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Abstract

We are already experiencing the rapid pace of environmental perturbation in the Anthropocene, necessitating the development of new tools and techniques for measuring changes in ecosystem dynamics. Sentinel species, from birds to invertebrates, have been used to provide insights into ecosystem function, as leading indicators of risk to human health and as harbingers of future change, with implications for ecosystem structure and function. Here, we offer an update to previous research identifying marine top predators as indicators of ecosystem shifts and examine terrestrial sentinels and the latest research on sentinels of pollution and human health. Using ecosystem sentinels enables rapid response and adaptation to ecosystem variability and environmental change in part because they may be easier to observe and in part because they may serve as leading indicators of ecosystem disruption. While there may not be a given taxon that is best suited as sentinels, we highlight how to select the most effective sentinels, including examples of when sentinel species have been incorporated into management. Choosing a suite of appropriate sentinels both will give insight into ecosystem processes and can help manage changing ecosystems into the future.

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2024-10-18
2024-12-02
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Literature Cited

  1. 1.
    Darling ES, McClanahan TR, Maina J, Gurney GG, Graham NAJ, et al. 2019.. Social–environmental drivers inform strategic management of coral reefs in the Anthropocene. . Nat. Ecol. Evol. 3:(9):134150
    [Crossref] [Google Scholar]
  2. 2.
    Szuwalski C, Cheng W, Foy R, Hermann AJ, Hollowed A, et al. 2021.. Climate change and the future productivity and distribution of crab in the Bering Sea. . ICES J. Mar. Sci. 78:(2):50215
    [Crossref] [Google Scholar]
  3. 3.
    Abrahms B, Carter NH, Clark-Wolf T, Gaynor KM, Johansson E, et al. 2023.. Climate change as a global amplifier of human-wildlife conflict. . Nat. Clim. Change 13:(3):22434
    [Crossref] [Google Scholar]
  4. 4.
    Hazen EL, Abrahms B, Brodie S, Carroll G, Jacox MG, et al. 2019.. Marine top predators as climate and ecosystem sentinels. . Front. Ecol. Environ. 17:(10):56574
    [Crossref] [Google Scholar]
  5. 5.
    Clark-Wolf T, Holt KA, Johansson E, Nisi AC, Rafiq K, et al. 2024.. The capacity of sentinel species to detect changes in environmental conditions and ecosystem structure. . J. Appl. Ecol. 61:(7):163848
    [Crossref] [Google Scholar]
  6. 6.
    Sydeman WJ, Santora JA, Thompson SA, Marinovic B, Lorenzo ED. 2013.. Increasing variance in North Pacific climate relates to unprecedented ecosystem variability off California. . Glob. Change Biol. 19:(6):166275
    [Crossref] [Google Scholar]
  7. 7.
    McGowan J, Beaumont LJ, Smith RJ, Chauvenet ALM, Harcourt R, et al. 2020.. Conservation prioritization can resolve the flagship species conundrum. . Nat. Commun. 11:(1):994
    [Crossref] [Google Scholar]
  8. 8.
    Jordán F. 2009.. Keystone species and food webs. . Philos. Trans. R. Soc. B 364:(1524):173341
    [Crossref] [Google Scholar]
  9. 9.
    Roberge J-M, Angelstam P. 2004.. Usefulness of the umbrella species concept as a conservation tool. . Conserv. Biol. 18:(1):7685
    [Crossref] [Google Scholar]
  10. 10.
    Zacharias MA, Roff JC. 2001.. Use of focal species in marine conservation and management: a review and critique. . Aquat. Conserv. Mar. Freshw. Ecosyst. 11:(1):5976
    [Crossref] [Google Scholar]
  11. 11.
    Caro T. 2010.. Conservation by Proxy: Indicator, Umbrella, Keystone, Flagship, and Other Surrogate Species. Washington, DC:: Island Press. 394 pp.
    [Google Scholar]
  12. 12.
    Caro T. 2015.. Conservation by proxy: thoughts 5 years on. . In Indicators and Surrogates of Biodiversity and Environmental Change, ed. D Lindenmayer, P Barton, J Pierson , pp. 2532. Collingwood, Aust:.: CSIRO Publ.
    [Google Scholar]
  13. 13.
    Ramirez MD, Avens L, Seminoff JA, Goshe LR, Heppell SS. 2015.. Patterns of loggerhead turtle ontogenetic shifts revealed through isotopic analysis of annual skeletal growth increments. . Ecosphere 6:(11):244
    [Crossref] [Google Scholar]
  14. 14.
    Trumble SJ, Norman SA, Crain D, Mansouri F, Winfield ZC, et al. 2018.. Baleen whale cortisol levels reveal a physiological response to 20th century whaling. . Nat. Commun. 9::4587
    [Crossref] [Google Scholar]
  15. 15.
    Gerson JR, Szponar N, Zambrano AA, Bergquist B, Broadbent E, et al. 2022.. Amazon forests capture high levels of atmospheric mercury pollution from artisanal gold mining. . Nat. Commun. 13:(1):559
    [Crossref] [Google Scholar]
  16. 16.
    Cohen LE, Fagre AC, Chen B, Carlson CJ, Becker DJ. 2023.. Coronavirus sampling and surveillance in bats from 1996–2019: a systematic review and meta-analysis. . Nat. Microbiol. 8:(6):117686
    [Crossref] [Google Scholar]
  17. 17.
