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    The influence of social cues on timing of animal migrations

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

    Google Scholar 
    Bauer, S., Lisovski, S. & Hahn, S. Timing is crucial for consequences of migratory connectivity. Oikos 125, 605–612 (2016).Article 

    Google Scholar 
    Bauer, S. & Hoye, B. J. Migratory animals couple biodiversity and ecosystem functioning worldwide. Science 344, 1242552 (2014).Article 
    CAS 
    PubMed 

    Google Scholar 
    Fricke, E. C., Ordonez, A., Rogers, H. S. & Svenning, J. C. The effects of defaunation on plants’ capacity to track climate change. Science 214, 210–214 (2022).Article 

    Google Scholar 
    Tucker, M. A. et al. Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science 359, 466–469 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Wilcove, D. S. & Wikelski, M. Going, going, gone: is animal migration disappearing? PLoS Biol. 6, e188 (2008).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change. Nature 421, 37–42 (2003).Article 
    CAS 
    PubMed 

    Google Scholar 
    Walther, G. et al. Ecological responses to recent climate change. Nature 4126, 389–395 (2002).Article 

    Google Scholar 
    Teitelbaum, C. S. et al. Experience drives innovation of new migration patterns of whooping cranes in response to global change. Nat. Commun. 7, 12793 (2016).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oestreich, W. K., Chapman, M. S. & Crowder, L. B. A comparative analysis of dynamic management in marine and terrestrial systems. Front. Ecol. Environ. 18, 496–504 (2020).Article 

    Google Scholar 
    Senzaki, M. et al. Sensory pollutants alter bird phenology and fitness across a continent. Nature 587, 605–609 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Guerra, A. S. Wolves of the sea: managing human–wildlife conflict in an increasingly tense ocean. Mar. Policy 99, 369–373 (2019).Article 

    Google Scholar 
    Abrahms, B. Human–wildlife conflict under climate change. Science 373, 484–485 (2021).Article 
    CAS 
    PubMed 

    Google Scholar 
    Both, C., Bouwhuis, S., Lessells, C. M. & Visser, M. E. Climate change and population declines in a long-distance migratory bird. Nature 441, 81–83 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Post, E. & Forchhammer, M. C. Climate change reduces reproductive success of an Arctic herbivore through trophic mismatch. Phil. Trans. R. Soc. B Biol. Sci. 363, 2369–2375 (2008).Article 

    Google Scholar 
    Winkler, D. W. et al. Cues, strategies, and outcomes: how migrating vertebrates track environmental change. Mov. Ecol. 2, 10 (2014).Article 

    Google Scholar 
    Xu, W. et al. The plasticity of ungulate migration in a changing world. Ecology 102, e03293 (2021).Article 
    PubMed 

    Google Scholar 
    McNamara, J. M., Barta, Z., Klaassen, M. & Bauer, S. Cues and the optimal timing of activities under environmental change. Ecol. Lett. 14, 1183–1190 (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bauer, S., McNamara, J. M. & Barta, Z. Environmental variability, reliability of information and the timing of migration. Proc. R. Soc. B Biol. Sci. 287, 20200622 (2020).Article 

    Google Scholar 
    Abrahms, B. et al. Emerging perspectives on resource tracking and animal movement ecology. Trends Ecol. Evol. 36, 308–320 (2020).Article 
    PubMed 

    Google Scholar 
    Visser, M. E., Holleman, L. J. M. & Gienapp, P. Shifts in caterpillar biomass phenology due to climate change and its impact on the breeding biology of an insectivorous bird. Oecologia 147, 164–172 (2006).Article 
    PubMed 

    Google Scholar 
    Aikens, E. O. et al. Wave-like patterns of plant phenology determine ungulate movement tactics. Curr. Biol. 30, 3444–3449 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Abrahms, B. et al. Memory and resource tracking drive blue whale migrations. Proc. Natl Acad. Sci. USA 116, 5582–5587 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lank, D. B., Butler, R. W., Ireland, J. & Ydenberg, R. C. Effects of predation danger on migration strategies of sandpipers. Oikos 103, 303–319 (2003).Article 

    Google Scholar 
    Sabal, M. C. et al. Predation landscapes influence migratory prey ecology and evolution. Trends Ecol. Evol. 36, 737–749 (2021).Article 
    PubMed 

    Google Scholar 
    Furey, N. B., Armstrong, J. B., Beauchamp, D. A. & Hinch, S. G. Migratory coupling between predators and prey. Nat. Ecol. Evol. 2, 1846–1853 (2018).Article 
    PubMed 

    Google Scholar 
    Altizer, S., Bartel, R. & Han, B. A. Animal migration and infectious disease risk. Science 331, 296–302 (2011).Article 
    CAS 
    PubMed 

    Google Scholar 
    Gunnarsson, T., Gill, J., Sigurbjörnsson, T. & Sutherland, W. Arrival synchrony in migratory birds. Nature 431, 646 (2004).Article 
    CAS 
    PubMed 

    Google Scholar 
    Beltran, R. S. et al. Elephant seals time their long-distance migration using a map sense. Curr. Biol. 32, R156–R157 (2022).Article 
    CAS 
    PubMed 

    Google Scholar 
    Yang, L. H. & Rudolf, V. H. W. Phenology, ontogeny and the effects of climate change on the timing of species interactions. Ecol. Lett. 13, 1–10 (2010).Article 
    CAS 
    PubMed 

    Google Scholar 
    Visser, M. E. & Gienapp, P. Evolutionary and demographic consequences of phenological mismatches. Nat. Ecol. Evol. 3, 879–885 (2019).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Furey, N. B. et al. Predator swamping reduces predation risk during nocturnal migration of juvenile salmon in a high-mortality landscape. J. Anim. Ecol. 85, 948–959 (2016).Article 
    PubMed 

    Google Scholar 
    Rickbeil, G. J. M. et al. Plasticity in elk migration timing is a response to changing environmental conditions. Glob. Change Biol. 25, 2368–2381 (2019).Article 

    Google Scholar 
    Schmaljohann, H. & Both, C. The limits of modifying migration speed to adjust to climate change. Nat. Clim. Change 7, 573–576 (2017).Article 

    Google Scholar 
    Gwinner, E. Circadian and circannual programmes in avian migration. J. Exp. Biol. 199, 39–48 (1996).Article 
    CAS 
    PubMed 

    Google Scholar 
    Liedvogel, M., Åkesson, S. & Bensch, S. The genetics of migration on the move. Trends Ecol. Evol. 26, 561–569 (2011).Article 
    PubMed 

    Google Scholar 
    Hauser, D. D. W. et al. Decadal shifts in autumn migration timing by Pacific Arctic beluga whales are related to delayed annual sea ice formation. Glob. Change Biol. 23, 2206–2217 (2017).Article 

    Google Scholar 
    Palacín, C., Alonso, J. C., Alonso, J. A., Magaña, M. & Martín, C. A. Cultural transmission and flexibility of partial migration patterns in a long-lived bird, the great bustard Otis tarda. J. Avian Biol. 42, 301–308 (2011).Article 

    Google Scholar 
    Couzin, I. D. Collective animal migration. Curr. Biol. 28, R976–R980 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Guttal, V. & Couzin, I. D. Social interactions, information use, and the evolution of collective migration. Proc. Natl Acad. Sci. USA 107, 16172–16177 (2010).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Berdahl, A. M. et al. Collective animal navigation and migratory culture: from theoretical models to empirical evidence. Phil. Trans. R. Soc. B Biol. Sci. 373, 20170009 (2018).Article 

    Google Scholar 
    Cohen, E. B. & Satterfield, D. A. ‘Chancing on a spectacle:’ co-occurring animal migrations and interspecific interactions. Ecography 43, 1657–1671 (2020).Article 

    Google Scholar 
    Berdahl, A., Torney, C. J., Ioannou, C. C., Faria, J. J. & Couzin, I. D. Emergent sensing of complex environments by mobile animal groups. Science 339, 574–576 (2013).Article 
    CAS 
    PubMed 

    Google Scholar 
    Abrahms, B., Teitelbaum, C. S., Mueller, T. & Converse, S. J. Ontogenetic shifts from social to experiential learning drive avian migration timing. Nat. Commun. 12, 7326 (2021).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sasaki, T. & Biro, D. Cumulative culture can emerge from collective intelligence in animal groups. Nat. Commun. 8, 15049 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Helm, B., Piersma, T. & van der Jeugd, H. Sociable schedules: interplay between avian seasonal and social behaviour. Anim. Behav. 72, 245–262 (2006).Article 

    Google Scholar 
    Piersma, T., Zwarts, L. & Bruggemann, J. H. Behavioural aspects of the departure of waders before long-distance flights: flocking, vocalizations, flight paths and diurnal timing. Ardea 78, 157–184 (1990).
    Google Scholar 
    Dingle, H. & Drake, V. A. What is migration? BioScience 57, 113–121 (2007).Article 

    Google Scholar 
    Oestreich, W. K. & Aiu, K. M. Code and data from: The influence of social cues on timing of animal migrations. Zenodo https://zenodo.org/record/6574762 (2022).Furey, N. B., Martins, E. G. & Hinch, S. G. Migratory salmon smolts exhibit consistent interannual depensatory predator swamping: effects on telemetry-based survival estimates. Ecol. Freshw. Fish 30, 18–30 (2021).Article 

    Google Scholar 
    Berdahl, A., Westley, P. A. H. & Quinn, T. P. Social interactions shape the timing of spawning migrations in an anadromous fish. Anim. Behav. 126, 221–229 (2017).Article 

    Google Scholar 
    Louca, V., Lindsay, S. W. & Lucas, M. C. Factors triggering floodplain fish emigration: importance of fish density and food availability. Ecol. Freshw. Fish 18, 60–64 (2009).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bastille-Rousseau, G. et al. Migration triggers in a large herbivore: Galápagos giant tortoises navigating resource gradients on volcanoes. Ecology 100, e02658 (2019).Article 
    PubMed 

    Google Scholar 
    Bracis, C. & Mueller, T. Memory, not just perception, plays an important role in terrestrial mammalian migration. Proc. R. Soc. B Biol. Sci. 284, 20170449 (2017).Article 

    Google Scholar 
    Barrett, B., Zepeda, E., Pollack, L., Munson, A. & Sih, A. Counter-culture: does social learning help or hinder adaptive response to human-induced rapid environmental change? Front. Ecol. Evol. 7, 183 (2019).Article 

    Google Scholar 
    Merkle, J. A. et al. Site fidelity as a maladaptive behavior in the Anthropocene. Front. Ecol. Environ. 20, 187–194 (2022).Article 

    Google Scholar 
    Teske, P. R. et al. The sardine run in southeastern Africa is a mass migration into an ecological trap. Sci. Adv. 7, eabf4514 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Corten, A. The role of ‘conservatism’ in herring migrations. Rev. Fish Biol. Fish. 11, 339–361 (2002).Article 

    Google Scholar 
    Mukhin, A., Chernetsov, N. & Kishkinev, D. Acoustic information as a distant cue for habitat recognition by nocturnally migrating passerines during landfall. Behav. Ecol. 19, 716–723 (2008).Article 

    Google Scholar 
    Barker, K. J. et al. Toward a new framework for restoring lost wildlife migrations. Conserv. Lett. 15, e12850 (2022).Article 

    Google Scholar 
    Teitelbaum, C. S., Converse, S. J. & Mueller, T. The importance of early life experience and animal cultures in reintroductions. Conserv. Lett. 12, e12599 (2019).Article 

    Google Scholar 
    Hughey, L. F., Hein, A. M., Strandburg-Peshkin, A., Jensen, F. H. & Hughey, L. F. Challenges and solutions for studying collective animal behaviour in the wild. Phil. Trans. R. Soc. B 373, 20170005 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Calabrese, J. M. et al. Disentangling social interactions and environmental drivers in multi-individual wildlife tracking data. Phil. Trans. R. Soc. B 373, 20170007 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jesmer, B. R. et al. Is ungulate migration culturally transmitted? Evidence of social learning from translocated animals. Science 361, 1023–1025 (2018).Article 
    CAS 
    PubMed 

    Google Scholar 
    Bousquet, C. A. H., Sumpter, D. J. T. & Manser, M. B. Moving calls: a vocal mechanism underlying quorum decisions in cohesive groups. Proc. R. Soc. B Biol. Sci. 278, 1482–1488 (2011).Article 

    Google Scholar 
    Dibnah, A. J. et al. Vocally mediated consensus decisions govern mass departures from jackdaw roosts. Curr. Biol. 32, R455–R456 (2022).Article 
    CAS 
    PubMed 

    Google Scholar 
    Robart, A. R., Zuñiga, H. X., Navarro, G. & Watts, H. E. Social environment influences termination of nomadic migration. Biol. Lett. 18, 20220006 (2022).Article 
    PubMed 

    Google Scholar 
    Dodson, S., Abrahms, B., Bograd, S. J., Fiechter, J. & Hazen, E. L. Disentangling the biotic and abiotic drivers of emergent migratory behavior using individual-based models. Ecol. Modell. 432, 109225 (2020).Article 

    Google Scholar 
    Kays, R., Crofoot, M. C., Jetz, W. & Wikelski, M. Terrestrial animal tracking as an eye on life and planet. Science 348, aaa2478 (2015).Article 
    PubMed 

    Google Scholar 
    Hussey, N. E. et al. Aquatic animal telemetry: a panoramic window into the underwater world. Science 348, 1255642 (2015).Article 
    PubMed 

    Google Scholar 
    Oestreich, W. K. et al. Acoustic signature reveals blue whale tune life history transitions to oceanographic conditions. Funct. Ecol. 36, 882–895 (2022).Article 
    CAS 

    Google Scholar 
    Chapman, J. W., Reynolds, D. R. & Smith, A. D. Vertical-looking radar: a new tool for monitoring high-altitude insect migration. BioScience 53, 503–511 (2003).Article 

    Google Scholar 
    Oestreich, W. K. et al. Animal-borne metrics enable acoustic detection of blue whale migration. Curr. Biol. 30, 4773–4779 (2020).Article 
    CAS 
    PubMed 

    Google Scholar 
    Fraser, K. C., Shave, A., de Greef, E., Siegrist, J. & Garroway, C. J. Individual variability in migration timing can explain long-term, population-level advances in a songbird. Front. Ecol. Evol. 7, 324 (2019).Article 

