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    Phenotypic and environmental correlates of natal dispersal in a long-lived territorial vulture

    1.
    Greenwood, P. J. & Harvey, P. H. The natal and breeding dispersal of birds. Annu. Rev. Ecol. Syst. 13, 1–21 (1982).
    Article  Google Scholar 
    2.
    Paradis, E., Baillie, S. R., Sutherland, W. J. & Gregory, R. D. Patterns of natal and breeding dispersal in birds. J. Anim. Ecol. 67, 518–536 (1998).
    Article  Google Scholar 

    3.
    Clobert, J. Dispersal (Oxford University Press, 2001).
    Google Scholar 

    4.
    Clobert, J., Baguette, M., Benton, T. G. & Bullock, J. M. Dispersal Ecology and Evolution (Oxford University Press, 2012).
    Google Scholar 

    5.
    Bowler, D. E. & Benton, T. G. Causes and consequences of animal dispersal strategies: Relating individual behaviour to spatial dynamics. Biol. Rev. 80, 205–225 (2005).
    PubMed  Article  Google Scholar 

    6.
    Ronce, O. How does it feel to be like a rolling stone? Ten questions about dispersal evolution. Annu. Rev. Ecol. Evol. Syst. 38, 231–253 (2007).
    Article  Google Scholar 

    7.
    Nathan, R., Perry, G., Cronin, J. T., Strand, A. E. & Cain, M. L. Methods for estimating long-distance dispersal. Oikos 103, 261–273 (2011).
    Article  Google Scholar 

    8.
    Stevens, V. M. et al. Dispersal syndromes and the use of life-histories to predict dispersal. Evol. Appl. 6, 630–642 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    9.
    Driscoll, D. A. et al. The trajectory of dispersal research in conservation biology: Systematic review. PLoS ONE 9, e95053 (2014).
    ADS  PubMed  PubMed Central  Article  Google Scholar 

    10.
    Smith, A. L. et al. Managing uncertainty in movement knowledge for environmental decisions. Conserv. Lett. 12, 1–8. https://doi.org/10.1111/conl.12620 (2018).
    Article  Google Scholar 

    11.
    Koenig, W. D., Van Vuren, D. & Hooge, P. N. Detectability, philopatry, and the distribution of dispersal distances in vertebrates. Trends Ecol. Evol. 11, 514–517 (1996).
    CAS  PubMed  Article  Google Scholar 

    12.
    Trakhtenbrotl, A., Nathan, R., Perry, G. & Richardson, D. M. The importance of long-distance dispersal in biodiversity conservation. Divers. Distrib. 11, 173–181 (2005).
    Article  Google Scholar 

    13.
    Nathan, R., Klein, E., Robledo-Arnuncio, J. J. & Revilla, E. Dispersal kernels: Review. In Dispersal Ecology and Evolution (eds Clobert, J. et al.) 187–210 (Oxford University Press, 2012).
    Google Scholar 

    14.
    Van Houtan, K. S., Pimm, S. L., Halley, J. M., Bierregaard, R. O. & Lovejoy, T. E. Dispersal of Amazonian birds in continuous and fragmented forest. Ecol. Lett. 10, 219–229 (2007).
    PubMed  Article  Google Scholar 

    15.
    Matthysen, E. Multicausality of dispersal: A review. Dispersal Ecol. Evol. 3, 18 (2012).
    Google Scholar 

    16.
    Ronce, O., Olivieri, I., Clobert, J. & Danchin, E. Perspectives on the study of dispersal evolution. In Dispersal (eds Clobert, J. et al.) 341–357 (Oxford University Press, 2001).
    Google Scholar 

    17.
    Clobert, J., Le Galliard, J.-F., Cote, J., Meylan, S. & Massot, M. Informed dispersal, heterogeneity in animal dispersal syndromes and the dynamics of spatially structured populations. Ecol. Lett. 12, 197–209 (2009).
    PubMed  Article  Google Scholar 

    18.
    McPeek, M. A. & Holt, R. D. The evolution of dispersal in spatially and temporally varying environments. Am. Midl. Nat. 140, 1010–1027 (1992).
    Article  Google Scholar 

    19.
    Dingle, H. Migration. The Biology of Life on the Move (Oxford University Press, 1996).
    Google Scholar 

    20.
    Verhulst, S., Perrins, C. M. & Riddington, R. Natal dispersal of great tits in a patchy environment. Ecology 78, 864 (1997).
    Article  Google Scholar 

    21.
    Tarwater, C. E., Beissinger, S. R. & Gaillard, J.-M. Dispersal polymorphisms from natal phenotype-environment interactions have carry-over effects on lifetime reproductive success of a tropical parrot. Ecol. Lett. 15, 1218–1229 (2012).
    PubMed  Article  Google Scholar 

    22.
    Baines, C. B., Ferzoco, I. M. C. & McCauley, S. J. Phenotype-by-environment interactions influence dispersal. J. Anim. Ecol. 88, 1263–1274 (2019).
    PubMed  Article  Google Scholar 

    23.
    López-López, P., Zuberogoitia, Í., Alcántara, M. & Gil, J. A. Philopatry, natal dispersal, first settlement and age of first breeding of bearded vultures Gypaetus barbatus in central Pyrenees. Bird Study 60, 555–560 (2013).
    Article  Google Scholar 

    24.
    Poessel, S. A., Bloom, P. H., Braham, M. A. & Katzner, T. E. Age- and season-specific variation in local and long-distance movement behavior of golden eagles. Eur. J. Wildl. Res. 62, 377–393 (2016).
    Article  Google Scholar 

    25.
    Benard, M. F. & McCauley, S. J. Integrating across life-history stages: Consequences of natal habitat effects on dispersal. Am. Nat. 171, 553–567 (2008).
    PubMed  Article  Google Scholar 

    26.
    Matthysen, E. Density-dependent dispersal in birds and mammals. Ecography 28, 403–416 (2005).
    Article  Google Scholar 

    27.
    Stamps, J. A. Conspecific attraction and aggregation in territorial species. Am. Nat. 131, 329–347 (1988).
    Article  Google Scholar 

    28.
    van Horne, B. Density as a misleading indicator of habitat quality. J. Wildl. Manage. 47, 893–901 (1983).
    Article  Google Scholar 

    29.
    Serrano, D. & Tella, J. L. The role of despotism and heritability in determining settlement patterns in the colonial lesser kestrel. Am. Nat. 169, E53–E67 (2007).
    PubMed  Article  Google Scholar 

    30.
    Pyle, P. Age at first breeding and natal dispersal in a declining population of Cassin’s Auklet. Auk 118, 996–1007 (2001).
    Article  Google Scholar 

    31.
    Greenwood, P. J. Mating systems, philopatry and dispersal in birds and mammals. Anim. Behav. 28, 1140–1162 (1980).
    Article  Google Scholar 

    32.
    Clarke, A., Sæther, B.-E. & Røskaft, E. Sex biases in avian dispersal: A reappraisal. Oikos 79, 429–438 (1997).
    Article  Google Scholar 

    33.
    Sanz-Aguilar, A. et al. Sex- and age-dependent patterns of survival and breeding success in a long-lived endangered avian scavenger. Sci. Rep. 7, 40204 (2017).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    34.
    Sergio, F., Blas, J. & Hiraldo, F. Predictors of floater status in a long-lived bird: A cross-sectional and longitudinal test of hypotheses. J. Anim. Ecol. 78, 109–118 (2009).
    PubMed  Article  Google Scholar 

    35.
    Zabala, J. & Zuberogoitia, I. Breeding performance and survival in the peregrine falcon Falco peregrinus support an age-related competence improvement hypothesis mediated via an age threshold. J. Avian Biol. 46, 141–150 (2015).
    Article  Google Scholar 

    36.
    Kim, S. Y., Velando, A., Torres, R. & Drummond, H. Effects of recruiting age on senescence, lifespan and lifetime reproductive success in a long-lived seabird. Oecologia 166, 615–626 (2011).
    ADS  PubMed  Article  Google Scholar 

    37.
    Bonte, D. et al. Costs of dispersal. Biol. Rev. Camb. Philos. Soc. 87, 290–312 (2012).
    PubMed  Article  Google Scholar 

    38.
    Spear, L. B., Pyle, P. & Nur, N. Natal dispersal in the western gull: Proximal factors and fitness consequences. J. Anim. Ecol. 67, 165–179 (2009).
    Article  Google Scholar 

    39.
    Forero, M., Donázar, J.A. & Hiraldo, F. Causes and fitness consequences of natal dispersal in a population of black kites. Ecology 83, 858–872 (2002).
    Article  Google Scholar 

    40.
    Barbraud, C., Johnson, A. R. & Bertault, G. Phenotypic correlates of post-fledging dispersal in a population of greater flamingos: The importance of body condition. J. Anim. Ecol. 72, 246–257 (2003).
    Article  Google Scholar 

    41.
    McNamara, J. M. & Dall, S. R. X. The evolution of unconditional strategies via the ‘multiplier effect’. Ecol. Lett. 14, 237–243 (2011).
    PubMed  Article  Google Scholar 

    42.
    Shields, W. M. Philopatry, inbreeding, and the evolution of sex (State University of New York, 1982).
    Google Scholar 

    43.
    Elorriaga, J. et al. First documented case of long-distance dispersal in the Egyptian Vulture (Neophron percnopterus). J. Raptor Res. 43, 142–145 (2009).
    Article  Google Scholar 

    44.
    Carrete, M. et al. Habitat, human pressure, and social behavior: Partialling out factors affecting large-scale territory extinction in an endangered vulture. Biol. Conserv. 136, 143–154 (2007).
    Article  Google Scholar 

    45.
    García-Ripollés, C. & López-López, P. Integrating effects of supplementary feeding, poisoning, pollutant ingestion and wind farms of two vulture species in Spain using a population viability analysis. J. Ornithol. 152, 879–888 (2011).
    Article  Google Scholar 

    46.
    Sanz-Aguilar, A. et al. Action on multiple fronts, illegal poisoning and wind farm planning, is required to reverse the decline of the Egyptian vulture in southern Spain. Biol. Conserv. 187, 10–18 (2015).
    Article  Google Scholar 

    47.
    Tauler, H. et al. Identifying key demographic parameters for the viability of a growing population of the endangered Egyptian Vulture Neophron percnopterus. Bird Conserv. Int. 25, 426–439 (2015).
    Article  Google Scholar 

    48.
    Lieury, N., Gallardo, M., Ponchon, C., Besnard, A. & Millon, A. Relative contribution of local demography and immigration in the recovery of a geographically-isolated population of the endangered Egyptian vulture. Biol. Conserv. 191, 349–356 (2015).
    Article  Google Scholar 

    49.
    Agudo, R., Rico, C., Hiraldo, F. & Donázar, J. A. Evidence of connectivity between continental and differentiated insular populations in a highly mobile species. Divers. Distrib. 17, 1–12 (2011).
    Article  Google Scholar 

    50.
    Travis, J. M. J. & Dytham, C. Habitat persistence, habitat availability and the evolution of dispersal. Proc. R. Soc. B Biol. Sci. 266, 723–728 (1999).
    Article  Google Scholar 

    51.
    Poethke, H. J. & Hovestadt, T. Evolution of density- and patch-size-dependent dispersal rates. Proc. R. Soc. B Biol. Sci. 269, 637–645 (2002).
    Article  Google Scholar 

    52.
    Kun, Á. & Scheuring, I. The evolution of density-dependent dispersal in a noisy spatial population model. Oikos 115, 308–320 (2006).
    Article  Google Scholar 

    53.
    Hovestadt, T., Kubisch, A. & Poethke, H. J. Information processing in models for density-dependent emigration: A comparison. Ecol. Modell. 221, 405–410 (2010).
    Article  Google Scholar 

    54.
    Morton, E. R. et al. Dispersal: a matter of scale. Ecology 99, 938–946 (2018).
    PubMed  Article  Google Scholar 

    55.
    Delestrade, A., McCleery, R. H. & Perrins, C. M. Natal dispersal in a heterogeneous environment: The case of the Great tit in Wytham. Acta Oecol. 17, 519–529 (1996).
    Google Scholar 

    56.
    Luna, Á., Palma, A., Sanz-Aguilar, A., Tella, J. L. & Carrete, M. Sex, personality and conspecific density influence natal dispersal with lifetime fitness consequences in urban and rural burrowing owls. PLoS ONE 15, 1–17 (2020).
    Google Scholar 

    57.
    Eikenaar, C., Richardson, D. S., Brouwer, L. & Komdeur, J. Sex-biased natal dispersal in a closed, saturated population of Seychelles warblers Acrocephalus sechellensis. J. Avian Biol. 39, 73–80 (2008).
    Article  Google Scholar 

    58.
    Serrano, D., Tella, J. L., Donázar, J. A. & Pomarol, M. Social and individual features affecting natal dispersal in the colonial Lesser Kestrel. Ecology 84, 3044–3054 (2003).
    Article  Google Scholar 

    59.
    Hernández, M. & Margalida, A. Poison-related mortality effects in the endangered Egyptian vulture (Neophron percnopterus) population in Spain. Eur. J. Wildl. Res. 55, 415–423 (2009).
    Article  Google Scholar 

    60.
    Fattebert, J., Balme, G., Dickerson, T., Slotow, R. & Hunter, L. Density-dependent natal dispersal patterns in a leopard population recovering from over-harvest. PLoS ONE 10, 1–15 (2015).
    Article  CAS  Google Scholar 

    61.
    Gundersen, G., Andreassen, H. P. & Ims, R. A. Individual and population level determinants of immigration success on local habitat patches: An experimental approach. Ecol. Lett. 5, 294–301 (2002).
    Article  Google Scholar 

    62.
    Newby, J. R. et al. Human-caused mortality influences spatial population dynamics: Pumas in landscapes with varying mortality risks. Biol. Conserv. 159, 230–239 (2013).
    Article  Google Scholar 

    63.
    Doligez, B., Danchin, E. & Clobert, J. Public information and breeding habitat selection in a wild bird population. Science 297, 1168–1170 (2002).
    ADS  CAS  PubMed  Article  Google Scholar 

    64.
    Delibes, M., Gaona, P. & Ferreras, P. Effects of an attractive sink leading into maladaptive habitat selection. Am. Nat. 158, 277–285 (2001).
    CAS  PubMed  Article  Google Scholar 

    65.
    Cortés-Avizanda, A., Ceballos, O. & Donázar, J. A. Long-term trends in population size and breeding success in the Egyptian Vulture (Neophron percnopterus) in Northern Spain. J. Raptor Res. 43, 43–49 (2009).
    Article  Google Scholar 

    66.
    Zuberogoitia, I., Zabala, J., Martínez, J. A., Martínez, J. E. & Azkona, A. Effect of human activities on Egyptian vulture breeding success. Anim. Conserv. 11, 313–320 (2008).
    Article  Google Scholar 

    67.
    Schlaepfer, M. A., Runge, M. C. & Sherman, P. W. Ecological and evolutionary traps. Trends Ecol. Evol. 17, 474–480 (2002).
    Article  Google Scholar 

    68.
    Robertson, B. A. & Hutto, R. L. A framework for understanding ecological traps and an evaluation of existing evidence. Ecology 87, 1075–1085 (2006).
    PubMed  Article  Google Scholar 

    69.
    Betts, M. G., Hadley, A. S., Rodenhouse, N. & Nocera, J. J. Social information trumps vegetation structure in breeding-site selection by a migrant songbird. Proc. R. Soc. B Biol. Sci. 275, 2257–2263 (2008).
    Article  Google Scholar 