    Mayor SJ, Guralnick RP, Tingley MW, Otegui J, Withey JC, et al. 2017.. Increasing phenological asynchrony between spring green-up and arrival of migratory birds. . Sci. Rep. 7:(1):1902
    [Crossref] [Google Scholar]
  18. 18.
    Boersma PD. 2008.. Penguins as marine sentinels. . BioScience 58:(7):597607
    [Crossref] [Google Scholar]
  19. 19.
    Marneweck CJ, Allen BL, Butler AR, Do Linh San E, Harris SN, et al. 2022.. Middle-out ecology: small carnivores as sentinels of global change. . Mammal Rev. 52:(4):47179
    [Crossref] [Google Scholar]
  20. 20.
    Weimerskirch H, Collet J, Corbeau A, Pajot A, Hoarau F, et al. 2020.. Ocean sentinel albatrosses locate illegal vessels and provide the first estimate of the extent of nondeclared fishing. . PNAS 117:(6):300614
    [Crossref] [Google Scholar]
  21. 21.
    Samhouri JF, Andrews KS, Fay G, Harvey CJ, Hazen EL, et al. 2017.. Defining ecosystem thresholds for human activities and environmental pressures in the California Current. . Ecosphere 8:(6):e01860
    [Crossref] [Google Scholar]
  22. 22.
    Ray A, Legg K, Robison H, Carpenter J, Thoma D. 2021.. Collaborative vital signs monitoring in Yellowstone National Park. . In Intermountain Park Science Series 2021. Fort Collins, CO:: National Park Service. https://www.nps.gov/articles/000/collaborative-vital-signs-monitoring-in-yellowstone-national-park.htm
    [Google Scholar]
  23. 23.
    Kühn S, Van Franeker JA, Van Loon W. 2022.. Plastic particles in fulmar stomachs in the North Sea. . In OSPAR 2023: The 2023 Quality Status Report for the Northeast Atlantic. London:: OSPAR Comm. https://oap.ospar.org/en/ospar-assessments/quality-status-reports/qsr-2023/indicator-assessments/plastic-in-fulmar/
    [Google Scholar]
  24. 24.
    Burrell GA, Seibert FM. 1914.. Experiments with small animals and carbon monoxide. . J. Ind. Eng. Chem. 6:(3):24144
    [Crossref] [Google Scholar]
  25. 25.
    Pollock C. 2016.. The canary in the coal mine. . J. Avian Med. Surg. 30:(4):38691
    [Crossref] [Google Scholar]
  26. 26.
    Cairns DK. 1987.. Seabirds as indicators of marine food supplies. . Biol. Oceanogr. 5:(4):26171
    [Google Scholar]
  27. 27.
    Murphy RC. 1936.. Oceanic Birds of South America, Vol. 2. New York:: Am. Mus. Nat. Hist.
    [Google Scholar]
  28. 28.
    Piatt JF, Sydeman WJ, Wiese F. 2007.. Introduction: a modern role for seabirds as indicators. . Mar. Ecol. Prog. Ser. 352::199204
    [Crossref] [Google Scholar]
  29. 29.
    Bargu S, Silver MW, Ohman MD, Benitez-Nelson CR, Garrison DL. 2012.. Mystery behind Hitchcock's birds. . Nat. Geosci. 5:(1):23
    [Crossref] [Google Scholar]
  30. 30.
    Marr JS, Calisher CH. 2003.. Alexander the Great and West Nile virus encephalitis. . Emerg. Infect. Dis. 9:(12):1599603
    [Crossref] [Google Scholar]
  31. 31.
    Eidson M, Kramer L, Stone W, Hagiwara Y, Schmit K. 2001.. Dead bird surveillance as an early warning system for West Nile virus. . Emerg. Infect. Dis. 7:(4):63135
    [Crossref] [Google Scholar]
  32. 32.
    Adepoju P. 2022.. Africa's outbreak sentinels. . Nat. Med. 28:(8):151215
    [Crossref] [Google Scholar]
  33. 33.
    Carlson CJ, Albery GF, Merow C, Trisos CH, Zipfel CM, et al. 2022.. Climate change increases cross-species viral transmission risk. . Nature 607:(7919):55562
    [Crossref] [Google Scholar]
  34. 34.
    Morell V. 1999.. Frogs: canaries in the hot zone?. Science 284:(5415):729
    [Crossref] [Google Scholar]
  35. 35.
    Jørgensen LB, Ørsted M, Malte H, Wang T, Overgaard J. 2022.. Extreme escalation of heat failure rates in ectotherms with global warming. . Nature 611:(7934):9398
    [Crossref] [Google Scholar]
  36. 36.
    Wake DB, Vredenburg VT. 2008.. Are we in the midst of the sixth mass extinction? A view from the world of amphibians. . PNAS 105:(Suppl. 1):1146673
    [Crossref] [Google Scholar]
  37. 37.
    Beck AC, Lash EM, Hack JB. 2020.. Environmental toxic exposures using companion animals as an indicator of human toxicity: a case report and discussion. . J. Emerg. Med. 59:(1):e17
    [Crossref] [Google Scholar]
  38. 38.
    Schmidt MF, Wild JM. 2014.. The respiratory-vocal system of songbirds. . Prog. Brain Res. 212::297335
    [Crossref] [Google Scholar]
  39. 39.