    Google Scholar 
    Byholm, P., Beal, M., Isaksson, N., Lötberg, U. & Åkesson, S. Paternal transmission of migration knowledge in a long-distance bird migrant. Nat. Commun. 13, 1566 (2022).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schneider, S. S. & McNally, L. C. Waggle dance behavior associated with seasonal absconding in colonies of the African honey bee, Apis mellifera scutellata. Insectes Soc. 41, 115–127 (1994).Article 

    Google Scholar 
    Raveling, D. G. Preflight and flight behavior of Canada geese. Auk 86, 671–681 (1969).Article 

    Google Scholar 
    Tennessen, J. B., Parks, S. E. & Langkilde, T. Traffic noise causes physiological stress and impairs breeding migration behaviour in frogs. Conserv. Physiol. 2, cou032 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lagarde, A., Lagarde, F. & Piersma, T. Vocal signalling by Eurasian spoonbills Platalea leucorodia in flocks before migratory departure. Ardea 109, 243–250 (2021).Article 

    Google Scholar 
    Rees, E. C. Conflict of choice within pairs of Bewick’s swans regarding their migratory movement to and from the wintering grounds. Anim. Behav. 35, 1685–1693 (1987).Article 

    Google Scholar 
    Mazeroll, A. I. & Montgomery, W. L. Daily migrations of a coral reef fish in the Red Sea (Gulf of Aqaba, Israel). Copiea 1998, 893–905 (1998).Article 

    Google Scholar 
    Méndez, V. et al. Paternal effects in the initiation of migratory behaviour in birds. Sci. Rep. 11, 2782 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nelson, M. E. Development of migratory behavior in northern white-tailed deer. Can. J. Zool. 76, 426–432 (1998).Article 

    Google Scholar 
    Sweanor, P. Y. & Sandgren, F. Winter-range philopatry of seasonally migratory moose. J. Appl. Ecol. 26, 25–33 (1989).Article 

    Google Scholar 
    Rees, E. C. Consistency in the timing of migration for individual Bewick’s swans. Anim. Behav. 38, 384–393 (1989).Article 

    Google Scholar 
    Corten, A. A possible adaptation of herring feeding migrations to a change in timing of the Calanus finmarchicus season in the eastern North Sea. ICES J. Mar. Sci. 57, 1261–1270 (2000).Article 

    Google Scholar 
    Loonstra, A. J. et al. Individual black-tailed godwits do not stick to single routes: a hypothesis on how low population densities might decrease social conformity. Ardea 107, 251–261 (2020).Article 

    Google Scholar 
    Hake, M., Kjellén, N. & Alerstam, T. Age‐dependent migration strategy in honey buzzards Pernis apivorus tracked by satellite. Oikos 103, 385–396 (2003).Article 

    Google Scholar 
    Gupte, P. R., Koffijberg, K., Müskens, G. J. D. M., Wikelski, M. & Kölzsch, A. Family size dynamics in wintering geese. J. Ornithol. 160, 363–375 (2019).Article 

    Google Scholar 
    Gonçalves, M. I. C. et al. Movement patterns of humpback whales (Megaptera novaeangliae) reoccupying a Brazilian breeding ground. Biota Neotrop. 18, e20180567 (2018).Article 

    Google Scholar 
    Trudelle, L. et al. First insights on spatial and temporal distribution patterns of humpback whales in the breeding ground at Sainte Marie Channel, Madagascar. Afr. J. Mar. Sci. 40, 75–86 (2018).Article 

    Google Scholar 
    De La Gala-Hernández, S. R., Heckel, G. & Sumich, J. L. Comparative swimming effort of migrating gray whales (Eschrichtius robustus) and calf cost of transport along Costa Azul, Baja California, Mexico. Can. J. Zool. 86, 307–313 (2008).Article 

    Google Scholar 
    Sword, G. A. Local population density and the activation of movement in migratory band-forming Mormon crickets. Anim. Behav. 69, 437–444 (2005).Article 

    Google Scholar 
    Buhl, J. et al. From disorder to order in marching locusts. Science 312, 1402–1406 (2006).Article 
    CAS 
    PubMed 

    Google Scholar 
    Mysterud, A., Loe, L. E., Zimmermann, B., Bischof, R. & Meisingset, E. Partial migration in expanding red deer populations at northern latitudes—a role for density dependence? Oikos 120, 1817–1825 (2011).Article 

    Google Scholar 
    Bukreeva, O. M. & Lidzhi-garyaeva, G. V. Mass migration of social voles (Microtus socialis Pallas, 1773) in the Northwestern Caspian region. Arid Ecosyst. 8, 147–151 (2018).Article 

    Google Scholar 
    Eggeman, S. L., Hebblewhite, M., Bohm, H., Whittington, J. & Merrill, E. H. Behavioural flexibility in migratory behaviour in a long-lived large herbivore. J. Anim. Ecol. 85, 785–797 (2016).Article 
    PubMed 

    Google Scholar 
    Weithman, C. et al. Senescence and carryover effects of reproductive performance influence migration, condition, and breeding propensity in a small shorebird. Ecol. Evol. 7, 11044–11056 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rappole, J. H. & Warner, D. W. Relationships between behavior, physiology and weather in avian transients at a migration stopover site. Oecologia 212, 193–212 (1976).Article 

    Google Scholar 
    Fauchald, P., Mauritzen, M. & Gjøsæter, H. Density‐dependent migratory waves in the marine pelagic ecosystem. Ecology 87, 2915–2924 (2006).Article 
    PubMed 

    Google Scholar 
    Makris, N. C. et al. Critical population density triggers rapid formation of vast oceanic fish shoals. Science 323, 1734–1737 (2009).Article 
    CAS 
    PubMed 

    Google Scholar 
    Tøttrup, A. P. & Thorup, K. Sex-differentiated migration patterns, protandry and phenology in North European songbird populations. J. Ornithol. 149, 161–167 (2008).Article 

    Google Scholar 
    Francis, C. M. & Cooke, C. F. Differential timing of spring migration in rose-breasted grosbeaks. J. Field Ornithol. 61, 404–412 (1990).
    Google Scholar 
    Corgos, A., Verísimo, P. & Freire, J. Timing and seasonality of the terminal molt and mating migration in the spider crab, Maja brachydactyla: evidence of alternative mating strategies. J. Shellfish Res. 25, 577–587 (2006).Article 

    Google Scholar 
    Gordo, O., Sanz, J. J. & Lobo, J. M. Spatial patterns of white stork (Ciconia ciconia) migratory phenology in the Iberian Peninsula. J. Ornithol. 148, 293–308 (2007).Article 

    Google Scholar 
    Sergio, F. et al. Individual improvements and selective mortality shape lifelong migratory performance. Nature 515, 410–413 (2014).Article 
    CAS 
    PubMed 

    Google Scholar 
    Manica, L. T., Graves, J. A., Podos, J. & Macedo, R. H. Hidden leks in a migratory songbird: mating advantages for earlier and more attractive males. Behav. Ecol. 31, 1180–1191 (2020).Article 

    Google Scholar 
    Cade, D. E. et al. Social exploitation of extensive, ephemeral, environmentally controlled prey patches by supergroups of rorqual whales. Anim. Behav. 182, 251–266 (2021).Article 

    Google Scholar 
    Urbanek, R. P., Fondow, L. E. A., Zimorski, S. E., Wellington, M. A. & Nipper, M. A. Winter release and management of reintroduced migratory whooping cranes Grus americana. Bird Conserv. Int. 20, 43–54 (2010).Article 

    Google Scholar 
    Németh, Z. & Moore, F. R. Information acquisition during migration: a social perspective. Auk 131, 186–194 (2014).Article 

    Google Scholar  More

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    Lessons from COVID-19 for wildlife ranching in a changing world

    Pascual, U. et al. Biodiversity and the challenge of pluralism. Nat. Sustain. 4, 567–572 (2021).Article 

    Google Scholar 
    Cumming, G. S. The relevance and resilience of protected areas in the Anthropocene. Anthropocene 13, 46–56 (2016).Article 

    Google Scholar 
    Cumming, G. S. et al. Understanding protected area resilience: a multi-scale, social-ecological approach. Ecol. Appl. 25, 299–319 (2015).Article 

    Google Scholar 
    Ellis, E. C. & Mehrabi, Z. Half Earth: promises, pitfalls, and prospects of dedicating half of Earth’s land to conservation. Curr. Opin. Environ. Sustain. 38, 22–30 (2019).Article 

    Google Scholar 
    Golden Kroner, R. E. et al. The uncertain future of protected lands and waters. Science 364, 881–886 (2019).Article 
    CAS 

    Google Scholar 
    Palfrey, R., Oldekop, J. & Holmes, G. Conservation and social outcomes of private protected areas. Conserv. Biol. 35, 1098–1110 (2021).Article 

    Google Scholar 
    Gurney, G. G. et al. Biodiversity needs every tool in the box: use OECMs. Nature 595, 646–649 (2021).Article 
    CAS 

    Google Scholar 
    Kremen, C. & Merenlender, A. M. Landscapes that work for biodiversity and people. Science 362, eaau6020 (2018).Article 

    Google Scholar 
    Taylor, W. A. et al. South Africa’s private wildlife ranches protect globally significant populations of wild ungulates. Biodivers. Conserv. 30, 4111–4135 (2021).Article 

    Google Scholar 
    Child, B. A., Musengezi, J., Parent, G. D. & Child, G. F. T. The economics and institutional economics of wildlife on private land in Africa. Pastoralism 2, 18 (2012).Article 

    Google Scholar 
    Kiffner, C. et al. Community-based wildlife management area supports similar mammal species richness and densities compared to a national park. Ecol. Evol. 10, 480–492 (2020).Article 

    Google Scholar 
    Naidoo, R. et al. Complementary benefits of tourism and hunting to communal conservancies in Namibia. Conserv. Biol. 30, 628–638 (2016).Article 

    Google Scholar 
    Cousins, J., Sadler, J. & Evans, J. Exploring the role of private wildlife ranching as a conservation tool in South Africa: stakeholder perspectives. Ecol. Soc. 13, 43 (2008).Article 

    Google Scholar 
    Kamal, S., Grodzińska-Jurczak, M. & Brown, G. Conservation on private land: a review of global strategies with a proposed classification system. J. Environ. Plann. Manage. 58, 576–597 (2015).Article 

    Google Scholar 
    Ogar, E., Pecl, G. & Mustonen, T. Science must embrace traditional and indigenous knowledge to solve our biodiversity crisis. One Earth 3, 162–165 (2020).Article 

    Google Scholar 
    De Vos, A. & Cumming, G. S. The contribution of land tenure diversity to the spatial resilience of protected area networks. People Nat. 1, 331–346 (2019).Article 

    Google Scholar 
    Biggs, R. et al. Toward principles for enhancing the resilience of ecosystem services. Annu. Rev. Environ. Resour. 37, 421–448 (2012).Article 

    Google Scholar 
    Cumming, G. & Collier, J. Change and identity in complex systems. Ecol. Soc. 10, 29 (2005).Article 

    Google Scholar 
    Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30, 673–684 (2015).Article 

    Google Scholar 
    Leslie, P. & McCabe, J. T. Response diversity and resilience in social–ecological systems. Curr. Anthropol. 54, 114–143 (2013).Article 

    Google Scholar 
    Clements, H. S., Knight, M., Jones, P. & Balfour, D. Private rhino conservation: diverse strategies adopted in response to the poaching crisis. Conserv. Lett. 13, e12741 (2020).Article 

    Google Scholar 
    Carpenter, S., Walker, B., Anderies, J. M. & Abel, N. From metaphor to measurement: resilience of what to what? Ecosystems 4, 765–781 (2001).Article 

    Google Scholar 
    Parker, K., De Vos, A., Clements, H. S., Biggs, D. & Biggs, R. Impacts of a trophy hunting ban on private land conservation in South African biodiversity hotspots. Conserv. Sci. Pract. 2, e214 (2020).
    Google Scholar 
    World Travel & Tourism Council. The Economic Impact of Global Wildlife Tourism (WTTC, 2019).Lindsey, P. et al. Conserving Africa’s wildlife and wildlands through the COVID-19 crisis and beyond. Nat. Ecol. Evol. 4, 1300–1310 (2020).Article 

    Google Scholar 
    Hambira, W. L., Stone, L. S. & Pagiwa, V. Botswana nature-based tourism and COVID-19: transformational implications for the future. Dev. South. Afr. 39, 51–67 (2021).Article 

    Google Scholar 
    Mudzengi, B. K., Gandiwa, E., Muboko, N. & Mutanga, C. N. Innovative community ecotourism coping and recovery strategies to COVID-19 pandemic shocks: the case of Mahenye. Dev. South. Afr. 39, 68–83 (2021).Article 

    Google Scholar 
    Waithaka, J. et al. Impacts of COVID-19 on protected and conserved areas: a global overview and regional perspectives. Parks 27, 41–56 (2021).Article 

    Google Scholar 
    Smith, M. K. S. et al. Sustainability of protected areas: vulnerabilities and opportunities as revealed by COVID-19 in a national park management agency. Biol. Conserv. 255, 108985 (2021).Article 

    Google Scholar 
    Miller-Rushing, A. J. et al. COVID-19 pandemic impacts on conservation research, management, and public engagement in US national parks. Biol. Conserv. 257, 109038 (2021).Article 

    Google Scholar 
    Thurstan, R. H. et al. Envisioning a resilient future for biodiversity conservation in the wake of the COVID‐19 pandemic. People Nat. 3, 990–1013 (2021).Article 

    Google Scholar 
    Taylor, W. A., Lindsey, P. A., Nicholson, S. K., Relton, C. & Davies-Mostert, H. T. Jobs, game meat and profits: the benefits of wildlife ranching on marginal lands in South Africa. Biol. Conserv. 245, 108561 (2020).Article 

    Google Scholar 
    Chidakel, A., Eb, C. & Child, B. The comparative financial and economic performance of protected areas in the Greater Kruger National Park, South Africa: functional diversity and resilience in the socio-economics of a landscape-scale reserve network.J. Sustain. Tour. 28, 1100–1119 (2020).Article 

    Google Scholar 
    Saayman, M., van der Merwe, P. & Saayman, A. The economic impact of trophy hunting in the South African wildlife industry. Glob. Ecol. Conserv. 16, e00510 (2018).Article 

