chen, X. J., Chen, Y., Xu, L. X. & Dai, X. J. Evaluating habitat suitability indices derived from CPUE and fishing effort data for Ommatrephes bratramii in the northwestern Pacific Ocean. Fish Res. 95, 181–188 (2009).Article 

    Google Scholar 
    Rouyer, T., Sadykov, A., Ohlberger, J. & Stenseth, N. C. Does increasing mortality change the response of fish populations to environmental fluctuations?. Ecol. Lett. 15, 658–665 (2012).PubMed 
    Article 

    Google Scholar 
    Grinsted, A., Moore, J. C. & Jevrejeva, S. Application of the cross wavelet transform and wavelet coherence to geophysical time series. Nonlinear Process Geophys. 11, 561–566 (2004).ADS 
    Article 

    Google Scholar 
    Torrence, C. & Compo, G. P. A practical guide to wavelet analysis. Bull. Amer. Meteorol. Soc. 79, 61–78 (1998).ADS 
    Article 

    Google Scholar  More

  • in

    Empirical support for sequential imprinting during downstream migration in Atlantic salmon (Salmo salar) smolts

    Lucas, M. & Baras, E. Migration of Freshwater Fishes (Wiley, 2008).
    Google Scholar 
    Milner-Gulland, E. J., Fryxell, J. M. & Sinclair, A. R. Animal Migration: A Synthesis (Oxford University Press, 2011).Book 

    Google Scholar 
    Hendry, A. P. et al. The evolution of philopatry and dispersal. Evolution Illuminated. Salmon and Their Relatives, 52–91 (2004).Greenwood, P. J. Mating systems, philopatry and dispersal in birds and mammals. Anim. Behav. 28, 1140–1162 (1980).Article 

    Google Scholar 
    Klemetsen, A. et al. Atlantic salmon Salmo salar L., brown trout Salmo trutta L. and Arctic charr Salvelinus alpinus (L): A review of aspects of their life histories. Ecol. Freshwater Fish 12, 1–59. https://doi.org/10.1034/j.1600-0633.2003.00010.x (2003).Article 

    Google Scholar 
    VÄHÄ, J. P., Erkinaro, J., Niemelä, E. & Primmer, C. R. Life-history and habitat features influence the within-river genetic structure of Atlantic salmon. Mol. Ecol. 16, 2638–2654 (2007).Article 

    Google Scholar 
    Hansen, L. P., Jonsson, N. & Jonsson, B. Oceanic migration in homing Atlantic salmon. Anim. Behav. 45, 927–941 (1993).Article 

    Google Scholar 
    Keefer, M. L. & Caudill, C. C. Homing and straying by anadromous salmonids: A review of mechanisms and rates. Rev. Fish Biol. Fish. 24, 333–368 (2014).Article 

    Google Scholar 
    Neave, F. Ocean migrations of Pacific salmon. J. Fish. Board Canada 21, 1227–1244 (1964).Article 

    Google Scholar 
    Lohmann, K. J. & Lohmann, C. M. There and back again: Natal homing by magnetic navigation in sea turtles and salmon. J. Exp. Biol. 222, 184077 (2019).Article 

    Google Scholar 
    Scholz, A. T., Horrall, R. M., Cooper, J. C. & Hasler, A. D. Imprinting to chemical cues: The basis for home stream selection in salmon. Science 192, 1247–1249 (1976).ADS 
    CAS 
    Article 

    Google Scholar 
    Hasler, A. D. & Wisby, W. J. Discrimination of stream odors by fishes and its relation to parent stream behavior. Am. Nat. 85, 223–238 (1951).CAS 
    Article 

    Google Scholar 
    Harden Jones, F. R. Fish Migration. (Edward Arnold, 1968).Donaldson, L. R. & Allen, G. H. Return of silver salmon, Oncorhynchus kisutch (Walbaum) to point of release. Trans. Am. Fish. Soc. 87, 13–22 (1958).Article 

    Google Scholar 
    Quinn, T. P. A review of homing and straying of wild and hatchery-produced salmon. Fish. Res. 18, 29–44 (1993).Article 

    Google Scholar 
    Hansen, L. P. & Jonsson, B. Homing of Atlantic salmon: Effects of juvenile learning on transplanted post-spawners. Animal Behav. 47, 220 (1994).Article 

    Google Scholar 
    Nevitt, G. A., Dittman, A. H., Quinn, T. P. & Moody, W. J. Evidence for a peripheral olfactory memory in imprinted salmon. Proc. Natl. Acad. Sci. 91, 4288–4292. https://doi.org/10.1073/pnas.91.10.4288 (1994).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dittman, A. H., Quinn, T. P. & Nevitt, G. A. Timing of imprinting to natural and artificial odors by coho salmon (Oncorhynchus kisutch). Can. J. Fish. Aquat. Sci. 53, 434–442 (1996).Article 

    Google Scholar 
    Morin, P.-P., Dodson, J. J. & Doré, F. Y. Cardiac responses to a natural odorant as evidence of a sensitive period for Olfactory imprinting in young Atlantic Salmon, Salmo salar. Can. J. Fish. Aquat. Sci. 46, 122–130. https://doi.org/10.1139/f89-016 (1989).Article 

    Google Scholar 
    Gunnerød, T., Hvidsten, N. & Heggberget, T. Open sea releases of Atlantic salmon smolts, Salmo salar, in central Norway, 1973–83. Can. J. Fish. Aquat. Sci. 45, 1340–1345 (1988).Article 

    Google Scholar 
    Heggberget, T. G., Hvidsten, N. A., Gunnerød, T. B. & Møkkelgjerd, P. I. Distribution of adult recaptures from hatchery-reared Atlantic salmon (Salmo salar) smolts released in and off-shore of the River Surna, western Norway. Aquaculture 98, 89–96 (1991).Article 

    Google Scholar 
    Solazzi, M. F., Nickelson, T. E. & Johnson, S. L. Survival, contribution, and return of hatchery Coho Salmon (Oncorhynchus kisutch) released into freshwater, Estuarine, and Marine environments. Can. J. Fish. Aquat. Sci. 48, 248–253. https://doi.org/10.1139/f91-034 (1991).Article 

    Google Scholar 
    Sturrock, A. M. et al. Eight decades of hatchery salmon releases in the California Central Valley: Factors influencing straying and resilience. Fisheries 44, 433–444 (2019).Article 

    Google Scholar 
    Chapman, D. et al. Homing in sockeye and Chinook salmon transported around part of their smolt migration route in the Columbia River. North Am. J. Fish. Manag. 17, 101–113 (1997).Article 

    Google Scholar 
    Bond, M. H. et al. Combined effects of barge transportation, river environment, and rearing location on straying and migration of adult Snake River fall-run Chinook Salmon. Trans. Am. Fish. Soc. 146, 60–73. https://doi.org/10.1080/00028487.2016.1235614 (2017).Article 

    Google Scholar 
    Hesthagen, T., Larsen, B. M. & Fiske, P. Liming restores Atlantic salmon (Salmo salar) populations in acidified Norwegian rivers. Can. J. Fish. Aquat. Sci. 68, 224–231. https://doi.org/10.1139/f10-133 (2011).Article 

    Google Scholar 
    Haraldstad, T., Höglund, E., Kroglund, F., Haugen, T. O. & Forseth, T. Common mechanisms for guidance efficiency of descending A tlantic salmon smolts in small and large hydroelectric power plants. River Res. Appl. https://doi.org/10.1002/rra.3360 (2018).Article 

    Google Scholar 
    Thorstad, E. B., Økland, F., Kroglund, F. & Jepsen, N. Upstream migration of Atlantic salmon at a power station on the River Nidelva Southern Norway. Fish. Manag. Ecol. 10, 139–146. https://doi.org/10.1046/j.1365-2400.2003.00335.x (2003).Article 

    Google Scholar 
    Fjeldstad, H.-P., Barlaup, B. T., Stickler, M., Gabrielsen, S.-E. & Alfredsen, K. Removal of weirs and the influence on physical habitat for salmonids in a Norwegian river. River Res. Appl. 28, 753–763. https://doi.org/10.1002/rra.1529 (2012).Article 

    Google Scholar 
    Wolf, P. a trap for the capture of fish and other organisms moving downstream. Trans. Am. Fish. Soc. 80, 41–45. https://doi.org/10.1577/1548-8659(1950)80[41:ATFTCO]2.0.CO;2 (1951).Article 

    Google Scholar 
    Johansen, K. When the Solution Becomes a Problem: A Study of Smolt Migration in the Regulated River of Nidelva in Agder county, Norway. MSc thesis, University of Agder, (2021).R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2016).Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723. https://doi.org/10.1109/TAC.1974.1100705 (1974).ADS 
    MathSciNet 
    Article 
    MATH 

    Google Scholar 
    Anderson, D. R. Model-Based Interference in the Life Sciences: A Primer on Evidence (Springer, 2008).Book 

    Google Scholar 
    Jonsson, B., Jonsson, N. & Hansen, L. P. Does juvenile experience affect migration and spawning of adult Atlantic salmon?. Behav. Ecol. Sociobiol. 26, 225–230 (1990).Article 

    Google Scholar 
    Thorstad, E., Heggberget, T. & Økland, F. Migratory behaviour of adult wild and escaped farmed Atlantic salmon, Salmo salar L., before, during and after spawning in a Norwegian river. Aquac. Res. 29, 419–428 (1998).Article 

    Google Scholar 
    Aarestrup, K. et al. Prespawning migratory behaviour and spawning success of sea-ranched Atlantic salmon, Salmo salar L., in the River Gudenaa, Denmark. Fish. Manag. Ecol. 7, 387–400 (2000).Article 

