Philippa Kaur

1.
Helm, B. et al. Annual rhythms that underlie phenology: Biological time-keeping meets environmental change. Proc. R. Soc. B 280, 20130016 (2013).
PubMed  Article  PubMed Central  Google Scholar 
2.
McNamara, J. M., Barta, Z., Klaassen, M. & Bauer, S. Cues and the optimal timing of activities under environmental changes. Ecol. Lett. 14, 1183–1190 (2011).
PubMed  PubMed Central  Article  Google Scholar 

3.
Walther, G.-R. et al. Ecological responses to recent climate change. Nature 416, 389 (2002).
ADS  CAS  PubMed  Article  PubMed Central  Google Scholar 

4.
Diez, J. M. et al. Forecasting phenology: From species variability to community patterns. Ecol. Lett. 15, 545–553 (2012).
PubMed  Article  Google Scholar 

5.
Post, E., Pedersen, C., Wilmers, C. C. & Forchhammer, M. C. Warming, plant phenology and the spatial dimension of trophic mismatch for large herbivores. Proc. R. Soc. Lond. B Biol. Sci. 275, 2005–2013 (2008).
Google Scholar 

6.
Primack, R. B. et al. Spatial and interspecific variability in phenological responses to warming temperatures. Biol. Conserv. 142, 2569–2577 (2009).
Article  Google Scholar 

7.
Fryxell, J. M. & Sinclair, A. R. E. Causes and consequences of migration by large herbivores. Trends Ecol. Evol. 3, 237–241 (1988).
CAS  PubMed  Article  Google Scholar 

8.
Levey, D. J. & Stiles, F. G. Evolutionary precursors of long-distance migration: Resource availability and movement patterns in neotropical landbirds. Am. Nat. 140, 447–476 (1992).
Article  Google Scholar 

9.
Alerstam, T., Hedenström, A. & Åkesson, S. Long-distance migration: Evolution and determinants. Oikos 103, 247–260 (2003).
Article  Google Scholar 

10.
Dawson, A. Control of the annual cycle in birds: Endocrine constraints and plasticity in response to ecological variability. Philos. Trans. R. Soc. B Biol. Sci. 363, 1621–1633 (2008).
Article  Google Scholar 

11.
Buehler, D. & Piersma, T. Travelling on a budget: Predictions and ecological evidence for bottlenecks in the annual cycle of long-distance migrants. Philos. Trans. R. Soc. B-Biol. Sci. 363, 247–266 (2008).
Article  Google Scholar 

12.
Kokko, H. Competition for early arrival in migratory birds. J. Anim. Ecol. 68, 940–950 (1999).
Article  Google Scholar 

13.
Moller, A. P. Heritability of arrival date in a migratory bird. Proc. R. Soc. Lond. B Biol. Sci. 268, 203–206 (2001).
CAS  Article  Google Scholar 

14.
Saino, N. et al. Ecological conditions during winter predict arrival date at the breeding quarters in a trans-Saharan migratory bird. Ecol. Lett. 7, 21–25 (2004).
Article  Google Scholar 

15.
Studds, C. E. & Marra, P. P. Rainfall-induced changes in food availability modify the spring departure programme of a migratory bird. Proc. R. Soc. B Biol. Sci. 278, 3437–3443 (2011).
Article  Google Scholar 

16.
Conklin, J. R., Battley, P. F., Potter, M. A. & Fox, J. W. Breeding latitude drives individual schedules in a trans-hemispheric migrant bird. Nat. Commun. 1, 67 (2010).
ADS  PubMed  Article  CAS  Google Scholar 

17.
Holmes, R. T. Latitudinal differences in the breeding and molt schedules of Alaskan Red-backed Sandpipers (Calidris alpina). Condor 73, 93–99 (1971).
Article  Google Scholar 

18.
Briedis, M., Hahn, S. & Adamík, P. Cold spell en route delays spring arrival and decreases apparent survival in a long-distance migratory songbird. BMC Ecol. 17, 11 (2017).
PubMed  PubMed Central  Article  Google Scholar 

19.
Sandercock, B. K., Lank, D. B. & Cooke, F. Seasonal declines in the fecundity of arctic-breeding sandpipers: Different tactics in two species with an invariant clutch size. J. Avian Biol. 30, 460–468 (1999).
Article  Google Scholar 

20.
Langin, K. M. & P. P. M. ,. Breeding latitude and timing of spring migration in songbirds crossing the Gulf of Mexico. J. Avian Biol. 40, 309–316 (2009).
Article  Google Scholar 

21.
Lappalainen, J. & Tarkan, A. S. Latitudinal gradients in onset date, onset temperature and duration of spawning of roach. J. Fish Biol. 70, 441–450 (2007).
Article  Google Scholar 

22.
Ben-David, M. Timing of reproduction in wild mink: The influence of spawning Pacific salmon. Can. J. Zool. 75, 376–382 (1997).
Article  Google Scholar 

23.
Burr, Z. M. et al. Later at higher latitudes: Large-scale variability in seabird breeding timing and synchronicity. Ecosphere 7, e01283 (2016).
Article  Google Scholar 

24.
Briedis, M. et al. Breeding latitude leads to different temporal but not spatial organization of the annual cycle in a long-distance migrant. J. Avian Biol. 47, 743–748 (2016).
Article  Google Scholar 

25.
Lourenço, P. M. et al. Repeatable timing of northward departure, arrival and breeding in Black-tailed Godwits Limosa l. limosa, but no domino effects. J. Ornithol. 152, 1023–1032 (2011).
Article  Google Scholar 

26.
Armstrong, J. B., Takimoto, G., Schindler, D. E., Hayes, M. M. & Kauffman, M. J. Resource waves: Phenological diversity enhances foraging opportunities for mobile consumers. Ecology 97, 1099–1112 (2016).
PubMed  Article  Google Scholar 

27.
Renfrew, R. B. et al. Phenological matching across hemispheres in a long-distance migratory bird. Divers. Distrib. 19, 1008–1019 (2013).
Article  Google Scholar 

28.
Visser, M. E., te Marvelde, L. & Lof, M. E. Adaptive phenological mismatches of birds and their food in a warming world. J. Ornithol. 153, 75–84 (2012).
Article  Google Scholar 

29.
Bertness, M. D. & Ellison, A. M. Determinants of pattern in a New England salt marsh plant community. Ecol. Monogr. 57, 129–147 (1987).
Article  Google Scholar 

30.
Hoekstra, J. M., Molnar, J. L., Jennings, M., Revenga, C. & Spalding, M. D. The Atlas of Global Conservation, Vol. 67 (University of California Press, California, 2010).
Google Scholar 

31.
Kirwan, M. L., Guntenspergen, G. R. & Morris, J. T. Latitudinal trends in Spartina alterniflora productivity and the response of coastal marshes to global change. Glob. Change Biol. 15, 1982–1989 (2009).
ADS  Article  Google Scholar 

32.
Lowther, P. E., Douglas, H. D. III. & Gratto-Trevor, C. L. Willet (Tringa semipalmata). Birds N. Am. Online https://doi.org/10.2173/bna.579 (2001).
Article  Google Scholar 

33.
Tomkins, I. R. the summer schedule of the Eastern Willet in Georgia. Wilson Bull. 27, 291–296 (1955).
Google Scholar 

34.
Howe, M. A. Social organization in a nesting population of eastern Willets (Catoptrophorus semipalmatus). Auk 99, 88–102 (1982).
Article  Google Scholar 

35.
Gratto-Trevor, C. L. The North American Bander’s Manual for Banding Shorebirds (North Am. Band. Counc. Publ. Comm, Point Reyes CA, 2004).
Google Scholar 

36.
Minton, C. et al. Initial results from light level geolocator trials on Ruddy Turnstone Arenaria interpres reveal unexpected migration route. Wader Study Group Bull. 117, 9–14 (2010).
Google Scholar 

37.
Gosler, A. G. Birds in the hand. In Bird Ecology and Conservation: A Handbook of Techniques (eds Sutherland, W. J. et al.) 85–118 (Oxford University Press, Oxford, 2004).
Google Scholar 

38.
Sumner, M. D., Wotherspoon, S. J. & Hindell, M. A. Bayesian estimation of animal movement from archival and satellite tags. PLoS ONE 4, e7324 (2009).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

39.
R Core Team. R: A Language and Environment for Statistical Computing (The R Foundation, Vienna, 2020).
Google Scholar 

40.
Lisovski, S. et al. Light-level geolocator analyses: A user’s guide. J. Anim. Ecol. 89, 221–236 (2020).
PubMed  Article  Google Scholar 

41.
Lisovski, S., Bauer, S., Emmenegger, T. & Lisovski, M. S. Package ‘GeoLight’ (2012).

42.
Wotherspoon, S., Sumner, M. & Lisovski, S. TwGeos: Basic data processing for light-level geolocation archival tags. Version 00-1 (2016).

43.
Tonra, C. M. et al. Concentration of a widespread breeding population in a few critically important nonbreeding areas: Migratory connectivity in the Prothonotary Warbler. Condor 121, duz019 (2019).
Article  Google Scholar 

44.
Porter, R. & Smith, P. A. Techniques to improve the accuracy of location estimation using light-level geolocation to track shorebirds. Wader Study Group Bull. 120, 147–158 (2014).
Google Scholar 

45.
Battley, P. F. & Conklin, J. R. Geolocator wetness data accurately detect periods of migratory flight in two species of shorebird. Wader Study 124, 112–119 (2017).
Article  Google Scholar 

46.
Burger, J. et al. Migration and over-wintering of Red Knots (Calidris canutus rufa) along the Atlantic Coast of the United States. Condor 114, 302–313 (2012).
Article  Google Scholar 

47.
Cooper, N. W., Hallworth, M. T. & Marra, P. P. Light-level geolocation reveals wintering distribution, migration routes, and primary stopover locations of an endangered long-distance migratory songbird. J. Avian Biol. 48, 209–219 (2017).
Article  Google Scholar 

48.
Lisovski, S. et al. Geolocation by light: Accuracy and precision affected by environmental factors. Methods Ecol. Evol. 3, 603–612 (2012).
Article  Google Scholar 

49.
Burger, J., Niles, L. J., Porter, R. R. & Dey, A. D. Using geolocator data to reveal incubation periods and breeding biology in Red Knots Calidris canutus rufa. Wader Study Group Bull. 119, 26–36 (2012).
Google Scholar 

50.
Bulla, M. et al. Unexpected diversity in socially synchronized rhythms of shorebirds. Nature 540, 109–113 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

51.
Bates, D. et al. Package ‘lme4’. Version 1, 17 (2018).
Google Scholar 

52.
Lenth, R., Singmann, H., Love, J., Buerkner, P. & Herve, M. Emmeans: Estimated marginal means, aka least-squares means. R Package Version 1, 3 (2018).
Google Scholar 

53.
Sullivan, B. L. et al. eBird: A citizen-based bird observation network in the biological sciences. Biol. Conserv. 142, 2282–2292 (2009).
Article  Google Scholar 

54.
Spano, D., Cesaraccio, C., Duce, P. & Snyder, R. L. Phenological stages of natural species and their use as climate indicators. Int. J. Biometeorol. 42, 124–133 (1999).
ADS  Article  Google Scholar 

55.
Oregon State University Integrated Plant Protection Center. http://pnwpest.org/US/ (2015).

56.
Baskerville, G. L. & Emin, P. Rapid estimation of heat accumulation from maximum and minimum temperatures. Ecology 50, 514–517 (1969).
Article  Google Scholar 

57.
van Wijk, R. E. et al. Individually tracked geese follow peaks of temperature acceleration during spring migration. Oikos 121, 655–664 (2012).
Article  Google Scholar 

58.
Kölzsch, A. et al. Forecasting spring from afar? Timing of migration and predictability of phenology along different migration routes of an avian herbivore. J. Anim. Ecol. 84, 272–283 (2015).
PubMed  Article  Google Scholar 

59.
Fitzjarrald, D. R., Acevedo, O. C. & Moore, K. E. Climatic consequences of leaf presence in the eastern United States. J. Clim. 14, 598–614 (2001).
ADS  Article  Google Scholar 

60.
Burger, J. & Shisler, J. Nest-site selection of Willets in a New Jersey salt marsh. Wilson Bull. 90, 599–607 (1978).
Google Scholar 

61.
Turner, R. E. Geographic Variations in Salt Marsh Macrophyte Production: A Review http://agris.fao.org/agris-search/search/display.do?f=2012/OV/OV201207875007875.xml;US19770198479 (1976).

62.
Pezeshki, S. R. & DeLaune, R. D. A comparative study of above-ground productivity of dominant U.S. Gulf Coast marsh species. J. Veg. Sci. 2, 331–338 (1991).
Article  Google Scholar 

63.
Morris, J., Sundberg, K. & Hopkinson, C. Salt marsh primary production and its responses to relative sea level and nutrients in estuaries at plum Island, Massachusetts, and North Inlet, South Carolina, USA. Oceanography 26, 78–84 (2013).
Article  Google Scholar 

64.
Dai, T. & Wiegert, R. G. Ramet population dynamics and net aerial primary productivity of Spartina alterniflora. Ecology 77, 276–288 (1996).
Article  Google Scholar 

65.
Gallagher, J. L., Reimold, R. J., Linthurst, R. A. & Pfeiffer, W. J. Aerial production, mortality, and mineral accumulation-export dynamics in Spartina alterniflora and Juncus roemerianus plant stands in a Georgia Salt Marsh. Ecology 61, 303–312 (1980).
Article  Google Scholar 

66.
Stroud, L. M. & Cooper, A. W. Color-Infrared Aerial Photographic Interpretation and Net Primary Productivity of a Regularly-Flooded North Carolina Salt Marsh http://repository.lib.ncsu.edu/dr/handle/1840.4/1681 (1969).

67.
Reidenbaugh, T. G. Productivity of cordgrass, Spartina alterniflora, estimated from live standing crops, mortality, and leaf shedding in a Virginia salt marsh. Estuaries 6, 57–65 (1983).
Article  Google Scholar 

68.
Squiers, E. R. & Good, R. E. Seasonal changes in the productivity, caloric content, and chemical composition of a population of salt-marsh cord-grass (Spartina alterniflora). Chesap. Sci. 15, 63–71 (1974).
Article  Google Scholar 

69.
Morris, J. & Sundberg, K. Aboveground biomass data from control sites in a Spartina alterniflora-dominated salt marsh at Law’s Point, Rowley River, Plum Island Ecosystem, MA (2012).

70.
Cranford, P. J., Gordon, D. C. & Jarvis, C. M. Measurement of cordgrass, Spartina alterniflora, production in a macrotidal estuary, Bay of Fundy. Estuaries 12, 27–34 (1989).
Article  Google Scholar 

71.
Hatcher, B. G. & Mann, K. H. Above-ground production of marsh cordgrass (Spartina alterniflora) near the northern end of its range. J. Fish. Board Can. 32, 83–87 (1975).
Article  Google Scholar 

72.
Rohatgi, A. Web Plot Digitizer, V 3.9 http://arohatgi.info/WebPlotDigitizer/ (2015).

73.
Morris, J. T. & Haskin, B. A 5-yr record of aerial primary production and stand characteristics of Spartina alterniflora. Ecology 71, 2209–2217 (1990).
Article  Google Scholar 

74.
Curtin, F. Meta-analysis combining parallel and crossover trials using generalised estimating equation method. Res. Synth. Methods 8, 312–320 (2017).
PubMed  Article  PubMed Central  Google Scholar 

75.
Müller, J. & Hothorn, T. Maximally selected two-sample statistics as a new tool for the identification and assessment of habitat factors with an application to breeding-bird communities in oak forests. Eur. J. For. Res. 123, 219–228 (2004).
Article  Google Scholar 

76.
Tomkins, I. R. The Willets of Georgia and South Carolina. Wilson Bull. 77, 151–167 (1965).
Google Scholar 

77.
Morrison, R. I. G. & Ross, R. K. Atlas of Nearctic Shorebirds on the Coast of South America (Canadian Wildlife Service, Ottawa, 1989).
Google Scholar 

78.
Merchant, D. et al. Shorebird Conservation in Brazil and Delaware Bay. In North American Migratory Bird Conservation Act Annual Report 2016–2017 (2017).

79.
Alerstam, T. & Hedenström, A. The development of bird migration theory. J. Avian Biol. 29, 343–369 (1998).
Article  Google Scholar 

80.
Meltofte, H., Piersma, T., Boyd, H., Mccaffery, B. J. & Tulp, I. Y. M. Effects of climate variation on the breeding ecology of Artic shorebirds. Meddelelser Om Groenl. Biosci. 59, 45 (2007).
Google Scholar 

81.
Willson, M. F. & Womble, J. N. Vertebrate exploitation of pulsed marine prey: A review and the example of spawning herring. Rev. Fish Biol. Fish. 16, 183–200 (2006).
Article  Google Scholar 

82.
Mizrahi, D. S. & Peters, K. A. Relationships between sandpipers and horseshoe crab in Delaware Bay: A synthesis. In Biology and Conservation of Horseshoe Crabs (eds Tanacredi, J. et al.) 65–87 (Springer, Berlin, 2009).
Google Scholar 

83.
Johansson, J. & Jonzén, N. Effects of territory competition and climate change on timing of arrival to breeding grounds: A game-theory approach. Am. Nat. 179, 463–474 (2012).
PubMed  Article  Google Scholar 

84.
Verhulst, S. & Nilsson, J. -Å. The timing of birds’ breeding seasons: A review of experiments that manipulated timing of breeding. Philos. Trans. R. Soc. B Biol. Sci. 363, 399–410 (2008).
Article  Google Scholar 

85.
Hatchwell, B. J. An Experimental study of the effects of timing of breeding on the reproductive success of common guillemots (Uria aalge). J. Anim. Ecol. 60, 721–736 (1991).
Article  Google Scholar 

86.
McKinnon, L. et al. Lower predation risk for migratory birds at high latitudes. Science 327, 326–327 (2010).

87.
Ruskin, K. J. et al. Demographic analysis demonstrates systematic but independent spatial variation in abiotic and biotic stressors across 59 percent of a global species range. The Auk 134, 903–916 (2017).