    Zhang S, Han Y, Peng J, Chen Y, Zhan L, Li J. 2023.. Human health risk assessment for contaminated sites: a retrospective review. . Environ. Int. 171::107700
    [Crossref] [Google Scholar]
  40. 40.
    McCluskey BJ. 2003.. Use of sentinel herds in monitoring and surveillance systems. . In Animal Disease Surveillance and Survey Systems, ed. MD Salman , pp. 11933. Ames, IA:: Iowa State Press
    [Google Scholar]
  41. 41.
    Harley JR, Gill VA, Lee S, Kannan K, Santana V, et al. 2019.. Concentrations of organohalogens (PCBs, DDTs, PBDEs) in hunted and stranded Northern sea otters (Enhydra lutris kenyoni) in Alaska from 1992 to 2010: links to pathology and feeding ecology. . Sci. Total Environ. 691::78998
    [Crossref] [Google Scholar]
  42. 42.
    Puryear W, Sawatzki K, Hill N, Foss A, Stone JJ, et al. 2023.. Highly pathogenic avian influenza A(H5N1) virus outbreak in New England seals, United States. . Emerg. Infect. Dis. 29:(4):78691
    [Crossref] [Google Scholar]
  43. 43.
    Hu D, Zhu C, Wang Y, Ai L, Yang L, et al. 2017.. Virome analysis for identification of novel mammalian viruses in bats from Southeast China. . Sci. Rep. 7:(1):10917
    [Crossref] [Google Scholar]
  44. 44.
    Baralla E, Demontis MP, Dessì F, Varoni MV. 2021.. An overview of antibiotics as emerging contaminants: occurrence in bivalves as biomonitoring organisms. . Animals 11:(11):3239
    [Crossref] [Google Scholar]
  45. 45.
    Oeschger TM, McCloskey DS, Buchmann RM, Choubal AM, Boza JM, et al. 2021.. Early warning diagnostics for emerging infectious diseases in developing into late-stage pandemics. . Acc. Chem. Res. 54:(19):365666
    [Crossref] [Google Scholar]
  46. 46.
    Rohr JR, Civitello DJ, Halliday FW, Hudson PJ, Lafferty KD, et al. 2020.. Towards common ground in the biodiversity–disease debate. . Nat. Ecol. Evol. 4:(1):2433
    [Crossref] [Google Scholar]
  47. 47.
    Halliday FW, Rohr JR, Laine A. 2020.. Biodiversity loss underlies the dilution effect of biodiversity. . Ecol. Lett. 23:(11):161122
    [Crossref] [Google Scholar]
  48. 48.
    Forman S, Hungerford N, Yamakawa M, Yanase T, Tsai H-J, et al. 2008.. Climate change impacts and risks for animal health in Asia. . Rev. Sci. Tech. 27:(2):58197
    [Crossref] [Google Scholar]
  49. 49.
    Meisner J, Baszler TV, Kuehl KE, Ramirez V, Baines A, et al. 2022.. Household transmission of SARS-CoV-2 from humans to pets, Washington and Idaho, USA. . Emerg. Infect. Dis. 28:(12):242534
    [Crossref] [Google Scholar]
  50. 50.
    Hilborn E, Beasley V. 2015.. One health and cyanobacteria in freshwater systems: animal illnesses and deaths are sentinel events for human health risks. . Toxins 7:(4):137495
    [Crossref] [Google Scholar]
  51. 51.
    Wang Z, Walker GW, Muir DCG, Nagatani-Yoshida K. 2020.. Toward a global understanding of chemical pollution: a first comprehensive analysis of national and regional chemical inventories. . Environ. Sci. Technol. 54:(5):257584
    [Crossref] [Google Scholar]
  52. 52.
    Van Der Schalie WH, Gardner HS, Bantle JA, De Rosa CT, Finch RA, et al. 1999.. Animals as sentinels of human health hazards of environmental chemicals. . Environ. Health Perspect. 107:(4):30915
    [Crossref] [Google Scholar]
  53. 53.
    Gostyukhina OL, Yu AA, Chelebieva ES, Vodiasova EA, Lantushenko AO, Kladchenko ES. 2022.. Adaptive potential of the Mediterranean mussel Mytilus galloprovincialis to short-term environmental hypoxia. . Fish Shellfish Immunol. 131::65461
    [Crossref] [Google Scholar]
  54. 54.
    Kraus RT, Cook HA, Faust MD, Schmitt JD, Rowe MD, Vandergoot CS. 2023.. Habitat selection of a migratory freshwater fish in response to seasonal hypoxia as revealed by acoustic telemetry. . J. Gt. Lakes Res. 49:(5):100414
    [Crossref] [Google Scholar]
  55. 55.
    Costa PR. 2016.. Impact and effects of paralytic shellfish poisoning toxins derived from harmful algal blooms to marine fish. . Fish Fish. 17:(1):22648
    [Crossref] [Google Scholar]
  56. 56.
    Kvrgić K, Lešić T, Džafić N, Pleadin J. 2022.. Occurrence and seasonal monitoring of domoic acid in three shellfish species from the Northern Adriatic Sea. . Toxins 14:(1):33
    [Crossref] [Google Scholar]
  57. 57.
    McClain AM, Field CL, Norris TA, Borremans B, Duignan PJ, et al. 2023.. The symptomatology and diagnosis of domoic acid toxicosis in stranded California sea lions (Zalophus californianus): a review and evaluation of 20 years of cases to guide prognosis. . Front. Vet. Sci. 10::1245864
    [Crossref] [Google Scholar]
  58. 58.