    70.
    Stodola, K. W. & Ward, M. P. The emergent properties of conspecific attraction can limit a species’ ability to track environmental change. Am. Nat. 189, 726–733 (2017).
    PubMed  Article  Google Scholar 

    71.
    Serrano, D. Dispersal in raptors. In Birds of Prey. Biology and Conservation in the XXI Century (eds Hernán Sarasola, J. et al.) 95–121 (Springer, 2018).
    Google Scholar 

    72.
    Trochet, A., Stevens, V. M. & Baguette, M. Evolution of sex-biased dispersal. Q. Rev. Biol. 91, 297–320 (2016).
    PubMed  Article  Google Scholar 

    73.
    Forsman, E. D., Anthony, R. G., Reid, J. A., Loschl, P. J. & Sovern, S. G. Natal and breeding dispersal of northern spotted owls. Wildl. Monogr. 1, 35 (2002).
    Google Scholar 

    74.
    Steiner, U. K. & Gaston, A. J. Reproductive consequences of natal dispersal in a highly philopatric seabird. Behav. Ecol. 16, 634–639 (2005).
    Article  Google Scholar 

    75.
    González, L. M. et al. Effective natal dispersal and age of maturity in the threatened Spanish Imperial Eagle Aquila adalberti: Conservation implications. Bird Stud. 53, 285–293 (2006).
    Article  Google Scholar 

    76.
    Oro, D., Tavecchia, G. & Genovart, M. Comparing demographic parameters for philopatric and immigrant individuals in a long-lived bird adapted to unstable habitats. Oecologia 165, 935–945 (2011).
    ADS  PubMed  Article  Google Scholar 

    77.
    Grande, J. M. et al. Survival in a long-lived territorial migrant: Effects of life-history traits and ecological conditions in wintering and breeding areas. Oikos 118, 580–590 (2009).
    Article  Google Scholar 

    78.
    Van Noordwijk, A. J. On bias due to observer distribution in the analysis of data on natal dispersal in birds. J. Appl. Stat. 22, 683–694 (1995).
    Article  Google Scholar 

    79.
    Ens, B. J. et al. Despotic distribution and deferred maturity: Two sides of the same coin?. Am. Nat. 146, 625–650 (2015).
    Article  Google Scholar 

    80.
    Maness, T. J. & Anderson, D. J. Predictors of juvenile survival in birds. Ornithol. Monogr. 78, 1–55 (2013).
    Article  Google Scholar 

    81.
    Azpillaga, M., Real, J. & Hernández-Matías, A. Effects of rearing conditions on natal dispersal processes in a long-lived predator bird. Ecol. Evol. 8, 6682–6698 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    82.
    Delgado, M., Penteriani, V., Revilla, E. & Nams, O. The effect of phenotypic traits and external cues on natal dispersal movements. J. Anim. Ecol. 79, 620–632 (2010).
    Article  Google Scholar 

    83.
    Zuberogoitia, I., Zabala, J., Martínez, J. E., González-Oreja, J. A. & López-López, P. Effective conservation measures to mitigate the impact of human disturbances on the endangered Egyptian vulture. Anim. Conserv. 17, 410–418 (2014).
    Article  Google Scholar 

    84.
    Donázar, J. A. et al. Epizootics and sanitary regulations drive long-term changes in fledgling body condition of a threatened vulture. Ecol. Indic. 113, 106188 (2020).
    Article  Google Scholar 

    85.
    Boulinier, T. & Danchin, E. The use of conspecific reproductive success for breeding patch selection in terrestrial migratory species. Evol. Ecol. 11, 505–517 (1997).
    Article  Google Scholar 

    86.
    Brown, J. H. & Kodric-Brown, A. Turnover rates in insular biogeography: Effect of immigration on extinction. Ecology 58, 445–449 (1977).
    Article  Google Scholar 

    87.
    Benton, T. G. & Bowler, D. E. Linking dispersal to spatial dynamics. In Dispersal Ecology and Evolution (eds Clobert, J. et al.) 251–265 (Oxford University Press, 2012).
    Google Scholar 

    88.
    Delgado, M. D. M., Ratikainen, I. I. & Kokko, H. Inertia: The discrepancy between individual and common good in dispersal and prospecting behaviour. Biol. Rev. 86, 717–732 (2011).
    Article  Google Scholar 

    89.
    Doncaster, C. P., Clobert, J., Doligez, B., Gustafsson, L. & Danchin, E. Balanced dispersal between spatially varying local populations: An alternative to the source-sink model. Am. Nat. 150, 425–445 (1997).
    CAS  PubMed  Article  Google Scholar 

    90.
    Millon, A., Lambin, X., Devillard, S. & Schaub, M. Quantifying the contribution of immigration to population dynamics: A review of methods, evidence and perspectives in birds and mammals. Biol. Rev. 94, 2049–2067 (2019).
    PubMed  Article  Google Scholar 

    91.
    Altwegg, R., Collingham, Y. C., Erni, B. & Huntley, B. Density-dependent dispersal and the speed of range expansions. Divers. Distrib. 19, 60–68 (2013).
    Article  Google Scholar 

    92.
    Tauler-Ametller, H., Hernández-Matías, A., Pretus, J. L. L. & Real, J. Landfills determine the distribution of an expanding breeding population of the endangered Egyptian Vulture Neophron percnopterus. Ibis 159, 757–768 (2017).
    Article  Google Scholar 

    93.
    Gilroy, J. J. & Sutherland, W. J. Beyond ecological traps: Perceptual errors and undervalued resources. Trends Ecol. Evol. 22, 351–356 (2007).
    PubMed  Article  Google Scholar 

    94.
    Patten, M. A. & Kelly, J. F. Habitat selection and the perceptual trap. Ecol. Appl. 20, 2148–2156 (2010).
    PubMed  Article  Google Scholar 

    95.
    Doebeli, M. & Ruxton, G. D. Evolution of dispersal rates in metapopulation models: Branching and cyclic dynamics in phenotype space. Evolution 51, 1730 (1997).
    PubMed  Article  Google Scholar 

    96.
    Murrell, D. J., Travis, J. M. J. & Dytham, C. The evolution of dispersal distance in spatially-structured populations. Oikos 97, 229–236 (2002).
    Article  Google Scholar 

    97.
    Heino, M. & Hanski, I. Evolution of migration rate in a spatially realistic metapopulation model. Am. Nat. 157, 495–511 (2001).
    CAS  PubMed  Article  Google Scholar 

    98.
    Mathias, A., Kisdi, È. & Olivieri, I. Divergent evolution of dispersal in a heterogeneous landscape. Evolution 55, 246–259 (2001).
    CAS  PubMed  Article  Google Scholar 

    99.
    Baguette, M., Clobert, J. & Schtickzelle, N. Metapopulation dynamics of the bog fritillary butterfly: Experimental changes in habitat quality induced negative density-dependent dispersal. Ecography 34, 170–176 (2011).
    Article  Google Scholar 

    100.
    Margalida, A. et al. Uneven large-scale movement patterns in wild and reintroduced pre-adult bearded vultures: Conservation implications. PLoS ONE 8, e65857 (2013).
    ADS  CAS  PubMed  PubMed Central  Article  Google Scholar 

    101.
    Buechley, E. R., McGrady, M. J., Çoban, E. & Şekercioğlu, Ç. H. Satellite tracking a wide-ranging endangered vulture species to target conservation actions in the Middle East and East Africa. Biodivers. Conserv. 27, 2293–2310 (2018).
    Article  Google Scholar 

    102.
    Dwyer, J. F., Fraser, J. D. & Morrison, J. L. Evolution of communal roosting: A social refuge-territory prospecting hypothesis. J. Raptor Res. 52, 407–419 (2018).
    Article  Google Scholar 

    103.
    Blanco, G. & Tella, J. L. Temporal, spatial and social segregation of red-billed choughs between two types of communal roost: A role for mating and territory acquisition. Anim. Behav. 57, 1219–1227 (1999).
    CAS  PubMed  Article  Google Scholar 

    104.
    Bocedi, G., Heinonen, J. & Travis, J. M. J. Uncertainty and the role of information acquisition in the evolution of context-dependent emigration. Am. Nat. 179, 606–620 (2012).
    PubMed  Article  Google Scholar 

    105.
    Delgado, M. M., Bartoń, K. A., Bonte, D. & Travis, J. M. J. Prospecting and dispersal: Their eco-evolutionary dynamics and implications for population patterns. Proc. R. Soc. B Biol. Sci. 281, 20132851 (2014).
    CAS  Article  Google Scholar 

    106.
    Kesler, D. C., Walters, J. R. & Kappes, J. J. Social influences on dispersal and the fat-tailed dispersal distribution in red-cockaded woodpeckers. Behav. Ecol. 21, 1337–1343 (2010).
    Article  Google Scholar 

    107.
    Ducros, D. et al. Beyond dispersal versus philopatry? Alternative behavioural tactics of juvenile roe deer in a heterogeneous landscape. Oikos 129, 81–92 (2019).
    Article  Google Scholar 

    108.
    BirdLife International. Species factsheet: Neophron percnopterus. (2019). Available at: http://www.birdlife.org. Accessed 19 Dec 2019.

    109.
    Donázar, J. A., Ceballos, O. & Tella, J. L. Communal roosts of Egyptian vulture (Neophron percnopterus): Dynamics and implications for the species conservation. In Biología y conservación de las rapaces Mediterráneas (eds Muntaner, J. & Muntaner, J.) 189–201 (SEO/Birdlife, 1996).
    Google Scholar 

    110.
    Hernández-Matías, A. et al. Determinants of territorial recruitment in bonelli’s eagle (Aquila fasciata) populations. Auk 127, 173–184 (2010).
    Article  Google Scholar 

    111.
    Phipps, W. L. et al. Spatial and temporal variability in migration of a soaring raptor across three continents. Front. Ecol. Evol. 7, 1–14 (2019).
    Article  Google Scholar 

    112.
    del Moral, J. C. El Alimoche Común en España Población Reproductora en 2008 y Método de Censo (SEO/Birdlife, 2009).
    Google Scholar 

    113.
    del Moral, J. C. & El Martí, R. Alimoche Común en España y Portugal. (I Censo Coordinado). Año 2000. Monografía no 8 (SEO/Birdlife, 2002).
    Google Scholar 

    114.
    Donázar, J. A. & Ceballos, O. Growth rates of nestling Egyptian Vultures Neophrone percnopterus in relation to brood size, hatching order and environmental factors. Ardea 77, 217–226 (1989).
    Google Scholar 

    115.
    Imdadullah, M., Aslam, M. & Altaf, S. Mctest: An r package for detection of collinearity among regressors. R J. 8, 499–509 (2016).
    Article  Google Scholar 

    116.
    Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer, 2002).
    Google Scholar 

    117.
    Giam, X. & Olden, J. D. Quantifying variable importance in a multimodel inference framework. Methods Ecol. Evol. 7, 388–397 (2016).
    Article  Google Scholar 

    118.
    Schabenberger, O. & Pierce, F. J. Contemporary Statistical Models for the Plant and Soil Sciences (CRC Press, 2002).
    Google Scholar 

    119.
    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, 2018).

    120.
    Hartig, F. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level / Mixed) Regression Models. R package version 0.2.4. (2019). More

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    Author Correction: Continent-wide tree fecundity driven by indirect climate effects

    Nicholas School of the Environment, Duke University, Durham, NC, USA
    James S. Clark, Christopher L. Kilner, Jordan Luongo, Renata Poulton-Kamakura, Ethan Ready, Chantal D. Reid, C. Lane Scher, William H. Schlesinger, Shubhi Sharma, Samantha Sutton, Jennifer J. Swenson & Margaret Swift

    INRAE, LESSEM, University Grenoble Alpes, Saint-Martin-d’Heres, France
    James S. Clark, Benoit Courbaud, Georges Kunstler, Kyle C. Rodman & Thomas T. Veblen

    Department of Geography, University of Colorado Boulder, Boulder, CO, USA
    Robert Andrus & Emily Moran

    School of Natural Sciences, University of California, Merced, Merced, CA, USA
    Melaine Aubry-Kientz

    Forest Research Institute, University of Quebec in Abitibi-Temiscamingue, Rouyn-Noranda, QC, Canada
    Yves Bergeron

    Department of Systematic Zoology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
    Michal Bogdziewicz

    USDA Forest Service, Southern Research Station, Monticello, AR, USA
    Don C. Bragg

    USDA Forest Service Southern Research Station, Auburn, AL, USA
    Dale Brockway & Timothy J. Fahey

    Natural Resources, Cornell University, Ithaca, NY, USA
    Natalie L. Cleavitt

    Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
    Susan Cohen

    Greater Yellowstone Network, National Park Service, Bozeman, MT, USA
    Robert Daley, Kristin L. Legg & Erin Shanahan

    USGS Western Ecological Research Center, Three Rivers, CA, USA
    Adrian J. Das & Nathan L. Stephenson

    Earth and Environment, Boston University, Boston, MA, USA
    Michael Dietze

    Finnish Meteorological Institute, Helsinki, Finland
    Istem Fer

    Forest Resources, University of Washington, Seattle, WA, USA
    Jerry F. Franklin

    Department of Biological Science, Northern Arizona University, Flagstaff, AZ, USA
    Catherine A. Gehring, Amy V. Whipple & Thomas G. Whitham

    University of California, Santa Cruz, Santa Cruz, CA, USA
    Gregory S. Gilbert & Kai Zhu

    USDA Forest Service, Bent Creek Experimental Forest, Asheville, NC, USA
    Cathryn H. Greenberg

    USDA Forest Service Southern Research Station, Eastern Forest Environmental Threat Assessment Center, Research Triangle Park, NC, USA
    Qinfeng Guo

    Department of Biology, University of Washington, Seattle, WA, USA
    Janneke HilleRisLambers

    School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, USA
    Ines Ibanez

    Department of Biology, University of Saskatchewan, Saskatoon, SK, Canada
    Jill Johnstone

    Health and Environmental Sciences Department, Xian Jiaotong-Liverpool University, Suzhou, China
    Johannes Knops

    Hastings Reservation, University of California Berkeley, Carmel Valley, CA, USA
    Walter D. Koenig

    Department of Biological Sciences, DePaul University, Chicago, IL, USA
    Jalene M. LaMontagne

    Department of Wildland Resources, Utah State University Ecology Center, Logan, UT, USA
    James A. Lutz

    Department of Biology, University of New Mexico, Albuquerque, NM, USA
    Diana Macias

    Pacific Forestry Centre, Victoria, BC, Canada
    Eliot J. B. McIntire

    Université du Québec en Abitibi-Témiscamingue, Rouyn-Noranda, Quebec, Canada
    Yassine Messaoud

    Department of Biology, Colby College, Waterville, ME, USA
    Christopher M. Moore

    Department of Biology, Washington University in St. Louis, St. Louis, MO, USA
    Jonathan A. Myers

    University of New Mexico, Albuquerque, NM, USA
    Orrin B. Myers

    Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, Konstanz, Germany
    Chase Nunez

    Valles Caldera National Preserve, National Park Service, Jemez Springs, NM, USA
    Robert Parmenter

    Fort Collins Science Center, Fort Collins, CO, USA
    Sam Pearse

    Department of Natural Sciences, Mars Hill University, Mars Hill, NC, USA
    Scott Pearson

    Department of Forest and Rangeland Stewardship, Colorado State University, Fort Collins, CO, USA
    Miranda D. Redmond & Andreas P. Wion

