Philippa Kaur

Ribic, C. A., Thompson, F. R. & Pietz, P. J. Video Surveillance of Nesting Birds (University of California Press, 2012).Book 

Google Scholar 
O’Brien, T. G. & Kinnaird, M. F. A picture is worth a thousand words: The application of camera trapping to the study of birds. Bird Conserv. Int. 18, S144–S162 (2008).Article 

Google Scholar 
Kristan, D. M., Golightly Jr, R. T. & Tomkiewicz Jr, S. M. A solar-powered transmitting video camera for monitoring raptor nests. Wildl. Soc. Bull. 24, 284–290 (1996).
Google Scholar 
Grubb, T. An infrared video camera system for monitoring diurnal and nocturnal raptors. J. Raptor Res. 32, 290–296 (1998).
Google Scholar 
Margalida, A. et al. A solar-powered transmitting video camera for monitoring cliff-nesting raptors. J. Field Ornithol. 77, 7–12 (2006).Article 

Google Scholar 
Bolton, M., Butcher, N., Sharpe, F., Stevens, D. & Fisher, G. Remote monitoring of nests using digital camera technology. J. Field Ornithol. 78, 213–220 (2007).Article 

Google Scholar 
Pierce, A. J. & Pobprasert, K. A portable system for continuous monitoring of bird nests using digital video recorders. J. Field Ornithol. 78, 322–328 (2007).Article 

Google Scholar 
Benson, T. J., Brown, J. D. & Bednarz, J. C. Identifying predators clarifies predictors of nest success in a temperate passerine. J. Anim. Ecol. 79, 225–234 (2010).Article 

Google Scholar 
Lewis, S. B., Fuller, M. R. & Titus, K. A comparison of 3 methods for assessing raptor diet during the breeding season. Wildl. Soc. Bull. 32, 373–385 (2004).Article 

Google Scholar 
Rogers, A. S. Quantifying Northern Goshawk diets using remote cameras and observations from blinds. J. Raptor Res. 39, 303–309 (2005).ADS 

Google Scholar 
Tornberg, R. & Reif, V. Assessing the diet of birds of prey: A comparison of prey items found in nests and images. Ornis Fenn. 84, 21 (2007).
Google Scholar 
López-López, P. & Urios, V. Use of digital trail cameras to study Bonelli’s eagle diet during the nestling period. Ital. J. Zool. 77, 289–295 (2010).Article 

Google Scholar 
Harrison, J. T., Kochert, M. N., Pauli, B. P. & Heath, J. A. Using motion-activated trail cameras to study diet and productivity of cliff-nesting Golden Eagles. J. Raptor Res. 53, 26–37 (2019).Article 

Google Scholar 
McRae, S. B., Weatherhead, P. J. & Montgomerie, R. American robin nestlings compete by jockeying for position. Behav. Ecol. Sociobiol. 33, 101–106 (1993).Article 

Google Scholar 
Nathan, A., Legge, S. & Cockburn, A. Nestling aggression in broods of a siblicidal kingfisher, the laughing kookaburra. Behav. Ecol. 12, 716–725 (2001).Article 

Google Scholar 
Grivas, C. et al. An audio–visual nest monitoring system for the study and manipulation of siblicide in bearded vultures Gypaetus barbatus on the island of Crete (Greece). J. Ethol. 27, 105–116 (2009).Article 

Google Scholar 
Gula, R., Theuerkauf, J., Rouys, S. & Legault, A. An audio/video surveillance system for wildlife. Eur. J. Wildl. Res. 56, 803–807 (2010).Article 

Google Scholar 
Sanaiotti, T. M., Seixas, G. H., Duleba, S. & Martins, F. D. Camera trapping at harpy eagle nests: Interspecies interactions under predation risk. J. Raptor Res. 51, 72–78 (2017).Article 

Google Scholar 
Allen, M. L., Inagaki, A. & Ward, M. P. Cannibalism in raptors: A review. J. Raptor Res. 54, 424–430 (2020).Article 

Google Scholar 
Academia, M. H. & Dalgleish, H. J. Use of nest web cameras and citizen science to quantify osprey prey delivery rate and nest success. J. Raptor Res. 56, 212–219 (2022).Article 

Google Scholar 
Gysel, L. W. & Davis, E. M. A simple automatic photographic unit for wildlife research. J. Wildl. Manag. 20, 451–453 (1956).Article 

Google Scholar 
Royama, T. A device of an auto-cinematic food-recorder. Jpn. J. Ornithol. 15, 172–176 (1959).Article 

Google Scholar 
Cox, W. A. et al. Development of camera technology for monitoring nests. In Chapter 15. Video Surveill. Nesting Birds Stud. Avian Biol. (eds Ribic, C. A. et al.) 185–210 (Univ. Calif. Press, 2012).Sanders, M. D. & Maloney, R. F. Causes of mortality at nests of ground-nesting birds in the Upper Waitaki Basin, South Island, New Zealand: A 5-year video study. Biol. Conserv. 106, 225–236 (2002).Article 

Google Scholar 
Reif, V. & Tornberg, R. Using time-lapse digital video recording for a nesting study of birds of prey. Eur. J. Wildl. Res. 52, 251–258 (2006).Article 

Google Scholar 
McKinnon, L. & Bêty, J. Effect of camera monitoring on survival rates of High-Arctic shorebird nests. J. Field Ornithol. 80, 280–288 (2009).Article 