    Levin R, Zilli Vieira CL, Rosenbaum MH, Bischoff K, Mordarski DC, Brown MJ. 2021.. The urban lead (Pb) burden in humans, animals and the natural environment. . Environ. Res. 193::110377
    [Crossref] [Google Scholar]
  59. 59.
    Slabe VA, Anderson JT, Millsap BA, Cooper JL, Harmata AR, et al. 2022.. Demographic implications of lead poisoning for eagles across North America. . Science 375:(6582):77982
    [Crossref] [Google Scholar]
  60. 60.
    Chen X, Cao S, Wen D, Zhang Y, Wang B, Duan X. 2023.. Domestic dogs as sentinels of children lead exposure: multi-pathway identification and source apportionment based on isotope technique. . Chemosphere 316::137787
    [Crossref] [Google Scholar]
  61. 61.
    Blum JD, Drazen JC, Johnson MW, Popp BN, Motta LC, Jamieson AJ. 2020.. Mercury isotopes identify near-surface marine mercury in deep-sea trench biota. . PNAS 117:(47):2929298
    [Crossref] [Google Scholar]
  62. 62.
    Padayachee K, Reynolds C, Mateo R, Amar A. 2023.. A global review of the temporal and spatial patterns of DDT and dieldrin monitoring in raptors. . Sci. Total Environ. 858::159734
    [Crossref] [Google Scholar]
  63. 63.
    Zheng G, Miller P, von Hippel FA, Buck CL, Carpenter DO, Salamova A. 2020.. Legacy and emerging semi-volatile organic compounds in sentinel fish from an arctic formerly used defense site in Alaska. . Environ. Pollut. 259::113872
    [Crossref] [Google Scholar]
  64. 64.
    Wu X, Zheng X, Yu L, Lu R, Zhang Q, et al. 2022.. Biomagnification of persistent organic pollutants from terrestrial and aquatic invertebrates to songbirds: associations with physiochemical and ecological indicators. . Environ. Sci. Technol. 56:(17):122009
    [Crossref] [Google Scholar]
  65. 65.
    Aristizabal-Henao JJ, Brown HJ, Griffin EK, Ostfeld RS, Oggenfuss K, et al. 2021.. Ticks as novel sentinels to monitor environmental levels of per- and polyfluoroalkyl substances (PFAS). . Environ. Sci. Process. Impacts 23:(9):13017
    [Crossref] [Google Scholar]
  66. 66.
    Sun J, Bossi R, Bustnes JO, Helander B, Boertmann D, et al. 2019.. White-tailed eagle (Haliaeetus albicilla) body feathers document spatiotemporal trends of perfluoroalkyl substances in the northern environment. . Environ. Sci. Technol. 53:(21):1274453
    [Crossref] [Google Scholar]
  67. 67.
    López-Berenguer G, Bossi R, Eulaers I, Dietz R, Peñalver J, et al. 2020.. Stranded cetaceans warn of high perfluoroalkyl substance pollution in the western Mediterranean Sea. . Environ. Pollut. 267::115367
    [Crossref] [Google Scholar]
  68. 68.
    Rock KD, Polera ME, Guillette TC, Starnes HM, Dean K, et al. 2023.. Domestic dogs and horses as sentinels of per- and polyfluoroalkyl substance exposure and associated health biomarkers in Gray's Creek North Carolina. . Environ. Sci. Technol. 57:(26):956779
    [Crossref] [Google Scholar]
  69. 69.
    Balmford A. 2013.. Pollution, politics, and vultures. . Science 339:(6120):65354
    [Crossref] [Google Scholar]
  70. 70.
    Santos RG, Machovsky-Capuska GE, Andrades R. 2021.. Plastic ingestion as an evolutionary trap: toward a holistic understanding. . Science 373::5660
    [Crossref] [Google Scholar]
  71. 71.
    Kenyon KW, Kridler E. 1969.. Laysan albatrosses swallow indigestible matter. . Auk 86:(2):33943
    [Crossref] [Google Scholar]
  72. 72.
    Fragão J, Bessa F, Otero V, Barbosa A, Sobral P, et al. 2021.. Microplastics and other anthropogenic particles in Antarctica: using penguins as biological samplers. . Sci. Total Environ. 788::147698
    [Crossref] [Google Scholar]
  73. 73.
    van Franeker JA, Kühn S, Anker-Nilssen T, Edwards EWJ, Gallien F, et al. 2021.. New tools to evaluate plastic ingestion by northern fulmars applied to North Sea monitoring data 2002–2018. . Mar. Pollut. Bull. 166::112246
    [Crossref] [Google Scholar]
  74. 74.
    Savoca MS, Kühn S, Sun C, Avery-Gomm S, Choy CA, et al. 2022.. Towards a North Pacific Ocean long-term monitoring program for plastic pollution: a review and recommendations for plastic ingestion bioindicators. . Environ. Pollut. 310::119861
    [Crossref] [Google Scholar]
  75. 75.
    Duarte CM, Chapuis L, Collin SP, Costa DP, Devassy RP, et al. 2021.. The soundscape of the Anthropocene ocean. . Science 371:(6529):eaba4658
    [Crossref] [Google Scholar]
  76. 76.