    Google Scholar 
    Thorstad, E. B. et al. Factors affecting the within-river spawning migration of Atlantic salmon, with emphasis on human impacts. Rev. Fish Biol. Fish. 18, 345–371 (2008).Article 

    Google Scholar 
    Silva, A. T. et al. The future of fish passage science, engineering, and practice. Fish Fish. 19, 340 (2017).Article 

    Google Scholar 
    Čada, G. F. The development of advanced hydroelectric turbines to improve fish passage survival. Fisheries 26, 14–23 (2001).Article 

    Google Scholar 
    Quaranta, E. et al. Hydropower case study collection: Innovative Low head and ecologically improved turbines, hydropower in existing infrastructures, hydropeaking reduction: Digitalization and governing systems. Sustainability 12, 8873 (2020).Article 

    Google Scholar 
    Lusardi, R. A. & Moyle, P. B. Two-way trap and haul as a conservation strategy for anadromous salmonids. Fisheries 42, 478–487 (2017).Article 

    Google Scholar 
    Keefer, M. L., Caudill, C. C., Peery, C. A. & Lee, S. R. Transporting juvenile salmon around dams impairs adult migration. Ecol. Appl. 18, 1888–1900. https://doi.org/10.1890/07-0710.1 (2008).Article 
    PubMed 

    Google Scholar 
    Haraldstad, T., Haugen, T. O., Olsen, E. M., Forseth, T. & Höglund, E. Hydropower-induced selection of behavioural traits in Atlantic salmon (Salmo salar). Sci. Rep. 11, 1–9 (2021).Article 

    Google Scholar 
    Waples, R. S. & Hendry, A. P. Special issue: Evolutionary perspectives on salmonid conservation and management. Evolut. Appl. 1, 183–188. https://doi.org/10.1111/j.1752-4571.2008.00035.x (2008).Article 

    Google Scholar 
    Jonsson, B., Jonsson, N. & Hansen, L. P. Atlantic salmon straying from the River Imsa. J. Fish Biol. 62, 641–657. https://doi.org/10.1046/j.0022-1112.2003.00053.x (2003).Article 

    Google Scholar 
    Brown, C. Fish intelligence, sentience and ethics. Anim. Cogn. 18, 1–17 (2015).Article 

    Google Scholar  More

  • in

    Thermal adaptation best explains Bergmann’s and Allen’s Rules across ecologically diverse shorebirds

    Delhey, K. A review of Gloger’s rule, an ecogeographical rule of colour: definitions, interpretations and evidence. Biol. Rev. 94, 1294–1316 (2019).PubMed 

    Google Scholar 
    Tian, L. & Benton, M. J. Predicting biotic responses to future climate warming with classic ecogeographic rules. Curr. Biol. 30, R744–R749 (2020).CAS 
    PubMed 

    Google Scholar 
    Ryding, S., Klaassen, M., Tattersall, G. J., Gardner, J. L. & Symonds, M. R. E. Shape-shifting: changing animal morphologies as a response to climatic warming. Trends Ecol. Evol. 36, 1036–1048 (2021).Salewski, V. & Watt, C. Bergmann’s rule: a biophysiological rule examined in birds. Oikos 126, 161–172 (2017).
    Google Scholar 
    Allen, J. A. The influence of physical conditions in the genesis of species. Radic. Rev. 1, 108–140 (1877).
    Google Scholar 
    Ashton, K. G., Tracy, M. C. & De Queiroz, A. Is Bergmann’s rule valid for mammals? Am. Nat. 156, 390–415 (2000).PubMed 

    Google Scholar 
    Ashton, K. G. Patterns of within-species body size variation of birds: strong evidence for Bergmann’s rule. Glob. Ecol. Biogeogr. 11, 505–523 (2002).
    Google Scholar 
    Nudds, R. L. & Oswald, S. A. An interspecific test of Allen’s rule: evolutionary implications for endothermic species. Evolution (N. Y) 61, 2839–2848 (2007).CAS 

    Google Scholar 
    Symonds, M. R. E. & Tattersall, G. J. Geographical variation in bill size across bird species provides evidence for Allen’s rule. Am. Nat. 176, 188–197 (2010).PubMed 

    Google Scholar 
    Cardilini, A. P. A., Buchanan, K. L., Sherman, C. D. H., Cassey, P. & Symonds, M. R. E. Tests of ecogeographical relationships in a non-native species: what rules avian morphology? Oecologia 181, 783–793 (2016).ADS 
    PubMed 

    Google Scholar 
    Alhajeri, B. H., Fourcade, Y., Upham, N. S. & Alhaddad, H. A global test of Allen’s rule in rodents. Glob. Ecol. Biogeogr. 29, 2248–2260 (2020).
    Google Scholar 
    McNab, B. K. On the ecological significance of Bergmann’s rule. Ecology 52, 845–854 (1971).
    Google Scholar 
    Meiri, S., Dayan, T. & Simberloff, D. Carnivores, biases and Bergmann’s rule. Biol. J. Linn. Soc. 81, 579–588 (2004).
    Google Scholar 
    Gohli, J. & Voje, K. L. An interspecific assessment of Bergmann’s rule in 22 mammalian families. BMC Evol. Biol. 16, 1–12 (2016).
    Google Scholar 
    Freeman, B. G. Little evidence for Bergmann’s rule body size clines in passerines along tropical elevational gradients. J. Biogeogr. 44, 502–510 (2017).
    Google Scholar 
    Riemer, K., Guralnick, R. P. & White, E. No general relationship between mass and temperature in endothermic species. Elife 7, e27166 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Blackburn, T. M., Gaston, K. J. & Loder, N. Geographic gradients in body size: a clarification of Bergmann’s rule. Divers. Distrib. 5, 165–174 (1999).
    Google Scholar 
    Watt, C., Mitchell, S. & Salewski, V. Bergmann’s rule; a concept cluster? Oikos 119, 89–100 (2010).
    Google Scholar 
    James, F. C. Geographic size variation in birds and its relationship to climate. Ecology 51, 365–390 (1970).
    Google Scholar 
    Cartar, R. V. & Morrison, R. I. G. Metabolic correlates of leg length in breeding arctic shorebirds: the cost of getting high. J. Biogeogr. 32, 377–382 (2005).
    Google Scholar 
    Friedman, N. R., Harmáčková, L., Economo, E. P. & Remeš, V. Smaller beaks for colder winters: thermoregulation drives beak size evolution in Australasian songbirds. Evolution (N. Y). 71, 2120–2129 (2017).Fan, L., Cai, T., Xiong, Y., Song, G. & Lei, F. Bergmann’s rule and Allen’s rule in two passerine birds in China. Avian. Res. 10, 1–11 (2019).
    Google Scholar 
    Romano, A., Séchaud, R. & Roulin, A. Geographical variation in bill size provides evidence for Allen’s rule in a cosmopolitan raptor. Glob. Ecol. Biogeogr. 29, 65–75 (2020).
    Google Scholar 
    Romano, A., Séchaud, R. & Roulin, A. Generalized evidence for Bergmann’s rule: body size variation in a cosmopolitan owl genus. J. Biogeogr. 48, 51–63 (2021).
    Google Scholar 
    Gardner, J. L. et al. Spatial variation in avian bill size is associated with humidity in summer among Australian passerines. Clim. Chang. Responses 3, 1–11 (2016).
    Google Scholar 
    Greenberg, R. & Danner, R. M. The influence of the california marine layer on bill size in a generalist songbird. Evolution (N. Y) 66, 3825–3835 (2012).
    Google Scholar 
    Greenberg, R., Danner, R., Olsen, B. & Luther, D. High summer temperature explains bill size variation in salt marsh sparrows. Ecography (Cop.) 35, 146–152 (2012).
    Google Scholar 
    Klir, J. J. & Heath, J. E. An infrared thermographic study of surface temperature in relation to external thermal stress in three species of foxes: the red fox (Vulpes vulpes), Arctic fox, and kit fox (Vulpes macrotis). Physiol. Zool. 65, 1011–1021 (1992).
    Google Scholar 
    Ballentine, B. & Greenberg, R. Common garden experiment reveals genetic control of phenotypic divergence between swamp sparrow subspecies that lack divergence in neutral genotypes. PLoS One 5, 1–6 (2010).
    Google Scholar 
    Nord, A. & Giroud, S. Lifelong effects of thermal challenges during development in birds and mammals. Front. Physiol. 11, 1–9 (2020).
    Google Scholar 
    Riek, A. & Geiser, F. Developmental phenotypic plasticity in a marsupial. J. Exp. Biol. 215, 1552–1558 (2012).PubMed 

    Google Scholar 
    Cunningham, S. J., Martin, R. O., Hojem, C. L. & Hockey, P. A. R. Temperatures in excess of critical thresholds threaten nestling growth and survival in a rapidly-warming arid savanna: a study of common fiscals. PLoS One 8, e74613 (2013).Mariette, M. M. & Buchanan, K. L. Prenatal acoustic communication programs offspring for high posthatching temperatures in a songbird. Science 353, 812–814 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Nord, A. & Nilsson, J. Å. Incubation temperature affects growth and energy metabolism in blue tit nestlings. Am. Nat. 178, 639–651 (2011).PubMed 

    Google Scholar 
    Serrat, M. A. Allen’s rule revisited: temperature influences bone elongation during a critical period of postnatal development. Anat. Rec. 296, 1534–1545 (2013).
    Google Scholar 
    Larson, E. R. et al. Nest microclimate predicts bill growth in the Adelaide rosella (Aves: Psittaculidae). Biol. J. Linn. Soc. 124, 339–349 (2018).
    Google Scholar 
    Burness, G., Huard, J. R., Malcolm, E. & Tattersall, G. J. Post-hatch heat warms adult beaks: irreversible physiological plasticity in Japanese quail. Proc. R. Soc. B Biol. Sci. 280, 20131436 (2013).Husby, A., Hille, S. M. & Visser, M. E. Testing mechanisms of bergmann’s rule: phenotypic decline but no genetic change in body size in three passerine bird populations. Am. Nat. 178, 202–213 (2011).PubMed 