    Google Scholar 
    Hall, R. A political economy of land reform in South Africa. Rev. Afr. Polit. Econ. 31, 213–227 (2004).Article 

    Google Scholar 
    Mkhize, N. Game farm conversions and the land question: unpacking present contradictions and historical continuities in farm dwellers’ tenure insecurity in Cradock. J. Contemp. Afr. Stud. 32, 207–219 (2014).Article 

    Google Scholar 
    Thakholi, L. Conservation labour geographies: subsuming regional labour into private conservation spaces in South Africa. Geoforum 123, 1–11 (2021).Article 

    Google Scholar 
    Brandt, F. Power battles on South African trophy-hunting farms: farm workers, resistance and mobility in the Karoo. J. Contemp. Afr. Stud. 34, 165–181 (2016).Article 

    Google Scholar 
    Child, B. & Barnes, G. The conceptual evolution and practice of community-based natural resource management in southern Africa: past, present and future. Environ. Conserv. 37, 283–295 (2010).Article 

    Google Scholar 
    Clements, H. S., Baum, J. & Cumming, G. S. Money and motives: an organizational ecology perspective on private land conservation. Biol. Conserv. 197, 108–115 (2016).Article 

    Google Scholar 
    van der Merwe, P., Saayman, A. & Jacobs, C. Assessing the economic impact of COVID-19 on the private wildlife industry of South Africa. Glob. Ecol. Conserv. 28, e01633 (2021).Article 

    Google Scholar 
    Clements, H. S. & Cumming, G. S. Traps and transformations influencing the financial viability of tourism on private-land conservation areas. Conserv. Biol. 32, 424–436 (2018).Article 

    Google Scholar 
    Winterbach, C. W., Whitesell, C. & Somers, M. J. Wildlife abundance and diversity as indicators of tourism potential in northern Botswana. PLoS ONE 10, e0135595 (2015).Article 

    Google Scholar 
    Di Minin, E., Fraser, I., Slotow, R. & MacMillan, D. C. Understanding heterogeneous preference of tourists for big game species: implications for conservation and management. Anim. Conserv. 16, 249–258 (2013).Article 

    Google Scholar 
    Clements, H. S., Biggs, R. & Cumming, G. S. Cross-scale and social–ecological changes constitute main threats to private land conservation in South Africa. J. Environ. Manag. 274, 111235 (2020).Article 

    Google Scholar 
    Breen, C. et al. Integrating cultural and natural heritage approaches to marine protected areas in the MENA region. Mar. Policy 132, 104676 (2021).Article 

    Google Scholar 
    Munasinghe, H. The politics of the past: constructing a national identity through heritage conservation. Int. J. Herit. Stud. 11, 251–260 (2005).Article 

    Google Scholar 
    MacKinnon, K. et al. Strengthening the global system of protected areas post-2020: a perspective from the IUCN World Commission on Protected Areas. Parks 36, 281–296 (2020).
    Google Scholar 
    van Kerkhoff, L. et al. Towards future-oriented conservation: managing protected areas in an era of climate change. Ambio 48, 699–713 (2019).Article 

    Google Scholar 
    De Vos, A. et al. Pathogens, disease, and the social–ecological resilience of protected areas. Ecol. Soc. 21, 20 (2016).Article 

    Google Scholar 
    Bengtsson, J. et al. Reserves, resilience and dynamic landscapes. Ambio 32, 389–396 (2003).Article 

    Google Scholar 
    Broom, D. M., Galindo, F. A. & Murgueitio, E. Sustainable, efficient livestock production with high biodiversity and good welfare for animals. Proc. R. Soc. B 280, 20132025 (2013).Article 
    CAS 

    Google Scholar 
    IPBES Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2019).Marnewick, D., Jonas, H. & Stevens, C. Site-level Methodology for Identifying Other Effective Area-based Conservation Measures (OECMs) Draft Version 1.0 (IUCN: Gland, Switzerland; 2020).Nalau, J., Becken, S. & Mackey, B. Ecosystem-based adaptation: a review of the constraints. Environ. Sci. Policy 89, 357–364 (2018).Article 

    Google Scholar 
    Hartung, C. et al. Open Data Kit: tools to build information services for developing regions. In Proc. 4th ACM/IEEE International Conference on Information and Communication Technologies and Development (ed Unwin, T.) pp 1–12 (Association for Computing Machinery, New York, NY, United States; 2010).Oksanen, A. J. et al. Vegan: Community Ecology Package. R version 2.6–2 (2022). https://cran.r-project.org/web/packages/vegan/vegan.pdfWard, J. Hierarchical grouping to optimize an objective function. J. Am. Stat. Assoc. 58, 236–244 (1963).Article 

    Google Scholar 
    Maechler, M. et al. Cluster: Finding Groups in Data. R version 2.0.3 (2015). https://cran.microsoft.com/snapshot/2015-11-17/web/packages/cluster/cluster.pdfR Core Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021). More

  • in

    The environmental footprint of global food production

    Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).Article 
    CAS 

    Google Scholar 
    Godfray, H. C. J. et al. Meat consumption, health, and the environment. Science 361, eaam5324 (2018).Article 

    Google Scholar 
    Hicks, C. C. et al. Harnessing global fisheries to tackle micronutrient deficiencies. Nature 574, 95–98 (2019).Article 
    CAS 

    Google Scholar 
    Willett, W. et al. Food in the Anthropocene: the EAT–Lancet Commission on healthy diets from sustainable food systems. Lancet 393, 447–492 (2019).Article 

    Google Scholar 
    Maxwell, S. L., Fuller, R. A., Brooks, T. M. & Watson, J. E. M. Biodiversity: the ravages of guns, nets and bulldozers. Nature 536, 143–145 (2016).Article 
    CAS 

    Google Scholar 
    Tilman, D. et al. Future threats to biodiversity and pathways to their prevention. Nature 546, 73–81 (2017).Article 
    CAS 

    Google Scholar 
    Ellis, E. C., Goldewikj, K. K., Siebert, S., Lightman, D. & Ramankutty, N. Anthropogenic transformation of the biomes, 1700 to 2000. Glob. Ecol. Biogeogr. 19, 589–606 (2010).
    Google Scholar 
    Crippa, M. et al. Food systems are responsible for a third of global anthropogenic GHG emissions. Nat. Food 2, 198–209 (2021).Article 
    CAS 

    Google Scholar 
    Rosegrant, M. W., Ringler, C. & Zhu, T. Water for agriculture: maintaining food security under growing scarcity. Annu. Rev. Environ. Resour. 34, 205–222 (2009).Article 

    Google Scholar 
    Tubiello, F. N. et al. The contribution of agriculture, forestry and other land use activities to global warming, 1990–2012. Glob. Change Biol. 21, 2655–2660 (2015).Article 

    Google Scholar 
    Lee, R. Y., Seitzinger, S. & Mayorga, E. Land-based nutrient loading to LMEs: a global watershed perspective on magnitudes and sources. Environ. Dev. 17, 220–229 (2016).Article 

    Google Scholar 
    Kroodsma, D. A. et al. Tracking the global footprint of fisheries. Science 359, 904–908 (2018).Article 
    CAS 

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

    Google Scholar 
    Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).Article 
    CAS 

    Google Scholar 
    Hilborn, R., Banobi, J., Hall, S. J., Pucylowski, T. & Walsworth, T. E. The environmental cost of animal source foods. Front. Ecol. Environ. 16, 329–335 (2018).Article 

    Google Scholar 
    Parker, R. W. R. et al. Fuel use and greenhouse gas emissions of world fisheries. Nat. Clim. Change 8, 333–337 (2018).Article 
    CAS 

    Google Scholar 
    Davis, K. F. et al. Meeting future food demand with current agricultural resources. Glob. Environ. Change 39, 125–132 (2016).Article 

    Google Scholar 
    Gephart, J. A. et al. The environmental cost of subsistence: optimizing diets to minimize footprints. Sci. Total Environ. 553, 120–127 (2016).Article 
    CAS 

    Google Scholar 
    Gephart, J. A. et al. Environmental performance of blue foods. Nature 597, 360–365 (2021).Article 
    CAS 

    Google Scholar 
    Halpern, B. S. et al. Putting all foods on the same table: achieving sustainable food systems requires full accounting. Proc. Natl Acad. Sci. USA 116, 18152–18156 (2019).Article 
    CAS 

    Google Scholar 
    Béné, C. et al. Feeding 9 billion by 2050—putting fish back on the menu. Food Secur. 7, 261–274 (2015).Article 

    Google Scholar 
    Tacon, A. G. J. & Metian, M. Fish matters: importance of aquatic foods in human nutrition and global food supply. Rev. Fish. Sci. 21, 22–38 (2013).Article 
    CAS 

    Google Scholar 
    Verones, F., Moran, D., Stadler, K., Kanemoto, K. & Wood, R. Resource footprints and their ecosystem consequences. Sci. Rep. 7, 40743 (2017).Article 
    CAS 

    Google Scholar 
    Mekonnen, M. M. & Hoekstra, A. Y. The green, blue and grey water footprint of crops and derived crop products. Hydrol. Earth Syst. Sci. 15, 1577–1600 (2011).Article 

    Google Scholar 
    Mekonnen, M. M. & Hoekstra, A. Y. The Green, Blue and Grey Water Footprint of Farm Animals and Animal Products (UNESCO-IHE, 2010).Carlson, K. M. et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Change 7, 63–68 (2017).Article 
    CAS 

    Google Scholar 
    Hong, C. et al. Global and regional drivers of land-use emissions in 1961–2017. Nature 589, 554–561 (2021).Article 
    CAS 

    Google Scholar 
    Amoroso, R. O. et al. Bottom trawl fishing footprints on the world’s continental shelves. Proc. Natl Acad. Sci. USA 115, E10275–E10282 (2018).Article 
    CAS 

    Google Scholar 
    Kuempel, C. D. et al. Integrating life cycle and impact assessments to map food’s cumulative environmental footprint. One Earth 3, 65–78 (2020).Article 

    Google Scholar 
    Halpern, B. S. et al. A global map of human impact on marine ecosystems. Science 319, 948–952 (2008).Article 
    CAS 

    Google Scholar 
    Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol. Lett. 11, 1304–1315 (2008).Article 

    Google Scholar 
    Birk, S. et al. Impacts of multiple stressors on freshwater biota across spatial scales and ecosystems. Nat. Ecol. Evol. 4, 1060–1068 (2020).Article 

    Google Scholar 
    Judd, A. D., Backhaus, T. & Goodsir, F. An effective set of principles for practical implementation of marine cumulative effects assessment. Environ. Sci. Policy 54, 254–262 (2015).Article 

    Google Scholar 
    IPBES Global Assessment Report on Biodiversity and Ecosystem Services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES, 2019).Froehlich, H. E., Jacobsen, N. S., Essington, T. E., Clavelle, T. & Halpern, B. S. Avoiding the ecological limits of forage fish for fed aquaculture. Nat. Sustain. 1, 298–303 (2018).Article 

    Google Scholar 
    FAO The State of World Fisheries and Aquaculture 2020 (FAO, 2020).Froehlich, H. E., Runge, C. A., Gentry, R. R., Gaines, S. D. & Halpern, B. S. Comparative terrestrial feed and land use of an aquaculture-dominant world. Proc. Natl Acad. Sci. USA 115, 5295–5300 (2018).Article 
    CAS 

    Google Scholar 
    FAOSTAT Database: New Food Balances (FAO, 2020); http://www.fao.org/faostat/en/#data/FBSFAOSTAT Database: Production, Crops (FAO, 2020); http://www.fao.org/faostat/en/#data/QCDong, F. et al. Assessing sustainability and improvements in US Midwestern soybean production systems using a PCA–DEA approach. Renew. Agric. Food Syst. 31, 524–539 (2016).Article 

    Google Scholar 
    Watson, R. A. & Tidd, A. Mapping nearly a century and a half of global marine fishing: 1869–2015. Mar. Policy 93, 171–177 (2018).Article 

    Google Scholar 
    Robinson, T. P. et al. Mapping the global distribution of livestock. PLoS ONE 9, e96084 (2014).Article 

    Google Scholar 
    Clark, M. & Tilman, D. Comparative analysis of environmental impacts of agricultural production systems, agricultural input efficiency, and food choice. Environ. Res. Lett. 12, 064016 (2017).Article 

    Google Scholar 
    Balmford, B., Green, R. E., Onial, M., Phalan, B. & Balmford, A. How imperfect can land sparing be before land sharing is more favourable for wild species? J. Appl. Ecol. 56, 73–84 (2019).Article 

    Google Scholar 
    Luskin, M. S., Lee, J. S. H., Edwards, D. P., Gibson, L. & Potts, M. D. Study context shapes recommendations of land-sparing and sharing; a quantitative review. Glob. Food Secur. 16, 29–35 (2018).Article 

    Google Scholar 
    Williams, D. R., Phalan, B., Feniuk, C., Green, R. E. & Balmford, A. Carbon storage and land-use strategies in agricultural landscapes across three continents. Curr. Biol. 28, 2500–2505.e4 (2018).Article 
    CAS 

    Google Scholar 
    Paul, B. G. & Vogl, C. R. Impacts of shrimp farming in Bangladesh: challenges and alternatives. Ocean Coastal Manage. 54, 201–211 (2011).Article 

    Google Scholar 
    Ahmed, N., Cheung, W. W. L., Thompson, S. & Glaser, M. Solutions to blue carbon emissions: shrimp cultivation, mangrove deforestation and climate change in coastal Bangladesh. Mar. Policy 82, 68–75 (2017).Article 

    Google Scholar 
    FAOSTAT Database: Livestock Primary (FAO, 2020); http://www.fao.org/faostat/en/#data/QLRamankutty, N., Ricciardi, V., Mehrabi, Z. & Seufert, V. Trade-offs in the performance of alternative farming systems. Agric. Econ. 50, 97–105 (2019).Article 

    Google Scholar 
    FAOSTAT Database: Detailed Trade Matrix (FAO, 2020); http://www.fao.org/faostat/en/#data/TMFisheries & Aquaculture—Fishery Statistical Collections—Fishery Commodities and Trade (FAO, 2019); http://www.fao.org/fishery/statistics/global-commodities-production/enInternational Food Policy Research Institute. Global spatially-disaggregated crop production statistics data for 2010, version 2.0. Harvard Dataverse https://doi.org/10.7910/DVN/PRFF8V (2019).Clawson, G. et al. Mapping the spatial distribution of global mariculture production. Aquaculture 553, 738066 (2022).Article 