    Willems JS, Phillips JN, Francis CD. 2022.. Artificial light at night and anthropogenic noise alter the foraging activity and structure of vertebrate communities. . Sci. Total Environ. 805::150223
    [Crossref] [Google Scholar]
  77. 77.
    Persson L, Almroth BMC, Collins CD, Cornell S, Wit CAD, et al. 2022.. Outside the safe operating space of the planetary boundary for novel entities. . Environ. Sci. Technol. 56:(3):151021
    [Crossref] [Google Scholar]
  78. 78.
    Galappaththi EK, Susarla VB, Loutet SJT, Ichien ST, Hyman AA, Ford JD. 2022.. Climate change adaptation in fisheries. . Fish Fish. 23:(1):421
    [Crossref] [Google Scholar]
  79. 79.
    Steiger R, Knowles N, Pöll K, Rutty M. 2022.. Impacts of climate change on mountain tourism: a review. . J. Sustain. Tour. https://doi.org/10.1080/09669582.2022.2112204
    [Google Scholar]
  80. 80.
    Bauch CT, Sigdel R, Pharaon J, Anand M. 2016.. Early warning signals of regime shifts in coupled human–environment systems. . PNAS 113:(51):1456067
    [Crossref] [Google Scholar]
  81. 81.
    Moore SE. 2008.. Marine mammals as ecosystem sentinels. . J. Mammal. 89:(3):53440
    [Crossref] [Google Scholar]
  82. 82.
    Gulland FMD, Baker JD, Howe M, LaBrecque E, Leach L, et al. 2022.. A review of climate change effects on marine mammals in United States waters: past predictions, observed impacts, current research and conservation imperatives. . Clim. Change Ecol. 3::100054
    [Crossref] [Google Scholar]
  83. 83.
    Szesciorka AR, Stafford KM. 2023.. Sea ice directs changes in bowhead whale phenology through the Bering Strait. . Mov. Ecol. 11:(1):8
    [Crossref] [Google Scholar]
  84. 84.
    Santora JA, Mantua NJ, Schroeder ID, Field JC, Hazen EL, et al. 2020.. Habitat compression and ecosystem shifts as potential links between marine heatwave and record whale entanglements. . Nat. Commun. 11:(1):536
    [Crossref] [Google Scholar]
  85. 85.
    Davies KTA, Brillant SW. 2019.. Mass human-caused mortality spurs federal action to protect endangered North Atlantic right whales in Canada. . Mar. Policy 104::15762
    [Crossref] [Google Scholar]
  86. 86.
    Tepsich P, Schettino I, Atzori F, Azzolin M, Campana I, et al. 2020.. Trends in summer presence of fin whales in the Western Mediterranean Sea region: new insights from a long-term monitoring program. . PeerJ 8::e10544
    [Crossref] [Google Scholar]
  87. 87.
    Berrow S, Whooley P. 2022.. Managing a dynamic North Sea in the light of its ecological dynamics: increasing occurrence of large baleen whales in the southern North Sea. . J. Sea Res. 182::102186
    [Crossref] [Google Scholar]
  88. 88.
    Breitburg D, Levin LA, Oschlies A, Grégoire M, Chavez FP, et al. 2018.. Declining oxygen in the global ocean and coastal waters. . Science 359:(6371):eaam7240
    [Crossref] [Google Scholar]
  89. 89.
    Hodapp D, Roca IT, Fiorentino D, Garilao C, Kaschner K, et al. 2023.. Climate change disrupts core habitats of marine species. . Glob. Change Biol. 29:(12):330417
    [Crossref] [Google Scholar]
  90. 90.
    Critchley EJ, Grecian WJ, Kane A, Jessopp MJ, Quinn JL. 2018.. Marine protected areas show low overlap with projected distributions of seabird populations in Britain and Ireland. . Biol. Conserv. 224::30917
    [Crossref] [Google Scholar]
  91. 91.
    Halupka L, Arlt D, Tolvanen J, Millon A, Bize P, et al. 2023.. The effect of climate change on avian offspring production: a global meta-analysis. . PNAS 120:(19):e2208389120
    [Crossref] [Google Scholar]
  92. 92.
    Olliff-Yang RL, Gardali T, Ackerly DD. 2020.. Mismatch managed? Phenological phase extension as a strategy to manage phenological asynchrony in plant–animal mutualisms. . Restor. Ecol. 28:(3):498505
    [Crossref] [Google Scholar]
  93. 93.
    Dakos V, Matthews B, Hendry AP, Levine J, Loeuille N, et al. 2019.. Ecosystem tipping points in an evolving world. . Nat. Ecol. Evol. 3:(3):35562
    [Crossref] [Google Scholar]
  94. 94.
    Hunsicker ME, Ward EJ, Litzow MA, Anderson SC, Harvey CJ, et al. 2022.. Tracking and forecasting community responses to climate perturbations in the California Current ecosystem. . PLOS Clim. 1:(3):e0000014
    [Crossref] [Google Scholar]
  95. 95.
    Beltran RS, Hernandez KM, Condit R, Robinson PW, Crocker DE, et al. 2023.. Physiological tipping points in the relationship between foraging success and lifetime fitness of a long-lived mammal. . Ecol. Lett. 26:(5):70616
    [Crossref] [Google Scholar]
  96. 96.
    Higa M, Yamaura Y, Senzaki M, Koizumi I, Takenaka T, et al. 2016.. Scale dependency of two endangered charismatic species as biodiversity surrogates. . Biodivers. Conserv. 25::182941
    [Crossref] [Google Scholar]
  97. 97.