    Ecology and Evolutionary Biology, University of Toronto, Toronto, ON, Canada
    Amanda M. Schwantes

    Department of Biology, Wilkes University, Wilkes-Barre, PA, USA
    Michael A. Steele

    Geography Department and Russian and East European Institute, Bloomington, IN, USA
    Roman Zlotin More

  • in

    Accepting the loss of habitat specialists in a changing world

    1.
    Stuart-Smith, R. D., Mellin, C., Bates, A. E. & Edgar, G. J. Nat. Ecol. Evol. https://doi.org/10.1038/s41559-020-01342-7 (2020).
    Article  Google Scholar 
    2.
    Wilson, S. K. et al. J. Anim. Ecol. 77, 220–228 (2008).
    Article  Google Scholar 

    3.
    Dornelas, M. et al. Science 344, 296–299 (2014).
    CAS  Article  Google Scholar 

    4.
    Sommer, B., Harrison, P. L., Beger, M. & Pandolfi, J. M. Ecology 95, 1000–1009 (2014).
    Article  Google Scholar 

    5.
    Feary, D. A. et al. Fish Fish. 15, 593–615 (2013).
    Article  Google Scholar 

    6.
    Brandl, S. J. et al. Science 364, 1189–1192 (2019).
    CAS  Article  Google Scholar 

    7.
    Hughes, T. P. et al. Nature 546, 82–90 (2017).
    CAS  Article  Google Scholar 

    8.
    Beyer, H. et al. Conserv. Lett. 11, e12587 (2018).
    Article  Google Scholar 

    9.
    Bottrill, M. C. et al. Trends Ecol. Evol. 24, 183–184 (2009).
    Article  Google Scholar 

    10.
    Wernberg, T. et al. Nat. Clim. Change 3, 78–82 (2013).
    Article  Google Scholar  More

  • in

    Habitat loss and range shifts contribute to ecological generalization among reef fishes

    1.
    McKinney, M. L. & Lockwood, J. L. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends Ecol. Evol. 14, 450–453 (1999).
    CAS  PubMed  Article  PubMed Central  Google Scholar 
    2.
    Magurran, A. E., Dornelas, M., Moyes, F., Gotelli, N. J. & McGill, B. Rapid biotic homogenization of marine fish assemblages. Nat. Commun. 6, 8405 (2015).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    3.
    Devictor, V. et al. Functional biotic homogenization of bird communities in disturbed landscapes. Glob. Ecol. Biogeogr. 17, 252–261 (2008).
    Article  Google Scholar 

    4.
    Devictor, V., Julliard, R. & Jiguet, F. Distribution of specialist and generalist species along spatial gradients of habitat disturbance and fragmentation. Oikos 117, 507–514 (2008).
    Article  Google Scholar 

    5.
    Richardson, L. E., Graham, N. A. J., Pratchett, M. S., Eurich, J. G. & Hoey, A. S. Mass coral bleaching causes biotic homogenization of reef fish assemblages. Glob. Change Biol. 24, 3117–3129 (2018).
    Article  Google Scholar 

    6.
    Wilson, S. K. et al. Habitat utilization by coral reef fish: implications for specialists vs. generalists in a changing environment. J. Anim. Ecol. 77, 220–228 (2008).
    Article  Google Scholar 

    7.
    Munday, P. L. Habitat loss, resource specialization, and extinction on coral reefs. Glob. Change Biol. 10, 1642–1647 (2004).
    Article  Google Scholar 

    8.
    Jones, G. P., McCormick, M. I., Srinivasan, M. & Eagle, J. V. Coral decline threatens fish biodiversity in marine reserves. Proc. Natl Acad. Sci. USA 101, 8251–8253 (2004).
    CAS  PubMed  Article  Google Scholar 

    9.
    Paddack, M. J. et al. Recent region-wide declines in Caribbean reef fish abundance. Curr. Biol. 19, 590–595 (2009).
    CAS  PubMed  Article  Google Scholar 

    10.
    Hughes, T. P. et al. Spatial and temporal patterns of mass bleaching of corals in the Anthropocene. Science 359, 80–83 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    11.
    Hughes, T. P. et al. Coral reefs in the Anthropocene. Nature 546, 82–90 (2017).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    12.
    Cheal, A. J., MacNeil, M. A., Emslie, M. J. & Sweatman, H. The threat to coral reefs from more intense cyclones under climate change. Glob. Change Biol. 23, 1511–1524 (2017).
    Article  Google Scholar 

    13.
    Oliver, E. C. J. et al. Longer and more frequent marine heatwaves over the past century. Nat. Commun. 9, 1324 (2018).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    14.
    Ling, S. D., Johnson, C. R., Frusher, S. D. & Ridgway, K. R. Overfishing reduces resilience of kelp beds to climate-driven catastrophic phase shift. Proc. Natl Acad. Sci. USA 106, 22341–22345 (2009).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    15.
    Sunday, J. M. et al. Species traits and climate velocity explain geographic range shifts in an ocean-warming hotspot. Ecol. Lett. 18, 944–953 (2015).
    PubMed  Article  Google Scholar 

    16.
    Mair, L. et al. Abundance changes and habitat availability drive species’ responses to climate change. Nat. Clim. Change 4, 127–131 (2014).
    Article  Google Scholar 

    17.
    Monaco, C. J. et al. Dietary generalism accelerates arrival and persistence of coral-reef fishes in their novel ranges under climate change. Glob. Change Biol. 26, 5564–5573 (2020).
    Article  Google Scholar 

    18.
    Kleypas, J. A., McManus, J. W. & Menez, L. A. B. Environmental limits to coral reef development: where do we draw the line? Am. Zool. 39, 146–159 (2015).
    Article  Google Scholar 

    19.
    Munday, P. L., Jones, G. P., Pratchett, M. S. & Williams, A. J. Climate change and the future for coral reef fishes. Fish Fish. 9, 261–285 (2008).
    Article  Google Scholar 

    20.
    Edgar, G. J. & Stuart-Smith, R. D. Systematic global assessment of reef fish communities by the Reef Life Survey program. Sci. Data 1, 140007 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    21.
    Pratchett, M. S. et al. in Oceanography and Marine Biology: Annual Review Vol. 46 (eds Gibson, R. N. et al.) 251–296 (Taylor and Francis, 2008).

    22.
    Stuart-Smith, R. D., Brown, C. J., Ceccarelli, D. M. & Edgar, G. J. Ecosystem restructuring along the Great Barrier Reef following mass coral bleaching. Nature 560, 92–96 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    23.
    Feary, D. A. The influence of resource specialization on the response of reef fish to coral disturbance. Mar. Biol. 153, 153–161 (2007).
    Article  Google Scholar 

    24.
    Mellin, C., Bradshaw, C., Fordham, D. & Caley, M. Strong but opposing β-diversity–stability relationships in coral reef fish communities. Proc. R. Soc. B 281, 20131993 (2014).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    25.
    Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353, 169–172 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    26.
    Stuart-Smith, R. D., Edgar, G. J. & Bates, A. E. Thermal limits to the geographic distributions of shallow-water marine species. Nat. Ecol. Evol. 1, 1846–1852 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    27.
    Stuart-Smith, R. D., Edgar, G. J., Barrett, N. S., Kininmonth, S. J. & Bates, A. E. Thermal biases and vulnerability to warming in the world’s marine fauna. Nature 528, 88–92 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    28.
    Vergés, A. et al. Long-term empirical evidence of ocean warming leading to tropicalization of fish communities, increased herbivory, and loss of kelp. Proc. Natl Acad. Sci. USA 113, 13791–13796 (2016).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    29.
    Booth, D. J., Figueira, W. F., Gregson, M. A., Brown, L. & Beretta, G. Occurrence of tropical fishes in temperate southeastern Australia: role of the East Australian Current. Estuar. Coast. Shelf Sci. 72, 102–114 (2007).
    Article  Google Scholar 

    30.
    Feary, D. A. et al. Latitudinal shifts in coral reef fishes: why some species do and others do not shift. Fish Fish. 15, 593–615 (2014).
    Article  Google Scholar 

    31.
    Guisan, A. et al. Scaling the linkage between environmental niches and functional traits for improved spatial predictions of biological communities. Glob. Ecol. Biogeogr. 28, 1384–1392 (2019).
    Article  Google Scholar 

    32.
    Pratchett, M. S., Hoey, A. S., Wilson, S. K., Messmer, V. & Graham, N. A. J. Changes in biodiversity and functioning of reef fish assemblages following coral bleaching and coral loss. Diversity 3, 424–452 (2011).
    Article  Google Scholar 

    33.
    Johnson, C. R. et al. Climate change cascades: shifts in oceanography, species’ ranges and subtidal marine community dynamics in eastern Tasmania. J. Exp. Mar. Biol. Ecol. 400, 17–32 (2011).
    Article  Google Scholar 

    34.
    Dornelas, M. et al. Assemblage time series reveal biodiversity change but not systematic loss. Science 344, 296–299 (2014).
    CAS  Article  Google Scholar 

    35.
    Blowes, S. A. et al. The geography of biodiversity change in marine and terrestrial assemblages. Science 366, 339–345 (2019).
    CAS  PubMed  Article  Google Scholar 

    36.
    Gilchrist, G. W. Specialists and generalists in changing environments. I. Fitness landscapes of thermal sensitivity. Am. Nat. 146, 252–270 (1995).
    Article  Google Scholar 

    37.
    Pellissier, L. et al. Quaternary coral reef refugia preserved fish diversity. Science 344, 1016–1019 (2014).
    CAS  PubMed  Article  Google Scholar 

    38.
    Graham, M. H., Kinlan, B. P. & Grosberg, R. K. Post-glacial redistribution and shifts in productivity of giant kelp forests. Proc. R. Soc. B 277, 399–406 (2010).
    PubMed  Article  PubMed Central  Google Scholar 

    39.
    Hughes, T. P. et al. Global warming and recurrent mass bleaching of corals. Nature 543, 373–377 (2017).
    CAS  Article  Google Scholar 

    40.
    Wismer, S., Tebbett, S. B., Streit, R. P. & Bellwood, D. R. Spatial mismatch in fish and coral loss following 2016 mass coral bleaching. Sci. Total Environ. 650, 1487–1498 (2019).
    CAS  PubMed  Article  Google Scholar 

    41.
    Waldock, C., Stuart-Smith, R. D., Edgar, G. J., Bird, T. J. & Bates, A. E. The shape of abundance distributions across temperature gradients in reef fishes. Ecol. Lett. 22, 685–696 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    42.
    Mouillot, D. et al. Rare species support vulnerable functions in high-diversity ecosystems. PLoS Biol. 11, e1001569 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    43.
    Robinson, J. P. W. et al. Productive instability of coral reef fisheries after climate-driven regime shifts. Nat. Ecol. Evol. 3, 183–190 (2019).
    PubMed  Article  Google Scholar 

    44.
    Cresswell, A. K. et al. Translating local benthic community structure to national biogenic reef habitat types. Glob. Ecol. Biogeogr. 26, 1112–1125 (2017).
    Article  Google Scholar 

    45.
    Edgar, G. J., Barrett, N. S. & Stuart-Smith, R. D. Exploited reefs protected from fishing transform over decades into conservation features otherwise absent from seascapes. Ecol. Appl. 19, 1967–1974 (2009).
    PubMed  Article  Google Scholar 

    46.
    Althaus, F. et al. A standardised vocabulary for identifying benthic biota and substrata from underwater imagery: the CATAMI classification scheme. PLoS ONE 10, e0141039 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    47.
    Carmona, C. P., de Bello, F., Mason, N. W. H. & Lepš, J. Traits without borders: integrating functional diversity across scales. Trends Ecol. Evol. 31, 382–394 (2016).
    PubMed  Article  Google Scholar 

    48.
    Stuart-Smith, R. D. et al. Integrating abundance and functional traits reveals new global hotspots of fish diversity. Nature 501, 539–542 (2013).
    CAS  PubMed  Article  Google Scholar 

    49.
    Spalding, M. D. et al. Marine ecoregions of the world: a bioregionalization of coastal and shelf areas. BioScience 57, 573–583 (2007).
    Article  Google Scholar 

    50.
    Becker, R. A., Wilks, A. R (original S code) & Brownrigg, R. (R version). mapdata: Extra map databases. R package version 2.3.0 (2018).

    51.
    Matis, P. A., Donelson, J. M., Bush, S., Fox, R. J. & Booth, D. J. Temperature influences habitat preference of coral reef fishes: will generalists become more specialised in a warming ocean? Glob. Change Biol. 24, 3158–3169 (2018).
    Article  Google Scholar  More

  • in

    Seventeen ‘extinct’ plant species back to conservation attention in Europe

    1.
    Guidelines for Using the IUCN Red List Categories and Criteria Version 14 (IUCN Standards and Petitions Committee, 2019); http://www.iucnredlist.org/documents/RedListGuidelines.pdf
    2.
    Dalrymple, S. E., Godefroid, S., Orsenigo, S. & Abeli, T. Frankenstein’s work or everyday conservation? How reintroductions are informing the de-extinction debate. J. Nat. Conserv. 56, 125870 (2020).
    Article  Google Scholar 

    3.
    IUCN SSC. Guiding Principles on Creating Proxies of Extinct Species for Conservation Benefit Version 1.0 (IUCN, 2016).

    4.
    Dalrymple, S. E. & Abeli, T. Ex situ seed banks and the IUCN Red List. Nat. Plants 5, 122–123 (2019).
    Article  Google Scholar 

    5.
    Humphreys, A. M., Govaerts, R., Ficinski, S. Z., Lughadha, E. N. & Vorontsova, M. S. Global dataset shows geography and life form predict modern plant extinction and rediscovery. Nat. Ecol. Evol. 3, 1043–1047 (2019).
    Article  Google Scholar 

    6.
    Knapp, W. M. et al. Regional records improve data quality in determining plant extinction rates. Nat. Ecol. Evol. 4, 512–514 (2020).
    Article  Google Scholar 

    7.
    Ladle, R. J., Jepson, P., Malhado, A. C. M., Jennings, S. & Barua, M. The causes and biogeographical significance of species’ rediscovery. Front. Biogeogr. 3, 111–118 (2011).
    Google Scholar 

    8.
    Scheffers, B. R., Yong, D. L., Harris, J. B. C., Giam, X. & Sodhi, N. S. The world’s rediscovered species: back from the brink? PLoS ONE 6, e22531 (2011).
    CAS  Article  Google Scholar 

    9.
    Aedo, C., Medina, L., Barberá, P. & Fernández-Albert, M. Extinctions of vascular plants in Spain. Nord. J. Bot. 33, 83–100 (2015).
    Article  Google Scholar 

    10.
    Bawri, A., Gajurel, P. R. & Khan, M. L. Rediscovery of Primula polonensis. Kew Bull. 70, 56–60 (2015).
    Article  Google Scholar 

    11.
    Bonini, F., Lastrucci, L. & Gigante, D. Juncus atratus Krock. (Juncaceae) rediscovered in Italy: a species deserving urgent conservation actions. Biologia 75, 1519–1527 (2020).
    Article  Google Scholar 

    12.
    Abeli, T. et al. Ex situ collections and their potential for the restoration of extinct plants. Conserv. Biol. 34, 303–313 (2020).
    Article  Google Scholar 

    13.
    Liu, U., Breman, E., Cossu, T. A. & Kenney, S. The conservation value of germplasm stored at the Millennium Seed Bank, Royal Botanic Gardens, Kew, UK. Biodivers. Conserv. 27, 1347–1386 (2018).
    Article  Google Scholar 

    14.
    Minteer, B. A., Collins, J. P., Love, K. E. & Puschendorf, R. Avoiding (re)extinction. Science 344, 260–261 (2014).
    CAS  Article  Google Scholar 

    15.
    Rossi, G. et al. Is legal protection sufficient to ensure plant conservation? The Italian Red List of policy species as a case study. Oryx 50, 431–436 (2016).
    Article  Google Scholar 

    16.
    Fos, S., Laguna, E., Jiménez, J. & Gómez-Serrano, M. Á. Plant micro-reserves in Valencia (E. Spain): a model to preserve threatened flora in China? Plant Divers. 39, 383–389 (2017).
    Article  Google Scholar 

    17.
    Keith, D. A. & Burgman, M. A. The Lazarus effect: can the dynamics of extinct species lists tell us anything about the status of biodiversity? Biol. Conserv. 117, 41–48 (2004).
    Article  Google Scholar 

    18.
    Dunkel, F. G. The Ranunculus auricomus L. complex (Ranunculaceae) in northern Italy. Webbia 65, 179–227 (2010).
    Article  Google Scholar 

    19.
    Bartolucci, F. et al. An updated checklist of the vascular flora native to Italy. Plant Biosyst. 152, 179–303 (2018).
    Article  Google Scholar 

    20.
    Lista Vermelha da Flora Vascular de Portugal Continental (Sociedade Portuguesa de Botânica e Associação Portuguesa de Ciência da Vegetação – PHYTOS, em parceria com o Instituto da Conservação da Natureza e das Florestas, 2020); https://listavermelha-flora.pt/

    21.
    Euro+Med PlantBase—the Information Resource for Euro-Mediterranean Plant Diversity (Euro+Med, 2020); http://ww2.bgbm.org/EuroPlusMed/

    22.
    Perehrym, M. M. in Vascular Plants of the Emerald Network of Ukraine Under Protection of the Bern Convention (ed. Solomakha, V. A.) (Ministry of Ecology and Natural Resources of Ukraine, 2016).