88.
Karagicheva, J. et al. Seasonal time keeping in a long-distance migrating shorebird. J. Biol. Rhythms 5, 509–521 (2016).
Article  Google Scholar 

89.
Daan, S., Dijkstra, C., Drent, R. & Meijer, T. Food supply and the annual timing of avian reproduction. In Proceedings of the International Ornithological Congress vol. 19 392–407 (University of Ottawa Press, Ottawa, 1988).

90.
Krebs, C. T. & Burns, K. A. Long-term effects of an oil spill on populations of the salt-marsh crab Uca pugnax. Science 197, 484–487 (1977).
ADS  CAS  PubMed  Article  Google Scholar 

91.
Williams, R. B. & Murdoch, M. B. Potential Importance of Spartina alterniflora in Conveying Zinc, Manganese, and Iron into Estuarine Food Chains in Conveying Zinc, Manganese, and Iron into Estuarine Food Chains (Radiobiological Lab, Bureau of Commercial Fisheries, Beaufort, NC, 1969).
Google Scholar 

92.
Anthes, N. Long-distance migration timing of Tringa sandpipers adjusted to recent climate change: Capsule evidence for earlier spring migration of Tringa sandpipers after warmer winters, but no clear pattern concerning autumn migration timing. Bird Study 51, 203–211 (2004).
Article  Google Scholar 

93.
Gill, J. A. et al. Why is timing of bird migration advancing when individuals are not?. Proc. R. Soc. B Biol. Sci. 281, 20132161 (2014).
Article  Google Scholar 

94.
Cotton, P. A. Avian migration phenology and global climate change. Proc. Natl. Acad. Sci. 100, 12219–12222 (2003).
ADS  CAS  PubMed  Article  Google Scholar 

95.
Crozier, L. G. et al. Potential responses to climate change in organisms with complex life histories: Evolution and plasticity in Pacific salmon. Evol. Appl. 1, 252–270 (2008).
CAS  PubMed  PubMed Central  Article  Google Scholar  More

1.
Tyack, P. L. & Clark, C. W. Communication and acoustic behaviour of dolphins and whales. In Hearing by Whales and Dolphins (eds Au, W. L. et al.) 156–224 (Springer, New York, 2000).
Google Scholar 
2.
Au, W. W. L. The Sonar of Dolphins (Springer, Berlin, 1993).
Google Scholar 

3.
Filatova, O. A. et al. Call diversity in the North Pacific killer whale populations: implications for dialect evolution and population history. Anim. Behav. 83, 595–603. https://doi.org/10.1016/j.anbehav.2011.12.013 (2012).
Article  Google Scholar 

4.
Ding, W., Wuersig, B. & Evans, W. E. Whistles of bottlenose dolphins: comparisons among populations. Aquat. Mamm. 21, 65–77 (1995).
Google Scholar 

5.
Caldwell, M. C. & Caldwell, D. D. Statistical evidence for individual signature whistles in Pacific whitesided dolphin Lagenorhynchus obliquidens. Cetology 3, 1–9 (1971).
Google Scholar 

6.
Erbe, C. et al. Review of underwater and in-air sounds emitted by Australian and Antarctic marine mammals. Acoust. Aust. 45, 179–241. https://doi.org/10.1007/s40857-017-0101-z (2017).
Article  Google Scholar 

7.
Sayigh, L. S., Esch, H. C., Wells, R. S. & Janik, V. M. Facts about signature whistles of bottlenose dolphins Tursiops truncatus. Anim. Behav. 74, 1631–1642. https://doi.org/10.1016/j.anbehav.2007.02.018 (2007).
Article  Google Scholar 

8.
Herzing, D. L. Clicks, whistles and pulses: passive and active signal use in dolphin communication. Acta Astronaut. 105, 534–537. https://doi.org/10.1016/j.actaastro.2014.07.003 (2014).
ADS  Article  Google Scholar 

9.
Ford, J. K. B. Acoustic behaviour of resident killer whales (Orcinus orca) off Vancouver Island, British Columbia. Can. J. Zool. 67, 727–745. https://doi.org/10.1139/z89-105 (1989).
Article  Google Scholar 

10.
Miller, P. J. O., Shapiro, A. D., Tyack, P. L. & Solow, A. R. Call-type matching in vocal exchanges of free-ranging resident killer whales, Orcinus orca. Anim. Behav. 67, 1099–1107. https://doi.org/10.1016/j.anbehav.2003.06.017 (2004).
Article  Google Scholar 

11.
Herzing, D. L. Vocalizations and associated underwater behavior of free-ranging Atlantic spotted dolphins, Stenella frontalis and bottlenose dolphins, Tursiops truncatus. Aquat. Mamm. 22, 61–79 (1996).
Google Scholar 

12.
Weilgart, L. & Whitehead, H. Coda communication by sperm whales (Physeter macrocephalus) off the Galápagos Islands. Can. J. Zool. 71, 744–752. https://doi.org/10.1139/z93-098 (1993).
Article  Google Scholar 

13.
Dawson, S. M. Clicks and communication: the behavioural and social contexts of hector’s dolphin vocalizations. Ethology 88, 265–276. https://doi.org/10.1111/j.1439-0310.1991.tb00281.x (1991).
Article  Google Scholar 

14.
Sørensen, P. M. et al. Click communication in wild harbour porpoises (Phocoena phocoena). Sci. Rep. 8, 9702. https://doi.org/10.1038/s41598-018-28022-8 (2018).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

15.
Karlsen, J. et al. Summer vocalisations of adult male white whales (Delphinapterus leucas) in Svalbard, Norway. Polar Biol. 25, 808–817. https://doi.org/10.1007/s00300-002-0415-6 (2002).
Article  Google Scholar 

16.
Murray, S. O., Mercado, E. & Roitblat, H. L. Characterizing the graded structure of false killer whale (Pseudorca crassidens) vocalizations. J. Acoust. Soc. Am. 104, 1679–1688. https://doi.org/10.1121/1.424380 (1998).
ADS  CAS  Article  PubMed  Google Scholar 

17.
Quick, N., Callahan, H. & Read, A. J. Two-component calls in short-finned pilot whales (Globicephala macrorhynchus). Mar. Mamm. Sci. 34, 155–168. https://doi.org/10.1111/mms.12452 (2018).
Article  Google Scholar 

18.
Aplan, J. D., Melillo-Sweeting, K. & Reiss, D. Biphonal calls in Atlantic spotted dolphins (Stenella frontalis): bitonal and burst-pulse whistles. Bioacoustics 27, 145–164. https://doi.org/10.1080/09524622.2017.1300105 (2018).
Article  Google Scholar 

19.
Vester, H., Hallerberg, S., Timme, M. & Hammerschmidt, K. Vocal repertoire of long-finned pilot whales (Globicephala melas) in northern Norway. J. Acoust. Soc. Am. 141, 4289–4299. https://doi.org/10.1121/1.4983685 (2017).
ADS  Article  PubMed  Google Scholar 

20.
Ford, J. K. B. A catalogue of underwater calls produced by killer whales (Orcinus orca) in British Columbia. Can. Data Rep. Fish. Aquat. Sci. 633, 165 (1987).
Google Scholar 

21.
Wellard, R., Pitman, R. L., Durban, J. & Erbe, C. Cold call: the acoustic repertoire of Ross Sea killer whales (Orcinus orca, Type C) in McMurdo Sound, Antarctica. R. Soc. Open Sci. 7, 191228. https://doi.org/10.1098/rsos.191228 (2020).
ADS  Article  PubMed  PubMed Central  Google Scholar 

22.
Steiner, W. W. Species-specific differences in pure tonal whistle vocalizations of five western North Atlantic dolphin species. Behav. Ecol. Sociobiol. 9, 241–246. https://doi.org/10.1007/bf00299878 (1981).
Article  Google Scholar 

23.
Tyack, P. L. Development and social functions of signature whistles in bottlenose dolphins Tursiops truncatus. Bioacoustics 8, 21–46. https://doi.org/10.1080/09524622.1997.9753352 (1997).
Article  Google Scholar 

24.
Mishima, Y. et al. Individuality embedded in the isolation calls of captive beluga whales (Delphinapterus leucas). Zool. Lett. 1, 27. https://doi.org/10.1186/s40851-015-0028-x (2015).
Article  Google Scholar 

25.
Azzolin, M., Papale, E., Lammers, M. O., Gannier, A. & Giacoma, C. Geographic variation of whistles of the striped dolphin (Stenella coeruleoalba) within the Mediterranean Sea. J. Acoust. Soc. Am. 134, 694–705. https://doi.org/10.1121/1.4808329 (2013).
ADS  Article  PubMed  Google Scholar 

26.
Papale, E., Gamba, M., Perez-Gil, M., Martin, V. M. & Giacoma, C. Dolphins adjust species-specific frequency parameters to compensate for increasing background noise. PLoS ONE 10, e0121711. https://doi.org/10.1371/journal.pone.0121711 (2015).
CAS  Article  PubMed  PubMed Central  Google Scholar 

27.
Fouda, L. et al. Dolphins simplify their vocal calls in response to increased ambient noise. Biol. Lett. 14, 20180484. https://doi.org/10.1098/rsbl.2018.0484 (2018).
Article  PubMed  PubMed Central  Google Scholar 

28.
Oremus, M. et al. Worldwide mitochondrial DNA diversity and phylogeography of pilot whales (Globicephala spp.). Biol. J. Linnean Soc. 98, 729–744. https://doi.org/10.1111/j.1095-8312.2009.01325.x (2009).
Article  Google Scholar 

29.
Olson, P. A. Pilot Whales: Globicephala melas and G macrorhynchus. In Encyclopedia of Marine Mammals (eds Perrin, W. F. et al.) 847–852 (Academic Press, Cambridge, 2009).
Google Scholar 

30.
Bloch, D. & Lastein, L. Morphometric segregation of long-finned pilot whales in eastern and western North Atlantic. Ophelia 38, 55–68. https://doi.org/10.1080/00785326.1993.10429924 (1993).
Article  Google Scholar 

31.
Rogan, E. et al. Distribution, abundance and habitat use of deep diving cetaceans in the North-East Atlantic. Deep Sea Res. Part II 141, 8–19. https://doi.org/10.1016/j.dsr2.2017.03.015 (2017).
Article  Google Scholar 

32.
Kemper, C. et al. Cetacean captures, strandings and mortalities in South Australia 1881–2000, with special reference to human interactions. Aust. Mammal. 27, 37–47. https://doi.org/10.1071/AM05037 (2005).
Article  Google Scholar 

33.
Minton, G., Reeves, R. & Braulik, G. The IUCN Red List of Threatened Species. (2018).

34.
Hamilton, V., Evans, K., Raymond, B., Betty, E. & Hindell, M. A. Spatial variability in responses to environmental conditions in Southern Hemisphere long-finned pilot whales. Mar. Ecol. Prog. Ser. 629, 207–218. https://doi.org/10.3354/meps13109 (2019).
ADS  Article  Google Scholar 

35.
Nemiroff, L. & Whitehead, H. Structural characteristics of pulsed calls of long-finned pilot whales Globicephala melas. Bioacoustics 19, 67–92. https://doi.org/10.1080/09524622.2009.9753615 (2009).
Article  Google Scholar 

36.
Zwamborn, E. M. J. & Whitehead, H. Repeated call sequences and behavioural context in long-finned pilot whales off Cape Breton, Nova Scotia, Canada. Bioacoustics 26, 169–183. https://doi.org/10.1080/09524622.2016.1233457 (2017).
Article  Google Scholar 

37.
Visser, F. et al. Vocal foragers and silent crowds: context-dependent vocal variation in Northeast Atlantic long-finned pilot whales. Behav. Ecol. Sociobiol. 71, 170. https://doi.org/10.1007/s00265-017-2397-y (2017).
Article  PubMed  PubMed Central  Google Scholar 

38.
Erbe, C. Underwater passive acoustic monitoring and noise impacts on marine fauna- a workshop report. Acoust. Aust. 41, 211–217 (2013).
Google Scholar 

39.
Watkins, W. A. The Harmonic Interval: Fact or Artefact in Spectral Analysis of Pulse Trains 15–43 (Pergamon Press, Oxford, 1967).
Google Scholar 

40.
Taruski, A. G. The whistle repertoire of the North Atlantic pilot whale (Globicephala melaena) and its relationship to behavior and environment. In Behavior of Marine Animals: Current Perspectives in Research (eds Winn, H. E. & Olla, B. L.) 345–368 (Springer US, New York, 1979).
Google Scholar 

41.
Rendell, L. E., Matthews, J. N., Gill, A., Gordon, J. C. D. & Macdonald, D. W. Quantitative analysis of tonal calls from five odontocete species, examining interspecific and intraspecific variation. J. Zool. 249, 403–410. https://doi.org/10.1111/j.1469-7998.1999.tb01209.x (1999).
Article  Google Scholar 

42.
Lesage, V., Barrette, C., Kingsley, M. C. S. & Sjare, B. The effect of vessel noise on the vocal behaviour of belugas in the St. Lawrence River Estuary, Canada. Mar. Mamm. Sci. 15, 65–84. https://doi.org/10.1111/j.1748-7692.1999.tb00782.x (1999).
Article  Google Scholar 

43.
Ding, W., Würsig, B. & Evans, W. E. Comparison of whistles among seven odontocete species. In Sensory Systems of Marine Mammals (eds Kastelein, R. A. et al.) 299–323 (DeSpil Publishers, Woerden, 1995).
Google Scholar 

44.
Baron, S. C., Martinez, A., Garrison, L. P. & Keith, E. O. Differences in acoustic signals from Delphinids in the western North Atlantic and northern Gulf of Mexico. Mar. Mamm. Sci. 24, 42–56. https://doi.org/10.1111/j.1748-7692.2007.00168.x (2008).
Article  Google Scholar 

45.
May-Collado, L. J. & Wartzok, D. A comparison of bottlenose dolphin whistles in the Atlantic Ocean: factors promoting whistle variation. J. Mammal. 89, 1229–1240. https://doi.org/10.1644/07-mamm-a-310.1 (2008).
Article  Google Scholar 

46.
Oswald, J., Rankin, S. & Barlow, J. To whistle or not to whistle? Geographic variation in the whistling behaviour of small odontocetes. Aquat. Mamm. 34, 288–302. https://doi.org/10.1578/AM.34.3.2008.288 (2008).
Article  Google Scholar 

47.
Ward-Geiger, L. I., Silber, G. K., Baumstark, R. D. & Pulfer, T. L. Characterization of ship traffic in right whale critical habitat. Coastal Manag. 33, 263–278. https://doi.org/10.1080/08920750590951965 (2005).
Article  Google Scholar 

48.
Weilgart, L. S. & Whitehead, H. Vocalizations of the North Atlantic pilot whale (Globicephala melas) as related to behavioral contexts. Behav. Ecol. Sociobiol. 26, 399–402. https://doi.org/10.1007/bf00170896 (1990).
Article  Google Scholar 

49.
Cato, D. H. & McCauley, R. D. Australian research in ambient sea noise. Acoust. Aust. 30, 1–13 (2009).
Google Scholar 

50.
Busnel, R. G. & Dziedzic, A. Acoustic signals of pilot whale Globicephala melaena and of the porpoises Delphinus delphis and Phocoena phocoena. In Whales, Dolphins, and Porpoise (ed. Norris, K. S.) 604–648 (University of California Press, Berkeley, 1966).
Google Scholar 

51.
Matthews, J. N., Rendell, L. E., Gordon, J. C. D. & Macdonald, D. W. A review of frequency and time parameters of cetacean tonal calls. Bioacoustics 10, 47–71. https://doi.org/10.1080/09524622.1999.9753418 (1999).
Article  Google Scholar 

52.
Davies, J. L. The Southern Form of the Pilot Whale. J. Mammal. 41, 29–34. https://doi.org/10.2307/1376514 (1960).
Article  Google Scholar 

53.
Scheer, M. Call vocalisations recorded among short-finned pilot whales (Globicephala macrorhynchus) off Tenerife, Canary Islands. Aquat. Mamm. 39, 306–313. https://doi.org/10.1578/AM.39.3.2013.306 (2013).
Article  Google Scholar 

54.
Wellard, R., Erbe, C., Fouda, L. & Blewitt, M. Vocalisations of killer whales (Orcinus orca) in the Bremer Canyon, Western Australia. PLoS ONE 10, e0136535. https://doi.org/10.1371/journal.pone.0136535 (2015).
CAS  Article  PubMed  PubMed Central  Google Scholar 

55.
Curé, C. et al. Pilot whales attracted to killer whale sounds: acoustically-mediated interspecific interactions in cetaceans. PLoS ONE 7, e52201. https://doi.org/10.1371/journal.pone.0052201 (2012).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

56.
Stenersen, J. & Simila, T. Norwegian Killer Whales (Tringa, Wales, 2004).
Google Scholar 

57.
De Stephanis, R. et al. Mobbing-like behavior by pilot whales towards killer whales: a response to resource competition or perceived predation risk?. Acta Ethologica 18, 69–78. https://doi.org/10.1007/s10211-014-0189-1 (2015).
Article  Google Scholar 