    Menon T, Shahabuddin G. 2021.. Assessing woodpeckers as indicators of bird diversity and habitat structure in managed forests. . Biodivers. Conserv. 30:(6):1689704
    [Crossref] [Google Scholar]
  98. 98.
    Law A, Gaywood MJ, Jones KC, Ramsay P, Willby NJ. 2017.. Using ecosystem engineers as tools in habitat restoration and rewilding: beaver and wetlands. . Sci. Total Environ. 605–6::102130
    [Crossref] [Google Scholar]
  99. 99.
    Natsukawa H, Sergio F. 2022.. Top predators as biodiversity indicators: a meta-analysis. . Ecol. Lett. 25:(9):206275
    [Crossref] [Google Scholar]
  100. 100.
    Boykin KG, Kepner WG, McKerrow AJ. 2021.. Applying biodiversity metrics as surrogates to a habitat conservation plan. . Environments 8:(8):69
    [Crossref] [Google Scholar]
  101. 101.
    Askeyev A, Askeyev O, Askeyev I, Monakhov S. 2021.. Predatory fish species as indicators of biodiversity: their distribution in environmental gradients in small and mid-sized rivers in Eastern Europe. . Environ. Biol. Fishes 104:(7):76778
    [Crossref] [Google Scholar]
  102. 102.
    Burgas D, Byholm P, Parkkima T. 2014.. Raptors as surrogates of biodiversity along a landscape gradient. . J. Appl. Ecol. 51:(3):78694
    [Crossref] [Google Scholar]
  103. 103.
    Sergio F, Marchesi L, Pedrini P. 2004.. Integrating individual habitat choices and regional distribution of a biodiversity indicator and top predator. . J. Biogeogr. 31:(4):61928
    [Crossref] [Google Scholar]
  104. 104.
    Drever MC, Aitken KE, Norris AR, Martin K. 2008.. Woodpeckers as reliable indicators of bird richness, forest health and harvest. . Biol. Conserv. 141:(3):62434
    [Crossref] [Google Scholar]
  105. 105.
    Møller AP, Morelli F, Benedetti Y, Mousseau T, Su T, et al. 2017.. Multiple species of cuckoos are superior predictors of bird species richness in Asia. . Ecosphere 8:(11):e02003
    [Crossref] [Google Scholar]
  106. 106.
    Nally RM, Fleishman E. 2004.. A successful predictive model of species richness based on indicator species. . Conserv. Biol. 18:(3):64654
    [Crossref] [Google Scholar]
  107. 107.
    Posdaljian N, Soderstjerna C, Jones JM, Solsona-Berga A, Hildebrand JA, et al. 2022.. Changes in sea ice and range expansion of sperm whales in the eclipse sound region of Baffin Bay, Canada. . Glob. Change Biol. 28:(12):386070
    [Crossref] [Google Scholar]
  108. 108.
    Jachowski DS, Marneweck CJ, Olfenbuttel C, Harris SN. 2024.. Support for the size-mediated sensitivity hypothesis within a diverse carnivore community. . J. Anim. Ecol. 93:(1):10922
    [Crossref] [Google Scholar]
  109. 109.
    Lowry M, Nehasil S, Moore J. 2022.. Spatio-temporal diet variability of the California sea lion Zalophus californianus in the southern California Current Ecosystem. . Mar. Ecol. Prog. Ser. 692::121
    [Crossref] [Google Scholar]
  110. 110.
    Natsukawa H. 2020.. Raptor breeding sites as a surrogate for conserving high avian taxonomic richness and functional diversity in urban ecosystems. . Ecol. Indic. 119::106874
    [Crossref] [Google Scholar]
  111. 111.
    Sydeman WJ, Thompson SA, Piatt JF, García-Reyes M, Zador S, et al. 2017.. Regionalizing indicators for marine ecosystems: Bering Sea–Aleutian Island seabirds, climate, and competitors. . Ecol. Indic. 78::45869
    [Crossref] [Google Scholar]
  112. 112.
    Ellis-Soto D, Wikelski M, Jetz W. 2023.. Animal-borne sensors as a biologically informed lens on a changing climate. . Nat. Clim. Change 13::104254
    [Crossref] [Google Scholar]
  113. 113.
    De Knegt HJ, Eikelboom JAJ, Van Langevelde F, Spruyt WF, Prins HHT. 2021.. Timely poacher detection and localization using sentinel animal movement. . Sci. Rep. 11:(1):4596
    [Crossref] [Google Scholar]
  114. 114.
    Rodhouse TJ, Sergeant CJ, Schweiger EW. 2016.. Ecological monitoring and evidence-based decision-making in America's National Parks: highlights of the Special Feature. . Ecosphere 7:(11):e01608
    [Crossref] [Google Scholar]
  115. 115.
    Ray AM, ed. 2019.. Vital Signs: Monitoring Yellowstone's Ecosystem Health. 27:(1). https://www.nps.gov/articles/upload/Yellowstone-Science-27-1-Vital-Signs_revised.pdf
    [Google Scholar]
  116. 116.
    Ray AM, Murphy MA, Hossack BR. 2022.. Long-term monitoring of a species suite of ecological indicators: a coordinated conservation framework for the Greater Yellowstone Ecosystem. . Ecol. Indic. 137::108774
    [Crossref] [Google Scholar]
  117. 117.