    23.
    Andrés-Sánchez, S., Galbany-Casals, M., Rico, E. & Martínez-Ortega, M. M. A nomenclatural treatment for Logfia Cass. and Filago L. (Asteraceae) as newly circumscribed: typification of several names. Taxon 60, 572–576 (2011).

    24.
    Vladimirov, V., Aybeke, A., Matevski, V. & Tan, K. New floristic records in the Balkans: 33*. Phytol. Balc. 23, 281–329 (2017).
    Google Scholar 

    25.
    Orsenigo, S. et al. Red list of threatened vascular plants in Italy. Plant Biosyst. 152, 310–335 (2021).
    Article  Google Scholar 

    26.
    Barina, Z. (ed.) Distribution Atlas of Vascular Plants in Albania (Hungarian Natural History Museum, 2017).

    27.
    La Liste Rouge des Espèces Menacées en France—Chapitre Flore Vasculaire de France Métropolitaine (UICN France, FCBN, AFB, MNHN, 2018).

    28.
    Blanca, G., Gavira, O. & Suárez-Santiago, V. N. Galatella malacitana (Asteraceae): a new species from the peridotitic mountains of southern Spain. Phytotaxa 205, 239–248 (2015).
    Article  Google Scholar 

    29.
    Bogdanović, S., Brullo, S., Ljubičić, I., Rat, M. & Salmeri, C. Cytotaxonomical remarks on Loncomelos visianicum (Hyacinthaceae), a poorly known species endemic to Croatia. Phytotaxa 430, 95–108 (2020).
    Article  Google Scholar 

    30.
    Banfi, E. in Flora d’Italia 2nd edn, Vol. 1 (eds Pignatti, S. et al.) (Edagricole, 2017). More

  • in

    Emerging strategies for precision microbiome management in diverse agroecosystems

    1.
    Leach, J. E., Triplett, L. R., Argueso, C. T. & Trivedi, P. Communication in the phytobiome. Cell 169, 587–596 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 
    2.
    Bahram, M. et al. Structure and function of the global topsoil microbiome. Nature 560, 233–237 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    3.
    Liu, H., Macdonald, C. A., Cook, J., Anderson, I. C. & Singh, B. K. An ecological loop: host microbiomes across multitrophic interactions. Trends Ecol. Evol. 34, 1118–1130 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    4.
    Banerjee, S., Schlaeppi, K. & van der Heijden, M. G. A. Keystone taxa as drivers of microbiome structure and functioning. Nat. Rev. Microbiol. 16, 567–576 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    5.
    Hoeksema, J. D. et al. Evolutionary history of plant hosts and fungal symbionts predicts the strength of mycorrhizal mutualism. Commun. Biol. 1, 116 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    6.
    Fisher, R. M., Henry, L. M., Cornwallis, C. K., Kiers, E. T. & West, S. A. The evolution of host–symbiont dependence. Nat. Commun. 8, 1–8 (2017).
    CAS  Article  Google Scholar 

    7.
    Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Natl Acad. Sci. USA 115, 6506–6511 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    8.
    Fierer, N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 15, 579–590 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    9.
    Van Der Heijden, M. G. A., Bardgett, R. D. & Van Straalen, N. M. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol. Lett. 11, 296–310 (2008).
    PubMed  Article  PubMed Central  Google Scholar 

    10.
    Dubey, A. et al. Soil microbiome: a key player for conservation of soil health under changing climate. Biodivers. Conserv. 28, 2405–2429 (2019).
    Article  Google Scholar 

    11.
    Berendsen, R. L., Pieterse, C. M. J. & Bakker, P. A. H. M. The rhizosphere microbiome and plant health. Trends Plant Sci. 17, 478–486 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    12.
    Hartmann, A. et al. Assessment of the structural and functional diversities of plant microbiota: achievements and challenges—a review. J. Adv. Res. 19, 3–13 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    13.
    Gurung, K., Wertheim, B. & Falcao Salles, J. The microbiome of pest insects: it is not just bacteria. Entomol. Exp. Appl. 167, 156–170 (2019).
    Article  Google Scholar 

    14.
    Finkel, O. M., Castrillo, G., Herrera Paredes, S., Salas González, I. & Dangl, J. L. Understanding and exploiting plant beneficial microbes. Curr. Opin. Plant Biol. 38, 155–163 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    15.
    Toju, H. et al. Core microbiomes for sustainable agroecosystems. Nat. Plants 4, 247–257 (2018).
    PubMed  Article  PubMed Central  Google Scholar 

    16.
    Sergaki, C., Lagunas, B., Lidbury, I., Gifford, M. L. & Schäfer, P. Challenges and approaches in microbiome research: from fundamental to applied. Front. Plant Sci. 9, 1205 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    17.
    Mariotte, P. et al. Plant–soil feedback: bridging natural and agricultural sciences. Trends Ecol. Evol. 33, 129–142 (2018).
    PubMed  Article  PubMed Central  Google Scholar 

    18.
    Porter, S. S. & Sachs, J. L. Agriculture and the disruption of plant–microbial symbiosis. Trends Ecol. Evol. 35, 426–439 (2020).
    PubMed  Article  PubMed Central  Google Scholar 

    19.
    Humphrey, P. T. & Whiteman, N. K. Insect herbivory reshapes a native leaf microbiome. Nat. Ecol. Evol. 4, 221–229 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    20.
    Lòpez-Fernàndez, S., Mazzoni, V., Pedrazzoli, F., Pertot, I. & Campisano, A. A phloem-feeding insect transfers bacterial endophytic communities between grapevine plants. Front. Microbiol. 8, 834 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    21.
    Kim, D. R. et al. A mutualistic interaction between Streptomyces bacteria, strawberry plants and pollinating bees. Nat. Commun. 10, 4802 (2019).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    22.
    Adeleke, R. A., Raimi, A. R., Roopnarain, A. & Mokubedi, S. M. in Biofertilizers for Sustainable Agriculture and Environment Vol 55 (eds Bhoopander, G. et al.) 137–172 (Springer, 2019).

    23.
    Besset-Manzoni, Y., Rieusset, L., Joly, P., Comte, G. & Prigent-Combaret, C. Exploiting rhizosphere microbial cooperation for developing sustainable agriculture strategies. Environ. Sci. Pollut. Res. 25, 29953–29970 (2018).
    Article  Google Scholar 

    24.
    Hussain, S., Siddique, T., Saleem, M., Arshad, M. & Khalid, A. Impact of pesticides on soil microbial diversity, enzymes, and biochemical reactions. Adv. Agron. 102, 159–200 (2009).
    CAS  Article  Google Scholar 

    25.
    Wolmarans, K. & Swart, W. J. Influence of glyphosate, other herbicides and genetically modified herbicide-resistant crops on soil microbiota: a review. South Afr. J. Plant Soil 31, 177–186 (2014).
    Article  Google Scholar 

    26.
    Kim, N., Zabaloy, M. C., Guan, K. & Villamil, M. B. Do cover crops benefit soil microbiome? A meta-analysis of current research. Soil Biol. Biochem. 142, 107701 (2020).
    CAS  Article  Google Scholar 

    27.
    Venter, Z. S., Jacobs, K. & Hawkins, H. J. The impact of crop rotation on soil microbial diversity: a meta-analysis. Pedobiologia 59, 215–223 (2016).
    Article  Google Scholar 

    28.
    Imfeld, G. & Vuilleumier, S. Measuring the effects of pesticides on bacterial communities in soil: a critical review. Eur. J. Soil Biol. 49, 22–30 (2012).
    CAS  Article  Google Scholar 

    29.
    Bünemann, E. K., Schwenke, G. D. & Van Zwieten, L. Impact of agricultural inputs on soil organisms—a review. Aust. J. Soil Res. 44, 379–406 (2006).
    Article  Google Scholar 

    30.
    Tsiafouli, M. A. et al. Intensive agriculture reduces soil biodiversity across Europe. Glob. Chang. Biol. 21, 973–985 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    31.
    Chen, H. et al. Global meta-analyses show that conservation tillage practices promote soil fungal and bacterial biomass. Agric. Ecosyst. Environ. 293, 106841 (2020).
    CAS  Article  Google Scholar 

    32.
    Pérez-Jaramillo, J. E., Carrión, V. J., de Hollander, M. & Raaijmakers, J. M. The wild side of plant microbiomes. Microbiome 6, 143 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    33.
    Ullah, M. & Dijkstra, F. Fungicide and bactericide effects on carbon and nitrogen cycling in soils: a meta-analysis. Soil Syst. 3, 23 (2019).
    CAS  Article  Google Scholar 

    34.
    Wang, Z., Li, Y., Li, T., Zhao, D. & Liao, Y. Conservation tillage decreases selection pressure on community assembly in the rhizosphere of arbuscular mycorrhizal fungi. Sci. Total Environ. 710, 136326 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    35.
    Gómez-Gallego, C. et al. Glyphosate-based herbicide affects the composition of microbes associated with Colorado potato beetle (Leptinotarsa decemlineata). FEMS Microbiol. Lett. 367, fnaa050 (2019).
    Article  CAS  Google Scholar 

    36.
    Jenkins, M., Locke, M., Reddy, K., McChesney, D. S. & Steinriede, R. Glyphosate applications, glyphosate resistant corn, and tillage on nitrification rates and distribution of nitrifying microbial communities. Soil Sci. Soc. Am. J. 81, 1371–1380 (2017).
    CAS  Article  Google Scholar 

    37.
    Ramakrishnan, B., Venkateswarlu, K., Sethunathan, N. & Megharaj, M. Local applications but global implications: can pesticides drive microorganisms to develop antimicrobial resistance? Sci. Total Environ. 654, 177–189 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    38.
    Felsot, A. S. Enhanced biodegradation of insecticides in soil: implications for agroecosystems. Annu. Rev. Entomol. 34, 453–476 (1989).
    CAS  Article  Google Scholar 

    39.
    Kikuchi, Y. et al. Symbiont-mediated insecticide resistance. Proc. Natl Acad. Sci. USA 109, 8618–8622 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    40.
    Tago, K., Kikuchi, Y., Nakaoka, S., Katsuyama, C. & Hayatsu, M. Insecticide applications to soil contribute to the development of Burkholderia mediating insecticide resistance in stinkbugs. Mol. Ecol. 24, 3766–3778 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    41.
    Zhang, J. et al. Rapid evolution of symbiotic bacteria populations in spirotetramat-resistant Aphis gossypii glover revealed by pyrosequencing. Comp. Biochem. Physiol. D 20, 151–158 (2016).
    Google Scholar 

    42.
    Xia, X. et al. Gut microbiota mediate insecticide resistance in the diamondback moth, Plutella xylostella (L.). Front. Microbiol. 9, 25 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    43.
    Almeida, L. G., de, Moraes, L. A. B., de, Trigo, J. R., Omoto, C. & Cônsoli, F. L. The gut microbiota of insecticide-resistant insects houses insecticide-degrading bacteria: a potential source for biotechnological exploitation. PLoS ONE 12, e0174754 (2017).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    44.
    Bowles, T. M., Jackson, L. E., Loeher, M. & Cavagnaro, T. R. Ecological intensification and arbuscular mycorrhizas: a meta-analysis of tillage and cover crop effects. J. Appl. Ecol. 54, 1785–1793 (2017).
    Article  Google Scholar 

    45.
    Valente, J., Gerin, F., Le Gouis, J., Moënne-Loccoz, Y. & Prigent-Combaret, C. Ancient wheat varieties have a higher ability to interact with plant growth-promoting rhizobacteria. Plant. Cell Environ. 43, 246–260 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    46.
    Newton, A. C., Gravouil, C. & Fountaine, J. M. Managing the ecology of foliar pathogens: ecological tolerance in crops. Ann. Appl. Biol. 157, 343–359 (2010).
    Article  Google Scholar 

    47.
    Huang, X., Zhao, J., Zhou, X., Zhang, J. & Cai, Z. Differential responses of soil bacterial community and functional diversity to reductive soil disinfestation and chemical soil disinfestation. Geoderma 348, 124–134 (2019).
    CAS  Article  Google Scholar 

    48.
    Karlsson, I., Friberg, H., Steinberg, C. & Persson, P. Fungicide effects on fungal community composition in the wheat phyllosphere. PLoS ONE 9, e111786 (2014).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    49.
    Schaeffer, R. N., Vannette, R. L., Brittain, C., Williams, N. M. & Fukami, T. Non-target effects of fungicides on nectar-inhabiting fungi of almond flowers. Environ. Microbiol. Rep. 9, 79–84 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    50.
    Lagnaoui, A. & Radcliffe, E. B. Potato fungicides interfere with entomopathogenic fungi impacting population dynamics of green peach aphid. Am. J. Potato Res. 75, 19–25 (1998).
    CAS  Article  Google Scholar 

    51.
    Sarkar, S., Narayanan, P., Divakaran, A., Balamurugan, A. & Premkumar, R. The in vitro effect of certain fungicides, insecticides, and biopesticides on mycelial growth in the biocontrol fungus Trichoderma harzianum. Turkish J. Biol. 34, 399–403 (2010).
    CAS  Google Scholar 

    52.
    Duke, S. O. Interaction of chemical pesticides and their formulation ingredients with microbes associated with plants and plant pests. J. Agric. Food Chem. 66, 7553–7561 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    53.
    Kakumanu, M. L., Reeves, A. M., Anderson, T. D., Rodrigues, R. R. & Williams, M. A. Honey bee gut microbiome is altered by in-hive pesticide exposures. Front. Microbiol. 7, 1255 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    54.
    del Mar Fernández, M. et al. Influence of microbiota in the susceptibility of parasitic wasps to abamectin insecticide: deep sequencing, esterase and toxicity tests. Pest Manag. Sci. 75, 79–86 (2019).
    Article  CAS  Google Scholar 

    55.
    Motta, E. V. S. & Moran, N. A. Impact of glyphosate on the honey bee gut microbiota: effects of intensity, duration, and timing of exposure. mSystems 5, e00268-20 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    56.
    Steffan, S. A. et al. Omnivory in bees: elevated trophic positions among all major bee families. Am. Nat. 194, 414–421 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    57.
    Bernauer, O. M., Gaines-Day, H. R. & Steffan, S. A. Colonies of bumble bees (Bombus impatiens) produce fewer workers, less bee biomass, and have smaller mother queens following fungicide exposure. Insects 6, 478–488 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    58.
    Yoder, J. A., Nelson, B. W., Jajack, A. J. & Sammataro, D. in Beekeeping – From Science to Practice (eds Vreeland, R. H. & Sammatoro, D.) 73–90 (Springer, 2017).