58.
Alves, A. et al. Vocal matching of naval sonar signals by long-finned pilot whales (Globicephala melas). Mar. Mamm. Sci. 30, 1248–1257. https://doi.org/10.1111/mms.12099 (2014).
Article  Google Scholar 

59.
Visser, I. N. et al. First record of predation on false killer whales (Pseudorca crassidens) by killer whales (Orcinus orca). Aquat. Mamm. 36, 195–204 (2010).
Article  Google Scholar 

60.
Filatova, O. A., Fedutin, I. D., Nagaylik, M. M., Burdin, A. M. & Hoyt, E. Usage of monophonic and biphonic calls by free-ranging resident killer whales (Orcinus orca) in Kamchatka, Russian Far East. Acta Ethologica 12, 37–44. https://doi.org/10.1007/s10211-009-0056-7 (2009).
Article  Google Scholar 

61.
Hall, M. L. A review of hypotheses for the functions of avian duetting. Behav. Ecol. Sociobiol. 55, 415–430. https://doi.org/10.1007/s00265-003-0741-x (2004).
Article  Google Scholar 

62.
Robinson, A. The biological significance of bird song in Australia. Emu 48, 291–315. https://doi.org/10.1071/MU948291 (1949).
Article  Google Scholar 

63.
Levin, R. N. Song behaviour and reproductive strategies in a duetting wren, Thryothorus nigricapillus: I Removal experiments. Anim. Behav. 52, 1093–1106. https://doi.org/10.1006/anbe.1996.0257 (1996).
Article  Google Scholar 

64.
Hall, M. L. A Review of Vocal Duetting in Birds. Advances in the Study of Behavior 67–121 (Academic Press, Cambridge, 2009).
Google Scholar 

65.
Constantine, R., Brunton, D. H. & Dennis, T. Dolphin-watching tour boats change bottlenose dolphin (Tursiops truncatus) behaviour. Biol. Conserv. 117, 299–307. https://doi.org/10.1016/j.biocon.2003.12.009 (2004).
Article  Google Scholar 

66.
Wellard, R. et al. Killer whale (Orcinus orca) predation on beaked whales (Mesoplodon spp.) in the Bremer Sub-Basin, Western Australia. PLoS ONE 11, e0166670. https://doi.org/10.1371/journal.pone.0166670 (2016).
CAS  Article  PubMed  PubMed Central  Google Scholar 

67.
Exon, N. F., Hill, P. J., Mitchell, C. & Post, A. Nature and origin of the submarine Albany canyons off southwest Australia. Aust. J. Earth Sci. 52, 101–115. https://doi.org/10.1080/08120090500100036 (2005).
Article  Google Scholar 

68.
Salgado-Kent, C., Parnum, I., Wellard, R., Erbe, C. & Fouda, L. Habitat preferences and distribution of killer whales (Orcinus orca) in the Bremer Sub-Basin, Australia. Report CMST 2017–15 by the Centre for Marine Science and Technology, Curtin University, for the National Environmental Science Programme; Perth, Australia (2017).

69.
Bronshtein, I. N., Semendyayev, K. A., Musiol, G. & Muhlig, H. Handbook of Mathematics 6th edn, 129–268 (Springer, New York, 2015).
Google Scholar 

70.
Fleiss, J. L. & Cohen, J. The equivalence of weighted kappa and the intraclass correlation coefficient as measures of reliability. Educ. Psychol. Meas. 33, 613–619. https://doi.org/10.1177/001316447303300309 (1973).
Article  Google Scholar 

71.
Landis, J. R. & Koch, G. G. The measurement of observer agreement for categorical data. Biometrics 33, 159–174. https://doi.org/10.2307/2529310 (1977).
CAS  Article  MATH  Google Scholar  More

1.
Garroway, C. J. et al. Fine-scale genetic structure in a wild bird population: The role of limited disperal and environmentally based selection as causal factors. Evolution 67, 3488–3500. https://doi.org/10.1111/evo.12121 (2013).
CAS  Article  PubMed  Google Scholar 
2.
Reudink, M. W. et al. Linking isotopes and panmixia: High within-colony variation in feather δ2H, δ13C, and δ15N across the range of the American White Pelican. PLoS ONE 11, e0150810. https://doi.org/10.1371/journal.pone.0150810 (2016).
CAS  Article  PubMed  PubMed Central  Google Scholar 

3.
Ward, R. D., Skibinski, D. O. & Woodwark, M. Protein heterozygosity, protein structure, and taxonomic differentiation. In Evolutionary Biology, Vol. 26 (eds Hecht M.K., Wallace B., & Macintyre R.J.) 73–159 (Springer, New York, 1992).

4.
White, T. A., Fotherby, H. A., Stephens, P. A. & Hoelzel, A. R. Genetic panmixia and demographic dependence across the North Atlantic in the deep-sea fish, blue hake (Antimora rostrata). Heredity 106, 690–699. https://doi.org/10.1038/hdy.2010.108 (2011).
CAS  Article  PubMed  Google Scholar 

5.
Mayr, E. Animal Species and Evolution. (Belknap Press of Harvard University Press, Cambridge, 1963).

6.
Frankham, R. Do island populations have less genetic variation than mainland populations?. Heredity 78, 311–327. https://doi.org/10.1038/hdy.1997.46 (1997).
Article  PubMed  Google Scholar 

7.
Küpper, C. et al. High gene flow on a continental scale in the polyandrous Kentish plover Charadrius alexandrinus. Mol. Ecol. 21, 5864–5879 (2012).
Article  Google Scholar 

8.
Friesen, V. L., Burg, T. M. & McCoy, K. D. Mechanisms of population differentiation in seabirds. Mol. Ecol. 16, 1765–1785. https://doi.org/10.1111/j.1365-294X.2006.03197.x (2007).
CAS  Article  PubMed  Google Scholar 

9.
Ibarguchi, G., Gaston, A. J. & Friesen, V. L. Philopatry, morphological divergence, and kin groups: Structuring in thick-billed murres Uria lomvia within a colony in Arctic Canada. J. Avian Biol. 42, 134–150. https://doi.org/10.1111/j.1600-048X.2010.05023.x (2011).
Article  Google Scholar 

10.
Griesser, M. Referential calls signal predator behavior in a group-living bird species. Curr. Biol. 18, 69–73. https://doi.org/10.1016/j.cub.2007.11.069 (2008).
CAS  Article  PubMed  Google Scholar 

11.
Wright, S. Isolation by distance. Genetics 28, 114–138 (1943).
CAS  PubMed  PubMed Central  Google Scholar 

12.
Innes, R. J. et al. Genetic relatedness and spatial associations of dusky-footed woodrats (Neotoma fuscipes). J. Mammal. 93, 439–446. https://doi.org/10.1644/11-mamm-a-171.1 (2012).
Article  Google Scholar 

13.
Foerster, K., Valcu, M., Johnsen, A. & Kempenaers, B. A spatial genetic structure and effects of relatedness on mate choice in a wild bird population. Mol. Ecol. 15, 4555–4567. https://doi.org/10.1111/j.1365-294X.2006.03091.x (2006).
CAS  Article  PubMed  Google Scholar 

14.
Planes, S. & Fauvelot, C. Isolation by distance and vicariance drive genetic structure of a coral reef fish in the Pacific Ocean. Evolution 56, 378–399. https://doi.org/10.1111/j.0014-3820.2002.tb01348.x (2002).
CAS  Article  PubMed  Google Scholar 

15.
Hendry, A. P. & Day, T. Population structure attributable to reproductive time: Isolation by time and adaptation by time. Mol. Ecol. 14, 901–916. https://doi.org/10.1111/j.1365-294X.2005.02480.x (2005).
CAS  Article  PubMed  Google Scholar 

16.
Ribolli, J. et al. Isolation-by-time population structure in potamodromous Dourado Salminus brasiliensis in southern Brazil. Conserv. Genet. 18, 67–76. https://doi.org/10.1007/s10592-016-0882-x (2017).
Article  Google Scholar 

17.
Weis, A. E. & Kossler, T. M. Genetic variation in flowering time induces phenological assortative mating: Quantitative genetic methods applied to Brassica rapa. Am. J. Bot. 91, 825–836. https://doi.org/10.3732/ajb.91.6.825 (2004).
Article  PubMed  Google Scholar 

18.
Coulson, M., Bradbury, I. & Bentzen, P. Temporal genetic differentiation: Continuous v. discontinuous spawning runs in anadromous rainbow smelt Osmerus mordax (Mitchill). J. Fish Biol. 69, 209–216 (2006).
Article  Google Scholar 

19.
Woody, C. A., Olsen, J., Reynolds, J. & Bentzen, P. Temporal variation in phenotypic and genotypic traits in two sockeye salmon populations, Tustumena Lake, Alaska. Trans. Am. Fish. Soc. 129, 1031–1043 (2000).
Article  Google Scholar 

20.
Cooley, J. R., Simon, C. & Marshall, D. C. Temporal separation and speciation in periodical cicadas. Bioscience 53, 151–157. https://doi.org/10.1641/0006-3568(2003)053[0151:TSASIP]2.0.CO;2 (2003).
Article  Google Scholar 

21.
Rolshausen, G., Hobson, K. A. & Schaefer, H. M. Spring arrival along a migratory divide of sympatric blackcaps (Sylvia atricapilla). Oecologia 162, 175–183. https://doi.org/10.1007/s00442-009-1445-3 (2009).
ADS  Article  PubMed  Google Scholar 

22.
Friesen, V. L. et al. Sympatric speciation by allochrony in a seabird. Proc. Natl. Acad. Sci. U.S.A. 107, 18589–18594 (2007).
ADS  Article  Google Scholar 

23.
Braga-Silva, A. & Galetti, P. M. Evidence of isolation by time in freshwater migratory fish Prochilodus costatus (Characiformes, Prochilodontidae). Hydrobiologia 765, 159–167. https://doi.org/10.1007/s10750-015-2409-8 (2016).
Article  Google Scholar 

24.
Schreiber, E. & Burger, J. Biology of Marine Birds (CRC Press, Boca Raton, 2001).
Google Scholar 

25.
Lawrence, H. A., Lyver, P. O. B. & Gleeson, D. M. Genetic panmixia in New Zealand’s Grey-faced Petrel: Implications for conservation and restoration. Emu 114, 249–258. https://doi.org/10.1071/MU13078 (2014).
Article  Google Scholar 

26.
Cristofari, R. et al. Spatial heterogeneity as a genetic mixing mechanism in highly philopatric colonial seabirds. PLoS ONE 10, e0117981. https://doi.org/10.1371/journal.pone.0117981 (2015).
CAS  Article  PubMed  PubMed Central  Google Scholar 

27.
Avise, J. C., Nelson, W. S., Bowen, B. W. & Walker, D. Phylogeography of colonially nesting seabirds, with special reference to global matrilineal patterns in the sooty tern (Sterna fuscata). Mol. Ecol. 9, 1783–1792 (2000).
CAS  Article  Google Scholar 

28.
Votier, S. C. & Sherley, R. B. Seabirds. Curr. Biol. 27, R448–R450. https://doi.org/10.1016/j.cub.2017.01.042 (2017).
CAS  Article  PubMed  Google Scholar 

29.
Hughes, B. J., Martin, G. R., Giles, A. D. & Reynolds, S. J. Long-term population trends of Sooty Terns Onychoprion fuscatus: Implications for conservation status. Popul. Ecol. 59, 213–224. https://doi.org/10.1007/s10144-017-0588-z (2017).
Article  Google Scholar 

30.
Reynolds, S. J. et al. Long-term dietary shift and population decline of a pelagic seabird—A health check on the tropical Atlantic?. Glob. Change Biol. 25, 1383–1394. https://doi.org/10.1111/gcb.14560 (2019).
ADS  Article  Google Scholar 

31.
Schreiber, E. et al. In Birds of North America No. 665 (eds A Poole & F Gill) 1–32 (American Ornithologists’ Union, Washington, DC, 2002).

32.
Maxwell, S. M. & Morgan, L. E. Foraging of seabirds on pelagic fishes: Implications for management of pelagic marine protected areas. Mar. Ecol. Prog. Ser. 481, 289–303 (2013).
ADS  Article  Google Scholar 

33.
Ashmole, N. P. The biology of the Wideawake or Sooty Tern Sterna fuscata on Ascension Island. Ibis 103b, 297–351 (1963).
Article  Google Scholar 

34.
Hughes, B. J., Martin, G. R. & Reynolds, S. J. Cats and seabirds: Effects of feral Domestic Cat Felis silvestris catus eradication on the population of Sooty Terns Onychoprion fuscata on Ascension Island, South Atlantic. Ibis 150, 122–131. https://doi.org/10.1111/j.1474-919X.2008.00838.x (2008).
Article  Google Scholar 

35.
ArcGIS Desktop: Release 10.2 (Environmental Systems Research Institute, Redlands, CA, USA, 2013).

36.
Garrett, L. J., Dawson, D. A., Horsburgh, G. J. & Reynolds, S. J. A multiplex marker set for microsatellite typing and sexing of sooty terns Onychoprion fuscatus. BMC Res. Notes 10, 756 (2017).
Article  Google Scholar 

37.
Dawson, D. A. Genomic analysis of passerine birds using conserved microsatellite loci. PhD thesis, University of Sheffield, UK, (2007).

38.
Dawson, D. A., dos Remedios, N. & Horsburgh, G. J. A new marker based on the avian spindlin gene that is able to sex most birds, including species problematic to sex with CHD markers. Zoo Biol. 35, 533–545. https://doi.org/10.1002/zoo.21326 (2016).
CAS  Article  PubMed  Google Scholar 

39.
Rousset, F. GENEPOP ’007: A complete re-implementation of the genepop software for Windows and Linux. Mol. Ecol. Resour. 8, 103–106. https://doi.org/10.1111/j.1471-8286.2007.01931.x (2008).
Article  PubMed  Google Scholar 

40.
Anderson, C. A. et al. Data quality control in genetic case-control association studies. Nat. Protoc. 5, 1564–1573. https://doi.org/10.1038/nprot.2010.116 (2010).
CAS  Article  PubMed  PubMed Central  Google Scholar 

41.
de Jager, D., Swarts, P., Harper, C. & Bloomer, P. Friends and family: A software program for identification of unrelated individuals from molecular marker data. Mol. Ecol. Resour. 17, e225–e233. https://doi.org/10.1111/1755-0998.12691 (2017).
Article  PubMed  Google Scholar 

42.
Verhoeven, K. J. F., Simonsen, K. L. & McIntyre, L. M. Implementing false discovery rate control: Increasing your power. Oikos 108, 643–647. https://doi.org/10.1111/j.0030-1299.2005.13727.x (2005).
Article  Google Scholar 

43.
Kalinowski, S. T., Taper, M. L. & Marshall, T. C. Revising how the computer program Cervus accommodates genotyping error increases success in paternity assignment. Mol. Ecol. 16, 1099–1106. https://doi.org/10.1111/j.1365-294X.2007.03089.x (2007).
Article  PubMed  Google Scholar 

44.
Torati, L. S. et al. Genetic diversity and structure in Arapaima gigas populations from Amazon and Araguaia-Tocantins river basins. BMC Genet. 20, 13. https://doi.org/10.1186/s12863-018-0711-y (2019).
Article  PubMed  PubMed Central  Google Scholar 

45.
Bonin, A. et al. How to track and assess genotyping errors in population genetics studies. Mol. Ecol. 13, 3261–3273. https://doi.org/10.1111/j.1365-294X.2004.02346.x (2004).
CAS  Article  PubMed  Google Scholar 

46.
Johnson, P. C. D. & Haydon, D. T. Software for quantifying and simulating microsatellite genotyping error. Bioinform. Biol. Insights 1, 71–75 (2007).
Article  Google Scholar 

47.
Pritchard, J. K., Stephens, M. & Donnelly, P. Inference of population structure using multilocus genotype data. Genetics 155, 945–959 (2000).
CAS  PubMed  PubMed Central  Google Scholar 

48.
Evanno, G., Regnaut, S. & Goudet, J. Detecting the number of clusters of individuals using the software structure: A simulation study. Mol. Ecol. 14, 2611–2620. https://doi.org/10.1111/j.1365-294X.2005.02553.x (2005).
CAS  Article  PubMed  Google Scholar 

49.
Earl, D. A. & von Holdt, B. M. Structure harvester: A website and program for visualizing Structure output and implementing the Evanno method. Conserv. Genet. Resour. 4, 359–361. https://doi.org/10.1007/s12686-011-9548-7 (2012).
Article  Google Scholar 

50.
Pew, J., Muir, P. H., Wang, J. & Frasier, T. R. Related: An R package for analysing pairwise relatedness from codominant molecular markers. Mol. Ecol. Resour. 15, 557–561. https://doi.org/10.1111/1755-0998.12323 (2015).
Article  PubMed  Google Scholar 

51.
Wang, J. An estimator for pairwise relatedness using molecular markers. Genetics 160, 1203–1215 (2002).
CAS  PubMed  PubMed Central  Google Scholar 

52.
Ritland, K. Estimators for pairwise relatedness and individual inbreeding coefficients. Genet. Res. 67, 175–185. https://doi.org/10.1017/S0016672300033620 (1996).
Article  Google Scholar 

53.
Peakall, R. & Smouse, P. E. GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research—An update. Bioinformatics 28, 2537–2539. https://doi.org/10.1093/bioinformatics/bts460 (2012).
CAS  Article  PubMed  PubMed Central  Google Scholar 

54.
Meirmans, P. G. & Hedrick, P. W. Assessing population structure: FST and related measures. Mol. Ecol. Resour. 11, 5–18. https://doi.org/10.1111/j.1755-0998.2010.02927.x (2011).
Article  PubMed  Google Scholar 

55.
Peakall, R. & Smouse, P. E. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes 6, 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x (2006).
Article  Google Scholar 

56.
Smouse, P. E., Peakall, R. O. D. & Gonzales, E. V. A. A heterogeneity test for fine-scale genetic structure. Mol. Ecol. 17, 3389–3400. https://doi.org/10.1111/j.1365-294X.2008.03839.x (2008).
Article  PubMed  Google Scholar 

57.
Banks, S. C. & Peakall, R. O. D. Genetic spatial autocorrelation can readily detect sex-biased dispersal. Mol. Ecol. 21, 2092–2105. https://doi.org/10.1111/j.1365-294X.2012.05485.x (2012).
Article  PubMed  Google Scholar 

58.
Jacob, G., Prévot, A.-C. & Baudry, E. Feral Pigeons (Columba livia) prefer genetically similar mates despite inbreeding depression. PLoS ONE 11, e0162451. https://doi.org/10.1371/journal.pone.0162451 (2016).
CAS  Article  PubMed  PubMed Central  Google Scholar 

59.
Double, M. C., Peakall, R., Beck, N. R. & Cockburn, A. Dispersal, philopatry, and infidelity: Dissecting local genetic structure in superb fairy-wren (Malurus cyaneus). Evolution 59, 625–635. https://doi.org/10.1111/j.0014-3820.2005.tb01021.x (2005).
CAS  Article  PubMed  Google Scholar 

60.
R Core Team. R: A language and environment for statistical computing. http://www.R-project.org/ (2019).

61.
rcompanion: Functions to support extension education program evaluation (2017).