    Google Scholar 
    Cresswell, W., Clark, J. A. & Macleod, R. How climate change might influence the starvation-predation risk trade-off response. Proc. R. Soc. B Biol. Sci. 276, 3553–3560 (2009).CAS 

    Google Scholar 
    McNamara, J. M., Higginson, A. D. & Verhulst, S. The influence of the starvation-predation trade-off on the relationship between ambient temperature and body size among endotherms. J. Biogeogr. 43, 809–819 (2016).PubMed 

    Google Scholar 
    Dickman, C. R. Body size, prey size, and community structure in insectivorous mammals. Ecology 69, 569–580 (1988).
    Google Scholar 
    Carbone, C., Mace, G. M., Roberts, S. C. & Macdonald, D. W. Energetic constraints on the diet of terrestrial carnivores. Nature 402, 286–288 (1999).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Cohen, J. E., Pimm, S. L., Yodzis, P., & Saldaña, J. Body sizes of animal predators and animal prey in food webs. J. Anim. Ecol. 62, 67–78 (1993).
    Google Scholar 
    McKinnon, L. et al. Lower predation risk for migratory birds at high latitudes. Science 327, 326–327 (2010).ADS 
    CAS 
    PubMed 

    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).Gosler, A. G., Greenwood, J. J. D. & Perrins, C. Predation risk and the cost of being fat. Nature 377, 621–623 (1995).ADS 
    CAS 

    Google Scholar 
    Anderson, A. M. et al. Consistent declines in wing lengths of Calidridine sandpipers suggest a rapid morphometric response to environmental change. PLoS One 14, 1–21 (2019).CAS 

    Google Scholar 
    Milá, B., Wayne, R. K. & Smith, T. B. Ecomorphology of migratory and sedentary populations of the yellow-rumped warbler (Dendroica Coronata). Condor 110, 335–344 (2008).
    Google Scholar 
    O’Hara, P. D., Fernández, G., Haase, B., de la Cueva, H. & Lank, D. B. Differential migration in western sandpipers with respect to body size and wing length. Condor 108, 225–232 (2006).
    Google Scholar 
    Ketterson, E. D. & Nolan, V. Geographic variation and its climatic correlates in the sex ratio of eastern-wintering dark-eyed juncos (Junco hyemalis hyemalis). Ecology 57, 679–693 (1976).
    Google Scholar 
    Nebel, S. Differential migration of shorebirds in the East Asian-Australasian Flyway. Emu 107, 14–18 (2007).
    Google Scholar 
    Elner, R. W. & Seaman, D. A. Calidrid conservation: unrequited needs. Wader Study Gr. Bull. 100, 30–34 (2003).
    Google Scholar 
    Greenberg, R. Dissimilar bill shapes in new world tropical versus temperate forest foliage-gleaning birds. Oecologia 49, 143–147 (1981).ADS 
    PubMed 

    Google Scholar 
    Nebel, S. Latitudinal clines in bill length and sex ratio in a migratory shorebird: a case of resource partitioning? Acta Oecologica 28, 33–38 (2005).ADS 

    Google Scholar 
    Mathot, K. J., Smith, B. D. & Elner, R. W. Latitudinal clines in food distribution correlate with differential migration in the Western Sandpiper. Ecology 88, 781–791 (2007).PubMed 

    Google Scholar 
    Duijns, S. et al. Sex-specific winter distribution in a sexually dimorphic shorebird is explained by resource partitioning. Ecol. Evol. 4, 4009–4018 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Wilson, J. R., Nebel, S. & Minton, C. D. T. Migration ecology and morphometrics of two Bar-tailed Godwit populations in Australia. Emu 107, 262–274 (2007).
    Google Scholar 
    Nebel, S., Rogers, K. G., Minton, C. D. T. & Rogers, D. I. Is geographical variation in the size of Australian shorebirds consistent with hypotheses on differential migration? Emu 113, 99–111 (2013).
    Google Scholar 
    Beltran, R. S., Burns, J. M. & Breed, G. A. Convergence of biannual moulting strategies across birds and mammals. Proc. R. Soc. B Biol. Sci. 285, 20180318 (2018).Tattersall, G. J., Arnaout, B. & Symonds, M. R. E. The evolution of the avian bill as a thermoregulatory organ. Biol. Rev. 92, 1630–1656 (2017).PubMed 

    Google Scholar 
    Battley, P. F., Rogers, D. I., Piersma, T. & Koolhaas, A. Behavioural evidence for heat-load problems in Great Knots in tropical Australia fuelling for long-distance flight. Emu 103, 97–103 (2003).
    Google Scholar 
    Rogers, D. I., Piersma, T. & Hassell, C. J. Roost availability may constrain shorebird distribution: Exploring the energetic costs of roosting and disturbance around a tropical bay. Biol. Conserv. 133, 225–235 (2006).
    Google Scholar 
    Danner, R. M. & Greenberg, R. A critical season approach to Allen’s rule: Bill size declines with winter temperature in a cold temperate environment. J. Biogeogr. 42, 114–120 (2015).
    Google Scholar 
    Buchholz, R. Thermoregulatory role of the unfeathered head and neck in male wild turkeys. Auk 113, 310–318 (1996).
    Google Scholar 
    Marchant, S. & Higgins, P. J. (eds.) Handbook of Australian, New Zealand and Antarctic Birds. Volume 2: Raptors to Lapwings (Oxford University Press, 1993).Higgins, P. J. & Davies, S. J. J. F. (eds.) Handbook of Australian, New Zealand and Antarctic Birds. Volume 3: Snipe to Pigeons (Oxford University Press, 1996).Andrew, S. C., Hurley, L. L., Mariette, M. M. & Griffith, S. C. Higher temperatures during development reduce body size in the zebra finch in the laboratory and in the wild. J. Evol. Biol. 30, 2156–2164 (2017).CAS 
    PubMed 

    Google Scholar 
    Morrick, Z. N. et al. Differential population trends align with migratory connectivity in an endangered shorebird. Conserv. Sci. Pract. 4, 1–13 (2022).
    Google Scholar 
    Hassell, C., Southey, I., Boyle, A. & Yang, H.-Y. Red knot Calidris canutus: subspecies and migration in the East Asian-Australasian flyway – where do all the red knot go? BirdingASIA 16, 89–93 (2011).
    Google Scholar 
    Battley, P. F. et al. Contrasting extreme long-distance migration patterns in bar-tailed godwits Limosa lapponica. J. Avian Biol. 43, 21–32 (2012).
    Google Scholar 
    Aharon-Rotman, Y., Buchanan, K. L., Clark, N. J., Klaassen, M. & Buttemer, W. A. Why fly the extra mile? Using stress biomarkers to assess wintering habitat quality in migratory shorebirds. Oecologia 182, 385–395 (2016).ADS 
    PubMed 

    Google Scholar 
    Aharon-Rotman, Y., Gosbell, K., Minton, C. & Klaassen, M. Why fly the extra mile? Latitudinal trend in migratory fuel deposition rate as driver of trans-equatorial long-distance migration. Ecol. Evol. 6, 6616–6624 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Hollands, D. & Minton, C. Waders: The Shorebirds of Australia (Bloomings Books, 2012).Siepielski, A. M. et al. No evidence that warmer temperatures are associated with selection for smaller body sizes. Proc. R. Soc. B Biol. Sci. 286, 20191332 (2019).Ho, C. K., Pennings, S. C. & Carefoot, T. H. Is diet quality an overlooked mechanism for Bergmann’s rule? Am. Nat. 175, 269–276 (2010).PubMed 

    Google Scholar 
    Piersma, T. et al. Fuel storage rates in Red Knots worldwide: facing the severest ecological constraint in tropical intertidal environments? In Birds of Two Worlds: Ecology and Evolution of Migration (eds Greenburg, R. & Marra, P. P.) (Smithsonian Institution Press, 2005).Hedenström, A. & Rosén, M. Predator versus prey: on aerial hunting and escape strategies in birds. Behav. Ecol. 12, 150–156 (2001).
    Google Scholar 
    Van Den Hout, P. J., Mathot, K. J., Maas, L. R. M. & Piersma, T. Predator escape tactics in birds: linking ecology and aerodynamics. Behav. Ecol. 21, 16–25 (2010).
    Google Scholar 
    Schemske, D. W., Mittelbach, G. G., Cornell, H. V., Sobel, J. M. & Roy, K. Is there a latitudinal gradient in the importance of biotic interactions? Annu. Rev. Ecol. Evol. Syst. 40, 245–269 (2009).
    Google Scholar 
    Cain, K. E. et al. Conspicuous plumage does not increase predation risk: a continent-wide test using model songbirds. Am. Nat. 193, 359–372 (2019).PubMed 

    Google Scholar 
    Cohen, J. E., Pimm, S. L., Yodzis, P. & Saldana, J. Body sizes of animal predators and animal prey in food webs. J. Anim. Ecol. 62, 67–78 (1993).
    Google Scholar 
    Gotmark, F. & Post, P. Prey selection by sparrowhawks, Accipiter nisus: relative predation risk for breeding passerine birds in relation to their size, ecology and behaviour. Philos. Trans. R. Soc. B Biol. Sci. 351, 1559–1577 (1996).ADS 

    Google Scholar 
    McQueen, A. et al. Evolutionary drivers of seasonal plumage colours: colour change by moult correlates with sexual selection, predation risk and seasonality across passerines. Ecol. Lett. 22, 1838–1849 (2019).PubMed 