    59.
    Vida, C., Vicente, A. & Cazorla, F. M. The role of organic amendments to soil for crop protection: induction of suppression of soilborne pathogens. Ann. Appl. Biol. 176, 1–15 (2020).
    Article  Google Scholar 

    60.
    Hartman, K. et al. Cropping practices manipulate abundance patterns of root and soil microbiome members paving the way to smart farming. Microbiome 6, 14 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    61.
    Ling, N. et al. Insight into how organic amendments can shape the soil microbiome in long-term field experiments as revealed by network analysis. Soil Biol. Biochem. 99, 137–149 (2016).
    CAS  Article  Google Scholar 

    62.
    Li, X. et al. Legacy of land use history determines reprogramming of plant physiology by soil microbiome. ISME J. 13, 738–751 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    63.
    Vukicevich, E., Lowery, T., Bowen, P., Úrbez-Torres, J. R. & Hart, M. Cover crops to increase soil microbial diversity and mitigate decline in perennial agriculture. A review. Agron. Sustain. Dev. 36, 48 (2016).
    Article  CAS  Google Scholar 

    64.
    Osipitan, O. A., Dille, J. A., Assefa, Y. & Knezevic, S. Z. Cover crop for early season weed suppression in crops: systematic review and meta-analysis. Agron. J. 110, 2211–2221 (2018).
    Article  Google Scholar 

    65.
    Hokkanen, H. M. T. & Menzler-Hokkanen, I. Insect pest suppressive soils: buffering pulse cropping systems against outbreaks of Sitona weevils. Ann. Entomol. Soc. Am. 111, 139–143 (2018).
    Article  Google Scholar 

    66.
    Esmaeili Taheri, A., Hamel, C. & Gan, Y. Cropping practices impact fungal endophytes and pathogens in durum wheat roots. Appl. Soil Ecol. 100, 104–111 (2016).
    Article  Google Scholar 

    67.
    Lucas, S. T., D’Angelo, E. M. & Williams, M. A. Improving soil structure by promoting fungal abundance with organic soil amendments. Appl. Soil Ecol. 75, 13–23 (2014).
    Article  Google Scholar 

    68.
    Misra, P. et al. Vulnerability of soil microbiome to monocropping of medicinal and aromatic plants and its restoration through intercropping and organic amendments. Front. Microbiol. 10, 2604 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    69.
    Nicola, L. et al. Fumigation with dazomet modifies soil microbiota in apple orchards affected by replant disease. Appl. Soil Ecol. 113, 71–79 (2017).
    Article  Google Scholar 

    70.
    Nobbe, F. & Hiltner, L. Inoculation of the soil for cultivating leguminous plants. US Patent 570 (1896).

    71.
    Thilakarathna, M. S. & Raizada, M. N. A meta-analysis of the effectiveness of diverse rhizobia inoculants on soybean traits under field conditions. Soil Biol. Biochem. 105, 177–196 (2017).
    CAS  Article  Google Scholar 

    72.
    Zhang, S., Lehmann, A., Zheng, W., You, Z. & Rillig, M. C. Arbuscular mycorrhizal fungi increase grain yields: a meta-analysis. N. Phytol. 222, 543–555 (2019).
    CAS  Article  Google Scholar 

    73.
    Veresoglou, S. D. & Menexes, G. Impact of inoculation with Azospirillum spp. on growth properties and seed yield of wheat: a meta-analysis of studies in the ISI Web of Science from 1981 to 2008. Plant Soil 337, 469–480 (2010).
    CAS  Article  Google Scholar 

    74.
    Federici, B. A., Bonning, B. C. & St. Leger, R. J. in Patho-Biotechnology (eds Sleator, R. & Hill, C.) 15–40 (CRC Press, 2008).

    75.
    Johnson, L. J. et al. The exploitation of epichloae endophytes for agricultural benefit. Fungal Divers. 60, 171–188 (2013).
    Article  Google Scholar 

    76.
    Castillo Lopez, D., Zhu-Salzman, K., Ek-Ramos, M. J. & Sword, G. A. The entomopathogenic fungal endophytes Purpureocillium lilacinum (formerly Paecilomyces lilacinus) and Beauveria bassiana negatively affect cotton aphid reproduction under both greenhouse and field conditions. PLoS ONE 9, e103891 (2014).
    PubMed  PubMed Central  Article  Google Scholar 

    77.
    Sessitsch, A., Pfaffenbichler, N. & Mitter, B. Microbiome applications from lab to field: facing complexity. Trends Plant Sci. 24, 194–198 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    78.
    Stephan, J. G. et al. Honeybee-specific lactic acid bacterium supplements have no effect on American foulbrood-infected honeybee colonies. Appl. Environ. Microbiol. 85, e00606-19 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    79.
    Bacilio, M., Moreno, M., Lopez-Aguilar, D. R. & Bashan, Y. Scaling from the growth chamber to the greenhouse to the field: demonstration of diminishing effects of mitigation of salinity in peppers inoculated with plant growth-promoting bacterium and humic acids. Appl. Soil Ecol. 119, 327–338 (2017).
    Article  Google Scholar 

    80.
    Latz, M. A. C., Jensen, B., Collinge, D. B. & Lyngs Jørgensen, H. J. Identification of two endophytic fungi that control Septoria tritici blotch in the field, using a structured screening approach. Biol. Control 141, 104128 (2020).
    CAS  Article  Google Scholar 

    81.
    Haney, C. H., Samuel, B. S., Bush, J. & Ausubel, F. M. Associations with rhizosphere bacteria can confer an adaptive advantage to plants. Nat. Plants 1, 15051 (2015).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    82.
    Smith, K. P., Handelsman, J. & Goodman, R. M. Genetic basis in plants for interactions with disease-suppressive bacteria. Proc. Natl Acad. Sci. USA 96, 4786–4790 (1999).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    83.
    Shrestha, A. et al. Genetic differences in barley govern the responsiveness to N-acyl homoserine lactone. Phytobiomes J. 3, 191–202 (2019).
    Article  Google Scholar 

    84.
    Chowdhury, S. P. et al. Effects of Bacillus amyloliquefaciens FZB42 on lettuce growth and health under pathogen pressure and its impact on the rhizosphere bacterial community. PLoS ONE 8, e68818 (2013).
    PubMed  PubMed Central  Article  Google Scholar 

    85.
    Papavizas, G. C. Survival of Trichoderma harzianum in soil and in pea and bean rhizospheres. Phytopathology 72, 121 (1982).
    Article  Google Scholar 

    86.
    Hungria, M., Campo, R. J., Chueire, L. M. O., Grange, L. & Megías, M. Symbiotic effectiveness of fast-growing rhizobial strains isolated from soybean nodules in Brazil. Biol. Fertil. Soils 33, 387–394 (2001).
    CAS  Article  Google Scholar 

    87.
    Cassán, F. & Diaz-Zorita, M. Azospirillum sp. in current agriculture: from the laboratory to the field. Soil Biol. Biochem. 103, 117–130 (2016).
    Article  CAS  Google Scholar 

    88.
    Ojiambo, P. S., Battilani, P., Cary, J. W., Blum, B. H. & Carbone, I. Cultural and genetic approaches to manage aflatoxin contamination: recent insights provide opportunities for improved control. Phytopathology 108, 1024–1037 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    89.
    Karise, R. et al. Reliability of the entomovector technology using Prestop-Mix and Bombus terrestris L. as a fungal disease biocontrol method in open field. Sci. Rep. 6, 31650 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    90.
    Hawkes, C. V. & Connor, E. W. Translating phytobiomes from theory to practice: ecological and evolutionary considerations. Phytobiomes J. 1, 57–69 (2017).
    Article  Google Scholar 

    91.
    Mitter, B. et al. A new approach to modify plant microbiomes and traits by introducing beneficial bacteria at flowering into progeny seeds. Front. Microbiol. 8, 11 (2017).
    PubMed  PubMed Central  Google Scholar 

    92.
    Prado, A., Marolleau, B., Vaissière, B. E., Barret, M. & Torres-Cortes, G. Insect pollination: an ecological process involved in the assembly of the seed microbiota. Sci. Rep. 10, 3575 (2020).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    93.
    Bosworth, A. H. et al. Alfalfa yield response to inoculation with recombinant strains of Rhizobium meliloti with an extra copy of dctABD and/or modified nifA expression. Appl. Environ. Microbiol. 60, 3815–3832 (1994).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    94.
    Suárez, R. et al. Improvement of drought tolerance and grain yield in common bean by overexpressing trehalose-6-phosphate synthase in rhizobia. Mol. Plant Microbe Interact. 21, 958–966 (2008).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    95.
    Leonard, S. P. et al. Engineered symbionts activate honey bee immunity and limit pathogens. Science 367, 573–576 (2020).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    96.
    Sarma, B. K., Yadav, S. K., Singh, S. & Singh, H. B. Microbial consortium-mediated plant defense against phytopathogens: readdressing for enhancing efficacy. Soil Biol. Biochem. 87, 25–33 (2015).
    CAS  Article  Google Scholar 

    97.
    Becker, J., Eisenhauer, N., Scheu, S. & Jousset, A. Increasing antagonistic interactions cause bacterial communities to collapse at high diversity. Ecol. Lett. 15, 468–474 (2012).
    PubMed  Article  PubMed Central  Google Scholar 

    98.
    Hu, J. et al. Probiotic diversity enhances rhizosphere microbiome function and plant disease suppression. mBio 7, e01790-16 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    99.
    Nuzzo, A., Satpute, A., Albrecht, U. & Strauss, S. L. Impact of soil microbial amendments on tomato rhizosphere microbiome and plant growth in field soil. Microb. Ecol. 80, 398–409 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    100.
    Xu, X. M. & Jeger, M. J. Combined use of two biocontrol agents with different biocontrol mechanisms most likely results in less than expected efficacy in controlling foliar pathogens under fluctuating conditions: a modeling study. Phytopathology 103, 108–116 (2013).
    PubMed  Article  PubMed Central  Google Scholar 

    101.
    Guijarro, B. et al. Compatibility interactions between the biocontrol agent Penicillium frequentans Pf909 and other existing strategies to brown rot control. Biol. Control 129, 45–54 (2019).
    Article  Google Scholar 

    102.
    Rubin, R. L., van Groenigen, K. J. & Hungate, B. A. Plant growth promoting rhizobacteria are more effective under drought: a meta-analysis. Plant Soil 416, 309–323 (2017).
    CAS  Article  Google Scholar 

    103.
    Rho, H. et al. Do endophytes promote growth of host plants under stress? A meta-analysis on plant stress mitigation by endophytes. Microb. Ecol. 75, 407–418 (2018).
    PubMed  Article  PubMed Central  Google Scholar 

    104.
    Johnson, K. B., Temple, T. N., Elkins, R. B. & Smith, T. J. Strategy for non-antibiotic fire blight control in U.S.-grown organic pome fruit. Acta Hortic. 1056, 93–100 (2014).
    Article  Google Scholar 

    105.
    Temple, T. N., Thompson, E. C., Uppala, S. S., Granatstein, D. & Johnson, K. Floral colonization dynamics and specificity of Aureobasidium pullulans strains used to suppress fire blight of pome fruit. Plant Dis. 104, 121–128 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    106.
    Rotolo, C. et al. Use of biocontrol agents and botanicals in integrated management of Botrytis cinerea in table grape vineyards. Pest Manag. Sci. 74, 715–725 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    107.
    Abbey, J. A., Percival, D., Asiedu, S. K., Prithiviraj, B. & Schilder, A. Management of Botrytis blossom blight in wild blueberries by biological control agents under field conditions. Crop Prot. 131, 105078 (2020).
    CAS  Article  Google Scholar 

    108.
    Morel, M. A., Cagide, C., Minteguiaga, M. A., Dardanelli, M. S. & Castro-Sowinski, S. The pattern of secreted molecules during the co-inoculation of alfalfa plants with Sinorhizobium meliloti and Delftia sp. strain JD2: an interaction that improves plant yield. Mol. Plant Microbe Interact. 28, 134–142 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    109.
    Remans, R. et al. Effect of Rhizobium–Azospirillum coinoculation on nitrogen fixation and yield of two contrasting Phaseolus vulgaris L. genotypes cultivated across different environments in Cuba. Plant Soil 312, 25–37 (2008).
    CAS  Article  Google Scholar 

    110.
    Carrión, V. J. et al. Pathogen-induced activation of disease-suppressive functions in the endophytic root microbiome. Science 366, 606–612 (2019).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    111.
    Santhanam, R. et al. Native root-associated bacteria rescue a plant from a sudden-wilt disease that emerged during continuous cropping. Proc. Natl Acad. Sci. USA 112, E5013–E5020 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    112.
    Gould, A. L. et al. Microbiome interactions shape host fitness. Proc. Natl Acad. Sci. USA 115, E11951–E11960 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    113.
    Carlström, C. I. et al. Synthetic microbiota reveal priority effects and keystone strains in the Arabidopsis phyllosphere. Nat. Ecol. Evol. 3, 1445–1454 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    114.
    Niu, B., Paulson, J. N., Zheng, X. & Kolter, R. Simplified and representative bacterial community of maize roots. Proc. Natl Acad. Sci. USA 114, E2450–E2459 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    115.
    Sanchez-Gorostiaga, A., Bajić, D., Osborne, M. L., Poyatos, J. F. & Sanchez, A. High-order interactions distort the functional landscape of microbial consortia. PLoS Biol. 17, e3000550 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    116.
    Herrera Paredes, S. et al. Design of synthetic bacterial communities for predictable plant phenotypes. PLoS Biol. 16, e2003962 (2018).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    117.
    Kehe, J. et al. Massively parallel screening of synthetic microbial communities. Proc. Natl Acad. Sci. USA 116, 12804–12809 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    118.
    Pineda, A., Kaplan, I. & Bezemer, T. M. Steering soil microbiomes to suppress aboveground insect pests. Trends Plant Sci. 22, 770–778 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    119.
    Mueller, U. G. & Sachs, J. L. Engineering microbiomes to improve plant and animal health. Trends Microbiol. 23, 606–617 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    120.
    Swenson, W., Wilson, D. S. & Elias, R. Artificial ecosystem selection. Proc. Natl Acad. Sci. USA 97, 9110–9114 (2000).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    121.
    Jochum, M. D., McWilliams, K. L., Pierson, E. A. & Jo, Y. K. Host-mediated microbiome engineering (HMME) of drought tolerance in the wheat rhizosphere. PLoS ONE 14, e0225933 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    122.
    Panke-Buisse, K., Poole, A. C., Goodrich, J. K., Ley, R. E. & Kao-Kniffin, J. Selection on soil microbiomes reveals reproducible impacts on plant function. ISME J. 9, 980–989 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    123.
    Arora, J., Mars Brisbin, M. A. & Mikheyev, A. S. Effects of microbial evolution dominate those of experimental host-mediated indirect selection. PeerJ 8, e9350 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    124.
    Morella, N. M. et al. Successive passaging of a plant-associated microbiome reveals robust habitat and host genotype-dependent selection. Proc. Natl Acad. Sci. USA 117, 1148–1159 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    125.
    Mason, C. J. et al. Plant defenses interact with insect enteric bacteria by initiating a leaky gut syndrome. Proc. Natl Acad. Sci. USA 116, 15991–15996 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    126.
    Pérez-Jaramillo, J. E. et al. Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits. ISME J. 11, 2244–2257 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    127.
    Walters, W. A. et al. Large-scale replicated field study of maize rhizosphere identifies heritable microbes. Proc. Natl Acad. Sci. USA 115, 7368–7373 (2018).
    PubMed  Article  PubMed Central  Google Scholar 

    128.
    Wallace, J. G., Kremling, K. A., Kovar, L. L. & Buckler, E. S. Quantitative genetics of the maize leaf microbiome. Phytobiomes J. 2, 208–224 (2018).
    Article  Google Scholar 

    129.
    Huang, R. et al. Natural variation at OsCERK1 regulates arbuscular mycorrhizal symbiosis in rice. N. Phytol. 225, 1762–1776 (2020).
    CAS  Article  Google Scholar 

    130.
    Zhang, J. et al. NRT1.1B is associated with root microbiota composition and nitrogen use in field-grown rice. Nat. Biotechnol. 37, 676–684 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    131.
    French, E., Tran, T. & Iyer-Pascuzzi, A. Tomato genotype modulates selection and responses to root microbiota. Phytobiomes J. 4, 314–326.