    Google Scholar 
    Petz, K. et al. Mapping and modelling trade-offs and synergies between grazing intensity and ecosystem services in rangelands using global-scale datasets and models. Glob. Environ. Change 29, 223–234 (2014).Article 

    Google Scholar 
    Global Fishing Watch. Fishing effort. Fleet daily, v2 100th degree. (2021). https://globalfishingwatch.org/dataset-and-code-fishing-effort/Verdegem, M. C. J., Bosma, R. H. & Verreth, J. A. J. Reducing water use for animal production through aquaculture. Int. J. Water Resour. Dev. 22, 101–113 (2006).Article 

    Google Scholar 
    Bouwman, A. F., Beusen, A. H. W. & Billen, G. Human alteration of the global nitrogen and phosphorus soil balances for the period 1970–2050. Glob. Biogeochem. Cycles 23, GB0A04 (2009).Article 

    Google Scholar 
    Bouwman, A. F., Van Drecht, G. & Van der Hoek, K. W. Nitrogen surface balances in intensive agricultural production systems in different world regions for the period 1970–2030. Pedosphere 15, 137–155 (2005).
    Google Scholar 
    Bouwman, A., Boumans, L. J. M. & Batjes, N. Estimation of global NH3 volatilization loss from synthetic fertilizers and animal manure applied to arable lands and grasslands. Glob. Biogeochem. Cycles 16, 8-1–8-14 (2002).Article 

    Google Scholar 
    FAOSTAT Database: Inputs, Fertilizers by Nutrient (FAO, 2020); http://www.fao.org/faostat/en/#data/RFNHeffer, P., Gruere, A. & Roberts, T. Assessment of fertilizer use by crop at the global level 2014–2014/15, International Fertilizer Association (2017).Fertilizer Use by Crop 5th edn (FAO, IFA & IFDC, 2002).Islam, Md. S. Nitrogen and phosphorus budget in coastal and marine cage aquaculture and impacts of effluent loading on ecosystem: review and analysis towards model development. Mar. Pollut. Bull. 50, 48–61 (2005).Article 
    CAS 

    Google Scholar 
    Wang, J., Beusen, A. H. W., Liu, X. & Bouwman, A. F. Aquaculture production is a large, spatially concentrated source of nutrients in Chinese freshwater and coastal seas. Environ. Sci. Technol. 54, 1464–1474 (2020).Article 

    Google Scholar 
    Bouwman, A. F. et al. Hindcasts and future projections of global inland and coastal nitrogen and phosphorus loads due to finfish aquaculture. Rev. Fish. Sci. 21, 112–156 (2013).Article 
    CAS 

    Google Scholar 
    Gavrilova, O. et al. in 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories Ch. 10, Intergovernmental Panel on Climate Change (IPCC); Review Editors on Overview: Dario Gómez (Argentina) and William Irving (USA) (2019).Seafood Carbon Emissions Tool, Lisa Max, Robert Parker, Peter Tyedmers, editors; (2020); http://seafoodco2.dal.ca/Hu, Z., Lee, J. W., Chandran, K., Kim, S. & Khanal, S. K. Nitrous oxide (N2O) emission from aquaculture: a review. Environ. Sci. Technol. 46, 6470–6480 (2012).Article 
    CAS 

    Google Scholar 
    IPCC Climate Change 2007: The Physical Science Basis (eds Solomon, S. et al.) (Cambridge Univ. Press, 2007).Lynch, J., Cain, M., Pierrehumbert, R. & Allen, M. Demonstrating GWP*: a means of reporting warming-equivalent emissions that captures the contrasting impacts of short- and long-lived climate pollutants. Environ. Res. Lett. 15, 044023 (2020).Article 
    CAS 

    Google Scholar 
    Global Livestock Environmental Assessment Model, GLEAM, v.2.0.121 (FAO, 2018).Aas, T. S., Ytrestøyl, T. & Åsgård, T. Utilization of feed resources in the production of Atlantic salmon (Salmo salar) in Norway: an update for 2016. Aquacult. Rep. 15, 100216 (2019).
    Google Scholar 
    Jackson, A. Fish in-fish out (FIFO) explained. Aquacult. Eur. 34, 5–10 (2009).
    Google Scholar 
    Halpern, B. S. et al. Spatial and temporal changes in cumulative human impacts on the world’s ocean. Nat. Commun. 6, 7615 (2015).Article 
    CAS 

    Google Scholar 
    Frazier, M. et al. Global food system pressure data. https://knb.ecoinformatics.org/view/doi:10.5063/F1V69H1B More

  • in

    Dual ancestries and ecologies of the Late Glacial Palaeolithic in Britain

    Housley, R. A., Gamble, C. S., Street, M. & Pettitt, P. Radiocarbon evidence for the lateglacial human recolonisation of Northern Europe. Proc. Prehist. Soc. 63, 25–54 (1997).
    Google Scholar 
    Blockley, S. P. E., Donahue, R. E. & Pollard, A. M. Radiocarbon calibration and Late Glacial occupation in northwest Europe. Antiquity 74, 112–119 (2000).
    Google Scholar 
    Terberger, T., Barton, N. & Street, M. in Humans, Environment and Chronology of the Late Glacial of the North European Plain (eds Street, M. et al.) 189–207 (Romisch-Germanisches Zentralmuseum, 2009).Miller, R. Mapping the expansion of the Northwest Magdalenian. Quat. Int. 272–273, 209–230 (2012).
    Google Scholar 
    Riede, F. & Pedersen, J. B. Late Glacial human dispersals in Northern Europe and disequilibrium dynamics. Hum. Ecol. 46, 621–632 (2018).
    Google Scholar 
    Lazaridis, I. et al. Ancient human genomes suggest three ancestral populations for present-day Europeans. Nature 513, 409–413 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jones, E. R. et al. Upper Palaeolithic genomes reveal deep roots of modern Eurasians. Nat. Commun. 6, 8912 (2015).CAS 
    PubMed 

    Google Scholar 
    Fu, Q. et al. The genetic history of Ice Age Europe. Nature 534, 200–205 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Villalba-Mouco, V. et al. Survival of Late Pleistocene hunter-gatherer ancestry in the Iberian Peninsula. Curr. Biol. 29, 1169–1177 (2019).Willis, K. J. & Whittaker, R. J. Perspectives: paleoecology. The refugial debate. Science 287, 1406–1407 (2000).CAS 
    PubMed 

    Google Scholar 
    Sommer, R. S. & Nadachowski, A. Glacial refugia of mammals in Europe: evidence from fossil records. Mamm. Rev. 36, 251–265 (2006).
    Google Scholar 
    Bennett, K. D. & Provan, J. What do we mean by ‘refugia’? Quat. Sci. Rev. 27, 2449–2455 (2008).
    Google Scholar 
    Terberger, T. & Street, M. Hiatus or continuity? New results for the question of pleniglacial settlement in Central Europe. Antiquity 76, 691–698 (2002).
    Google Scholar 
    Maier, A. in The Central European Magdalenian. Vertebrate Paleobiology and Paleoanthropology (ed. Maier, A.) 231–241 (Springer, 2015).Reade, H. et al. Radiocarbon chronology and environmental context of Last Glacial Maximum human occupation in Switzerland. Sci. Rep. 10, 4694 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stevens, R. E., Hermoso-Buxán, X. L., Marín-Arroyo, A. B., González-Morales, M. R. & Straus, L. G. Investigation of Late Pleistocene and Early Holocene palaeoenvironmental change at El Mirón cave (Cantabria, Spain): insights from carbon and nitrogen isotope analyses of red deer. Palaeogeogr. Palaeoclimatol. Palaeoecol. 414, 46–60 (2014).
    Google Scholar 
    Clark, C. D., Hughes, A. L. C., Greenwood, S. L., Jordan, C. & Sejrup, H. P. Pattern and timing of retreat of the last British–Irish Ice Sheet. Quat. Sci. Rev. 44, 112–146 (2012).
    Google Scholar 
    Currant, A. P. & Jacobi, R. in The Ancient Human Occupation of Britain Vol. 14 (eds Ashton, N. et al.) 165–180 (Elsevier, 2011).Walker, M. J. C. et al. Devensian lateglacial environmental changes in Britain: a multi-proxy environmental record from Llanilid, South Wales, UK. Quat. Sci. Rev. 22, 475–520 (2003).
    Google Scholar 
    Hill, T. C. B. et al. Devensian late-glacial environmental change in the Gordano Valley, North Somerset, England: a rare archive for southwest Britain. J. Paleolimnol. 40, 431–444 (2008).
    Google Scholar 
    Jacobi, R. M. & Higham, T. F. G. The early Lateglacial re-colonization of Britain: new radiocarbon evidence from Gough’s Cave, southwest England. Quat. Sci. Rev. 28, 1895–1913 (2009).
    Google Scholar 
    Jacobi, R. & Higham, T. in The Ancient Human Occupation of Britain Vol. 14 (eds Ashton, N. M. et al.) 223–247 (Elsevier, 2011).Grimm, S. B. & Weber, M.-J. The chronological framework of the Hamburgian in the light of old and new 14C dates. Quartär. 55, 17–40 (2008).
    Google Scholar 
    Olalde, I. et al. The Beaker phenomenon and the genomic transformation of northwest Europe. Nature 555, 190–196 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Brace, S. et al. Ancient genomes indicate population replacement in Early Neolithic Britain. Nat. Ecol. Evol. 3, 765–771 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Jacobi, R. M. & Higham, T. F. G. The ‘Red Lady’ ages gracefully: new ultrafiltration AMS determinations from Paviland. J. Hum. Evol. 55, 898–907 (2008).CAS 
    PubMed 

    Google Scholar 
    Schulting, R. J. et al. A mid-upper Palaeolithic human humerus from Eel Point, South Wales, UK. J. Hum. Evol. 48, 493–505 (2005).PubMed 

    Google Scholar 
    Richards, M. P., Hedges, R. E. M., Jacobi, R., Current, A. & Stringer, C. FOCUS: Gough’s Cave and Sun Hole Cave human stable isotope values indicate a high animal protein diet in the British Upper Palaeolithic. J. Archaeol. Sci. 27, 1–3 (2000).
    Google Scholar 
    Proctor, C., Douka, K., Proctor, J. W. & Higham, T. The age and context of the KC4 Maxilla, Kent’s Cavern, UK. Eur. J. Archaeol. 20, 74–97 (2017).
    Google Scholar 
    Richards, M. P., Jacobi, R., Cook, J., Pettitt, P. B. & Stringer, C. B. Isotope evidence for the intensive use of marine foods by Late Upper Palaeolithic humans. J. Hum. Evol. 49, 390–394 (2005).CAS 
    PubMed 

    Google Scholar 
    Bello, S. M., Saladié, P., Cáceres, I., Rodríguez-Hidalgo, A. & Parfitt, S. A. Upper Palaeolithic ritualistic cannibalism at Gough’s Cave (Somerset, UK): the human remains from head to toe. J. Hum. Evol. 82, 170–189 (2015).PubMed 

    Google Scholar 
    Andrews, P. & Fernández-Jalvo, Y. Cannibalism in Britain: taphonomy of the Creswellian (Pleistocene) faunal and human remains from Gough’s Cave (Somerset, England). Bull. Nat. Hist. Mus. Geol. 58, 59–81 (2003).
    Google Scholar 
    Bello, S. M., Parfitt, S. A. & Stringer, C. B. Earliest directly-dated human skull-cups. PLoS ONE 6, e17026 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Currant, A. P., Jacobi, R. M. & Stringer, C. B. Excavations at Gough’s Cave, Somerset 1986–7. Antiquity 63, 131–136 (1989).
    Google Scholar 
    Davies, M. in Limestones and Caves of Wales (ed. Ford, T. D.) 92–101 (Cambridge Univ. Press, 1989).Dawkins, W. B. Memorandum on the remains from the cave at the Great Ormes Head. Proc. Liverp. Geol. Soc. 4, 156–159 (1880).
    Google Scholar 
    Sieveking, G. & de, G. The Kendrick’s Cave mandible. Br. Mus. Q. 35, 230–250 (1971).
    Google Scholar 
    Pettitt, P. B. Discovery, nature and preliminary thoughts about Britain’s first cave art.Capra 5,1–12 (2003).
    Google Scholar 
    Bello, S. M., Wallduck, R., Parfitt, S. A. & Stringer, C. B. An Upper Palaeolithic engraved human bone associated with ritualistic cannibalism. PLoS ONE 12, e0182127 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Bocherens, H. & Drucker, D. Isotope evidence for paleodiet of late Upper Paleolithic humans in Great Britain: a response to Richards et al. 2005. J. Hum. Evol. 51, 440–442 (2006).PubMed 

    Google Scholar 
    Fernandes, R., Millard, A. R., Brabec, M., Nadeau, M.-J. & Grootes, P. Food reconstruction using isotopic transferred signals (FRUITS): a Bayesian model for diet reconstruction. PLoS ONE 9, e87436 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Rasmussen, S. O. et al. A stratigraphic framework for abrupt climatic changes during the Last Glacial period based on three synchronized Greenland ice-core records: refining and extending the INTIMATE event stratigraphy. Quat. Sci. Rev. 106, 14–28 (2014).
    Google Scholar 
    Kloss-Brandstätter, A. et al. HaploGrep: a fast and reliable algorithm for automatic classification of mitochondrial DNA haplogroups. Hum. Mutat. 32, 25–32 (2011).PubMed 

    Google Scholar 
    Skoglund, P., Storå, J., Götherström, A. & Jakobsson, M. Accurate sex identification of ancient human remains using DNA shotgun sequencing. J. Archaeol. Sci. 40, 4477–4482 (2013).CAS 

    Google Scholar 
    Haak, W. et al. Massive migration from the steppe was a source for Indo-European languages in Europe. Nature 522, 207–211 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fu, Q. et al. An early modern human from Romania with a recent Neanderthal ancestor. Nature 524, 216–219 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Patterson, N., Price, A. L. & Reich, D. Population structure and eigenanalysis. PLoS Genet. 2, e190 (2006).PubMed 
    PubMed Central 

    Google Scholar 
    Price, A. L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).CAS 
    PubMed 