    Google Scholar 
    Martínez, A. E. & Zenil, R. T. Foraging guild influences dependence on heterospecific alarm calls in Amazonian bird flocks. Behav. Ecol. 23, 544–550 (2012).
    Google Scholar 
    Gauthreaux, S. A. The ecological significance of behavioral dominance. In Social Behavior. Perspectives in Ethology, vol 3 (eds Bateson, P. P. G. & Klopfer, P. H.) (Springer, 1978).Friedman, N. R. et al. Evolution of a multifunctional trait: Shared effects of foraging ecology and thermoregulation on beak morphology, with consequences for song evolution. Proc. R. Soc. B Biol. Sci. 286, 20192474 (2019).Campbell-Tennant, D. J. E., Gardner, J. L., Kearney, M. R. & Symonds, M. R. E. Climate-related spatial and temporal variation in bill morphology over the past century in Australian parrots. J. Biogeogr. 42, 1163–1175 (2015).
    Google Scholar 
    Sullivan, T. N., Meyers, M. A. & Arzt, E. Scaling of bird wings and feathers for efficient flight. Sci. Adv. 5, 1–9 (2019).
    Google Scholar 
    Gosler, A. G., Greenwood, J. J. D., Baker, J. K. & Davidson, N. C. The field determination of body size and condition in passerines: a report to the British Ringing Committee. Bird. Study 45, 92–103 (1998).
    Google Scholar 
    Tattersall, G. J., Chaves, J. A. & Danner, R. M. Thermoregulatory windows in Darwin’s finches. Funct. Ecol. 32, 358–368 (2018).
    Google Scholar 
    Weeks, B. C. et al. Shared morphological consequences of global warming in North American migratory birds. Ecol. Lett. 23, 316–325 (2020).PubMed 

    Google Scholar 
    Minton, C. The history and achievements of the Victorian Wader Study Group. Stilt 50, 285–294 (2006).
    Google Scholar 
    Minton, C. The history of wader studies in north-west Australia. Stilt 50, 224–234 (2006).
    Google Scholar 
    Lowe, K. W. The Australian Bird Bander’s Manual (Australian Bird and Bat Banding Scemes, Australian National Parks and Wildlife Services, 1989).Aarif, K. M. Some aspects of feeding ecology of the lesser sand plover Charadrius mongolus in three different zones in the Kadalundy Estuary, Kerala, South India. Podoces 4, 100–1007 (2009).
    Google Scholar 
    Bates, D., Maechler, M. & Bolker, B. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Google Scholar 
    Rue, H. et al. Bayesian computing with INLA: a review. Annu. Rev. Stat. Its Appl. 4, 395–421 (2017).ADS 

    Google Scholar 
    Li, D., Dinnage, R., Nell, L. A., Helmus, M. R. & Ives, A. R. phyr: an r package for phylogenetic species-distribution modelling in ecological communities. Methods Ecol. Evol. 11, 1455–1463 (2020).
    Google Scholar 
    Simpson, D., Rue, H., Riebler, A., Martins, T. G. & Sørbye, S. H. Penalising model component complexity: a principled, practical approach to constructing priors. Stat. Sci. 32, 1–28 (2017).MathSciNet 
    MATH 

    Google Scholar 
    Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Schliep, K. Phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).CAS 
    PubMed 

    Google Scholar 
    McQueen, A et al. Data from: thermal adaptation best explains Bergmann’s and Allen’s rule across ecologically diverse shorebirds. Dryad Dataset. https://doi.org/10.5061/dryad.xsj3tx9j5.Tattersall, G. J., Andrade, D. V. & Abe, A. S. Heat exchange from the toucan bill reveals a controllable vascular thermal radiator. Science 325, 468–470 (2009).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Greenberg, R., Cadena, V., Danner, R. M. & Tattersall, G. Heat loss may explain bill size differences between birds occupying different habitats. PLoS One 7, 1–9 (2012).
    Google Scholar 
    Ryeland, J., Weston, M. A. & Symonds, M. R. E. Bill size mediates behavioural thermoregulation in birds. Funct. Ecol. 31, 885–893 (2017).
    Google Scholar 
    Pavlovic, G., Weston, M. A. & Symonds, M. R. E. Morphology and geography predict the use of heat conservation behaviours across birds. Funct. Ecol. 33, 286–296 (2019).
    Google Scholar  More

  • in

    Distribution and genetic diversity of Anisakis spp. in cetaceans from the Northeast Atlantic Ocean and the Mediterranean Sea

    Kuhn, T., Cunze, S., Kochmann, J. & Klimpel, S. Environmental variables and definitive host distribution: A habitat suitability modelling for endohelminth parasites in the marine realm. Sci. Rep. 6, 30246 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mattiucci, S. & Nascetti, G. Advances and trends in the molecular systematics of anisakid nematodes, with implications for their evolutionary ecology and host-parasite co-evolutionary processes. Adv. Parasitol. 66, 47–148 (2008).PubMed 
    Article 

    Google Scholar 
    Mattiucci, S., Cipriani, P., Levsen, A., Paoletti, M. & Nascetti, G. Molecular epidemiology of Anisakis and Anisakiasis: An ecological and evolutionary road map. Adv. Parasitol. 99, 93–263 (2018).PubMed 
    Article 

    Google Scholar 
    Colón-Llavina, M. M. et al. Additional records of metazoan parasites from Caribbean marine mammals, including genetically identified anisakid nematodes. Parasitol. Res. 105, 1239–1252 (2009).PubMed 
    Article 

    Google Scholar 
    Iñiguez, A. M., Santos, C. P. & Vicente, A. C. P. Genetic characterization of Anisakis typica and Anisakis physeteris from marine mammals and fish from the Atlantic Ocean off Brazil. Vet. Parasitol. 165, 350–356 (2009).PubMed 
    Article 

    Google Scholar 
    Gomes, T. L. et al. Anisakis spp. in toothed and baleen whales from Japanese waters with notes on their potential role as biological tags. Parasitol. Int. 80, 102228 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Irigoitia, M. et al. Genetic identification of Anisakis spp. (Nematoda: Anisakidae) from cetaceans of the Southwestern Atlantic Ocean: Ecological and zoogeographical implications. Parasit. Res. 120, 1–13 (2021).Article 

    Google Scholar 
    Ugland, K. I., Strømnes, E., Berland, B. & Aspholm, P. E. Growth, fecundity and sex ratio of adult whaleworm (Anisakis simplex; Nematoda, Ascaridoidea, Anisakidae) in three whale species from the North-East Atlantic. Parasitol. Res. 92, 484–489 (2004).PubMed 
    Article 

    Google Scholar 
    Berland, B. Musings on nematode parasites. Fisken og Havet 11, 1–26 (2006).
    Google Scholar 
    Roca-Geronès, X., Alcover, M. M., Godínez-González, C., Montoliu, I. & Fisa, R. Hybrid genotype of Anisakis simplex (s.s.) and A. pegreffii identified in third- and fourth-stage larvae from sympatric and allopatric Spanish marine waters. Animals 11, 2458 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Smith, J. Ulcers associated with larval Anisakis simplex B (Nematoda: Ascaridoidea) in the forestomach of harbour porpoises Phocoena phocoena (L.). Can. J. Zool. 67, 2270–2276 (1989).Article 

    Google Scholar 
    Abollo, E., Lopez, A., Gestal, C., Benavente, P. & Pascual, S. Macroparasites in cetaceans stranded on the northwestern Spanish Atlantic coast. Dis. Aquat. Org. 32, 227–231 (1998).CAS 
    Article 

    Google Scholar 
    Hrabar, J., Bočina, I., Gudan Kurilj, A., Đuras, M. & Mladineo, I. Gastric lesions in dolphins stranded along the Eastern Adriatic coast. Dis. Aquat. Organ. 125, 125–139 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Pons-Bordas, C. et al. Recent increase of ulcerative lesions caused by Anisakis spp. in cetaceans from the north-east Atlantic. J. Helminthol. 94, E127 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ryeng, K. A., Lakemeyer, J., Roller, M., Wohlsein, P. & Sieber, U. Pathological findings in bycaught harbour porpoises (Phocoena phocoena) from the coast of Northern Norway. Polar Biol. 45, 45–57 (2021).Article 

    Google Scholar 
    Mattiucci, S., Cipriani, P., Paoletti, M., Levsen, A. & Nascetti, G. Reviewing biodiversity and epidemiological aspects of anisakid nematodes from the North East Atlantic Ocean. J. Helminthol. 91, 422–439 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mattiucci, S. et al. Novel polymorphic microsatellite loci in Anisakis pegreffii and A. simplex (s.s.) (Nematoda: Anisakidae): Implications for species recognition and population genetic analysis. Parasitology 146, 1387–1403 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shamsi, S., Sprohnle-Barrera, C. & Hossen, M. D. S. Occurrence of Anisakis spp. (Nematoda: Anisakidae) in a pygmy sperm whale Kogia breviceps (Cetacea: Kogiidae) in Australian waters. Dis. Aquat. Organ. 134, 65–74 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cavallero, S., Nadler, S. A., Paggi, L., Barros, N. B. & D’Amelio, S. Molecular characterization and phylogeny of anisakid nematodes from cetaceans from southeastern Atlantic coasts of USA, Gulf of Mexico, and Caribbean Sea. Parasitol. Res. 108, 781–792 (2011).PubMed 
    Article 