62.
Bicknell, A. W. J. et al. Population genetic structure and long-distance dispersal among seabird populations: Implications for colony persistence. Mol. Ecol. 21, 2863–2876. https://doi.org/10.1111/j.1365-294X.2012.05558.x (2012).
CAS  Article  PubMed  Google Scholar 

63.
Palestis, B. G. The role of behaviour in tern conservation. Curr. Zool. 60, 500–514 (2014).
Article  Google Scholar 

64.
Lebreton, J. D., Hines, J. E., Pradel, R., Nichols, J. D. & Spendelow, J. A. Estimation by capture-recapture of recruitment and dispersal over several sites. Oikos 101, 253–264. https://doi.org/10.1034/j.1600-0706.2003.11848.x (2003).
Article  Google Scholar 

65.
Bicknell, A. W. J. et al. Intercolony movement of pre-breeding seabirds over oceanic scales: Implications of cryptic age-classes for conservation and metapopulation dynamics. Divers. Distrib. 20, 160–168. https://doi.org/10.1111/ddi.12137 (2014).
Article  Google Scholar 

66.
Hughes, B. J., Martin, G. R. & Reynolds, S. J. Sooty Terns Onychoprion fuscatus on Ascension Island in the south Atlantic are a reproductively isolated population. Revista Brasileira de Ornitologia 18, 194–198 (2010).
Google Scholar 

67.
Robertson, W. B. Jr. Transatlantic migration of juvenile sooty terns. Nature 223, 632–634 (1969).
ADS  Article  Google Scholar 

68.
Peck, D. R. & Congdon, B. C. Reconciling historical processes and population structure in the sooty tern Sterna fuscata. J. Avian Biol. 35, 327–335 (2004).
Article  Google Scholar 

69.
Conradt, L. & Roper, T. J. Deciding group movements: Where and when to go. Behav. Proc. 84, 675–677. https://doi.org/10.1016/j.beproc.2010.03.005 (2010).
Article  Google Scholar 

70.
Sonsthagen, S. A., Talbot, S. L., Lanctot, R. B. & McCracken, K. G. Do common eiders nest in kin groups? Microgeographic genetic structure in a philopatric sea duck. Mol. Ecol. 19, 647–657. https://doi.org/10.1111/j.1365-294X.2009.04495.x (2010).
Article  PubMed  Google Scholar 

71.
Hatchwell, B. J. Cryptic kin selection: Kin structure in vertebrate populations and opportunities for kin-directed cooperation. Ethology 116, 203–216. https://doi.org/10.1111/j.1439-0310.2009.01732.x (2010).
Article  Google Scholar 

72.
Péron, G. et al. Capture–recapture models with heterogeneity to study survival senescence in the wild. Oikos 119, 524–532. https://doi.org/10.1111/j.1600-1706.2009.17882.x (2010).
Article  Google Scholar 

73.
Prince, P. A., Rothery, P., Croxall, J. P. & Wood, A. G. Population dynamics of Black-browed and Grey-headed Albatrosses Diomedea melanophris and D. chrysostoma at Bird Island, South Georgia. Ibis 136, 50–71. https://doi.org/10.1111/j.1474-919X.1994.tb08131.x (1994).
Article  Google Scholar 

74.
Monteiro, L. R. & Furness, R. W. Speciation through temporal segregation of Madeiran storm petrel (Oceanodroma castro) populations in the Azores?. Philos. Trans. R. Soc. Lond. B Biol. Sci. 353, 945–953. https://doi.org/10.1098/rstb.1998.0259 (1998).
Article  PubMed Central  Google Scholar 

75.
Dobson, F. S., Becker, P. H., Arnaud, C. M., Bouwhuis, S. & Charmantier, A. Plasticity results in delayed breeding in a long-distant migrant seabird. Ecol. Evol. 7, 3100–3109. https://doi.org/10.1002/ece3.2777 (2017).
Article  PubMed  PubMed Central  Google Scholar 

76.
Casagrande, S., Dell’Omo, G., Costantini, D. & Tagliavini, J. Genetic differences between early-and late-breeding Eurasian kestrels. Evol. Ecol. Res. 8, 1029–1038 (2006).
Google Scholar 

77.
Danchin, É., Giraldeau, L.-A., Valone, T. J. & Wagner, R. H. Public information: From nosy neighbors to cultural evolution. Science 305, 487–491. https://doi.org/10.1126/science.1098254 (2004).
ADS  CAS  Article  PubMed  Google Scholar 

78.
Boulinier, T., McCoy, K. D., Yoccoz, N. G., Gasparini, J. & Tveraa, T. Public information affects breeding dispersal in a colonial bird: Kittiwakes cue on neighbours. Biol. Lett. 4, 538–540. https://doi.org/10.1098/rsbl.2008.0291 (2008).
Article  PubMed  PubMed Central  Google Scholar 

79.
Francesiaz, C. et al. Familiarity drives social philopatry in an obligate colonial breeder with weak interannual breeding-site fidelity. Anim. Behav. 124, 125–133. https://doi.org/10.1016/j.anbehav.2016.12.011 (2017).
Article  Google Scholar 

80.
Reusch, T. B., Ehlers, A., Hämmerli, A. & Worm, B. Ecosystem recovery after climatic extremes enhanced by genotypic diversity. Proc. Natl. Acad. Sci. U.S.A. 102, 2826–2831. https://doi.org/10.1073/pnas.0500008102 (2005).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

81.
Bay, R. A. et al. Genomic signals of selection predict climate-driven population declines in a migratory bird. Science 359, 83–86. https://doi.org/10.1126/science.aan4380 (2018).
ADS  CAS  Article  PubMed  Google Scholar 

82.
Durant, J. M., Krasnov, Y. V., Nikolaeva, N. G. & Stenseth, N. C. Within and between species competition in a seabird community: Statistical exploration and modeling of time-series data. Oecologia 169, 685–694. https://doi.org/10.1007/s00442-011-2226-3 (2012).
ADS  CAS  Article  PubMed  Google Scholar 

83.
Cury, P. M. et al. Global seabird response to forage fish depletion—One-third for the birds. Science 334, 1703–1706. https://doi.org/10.1126/science.1212928 (2011).
ADS  CAS  Article  PubMed  Google Scholar 

84.
Paleczny, M., Hammill, E., Karpouzi, V. & Pauly, D. Population trend of the world’s monitored seabirds, 1950–2010. PLoS ONE 10, e0129342. https://doi.org/10.1371/journal.pone.0129342 (2015).
CAS  Article  PubMed  PubMed Central  Google Scholar 

85.
Feare, C. J. & Lesperance, C. Intra- and inter-colony movements of breeding adult Sooty Terns in Seychelles. Waterbirds 25, 52–55. https://doi.org/10.1675/1524-4695(2002)025[0052:IAIMOB]2.0.CO;2 (2002).
Article  Google Scholar 

86.
Grémillet, D. & Boulinier, T. Spatial ecology and conservation of seabirds facing global climate change: A review. Mar. Ecol. Prog. Ser. 391, 121–137. https://doi.org/10.3354/meps08212 (2009).
ADS  Article  Google Scholar 

87.
Colchero, F., Bass, O. L., Zambrano, R. & Gore, J. A. Clustered nesting and vegetation thresholds reduce egg predation in Sooty Terns. Waterbirds 33, 169–178. https://doi.org/10.1675/063.033.0205 (2010).
Article  Google Scholar  More

1.
Elder, C. J. & Bishop, N. J. Rickets. Lancet 383(9929), 1665–1676 (2014).
PubMed  Article  Google Scholar 
2.
Dittmer, K. E. & Thompson, K. G. Vitamin D metabolism and rickets in domestic animals: A review. Vet. Pathol. 48(2), 389–407 (2011).
CAS  PubMed  Article  Google Scholar 

3.
Hymoller, L. & Jensen, S. K. Vitamin D(3) synthesis in the entire skin surface of dairy cows despite hair coverage. J. Dairy Sci. 93(5), 2025–2029 (2010).
CAS  PubMed  Article  Google Scholar 

4.
Mellanby E. Nutrition classics. Lancet 1, 407–12 (1919) (an experimental investigation of rickets. Edward Mellanby. Nutr. Rev. 34(11), 338–40, 1976).

5.
Provvedini, D. M., Tsoukas, C. D., Deftos, L. J. & Manolagas, S. C. 1,25-dihydroxyvitamin D3 receptors in human leukocytes. Science 221(4616), 1181–1183 (1983).
ADS  CAS  PubMed  Article  Google Scholar 

6.
Holick, M. F. Vitamin D deficiency. N. Engl. J. Med. 357(3), 266–281 (2007).
CAS  PubMed  Article  Google Scholar 

7.
Baeke, F., Takiishi, T., Korf, H., Gysemans, C. & Mathieu, C. Vitamin D: Modulator of the immune system. Curr. Opin. Pharmacol. 10(4), 482–496 (2010).
CAS  PubMed  Article  Google Scholar 

8.
Besusso, D. et al. 1,25-Dihydroxyvitamin D-conditioned CD11c+ dendritic cells are effective initiators of CNS autoimmune disease. Front. Immunol. 6, 575 (2015).
PubMed  PubMed Central  Article  CAS  Google Scholar 

9.
Saul, L. et al. 1,25-Dihydroxyvitamin D3 restrains CD4(+) T cell priming ability of CD11c(+) dendritic cells by upregulating expression of CD31. Front. Immunol. 10, 600 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

10.
Afzal, S., Brondum-Jacobsen, P., Bojesen, S. E. & Nordestgaard, B. G. Genetically low vitamin D concentrations and increased mortality: Mendelian randomisation analysis in three large cohorts. BMJ 349, g6330 (2014).
PubMed  PubMed Central  Article  CAS  Google Scholar 

11.
Chowdhury, R. et al. Vitamin D and risk of cause specific death: Systematic review and meta-analysis of observational cohort and randomised intervention studies. BMJ 348, g1903 (2014).
PubMed  PubMed Central  Article  Google Scholar 

12.
Schottker, B. et al. Vitamin D and mortality: Meta-analysis of individual participant data from a large consortium of cohort studies from Europe and the United States. BMJ 348, g3656 (2014).
PubMed  PubMed Central  Article  CAS  Google Scholar 

13.
Ganmaa, D., Munkhzul B, Fawzi W, Spiegelman D, Willett WC, Bayasgalan P, et al. High-dose vitamin D3 during tuberculosis treatment in Mongolia. A randomized controlled trial. Am. J. Respir. Crit. Care Med. 196(5), 628–637 (2017).

14.
Aibana, O. et al. Vitamin D status and risk of incident tuberculosis disease: A nested case-control study, systematic review, and individual-participant data meta-analysis. PLoS Med. 16(9), e1002907 (2019).
PubMed  PubMed Central  Article  Google Scholar 

15.
Wu, H. X. et al. Effects of vitamin D supplementation on the outcomes of patients with pulmonary tuberculosis: A systematic review and meta-analysis. BMC Pulm. Med. 18(1), 108 (2018).
PubMed  PubMed Central  Article  CAS  Google Scholar 

16.
Jolliffe, D. A. et al. Vitamin D supplementation to prevent asthma exacerbations: A systematic review and meta-analysis of individual participant data. Lancet Respir. Med. 5(11), 881–890 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

17.
Munger, K. L., Levin, L. I., Hollis, B. W., Howard, N. S. & Ascherio, A. Serum 25-hydroxyvitamin D levels and risk of multiple sclerosis. JAMA 296(23), 2832–2838 (2006).
CAS  PubMed  Article  PubMed Central  Google Scholar 

18.
Rhead, B. et al. Mendelian randomization shows a causal effect of low vitamin D on multiple sclerosis risk. Neurol. Genet. 2(5), e97 (2016).
PubMed  PubMed Central  Article  CAS  Google Scholar 

19.
Manson, J. E. et al. Vitamin D supplements and prevention of cancer and cardiovascular disease. N. Engl. J. Med. 380(1), 33–44 (2019).
CAS  PubMed  Article  Google Scholar 

20.
Pittas, A. G. et al. Vitamin D supplementation and prevention of type 2 diabetes. N. Engl. J. Med. 381(6), 520–530 (2019).
CAS  PubMed  PubMed Central  Article  Google Scholar 

21.
Titmarsh, H. et al. Vitamin D status predicts 30 day mortality in hospitalised cats. PLoS ONE 10(5), e0125997 (2015).
PubMed  PubMed Central  Article  CAS  Google Scholar 

22.
Jaffey, J. A., Backus, R. C., McDaniel, K. M. & DeClue, A. E. Serum vitamin D concentrations in hospitalized critically ill dogs. PLoS ONE 13(3), e0194062 (2018).
PubMed  PubMed Central  Article  CAS  Google Scholar 

23.
Titmarsh, H., Gow, A.G., Kilpatrick, S., Sinclair, J., Hill, T., Milne, E., et al. Association of vitamin D status and clinical outcome in dogs with a chronic enteropathy. J. Vet. Intern. Med. (2015).

24.
Allenspach, K., Rizzo, J., Jergens, A. E. & Chang, Y. M. Hypovitaminosis D is associated with negative outcome in dogs with protein losing enteropathy: A retrospective study of 43 cases. BMC Vet. Res. 13(1), 96 (2017).
CAS  PubMed  PubMed Central  Article  Google Scholar 

25.
Titmarsh, H. F. et al. Low vitamin D status is associated with systemic and gastrointestinal inflammation in dogs with a chronic enteropathy. PLoS ONE 10(9), e0137377 (2015).
PubMed  PubMed Central  Article  CAS  Google Scholar 

26.
Titmarsh, H.F., Cartwright, J.A., Kilpatrick, S., Gaylor, D., Milne, E.M., Berry, J.L., et al. Relationship between vitamin D status and leukocytes in hospitalised cats. J. Feline Med. Surg. (2016).

27.
Handel, I. et al. Vitamin D status predicts reproductive fitness in a wild sheep population. Sci. Rep. 6, 18986 (2016).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

28.
Zhou, P. et al. Investigation of relationship between vitamin D status and reproductive fitness in Scottish hill sheep. Sci. Rep. 9(1), 1162 (2019).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

29.
Corripio-Miyar, Y., Mellanby, R. J., Morrison, K. & McNeilly, T. N. 1,25-Dihydroxyvitamin D3 modulates the phenotype and function of Monocyte derived dendritic cells in cattle. BMC Vet. Res. 13(1), 390 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

30.
Yue, Y., Hymoller, L., Jensen, S. K., Lauridsen, C. & Purup, S. Effects of vitamin D and its metabolites on cell viability and Staphylococcus aureus invasion into bovine mammary epithelial cells. Vet. Microbiol. 203, 245–251 (2017).
CAS  PubMed  Article  Google Scholar 

31.
Garcia-Barragan, A., Gutierrez-Pabello, J. A. & Alfonseca-Silva, E. Calcitriol increases nitric oxide production and modulates microbicidal capacity against Mycobacterium bovis in bovine macrophages. Comp. Immunol. Microbiol. Infect. Dis. 59, 17–23 (2018).
PubMed  Article  Google Scholar 

32.
Waters, W. R. et al. Modulation of Mycobacterium bovis-specific responses of bovine peripheral blood mononuclear cells by 1,25-dihydroxyvitamin D(3). Clin. Diagn. Lab. Immunol. 8(6), 1204–1212 (2001).
CAS  PubMed  PubMed Central  Article  Google Scholar 

33.
Lippolis, J. D., Reinhardt, T. A., Sacco, R. A., Nonnecke, B. J. & Nelson, C. D. Treatment of an intramammary bacterial infection with 25-hydroxyvitamin D(3). PLoS ONE 6(10), e25479 (2011).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

34.
Merriman, K. E., Poindexter, M. B., Kweh, M. F., Santos, J. E. P. & Nelson, C. D. Intramammary 1,25-dihydroxyvitamin D3 treatment increases expression of host-defense genes in mammary immune cells of lactating dairy cattle. J. Steroid Biochem. Mol. Biol. 173, 33–41 (2017).
CAS  PubMed  Article  Google Scholar 

35.
Stabel, J. R., Reinhardt, T. A. & Hempel, R. J. Short communication: Vitamin D status and responses in dairy cows naturally infected with Mycobacterium avium ssp. paratuberculosis. J. Dairy Sci. 102(2), 1594–1600 (2019).
CAS  PubMed  Article  Google Scholar 

36.
de Clare Bronsvoort, B. M. et al. Design and descriptive epidemiology of the Infectious Diseases of East African Livestock (IDEAL) project, a longitudinal calf cohort study in western Kenya. BMC Vet. Res. 9, 171 (2013).
PubMed  PubMed Central  Article  Google Scholar 

37.
Hunt, S.E., McLaren, W., Gil, L., Thormann, A., Schuilenburg, H., Sheppard, D., et al. Ensembl variation resources. Database (2018).