    132.
    Wintermans, P. C. A., Bakker, P. A. H. M. & Pieterse, C. M. J. Natural genetic variation in Arabidopsis for responsiveness to plant growth-promoting rhizobacteria. Plant Mol. Biol. 90, 623–634 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    133.
    Pérez-Jaramillo, J. E., Mendes, R. & Raaijmakers, J. M. Impact of plant domestication on rhizosphere microbiome assembly and functions. Plant Mol. Biol. 90, 635–644 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    134.
    Hacquard, S., Spaepen, S., Garrido-Oter, R. & Schulze-Lefert, P. Interplay between innate immunity and the plant microbiota. Annu. Rev. Phytopathol. 55, 565–589 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    135.
    Mendes, L. W., Mendes, R., Raaijmakwers, J. M. & Tsai, S. M. Breeding for soil-borne pathogen resistance impacts active rhizosphere microbiome of common bean. ISME J. 12, 3038–3042 (2018).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    136.
    Koprivova, A. et al. Root-specific camalexin biosynthesis controls the plant growth-promoting effects of multiple bacterial strains. Proc. Natl Acad. Sci. USA 116, 15735–15744 (2019).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    137.
    Vílchez, J. I. et al. DNA demethylases are required for myo-inositol-mediated mutualism between plants and beneficial rhizobacteria. Nat. Plants 6, 983–995 (2020).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    138.
    Zhalnina, K. et al. Dynamic root exudate chemistry and microbial substrate preferences drive patterns in rhizosphere microbial community assembly. Nat. Microbiol. 3, 470–480 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    139.
    Esse, H. P., Reuber, T. L. & Does, D. Genetic modification to improve disease resistance in crops. N. Phytol. 225, 70–86 (2020).
    Article  Google Scholar 

    140.
    Ryu, M. et al. Control of nitrogen fixation in bacteria that associate with cereals. Nat. Microbiol. 5, 80–84 (2020).
    Article  CAS  Google Scholar 

    141.
    Murphy, K. A., Tabuloc, C. A., Cervantes, K. R. & Chiu, J. C. Ingestion of genetically modified yeast symbiont reduces fitness of an insect pest via RNA interference. Sci. Rep. 6, 22587 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    142.
    Whitten, M. M. A. et al. Symbiont-mediated RNA interference in insects. Proc. R. Soc. B 283, 20160042 (2016).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    143.
    Chung, S. H., Jing, X., Luo, Y. & Douglas, A. E. Targeting symbiosis-related insect genes by RNAi in the pea aphid–Buchnera symbiosis. Insect Biochem. Mol. Biol. 95, 55–63 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    144.
    Lemmon, Z. H. et al. Rapid improvement of domestication traits in an orphan crop by genome editing. Nat. Plants 4, 766–770 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    145.
    Li, T. et al. Domestication of wild tomato is accelerated by genome editing. Nat. Biotechnol. 36, 1160–1163 (2018).
    CAS  Article  Google Scholar 

    146.
    Zsögön, A. et al. De novo domestication of wild tomato using genome editing. Nat. Biotechnol. 36, 1211–1216 (2018).
    Article  CAS  Google Scholar 

    147.
    Geddes, B. A. et al. Engineering transkingdom signalling in plants to control gene expression in rhizosphere bacteria. Nat. Commun. 10, 3430 (2019).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    148.
    Petrosino, J. F. The microbiome in precision medicine: the way forward. Genome Med. 10, 12 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    149.
    Basso, B. & Antle, J. Digital agriculture to design sustainable agricultural systems. Nat. Sustain. 3, 254–256 (2020).
    Article  Google Scholar 

    150.
    Schlaeppi, K. & Bulgarelli, D. The plant microbiome at work. Mol. Plant Microbe Interact. 28, 212–217 (2015).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    151.
    Vannette, R. L. The floral microbiome: plant, pollinator, and microbial perspectives. Annu. Rev. Ecol. Evol. Syst. 51, 363–386 (2020).
    Article  Google Scholar 

    152.
    Pineda, A., Kaplan, I., Hannula, S. E., Ghanem, W. & Bezemer, M. T. Conditioning the soil microbiome through plant‐soil feedbacks suppresses an aboveground insect pest. New Phytol. 226, 595–608 (2020).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    153.
    Blundell, R. et al. Organic management promotes natural pest control through altered plant resistance to insects. Nat. Plants 6, 483–491 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    154.
    Mendes, R. et al. Deciphering the rhizosphere microbiome for disease-suppressive bacteria. Science 332, 1097–1100 (2011).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    155.
    Gu, S. et al. Competition for iron drives phytopathogen control by natural rhizosphere microbiomes. Nat. Microbiol. 5, 1002–1010 (2020).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    156.
    Zengler, K. et al. EcoFABs: advancing microbiome science through standardized fabricated ecosystems. Nat. Methods 16, 567–571 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    157.
    Kaplan, I. et al. Phylogenetic farming: can evolutionary history predict crop rotation via the soil microbiome? Evol. Appl. 13, 1984–1999 (2020).
    PubMed  PubMed Central  Article  Google Scholar 

    158.
    Chang, H. X., Haudenshield, J. S., Bowen, C. R. & Hartman, G. L. Metagenome-wide association study and machine learning prediction of bulk soil microbiome and crop productivity. Front. Microbiol. 8, 519 (2017).
    PubMed  PubMed Central  Google Scholar 

    159.
    Ribière, C., Hegarty, C., Stephenson, H., Whelan, P. & O’Toole, P. W. Gut and whole-body microbiota of the honey bee separate thriving and non-thriving hives. Microb. Ecol. 78, 195–205 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    160.
    Wei, Z. et al. Initial soil microbiome composition and functioning predetermine future plant health. Sci. Adv. 5, eaaw0759 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    161.
    Bainard, L. D., Bainard, J. D., Hamel, C. & Gan, Y. Spatial and temporal structuring of arbuscular mycorrhizal communities is differentially influenced by abiotic factors and host crop in a semi-arid prairie agroecosystem. FEMS Microbiol. Ecol. 88, 333–344 (2014).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    162.
    Stedtfeld, R. D. et al. Primer set 2.0 for highly parallel qPCR array targeting antibiotic resistance genes and mobile genetic elements. FEMS Microbiol. Ecol. 94, fiy130 (2018).
    CAS  Article  Google Scholar 

    163.
    Shade, A. Diversity is the question, not the answer. ISME J. 11, 1–6 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    164.
    Saleem, M., Hu, J. & Jousset, A. More than the sum of its parts: microbiome biodiversity as a driver of plant growth and soil health. Annu. Rev. Ecol. Evol. Syst. 50, 145–168 (2019).
    Article  Google Scholar 

    165.
    Shao, H. & Zhang, Y. Non-target effects on soil microbial parameters of the synthetic pesticide carbendazim with the biopesticides cantharidin and norcantharidin. Sci. Rep. 7, 5521 (2017).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    166.
    Wu, M. et al. Rational dose of insecticide chlorantraniliprole displays a transient impact on the microbial metabolic functions and bacterial community in a silty-loam paddy soil. Sci. Total Environ. 616–617, 236–244 (2018).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    167.
    Adak, T. et al. Target and non-target effect of commonly used fungicides on microbial properties in rhizospheric soil of rice. Int. J. Environ. Anal. Chem. 100, 1350–1361 (2019).
    Article  CAS  Google Scholar 

    168.
    Wang, Y. et al. Long-term no-tillage and organic input management enhanced the diversity and stability of soil microbial community. Sci. Total Environ. 609, 341–347 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    169.
    Hartmann, M., Frey, B., Mayer, J., Mäder, P. & Widmer, F. Distinct soil microbial diversity under long-term organic and conventional farming. ISME J. 9, 1177–1194 (2015).
    PubMed  Article  PubMed Central  Google Scholar 

    170.
    Zhu, S., Vivanco, J. M. & Manter, D. K. Nitrogen fertilizer rate affects root exudation, the rhizosphere microbiome and nitrogen-use-efficiency of maize. Appl. Soil Ecol. 107, 324–333 (2016).
    Article  Google Scholar 

    171.
    Yeoh, Y. K. et al. The core root microbiome of sugarcanes cultivated under varying nitrogen fertilizer application. Environ. Microbiol. 18, 1338–1351 (2016).
    PubMed  Article  PubMed Central  Google Scholar 

    172.
    Liu, Y. & Ludewig, U. Nitrogen-dependent bacterial community shifts in root, rhizome and rhizosphere of nutrient-efficient Miscanthus x giganteus from long-term field trials. GCB Bioenergy 11, 1334–1347 (2019).
    CAS  Article  Google Scholar 

    173.
    Shaharoona, B., Naveed, M., Arshad, M. & Zahir, Z. A. Fertilizer-dependent efficiency of Pseudomonads for improving growth, yield, and nutrient use efficiency of wheat (Triticum aestivum L.). Appl. Microbiol. Biotechnol. 79, 147–155 (2008).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    174.
    Chen, S. et al. Root-associated microbiomes of wheat under the combined effect of plant development and nitrogen fertilization. Microbiome 7, 136 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    175.
    Shen, W. et al. Higher rates of nitrogen fertilization decrease soil enzyme activities, microbial functional diversity and nitrification capacity in a Chinese polytunnel greenhouse vegetable land. Plant Soil 337, 137–150 (2010).
    CAS  Article  Google Scholar 

    176.
    Wang, Z., Li, Y., Li, T., Zhao, D. & Liao, Y. Tillage practices with different soil disturbance shape the rhizosphere bacterial community throughout crop growth. Soil Tillage Res. 197, 104501 (2020).
    Article  Google Scholar 

    177.
    Kraut-Cohen, J. et al. Effects of tillage practices on soil microbiome and agricultural parameters. Sci. Total Environ. 705, 135791 (2020).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    178.
    Mavrodi, D. V. et al. Long-term irrigation affects the dynamics and activity of the wheat rhizosphere microbiome. Front. Plant Sci. 9, 345 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    179.
    Hartmann, M. et al. A decade of irrigation transforms the soil microbiome of a semi‐arid pine forest. Mol. Ecol. 26, 1190–1206 (2017).
    PubMed  Article  PubMed Central  Google Scholar 

    180.
    Palacios, O. A. et al. Monitoring of indicator and multidrug resistant bacteria in agricultural soils under different irrigation patterns. Agric. Water Manag. 184, 19–27 (2017).
    Article  Google Scholar 

    181.
    Mavrodi, D. V. et al. Long-term irrigation affects the dynamics and activity of the wheat rhizosphere microbiome. Front. Plant. Sci. 9, 345 (2018).
    PubMed  PubMed Central  Article  Google Scholar  More

  • in

    The Fennoscandian Shield deep terrestrial virosphere suggests slow motion ‘boom and burst’ cycles

    1.
    Edwards, K. J., Becker, K. & Colwell, F. The deep, dark energy biosphere: intraterrestrial life on Earth. Ann. Rev. Earth Planet Sci. 40, 551–568 (2012).
    CAS  Article  Google Scholar 
    2.
    Kallmeyer, J., Pockalny, R., Adhikari, R. R., Smith, D. C. & D’Hondt, S. Global distribution of microbial abundance and biomass in subseafloor sediment. Proc. Nat. Acad. Sci. USA 109, 16213–16216 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    3.
    Bar-On, Y. M., Phillips, R. & Milo, R. The biomass distribution on Earth. Proc. Nat. Acad. Sci. USA 115, 6506–6511 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    4.
    Magnabosco, C. et al. The biomass and biodiversity of the continental subsurface. Nat. Geosci. 11, 707–717 (2018).
    CAS  Article  Google Scholar 

    5.
    Lau, M. C. Y. et al. An oligotrophic deep-subsurface community dependent on syntrophy is dominated by sulfur-driven autotrophic denitrifiers. Proc. Nat. Acad. Sci. USA 113, E7927–E7936 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    6.
    Lopez-Fernandez, M., Broman, E., Simone, D., Bertilsson, S. & Dopson, M. Statistical analysis of community RNA transcripts between organic carbon and ‘geogas’ fed continental deep biosphere groundwaters. mBio 10, e01470–01419 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    7.
    Lopez-Fernandez, M. et al. Metatranscriptomes reveal all three domains of life are active, but are dominated by bacteria in the Fennoscandian crystalline granitic continental deep biosphere. mBio 9, e01792–01718 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    8.
    Borgonie, G. et al. Eukaryotic opportunists dominate the deep-subsurface biosphere in South Africa. Nat. Comm. 6, 8952 (2015).
    CAS  Article  Google Scholar 

    9.
    Wilkins, M. J. et al. Trends and future challenges in sampling the deep terrestrial biosphere. Front. Microbiol. 5, 481 (2014).
    PubMed  PubMed Central  Google Scholar 

    10.
    Guemes, A. G. C. et al. Viruses as winners in the Game of Life. Ann. Rev. Virol. 3, 197–214 (2016).
    Article  CAS  Google Scholar 

    11.
    Dávila-Ramos, S. et al. A review on viral metagenomics in extreme environments. Front. Microbiol. 10, 2403 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    12.
    Roudnew, B. et al. Bacterial and virus-like particle abundances in purged and unpurged groundwater depth profiles. Ground Water Monit. Remed. 32, 72–77 (2012).
    Article  Google Scholar 

    13.
    Nyyssönen, M. et al. Taxonomically and functionally diverse microbial communities in deep crystalline rocks of the Fennoscandian shield. ISME J. 8, 126–138 (2014).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    14.
    Daly, R. A. et al. Microbial metabolisms in a 2.5-km-deep ecosystem created by hydraulic fracturing in shales. Nat. Microbiol. 1, 16146 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    15.
    Anderson, R. E., Brazelton, W. J. & Baross, J. A. Is the genetic landscape of the deep subsurface biosphere affected by viruses? Front. Microbiol. 2, 219–219 (2011).
    PubMed  PubMed Central  Article  Google Scholar 

    16.
    Anderson, R. E., Brazelton, W. J. & Baross, J. A. The deep viriosphere: assessing the viral impact on microbial community dynamics in the deep subsurface. Rev. Min. Geochem. 75, 649–675 (2013).
    CAS  Article  Google Scholar 

    17.
    Labonté, J. M. et al. Single cell genomics indicates horizontal gene transfer and viral infections in a deep subsurface Firmicutes population. Front. Microbiol. 6, 349–349 (2015).
    PubMed  PubMed Central  Google Scholar 

    18.
    Hallbeck, L. & Pedersen, K. Characterization of microbial processes in deep aquifers of the Fennoscandian Shield. Appl. Geochem. 23, 1796–1819 (2008).
    CAS  Article  Google Scholar 

    19.
    Ström, A., Andersson, J., Skagius, K. & Winberg, A. Site descriptive modelling during characterization for a geological repository for nuclear waste in Sweden. Appl. Geochem. 23, 1747–1760 (2008).
    Article  CAS  Google Scholar 

    20.
    Jägevall, S., Rabe, L. & Pedersen, K. Abundance and diversity of biofilms in natural and artificial aquifers of the Äspö Hard Rock Laboratory, Sweden. Microb. Ecol. 61, 410–422 (2011).
    PubMed  Article  Google Scholar 

    21.
    Pedersen, K. Influence of H2 and O2 on sulphate-reducing activity of a subterranean community and the coupled response in redox potential. FEMS Microbiol. Ecol. 82, 653–665 (2012).
    CAS  PubMed  Article  Google Scholar 

    22.
    Pedersen, K. Metabolic activity of subterranean microbial communities in deep granitic groundwater supplemented with methane and H2. ISME J. 7, 839–849 (2013).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    23.
    Lopez-Fernandez, M., Broman, E., Wu, X., Bertilsson, S. & Dopson, M. Investigation of viable taxa in the deep terrestrial biosphere suggests high rates of nutrient recycling. FEMS Microbiol. Ecol. 94, fiy121 (2018).