    Yellowstone Center for Resources. 2018.. The State of Yellowstone Vital Signs and Select Park Resources, 2017. Yellowstone National Park, WY:: Yellowstone National Park. https://www.nps.gov/yell/learn/management/upload/Vital-Signs_Report_2017_508_Reduced.pdf
    [Google Scholar]
  118. 118.
    Hansen AJ, Monahan WB, Olliff ST, Theobald DM, eds. 2016.. Climate Change in Wildlands: Pioneering Approaches to Science and Management. Washington, DC:: Island Press. 391 pp.
    [Google Scholar]
  119. 119.
    Hansen AJ, Phillips L. 2018.. Trends in vital signs for Greater Yellowstone: application of a Wildland Health Index. . Ecosphere 9:(8):e02380
    [Crossref] [Google Scholar]
  120. 120.
    Brandt LA, Beauchamp J, Browder JA, Cherkiss M, Clarke A, et al. 2014.. System-wide indicators for Everglades restoration. Unpubl. Tech. Rep. , US DOI Off. Everglades Restoration Initiatives, Davie, FL:
    [Google Scholar]
  121. 121.
    Vargas-Nguyen V, Fries A, Edgerton J, Dennison B, Anderson S, et al. 2022.. Chesapeake Bay and Watershed Report Card. Cambridge, MD:: Univ. Md. Cent. Environ. Sci. Integr. Appl. Netw. https://ian.umces.edu/site/assets/files/30002/2022-chesapeake-bay-and-watershed-report-card.pdf
    [Google Scholar]
  122. 122.
    Ray AM, Hossack BR, Gould WR, Patla DA, Spear SF, et al. 2022.. Multi-species amphibian monitoring across a protected landscape: critical reflections on 15 years of wetland monitoring in Grand Teton and Yellowstone national parks. . Ecol. Indic. 135::108519
    [Crossref] [Google Scholar]
  123. 123.
    Gould WR, Ray AM, Bailey LL, Thoma D, Daley R, Legg K. 2019.. Multistate occupancy modeling improves understanding of amphibian breeding dynamics in the Greater Yellowstone Area. . Ecol. Appl. 29:(1):e01825
    [Crossref] [Google Scholar]
  124. 124.
    Brice EM, Halabisky M, Ray AM. 2022.. Making the leap from ponds to landscapes: integrating field-based monitoring of amphibians and wetlands with satellite observations. . Ecol. Indic. 135::108559
    [Crossref] [Google Scholar]
  125. 125.
    Hossack BR, Gould WR, Patla DA, Muths E, Daley R, et al. 2015.. Trends in Rocky Mountain amphibians and the role of beaver as a keystone species. . Biol. Conserv. 187::26069
    [Crossref] [Google Scholar]
  126. 126.
    Swartz LK, Hossack BR, Muths E, Newell RL, Lowe WH. 2019.. Aquatic macroinvertebrate community responses to wetland mitigation in the Greater Yellowstone Ecosystem. . Freshw. Biol. 64:(5):94253
    [Crossref] [Google Scholar]
  127. 127.
    Oja EB, Swartz LK, Muths E, Hossack BR. 2021.. Amphibian population responses to mitigation: relative importance of wetland age and design. . Ecol. Indic. 131::108123
    [Crossref] [Google Scholar]
  128. 128.
    Levin PS, Fogarty MJ, Murawski SA, Fluharty D. 2009.. Integrated ecosystem assessments: developing the scientific basis for ecosystem-based management of the ocean. . PLOS Biol. 7:(1):e1000014
    [Crossref] [Google Scholar]
  129. 129.
    DePiper GS, Gaichas SK, Lucey SM, Pinto Da Silva P, Anderson MR, et al. 2017.. Operationalizing integrated ecosystem assessments within a multidisciplinary team: lessons learned from a worked example. . ICES J. Mar. Sci. 74:(8):207686
    [Crossref] [Google Scholar]
  130. 130.
    Peterson WT, Fisher JL, Peterson JO, Morgan CA, Burke BJ, Fresh K. 2014.. Applied fisheries oceanography: Ecosystem indicators of ocean conditions inform fisheries management in the California Current. . Oceanography 27:(4):8089
    [Crossref] [Google Scholar]
  131. 131.
    Daly E, Auth T, Brodeur R, Peterson W. 2013.. Winter ichthyoplankton biomass as a predictor of early summer prey fields and survival of juvenile salmon in the northern California Current. . Mar. Ecol. Prog. Ser. 484::20317
    [Crossref] [Google Scholar]
  132. 132.
    Emmett RL, Krutzikowsky GK, Bentley P. 2006.. Abundance and distribution of pelagic piscivorous fishes in the Columbia River plume during spring/early summer 1998–2003: relationship to oceanographic conditions, forage fishes, and juvenile salmonids. . Prog. Oceanogr. 68:(1):126
    [Crossref] [Google Scholar]
  133. 133.
    Wainwright TC. 2021.. Ephemeral relationships in salmon forecasting: a cautionary tale. . Prog. Oceanogr. 193::102522
    [Crossref] [Google Scholar]
  134. 134.
    White EP, Yenni GM, Taylor SD, Christensen EM, Bledsoe EK, et al. 2019.. Developing an automated iterative near-term forecasting system for an ecological study. . Methods Ecol. Evol. 10:(3):33244
    [Crossref] [Google Scholar]
  135. 135.