38.
Jiang, X. et al. Genome-wide association study in 79,366 European-ancestry individuals informs the genetic architecture of 25-hydroxyvitamin D levels. Nat. Commun. 9(1), 260 (2018).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

39.
Manousaki, D., Mitchell, R., Dudding, T., Haworth, S., Harroud, A., Forgetta, V., et al. Genome-wide association study for vitamin D levels reveals 69 independent loci. Am. J. Hum. Genet. (2020).

40.
Titmarsh, H. et al. Association of vitamin D status and clinical outcome in dogs with a chronic enteropathy. J. Vet. Intern. Med. 29(6), 1473–1478 (2015).
CAS  PubMed  PubMed Central  Article  Google Scholar 

41.
Aspelund, T. et al. Effect of genetically low 25-hydroxyvitamin D on mortality risk: Mendelian randomization analysis in 3 large European cohorts. Nutrients. 11(1), 1 (2019).
Article  CAS  Google Scholar 

42.
Huang, T. et al. Vitamin D and cause-specific vascular disease and mortality: a Mendelian randomisation study involving 99,012 Chinese and 106,911 European adults. BMC Med. 17(1), 160 (2019).
PubMed  PubMed Central  Article  CAS  Google Scholar 

43.
Ong, J. S. et al. Association of vitamin D levels and risk of ovarian cancer: A Mendelian randomization study. Int. J. Epidemiol. 45(5), 1619–1630 (2016).
PubMed  PubMed Central  Article  Google Scholar 

44.
Reid, D. et al. The relation between acute changes in the systemic inflammatory response and plasma 25-hydroxyvitamin D concentrations after elective knee arthroplasty. Am. J. Clin. Nutr. 93(5), 1006–1011 (2011).
CAS  PubMed  Article  Google Scholar 

45.
Waldron, J. L. et al. Vitamin D: a negative acute phase reactant. J Clin Pathol. 66(7), 620–622 (2013).
CAS  PubMed  Article  Google Scholar 

46.
Nonnecke, B. J. et al. Acute phase response elicited by experimental bovine diarrhea virus (BVDV) infection is associated with decreased vitamin D and E status of vitamin-replete preruminant calves. J. Dairy Sci. 97(9), 5566–5579 (2014).
CAS  PubMed  Article  Google Scholar 

47.
Nelson, C. D. et al. Assessment of serum 25-hydroxyvitamin D concentrations of beef cows and calves across seasons and geographical locations. J. Anim. Sci. 94(9), 3958–3965 (2016).
CAS  PubMed  Article  Google Scholar 

48.
Saliba, W., Barnett, O., Stein, N., Kershenbaum, A. & Rennert, G. The longitudinal variability of serum 25(OH)D levels. Eur. J. Intern. Med. 23(4), e106–e111 (2012).
CAS  PubMed  Article  Google Scholar 

49.
Major, J. M. et al. Variability and reproducibility of circulating vitamin D in a nationwide U.S. population. J. Clin. Endocrinol. Metab. 98(1), 97–104 (2013).
CAS  PubMed  Article  Google Scholar 

50.
Jorde, R. et al. Tracking of serum 25-hydroxyvitamin D levels during 14 years in a population-based study and during 12 months in an intervention study. Am. J. Epidemiol. 171(8), 903–908 (2010).
PubMed  Article  Google Scholar 

51.
McKibben, R. A. et al. Factors associated with change in 25-hydroxyvitamin D levels over longitudinal followup in the ARIC study. J. Clin. Endocrinol. Metab. 1, jc20151711 (2015).
Google Scholar 

52.
van Schoor, N. M. et al. Longitudinal changes and seasonal variations in serum 25-hydroxyvitamin D levels in different age groups: Results of the Longitudinal Aging Study Amsterdam. Osteoporos. Int. 25(5), 1483–1491 (2014).
PubMed  Google Scholar 

53.
Liu, X. et al. Longitudinal trajectory of vitamin D status from birth to early childhood in the development of food sensitization. Pediatr. Res. 74(3), 321–326 (2013).
CAS  PubMed  PubMed Central  Article  Google Scholar 

54.
Baiz, N. et al. Cord serum 25-hydroxyvitamin D and risk of early childhood transient wheezing and atopic dermatitis. J. Allergy Clin. Immunol. 133(1), 147–153 (2014).
CAS  PubMed  Article  Google Scholar 

55.
Lai, S. H. et al. Low cord-serum 25-hydroxyvitamin D levels are associated with poor lung function performance and increased respiratory infection in infancy. PLoS ONE 12(3), e0173268 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

56.
Sauder, K. A. et al. Cord blood vitamin D levels and early childhood blood pressure: The healthy start study. J. Am. Heart Assoc. 8(9), e011485 (2019).
PubMed  PubMed Central  Article  Google Scholar 

57.
Cetinkaya, M. et al. Lower vitamin D levels are associated with increased risk of early-onset neonatal sepsis in term infants. J. Perinatol. 35(1), 39–45 (2015).
CAS  PubMed  Article  Google Scholar 

58.
Behera, C.K., Sahoo, J.P., Patra, S.D., Jena, P.K. Is lower vitamin D level associated with increased risk of neonatal sepsis? A prospective cohort study. Indian J. Pediatr. (2020).

59.
Sacco, R. E. et al. Differential expression of cytokines in response to respiratory syncytial virus infection of calves with high or low circulating 25-hydroxyvitamin D3. PLoS ONE 7(3), e33074 (2012).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

60.
Yue, Y., Hymoller, L., Jensen, S. K. & Lauridsen, C. Effect of vitamin D treatments on plasma metabolism and immune parameters of healthy dairy cows. Arch. Anim. Nutr. 72(3), 205–220 (2018).
CAS  PubMed  Article  Google Scholar 

61.
Hidiroglou, M., Williams, C. J. & Proulx, J. G. Plasma vitamin D3 response in cattle and sheep exposed to ultraviolet radiation. Int. J. Vitam. Nutr. Res. 55(1), 41–46 (1985).
CAS  PubMed  Google Scholar 

62.
Casas, E., Lippolis, J. D., Kuehn, L. A. & Reinhardt, T. A. Seasonal variation in vitamin D status of beef cattle reared in the central United States. Domest. Anim. Endocrinol. 52, 71–74 (2015).
CAS  PubMed  Article  Google Scholar 

63.
Hymoller, L., Jensen, S. K., Kaas, P. & Jakobsen, J. Physiological limit of the daily endogenous cholecalciferol synthesis from UV light in cattle. J. Anim. Physiol. Anim. Nutr. (Berl). 101(2), 215–221 (2017).
CAS  Article  Google Scholar 

64.
Jolliffe, D. A. et al. Vitamin D to prevent exacerbations of COPD: Systematic review and meta-analysis of individual participant data from randomised controlled trials. Thorax 74(4), 337–345 (2019).
PubMed  Article  Google Scholar 

65.
Martineau, A. R. et al. Vitamin D supplementation to prevent acute respiratory tract infections: Systematic review and meta-analysis of individual participant data. BMJ 356, i6583 (2017).
PubMed  PubMed Central  Article  CAS  Google Scholar 

66.
Nicholson, M., Butterworth, M.H. A guide to condition scoring of zebu cattle: ILRI (aka ILCA and ILRAD) (1986).

67.
Callaby, R., Pendarovski, C., Thumbi, S.M., Van Wyk, I., Mbole-Kariuki, M.N., Kiara, H., et al. The infectious diseases of East African livestock (IDEAL) project database. Nat. Sci. Data (submitted).

68.
Hurst, E.A., Homer, N.Z., Gow, A.G., Clements, D.N., Evans, H., Gaylor, D., et al. Vitamin D status is seasonally stable in northern European dogs. Vet. Clin. Pathol. (2020).

69.
Purcell, S., Chang, C. PLINK 2.0.

70.
Chang, C. C. et al. Second-generation PLINK: Rising to the challenge of larger and richer datasets. GigaScience. 4(1), 1 (2015).
Article  CAS  Google Scholar 

71.
R Core Team. R: A language and environment for statistical computing. (R Foundation for Statistical Computing, Vienna, 2019).

72.
Wickham H. ggplot2: Elegant Graphics for Data Analysis (Springer, New York, 2016).

73.
Fox, J. & Weisberg, S. An R companion to applied regression (Sage, Thousand Oaks, 2019).
Google Scholar 

74.
Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1(1), 3–14 (2010).
Article  Google Scholar 

75.
Bartoń K. MuMIn: Multi-Model Inference. R package version 1.43.15 (2019).

76.
Gilmour, A., Gogel, B., Cullis, B., Thompson, R., Butler, D., Cherry, M., et al. ASReml user guide release 3.0. (VSN Int Ltd, 2008).

77.
Zheng, X. et al. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28(24), 3326–3328 (2012).
CAS  PubMed  PubMed Central  Article  Google Scholar 

78.
Hill, W. G. & Mackay, T. F. DS Falconer and introduction to quantitative genetics. Genetics 167(4), 1529–1536 (2004).
PubMed  PubMed Central  Google Scholar 

79.
Chen H. GMMAT: Generalized linear Mixed Model Association Tests Version 1.1. 2. (2019).

80.
Turner S. qqman: Q-Q and Manhattan Plots for GWAS Data. (2017). More

1.
Hunt, A. P. Late Pennsylvanian coprolites fromthe Kinney Brick Quarry, central New Mexico with notes on the classification and utility of coprolites. Bull. New Mex. Bur. Min. Mineral Resour. 138, 221–229 (1992).
Google Scholar 
2.
Hunt, A. P., Chin, K. & Lockley, M. In The palaeobiology of vertebrate coprolites (ed. Donovan, S.) 221–240 (Wiley, New York, 1994).
Google Scholar 

3.
Northwood, C. Early Triassic coprolites from Australia and their palaeobiological significance. Palaeontology 48, 49–68 (2005).
Article  Google Scholar 

4.
Zatoń, M. et al. Coprolites of Late Triassic carnivorous vertebrates from Poland: an integrative approach. Palaeogeogr. Palaeoclimatol. Palaeoecol. 430, 21–46 (2015).
Article  Google Scholar 

5.
Salamon, M. A., Niedźwiedzki, R., Gorzelak, P., Lach, R. & Surmik, D. Bromalites from the Middle Triassic of Poland and the rise of the Mesozoic Marine Revolution. Palaeogeogr. Palaeoclimatol. Palaeoecol. 321–322, 142–150. https://doi.org/10.1016/j.palaeo.2012.01.029 (2012).
Article  Google Scholar 

6.
Niedźwiedzki, G., Bajdek, P., Owocki, K. & Kear, B. P. An Early Triassic polar predator ecosystem revealed by vertebrate coprolites from the Bulgo Sandstone (Sydney Basin) of southeastern Australia. Palaeogeogr. Palaeoclimatol. Palaeoecol. 464, 5–15. https://doi.org/10.1016/j.palaeo.2016.04.003 (2016).
Article  Google Scholar 

7.
Hansen, B. B. et al. Coprolites from the Late Triassic Kap Stewart Formation, Jameson Land, East Greenland: morphology, classification and prey inclusions. Geol. Soc. Lond. Spec. Publ. 434, 49–69. https://doi.org/10.1144/SP434.12 (2016).
ADS  Article  Google Scholar 

8.
Brachaniec, T. et al. Coprolites of marine vertebrate predators from the Lower Triassic of southern Poland. Palaeogeogr. Palaeoclimatol. Palaeoecol. 435, 118–126. https://doi.org/10.1016/j.palaeo.2015.06.005 (2015).
Article  Google Scholar 

9.
Umamaheswaran, R., Prasad, G. V. R., Rudra, A. & Dutta, S. Investigation of Biomarkers in Triassic Coprolites from India, 1–1 (2019).

10.
Chrząstek, A. & Niedźwiedzki, R. Kręgowce retu i dolnego wapienia muszlowego na Śląsku. Prace geologiczno-mineralogiczne LXIV. Acta Universitatis Wratislaviensis, 69–81 (in Polish) (1998).

11.
Glaessner, M. F. Eine Crustaceen fauna aus den Lunzer Schichten Niederösterreichs. Jahrbuch Geologische Bundesanstalt Wien 81, 467–486 (1931).
Google Scholar 

12.
Stur, D. Neue Aufschlüsse im Lunzer Sandsteine bei Lunz und ein neuer Fundort von Wengerschiefer im Pölzberg zwischen Lunzersee und Gaming. Verhandlungen der kaiserlich königlichen Geologischen Reichsanstalt 1, 271–273 (1874).
Google Scholar 

13.
Seilacher, A. Begriff und Bedeutung der Fossil-Lagerstätten (Concept and meaning of fossil lagerstätten). Neues Jahrbuch für Geologie und Paläontologie, Abhandlungen 1970, 34–39 (1970).
Google Scholar 

14.
Krystyn, L. Die Fossillagerstätten der alpinen Trias. (eds. D. Nagel & G. Rabeder) 23–78 (Österreichische Paläontologische Gesellschaft Wien, 1991).

15.
Forchielli, A. & Pervesler, P. Phosphatic cuticle in thylacocephalans: a taphonomic case study of (Arthropoda, Thylacocephala) from the Fossil-Lagerstätte Polzberg (Reingraben shales, Carnian, Upper Triassic, Lower Austria). Aust. J. Earth Sci. 106, 46–61 (2013).
Google Scholar 

16.
Teller, F. Über den Schädel eines fossilen Dipnoers, Ceratodus Sturii nov. spec aus den Schichten der oberen Trias der Nordalpen. Abhandlungen der kaiserlich königlichen Geologischen Reichsanstalt 15, 1–2 (1981).
Google Scholar 

17.
Griffith, J. The Upper Triassic fishes from Polzberg bei Lunz. Zool. J. Linnaean Soc. 60, 1–93 (1977).
Article  Google Scholar 

18.
Doguzhaeva, L. A., Mapes, R. H., Summesberger, H. & Mutvei, H. In The Preservation of Body Tissues, Shell, and Mandibles in the Ceratitid Ammonoid Austrotrachyceras (Late Triassic), Austria (eds Landman, H. N. et al.) 221–237 (Springer, New York, 2007).
Google Scholar 

19.
Doguzhaeva, L. A., Summesberger, H., Mutvei, H. & Brandstaetter, F. The mantle, ink sac, ink, arm hooks and soft body debris associated with the shells in Late Triassic coleoid cephalopod Phragmoteuthis from the Austrian Alps. Palaeoworld 16, 272–284 (2007).
Article  Google Scholar 

20.
Doguzhaeva, L. A. & Summesberger, H. Pro-ostraca of Triassic belemnoids (Cephalopoda) from Northern Calcareous Alps, with observations on their mode of preservation in an environment of northern Tethys which allowed for carbonization of non-biomineralized structures. Neues Jahrbuch für Geologie und Paläontologie Abhandlungen 266, 31–38 (2012).
Article  Google Scholar 

21.
Austromap Online 2020. Bundesamt für Eich- und Vermessungswesen, Wien. https://www.austrianmap.at/amap/index.php?SKN=1andXPX=637andYPX=492 (accessed 5 Feb 2020).

22.
Wagreich, M., Pervesler, P., Khatun, M., Wimmer-Frey, I. & Scholger, R. Probing the underground at the Badenian type locality: geology and sedimentology of the Baden-Sooss section (Middle Miocene, Vienna Basin, Austria). Geol. Carpath. 59, 375–394 (2008).
CAS  Google Scholar 

23.
Lukeneder, A. & Zverkov, N. First evidence of a conical-toothed pliosaurid (Reptilia, Sauropterygia) in the Hauterivian of the Northern Calcareous Alps, Austria. Cretac. Res. 106, 104248 (2020).
Article  Google Scholar 

24.
Geologische Karte der Republik Österreich, Sheet Ybbsitz 71 1:50.000. Geologische Bundesanstalt Wien (1988).

25.
Geologische Karte der Republik Österreich, Sheet Mariazell 72, 1:50.000. Geologische Bundesanstalt Wien (1997).

26.
Tollmann, A. Analyse des klassischen nordalpinen Mesozoikums 580 (Franz Deuticke Wien, 1976).

27.
von Hauer, F. R. Ueber die Gliederung der Trias-, Lias- und Juragebilde in den nördlichsten Alpen. Kaiserlich Königliche reichsanstalt 4, 715–783 (1853).
Google Scholar 

28.
Piller, W. E. et al. M. Die Stratigraphische Tabelle von Österreich 2004 (sedimentäre Schichtfolgen). Kommission für die Paläontologische und stratigraphische Erforschung Österreichs. Österreichische Akademie der Wissenschaften und Österreichische Stratigraphische Kommission, Wien (2004).