    Google Scholar 
    Klimpel, S. & Palm, H. W. Anisakid nematode (Ascaridoidea) life cycles and distribution: increasing zoonotic potential in the time of climate change? In Progress in Parasitology, Parasitology Research Monographs Vol. 2 (ed. Mehlhorn, H.) 201–222 (Springer, 2011).
    Google Scholar 
    Li, L. et al. Molecular phylogeny and dating reveal a terrestrial origin in the early Carboniferous for Ascaridoid nematodes. Syst. Biol. 67, 888–900 (2018).PubMed 
    Article 

    Google Scholar 
    Shamsi, S. Recent advances in our knowledge of Australian anisakid nematodes. Int. J. Parasitol. Parasites Wildl. 3, 178–187 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mattiucci, S. et al. Genetic and morphological approaches distinguish the three sibling species of the Anisakis simplex species complex, with a species designation as Anisakis berlandi n. sp. for A. simplex sp. C (Nematoda: Anisakidae). J. Parasitol. 100, 199–214 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    D’Amelio, S. et al. Genetic markers in ribosomal DNA for the identification of members of the genus Anisakis (Nematoda: Ascaridoidea) defined by polymerase-chain-reaction-based restriction fragment length polymorphism. Int. J. Parasitol. 30, 223–226 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    Valentini, A. et al. Genetic relationships among Anisakis species (Nematoda: Anisakidae) inferred from mitochondrial cox2 sequences, and comparison with allozyme data. J. Parasitol. 92, 156–166 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mattiucci, S. et al. No more time to stay ‘single’ in the detection of Anisakis pegreffii, A. simplex (s.s.) and hybridization events between them: A multi-marker nuclear genotyping approach. Parasitology 143, 998–1011 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Palomba, M., Paoletti, M., Webb, S. C., Nascetti, G. & Mattiucci, S. A novel nuclear marker and development of an ARMS-PCR assay targeting the metallopeptidase 10 (nas 10) locus to identify the species of the Anisakis simplex (s. l.) complex (Nematoda, Anisakidae). Parasite 27, 39 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mladineo, I. et al. Anisakis simplex complex: Ecological significance of recombinant genotypes in an allopatric area of the Adriatic Sea inferred by genome-derived simple sequence repeats. Int. J. Parasitol. 47, 215–223 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bello, E., Paoletti, M., Webb, S. C., Nascetti, G. & Mattiucci, S. Cross-species utility of microsatellite loci for the genetic characterisation of Anisakis berlandi (Nematoda: Anisakidae). Parasite 27, 9 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Bello, E. et al. Investigating the genetic structure of the parasites Anisakis pegreffii and A. berlandi (Nematoda: Anisakidae) in a sympatric area of the southern Pacific Ocean waters using a multilocus genotyping approach: First evidence of their interspecific hybridization. Infect. Genet. Evol. 92, 104887 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    Klapper, R. et al. Anisakid nematodes in beaked redfish (Sebastes mentella) from three fishing grounds in the North Atlantic, with special notes on distribution in the fish musculature. Vet. Parasit. 207, 72–80 (2015).Article 

    Google Scholar 
    Bušelić, I. et al. Geographic and host size variations as indicators of Anisakis pegreffii infection in European pilchard (Sardina pilchardus) from the Mediterranean Sea: Food safety implications. Int. J. Food Microb. 266, 126–132 (2018).Article 
    CAS 

    Google Scholar 
    Cipriani, P. et al. Anisakis pegreffii (Nematoda: Anisakidae) in European anchovy Engraulis encrasicolus from the Mediterranean Sea: Fishing ground as a predictor of parasite distribution. Fish. Res. 202, 59–68 (2018).Article 

    Google Scholar 
    Cipriani, P. et al. The Mediterranean European hake, Merluccius merluccius: Detecting drivers influencing the Anisakis spp. larvae distribution. Fish. Res. 202, 79–89 (2018).Article 

    Google Scholar 
    Levsen, A. et al. A survey of zoonotic nematodes of commercial key fish species from major European fishing grounds—Introducing the FP7 PARASITE exposure assessment study. Fish. Res. 202, 4–21 (2018).Article 

    Google Scholar 
    Gibson, D. I. et al. A survey of the helminth parasites of cetaceans stranded on the coast of England and Wales during the period 1990–1994. J. Zool. 244, 563–574 (1998).Article 

    Google Scholar 
    Mattiucci, S. et al. Evidence for a new species of Anisakis Dujardin, 1845: Morphological description and genetic relationships between congeners (Nematoda: Anisakidae). Syst. Parasitol. 61, 157–171 (2005).PubMed 
    Article 

    Google Scholar 
    Blažeković, K., Pleić, I. L., Đuras, M., Gomerčić, T. & Mladineo, I. Three Anisakis spp. isolated from toothed whales stranded along the eastern Adriatic Sea coast. Int. J. Parasitol. 45, 17–31 (2015).PubMed 
    Article 

    Google Scholar 
    Mazzariol, S. et al. Multidisciplinary studies on a sick-leader syndrome-associated mass stranding of sperm whales (Physeter macrocephalus) along the Adriatic coast of Italy. Sci. Rep. 8, 11577 (2018).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Gomerčić, M. et al. Bottlenose dolphin (Tursiops truncatus) depredation resulting in larynx strangulation with gill-net parts. Mar. Mammal Sci. 25, 392–401 (2009).Article 

    Google Scholar 
    Pyenson, N. The high fidelity of the cetacean stranding record: Insights into measuring diversity by integrating taphonomy and macroecology. Proc. R. Soc. B. 278, 3608–3616 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    MacLeod, C. D., Santos, B., López Fernandez, A. & Pierce, G. Relative prey size consumption in toothed whales: Implications for prey selection and level of specialisation. Mar. Ecol. Prog. Ser. 326, 295–307 (2006).ADS 
    Article 

    Google Scholar 
    Santos, M. B. et al. Pygmy sperm whales Kogia Breviceps in the Northeast Atlantic: New information on stomach contents and strandings. Mar. Mammal Sci. 22, 600–616 (2006).Article 

    Google Scholar 
    Covelo, P., Martínez-Cedeira, J., Llavona, A., Díaz, J. & López Fernandez, A. Strandings of Beaked Whales (Ziphiidae) in Galicia (NW Spain) between 1990 and 2013. J. Mar. Biol. Assoc. U. K. 1, 1–7 (2016).
    Google Scholar 
    Moura, J. et al. Stranding events of Kogia whales along the Brazilian Coast. PLoS ONE 11, e0146108 (2016).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cordes, D. O. The causes of whale strandings. N. Z. Vet. J. 30, 21–24 (1982).CAS 
    PubMed 
    Article 

    Google Scholar 
    Frantzis, A. Does acoustic testing strand whales?. Nature 392, 29 (1998).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Laist, D. W., Knowlton, A. R., Mead, J. G., Collet, A. S. & Podesta, M. Collisions between ships and whales. Mar. Mammal Sci. 17, 35–75 (2001).Article 

    Google Scholar 
    Jepson, P. D. et al. Gas-bubble lesions in stranded cetaceans. Nature 425, 575–576 (2003).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Pierce, G. J., Santos, M. B., Smeenk, C., Saveliev, A. & Zuur, A. F. Historical trends in the incidence of strandings of sperm whales (Physeter macrocephalus) on North Sea coasts: An association with positive temperature anomalies. Fish. Res. 87, 219–228 (2007).Article 

    Google Scholar 
    Coombs, E. et al. What can cetacean stranding records tell us? A study of UK and Irish cetacean diversity over the past 100 years. Mar. Mammal Sci. 35, 1527–1555 (2019).Article 

    Google Scholar 
    Fossi, M. C., Baini, M., Panti, C. & Baulch, S. Chapter 6—Impacts of marine litter on cetaceans: A focus on plastic pollution. In Marine Mammal Ecotoxicology (eds Fossi, M. C. & Panti, C.) 147–184 (Academic Press, 2018).Chapter 

    Google Scholar 
    Alexiadou, P., Foskolos, I. & Frantzis, A. Ingestion of macroplastics by odontocetes of the Greek Seas, Eastern Mediterranean: Often deadly!. Mar. Poll. Bull. 146, 67–75 (2019).CAS 
    Article 

    Google Scholar 
    Nicol, C. et al. Anthropogenic threats to Wild Cetacean welfare and a tool to inform policy in this area. Vet. Sci. Res. J. 7, 57 (2020).
    Google Scholar 
    Abollo, E., Paggi, L., Pascual, S. & D’Amelio, S. Occurrence of recombinant genotypes of Anisakis simplex s.s. and Anisakis pegreffii (Nematoda: Anisakidae) in an area of sympatry. Infect. Genet. Evol. 3, 175–181 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Marques, J. F., Cabral, H., Busi, M. & D’Amelio, S. Molecular identification of Anisakis species from Pleuronectiformes off the Portuguese coast. J. Helminthol. 80, 47–51 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lee, M. H., Cheon, D. & Choi, C. Molecular genotyping of Anisakis species from Korean sea fish by polymerase chain reaction–restriction fragment length polymorphism (PCR-RFLP). Food Control 20, 623–626 (2009).CAS 
    Article 

    Google Scholar 
    Suzuki, J., Murata, R., Hosaka, M. & Araki, J. Risk factors for human Anisakis infection and association between the geographic origins of Scomber japonicus and anisakid nematodes. Int. J. Food Microbiol. 137, 88–93 (2010).PubMed 
    Article 

    Google Scholar 
    Molina-Fernández, D. et al. Fishing area and fish size as risk factors of Anisakis infection in sardines (Sardina pilchardus) from Iberian waters, southwestern Europe. Int. J. Food Microb. 203, 27–34 (2015).Article 

    Google Scholar 
    Cipriani, P. et al. Genetic identification and distribution of the parasitic larvae of Anisakis pegreffii and Anisakis simplex (s.s.) in European hake Merluccius merluccius from the Tyrrhenian Sea and Spanish Atlantic coast: Implications for food safety. Int. J. Food Microbiol. 198, 1–8 (2015).PubMed 
    Article 