    Halpern BS, Frazier M, Afflerbach J, O'Hara C, Katona S, et al. 2017.. Drivers and implications of change in global ocean health over the past five years. . PLOS ONE 12:(7):e0178267
    [Crossref] [Google Scholar]
  136. 136.
    Mitchell MS, Cooley H, Gude JA, Kolbe J, Nowak JJ, et al. 2018.. Distinguishing values from science in decision making: setting harvest quotas for mountain lions in Montana. . Wildl. Soc. Bull. 42:(1):1321
    [Crossref] [Google Scholar]
  137. 137.
    Prăvălie R, Sîrodoev I, Nita I-A, Patriche C, Dumitraşcu M, et al. 2022.. NDVI-based ecological dynamics of forest vegetation and its relationship to climate change in Romania during 1987–2018. . Ecol. Indic. 136::108629
    [Crossref] [Google Scholar]
  138. 138.
    Boyer JN, Kelble CR, Ortner PB, Rudnick DT. 2009.. Phytoplankton bloom status: chlorophyll a biomass as an indicator of water quality condition in the southern estuaries of Florida, USA. . Ecol. Indic. 9:(6):S5667
    [Crossref] [Google Scholar]
  139. 139.
    Turner W. 2014.. Sensing biodiversity. . Science 346:(6207):3012
    [Crossref] [Google Scholar]
  140. 140.
    Satterthwaite EV, Allen AE, Lampe RH, Gold Z, Thompson AR, et al. 2023.. Toward identifying the critical ecological habitat of larval fishes: an environmental DNA window into fisheries management. . Oceanography 36:(Suppl. 1):9093
    [Google Scholar]
  141. 141.
    Oestreich WK, Chapman MS, Crowder LB. 2020.. A comparative analysis of dynamic management in marine and terrestrial systems. . Front. Ecol. Environ. 18:(9):496504
    [Crossref] [Google Scholar]
  142. 142.
    Desforges J-P, Hall A, McConnell B, Rosing-Asvid A, Barber JL, et al. 2018.. Predicting global killer whale population collapse from PCB pollution. . Science 361:(6409):137376
    [Crossref] [Google Scholar]
  143. 143.
    Galaz García C, Bagstad KJ, Brun J, Chaplin-Kramer R, Dhu T, et al. 2023.. The future of ecosystem assessments is automation, collaboration, and artificial intelligence. . Environ. Res. Lett. 18::011003
    [Crossref] [Google Scholar]
  144. 144.
    Wilkinson MD, Dumontier M, Aalbersberg IJJ, Appleton G, Axton M, et al. 2016.. The FAIR Guiding Principles for scientific data management and stewardship. . Sci. Data 3:(1):160018
    [Crossref] [Google Scholar]
  145. 145.
    Sun M, Zhao S, Gilvary C, Elemento O, Zhou J, Wang F. 2020.. Graph convolutional networks for computational drug development and discovery. . Brief. Bioinform. 21:(3):91935
    [Crossref] [Google Scholar]
  146. 146.
    Fisher JRB, Wood SA, Bradford MA, Kelsey TR. 2020.. Improving scientific impact: how to practice science that influences environmental policy and management. . Conserv. Sci. Pract. 2:(7):e210
    [Crossref] [Google Scholar]
  147. 147.
    Buxton RT, Nyboer EA, Pigeon KE, Raby GD, Rytwinski T, et al. 2021.. Avoiding wasted research resources in conservation science. . Conserv. Sci. Pract. 3:(2):e329
    [Crossref] [Google Scholar]
  148. 148.
    Roche DG, O'Dea RE, Kerr KA, Rytwinski T, Schuster R, et al. 2022.. Closing the knowledge–action gap in conservation with open science. . Conserv. Biol. 36:(3):e13835
    [Crossref] [Google Scholar]
  149. 149.
    Roche DG, Berberi I, Dhane F, Lauzon F, Soeharjono S, et al. 2022.. Slow improvement to the archiving quality of open datasets shared by researchers in ecology and evolution. . Proc. R. Soc. B 2891975::20212780
    [Crossref] [Google Scholar]
  150. 150.
    Heberling JM, Miller JT, Noesgaard D, Weingart SB, Schigel D. 2021.. Data integration enables global biodiversity synthesis. . PNAS 118:(6):e2018093118
    [Crossref] [Google Scholar]
  151. 151.
    Kays R, Davidson SC, Berger M, Bohrer G, Fiedler W, et al. 2022.. The Movebank system for studying global animal movement and demography. . Methods Ecol. Evol. 13:(2):41931
    [Crossref] [Google Scholar]
  152. 152.
    Davidson SC, Bohrer G, Gurarie E, LaPoint S, Mahoney PJ, et al. 2020.. Ecological insights from three decades of animal movement tracking across a changing Arctic. . Science 370:(6517):71215
    [Crossref] [Google Scholar]
  153. 153.
    Ropert-Coudert Y, Van de Putte AP, Reisinger RR, Bornemann H, Charrassin J-B, et al. 2020.. The retrospective analysis of Antarctic tracking data project. . Sci. Data 7:(1):94
    [Crossref] [Google Scholar]
  154. 154.
    Provencher JF, Covernton GA, Moore RC, Horn DA, Conkle JL, Lusher AL. 2020.. Proceed with caution: the need to raise the publication bar for microplastics research. . Sci. Total Environ. 748::141426
    [Crossref] [Google Scholar]
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