    24.
    Lopez-Fernandez, M., Åström, M., Bertilsson, S. & Dopson, M. Depth and dissolved organic carbon shape microbial communities in surface influenced but not ancient saline terrestrial aquifers. Front. Microbiol. 9, 2880 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    25.
    Wu, X. et al. Microbial metagenomes from three aquifers in the Fennoscandian shield terrestrial deep biosphere reveal metabolic partitioning among populations. ISME J. 10, 1192–1203 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    26.
    Kyle, J. E., Eydal, H. S., Ferris, F. G. & Pedersen, K. Viruses in granitic groundwater from 69 to 450 m depth of the Äspö hard rock laboratory, Sweden. ISME J. 2, 571–574 (2008).
    PubMed  Article  PubMed Central  Google Scholar 

    27.
    Eydal, H. S., Jagevall, S., Hermansson, M. & Pedersen, K. Bacteriophage lytic to Desulfovibrio aespoeensis isolated from deep groundwater. ISME J. 3, 1139–1147 (2009).
    PubMed  Article  PubMed Central  Google Scholar 

    28.
    Castelle, C. J. et al. Biosynthetic capacity, metabolic variety and unusual biology in the CPR and DPANN radiations. Nat. Rev. Microbiol. 16, 629–645 (2018).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    29.
    Hurwitz, B. L. & Sullivan, M. B. The Pacific Ocean Virome (POV): A marine viral metagenomic dataset and associated protein clusters for quantitative viral ecology. PLoS ONE 8, e57355 (2013).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    30.
    Angly, F. E. et al. The marine viromes of four oceanic regions. PLoS Biol. 4, e368 (2006).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    31.
    Holmfeldt, K. et al. Twelve previously unknown phage genera are ubiquitous in global oceans. Proc. Nat. Acad. Sci. USA 110, 12798–12803 (2013).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    32.
    Nilsson, E. et al. Genomic and seasonal variations among aquatic phages infecting the Baltic Sea Gammaproteobacterium Rheinheimera sp. strain BAL341. Appl. Environ. Microbiol. 85, e01003-19, https://doi.org/10.1128/aem.01003-19 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    33.
    Hurwitz, B. L., U’Ren, J. M. & Youens-Clark, K. Computational prospecting the great viral unknown. FEMS Microbiol. Lett. 363, fnw077 (2016).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    34.
    Bolduc, B. et al. vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect Archaea and Bacteria. PeerJ 5, e3243–e3243 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    35.
    Lundin, D. & Holmfeldt, K. The deep terrestrial virosphere. Figshare, https://doi.org/10.6084/m6089.figshare.11590494.v11590491 (2020).

    36.
    Brum, J. R. et al. Patterns and ecological drivers of ocean viral communities. Science 348, 1261498 (2015).
    PubMed  Article  CAS  PubMed Central  Google Scholar 

    37.
    Kadnikov, V. V. et al. Genomes of three bacteriophages from the deep subsurface aquifer. Data Brief. 22, 488–491 (2019).
    PubMed  Article  PubMed Central  Google Scholar 

    38.
    Starnawski, P. et al. Microbial community assembly and evolution in subseafloor sediment. Proc. Nat. Acad. Sci. USA 114, 2940–2945 (2017).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    39.
    Broman, E., Sjöstedt, J., Pinhassi, J. & Dopson, M. Shifts in coastal sediment oxygenation cause pronounced changes in microbial community composition and associated metabolism. Microbiome 5, 96 (2017).
    PubMed  PubMed Central  Article  Google Scholar 

    40.
    Edwards, R. A., McNair, K., Faust, K., Raes, J. & Dutilh, B. E. Computational approaches to predict bacteriophage-host relationships. FEMS Microbiol. Rev. 40, 258–272 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    41.
    Hug, L. A. et al. A new view of the tree of life. Nat. Microbiol. 1, 16048, https://doi.org/10.1038/nmicrobiol.2016.48 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    42.
    Parks, D. H. et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat. Biotechnol. 36, 996–1004, https://doi.org/10.1038/nbt.4229 (2018).
    Article  PubMed  PubMed Central  Google Scholar 

    43.
    Herrmann, M. et al. Predominance of Cand. Patescibacteria in groundwater is caused by their preferential mobilization from soils and flourishing under oligotrophic conditions. Front. Microbiol. 10, 1407 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    44.
    Probst, A. J. et al. Differential depth distribution of microbial function and putative symbionts through sediment-hosted aquifers in the deep terrestrial subsurface. Nat. Microbiol. 3, 328–336 (2018).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    45.
    Anantharaman, K. et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat. Comm. 7, https://doi.org/10.1038/ncomms13219 (2016).

    46.
    Bouvier, T. & del Giorgio, P. A. Key role of selective viral-induced mortality in determining marine bacterial community composition. Environ. Microbiol. 9, 287–297 (2007).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    47.
    Dinsdale, E. A. et al. Functional metagenomic profiling of nine biomes. Nature 452, 629–632 (2008).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    48.
    Craig, W. A. & Andes, D. R. in Mandell, Douglas, and Bennett’s Principles and Practice of Infectious Diseases (eds Bennett, J. E., Dolin, R. & Blaser, M. J.) 278–292.e274 (2015).

    49.
    Hubalek, V. et al. Connectivity to the surface determines diversity patterns in subsurface aquifers of the Fennoscandian shield. ISME J. 10, 2447–2458 (2016).
    PubMed  PubMed Central  Article  Google Scholar 

    50.
    Laaksoharju, M., Gascoyne, M. & Gurban, I. Understanding groundwater chemistry using mixing models. Appl. Geochem. 23, 1921–1940 (2008).
    CAS  Article  Google Scholar 

    51.
    Mathurin, F. A., Astrom, M. E., Laaksoharju, M., Kalinowski, B. E. & Tullborg, E. L. Effect of tunnel excavation on source and mixing of groundwater in a coastal granitoidic fracture network. Environ. Sci. Technol. 46, 12779–12786 (2012).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    52.
    Smellie, J. A. T., Laaksoharju, M., Wikberg, P. & Äspö, S. E. Sweden—a natural groundwater-flow model derived from hydrogeological observations. J. Hydrol. 172, 147–169 (1995).
    CAS  Article  Google Scholar 

    53.
    John, S. G. et al. A simple and efficient method for concentration of ocean viruses by chemical flocculation. Environ. Microbiol. Rep. 3, 195–202 (2011).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    54.
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    55.
    Boisvert, S., Raymond, F., Godzaridis, E., Laviolette, F. & Corbeil, J. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol. 13, R122 (2012).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    56.
    Rodriguez-R, L. M., Gunturu, S., Tiedje, J. M., Cole, J. R. & Konstantinidis, K. T. Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems 3, e00039–00018 (2018).
    PubMed  PubMed Central  Article  Google Scholar 

    57.
    Roux, S., Enault, F., Hurwitz, B. L. & Sullivan, M. B. VirSorter: mining viral signal from microbial genomic data. PeerJ 3, e985–e985 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    58.
    Brum, J. R. et al. Illuminating structural proteins in viral “dark matter” with metaproteomics. Proc. Nat. Acad. Sci. USA 113, 2436–2441 (2016).
    CAS  PubMed  Article  PubMed Central  Google Scholar 

    59.
    Hugerth, L. W. et al. Metagenome-assembled genomes uncover a global brackish microbiome. Genome Biol. 16, 279 (2015).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    60.
    Dupont, C. L. et al. Functional tradeoffs underpin salinity-driven divergence in microbial community composition. PloS One 9, e89549 (2014).
    PubMed  PubMed Central  Article  CAS  Google Scholar 

    61.
    Chow, C. E., Winget, D. M., White, R. A., 3rd, Hallam, S. J. & Suttle, C. A. Combining genomic sequencing methods to explore viral diversity and reveal potential virus-host interactions. Front. Microbiol. 6, 265, https://doi.org/10.3389/fmicb.2015.00265 (2015).

    62.
    Tangherlini, M., Dell’Anno, A., Zeigler Allen, L., Riccioni, G. & Corinaldesi, C. Assessing viral taxonomic composition in benthic marine ecosystems: reliability and efficiency of different bioinformatic tools for viral metagenomic analyses. Sci. Rep. 6, 28428, https://doi.org/10.1038/srep28428 (2016).

    63.
    Sible, E. et al. Survey of viral populations within Lake Michigan nearshore waters at four Chicago area beaches. Data Brief. 5, 9–12 (2015).
    PubMed  PubMed Central  Article  Google Scholar 

    64.
    Roux, S. et al. Ecogenomics and potential biogeochemical impacts of globally abundant ocean viruses. Nature 537, 689 (2016).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    65.
    Wu, X. et al. Potential for hydrogen-oxidizing chemolithoautotrophic and diazotrophic populations to initiate biofilm formation in oligotrophic, deep terrestrial subsurface waters. Microbiome 5, 37, https://doi.org/10.1186/s40168-40017-40253-y (2017).

    66.
    Marcais, G. & Kingsford, C. A fast, lock-free approach for efficient parallel counting of occurrences of k-mers. Bioinformatics 27, 764–770 (2011).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    67.
    Sullivan, M. J., Petty, N. K. & Beatson, S. A. Easyfig: a genome comparison visualizer. Bioinformatics 27, 1009–1010 (2011).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    68.
    Simone, D. Domenico-simone/deep-metaviriomes: analysis for paper. Zenodo https://doi.org/10.5281/zenodo.3700451 (2020).
    Article  Google Scholar  More

  • in

    An ecological niche shift for Neanderthal populations in Western Europe 70,000 years ago

    1.
    d’Errico, F. & Banks, W. E. Identifying mechanisms behind Middle Paleolithic and Middle Stone Age cultural trajectories. Curr. Anthropol. 54, S371–S387 (2013).
    Article  Google Scholar 
    2.
    Richerson, P. J., Bettinger, R. L. & Boyd, R. Evolution on a restless planet: Were environmental variability and environmental change major drivers of human evolution? In Handbook of Evolution: The Evolution of Living Systems (Including Hominids) Vol. 2 (eds Wuketits, F. M. & Ayala, F. J.) 223–242 (Wiley-VCH, New York, 2005).
    Google Scholar 

    3.
    Pedersen, J., Maier, A. & Riede, F. A punctuated model for the colonisation of the Late Glacial margins of northern Europe by Hamburgian hunter-gatherers. Quartär 65, 85–104 (2018).
    Google Scholar 

    4.
    Riede, F. & Pedersen, J. B. Late glacial human dispersals in Northern Europe and disequilibrium dynamics. Hum. Ecol. 46, 621–632 (2018).
    Article  Google Scholar 

    5.
    Langley, M. C., Clarkson, C. & Ulm, S. Behavioural complexity in Eurasian Neanderthal Populations: A chronological examination of the archaeological evidence. Camb. Archaeol. J. 18, 289–307 (2008).
    Article  Google Scholar 

    6.
    Roebroeks, W. & Soressi, M. Neandertals revised. Proc. Natl. Acad. Sci. USA 113, 6372–6379 (2016).
    CAS  PubMed  Article  Google Scholar 

    7.
    Zilhão, J. et al. Last Interglacial Iberian Neandertals as fisher-hunter-gatherers. Science 367, 6485 (2020).
    Article  CAS  Google Scholar 

    8.
    Benito, B. M. et al. The ecological niche and distribution of Neanderthals during the Last Interglacial. J. Biogeogr. 44, 51–61 (2017).
    Article  Google Scholar 

    9.
    Nielsen, T. K. et al. Investigating Neanderthal dispersal above 55°N in Europe during the Last Interglacial Complex. Quat. Int. 431, 88–103 (2017).
    Article  Google Scholar 

    10.
    Bocquet-Appel, J.-P. & Tuffreau, A. Technological responses of neanderthals to macroclimatic variations (240,000–40,000 BP). Hum. Biol. 81, 287–307 (2009).
    PubMed  Article  Google Scholar 

    11.
    Daujeard, C. et al. Neanderthal subsistence strategies in Southeastern France between the plains of the Rhone Valley and the mid-mountains of the Massif Central (MIS 7 to MIS 3). Quat. Int. 252, 32–47 (2012).
    Article  Google Scholar 

    12.
    Discamps, E., Jaubert, J. & Bachellerie, F. Human choices and environmental constraints: deciphering the variability of large game procurement from Mousterian to Aurignacian times (MIS 5–3) in southwestern France. Quat. Sci. Rev. 30, 2755–2775 (2011).
    Article  ADS  Google Scholar 

    13.
    Hublin, J. J. The origin of Neandertals. Proc. Natl. Acad. Sci. USA 106, 16022–16027 (2009).
    CAS  PubMed  Article  ADS  Google Scholar 

    14.
    Rogers, A. R., Bohlender, R. J. & Huff, C. D. Early history of Neanderthals and Denisovans. Proc. Natl. Acad. Sci. USA 114, 9859–9863 (2017).
    CAS  PubMed  Article  Google Scholar 

    15.
    Moncel, M.-H. et al. Early Levallois core technology between Marine Isotope Stage 12 and 9 in Western Europe. J. Hum. Evol. 139, 102735 (2020).
    PubMed  Article  Google Scholar 