    Google Scholar 
    Mallick, S. et al. The Simons Genome Diversity Project: 300 genomes from 142 diverse populations. Nature 538, 201–206 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Patterson, N. et al. Ancient admixture in human history. Genetics 192, 1065–1093 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Harney, É., Patterson, N., Reich, D. & Wakeley, J. Assessing the performance of qpAdm: a statistical tool for studying population admixture. Genetics 217, iyaa045 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Currant, A. & Jacobi, R. A formal mammalian biostratigraphy for the Late Pleistocene of Britain. Quat. Sci. Rev. 20, 1707–1716 (2001).
    Google Scholar 
    Pickard, C. & Bonsall, C. Post-glacial hunter-gatherer subsistence patterns in Britain: dietary reconstruction using FRUITS. Archaeol. Anthropol. Sci. 12, 142 (2020).
    Google Scholar 
    Stevens, R. E., Jacobi, R. M. & Higham, T. F. G. Reassessing the diet of Upper Palaeolithic humans from Gough’s Cave and Sun Hole, Cheddar Gorge, Somerset, UK. J. Archaeol. Sci. 37, 52–61 (2010).
    Google Scholar 
    Sala, N. & Conard, N. Taphonomic analysis of the hominin remains from Swabian Jura and their implications for the mortuary practices during the Upper Paleolithic. Quat. Sci. Rev. 150, 278–300 (2016).
    Google Scholar 
    Saladié, P. & Rodríguez-Hidalgo, A. Archaeological evidence for cannibalism in prehistoric Western Europe: from Homo antecessor to the Bronze Age. J. Archaeol. Method Theory 24, 1034–1071 (2017).
    Google Scholar 
    Cook, J. Ice Age Art: Arrival of the Modern Mind (British Museum Press, 2013).Gupta, S., Collier, J. S., Palmer-Felgate, A. & Potter, G. Catastrophic flooding origin of shelf valley systems in the English Channel. Nature 448, 342–345 (2007).CAS 
    PubMed 

    Google Scholar 
    Mills, W. in From the Atlantic to Beyond the Bug River. Finding and Defining the Federmesser-Gruppen/Azilian (eds Grimm, S. B. et al.) 1–24 (Propylaeum, 2020).Amkreutz, L. et al. What lies beneath … Late Glacial human occupation of the submerged North Sea landscape. Antiquity 92, 22–37 (2018).
    Google Scholar 
    Ward, I., Larcombe, P. & Lillie, M. The dating of Doggerland—post-glacial geochronology of the southern North Sea. Environ. Archaeol. 11, 207–218 (2006).
    Google Scholar 
    Brock, F., Higham, T., Ditchfield, P. & Ramsey, C. B. Current pretreatment methods for AMS radiocarbon dating at the Oxford Radiocarbon Accelerator Unit (ORAU). Radiocarbon 52, 103–112 (2010).CAS 

    Google Scholar 
    Dabney, J. et al. Complete mitochondrial genome sequence of a Middle Pleistocene cave bear reconstructed from ultrashort DNA fragments. Proc. Natl Acad. Sci. USA 110, 15758–15763 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Meyer, M. & Kircher, M. Illumina sequencing library preparation for highly multiplexed target capture and sequencing. Cold Spring Harb. Protoc. 2010, pdb.prot5448 (2010).Rohland, N., Harney, E., Mallick, S., Nordenfelt, S. & Reich, D. Partial uracil–DNA–glycosylase treatment for screening of ancient DNA. Philos. Trans. R. Soc. Lond. B 370, 20130624 (2015).
    Google Scholar 
    Kircher, M., Sawyer, S. & Meyer, M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 40, e3 (2012).CAS 
    PubMed 

    Google Scholar 
    Briggs, A. W. et al. Patterns of damage in genomic DNA sequences from a Neandertal. Proc. Natl Acad. Sci. USA 104, 14616–14621 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Skoglund, P. et al. Separating endogenous ancient DNA from modern day contamination in a Siberian Neandertal. Proc. Natl Acad. Sci. USA 111, 2229–2234 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Petr, M., Vernot, B. & Kelso, J. admixr—R package for reproducible analyses using ADMIXTOOLS. Bioinformatics 35, 3194–3195 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Busing, F. M., Meijer, E. & Van Der Leeden, R. Delete-m jackknife for unequal m. Stat. Comput. 9, 3–8 (1999).
    Google Scholar 
    Fu, Q. et al. Genome sequence of a 45,000-year-old modern human from western Siberia. Nature 514, 445–449 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Raghavan, M. et al. Upper Palaeolithic Siberian genome reveals dual ancestry of Native Americans. Nature 505, 87–91 (2014).PubMed 

    Google Scholar 
    Lazaridis, I. et al. Genomic insights into the origin of farming in the ancient Near East. Nature 536, 419–424 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lipson, M. et al. Parallel palaeogenomic transects reveal complex genetic history of early European farmers. Nature 551, 368–372 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gallego Llorente, M. et al. Ancient Ethiopian genome reveals extensive Eurasian admixture throughout the African continent. Science 350, 820–822 (2015).CAS 
    PubMed 

    Google Scholar 
    Villalba-Mouco, V. et al. Survival of Late Pleistocene hunter-gatherer ancestry in the Iberian Peninsula. Curr. Biol. 29, 1169–1177 (2019).CAS 
    PubMed 

    Google Scholar  More

  • in

    Contrasting sea ice conditions shape microbial food webs in Hudson Bay (Canadian Arctic)

    Laxon SW, Giles KA, Ridout AL, Wingham DJ, Willatt R, Cullen R, et al. CryoSat-2 estimates of Arctic sea ice thickness and volume. Geophys Res Lett. 2013;40:732–7.
    Google Scholar 
    Stroeve J, Notz D. Changing state of Arctic sea ice across all seasons. Environ Res Lett. 2018;13:103001.
    Google Scholar 
    Macdonald RW, Kuzyk ZZA. The Hudson Bay system: a northern inland sea in transition. J Mar Syst. 2011;88:337–40.
    Google Scholar 
    Serreze MC, Barry RG. Processes and impacts of Arctic amplification: a research synthesis. Glob Planet Change. 2011;77:85–96.
    Google Scholar 
    Hochheim KP, Barber DG. An update on the ice climatology of the Hudson Bay system. Arctic, Antarctic, and Alpine Research. 2014;46:66–83.
    Google Scholar 
    Gagnon AS, Gough WA. Climate change scenarios for the Hudson Bay region: an intermodel comparison. Climatic Change. 2005;69:269–97.
    Google Scholar 
    Bring A, Shiklomanov A, Lammers RB. Pan-Arctic river discharge: prioritizing monitoring of future climate change hot spots. Earths Future. 2017;5:72–92.
    Google Scholar 
    Comeau AM, Li WKW, Tremblay JÉ, Carmack EC, Lovejoy C. Arctic Ocean microbial community structure before and after the 2007 record sea ice minimum. PLoS One. 2011;6:e27492.PubMed 
    PubMed Central 

    Google Scholar 
    Li W, McLaughlin F, Lovejoy C, Carmack E. Smallest algae thrive as the Arctic Ocean freshens. Science. 2009;326:539.PubMed 

    Google Scholar 
    Ji R, Jin M, Varpe Ø. Sea ice phenology and timing of primary production pulses in the Arctic Ocean. Glob Change Biol. 2013;19:734–41.
    Google Scholar 
    Ardyna M, Mundy C, Mills M, Oziel L, Lacour L, Verin G, et al. Environmental drivers of under-ice phytoplankton bloom dynamics in the Arctic Ocean. Elem Sci Anthr. 2020;8:e30.
    Google Scholar 
    Kahru M, Brotas V, Manzano-Sarabia M, Mitchell BG. Are phytoplankton blooms occurring earlier in the Arctic? Glob Change Biol. 2011;17:1733–9.
    Google Scholar 
    Barbedo L, Bélanger S, Tremblay J. Climate control of sea-ice edge phytoplankton blooms in the Hudson Bay system. Elem Sci Anthr. 2020;8:1.
    Google Scholar 
    Matthes LC, Ehn JK, Dalman LA, Babb DG, Peeken I, Harasyn M, et al. Environmental drivers of spring primary production in Hudson Bay. Elem Sci Anthr. 2021;9:00160.
    Google Scholar 
    Harvey M, Therriault JC, Simard N. Late-summer distribution of phytoplankton in relation to water mass characteristics in Hudson Bay and Hudson Strait (Canada). Can J Fish Aquat Sci. 1997;54:1937–52.
    Google Scholar 
    Ferland J, Gosselin M, Starr M. Environmental control of summer primary production in the Hudson Bay system: The role of stratification. J Mar Syst. 2011;88:385–400.
    Google Scholar 
    Raven JA. The twelfth Tansley Lecture. Small is beautiful: the picophytoplankton. Funct Ecol. 1998;12:503–13.
    Google Scholar 
    Tilman D, Kilham SS, Kilham P. Phytoplankton community ecology: the role of limiting nutrients. Annu Rev Ecol Syst. 1982;13:349–72.
    Google Scholar 
    Onda DFL, Medrinal E, Comeau AM, Thaler M, Babin M, Lovejoy C. Seasonal and interannual changes in ciliate and dinoflagellate species assemblages in the Arctic Ocean (Amundsen Gulf, Beaufort Sea, Canada). Front Mar Sci. 2017;4:16.
    Google Scholar 
    Campbell K, Mundy CJ, Belzile C, Delaforge A, Rysgaard S. Seasonal dynamics of algal and bacterial communities in Arctic sea ice under variable snow cover. Polar Biol. 2018;41:41–58.
    Google Scholar 
    Forest A, Tremblay JÉ, Gratton Y, Martin J, Gagnon J, Darnis G, et al. Biogenic carbon flows through the planktonic food web of the Amundsen Gulf (Arctic Ocean): a synthesis of field measurements and inverse modeling analyses. Prog Oceanogr. 2011;91:410–36.
    Google Scholar 
    Buchan A, Lecleir GR, Gulvik CA, González JM. Master recyclers: features and functions of bacteria associated with phytoplankton blooms. Nat Rev Microbiol. 2014;12:686–98.PubMed 

    Google Scholar 
    Cole JJ, Likens GE, Strayer DL. Photosynthetically produced dissolved organic carbon: an important carbon source for planktonic bacteria. Limnol Oceanogr. 1982;27:1080–90.
    Google Scholar 
    Horňák K, Kasalický V, Šimek K, Grossart HP. Strain-specific consumption and transformation of alga-derived dissolved organic matter by members of the Limnohabitans-C and Polynucleobacter-B clusters of Betaproteobacteria. Environ Microbiol. 2017;19:4519–35.PubMed 

    Google Scholar 
    Šimek K, Kasalický V, Zapomělová E, Horňák K. Alga-derived substrates select for distinct betaproteobacterial lineages and contribute to niche separation in Limnohabitans strains. Appl Environ Microbiol. 2011;77:7307–15.PubMed 
    PubMed Central 

    Google Scholar 
    Orsi WD, Smith JM, Liu S, Liu Z, Sakamoto CM, Wilken S, et al. Diverse, uncultivated bacteria and archaea underlying the cycling of dissolved protein in the ocean. ISME J. 2016;10:2158–73.PubMed 
    PubMed Central 

    Google Scholar 
    Williams TJ, Wilkins D, Long E, Evans F, Demaere MZ, Raftery MJ, et al. The role of planktonic Flavobacteria in processing algal organic matter in coastal East Antarctica revealed using metagenomics and metaproteomics. Environ Microbiol. 2013;15:1302–17.PubMed 

    Google Scholar 
    Teeling H, Fuchs BM, Becher D, Klockow C, Gardebrechet A, Bennke CM, et al. Substrate-controlled succession of marine bacterioplankton populations induced by a phytoplankton bloom. Science. 2012;336:608–11.PubMed 

    Google Scholar 
    Armengol L, Calbet A, Franchy G, Rodríguez-Santos A, Hernández-León S. Planktonic food web structure and trophic transfer efficiency along a productivity gradient in the tropical and subtropical Atlantic Ocean. Sci Rep. 2019;9:1–19.
    Google Scholar 
    Joly S, Senneville S, Caya D, Saucier FJ. Sensitivity of Hudson Bay Sea ice and ocean climate to atmospheric temperature forcing. Clim Dyn. 2011;36:1835–49.
    Google Scholar 
    Kirillov S, Babb D, Dmitrenko I, Landy D, Lukovich JV, Ehn J, et al. Atmospheric forcing drives the winter sea ice thickness asymmetry of Hudson Bay. Geophys Res Oceans. 2020;125:1–12.
    Google Scholar 
    Tivy A, Howell SEL, Alt B, McCourt S, Chagnon R, Crocker G, et al. Trends and variability in summer sea ice cover in the Canadian Arctic based on the Canadian Ice Service Digital Archive, 1960-2008 and 1968-2008. J Geophys Res Oceans. 2011;116:C03007.
    Google Scholar 
    Barber D, Landry D, Babb D, Kirillov S, Aubry C, Schembri S, et al. Bay-Wide Survey Program Cruise Report – CCGS Amundsen (LEG-1). In: Hudson Bay System Study (BaySys) Phase 1 Report: Hudson Bay Field Program and Data Collection. Landry, DL & Candlish, LM. (Eds). 2019. p. 131–222.Jacquemot L, Kalenitchenko D, Matthes LC, Vigneron A, Mundy CJ, Tremblay JE, et al. Protist communities along freshwater-marine transition zones in Hudson Bay (Canada). Elem Sci Anthr. 2021;9:00111.
    Google Scholar 
    Grasshoff K, Kremling K, Ehrhardt M. Determination of nutrients. In: Methods of Seawater Analysis: Third, Completely Revised and Extended Edition. 1999. p. 159–228.Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci. 2011;108:4516–22.PubMed 

    Google Scholar 
    Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.PubMed 
    PubMed Central 

    Google Scholar 
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high- throughput community sequencing data. Nat Publ Group. 2010;7:335–6.
    Google Scholar 
    Guillou L, Bachar D, Audic S, Bass D, Berney C, Bittner L, et al. The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res. 2013;41:597–604.
    Google Scholar 
    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:590–6.
    Google Scholar 
    McMurdie PJ, Holmes S. Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. 2013;8:e61217.PubMed 
    PubMed Central 