    Google Scholar 
    Gómez-Mateos, M., Merino-Espinosa, G., Corpas-López, V., Valero-López, A. & Martín-Sánchez, J. A multi-restriction fragment length polymorphism genotyping approach including the beta-tubulin gene as a new differential nuclear marker for the recognition of the cryptic species Anisakis simplex s.s. and Anisakis pegreffii and their hybridization events. Vet. Parasitol. 283, 109162 (2020).PubMed 
    Article 
    CAS 

    Google Scholar 
    Klimpel, S., Busch, M. W., Kuhn, T., Rohde, A. & Palm, H. The Anisakis simplex complex off the South Shetland Islands (Antarctica): Endemic populations versus introduction through migratory hosts. Mar. Ecol. Progr. Ser. 40, 1–11 (2010).ADS 
    Article 
    CAS 

    Google Scholar 
    Santoro, M. et al. Helminth parasites of the dwarf sperm whale Kogia sima (Cetacea: Kogiidae) from the Mediterranean Sea, with implications on host ecology. Dis. Aquat. Organ. 129, 175–182 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mattiucci, S., Nascetti, G., Bullini, L., Orecchia, P. & Paggi, L. Genetic structure of Anisakis physeteris and its differentiation from the Anisakis simplex complex (Ascaridida: Anisakidae). Parasitology 93, 383–387 (1986).CAS 
    PubMed 
    Article 

    Google Scholar 
    Palomba, M., Mattiucci, S., Crocetta, F., Osca, D. & Santoro, M. Insights into the role of deep-sea squids of the genus Histioteuthis (Histioteuthidae) in the life cycle of ascaridoid parasites in the Central Mediterranean Sea waters. Sci. Rep. 11, 7135 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Clarke, M. R., Martins, H. R. & Pascoe, P. The diet of sperm whales (Physeter macrocephalus Linnaeus 1758) off the Azores. Philos. Trans. R. Soc. Lond. B. 339, 67–82 (1993).ADS 
    CAS 
    Article 

    Google Scholar 
    Santos, M. & Pierce, G. A note on niche overlap in teuthophagous whales in the northern Northeast Atlantic. Phuket Mar. Biol. Cent. Res. Bull. 66, 291–298 (2005).
    Google Scholar 
    Rendell, L. & Frantzis, A. Mediterranean Sperm Whales, Physeter macrocephalus: The precarious state of a lost tribe. In Advances in Marine Biology (eds Notarbartolo di Sciara, G. et al.) 37–74 (Academic Press, 2016).
    Google Scholar 
    Foskolos, I., Koutouzi, N., Polychronidis, L., Alexiadou, P. & Frantzis, A. A taste for squid: the diet of sperm whales stranded in Greece, Eastern Mediterranean. Deep Sea Res. I Oceanogr. Res. Pap. 155, 103164 (2020).Article 

    Google Scholar 
    Mattiucci, S. et al. Genetic heterogeneity within Anisakis physeteris (sensu lato) (Nematoda: Anisakidae) from sperm whales, Physeter macrocephalus, from Mediterranean Sea (Apulian coast) and Atlantic Ocean (Canaries coast). Abstract of XXVI Congresso Nazionale SoIPa. Parassitologia 52, 357 (2010).
    Google Scholar 
    Mattiucci, S. et al. Genetic identification and insights into the ecology of Contracaecum rudolphii A and C. rudolphii B (Nematoda: Anisakidae) from cormorants and fish of aquatic ecosystems of Central Italy. Parasitol. Res. 119, 1243–1257 (2020).PubMed 
    Article 

    Google Scholar 
    Karvonen, A., Jokela, J. & Laine, A. L. Importance of sequence and timing in parasite coinfections. Trends Parasitol. 35, 109–118 (2019).PubMed 
    Article 

    Google Scholar 
    Paggi, L. et al. A new species of Anisakis Dujardin, 1845 (Nematoda: Anisakidae) from beaked whale (Ziphiidae): Allozyme and morphological evidence. Syst. Parasitol. 40, 161–174 (1998).Article 

    Google Scholar 
    Mattiucci, S., Paoletti, M. & Webb, S. C. Anisakis nascettii n. sp. (Nematoda: Anisakidae) from beaked whales of the southern hemisphere: Morphological description, genetic relationships between congeners and ecological data. Syst. Parasitol. 74, 199–217 (2009).PubMed 
    Article 

    Google Scholar 
    Leatherwood, S. & Reeves, R. R. The Sierra Club Handbook of Whales and Dolphins 302 (Sierra Club Books, 1983).
    Google Scholar 
    Ross, G. J. B. The smaller cetaceans of the South East coast of southern Africa. Ann. Cape Prov. Mus. Nat. Hist. 15, 173–410 (1984).
    Google Scholar 
    Santos, B. et al. Feeding ecology of Cuvier’s beaked whale (Ziphius cavirostris): A review with new information on the diet of this species. J. Mar. Biol. Assoc. U. K. 81, 687–694 (2001).Article 

    Google Scholar 
    Lakemeyer, J. et al. Anisakid nematode species identification in harbour porpoises (Phocoena phocoena) from the North Sea, Baltic Sea and North Atlantic using RFLP analysis. Int. J. Parasitol. Parasites Wildl. 12, 93–98 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Højgaard, D. No significant development of Anisakis simplex (Nematoda, Anisakidae) eggs in the intestine of long-finned pilot whales, Globicephala melas (Traill, 1809). Sarsia 84, 479–482 (1999).Article 

    Google Scholar 
    Smith, J. W. & Wootten, R. Experimental studies on the migration of Anisakis sp. larvae (Nematoda: ascaridida) into the flesh of herring, Clupea harengus L. Int. J. Parasitol. 5, 133–136 (1975).CAS 
    PubMed 
    Article 

    Google Scholar 
    Iglesias, L., Valero, A., Benítez, R. & Adroher, F. J. In vitro cultivation of Anisakis simplex: Pepsin increases survival and moulting from fourth larval to adult stage. Parasitology 123, 285–291 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mladineo, I. & Poljak, V. Ecology and genetic structure of zoonotic Anisakis spp. from adriatic commercial fish species. Appl. Environ. Microbiol. 80, 1281–1290 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Mladineo, I., Bušelić, I., Hrabar, J., Vrbatović, A. & Radonić, I. Population parameters and mito-nuclear mosaicism of Anisakis spp. in the Adriatic Sea. Mol. Biochem. Parasitol. 212, 46–54 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Levsen, A. et al. Anisakis species composition and infection characteristics in Atlantic mackerel, Scomber scombrus, from major European fishing grounds—Reflecting changing fish host distribution and migration pattern. Fish. Res. 202, 112–121 (2018).Article 

    Google Scholar 
    Gay, M. et al. Infection levels and species diversity of ascaridoid nematodes in Atlantic cod, Gadus morhua, are correlated with geographic area and fish size. Fish. Res. 202, 90–102 (2018).Article 

    Google Scholar 
    Stevick, P. et al. Segregation of migration by feeding ground origin in North Atlantic humpback whales (Megaptera novaeangliae). J. Zool. 259, 231–237 (2003).Article 

    Google Scholar 
    Lambert, E. et al. Cetacean range and climate in the eastern North Atlantic: Future predictions and implications for conservation. Glob. Change Biol. 20, 1782–1793 (2014).ADS 
    Article 

    Google Scholar 
    Szesciorka, A. et al. Timing is everything: Drivers of interannual variability in blue whale migration. Sci. Rep. 10, 7710 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hoelzel, A. R., Goldsworthy, S. D. & Fleischer, R. C. Population genetic structure. In Marine Mammal Biology: An Evolutionary Approach (ed. Hoelzel, A. R.) 1–134 (Blackwell Publishing, 2002).
    Google Scholar 
    Lahaye, V. et al. Long-term dietary segregation of common dolphins Delphinus delphis in the Bay of Biscay, determined using cadmium as an ecological tracer. Mar. Ecol. Prog. Ser. 305, 275–285 (2005).ADS 
    CAS 
    Article 

    Google Scholar 
    Mattiucci, S. et al. Population genetic structure of the parasite Anisakis simplex (s.s.) collected in Clupea harengus L. from North East Atlantic fishing grounds. Fish. Res. 202, 103–111 (2018).Article 

    Google Scholar 
    Natoli, A. et al. Conservation genetics of the short-beaked common dolphin (Delphinus delphis) in the Mediterranean Sea and in the eastern North Atlantic Ocean. Conserv. Genet. 9, 1479–1487 (2008).Article 

    Google Scholar 
    Mazzariol, S. et al. Sometimes sperm whales (Physeter macrocephalus) cannot find their way back to the high seas: A multidisciplinary study on a mass stranding. PLoS ONE 6, e19417 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mazzariol, S. et al. Dolphin Morbillivirus associated with a mass stranding of sperm Whales, Italy. Emerg. Infect. Dis. 23, 144–146 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Podestà, M. et al. Cuvier’s beaked whale, Ziphius cavirostris, distribution and occurrence in the Mediterranean Sea: High-use areas and conservation threats. Adv. Mar. Biol. 75, 103–140 (2016).PubMed 
    Article 

    Google Scholar 
    Davies, K., Pagan, C. & Nadler, S. A. Host population expansion and the genetic architecture of the pinniped hookworm Uncinaria lucasi. J. Parasitol. 106, 383–391 (2020).PubMed 
    Article 