29.
Glaessner, M. F. Eine Crustacenfauna aus den Lunzer Schichten Niederӧsterreichs. Jahrbuch der geologischen Bundes-Anstalt 81, 467–489 (1931).
Google Scholar 

30.
Bronn, H. G. Nachtrag über die Trias-Fauna von Raibl. Neues Jahrbuch für Mineralogie, Geognosie, Geologie und Petrefaktenkunde 1859, 39–45 (1859).
Google Scholar 

31.
Abel, O. Fossile Flugfische. Abhandlungen der kaiserlich königlichen Geologischen Reichsanstalt 56, 1–88 (1906).
Google Scholar 

32.
Trauth, F. Geologie des Kalkalpenbereiches der zweiten Wiener Hochquellenleitung. Abhandlungen der Geologisches Bundesanstalt 26, 1–99 (1948).
Google Scholar 

33.
Mostler, H. & Scheuring, B. W. Mikrofloren aus dem Langobard und Cordevol der Nördlichen Kalkalpen und das Problem des beginns der Keupersedimentation im Germanischen Raum. Geol. Paläontol. Mitteilungen Innsbruck 4, 1–35 (1974).
Google Scholar 

34.
Hornung, T. & Brandner, R. Biochronostratigraphy of the Reingraben Turnover (Hallstatt facies belt): Local black shale events controlled by regional tectonism, climatic change and plate tectonics. Facies 51, 460–479 (2005).
Article  Google Scholar 

35.
Hornung, T., Brandner, R., Krystyn, L., Joachimski, M. M. & Keim, L. Multistratigraphic constraints on the NW Tethyan ’Carnin Crisis. New Mexico Museum Nat. Hist. Bull. 41, 59–67 (2007).
Google Scholar 

36.
Hasiotis, S. T., Platt, B. F., Hembree, D. I. & Everhart, M. J. In The Trace−Fossil Record of Vertebrates (ed. Miller, W.) 196–218 (Elsevier, Amsterdam, 2007).
Google Scholar 

37.
Gordon, C. M., Roach, B. T., Parker, W. G. & Briggs, D. E. G. Distinguishing regurgitalites and coprolites: a case study using a Triassic bromalite with soft tissue of the pseudosuchian archosaur Revueltosaurus. Palaios 35, 111–121 (2020).
ADS  Article  Google Scholar 

38.
Salamon, M. A., Gorzelak, P., Niedźwiedzki, R., Trzęsiok, D. & Baumiller, T. K. Trends in shell fragmentation as evidence of mid-Paleozoic changes in marine predation. Paleobiology 40, 14–23 (2014).
Article  Google Scholar 

39.
Salamon, M. A., Leśko, K. & Gorzelak, P. Experimental tumbling of Dreissena polymorpha: implications for recognizing durophagous predation in the fossil record. Facies 64, 4 (2018).
Article  Google Scholar 

40.
Salamon, M. A., Brachaniec, T. & Gorzelak, P. Durophagous fish predation traces versus tumbling-induced shell damage: a paleobiological perspective. Palaios 35, 37–47 (2020).
ADS  Article  Google Scholar 

41.
Reboulet, S. & Rard, A. Double alignments of ammonoid aptychi from the Lower Cretaceous of Southeast France: result of a post−mortem transport or bromalites?. Acta Palaeontol. Pol. 53, 261–274 (2008).
Article  Google Scholar 

42.
Mapes, R. H. & Chaffin, D. T. In Predation on Cephalopods: A General Overview with a Case Study from the Upper Carboniferous of Texas (eds Kelley, H. P. et al.) 177–213 (Kluwer/Plenum, New York, 2003).
Google Scholar 

43.
Hoffmann, R., Stevens, K., Keupp, H., Simonsen, S. & Schweigert, G. Regurgitalites: a winodw into the trophic ecology of fossil cephalopods. J. Geol. Soc. 177, 82–102 (2020).
ADS  Article  Google Scholar 

44.
Keupp, H. Ammoniten: Paläobiologische Erfolgsspiralen (Thorbecke, Stuttgart, 2000).
Google Scholar 

45.
Vullo, R. Direct evidence of hybodont shark predation on Late Jurassic ammonites. Naturwissenschaften 98, 545–549 (2011).
ADS  CAS  PubMed  Article  Google Scholar 

46.
Ward, P., Dooley, F. & Barord, G. J. Nautilus: biology, systematics, and paleobiology as viewed from 2015. Swiss J. Palaeont. 135, 169–185 (2016).
Article  Google Scholar 

47.
Palmer, A. R. Fish predation and the evolution of gastropod shell sculpture: experimental and geographic evidence. Evolution 33, 697–713 (1979).
PubMed  Article  Google Scholar 

48.
Reis, O. M. Coelacanthus lunzensis Teller. Jahrbuch der kaiserlich königlichen Geologischen Reichsanstalt 50, 187–192 (1900).
Google Scholar 

49.
Skrzycki, P., Niedźwiedzki, G. & Tałanda, M. Dipnoan remains from the Lower-Middle Triassic of the Holy Cross Mountains and northeastern Poland, with remarks on dipnoan palaeobiogeography. Palaeogeogr. Palaeoclimatol. Palaeoecol. 496, 332–345 (2018).
Article  Google Scholar 

50.
Mutter, R. J. Tooth variability and reconstruction of dentition in Acrodus sp (Chondrichthyes, Selachii, Hybodontoidea) from the Grenzbitumenzone (Middle Triassic) of Monte San Giorgio (Ticino, Switzerland). Geologisch 3, 25–31 (1998).
Google Scholar 

51.
Griffith, J. The Triassic fish Saurichthys krambergeri Schlosser. Palaeontology 5, 344–354 (1962).
Google Scholar 

52.
Romano, C., Kogan, I., Jenks, J., Jerjen, I. & Brinkmann, W. Saurichthys and other fossil fishes from the late Smithian (Early Triassic) of Bear Lake County (Idaho, USA), with a discussion of saurichthyid palaeogeography and evolution. Bull. Geosci. 87, 543–570 (2012).
Article  Google Scholar 

53.
Cavin, L., Furrer, H. & Obrist, Ch. New coelacanth material from the Middle Triassic of eastern Switzerland, and comments on the taxic diversity of actinistans. Swiss J. Geosci. 106, 161–177 (2013).
Article  Google Scholar 

54.
Hauser, L. M. & Martill, D. M. Evidence for coelacanths in the Late Triassic (Rhaetian) of England. Proc. Geol. Assoc. 124, 982–987 (2013).
Article  Google Scholar 

55.
Tintori, A. Fish biodiversity in the marine Norian (Late Triassic) of northern Italy: the first neopterygian radiation. Italian J. Zool. 65, 193–198 (1998).
Article  Google Scholar 

56.
Wilga, C. D. & Motta, P. J. Durophagy in sharks: feeding mechanics of hammerhead sharks Sphyrna tiburo. J. Exp. Biol. 203, 2781–2796 (2000).
CAS  PubMed  PubMed Central  Google Scholar 

57.
Huber, D. R., Eason, T. G., Hueter, R. E. & Motta, P. J. Analysis of the bite force and mechanical design of the feeding mechanism of the durophagous horn shark Heterodontus francisci. J. Exp. Biol. 208, 3553–3571 (2005).
Article  Google Scholar 

58.
Cappetta, H. Chondrichthyes II: Mesozoic and Cenozoic Elasmobranchii Handbook of Paleoichthyology 1–193 (Gustav Fischer Verlag, Stuttgart, 1987).
Google Scholar 

59.
Rees, J. Interrelationships of Mesozoic hybodont sharks as indicated by dental morphology: preliminary results. Acta Geol. Pol. 58, 217–221 (2008).
Google Scholar 

60.
Massare, J. A. Tooth morphology and prey preference of Mesozoic marine reptiles. J. Vertebr. Paleontol. 7, 121–137 (1987).
Article  Google Scholar 

61.
Schmidt, M. Die Lebewelt Unserer Trias 461 (Ferdinand Rau, Öhringen, 1928).
Google Scholar 

62.
Griffith, J. On the anatomy of two saurichthyid fishes, Saurichthys striolatus (Bronn) and S. curioni (Belotti). Proc. Zool. Soc. Lond. 132, 587–606 (1959).
Article  Google Scholar 

63.
Wen, W. et al. Coelacanths from the Middle Triassic Luoping Biota, Yunnan, South China, with the earliest evidence of ovoviviparity. Acta Palaeontol. Pol. 58, 175–193 (2013).
Google Scholar 

64.
Bernardi, M., Avanzini, M. & Bizzarini, F. Vertebrate fauna from the San Cassiano Formation (early Carnian) of the Dolomites region. Geo. Alp. 8, 122–127 (2011).
Google Scholar 

65.
Dalla Vecchia, F. M. Reptile remains from the Middle-Upper Triassic of Carnic and Julian Alps (Friuli-Venezia Giulia, Northeastern Italy), Gortania. Atti del Museo Friulano di Storia Naturale 15, 49–66 (1994).
Google Scholar 

66.
Buffetaut, E. & Novak, M. A cyamodontid placodont (Reptilia: Sauropterygia) from the Triassic of Slovenia. Palaeontology 51, 1301–1306 (2008).
Article  Google Scholar 

67.
Sirna, G., Dalla Vecchia, F. M., Muscio, G. & Piccoli, G. Catalogue of paleozoic and mesozoic vertebrates and vertebrate localities of the Tre Venezie area (North Eastern Italy). Mem. Istit. Geol. Mineral. Univ. Padova 46, 255–281 (1994).
Google Scholar 

68.
Qvarnström, M., Niedźwiedzki, G., Tafforeau, P., Žigaitė, Ž & Ahlberg, P. E. Synchrotron phase-contrast microtomography of coprolites generates novel palaeobiological data. Sci. Rep. 7, 2723 (2017).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

69.
Vermeij, G. J. The Mesozoic marine revolution: evidence from snails, predators and grazers. Paleobiology 3, 245–258 (1977).
Article  Google Scholar 

70.
Baumiller, T. K. et al. Post-Paleozoic crinoid radiation to benthic predation preceded the Mesozoic marine revolution. Proc. Natl. Acad. Sci. USA 107, 5893–5896 (2010).
ADS  CAS  PubMed  Article  Google Scholar 

71.
McRoberts, C. A. Triassic bivalves and the initial marine Mesozoic revolution; a role of predators?. Geology 29, 359–362 (2001).
ADS  Article  Google Scholar 

72.
Huang, J. et al. Repeated evolution of durophagy during ichthyosaur radiation after mass extinction indicated by hidden dentition. Sci. Rep. 10, 7798 (2020).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

73.
Walker, S. E. & Brett, C. E. Post-Paleozoic patterns in marine predations: was there a Mesozoic and Cenozoic Marine Predatory Revolution?. Palentol. Soc. Pap. 8, 119–193 (2002).
Article  Google Scholar 

74.
Underwood, C. J. Diversification of the Neoselachii (Chondrichthyes) during the Jurassic and Cretaceous. Paleobiology 32, 215–235 (2006).
Article  Google Scholar 

75.
Kriwet, J., Kiessling, W. & Klug, S. Diversification trajectories and evolutionary lifehistory traits in early sharks and batoids. Proc. R. Soc. Lond. B 276, 945–951 (2009).
Google Scholar 

76.
Gorzelak, P., Salamon, M. A. & Baumiller, T. K. Predator induced macroevolutionary trends in Mesozoic crinoids. Proc. Natl. Acad. Sci. USA 109, 7004–7007 (2012).
ADS  CAS  PubMed  Article  Google Scholar 

77.
Scheyer, T. M., Romano, C., Jenks, J. & Bucher, H. Early triassic marine biotic recovery: the predators’ perspective. PLoS ONE 9, e88987 (2014).
ADS  PubMed  PubMed Central  Article  CAS  Google Scholar 

78.
Gorzelak, P. Microstructural evidence for stalk autotomy in Holocrinus: the oldest stem-group isocrinid. Palaeogeogr. Palaeoclimatol. Palaeoecol. 506, 202–207 (2018).
Article  Google Scholar 

79.
Gorzelak, P. et al. Experimental neoichnology of post-autotomy arm movements of sea lilies and possible evidence of thrashing behaviour in Triassic holocrinids. Sci. Rep. 10, 15147 (2020).
CAS  PubMed  PubMed Central  Article  Google Scholar  More

1.
Hambright, K. D., Gophen, M. & Serruya, S. Influence of long-term climatic changes on the stratification of a subtropical, warm monomictic lake. Limnol. Oceanogr. 39, 1233–1242 (1994).
ADS  Article  Google Scholar 
2.
Pilla, R. M. et al. Browning-related decreases in water transparency lead to long-term increases in surface water temperature and thermal stratification in two small lakes. J. Geophys. Res. Biogeo. https://doi.org/10.1029/2017JG004321 (2018).
Article  Google Scholar 

3.
Foley, B., Jones, I. D., Maberly, S. C. & Rippey, B. Long-term changes in oxygen depletion in a small temperate lake: Effects of climate change and eutrophication. Freshwater Biol. 57, 278–289 (2012).
CAS  Article  Google Scholar 

4.
Knoll, L. B. et al. Browning-related oxygen depletion in an oligotrophic lake. Inland Waters https://doi.org/10.1080/20442041.2018.1452355 (2018).
Article  Google Scholar 

5.
O’Reilly, C. M., Alin, S. R., Plisnier, P.-D., Cohen, A. S. & McKee, B. A. Climate change decreases aquatic ecosystem productivity of Lake Tanganyika Africa. Nature 424, 766–768 (2003).
ADS  CAS  PubMed  Article  Google Scholar 

6.
Verburg, P., Hecky, R. E. & Kling, H. Ecological consequences of a century of warming in Lake Tanganyika. Science 301, 505–507 (2003).
ADS  CAS  PubMed  Article  Google Scholar 

7.
Saulnier-Talbot, É. et al. Small changes in climate can profoundly alter the dynamics and ecosystem services of tropical crater lakes. PLoS ONE https://doi.org/10.1371/journal.pone.0086561 (2014).
Article  PubMed  PubMed Central  Google Scholar 

8.
Cohen, A. S. et al. Climate warming reduces fish production and benthic habitat in Lake Tanganyika, one of the most biodiverse freshwater ecosystems. P. Natl. Acad. Sci. 113, 9563–9568 (2016).
ADS  CAS  Article  Google Scholar 

9.
Hansen, G. J. A., Read, J. S., Hansen, J. F. & Winslow, L. A. Projected shifts in fish species dominance in Wisconsin lakes under climate change. Glob. Change Biol. 23, 1463–1476 (2017).
ADS  Article  Google Scholar 

10.
De Stasio, B. T., Hill, D. K., Kleinhans, J. M., Nibbelink, N. P. & Magnuson, J. J. Potential effects of global climate change on small north-temperate lakes: Physics, fish, and plankton. Limnol. Oceanogr. 41, 1136–1149 (1996).
ADS  Article  Google Scholar 

11.
Craig, N., Jones, S. E., Weidel, B. C. & Solomon, C. T. Habitat, not resource availability, limits consumer production in lake ecosystems. Limnol. Oceanogr. 60, 2079–2089 (2015).
ADS  Article  Google Scholar 

12.
Brothers, S. et al. A feedback loop links brownification and anoxia in a temperate, shallow lake. Limnol. Oceanogr. 59, 1388–1398 (2014).
ADS  CAS  Article  Google Scholar 

13.
Marotta, H. et al. Greenhouse gas production in low-latitude lake sediments responds strongly to warming. Nat. Clim. Change https://doi.org/10.1038/NCLIMATE2222 (2014).
Article  Google Scholar 

14.
Schneider, P. & Hook, S. J. Space observations of inland water bodies show rapid surface warming since. Geophys. Res. Lett. https://doi.org/10.1029/2010GL045059 (2010).
Article  Google Scholar 

15.
O’Reilly, C. M. et al. Rapid and highly variable warming of lake surface waters around the globe. Geophys. Res. Lett. https://doi.org/10.1002/2015GL066235 (2015).
Article  Google Scholar 

16.
Woolway, R. I. & Merchant, C. J. Worldwide alteration of lake mixing regimes in response to climate change. Nat. Geosci. https://doi.org/10.1038/s41561-019-0322-x (2019).
Article  Google Scholar 

17.
Kraemer, B. M. et al. Morphometry and average temperature affect lake stratification responses to climate change. Geophys. Res. Lett. https://doi.org/10.1002/2015GL064097 (2015).
Article  Google Scholar 

18.
Keller, W., Heneberry, J. & Leduc, J. Linkages between weather, dissolved, organic carbon, and cold-water habitat in a Boreal Shield lake recovering from acidification. Can. J. Fish. Aquat. Sci. 62, 341–347 (2005).
CAS  Article  Google Scholar 

19.
Wagner, A., Volkmann, S. & Dettinger-Klemm, P. M. A. Benthic-pelagic coupling in lake ecosystems: The key role of chironomid pupae as prey of pelagic fish. Ecosphere https://doi.org/10.1890/ES11-00181.1 (2012).
Article  Google Scholar 

20.
Straile, D., Kerimoglu, O. & Peeters, F. Trophic mismatch requires seasonal heterogeneity of warming. Ecology 96, 2794–2805 (2015).
PubMed  Article  PubMed Central  Google Scholar 