    Google Scholar 
    Stamatakis A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics. 2014;30:1312–3.PubMed 
    PubMed Central 

    Google Scholar 
    Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin PR, O’hara RB, et al. Package ‘vegan’. Community ecology package, version 2(9). 2013;1-295.Faust K, Raes J. CoNet app: inference of biological association networks using Cytoscape. F1000Research. 2016;5:1–14.
    Google Scholar 
    Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13:2498–504.PubMed 
    PubMed Central 

    Google Scholar 
    Volterra V. Fluctuations in the abundance of a species considered mathematically. Nature. 1926;118:558–60.
    Google Scholar 
    Joli N, Monier A, Logares R, Lovejoy C. Seasonal patterns in Arctic prasinophytes and inferred ecology of Bathycoccus unveiled in an Arctic winter metagenome. ISME J. 2017;11:1372–85.PubMed 
    PubMed Central 

    Google Scholar 
    Barber DG, Hop H, Mundy CJ, Else B, Dmitrenko IA, Tremblay JE, et al. Selected physical, biological and biogeochemical implications of a rapidly changing Arctic Marginal Ice Zone. Prog Oceanogr. 2015;139:122–50.
    Google Scholar 
    Tremblay JÉ, Anderson LG, Matrai P, Coupel P, Bélanger S, Michel C, et al. Global and regional drivers of nutrient supply, primary production and CO2 drawdown in the changing Arctic Ocean. Prog Oceanogr. 2015;139:171–96.
    Google Scholar 
    Needham DM, Fuhrman JA. Pronounced daily succession of phytoplankton, archaea and bacteria following a spring bloom. Nat Microbiol. 2016;1:1–7.
    Google Scholar 
    Berry D, Widder S. Deciphering microbial interactions and detecting keystone species with co-occurrence networks. Front Microbiol. 2014;5.Faust K, Raes J. Microbial interactions: from networks to models. Nat Rev Microbiol. 2012;10:538–50.PubMed 

    Google Scholar 
    Shi S, Nuccio EE, Shi ZJ, He Z, Zhou J, Firestone MK. The interconnected rhizosphere: high network complexity dominates rhizosphere assemblages. Ecol Lett. 2016;19:926–36.PubMed 

    Google Scholar 
    Guillou L, Viprey M, Chambouvet A, Welsh RM, Kirkham AR, Massana R, et al. Widespread occurrence and genetic diversity of marine parasitoids belonging to Syndiniales (Alveolata). Environ Microbiol. 2008;10:3349–65.PubMed 

    Google Scholar 
    Lima-Mendez G, Faust K, Henry N, Decelle J, Colin S, Carcillo F, et al. Determinants of community structure in the global plankton interactome. Science. 2015;10:1–10.
    Google Scholar 
    Chaffron S, Delage E, Budinich M, Vintache D, Henry N, Nef C, et al. Environmental vulnerability of the global ocean epipelagic plankton community interactome. Sci Adv. 2021;7:eabg1921.PubMed 
    PubMed Central 

    Google Scholar 
    Clarke LJ, Bestley S, Bissett A, Deagle BE. A globally distributed Syndiniales parasite dominates the Southern Ocean micro-eukaryote community near the sea-ice edge. ISME J. 2019;13:734–7.PubMed 

    Google Scholar 
    Not F, del Campo J, Balagué V, de Vargas C, Massana R. New insights into the diversity of marine picoeukaryotes. PLoS One. 2009;4:e7143.PubMed 
    PubMed Central 

    Google Scholar 
    Bass D, Stentiford GD, Littlewood DTJ, Hartikainen H. Diverse Applications of Environmental DNA Methods in Parasitology. Trends Parasitol. 2015;31:499–513.PubMed 

    Google Scholar 
    Kellogg CTE, Mcclelland JW, Dunton KH, Crump BC. Strong seasonality in arctic estuarine microbial food webs. Front Microbiol. 2019;10:2628.PubMed 
    PubMed Central 

    Google Scholar 
    Nitsche F, Weittere M, Scheckenbach F, Hausmann K, Wylezich C, Ardnt H. Deep sea records of choanoflagellates with a description of two new species. Acta Protozool. 2007;46:99–106.
    Google Scholar 
    Thaler M, Lovejoy C. Biogeography of heterotrophic flagellate populations indicates the presence of generalist and specialist taxa in the Arctic Ocean. Appl Environ Microbiol. 2015;81:2137–48.PubMed 
    PubMed Central 

    Google Scholar 
    Thomsen HA, Østergaard JB, Hansen LE. Loricate choanoflagellates from West Greenland (August 1988) including the description of Spinoeca buckii gen. et sp. nov. Eur J Protistol. 1995;31:38–44.
    Google Scholar 
    Thomsen HA, Østergaard JB. Acanthoecid choanoflagellates from the Atlantic Arctic Region − a baseline study. Heliyon. 2017;3:e00345.PubMed 
    PubMed Central 

    Google Scholar 
    Buck KR, Garrison DL, Cruz S. Distribution and abundance of choanoflagellates (Acanthoecidae) across the ice-edge zone in the Weddell Sea, Antarctica. Mar Biol. 1988;98:263–9.
    Google Scholar 
    Escalera L, Mangoni O, Bolinesi F, Saggiomo M. Austral summer bloom of loricate choanoflagellates in the central Ross Sea polynya. J Eukaryot Microbiol. 2019;66:849–52.PubMed 

    Google Scholar 
    Delmont TO, Hammar KM, Ducklow HW, Yager PL, Post AF. Phaeocystis antarctica blooms strongly influence bacterial community structures in the Amundsen Sea polynya. Front Microbiol. 2014;5:1–13.
    Google Scholar 
    Dupont CL, Rusch DB, Yooseph S, Lombardo MJ, Alexander Richter R, Valas R, et al. Genomic insights to SAR86, an abundant and uncultivated marine bacterial lineage. ISME J. 2012;6:1186–99.PubMed 

    Google Scholar 
    Abell GCJ, Bowman JP. Ecological and biogeographic relationships of class Flavobacteria in the Southern Ocean. FEMS Microbiol Ecol. 2005;51:265–77.PubMed 

    Google Scholar 
    Delmont TO, Murat Eren A, Vineis JH, Post AF. Genome reconstructions indicate the partitioning of ecological functions inside a phytoplankton bloom in the Amundsen Sea, Antarctica. Front Microbiol. 2015;6:e1090.
    Google Scholar 
    Stingl U, Desiderio RA, Cho JC, Vergin KL, Giovannoni SJ. The SAR92 clade: an abundant coastal clade of culturable marine bacteria possessing proteorhodopsin. Appl Environ Microbiol. 2007;73:2290–6.PubMed 
    PubMed Central 

    Google Scholar 
    de Sousa AGG, Tomasino MP, Duarte P, Fernández-Méndez M, Assmy P, Ribeiro H, et al. Diversity and composition of pelagic prokaryotic and protist communities in a thin Arctic sea-ice regime. Microb Ecol. 2019;78:388–408.PubMed 

    Google Scholar 
    Rapp JZ, Fernández-Méndez M, Bienhold C, Boetius A. Effects of ice-algal aggregate export on the connectivity of bacterial communities in the central Arctic Ocean. Front Microbiol. 2018;9:1035.PubMed 
    PubMed Central 

    Google Scholar 
    Wemheuer B, Güllert S, Billerbeck S, Giebel HA, Voget S, Simon M, et al. Impact of a phytoplankton bloom on the diversity of the active bacterial community in the southern North Sea as revealed by metatranscriptomic approaches. FEMS Microbiol Ecol. 2014;87:378–89.PubMed 

    Google Scholar 
    Jain A, Krishnan KP. Differences in free-living and particle-associated bacterial communities and their spatial variation in Kongsfjorden, Arctic. J Basic Microbiol. 2017;57:827–38.PubMed 

    Google Scholar 
    Granskog MA, Kuzyk ZZA, Azetsu-Scott K, Macdonald RW. Distributions of runoff, sea-ice melt and brine using δ18o and salinity data – a new view on freshwater cycling in Hudson Bay. J Mar Syst. 2011;88:362–74.
    Google Scholar 
    Stegen JC, Lin X, Konopka AE, Fredrickson JK. Stochastic and deterministic assembly processes in subsurface microbial communities. ISME J. 2012;6:1653–64.PubMed 
    PubMed Central 

    Google Scholar 
    Boeuf D, Edwards BR, Eppley JM, Hu SK, Poff KE, Romano AE, et al. Biological composition and microbial dynamics of sinking particulate organic matter at abyssal depths in the oligotrophic open ocean. Proc Natl Acad Sci USA. 2019;116:11824–32.PubMed 
    PubMed Central 

    Google Scholar 
    Gutierrez-Rodriguez A, Stukel MR, Lopes dos Santos A, Biard T, Scharek R, Vaulot D, et al. High contribution of Rhizaria (Radiolaria) to vertical export in the California Current Ecosystem revealed by DNA metabarcoding. ISME J. 2019;13:964–76.PubMed 

    Google Scholar 
    Bråte J, Krabberød AK, Dolven JK, Ose RF, Kristensen T, Bjørklund KR, et al. Radiolaria associated with large diversity of marine alveolates. Protist. 2012;163:767–77.PubMed 

    Google Scholar 
    Dolven JK, Lindqvist C, Albert VA, Bjørklund KR, Yuasa T, Takahashi O, et al. Molecular diversity of alveolates associated with neritic North Atlantic radiolarians. Protist. 2007;158:65–76.PubMed 

    Google Scholar 
    Decelle J, Martin P, Paborstava K, Pond DW, Tarling G, Mahé F, et al. Diversity, ecology and biogeochemistry of cyst-forming Acantharia (Radiolaria) in the oceans. PLoS One. 2013;8:e53598.PubMed 
    PubMed Central 

    Google Scholar 
    Fernandes GL, Shenoy BD, Damare SR. Diversity of bacterial community in the oxygen minimum zones of Arabian Sea and Bay of Bengal as deduced by illumina sequencing. Front Microbiol. 2020;10:e3153.
    Google Scholar 
    Vigneron A, Cruaud P, Culley A, Couture RM, Lovejoy C, Vincent W. Genomic evidence for sulfur intermediates as new biogeochemical hubs in a model aquatic microbial ecosystem. Microbiome. 2020;9:e46.
    Google Scholar 
    Wright JJ, Konwar KM, Hallam SJ. Microbial ecology of expanding oxygen minimum zones. Nat Publ Group. 2012;10:381–94.
    Google Scholar 
    Bianchi D, Weber TS, Kiko R, Deutsch C. Global niche of marine anaerobic metabolisms expanded by particle microenvironments. Nat Geosci. 2018;11:263–68.
    Google Scholar 
    Michel C, Legendre L, Therriault JC, Demers S, Vandevelde T. Springtime coupling between ice algal and phytoplankton assemblages in southeastern Hudson Bay, Canadian Arctic. Polar Biol. 1993;13:441–9.
    Google Scholar 
    Boetius A, Albrecht S, Bakker K, Bienhold C, Felden J, Fernández-méndez M, et al. Export of algal biomass from the metling Arctic sea ice. Science. 2013;339:1430–2.PubMed 

    Google Scholar 
    Vigneron A, Lovejoy C, Cruaud P, Kalenitchenko D, Culley A, Vincent WF. Contrasting winter versus summer microbial communities and metabolic functions in a permafrost thaw lake. Front Microbiol. 2019;10:e1656.
    Google Scholar 
    Tremblay JÉ, Lee J-H, Gosselin M, Belanger S. Nutrient dynamic and marine biological productivity in the greater Hudson Bay marine region. In: An integrated regional impact study (IRIS) Arcticnet University of Manitoba and ArcticNet. 2019. p. 225–44.Wassmann P, Reigstad M. Future Arctic Ocean seasonal ice zones and implications for pelagic-benthic coupling. Oceanography. 2011;24:220–31.
    Google Scholar  More

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    Effects of mine water on growth characteristics of ryegrass and soil matrix properties