    Google Scholar 
    IJsseldijk, L. L., Brownlow, A. C. & Mazzariol, S. European best practice on cetacean post-mortem investigation and tissue sampling (ed. IJsseldijk, L. L., Brownlow, A. C., & Mazzariol, S.) 1–72 (ASCOBANS/ACCOBAMS, 2019).Nadler, S. A. & Hudspeth, D. S. Phylogeny of the Ascaridoidea (Nematoda: Ascaridida) based on three genes and morphology: Hypotheses of structural and sequence evolution. J. Parasitol. 86, 380–393 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hall, T. A. BioEdit: A user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT. Nucleic Acids Symp. Ser. 41, 95–98 (1999).CAS 

    Google Scholar 
    Suchard, M. A. et al. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol. 4, vey016 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Darriba, D., Taboada, G. L., Doallo, R. & Posada, D. jModelTest 2: More models, new heuristics and parallel computing. Nat. Methods 9, 772 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zuckerkandl, E. & Pauling, L. Molecular disease, evolution, and genetic heterogeneity. In Horizons in Biochemistry (eds Kasha, M. & Pullman, B.) 189–225 (Academic Press, 1962).
    Google Scholar 
    Gernhard, T. The conditioned reconstructed process. J. Theor. Biol. 253, 769–778 (2008).ADS 
    MathSciNet 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Rambaut, A., Drummond, A. J., Xie, D., Baele, G. & Suchard, M. A. Posterior summarisation in Bayesian phylogenetics using Tracer 1.7. Syst. Biol. 67, 901–904 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Weir, B. & Cockerham, C. Estimating F-statistics for the analysis of population structure. Evolution 38, 1358–1370 (1984).CAS 
    PubMed 

    Google Scholar 
    Excoffier, L. & Lischer, H. E. Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows. Mol. Ecol. Resour. 10, 564–567 (2010).PubMed 
    Article 

    Google Scholar 
    Librado, P. & Rozas, J. DnaSP v5: A software for comprehensive analysis of DNA polymorphism data. Bioinformatics 25, 1451–1452 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bandelt, H., Forster, P. & Röhl, A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16, 37–48 (1999).CAS 
    PubMed 
    Article 

    Google Scholar 
    Clement, M., Posada, D. & Crandall, K. A. TCS: A computer program to estimate gene genealogies. Mol. Ecol. 9, 1657–1659 (2000).CAS 
    PubMed 
    Article 

    Google Scholar  More

  • in

    Drivers of avian habitat use and detection of backyard birds in the Pacific Northwest during COVID-19 pandemic lockdowns

    Liu, X. et al. High-spatiotemporal-resolution mapping of global urban change from 1985 to 2015. Nat. Sustain. 3, 564–570 (2020).Article 

    Google Scholar 
    Chace, J. F. & Walsh, J. J. Urban effects on native avifauna: A review. Landsc. Urban Plan. 74, 46–69 (2006).Article 

    Google Scholar 
    Rosenberg, K. V. et al. Decline of the North American avifauna. Science (1979) 366, 120–124 (2019).CAS 

    Google Scholar 
    Isaksson, C. Impact of Urbanization on Birds https://doi.org/10.1007/978-3-319-91689-7_13 (2018).Article 

    Google Scholar 
    Grimm, N. B. et al. Global change and the ecology of cities. Science 319, 756–760. https://doi.org/10.1126/science.1150195 (2008).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Pipoly, I. et al. Extreme hot weather has stronger impacts on Avian reproduction in forests than in cities. Front. Ecol. Evol. 10, 1 (2022).Article 

    Google Scholar 
    Newberry, G. N., O’Connor, R. S. & Swanson, D. L. Urban rooftop-nesting Common Nighthawk chicks tolerate high temperatures by hyperthermia with relatively low rates of evaporative water loss. Condor 123, 016 (2021).Article 

    Google Scholar 
    da Silva, A., Valcu, M. & Kempenaers, B. Light pollution alters the phenology of dawn and dusk singing in common European songbirds. Philos. Trans. R. Soc. B: Biol. Sci. 370, 126 (2015).Article 

    Google Scholar 
    Welbers, A. A. M. H. et al. Artificial light at night reduces daily energy expenditure in breeding great tits (Parus major). Front. Ecol. Evol. 5, 55 (2017).Article 

    Google Scholar 
    van Doren, B. M. et al. High-intensity urban light installation dramatically alters nocturnal bird migration. Proc. Natl. Acad. Sci. USA. 114, 11175–11180 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Miller, M. W. Apparent effects of light pollution on singing behavior of American Robins. Condor 108, 130–139 (2006).Article 

    Google Scholar 
    Nemeth, E. & Brumm, H. Birds and anthropogenic noise: Are urban songs adaptive?. Am. Nat. 176, 465 (2010).PubMed 
    Article 

    Google Scholar 
    Nemeth, E. et al. Bird song and anthropogenic noise: Vocal constraints may explain why birds sing higher-frequency songs in cities. Proc. R. Soc. B: Biol. Sci. 280, 20122798 (2013).Article 

    Google Scholar 
    Senzaki, M., Yamaura, Y., Francis, C. D. & Nakamura, F. Traffic noise reduces foraging efficiency in wild owls. Sci. Rep. 6, 1–7 (2016).Article 
    CAS 

    Google Scholar 
    Ortega, C. P. Effects of noise pollution on birds: A brief review of our knowledge. Ornithol. Monogr. 74, 6–22 (2012).Article 

    Google Scholar 
    Sanderfoot, O. V. & Holloway, T. Air pollution impacts on avian species via inhalation exposure and associated outcomes. Environ. Res. Lett. 12, 832. https://doi.org/10.1088/1748-9326/aa8051 (2017).CAS 
    Article 

    Google Scholar 
    Eeva, T. & Lehikoinen, E. Egg shell quality, clutch size and hatching success of the great tit (Parus major) and the pied flycatcher (Ficedula hypoleuca) in an air pollution gradient. Oecologia 102, 312–323 (1995).ADS 
    PubMed 
    Article 

    Google Scholar 
    Tablado, Z. et al. Effect of human disturbance on bird telomere length: An experimental approach. Front. Ecol. Evol. 9, 1 (2022).Article 

    Google Scholar 
    Kang, W., Minor, E. S., Park, C. R. & Lee, D. Effects of habitat structure, human disturbance, and habitat connectivity on urban forest bird communities. Urban Ecosyst. 18, 857–870 (2015).Article 

    Google Scholar 
    Blair, R. B. Land use and avian species diversity along an urban gradient. Ecol. Appl. 6, 506–519 (1996).Article 

    Google Scholar 
    Estela, F. A. et al. Changes in the nocturnal activity of birds during the covid–19 pandemic lockdown in a neotropical city. Anim. Biodivers. Conserv. 44, 1 (2021).
    Google Scholar 
    Bates, A. E., Primack, R. B., Moraga, P. & Duarte, C. M. COVID-19 pandemic and associated lockdown as a “Global Human Confinement Experiment” to investigate biodiversity conservation. Biol. Conserv. 248, 108665. https://doi.org/10.1016/j.biocon.2020.108665 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rutz, C. et al. COVID-19 lockdown allows researchers to quantify the effects of human activity on wildlife. Nat. Ecol. Evol. 4, 1156–1159. https://doi.org/10.1038/s41559-020-1237-z (2020).Article 
    PubMed 

    Google Scholar 
    Czech, K., Davy, A. & Wielechowski, M. Does the covid-19 pandemic change human mobility equally worldwide? Cross-country cluster analysis. Economies 9, 182 (2021).Article 

    Google Scholar 
    Galeazzi, A. et al. Human mobility in response to COVID-19 in France, Italy and UK. Sci. Rep. 11, 1 (2021).Article 
    CAS 

    Google Scholar 
    Joshi, Y. V. & Musalem, A. Lockdowns lose one third of their impact on mobility in a month. Sci. Rep. 11, 1 (2021).Article 
    CAS 

    Google Scholar 
    Dobbie, L. J., Hydes, T. J., Alam, U., Tahrani, A. & Cuthbertson, D. J. The impact of the COVID-19 pandemic on mobility trends and the associated rise in population-level physical inactivity: Insights From International Mobile Phone and National Survey Data. Front. Sports Active Living 4, 80 (2022).Article 

    Google Scholar 
    Basu, B. et al. Investigating changes in noise pollution due to the COVID-19 lockdown: The case of Dublin, Ireland. Sustain. Cities Soc. 65, 102597 (2021).Article 

    Google Scholar 
    Lecocq, T. et al. Global quieting of high-frequency seismic noise due to COVID-19 pandemic lockdown measures. Science (1979) 369, 1338 (2020).
    Google Scholar 
    Terry, C., Rothendler, M., Zipf, L., Dietze, M. C. & Primack, R. B. Effects of the COVID-19 pandemic on noise pollution in three protected areas in metropolitan Boston (USA). Biol. Cons. 256, 109039 (2021).Article 

    Google Scholar 
    Venter, Z. S., Aunan, K., Chowdhury, S. & Lelieveld, J. COVID-19 lockdowns cause global air pollution declines. Proc Natl Acad Sci U S A 117, 18984 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Archer, C. L., Cervone, G. & Golbazi, M. Changes in air quality and human mobility in the US during the COVID-19 pandemic. Bull. Atmosp. Sci. Technol. 1, 491–541. https://doi.org/10.1007/s42865-020-00019-0 (2020).Article 

    Google Scholar 
    Jiang, Z. et al. Modeling the impact of COVID-19 on air quality in Southern California: Implications for future control policies. Atmosp. Chem. Phys. Discuss. https://doi.org/10.5194/acp-2020-1197 (2020).Shi, Z. et al. Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns. Sci. Adv. 7, 6696 (2021).ADS 
    Article 
    CAS 