    16.
    Castellano, S. et al. Patterns of coding variation in the complete exomes of three Neandertals. Proc. Natl. Acad. Sci. USA 111, 6666–6671 (2014).
    CAS  PubMed  Article  ADS  Google Scholar 

    17.
    Mafessoni, F. & Prüfer, K. Better support for a small effective population size of Neandertals and a long shared history of Neandertals and Denisovans. Proc. Natl. Acad. Sci. USA 114, E10256–E10257 (2017).
    CAS  PubMed  Article  Google Scholar 

    18.
    Prüfer, K. et al. A high-coverage Neandertal genome from Vindija Cave in Croatia. Science 358, 655–658 (2017).
    PubMed  PubMed Central  Article  ADS  CAS  Google Scholar 

    19.
    Moncel, M.-H., Fernandes, P., Willmes, M., James, H. & Grün, R. Rocks, teeth, and tools: New insights into early Neanderthal mobility strategies in South-Eastern France from lithic reconstructions and strontium isotope analysis. PLoS ONE 14, e0214925 (2019).
    CAS  PubMed  PubMed Central  Article  Google Scholar 

    20.
    Peterson, A. T. et al. Ecological Niches and Geographic Distributions (Princeton University Press, Princeton, 2011).
    Google Scholar 

    21.
    Rogers, A. R., Bohlender, R. J. & Huff, C. D. Reply to Mafessoni and Prüfer: Inferences with and without singleton site patterns. Proc. Natl. Acad. Sci. USA 114, E10258–E10260 (2017).
    CAS  PubMed  Article  Google Scholar 

    22.
    Vaissié, E. et al. Techno-économie et signification culturelle de l’occupation moustérienne supérieure de Baume-Vallée (Haute-Loire). C.R. Palevol 16, 804–819 (2017).
    Article  Google Scholar 

    23.
    Bocquet-Appel, J.-P., Demars, P.-Y., Noiret, L. & Dobrowsky, D. Estimates of Upper Palaeolithic meta-population size in Europe from archaeological data. J. Archaeol. Sci. 32, 1656–1668 (2005).
    Article  Google Scholar 

    24.
    Delagnes, A., Jaubert, J. & Meignen, L. Les technocomplexes du Paléolithique moyen en Europe occidentale dans leur cadre diachronique et géographique. In Les Néandertaliens Biologie et cultures (eds Vandermeersch, B. & Maureille, B.) 213–229 (Editions du Comité des Travaux Historiques et Scientifiques, Aubervilliers, 2007).
    Google Scholar 

    25.
    Faivre, J.-P., Gravina, B., Bourguignon, L., Discamps, E. & Turq, A. Late Middle Palaeolithic lithic technocomplexes (MIS 5–3) in the northeastern Aquitaine Basin: Advances and challenges. Quat. Int. 433, 116–131 (2017).
    Article  Google Scholar 

    26.
    Jaubert, J., Bordes, J.-G., Discamps, E. & Gravina, B. A new look at the end of the Middle Palaeolithic Sequence in Southwestern France. In Characteristic Features of the Middle to Upper Paleolithic transition in Eurasia (eds Derevianko, A. P. & Shunkov, M. V.) 102–115 (Asian Palaeolithic Association, Tokyo, 2011).
    Google Scholar 

    27.
    Boëda, E. Levallois: A volumetric construction, methods, A technique. In The Definition and Intrepretation of Levallois Technology (eds Dibble, H. L. & Bar-Yosef, O.) 41–68 (Prehistory Press, Madison, 1995).
    Google Scholar 

    28.
    Boëda, E. L. débitage discoïde et le débitage Levallois récurrent centripède. Bull. Soc. Préhist. Fr. 90, 392–404 (1993).
    Article  Google Scholar 

    29.
    Bourguignon, L. Le Moustérien de type Quina: Nouvelles définitions d’une entité technique (University of Paris 10, Paris, 1997).
    Google Scholar 

    30.
    Turq, A. L. Moustérien de type Quina. Paléo Rev. Archéol. Préhist. 2, 310–343 (2000).
    Google Scholar 

    31.
    Turq, A. Approche technologique et économique du faciès Moustérien de type Quina: Étude préliminaire. Bull. Soc. Préhist. Fr. 86, 244–256 (1989).
    Article  Google Scholar 

    32.
    Collard, M., Vaesen, K., Cosgrove, R. & Roebroeks, W. The empirical case against the ‘demographic turn’ in Palaeolithic archaeology. Philos. Trans. R. Soc. B 371, 20150242 (2016).
    Article  Google Scholar 

    33.
    Soberón, J. & Nakamura, M. Niches and distributional areas: Concepts, methods, and assumptions. Proc. Natl. Acad. Sci. USA 106, 19644–19650 (2009).
    PubMed  Article  ADS  Google Scholar 

    34.
    Cobos, M. E., Peterson, A. T., Barve, N. & Osorio-Olvera, L. kuenm: An R package for detailed development of ecological niche models using Maxent. PeerJ 7, e6281 (2019).
    PubMed  PubMed Central  Article  Google Scholar 

    35.
    Cobos, M. E., Osorio-Olvera, L., Soberón, J. & Peterson, A. T. ellipsenm: An R package for ecological niche’s characterization using ellipsoids. (2020).

    36.
    Waelbroeck, C. et al. Sea-level and deep water temperature changes derived from benthic foraminifera isotopic records. Quat. Sci. Rev. 21, 295–305 (2002).
    Article  ADS  Google Scholar 

    37.
    Peterson, A. T., Papeş, M. & Soberón, J. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Model. 213, 63–72 (2008).
    Article  Google Scholar 

    38.
    Antoine, P. et al. Paléoenvironnements pléistocènes et peuplements paléolithiques dans le bassin de la Somme (nord de la France). Bull. Soc. Préhist. Fr. 100, 5–28 (2003).
    Article  Google Scholar 

    39.
    Locht, J.-L. et al. Timescales, space and culture during the Middle Palaeolithic in northwestern France. Quat. Int. 411, 129–148 (2016).
    Article  Google Scholar 

    40.
    Raynal, J.-P. et al. Land-use strategies, related tool-kits and social organization of lower and middle Palaeolithic groups in the South-East of the Massif Central, France. Quartär 60, 29–59 (2013).
    Google Scholar 

    41.
    Turq, A., Faivre, J.-P., Gravina, B. & Bourguignon, L. Building models of Neanderthal territories from raw material transports in the Aquitaine Basin (southwestern France). Quat. Int. 433, 88–101 (2017).
    Article  Google Scholar 

    42.
    Mathias, C., Bourguignon, L., Brenet, M., Grégoire, S. & Moncel, M.-H. Between new and inherited technical behaviours: A case study from the Early Middle Palaeolithic of Southern France. Archaeol. Anthropol. Sci. 12, 1–39 (2020).
    Article  Google Scholar 

    43.
    Lebegue, F. & Meignen, L. Quina ou pas ? Révision techno-économique d’un site moustérien charentien en Languedoc oriental: La grotte de la Roquette à Conqueyrac (Gard, France). Bull. Soc. Préhist. Fr. 111, 603–630 (2014).
    Article  Google Scholar 

    44.
    Moncel, M.-H. et al. La grotte du Figuier (Saint-Martin-d’Ardèche): Bilan des travaux récents sur un site du Paléolithique moyen et supérieur de la moyenne vallée du Rhône (Sud-Est de la France). Bull. Soc. Préhist. Fr. 109, 35–67 (2012).
    Article  Google Scholar 

    45.
    Slimak, L. Moustériens Quina Rhodaniens et Quina classiques dans le sud-est de la France. In Territoires, Déplacements, Mobilité, Echanges durant la Préhistoire (eds Jaubert, J. & Barbaza, M.) 95–113 (Comité des travaux historiques et scientifiques, Aubervilliers, 2005).
    Google Scholar 

    46.
    Sánchez Goñi, M. F., Bard, E., Landais, A., Rossignol, L. & d’Errico, F. Air–sea temperature decoupling in western Europe during the last interglacial–glacial transition. Nat. Geosci. 6, 837–841 (2013).
    Article  ADS  CAS  Google Scholar 

    47.
    Antoine, P., Munaut, A.-V. & Sommé, J. Réponse des environnements aux climats du début glaciaire weichsélien: Données de la France du Nord-Ouest [Responses of the environments to Early Weichselian climates. Records in north­western France]. Quaternaire 5, 151–156 (1994).
    Article  Google Scholar 

    48.
    Fletcher, W. J. et al. Millennial-scale variability during the last glacial in vegetation records from Europe. Quat. Sci. Rev. 29, 2839–2864 (2010).
    Article  ADS  Google Scholar 

    49.
    Baena, J., Moncel, M.-H., Cuartero, F., Chacón Navarro, M. G. & Rubio, D. Late Middle Pleistocene genesis of Neanderthal technology in Western Europe: The case of Payre site (south-east France). Quat. Int. 436, 212–238 (2017).
    Article  Google Scholar 

    50.
    Geneste, J.-M., Jaubert, J., Lenoir, M., Meignen, L. & Turq, A. Approche technologique des Moustériens Charentiens du Sud-Ouest de la France et du Languedoc oriental. Paléo Rev. Archéol. Préhist. 9, 101–142 (1997).
    Google Scholar 

    51.
    Geneste, J.-M. & Plisson, H. Production et utilisation de l’outillage lithique dans le Moustérien du sud-ouest de la France: les Tares à Sourzac, Vallé de l’Isle, Dordogne. Quat. Nova 6, 343–367 (1996).
    Google Scholar 

    52.
    Mathias, C. & Bourguignon, L. Cores-on-flakes and ramification during the middle palaeolithic in Southern France: A gradual process from the early to late middle palaeolithic?. J. Archaeol. Sci. Rep. 31, 102336 (2020).
    Google Scholar 

    53.
    Halstead, P. & O’Shea, J. Introduction: Cultural responses to risk and uncertainty. In Bad Year Economics: Cultural Responses to Risk and Uncertainty (eds Halstead, P. & O’Shea, J.) 1–7 (Cambridge University Press, Cambridge, 1989).
    Google Scholar 

    54.
    d’Errico, F. et al. Identifying early modern human ecological niche expansions and associated cultural dynamics in the South African Middle Stone Age. Proc. Natl. Acad. Sci. USA 114, 7869–7876 (2017).
    PubMed  Article  CAS  Google Scholar 

    55.
    Delagnes, A. & Meignen, L. Diversity of lithic production systems during the Middle Paleolithic in France. In Transitions Before the Transition: Evolution and Stability in the Middle Paleolithic and Middle Stone Age (eds Hovers, E. & Kuhn, S. L.) 85–107 (Springer Verlag, New York, 2006).
    Google Scholar 

    56.
    Hiscock, P., Turq, A., Faivre, J.-P. & Bourguignon, L. Quina procurement and tool production. In Lithic Materials and Paleolithic Societies (eds Adams, B. & Blades, B. S.) 232–246 (Wiley-Blackwell, New York, 2009).
    Google Scholar 

    57.
    Binford, L. R. Willow smoke and dogs’ tails: Hunter-gatherer settlement systems and archaeological site formation. Am. Antiq. 45, 4–20 (1980).
    Article  Google Scholar 

    58.
    Dibble, H. L. et al. Context, curation, and bias: An evaluation of the Middle Paleolithic collections of Combe-Grenal (France). J. Archaeol. Sci. 36, 2540–2550 (2009).
    Article  Google Scholar 

    59.
    R Core Team. R: A Language and Environment for STATISTICAL Computing (R Foundation for Statistical Computing, Vienna, 2019).
    Google Scholar 

    60.
    Lê, S., Josse, J. & Husson, F. FactoMineR: An R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).
    Article  Google Scholar 

    61.
    Sarkar, D. Lattice: Multivariate Data Visualization with R (Springer, Berlin, 2008).
    Google Scholar 

    62.
    Fernandes, P., Raynal, J.-P. & Moncel, M.-H. Middle Palaeolithic raw material gathering territories and human mobility in the southern Massif Central, France: first results from a petro-archaeological study on flint. J. Archaeol. Sci. 35, 2357–2370 (2008).
    Article  Google Scholar 

    63.
    Dufresne, J.-L. et al. Climate change projections using the IPSL-CM5 Earth System Model: from CMIP3 to CMIP5. Clim. Dyn. 40, 2123–2165 (2013).
    Article  Google Scholar 

    64.
    Argus, D. F. & Peltier, W. R. Constraining models of postglacial rebound using space geodesy: A detailed assessment of model ICE-5G (VM2) and its relatives. Geophys. J. Int. 181, 697–723 (2010).
    ADS  Google Scholar 

    65.
    Petit, J. R. et al. Climate and atmospheric history of the past 420,000 years from the Vostok ice core, Antarctica. Nature 399, 429–436 (1999).
    CAS  Article  ADS  Google Scholar 

    66.
    Laskar, J. et al. A long-term numerical solution for the insolation quantities of the Earth. Astron. Astrophys. 428, 261–285 (2004).
    Article  ADS  Google Scholar 

    67.
    Vrac, M., Marbaix, P., Paillard, D. & Naveau, P. Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe. Clim. Past 3, 669–682 (2007).
    Article  Google Scholar 

    68.
    Pfeiffer, M., Spessa, A. & Kaplan, J. O. A model for global biomass burning in preindustrial time: LPJ-LMfire (v1.0). Geosci. Model Dev. 6, 643–685 (2013).
    Article  ADS  CAS  Google Scholar 

    69.
    Phillips, S. J., Anderson, R. P., Dudík, M., Schapire, R. E. & Blair, M. E. Opening the black box: An open-source release of Maxent. Ecography 40, 887–893 (2017).
    Article  Google Scholar 

    70.
    Cobos, M. E., Peterson, A. T., Osorio-Olvera, L. & Jiménez-García, D. An exhaustive analysis of heuristic methods for variable selection in ecological niche modeling and species distribution modeling. Ecol. Inform. 53, 100983 (2019).
    Article  Google Scholar 

    71.
    Anderson, R. P., Lew, D. & Peterson, A. T. Evaluating predictive models of species’ distributions: Criteria for selecting optimal models. Ecol. Model. 162, 211–232 (2003).
    Article  Google Scholar 

    72.
    Warren, D. L. & Seifert, S. N. Ecological niche modeling in Maxent: the importance of model complexity and the performance of model selection criteria. Ecol. Appl. 21, 335–342 (2011).
    PubMed  Article  Google Scholar 

    73.
    Owens, H. L. et al. Constraints on interpretation of ecological niche models by limited environmental ranges on calibration areas. Ecol. Model. 263, 10–18 (2013).
    Article  Google Scholar 

    74.
    Nuñez-Penichet, C., Cobos, M. E. & Soberon, J. Non-overlapping climatic niches and biogeographic barriers explain disjunct distributions of continental Urania moths. Front. Biogeogr. 13(2), e52142 (2021).
    Google Scholar 

    75.
    Qiao, H. et al. NicheA: Creating virtual species and ecological niches in multivariate environmental scenarios. Ecography 39, 805–813 (2016).
    Article  Google Scholar 

    76.
    Mammola, S. Assessing similarity of n-dimensional hypervolumes: Which metric to use?. J. Biogeogr. 46, 2012–2023 (2019).
    Article  Google Scholar 

    77.
    Van Aelst, S. & Rousseeuw, P. Minimum volume ellipsoid. WIREs. Comput. Stat. 1, 71–82 (2009).
    Article  Google Scholar 

    78.
    Murdoch, D. J. & Chow, E. D. A graphical display of large correlation matrices. Am. Stat. 50, 178–180 (1996).
    Google Scholar  More