21.
Schmid, M. & Köster, O. Excess warming of a Central European lake driven by solar brightening. Water Resour. Res. https://doi.org/10.1002/2016WR018651 (2016).
Article  Google Scholar 

22.
Woolway, R. I., Meinson, P., Nõges, P., Jones, I. D. & Laas, A. Atmospheric stilling leads to prolonged thermal stratification in a large shallow polymictic lake. Clim. Change 141, 759–773 (2017).
Article  Google Scholar 

23.
Read, J. S. & Rose, K. C. Physical responses of small temperate lakes to variation in dissolved organic carbon concentrations. Limnol. Oceanogr. 58, 921–931 (2013).
ADS  CAS  Article  Google Scholar 

24.
Winslow, L. A., Read, J. S., Hansen, G. J. A. & Hanson, P. C. Small lakes show muted climate change signal in deepwater temperatures. Geophys. Res. Lett. https://doi.org/10.1002/2014GL062325 (2015).
Article  Google Scholar 

25.
Morris, D. P. et al. The attenuation of solar UV radiation in lakes and the role of dissolved organic carbon. Limnol. Oceanogr. 40, 1381–1391 (1995).
ADS  CAS  Article  Google Scholar 

26.
Fee, E. J., Hecky, R. E., Kasian, S. E. M. & Cruikshank, D. R. Effects of lake size, water clarity, and climatic variability on mixing depths in Canadian Shield lakes. Limnol. Oceanogr. 41, 912–920 (1996).
ADS  CAS  Article  Google Scholar 

27.
Snucins, E. & Gunn, J. Interannual variation in the thermal structure of clear and colored lakes. Limnol. Oceanogr. 45, 1639–1646 (2000).
ADS  Article  Google Scholar 

28.
Jankowski, T., Livingstone, D. M., Bührer, H., Forster, R. & Niederhauser, P. Consequences of the 2003 European heat wave for lake temperature profiles, thermal stability, and hypolimnetic oxygen depletion: implications for a warmer world. Limnol. Oceanogr. 51, 815–819 (2006).
ADS  Article  Google Scholar 

29.
Downing, J. A. et al. The global abundance and size distribution of lakes, ponds, and impoundments. Limnol. Oceanogr. 51, 2388–2397 (2006).
ADS  Article  Google Scholar 

30.
Maberly, S. C. et al. Global lake thermal regions shift under climate change. Nat. Commun. 11, 1232. https://doi.org/10.1038/s41467-020-15108-z (2020).
ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

31.
IPCC In Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) (Cambridge University Press, Cambridge, 2013).
Google Scholar 

32.
Pepin, N. et al. Elevation-dependent warming in mountain regions of the world. Nat. Clim. Change https://doi.org/10.1038/NCLIMATE2563 (2015).
Article  Google Scholar 

33.
Rose, K. C., Winslow, L. A., Read, J. S. & Hansen, G. J. A. Climate-induced warming of lakes can be either amplified or suppressed by trends in water clarity. Limnol. Oceanogr. Lett. https://doi.org/10.1002/lol2.10027 (2016).
Article  Google Scholar 

34.
Benson, B. J. et al. Extreme events, trends, and variability in Northern Hemisphere lake-ice phenology (1855–2005). Clim. Change 112, 299–323 (2012).
ADS  Article  Google Scholar 

35.
Sharma, S. et al. Widespread loss of lake ice around the Northern Hemisphere in a warming world. Nat. Clim. Change https://doi.org/10.1038/s41558-018-0393-5 (2019).
Article  Google Scholar 

36.
Woolway, R. I. et al. Global lake responses to climate change. Nat. Rev. Earth. Environ. 1, 388–403 (2020).
ADS  Article  Google Scholar 

37.
Zhang, G. et al. Response of Tibetan Plateau lakes to climate change: Trends, patterns, and mechanisms. Earth Sci. Rev. https://doi.org/10.1016/j.earscirev.2020.103269 (2020).
Article  Google Scholar 

38.
Dokulil, M. T. et al. Twenty years of spatially coherent deepwater warming in lakes across Europe related to the North Atlantic Oscillation. Limnol. Oceanogr. 51, 2787–2793 (2006).
ADS  Article  Google Scholar 

39.
Ficker, H., Luger, M. & Gassner, H. From dimictic to monomictic: Empirical evidence of thermal regime transitions in three deep alpine lakes in Austria induced by climate change. Freshw. Biol. https://doi.org/10.1111/fwb.12946 (2017).
Article  Google Scholar 

40.
Markfort, C. D. et al. Wind sheltering of a lake by a tree canopy or bluff topography. Water Resour. Res. https://doi.org/10.1029/2009WR007759 (2010).
Article  Google Scholar 

41.
Read, J. S. et al. Lake-size dependency of wind shear and convection as controls on gas exchange. Geophys. Res. Lett. https://doi.org/10.1029/2012GL051886 (2012).
Article  Google Scholar 

42.
Beniston, M., Diaz, H. F. & Bradley, R. S. Climatic change at high elevation sites: An overview. Clim. Change 36, 233–251 (1997).
Article  Google Scholar 

43.
Sommaruga-Wögrath, S. et al. Temperature effects on the acidity of remote alpine lakes. Nature 387, 64–67 (1997).
ADS  Article  Google Scholar 

44.
Václavík, T., Lautenback, S., Kuemmerle, T. & Seppelt, R. Mapping global land system archetypes. Glob. Environ. Change https://doi.org/10.1016/j.gloenvcha.2013.09.004 (2013).
Article  Google Scholar 

45.
Bartosiewicz, M. et al. Hot tops, cold bottoms: Synergistic climate warming and shielding effects increase carbon burial in lakes. Limnol. Oceanogr. Lett. https://doi.org/10.1002/lol2.10117 (2019).
Article  Google Scholar 

46.
Williamson, C. E. et al. Ecological consequences of long-term browning in lakes. Sci. Rep. https://doi.org/10.1038/srep18666 (2015).
Article  PubMed  PubMed Central  Google Scholar 

47.
Evans, C. D., Chapman, P. J., Clark, J. M., Monteith, D. T. & Cresser, M. S. Alternative explanations for rising dissolved organic carbon export from organic soils. Glob. Change Biol. 12, 2044–2053 (2006).
ADS  Article  Google Scholar 

48.
Monteith, D. et al. Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry. Nature https://doi.org/10.1038/nature06316 (2007).
Article  PubMed  Google Scholar 

49.
Couture, S., Houle, D. & Gagnon, C. Increases of dissolved organic carbon in temperate and boreal lakes in Quebec Canada. Environ. Sci. Pollut. Res. 19, 361–371 (2012).
CAS  Article  Google Scholar 

50.
Read, J. S. et al. Derivation of lake mixing and stratification indices from high-resolution lake buoy data. Environ. Model. Softw. 26, 1325–1336 (2011).
Article  Google Scholar 

51.
Gray, E., Mackay, E. B., Elliot, J. A., Folkard, A. M. & Jones, I. D. Wide-spread inconsistency in estimation of lake mixed depth impacts interpretation of limnological processes. Water Res. https://doi.org/10.1016/j.watres.2019.115136 (2020).
Article  PubMed  Google Scholar 

52.
Prokopkin, I. G. & Zadereev, E. S. A model study of the effect of weather forcing on the ecology of a meromictic Siberian Lake. J. Oceanol. Limnol. 36, 2018–2032 (2018).
ADS  CAS  Article  Google Scholar 

53.
Austin, J. A. & Colman, S. M. Lake Superior summer water temperatures are increasing more rapidly than regional air temperatures: A positive ice-albedo feedback. Geophys. Res. Lett. https://doi.org/10.1029/2006GL029021 (2007).
Article  Google Scholar 

54.
Preston, D. L. et al. Climate regulates alpine lake ice cover phenology and aquatic ecosystem structure. Geophys. Res. Lett. https://doi.org/10.1002/2016GL069036 (2016).
Article  Google Scholar 

55.
Sadro, S., Melack, J. M., Sickman, J. O. & Skeen, K. Climate warming response of mountain lakes affected by variations in snow. Limnol. Oceanogr. Lett. https://doi.org/10.1002/lol2.10099 (2018).
Article  Google Scholar 

56.
Zhang, G. et al. Estimating surface temperature changes of lakes in the Tibetan Plateau using MODIS LST data. J. Geophys. Res. Atmos. 119, 8552–8567 (2014).
ADS  Article  Google Scholar 

57.
Taylor, C. A. & Stefan, H. G. Shallow groundwater temperature response to climate change and urbanization. J. Hydrol. 375, 601–612 (2009).
ADS  CAS  Article  Google Scholar 

58.
Zhang, X. Conjunctive surface water and groundwater management under climate change. Front. Environ. Sci. https://doi.org/10.3389/fenvs.2015.00059 (2015).
Article  Google Scholar 

59.
Gaiser, E. E., Deyrup, N. D., Bachmann, R. W., Battoe, L. E. & Swain, H. M. Effects of climate variability on transparency and thermal structure in subtropical, monomictic Lake Annie Florida. Fund. Appl. Limnol. 175, 217–230 (2009).
Article  Google Scholar 

60.
Zhang, J. et al. Long-term patterns of dissolved organic carbon in lakes across eastern Canada: Evidence of a pronounced climate effect. Limnol. Oceanogr. 55, 30–42 (2010).
ADS  CAS  Article  Google Scholar 

61.
Williamson, C. E. et al. Sentinel responses to droughts, wildfires, and floods: effects of UV radiation on lakes and their ecosystem services. Front. Ecol. Environ. 14, 102–109 (2016).
Article  Google Scholar 

62.
Thiery, W. et al. Understanding the performance of the Flake model over two African Great Lakes. Geosci. Model Dev. 7, 317–337 (2014).
ADS  Article  Google Scholar 

63.
Shatwell, T., Thiery, W. & Kirillin, G. Future projections of temperature and mixing regime of European temperate lakes. Hydrol. Earth Syst. Sci. 23, 1533–1551 (2019).
ADS  Article  Google Scholar 

64.
Winslow, L. A., Read, J. S., Hansen, G. J. A., Rose, K. C. & Robertson, D. M. Seasonality of change: summer warming rates do not fully represent effects of climate change on lake temperatures. Limnol. Oceanogr. 62, 2168–2178 (2017).
ADS  Article  Google Scholar 

65.
Fang, X. & Stefan, H. G. Simulations of climate effects on water temperatures, dissolved oxygen, and ice and snow covers in lakes of the contiguous United States under past and future climate scenarios. Limnol. Oceanogr. 54, 2359–2370 (2009).
ADS  CAS  Article  Google Scholar 

66.
Rösner, R., Müller-Navarra, D. C. & Zorita, E. Trend analysis of weekly temperatures and oxygen concentrations during summer stratification in Lake Plußsee: a long-term study. Limnol. Oceanogr. 57, 1479–1491 (2012).
ADS  Article  CAS  Google Scholar 

67.
Rogora, M. et al. Climatic effects on vertical mixing and deep-water oxygen content in the subalpine lakes in Italy. Hydrobiologia 824, 33–50 (2018).
CAS  Article  Google Scholar 

68.
Wilhelm, S. & Adrian, R. Impact of summer warming on the thermal characteristics of a polymictic lake and consequences for oxygen, nutrients and phytoplankton. Freshw. Biol. 53, 226–237 (2008).
CAS  Article  Google Scholar 

69.
North, R. P., North, R. L., Livingstone, D. M., Köster, O. & Kipfer, R. Long-term changes in hypoxia and soluble reactive phosphorus in the hypolimnion of a large temperate lake: consequences of a climate regime shift. Glob. Change Biol. https://doi.org/10.1111/gcb.12371 (2014).
Article  Google Scholar 

70.
Zadereev, E. S., Tolomeev, A. P., Drobotov, A. V. & Kolmakova, A. A. Impact of weather variability on spatial and seasonal dynamics of dissolved and suspended nutrients in water column of meromictic Lake Shira. Contemp. Probl. Ecol. 21, 515–530 (2014).
Google Scholar 

71.
Couture, R.-M., deWit, H. A., Tominaga, K., Kiuru, P. & Markelov, I. Oxygen dynamics in a boreal lake responds to long-term changes in climate, ice phenology, and DOC inputs. J. Geophys. Res. Biogeo. https://doi.org/10.1002/2015JG003065 (2015).
Article  Google Scholar 

72.
Richardson, D. C. et al. Transparency, geomorphology and mixing regime explain variability in trends in lake temperature and stratification across Northeastern North America (1975–2004). Water https://doi.org/10.3390/w9060442 (2017).
Article  Google Scholar 

73.
Kalff, J. Limnology: Inland Water Ecosystems (Prentice Hall, Upper Saddle River, 2002).
Google Scholar 

74.
Wetzel, R. G. Limnology: Lake and River Ecosystems (Academic Press, New York, 2001).
Google Scholar 

75.
Woolway, R. I. et al. Diel surface temperature range scales with lake size. PLoS ONE https://doi.org/10.1371/journal.pone.0152466 (2016).
Article  PubMed  PubMed Central  Google Scholar 

76.
Williamson, C. E., Fischer, J. M., Bollens, S. M., Overholt, E. P. & Breckenridge, J. K. Toward a more comprehensive theory of zooplankton diel vertical migration: Integrating ultraviolet radiation and water transparency into the biotic paradigm. Limnol. Oceanogr. 56, 1603–1623 (2011).
ADS  Article  Google Scholar 

77.
Winslow, L. et al. rLakeAnalyzer: Lake physics tools. R package version 1.11.4.1. https://CRAN.R-project.org/package=rLakeAnalyzer (2019).

78.
Sen, P. K. Estimates of the regression coefficient based on Kendall’s Tau. J. Am. Stat. Assoc. 63, 1379–1389 (1968).
MathSciNet  MATH  Article  Google Scholar 

79.
Hirsch, R. M., Slack, J. R. & Smith, R. A. Techniques of trend analysis for monthly water quality data. Water Resour. Res. 18, 107–121 (1982).
ADS  Article  Google Scholar 

80.
Jassby, A. D. & Cloern, J. E. wq: Some tools for exploring water quality monitoring data. R package version 0.4.8. https://cran.r-project.org/package=wq (2016).

81.
Leach, T. H. et al. Patterns and drivers of deep chlorophyll maxima structure in 100 lakes: the relative importance of light and thermal stratification. Limnol. Oceanogr. 63, 628–646 (2018).
ADS  CAS  Article  Google Scholar 

82.
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).
MATH  Article  Google Scholar 

83.
James, G., Witten, D., Hastie, T. & Tibshirani, R. Tree-based methods. In An Introduction to Statistical Learning: With Applications in R (Springer, Berlin, 2015).
Google Scholar 

84.
Genuer, R., Poggi, J.-M. & Tuleau-Malot, C. Variable selection using random forests. Pattern Recogn. Lett. 31, 2225–2236 (2010).
Article  Google Scholar 

85.
Dormann, C. F. et al. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 027–046 (2013).
Article  Google Scholar 

86.
Auret, L. & Alrich, C. Interpretation of nonlinear relationships between process variables by use of random forests. Miner. Eng. 35, 27–42 (2012).
CAS  Article  Google Scholar 

87.
Liaw, A. & Wiener, M. Classification and regression by randomForest. R News 2, 18–22 (2002).
Google Scholar 

88.
R Core Team. R: a language and environment for statistical computing, R Foundation for Statistical Computing. https://www.R-project.org/ (2019).