    Our findings indicated that mine water had a certain inhibitory effect on ryegrass seed germination, and the intensity of this inhibitory effect increased with increased mine water proportion. These effects were mainly reflected as changes in germination potential. Concretely, irrigation with mine water prolonged the germination of ryegrass seeds but had no significant effect on germination rate. Min Zhu et al. found that recycled water inhibited the seed germination of turfgrass, and this effect became more notorious when the concentration of reclaimed water increased. This was likely because the water contained salt ions, heavy metal ions, and E. coli, all of which are known to affect seed germination22. The mine water was taken from the Laohutai mining area, where the water composition and quality are good. Therefore, mine water did not significantly affect seed germination and the seeds maybe germinate normally if given sufficient time.The physiological and photosynthetic characteristics of ryegrass were impacted by the mine water, and the intensity of inhibition increased with higher mine water proportions. When the ratio of mine water to clean water reached a certain proportion (1:2, A1 and B1), the physiological and growth characteristics of ryegrass were improved to a certain extent. When only mine water was used for irrigation, the indices were significantly suppressed. In contrast, mixing clear water with mine water for irrigation promoted the physiological characteristics of the plants, as well as photosynthesis. This was likely because the mineral content of mine water is higher. However, mine water not only contains elements needed for plant growth but also some elements and ions that have inhibitory effects on plant growth. Therefore, the quality of ryegrass growth were suppressed when irrigating only with mine water. In contrast, after mixing the mine water with clean water, the concentrations of certain substances that produce adverse effects are diluted, and the mixed irrigation water promoted ryegrass growth in appropriate proportion.A certain concentration of heavy metal elements will affect the absorption of essential elements by plants and produce antagonism, and high concentration can directly lead to plant death. Heavy metal stress affects chlorophyll content through two aspects: Heavy metal destroys enzymes needed for chlorophyll synthesis, affects plant chlorophyll synthesis, and then inhibits plant photosynthesis23. The second is the destruction of chloroplast structure and cell membrane24,25,26. In the treatment of high concentrations of heavy metals, the chlorophyll content of plants is significantly reduced due to the inhibition of chlorophylase or aminolevulinic acid dehydrase, thus inhibiting plant photosynthesis27. The heavy metal threat forcing stimulates the formation of reactive oxygen species that convert fatty acids into toxic lipid peroxides, which damage to plant cells28,29,30. Heavy metal stress can induce a lot of activity in plants sexual oxygen and inhibit the normal metabolism of plants, causing membrane lipid peroxidation and increased plasma membrane permeability31, 32. Low concentration of heavy metal stress will stimulate the protective mechanism of plants, so low concentration of stimulation will not damage plants, on the contrary, may help plant growth. Heavy metal stress causes water loss in plants, and a certain amount of proline can be produced to regulate the water balance of plant cells and reduce the damage degree of plant cells33. SOD, POD and CATT are important antioxidant enzymes in plants, which can scavenge excessive free radicals. The synergistic action of three enzymes can protect plants from free radical damage. When the concentration of heavy metals was low, the activity of protective enzymes increased under the induction of reactive oxygen radicals. However, with the increase of stress degree, the activities of SOD, POD and CAT decreased, which eventually led to the persecution of plant cells34. These conclusions are consistent with the results of this paper. When mine water was mixed with clear water at a ratio of 1:2, heavy metal stress stimulated the protective mechanism of ryegrass most appropriately, and improved plant quality and resistance. On the contrary, when the proportion of mine water increased, the physiological characteristics and quality of ryegrass plants were inhibited to different degrees.Precious Nneka Amori et al. studied physiological traits of leaves and Silverbeet using treated wastewater, the results show that the biomass of plants watered with only the treated wastewater were more than 50% higher than the yield in tap water control and plants exhibited high degree of root foraging1. Libutti et al. irrigated tomato and broccoli with purified agro-industrial effluent and reported that yield and quality traits of agricultural products were not affected35. Radish was grown using a reclaimed synthetic textile wastewater treated in an anoxic-aerobic photobioreactor, and the dry weight, leaf number and leaf area of plant harvest were 49, 19.2 and 62% higher than the growth performance in freshwater irrigation36. FU et al. studied four native Chenopodiaceae plants of Halogeton glomeratus, Kochia scoparia, Suaeda glauca and Chenopodium glaucum in Jinchang area northwest China, from their changes of net photosynthetic rate (Pn), Stomatal conductance (Gs), transpiration rate (Tr). chlorophyll content (Chl), malondialdehyde (MDA), soluble protein (SP), proline (Pro) and antioxidant enzymes activity under the treatment of farmland soil (T1) and sedendary soil mixed with tailing (1:1, T2), they concluded that under T2 treatment, Pn, Gs, and Tr of Halogeton glomeratus and Kochia scoparia were decreased , the other six indexes were increased significantly. Gs, Tr, MDA, Pro, and SOD increased, yet CAT, Chl and Pn of Suaeda glauca decreased significantly, respectively. Pn, Gs, and Tr of Chenopodium glaucum decreased significantly, while SP, POD increased significantly37. Our results also indicated that mine water irrigation had significant effects on soil characteristics. At higher mine water ratios, the soil conductivity increased exponentially, the pH decreased gradually, the content of K+, Na+, Ca2+ and Mg2+ increased, and the content of N, P and K also increased gradually. In contrast, the clean water and mine water mixture had little effect on the soil properties. This was because the salt and metal ions in mine water migrate to the soil during the irrigation process, which significantly changes the soil properties. As a result, the concentration of salt in the soil increased and soil acidity also increased. After mixing with clean water, the concentration of salt decreases, and the influence on the soil matrix weakened. These results also indicated that the growth, physiological, and photosynthetic effects of ryegrass in the pot experiments were better than those in soilless culture, because there were many other organic materials and inorganic ions in soil that could promote growth, whereas the plants in the hydroponic system lacked other nutrients that benefit plant growth. Many existing studies have shown that mine drainage or other wastewater can improve the quality and yield of one or more kinds of plants to different degrees after certain treatment, but some studies also show that the reclaimed water used for irrigation will cause harm to plants, soil and even human health.Jinfang Yang et al. reported that long-term irrigation with mine water significantly reduced the soil respiration rate and soil enzyme activity. Mine water irrigation also significantly inhibited wheat plant height, leaf area, chlorophyll content, and photosynthetic rate, and wheat production was also markedly reduced38. Jianjun Cha found that acidic mining waste water can reduce the pH of the soil profile and increase its electrical conductivity39. Junhao Qin et al. found that if treated mine water is used as an irrigation water source, acidic substances may still be introduced into the soil. This inhibits plant growth and may also enhance leaching of some trace elements in the soil to shallow aquifers, resulting in groundwater pollution40, 41. The results of this study are consistent with the above conclusions, that is, directly irrigating with mine water can significantly inhibit plant growth and photosynthesis, thus affecting the quality of ryegrass plants. MA et al. studied the effects of irrigation with mine wastewater on the physiological characters and heavy metals accumulation of winter wheat. It shows that irrigation with mine wastewater had negative effects on the winter wheat growth and grain yield. At anthesis stage, the leaf area, dry mass per stem, root activity and net photosynthetic rate of winter wheat in treatments were significantly lower and the plant height and leaf chlorophyll content was decreased. In addition, the heavy metals (Cr, Pb, Cu and Zn) contents in the grain of winter wheat under mine wastewater irrigation were significantly higher than those in control, it suggested that the irrigation with mine water could result in the heavy metals accumulation in wheat grain42. A large number of studies have shown that direct use of mine water for irrigation will have a negative impact on soil and plants, but this study found that after a certain processing of mine water (mine water was mixed with clear water in a ratio of 1:2) used for irrigation does not significantly alter soil properties, but can increase plant yield and quality, it will be meaningful to mine water reuse, soil utilization around the mining area and the agriculture.The conclusions of this study are based on mine water from Fushun mining area in Northeast China, but the effects of mine water on plants from other mining areas are uncertain. At the same time, ryegrass, a cold-season turfgrass, is only selected in this study. If it is other kinds of plants, how they respond to mine water irrigation needs further study. What are the effects of mine water irrigation on plants other than ryegrass that need further study. Moreover, this study was only a short-term experiment, and the effects of mine water on the properties of the soil matrix cannot be generalized. Indoor experiments can be regularly watered to maintain moisture, indoor temperature is relatively fixed, while the natural environment is a lot of uncertainty and uncontrollable. Would the results of a small-scale pot experiment in a controlled environment be different if it were applied to a field where there are many uncertainties about soil properties and atmospheric conditions? Long-term field experiments must also be conducted to confirm our findings in more realistic conditions. The use of mine water resources not only has environmental and social benefits but could also bring economic benefits43. This study demonstrated that mine water can be used in ecological restoration and agricultural irrigation in mining areas, and is therefore of great significance to environmental restoration. More

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    Hunting and persecution drive mammal declines in Iran

    Ceballos, G. et al. Accelerated modern human–induced species losses: Entering the sixth mass extinction. Sci. Adv. 1, e1400253. https://doi.org/10.1126/sciadv.1400253 (2015).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bradshaw, C. J. A. et al. Underestimating the challenges of avoiding a ghastly future. Front. Environ. Sci. 1, 615469. https://doi.org/10.3389/fcosc.2020.615419 (2021).Article 

    Google Scholar 
    IUCN. The IUCN Red List of Threatened Species. IUCN, Gland, Switzerland. http://www.iucnredlist.org (2020).Murray, K. A., Verde Arregoitia, L. D., Davidson, A., Di Marco, M. & Di Fonzo, M. M. I. Threat to the point: Improving the value of comparative extinction risk analysis for conservation action. Glob. Chang. Biol. 20, 483–494 (2014).Article 
    ADS 

    Google Scholar 
    Benítez-López, A. et al. The impact of hunting on tropical mammal and bird populations. Science 356, 180–183 (2017).Article 
    ADS 

    Google Scholar 
    Chichorro, F., Juslén, A. & Cardoso, P. A review of the relation between species traits and extinction risk. Biol. Conserv. 237, 220–229 (2019).Article 

    Google Scholar 
    Ripple, W. J. et al. Bushmeat hunting and extinction risk to the world’s mammals. R. Soc. Open. Sci. 3, 160498. https://doi.org/10.1098/rsos.160498 (2016).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hoffmann, M. et al. The changing fates of the world’s mammals. Phil. Trans. R. Soc. B. 366, 2598–2610 (2011).Article 

    Google Scholar 
    Verde Arregoitia, L. D. Biases, gaps, and opportunities in mammalian extinction risk research. Mammal. Rev. 46, 17–29 (2016).Article 

    Google Scholar 
    Di Marco, M. et al. Drivers of extinction risk in African mammals: The interplay of distribution state, human pressure, conservation response and species biology. Philos. Trans. R. Soc. Lond. B. 369, 1–12 (2014).Article 

    Google Scholar 
    Di Marco, M., Collen, B., Rondinini, C. & Mace, G. M. Historical drivers of extinction risk: Using past evidence to direct future monitoring. Proc. R. Soc. B. 282, 20150928. https://doi.org/10.1098/rspb.2015.0928 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bogoni, J. A., Ferraz, K. M. & Peres, C. A. Continental-scale local extinctions in mammal assemblages are synergistically induced by habitat loss and hunting pressure. Biol. Conserv. 272, 109635. https://doi.org/10.1016/j.biocon.2022.109635 (2022).Article 

    Google Scholar 
    Yusefi, G. H., Faizolahi, K., Darvish, J., Safi, K. & Brito, J. C. The species diversity, distribution and conservation status of the terrestrial mammals of Iran. J. Mammal. 100, 55–71 (2019).Article 

    Google Scholar 
    Keil, P. et al. Spatial scaling of extinction rates: Theory and data reveal nonlinearity and a major upscaling and downscaling challenge. Glob. Ecol. Biogeogr. 27, 2–13 (2018).Article 

    Google Scholar 
    Howard, C., Flather, C. H. & Stephens, P. A. A global assessment of the drivers of threatened terrestrial species richness. Nat. Commun. 11, 993. https://doi.org/10.1038/s41467-020-14771-6 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rodríguez, J. P. The difference conservation can make: integrating knowledge to reduce extinction risk. Oryx 51, 1–2 (2017).Article 

    Google Scholar 
    Cardillo, M. & Meijaard, E. Are comparative studies of extinction risk useful for conservation?. Trends Ecol. Evol. 27, 167–171 (2012).Article 

    Google Scholar 
    Davidson, A. D. et al. Geography of current and future global mammal extinction risk. PLoS ONE 12, e0186934. https://doi.org/10.1371/journal.pone.0186934 (2017).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Collen, B., Bykova, E., Ling, S., Milner-Gulland, E. J. & Purvis, A. Extinction risk: A comparative analysis of central Asian vertebrates. Biodivers. Conserv. 15, 1859–1871 (2006).Article 

    Google Scholar 
    Peñaranda, D. A. & Simonetti, J. A. Predicting and setting conservation priorities for Bolivian mammals based on biological correlates of the risk of decline. Conserv. Biol. 29, 834–843 (2015).Article 

    Google Scholar 
    Fritz, S. A., Bininda-Emonds, O. R. & Purvis, A. Geographical variation in predictors of mammalian extinction risk: Big is bad, but only in the tropics. Ecol. Lett. 12, 538–549 (2009).Article 

    Google Scholar 
    Cardillo, M. et al. Human population density and extinction risk in the world’s carnivores. PLoS Biol. 2, 909–914 (2004).Article 
    CAS 

    Google Scholar 
    Cardillo, M. et al. The predictability of extinction: Biological and external correlates of decline in mammals. Proc. R. Soc. B. 275, 1441–1448 (2008).Article 

    Google Scholar 
    Yackulic, C. B., Sanderson, E. W. & Uriat, M. Anthropogenic and environmental drivers of modern range loss in large mammals. Proc. Natl. Acad. Sci. USA 108, 4024–4029 (2011).Article 
    ADS 
    CAS 

    Google Scholar 
    Ripple, W. J. et al. Are we eating the world’s megafauna to extinction?. Conserv Lett 12, e12627. https://doi.org/10.1111/conl.12627 (2019).Article 

    Google Scholar 
    Ripple, W. J. et al. Extinction risk is most acute for the world’s largest and smallest vertebrates. PNAS https://doi.org/10.1073/pnas.1702078114 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bodmer, R. E., Eisenberg, J. E. & Redford, K. H. Hunting and the likelihood of extinction of Amazonian mammals. Conserv. Biol. 11, 460–466 (1997).Article 

    Google Scholar 
    Lee, T. M. & Jetz, W. Unravelling the structure of species extinction risk for predictive conservation science. Proc. R. Soc. B. 278, 1329–1338 (2011).Article 

    Google Scholar 
    Wolf, C. & Ripple, W. J. Prey depletion as a threat to the world’s large carnivores. Roy. Soc Open Sci 3, 160252. https://doi.org/10.1098/rsos.160252 (2016).Article 
    ADS 

    Google Scholar 
    Firouz, E. The complete fauna of Iran. I. B. (Tauris and Co Ltd, London, 2005).Cardillo, M. et al. Multiple causes of high extinction risk in large mammal species. Science 309, 1239–1241 (2005).Article 
    ADS 
    CAS 

    Google Scholar 
    Davidson, A. D., Hamilton, M. J., Boyer, A. G., Brown, J. H. & Ceballos, G. Multiple ecological pathways to extinction in mammals. Proc. Natl. Acad. Sci. USA 106, 10702–10705 (2009).Article 
    ADS 
    CAS 

    Google Scholar 
    Hill, J., DeVault, T. & Belant, J. Comparative influence of anthropogenic landscape pressures on cause-specific mortality of mammals. Perspect. Ecol. Conserv. 20, 38–44 (2022).
    Google Scholar 
    DOE-GIS. Areas under protection by the Department of Environment of Iran. Department of the Environment of Iran: GIS and Remote Sensing Section (2016).Kolahi, M., Sakai, T., Moriya, K. & Makhdoum, M. F. Challenges to the future development of Iran’s protected areas system. Environ. Manage. 50, 750–765 (2012).Article 
    ADS 

    Google Scholar 
    Morrison, J. M., Sechrest, W., Dinerstein, E., Wilcove, D. S. & Lamoreux, J. L. Persistence of large mammal faunas as indicators of human impact. J. Mammal. 88, 1363–1380 (2007).Article 

    Google Scholar 
    Ghoddousi, A. et al. The decline of ungulate populations in Iranian protected areas calls for urgent action against poaching. Oryx 53, 151–158 (2017).Article 

    Google Scholar 
    Soofi, M. et al. Assessing the relationship between illegal hunting of ungulates, wild prey occurrence and livestock depredation rate by large carnivores. J. Appl. Ecol. 56, 365–374 (2019).Article 