    Google Scholar 
    Hentati-Sundberg, J., Berglund, P. A., Hejdström, A. & Olsson, O. COVID-19 lockdown reveals tourists as seabird guardians. Biol. Conserv. 254, 108950 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Derryberry, E. P., Phillips, J. N., Derryberry, G. E., Blum, M. J. & Luther, D. Singing in a silent spring: Birds respond to a half-century soundscape reversion during the COVID-19 shutdown. Science (1979) 370, 575 (2020).CAS 

    Google Scholar 
    Schrimpf, M. B. et al. Reduced human activity during COVID-19 alters avian land use across North America. Sci. Adv. 7, 5073 (2021).ADS 
    Article 
    CAS 

    Google Scholar 
    MacKenzie, D. I. et al. Estimating site occupancy rates when detection probabilities are less than one. Ecology 83, 2248–2252 (2002).Article 

    Google Scholar 
    Gordo, O., Brotons, L., Herrando, S. & Gargallo, G. Rapid behavioural response of urban birds to COVID-19 lockdown. Proc. R. Soc. B: Biol. Sci. 288, 20202513 (2021).CAS 
    Article 

    Google Scholar 
    Johnson, D. H. In defense of indices: The Case of Bird Surveys. J. Wildl. Manag. 72, 857–868 (2008).Article 

    Google Scholar 
    Sanderfoot, O. V. & & Gardner, B.,. Wildfire smoke affects detection of birds in Washington State. Ornithol. Appl. 123, 28 (2021).
    Google Scholar 
    Sumasgutner, P. et al. Raptor research during the COVID-19 pandemic provides invaluable opportunities for conservation biology. Biol. Conserv. 260, 109149 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Crimmins, T. M., Posthumus, E., Schaffer, S. & Prudic, K. L. COVID-19 impacts on participation in large scale biodiversity-themed community science projects in the United States. Biol. Conserv. 256, 109017 (2021).Article 

    Google Scholar 
    Basile, M., Russo, L. F., Russo, V. G., Senese, A. & Bernardo, N. Birds seen and not seen during the COVID-19 pandemic: The impact of lockdown measures on citizen science bird observations. Biol. Conserv. 256, 109079 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Kishimoto, K. & Kobori, H. COVID-19 pandemic drives changes in participation in citizen science project “City Nature Challenge” in Tokyo. Biol. Conserv. 255, 109001 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Sullivan, B. L. et al. eBird: A citizen-based bird observation network in the biological sciences. Biol. Conserv. 142, 2282 (2009).Article 

    Google Scholar 
    Pacifici, K., Simons, T. R. & Pollock, K. H. Effects of vegetation and background noise on the detection process in auditory avian point-count surveys. Auk 125, 600–607 (2008).Article 

    Google Scholar 
    Mitchell, M. S. et al. Testing a priori hypotheses improves the reliability of wildlife research. J. Wildl. Manag. 82, 1568. https://doi.org/10.1002/jwmg.21568 (2018).Article 

    Google Scholar 
    Sells, S. N. et al. Increased scientific rigor will improve reliability of research and effectiveness of management. J. Wildl. Manag. 82, 485. https://doi.org/10.1002/jwmg.21413 (2018).Article 

    Google Scholar 
    Strimas-Mackey, M., E. Miller, and W. Hochachka. auk: eBird Data Extraction and Processing with AWK. R package version 0.3.0. (2018) https://cornelllabofornithology.github.io/auk/R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (2020). https://www.R-project.org/.U.S. Environmental Protection Agency (EPA). Air Quality System Data Mart (2020). https://www.epa.gov/airdataKaragulian, F. et al. Contributions to cities’ ambient particulate matter (PM): A systematic review of local source contributions at global level. Atmos. Environ. 120, 475. https://doi.org/10.1016/j.atmosenv.2015.08.087 (2015).ADS 
    CAS 
    Article 

    Google Scholar 
    Ito, K., Thurston, G. D. & Silverman, R. A. Characterization of PM25, gaseous pollutants, and meteorological interactions in the context of time-series health effects models. J. Exposure Sci. Environ. Epidemiol. 17, S45–S60 (2007).CAS 
    Article 

    Google Scholar 
    Google LLC “Google COVID-19 Community Mobility Reports”. https://www.google.com/covid19/mobility/ Accessed: November 1, 2020.Waze “Global Mobility Report”. https://www.waze.com Accessed: May 22, 2020.Pierce, D. ncdf4: Interface to Unidata netCDF (Version 4 or Earlier) Format Data Files. R package version 1.17 (2019). https://CRAN.R-project.org/package=ncdf4Esri “USA NLCD Land Cover” [imagery layer]. Esri Inc (2019). https://www.arcgis.com/home/item.html?id=3ccf118ed80748909eb85c6d262b426f.Esri Inc. ArcMap (Version 10.8.1). Esri Inc. Redlands, California, USA (2020). https://desktop.arcgis.com/en/arcmap/.Fiske, I. & Chandler, R. unmarked: An R package for fitting hierarchical models of wildlife occurrence and abundance. J. Stat. Softw. 43(10), 1–23 (2011).Article 

    Google Scholar 
    Efford, M. G. & Dawson, D. K. Occupancy in continuous habitat. Ecosphere 3, 1 (2012).Article 

    Google Scholar 
    Lee, B. P. Y. H., Davies, Z. G. & Struebig, M. J. Smoke pollution disrupted biodiversity during the 2015 El Niño fires in Southeast Asia. Environ. Res. Lett. 12, 094022 (2017).ADS 
    Article 

    Google Scholar 
    Leonard, R. J. & Hochuli, D. F. Exhausting all avenues: why impacts of air pollution should be part of road ecology. Front. Ecol. Environ. 15, 443. https://doi.org/10.1002/fee.1521 (2017).Article 

    Google Scholar 
    Plummer, K. E., Risely, K., Toms, M. P. & Siriwardena, G. M. The composition of British bird communities is associated with long-term garden bird feeding. Nat. Commun. 10, 1 (2019).CAS 
    Article 

    Google Scholar 
    Cleary, G. P. et al. Avian assemblages at bird baths: A comparison of urban and rural bird baths in Australia. PLoS ONE 11, e0150899 (2016).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Bailey, L. L., Mackenzie, D. I. & Nichols, J. D. Advances and applications of occupancy models. Methods Ecol. Evol. 5, 1269 (2014).Article 

    Google Scholar 
    Leong, M., Dunn, R. R. & Trautwein, M. D. Biodiversity and socioeconomics in the city: a review of the luxury effect. Biol. Lett. 14, 1. https://doi.org/10.1098/rsbl.2018.0082 (2018).Article 

    Google Scholar  More

  • in

    Context-specific emergence and growth of the SARS-CoV-2 Delta variant

    These authors contributed equally: John T. McCrone, Verity Hill, Sumali Bajaj, Rosario Evans PenaThese authors jointly supervised this work: Oliver G. Pybus, Andrew Rambaut, Moritz U.G. KraemerA list of authors and their affiliations appears in the Supplementary InformationInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh, UKJohn T. McCrone, Verity Hill, Ben Jackson, Rachel Colquhoun, Áine O’Toole & Andrew RambautDepartment of Zoology, University of Oxford, Oxford, UKSumali Bajaj, Rosario Evans Pena, Rhys Inward, Alexander E. Zarebski, Jayna Raghwani, Nuno R. Faria, Louis du Plessis, Oliver G. Pybus & Moritz U. G. KraemerDepartment of Computer Science, University of Oxford, Oxford, UKBen C. LambertMRC Centre of Global Infectious Disease Analysis, Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UKRhys Inward, Samir Bhatt, Erik Volz & Nuno R. FariaSection of Epidemiology, Department of Public Health, University of Copenhagen, Copenhagen, DenmarkSamir BhattMolecular Immunity Unit, Department of Medicine, Cambridge University, Cambridge, UKChristopher RuisSpatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, BelgiumSimon DellicourDepartment of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, BelgiumSimon Dellicour & Guy BaeleGoogle, Mountain View, CA, USAAdam Sadilek, Neo Wu & Aaron SchneiderDepartment of Mathematics, School of Science & Engineering, Tulane University, New Orleans, LA, USAXiang JiDepartment of Infectious Disease, Imperial College London, London, UKThomas P. Peacock & Wendy S. BarclayUK Health Security Agency, London, UKThomas P. Peacock, Kate Twohig, Simon Thelwall, Gavin Dabrera, Richard Myers & Meera ChandInstituto de Medicina Tropical, Faculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, BrazilNuno R. FariaBlueDot, Toronto, CanadaCarmen Huber & Kamran KhanDivisions of Internal Medicine & Infectious Diseases, Toronto General Hospital, University Health Network, Toronto, CanadaIsaac I. BogochDepartment of Medicine, Division of Infectious Diseases, University of Toronto, Toronto, ON, CanadaIsaac I. Bogoch & Kamran KhanLi Ka Shing Knowledge Institute, St. Michael’s Hospital, Toronto, ON, CanadaKamran KhanDepartment of Biosystems Science and Engineering, ETH Zurich, Zurich, SwitzerlandLouis du PlessisWellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UKJeffrey C. Barrett & David M. AanensenBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UKDavid M. AanensenPathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UKThomas ConnorSchool of Biosciences, The Sir Martin Evans Building, Cardiff University, Cardiff, UKThomas ConnorQuadram Institute, Norwich, UKThomas ConnorInstitute of Microbiology and Infection, University of Birmingham, Birmingham, UKNicholas J. LomanDepartments of Biostatistics, Biomathematics and Human Genetics, University of California, Los Angeles, Los Angeles, CA, USAMarc A. SuchardDepartment of Pathobiology and Population Sciences, Royal Veterinary College London, London, UKOliver G. PybusPandemic Sciences Institute, University of Oxford, Oxford, UKOliver G. Pybus & Moritz U. G. Kraemer More