89.
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, Berlin, 2016).
Google Scholar  More

1.
Prasad, A. M. et al. Modeling the invasive emerald ash borer risk of spread using a spatially explicit cellular model. Landsc. Ecol. 25(3), 353–369 (2010).
Article  Google Scholar 
2.
Huang, D., Zhang, R., Kim, K. C. & Suarez, A. V. Spatial pattern and determinants of the first detection locations of invasive alien species in mainland China. PLoS ONE 7(2), e31734 (2012).
ADS  CAS  Article  Google Scholar 

3.
Roy, H. E. et al. Invasive alien predator causes rapid declines of native European ladybirds. Divers. Distrib. 18(7), 717–725 (2012).
Article  Google Scholar 

4.
Cini, A. et al. Tracking the invasion of the alien fruit pest Drosophila suzukii in Europe. J. Pest Sci. 87(4), 559–566 (2014).
Article  Google Scholar 

5.
Filipe, A. F., Quaglietta, L., Ferreira, M., Magalhães, M. F. & Beja, P. Geostatistical distribution modelling of two invasive crayfish across dendritic stream networks. Biol. Invas. 19(10), 2899–2912 (2017).
Article  Google Scholar 

6.
Hahn, N. G., Rodriguez-Saona, C. & Hamilton, G. C. Characterizing the spatial distribution of brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), populations in peach orchards. PLoS ONE 12(3), e0170889 (2017).
Article  Google Scholar 

7.
Carrière, Y. et al. Effects of local and landscape factors on population dynamics of a cotton pest. PLoS ONE 7(6), e39862 (2012).
ADS  Article  Google Scholar 

8.
Wang, X. G., Kaçar, G., Biondi, A. & Daane, K. M. Foraging efficiency and outcomes of interactions of two pupal parasitoids attacking the invasive spotted wing drosophila. Biol. Control 96, 64–71 (2016).
Article  Google Scholar 

9.
Dara, S. K., Barringer, L. & Arthurs, S. P. Lycorma delicatula (Hemiptera: Fulgoridae): a new invasive pest in the United States. J. Integr. Pest Manage. 6, 1–20 (2015).
Article  Google Scholar 

10.
Kim, H. et al. Molecular comparison of Lycorma delicatula (Hemiptera: Fulgoridae) isolates in Korea, China, and Japan. J. Asia-Pac. Entomol. 16(4), 503–506 (2013).
CAS  Article  Google Scholar 

11.
Han, J. M. et al. Lycorma delicatula (Hemiptera: Auchenorrhyncha: Fulgoridae: Aphaeninae) finally, but suddenly arrived in Korea. Entomol. Res. 38(4), 281–286 (2008).
Article  Google Scholar 

12.
Wakie, T. T., Neven, L. G., Yee, W. L. & Lu, Z. The establishment risk of Lycorma delicatula (Hemiptera: Fulgoridae) in the United States and globally. J. Econ. Entomol. https://doi.org/10.1093/jee/toz259 (2019).
Article  Google Scholar 

13.
Jung, J. M., Jung, S., Byeon, D. & Lee, W. H. Model-based prediction of potential distribution of the invasive insect pest, spotted lanternfly Lycorma delicatula (Hemiptera: Fulgoridae), by using CLIMEX. J. Asia-Pac. Biodivers. 10, 532–538 (2017).
Article  Google Scholar 

14.
Harper, J. K., Stone, W., Kelsey, T. W. & Kime, L. F. Potential economic impact of the spotted lanternfly on agriculture and forestry in Pennsylvania. Control Rural Pennsylvania Rep. 1, 1–84 (2019).
Google Scholar 

15.
Leach, H. & Leach, A. Seasonal phenology and activity of spotted lanternfly (Lycorma delicatula) in eastern US vineyards. J. Pest Sci. https://doi.org/10.1007/s10340-020-01233-7 (2020).
Article  Google Scholar 

16.
Barringer, L. E. & Smyers, E. Predation of the spotted lanternfly, Lycorma delicatula (White) (Hemiptera: Fulgoridae) by two native Hemiptera. Entomol. News 126, 71–73 (2016).
Article  Google Scholar 

17.
Cooperband, M. F., Mack, R. & Spichiger, S. E. Chipping to destroy egg masses of the spotted lanternfly, Lycorma delicatula (Hemiptera: Fulgoridae). J. Insect Sci. 18(3), 7–10 (2018).
Article  Google Scholar 

18.
Leach, H., Biddinger, D. J., Krawczyk, G., Smyer, S. E. & Urban, J. M. Evaluation of insecticides for control of the spotted lanternfly, Lycorma delicatula, (Hemiptera: Fulgoridae), a new pest of fruit in the Northeastern US. Crop Prot. https://doi.org/10.1016/j.cropro.2019.05.027 (2019).
Article  Google Scholar 

19.
Clifton, E. H., Castrillo, L. A., Gryganskyi, A. & Hajek, A. E. A pair of native fungal pathogens drives decline of a new invasive herbivore. Proc. Natl. Acad. Sci. 116(19), 9178–9180 (2019).
CAS  Article  Google Scholar 

20.
Urban, J. M. Perspective: shedding light on spotted lanternfly impacts in the USA. Pest Manage. Sci. https://doi.org/10.1002/ps.5619 (2020).
Article  Google Scholar 

21.
Wolfin, M. S. et al. Flight dispersal capabilities of female spotted lanternflies (Lycorma delicatula) related to size and mating status. J. Insect Behav. 32(3), 188–200 (2019).
Article  Google Scholar 

22.
Clifton, E. H. et al. Applications of Beauveria bassiana (Hypocreales: Cordycipitaceae) to control populations of spotted lanternfly (Hemiptera: Fulgoridae), in semi-natural landscapes and on grapevines. Environ. Entomol. https://doi.org/10.1093/ee/nvaa064 (2020).
Article  PubMed  Google Scholar 

23.
Francese, J. A. et al. Developing traps for the spotted lanternfly, Lycorma delicatula (Hemiptera: Fulgoridae). Environ. Entomol. 49(2), 269–276 (2020).
Article  Google Scholar 

24.
Nguyen, H. D. D. & Nansen, C. Edge-biased distributions of insects. A review. Agron. Sustain. Dev. 38, 11 (2018).
Article  Google Scholar 

25.
Ries, L. & Sisk, T. D. A predictive model of edge effects. Ecology https://doi.org/10.1890/03-8021 (2004).
Article  Google Scholar 

26.
Leskey, T. C., Short, B. D. & Ludwick, D. Comparison and refinement of integrated pest management tactics for Halyomorpha halys (Hemiptera: Pentatomidae) management in apple orchards. J. Econ. Entomol. https://doi.org/10.1093/jee/toaa067 (2020).
Article  PubMed  Google Scholar 

27.
Mason, K. S., Roubos, C. R., Teixeira, L. A. & Isaacs, R. Spatially targeted applications of reduced-risk insecticides for economical control of grape berry moth, Paralobesia viteana (Lepidoptera: Tortricidae). J. Econ. Entomol. 109(5), 2168–2174 (2016).
CAS  Article  Google Scholar 

28.
Goffinet, M.C. Anatomy of grapevine winter injury and recovery. Dept. Hort. Services Res. Paper, Cornell Univ. (2004). Accessed April 20, 2020 from https://www.eaglegrapegrowers.org/uploads/1/1/8/4/118472897/anatomy_of_winter_injury_hi_res.pdf.

29.
Halldorson, M. M. & Keller, M. Grapevine leafroll disease alters leaf physiology but has little effect on plant cold hardiness. Planta 248(5), 1201–1211 (2018).
CAS  Article  Google Scholar 

30.
Süle, S. & Burr, T. J. The effect of resistance of rootstocks to crown gall (Agrobacterium spp.) on the susceptibility of scions in grape vine cultivars. Plant Pathol. 47, 84–88 (1998).
Article  Google Scholar 

31.
Bates, D., Maechler, M., Bolker, B., Walker, S., Christensen, R.H.B., Singmann, H., Dai, B., Scheipl, F., Grothendieck, G. & Green, P. R Package ‘lme4’. 1.17 (2018).

32.
Bartoń, K. MuMIn: Multi-model Inference. R Package version 1.40.4 (2018).

33.
Korner-Nievergelt, F. et al. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS and Stan (Elsevier, Hoboken, 2015).
Google Scholar 

34.
Anselin, L. Local indicators of spatial association—LISA. Geogr. Anal. 27(2), 93–115 (1995).
Article  Google Scholar 

35.
Mitchell, A. The ESRI Guide to GIS Analysis (ESRI Press, Redlands, 2005).
Google Scholar 

36.
Krivoruchko, K. Spatial Statistical Data Analysis for GIS Users 928 (ESRI Press, Redland, 2011).
Google Scholar  More

1.
Worm, B. et al. Rebuilding global fisheries. Science 325, 578–585 (2009).
ADS  CAS  PubMed  Article  Google Scholar 
2.
Costello, C. et al. Global fishery prospects under contrasting management regimes. Proc. Natl Acad. Sci. USA 113, 5125–5129 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

3.
Allan, J. D. et al. Overfishing of inland waters. Bioscience 55, 1041–1051 (2005).
Article  Google Scholar 

4.
Lester, S. E. et al. Biological effects within no-take marine reserves: a global synthesis. Mar. Ecol. Prog. Ser. 384, 33–46 (2009).
ADS  Article  Google Scholar 

5.
Halpern, B. S., Lester, S. E. & McLeod, K. L. Placing marine protected areas onto the ecosystem-based management seascape. Proc. Natl Acad. Sci. USA 107, 18312–18317 (2010).
ADS  CAS  PubMed  Article  Google Scholar 

6.
Carr, M. H. et al. Marine protected areas exemplify the evolution of science and policy. Oceanography (Wash. D.C.) 32, 94–103 (2019).
Article  Google Scholar 

7.
Gaines, S. D., White, C., Carr, M. H. & Palumbi, S. R. Designing marine reserve networks for both conservation and fisheries management. Proc. Natl Acad. Sci. USA 107, 18286–18293 (2010).
ADS  CAS  PubMed  Article  Google Scholar 

8.
Edgar, G. J. et al. Global conservation outcomes depend on marine protected areas with five key features. Nature 506, 216–220 (2014).
ADS  CAS  PubMed  Article  Google Scholar 

9.
Abell, R., Lehner, B., Thieme, M. & Linke, S. Looking beyond the fenceline: assessing protection gaps for the world’s rivers. Conserv. Lett. 10, 384–394 (2017).
Article  Google Scholar 

10.
Grill, G. et al. Mapping the world’s free-flowing rivers. Nature 569, 215–221 (2019).
ADS  CAS  PubMed  Article  Google Scholar 

11.
Vörösmarty, C. J. et al. Global threats to human water security and river biodiversity. Nature 467, 555–561 (2010).
ADS  PubMed  Article  CAS  Google Scholar 

12.
McIntyre, P. B., Reidy Liermann, C. A. & Revenga, C. Linking freshwater fishery management to global food security and biodiversity conservation. Proc. Natl Acad. Sci. USA 113, 12880–12885 (2016).
CAS  PubMed  Article  Google Scholar 

13.
Fluet-Chouinard, E., Funge-Smith, S. & McIntyre, P. B. Global hidden harvest of freshwater fish revealed by household surveys. Proc. Natl Acad. Sci. USA 115, 7623–7628 (2018).
CAS  PubMed  Article  Google Scholar 

14.
Golden, C. D. et al. Nutrition: Fall in fish catch threatens human health. Nature 534, 317–320 (2016).
ADS  PubMed  Article  Google Scholar 

15.
Botsford, L. W., Micheli, F. & Hastings, A. Principles for the design of marine reserves. Ecol. Appl. 13, 25–31 (2003).
Article  Google Scholar 

16.
Gell, F. R. & Roberts, C. M. Benefits beyond boundaries: the fishery effects of marine reserves. Trends Ecol. Evol. 18, 448–455 (2003).
Article  Google Scholar 

17.
Hastings, A. & Botsford, L. W. Comparing designs of marine reserves for fisheries and for biodiversity. Ecol. Appl. 13, 65–70 (2003).
Article  Google Scholar 

18.
Pendleton, L. H. et al. Debating the effectiveness of marine protected areas. ICES J. Mar. Sci. 75, 1156–1159 (2018).
Article  Google Scholar 

19.
Chessman, B. C. Do protected areas benefit freshwater species? A broad-scale assessment for fish in Australia’s Murray–Darling Basin. J. Appl. Ecol. 50, 969–976 (2013).
Article  Google Scholar 

20.
Lawrence, D. J. et al. National parks as protected areas for U.S. freshwater fish diversity. Conserv. Lett. 4, 364–371 (2011).
Article  Google Scholar 

21.
Abell, R. et al. Concordance of freshwater and terrestrial biodiversity. Conserv. Lett. 4, 127–136 (2011).
Article  Google Scholar 

22.
Hilborn, R. Policy: Marine biodiversity needs more than protection. Nature 535, 224–226 (2016).
ADS  CAS  PubMed  Article  Google Scholar 

23.
Halpern, B. S. et al. Achieving the triple bottom line in the face of inherent trade-offs among social equity, economic return, and conservation. Proc. Natl Acad. Sci. USA 110, 6229–6234 (2013).
ADS  CAS  PubMed  Article  Google Scholar 

24.
Gill, D. A. et al. Capacity shortfalls hinder the performance of marine protected areas globally. Nature 543, 665–669 (2017).
ADS  CAS  PubMed  Article  Google Scholar 

25.
Baird, I. G., Flaherty, M. S. & Baird, I. G. Mekong River fish conservation zones in southern Laos: assessing effectiveness using local ecological knowledge. Environ. Manage. 36, 439–454 (2005).
PubMed  Article  Google Scholar 

26.
Loury, E. K. et al. Salty stories, fresh spaces: lessons for aquatic protected areas from marine and freshwater experiences. Aquat. Conserv. 28, 485–500 (2018).
Article  Google Scholar 

27.
McCann, K. S. et al. Food webs and the sustainability of indiscriminate fisheries. Can. J. Fish. Aquat. Sci. 73, 656–665 (2016).
CAS  Article  Google Scholar 

28.
Gutiérrez, N. L., Hilborn, R. & Defeo, O. Leadership, social capital and incentives promote successful fisheries. Nature 470, 386–389 (2011).
ADS  PubMed  Article  CAS  Google Scholar 

29.
Kramer, D. L. & Chapman, M. R. Implications of fish home range size and relocation for marine reserve function. Environ. Biol. Fishes 55, 65–79 (1999).
Article  Google Scholar 

30.
Morrison, S. A. A framework for conservation in a human-dominated world. Conserv. Biol. 29, 960–964 (2015).
PubMed  Article  Google Scholar 

31.
Campos-Silva, J. V. & Peres, C. A. Community-based management induces rapid recovery of a high-value tropical freshwater fishery. Sci. Rep. 6, 34745 (2016).
ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

32.
Castello, L., Viana, J. P., Watkins, G., Pinedo-Vasquez, M. & Luzadis, V. A. Lessons from integrating fishers of arapaima in small-scale fisheries management at the Mamirauá Reserve, Amazon. Environ. Manage. 43, 197–209 (2009).
ADS  PubMed  Article  Google Scholar 

33.
Pinho, P. F., Orlove, B. & Lubell, M. Overcoming barriers to collective action in community-based fisheries management in the Amazon. Hum. Organ. 71, 99–109 (2012).
Article  Google Scholar 

34.
Thompson, P. M., Sultana, P. & Islam, N. Lessons from community based management of floodplain fisheries in Bangladesh. J. Environ. Manage. 69, 307–321 (2003).
PubMed  Article  Google Scholar 

35.
Alexander, S. M., Epstein, G., Bodin, Ö., Armitage, D. & Campbell, D. Participation in planning and social networks increase social monitoring in community-based conservation. Conserv. Lett. 11, e12562 (2018).
Article  Google Scholar 

36.
Ostrom, E. A general framework for analyzing sustainability of social-ecological systems. Science 325, 419–422 (2009).
ADS  MathSciNet  CAS  PubMed  MATH  Article  Google Scholar 

37.
Halpern, B. S., Lester, S. E. & Kellner, J. B. Spillover from marine reserves and the replenishment of fished stocks. Environ. Conserv. 36, 268–276 (2009).
Article  Google Scholar 

38.
Campbell Grant, E. H., Lowe, W. H. & Fagan, W. F. Living in the branches: population dynamics and ecological processes in dendritic networks. Ecol. Lett. 10, 165–175 (2007).
PubMed  Article  Google Scholar 

39.
Palumbi, S. R. Population genetics, demographic connectivity, and the design of marine reserves. Ecol. Appl. 13, 146–158 (2003).
Article  Google Scholar 

40.
Tilman, D., May, R. M., Lehman, C. L. & Nowak, M. A. Habitat destruction and the extinction debt. Nature 371, 65–66 (1994).
ADS  Article  Google Scholar 

41.
McIntyre, P. B. et al. in Conservation of Freshwater Fishes (eds Closs, G. P. et al.) 324–360 (Cambridge Univ. Press, 2015).

42.
Dudgeon, D. et al. Freshwater biodiversity: importance, threats, status and conservation challenges. Biol. Rev. Camb. Philos. Soc. 81, 163–182 (2006).
PubMed  Article  Google Scholar 

43.
Roberts, C. M. et al. Marine reserves can mitigate and promote adaptation to climate change. Proc. Natl Acad. Sci. USA 114, 6167–6175 (2017).
ADS  CAS  PubMed  Article  Google Scholar 

44.
Koning, A. A., Moore, J., Suttidate, N., Hannigan, R. & McIntyre, P. B. Aquatic ecosystem impacts of land sharing versus sparing: nutrient loading to Southeast Asian rivers. Ecosystems (N. Y.) 20, 393–405 (2017).
CAS  Article  Google Scholar 

45.
Froese, R. & Pauly, D. (eds) FishBase http://www.fishbase.org (2019).

46.
Lamberti, G. A. & Hauer, F. R. Methods in Stream Ecology (Academic, 2017).

47.
Jari Oksanen, F. et al. vegan: Community Ecology Package. R package version 2.5-6 https://CRAN.R-project.org/package=vegan (2019).

48.
R Core Team. R: A Language and Environment for Statistical Computing https://www.R-project.org/ (R Foundation for Statistical Computing, 2019).

49.
Google Earth (November, 2015). Mae Ngao, Thailand. https://www.google.co.uk/earth/ (2020).

50.
Environmental Systems Research Institute (ESRI). ArcGIS Release 10.3 (2015).

51.
Yamazaki, D. et al. A high-accuracy map of global terrain elevations. Geophys. Res. Lett. 44, 5844–5853 (2017).
ADS  Article  Google Scholar 

52.
Robin, X. et al. pROC: an open-source package for R and S+ to analyze and compare ROC curves. BMC Bioinformatics 12, 77 (2011).
PubMed  PubMed Central  Article  Google Scholar 

53.
Jordán, F., Liu, W. C. & Andrew, J. D. Topological keystone species: measures of positional importance in food webs. Oikos 112, 535–546 (2006).
Article  Google Scholar 

54.
Bates, D., Maechler, M. & Ben Bolker, S. W. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).
Article  Google Scholar 

55.
Claudet, J. et al. Marine reserves: size and age do matter. Ecol. Lett. 11, 481–489 (2008).
PubMed  Article  Google Scholar 

56.
Claudet, J. et al. Marine reserves: fish life history and ecological traits matter. Ecol. Appl. 20, 830–839 (2010).
CAS  PubMed  Article  Google Scholar 

57.
Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).
PubMed  Article  Google Scholar 

58.
Barton, K. MuMIn: Multi-Model Inference. R package version 1.43.6 https://CRAN.R-project.org/package=MuMIn (2019). More