    Google Scholar 
    Khalatbari, L., Yusefi, G. H., Martinez-Freiria, F., Jowkar, H. & Brito, J. C. Availability of prey and natural habitats are related with temporal dynamics in range and habitat suitability for Asiatic cheetah. Hystrix Ital. J. Mammal. 29, 145–151 (2018).
    Google Scholar 
    Ripple, W. J. et al. Collapse of the world’s largest herbivores. Sci. Adv. 1, e1400103 (2015).Article 
    ADS 

    Google Scholar 
    Hoffmann, M. et al. The difference conservation makes to extinction risk of the world’s ungulates. Conserv. Biol. 29, 1303–1313 (2015).Article 

    Google Scholar 
    Yusefi, G. H. Conservation biogeography of terrestrial mammals in Iran diversity distribution and vulnerability to extinction. Front Biogeogr 13(2), 49765. https://doi.org/10.21425/F5FBG49765 (2021).Article 

    Google Scholar 
    Faurby, S. & Svenning, J.-C. A species-level phylogeny of all extant and late Quaternary extinct mammals using a novel heuristic-hierarchical Bayesian approach. Mol. Phylogenet. Evol. 84, 14–26 (2015).Article 

    Google Scholar 
    R Development Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing (2021).Paradis, E. & Schliep, K. ape 5.0: An environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35, 526–528 (2018).Article 

    Google Scholar 
    Jones, K. et al. PanTHERIA: A species-level database of life history, ecology, and geography of extant and recently extinct mammals. Ecology 90, 2648. https://doi.org/10.1890/08-1494.1 (2009).Article 

    Google Scholar 
    González-Suárez, M., Lucas, P. M. & Revilla, E. Biases in comparative analyses of extinction risk: Mind the gap. J. Anim. Ecol. 81, 1211–1222 (2012).Article 

    Google Scholar 
    Wang, Y. et al. Ecological correlates of extinction risk in Chinese birds. Ecography 41, 782–794 (2018).Article 

    Google Scholar 
    Wildlife Conservation Society-WCS, and Center for International Earth Science Information Network-CIESIN, Columbia University. Last of the wild project, Version 2, 2005 (LWP-2): Global human influence index (HII) Dataset. https://sedac.ciesin.columbia.edu/data/set/wildareas-v2-human-influence-index-geographic (2005).ESRI ArcGIS Desktop10.6. Redlands, CA: Environmental Systems Research Institute (2017).Hijmans, R. J. et al. raster: geographic data analysis and modeling. https://cran.r-project.org/web/packages/raster/index.html (2018).Pebesma, E. et al. rgdal: bindings for the geospatial data abstraction library. https://cran.r-project.org/web/packages/rgdal/index.html (2018).Bivand, R. et al. maptools: tools for reading and handling spatial objects. https://cran.r-project.org/web/packages/maptools/ index.html (2018).Purvis, A. Phylogenetic approaches to the study of extinction. Annu. Rev. Ecol. Evol. Syst. 39, 301–319 (2008).Article 

    Google Scholar 
    Venables, W. N. & Ripley, B. D. Modern applied statistics with S (Springer, 2002).Book 

    Google Scholar 
    Gittleman, J. L. & Kot, M. Adaptation: Statistics and a null model for estimating phylogenetic effects. Syst. Zool. 39, 227–241 (1990).Article 

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

    Google Scholar 
    Grueber, C. E., Nakagawa, S., Laws, R. J. & Jamieson, I. G. Multimodal inference in ecology and solution: Challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).Article 
    CAS 

    Google Scholar 
    Bartón, K. MuMIn: multi-model inference R package version 1.43.17. https://CRAN.R-project.org/package=MuMIn (2020). More

  • in

    Effects of plastic fragments on plant performance are mediated by soil properties and drought

    Peñuelas, J. et al. Assessment of the impacts of climate change on mediterranean terrestrial ecosystems based on data from field experiments and long-term monitored field gradients in Catalonia. Environ. Exp. Bot. 152, 49–59 (2018).
    Google Scholar 
    Pugnaire, F. I. et al. Climate change effects on plant-soil feedbacks and consequences for biodiversity and functioning of terrestrial ecosystems. Sci. Adv. 5, eaaz1834 (2019).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Baho, D. L., Bundschuh, M. & Futter, M. N. Microplastics in terrestrial ecosystems: Moving beyond the state of the art to minimize the risk of ecological surprise. Glob. Change Biol. 27, 3969–3986 (2021).CAS 

    Google Scholar 
    Rillig, M. C., Kim, S. W., Kim, T.-Y. & Waldman, W. R. The global plastic toxicity debt. Environ. Sci. Technol. 55, 2717–2719 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nizzetto, L., Futter, M. & Langaas, S. Are agricultural soils dumps for microplastics of urban origin?. (2016).Geyer, R., Jambeck, J. R. & Law, K. L. Production, use, and fate of all plastics ever made. Sci. Adv. 3, e1700782 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Barnes, D. K., Galgani, F., Thompson, R. C. & Barlaz, M. Accumulation and fragmentation of plastic debris in global environments. Philos. Trans. R. Soc. B Biol. Sci. 364, 1985–1998 (2009).CAS 

    Google Scholar 
    Rillig, M. C. Microplastic in terrestrial ecosystems and the soil?. (2012).de Souza Machado, A. A. et al. Microplastics can change soil properties and affect plant performance. Environ. Sci. Technol. 53, 6044–6052 (2019).ADS 
    PubMed 

    Google Scholar 
    Büks, F. & Kaupenjohann, M. Global concentrations of microplastics in soils–A review. Soil 6, 649–662 (2020).ADS 

    Google Scholar 
    Evangeliou, N. et al. Atmospheric transport is a major pathway of microplastics to remote regions. Nat. Commun. 11, 1–11 (2020).
    Google Scholar 
    Steinmetz, Z. et al. Plastic mulching in agriculture. Trading short-term agronomic benefits for long-term soil degradation?. Sci. Total Environ. 550, 690–705 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    de Souza Machado, A. A., Kloas, W., Zarfl, C., Hempel, S. & Rillig, M. C. Microplastics as an emerging threat to terrestrial ecosystems. Glob. Change Biol. 24, 1405–1416 (2018).ADS 

    Google Scholar 
    Qi, Y. et al. Macro-and micro-plastics in soil-plant system: Effects of plastic mulch film residues on wheat (Triticum aestivum) growth. Sci. Total Environ. 645, 1048–1056 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Weithmann, N. et al. Organic fertilizer as a vehicle for the entry of microplastic into the environment. Sci. Adv. 4, eaap8060 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Allen, S. et al. Atmospheric transport and deposition of microplastics in a remote mountain catchment. Nat. Geosci. 12, 339–344 (2019).ADS 
    CAS 

    Google Scholar 
    Kiyama, Y., Miyahara, K. & Ohshima, Y. Active uptake of artificial particles in the nematode Caenorhabditis elegans. J. Exp. Biol. 215, 1178–1183 (2012).PubMed 

    Google Scholar 
    Helmberger, M. S., Tiemann, L. K. & Grieshop, M. J. Towards an ecology of soil microplastics. Funct. Ecol. 34, 550–560 (2020).
    Google Scholar 
    Liu, M. et al. Microplastic and mesoplastic pollution in farmland soils in suburbs of Shanghai, China. Environ. Pollut. 242, 855–862 (2018).CAS 
    PubMed 

    Google Scholar 
    Lehmann, A., Fitschen, K. & Rillig, M. C. Abiotic and biotic factors influencing the effect of microplastic on soil aggregation. Soil Syst. 3, 21 (2019).CAS 

    Google Scholar 
    de Souza Machado, A. A. et al. Impacts of microplastics on the soil biophysical environment. Environ. Sci. Technol. 52, 9656–9665 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kim, S. W. & Rillig, M. C. Research trends of microplastics in the soil environment: Comprehensive screening of effects. Soil Ecol. Lett. 4, 109–118 (2022).CAS 

    Google Scholar 
    Lehmann, A., Leifheit, E. F., Gerdawischke, M. & Rillig, M. C. Microplastics have shape-and polymer-dependent effects on soil aggregation and organic matter loss–An experimental and meta-analytical approach. Microplast. Nanoplast. 1, 1–14 (2021).
    Google Scholar 
    Wan, Y., Wu, C., Xue, Q. & Hui, X. Effects of plastic contamination on water evaporation and desiccation cracking in soil. Sci. Total Environ. 654, 576–582 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Liang, Y., Lehmann, A., Yang, G., Leifheit, E. F. & Rillig, M. C. Effects of microplastic fibers on soil aggregation and enzyme activities are organic matter dependent. Front. Environ. Sci. 9, 97 (2021).
    Google Scholar 
    Lozano, Y. M., Lehnert, T., Linck, L. T., Lehmann, A. & Rillig, M. C. Microplastic shape, polymer type, and concentration affect soil properties and plant biomass. Front. Plant Sci. 12, 169 (2021).
    Google Scholar 
    Kemper, W. Aggregate stability. Methods Soil Anal. Part 1 Phys. Mineral. Prop. Incl. Stat. Meas. Sampl. 9, 511–519 (1965).
    Google Scholar 
    Rose, C. W. & Rose, C. W. An Introduction to the Environmental Physics of Soil, Water and Watersheds (Cambridge University Press, 2004).
    Google Scholar 
    Horn, R., Taubner, H., Wuttke, M. & Baumgartl, T. Soil physical properties related to soil structure. Soil Tillage Res. 30, 187–216 (1994).
    Google Scholar 
    Beven, K. & Germann, P. Macropores and water flow in soils. Water Resour. Res. 18, 1311–1325 (1982).ADS 

    Google Scholar 
    De Vries, F. T. et al. Abiotic drivers and plant traits explain landscape-scale patterns in soil microbial communities. Ecol. Lett. 15, 1230–1239 (2012).PubMed 

    Google Scholar 
    Kaisermann, A., de Vries, F. T., Griffiths, R. I. & Bardgett, R. D. Legacy effects of drought on plant–soil feedbacks and plant–plant interactions. New Phytol. 215, 1413–1424 (2017).CAS 
    PubMed 

    Google Scholar 
    Martorell, C., MartÍnez-Blancas, A. & GarcíaMeza, D. Plant–soil feedbacks depend on drought stress, functional group, and evolutionary relatedness in a semiarid grassland. Ecology 102, e03499 (2021).PubMed 

    Google Scholar 
    Rillig, M. C., Lehmann, A., de Souza Machado, A. A. & Yang, G. Microplastic effects on plants. New Phytol. 223, 1066–1070 (2019).PubMed 

    Google Scholar 
    Lozano, Y. M. & Rillig, M. C. Effects of microplastic fibers and drought on plant communities. Environ. Sci. Technol. 54, 6166–6173 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Denef, K. et al. Influence of dry–wet cycles on the interrelationship between aggregate, particulate organic matter, and microbial community dynamics. Soil Biol. Biochem. 33, 1599–1611 (2001).CAS 

    Google Scholar 
    Ochoa-Hueso, R. et al. Drought consistently alters the composition of soil fungal and bacterial communities in grasslands from two continents. Glob. Change Biol. 24, 2818–2827 (2018).ADS 

    Google Scholar 
    Naylor, D. & Coleman-Derr, D. Drought stress and root-associated bacterial communities. Front. Plant Sci. 8, 2223 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Fu, W. et al. Community response of arbuscular mycorrhizal fungi to extreme drought in a cold-temperate grassland. New Phytol. 234, 2003–2017 (2022).PubMed 

    Google Scholar 
    Lin, D. et al. Microplastics negatively affect soil fauna but stimulate microbial activity: Insights from a field-based microplastic addition experiment. Proc. R. Soc. B 287, 20201268 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Boots, B., Russell, C. W. & Green, D. S. Effects of microplastics in soil ecosystems: Above and below ground. Environ. Sci. Technol. 53, 11496–11506 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bosker, T., Bouwman, L. J., Brun, N. R., Behrens, P. & Vijver, M. G. Microplastics accumulate on pores in seed capsule and delay germination and root growth of the terrestrial vascular plant Lepidium sativum. Chemosphere 226, 774–781 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Zimmerman, R. & Kardos, L. Effect of bulk density on root growth. Soil Sci. 91, 280–288 (1961).ADS 

    Google Scholar 
    Ruser, R., Sehy, U., Weber, A., Gutser, R. & Munch, J. Main driving variables and effect of soil management on climate or ecosystem-relevant trace gas fluxes from fields of the FAM. In Perspectives for agroecosystem
    management Chp 2.2, 79–120. ISBN 9780444519054 Elsevier, (2008).Huang, Y. et al. LDPE microplastic films alter microbial community composition and enzymatic activities in soil. Environ. Pollut. 254, 112983 (2019).CAS 
    PubMed 

    Google Scholar 
    Fierer, N., Bradford, M. A. & Jackson, R. B. Toward an ecological classification of soil bacteria. Ecology 88, 1354–1364 (2007).PubMed 

    Google Scholar 
    Hortal, S. et al. Soil microbial community under a nurse-plant species changes in composition, biomass and activity as the nurse grows. Soil Biol. Biochem. 64, 139–146 (2013).CAS 

    Google Scholar 
    Scheurer, M. & Bigalke, M. Microplastics in Swiss floodplain soils. Environ. Sci. Technol. 52, 3591–3598 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Jambeck, J. R. et al. Plastic waste inputs from land into the ocean. Science 347, 768–771 (2015).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Fuller, S. & Gautam, A. A procedure for measuring microplastics using pressurized fluid extraction. Environ. Sci. Technol. 50, 5774–5780 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Schloerke, B. et al. GGally: Extension to ‘ggplot2’. R package version 2.1. 2. (2021).Venables, W. & Ripley, B. Modern applied statistics with S fourth edition. Publisher Springer-Verlag, New York. (2002).Lenth, R. V. Emmeans: Estimated marginal means, aka least-squares means. R package version 1.6.3 (2021).R Core Team et al. R: A language and environment for statistical computing. (2013).Wickham, H. et al. Welcome to the Tidyverse. J. Open Source Softw. 4, 1686 (2019).ADS 

    Google Scholar 
    Pedersen, T. L. Patchwork: The composer of plots. R package version 1, 182 (2020).Neuwirth, E. RColorBrewer: ColorBrewer palettes. R package version 1.1-2. (2014). More