Google Scholar 
Powell, L. A., Giovanni, M. D., Groepper, S. R., Reineke, M. & Schacht, W. H. Attendance Patterns and Survival of Western Meadowlark Nests (University of California Press, 2012).Book 

Google Scholar 
Herranz, J., Yanes, M. & Suárez, F. Does Photo-Monitoring Affect Nest Predation? J. Field Ornithol. 73, 97–101 (2002).Article 

Google Scholar 
Richardson, T. W., Gardali, T. & Jenkins, S. H. Review and meta-analysis of camera effects on avian nest success. J. Wildl. Manag. 73, 287–293 (2009).Article 

Google Scholar 
Cain, S. L. Nesting activity time budgets of Bald Eagles in southeast Alaska. (1985).García-Salgado, G. et al. Evaluation of trail-cameras for analyzing the diet of nesting raptors using the Northern Goshawk as a model. PLoS ONE 10, e0127585 (2015).Article 

Google Scholar 
Swann, D. E., Kawanishi, K. & Palmer, J. Evaluating types and features of camera traps in ecological studies: a guide for researchers. In Camera Traps in Animal Ecology 27–43 (Springer, 2011).Dykstra, C., Meyer, M. & Warnke, D. Bald Eagle reproductive performance following video camera placement. J. Raptor Res. 36, 136–139 (2002).
Google Scholar 
Del Moral, J. C. & Molina, B. El águila perdicera en España, población reproductora en 2018 y método de censo (SEO/BirdLife, 2018).
Google Scholar 
Generalitat Valenciana. Orden 2/2022, de 16 de febrero, de la Conselleria de Agricultura, Desarrollo Rural, Emergencia Climática y Transición Ecológica, por la que se actualizan los listados valencianos de especies protegidas de flora y fauna (2022).Real, J. & Mañosa, S. Demography and conservation of western European Bonelli’s eagle Hieraaetus fasciatus populations. Biol. Conserv. 79, 59–66 (1997).Article 

Google Scholar 
Hernández-Matías, A. et al. From local monitoring to a broad-scale viability assessment: A case study for the Bonelli’s Eagle in western Europe. Ecol. Monogr. 83, 239–261 (2013).Article 

Google Scholar 
Rollan, A. et al. Guiding local-scale management to improve the conservation of endangered populations: The example of Bonelli’s Eagle Aquila fasciata. Bird Conserv. Int. 31, 395–409 (2021).Article 

Google Scholar 
López-López, P., García-Ripollés, C. & Urios, V. Population size, breeding performance and territory quality of Bonelli’s Eagle Hieraaetus fasciatus in eastern Spain. Bird Study 54, 335–342 (2007).Article 

Google Scholar 
López-López, P. Informe científico valoración de la inclusión del águila perdicera como especie en peligro de extinción en el Catálogo Valenciano de Especies de Fauna Amenazadahttps://doi.org/10.13140/RG.2.2.32806.04166 (2021).López-López, P., Perona, A., Egea-Casas, O., Morant, J. & Urios, V. Tri-axial accelerometry shows differences in energy expenditure and parental effort throughout the breeding season in long-lived raptors. Curr. Zool. 68, 57–67 (2022).Article 

Google Scholar 
Perona, A. M., Urios, V. & López-López, P. Holidays? Not for all Eagles have larger home ranges on holidays as a consequence of human disturbance. Biol. Conserv. 231, 59–66 (2019).Article 

Google Scholar 
Morollón, S., Urios, V. & López-López, P. Fifteen days are enough to estimate home-range size in some long-lived resident eagles. J. Ornithol. 163, 849–854 (2022).Article 

Google Scholar 
Stewart-Oaten, A., Murdoch, W. W. & Parker, K. R. Environmental impact assessment:” Pseudoreplication” in time?. Ecology 67, 929–940 (1986).Article 

Google Scholar 
Underwood, A. Beyond BACI: The detection of environmental impacts on populations in the real, but variable, world. J. Exp. Mar. Biol. Ecol. 161, 145–178 (1992).Article 

Google Scholar 
López-López, P., García-Ripollés, C., García-López, F., Aguilar, J. M. & Verdejo, J. Patrón de distribución del águila real Aquila chrysaetos y del águila-azor perdicera Hieraaetus fasciatus en la provincia de Castellón. Ardeola 51, 275–283 (2004).
Google Scholar 
López-López, P., García-Ripollés, C., Aguilar, J. M., Garcia-López, F. & Verdejo, J. Modelling breeding habitat preferences of Bonelli’s eagle (Hieraaetus fasciatus) in relation to topography, disturbance, climate and land use at different spatial scales. J. Ornithol. 147, 97–106 (2006).Article 

Google Scholar 
Gil-Sánchez, J. Effects of altitude and prey availability on the laying date of Bonelli’s Eagles (Hieraaetus fasciatus) in Granada (SE Spain). Ardeola 47, 1–8 (2000).
Google Scholar 
Forsman, D. Flight Identification of Raptors of Europe, North Africa and the Middle East (Bloomsbury Publishing, 2016).
Google Scholar 
Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R Vol. 574 (Springer, 2009).Book 
MATH 

Google Scholar 
Harrison, X. A. et al. A brief introduction to mixed effects modelling and multi-model inference in ecology. PeerJ 6, e4794 (2018).Article 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9, 378–400 (2017).Article 

Google Scholar 
Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).Article 

Google Scholar 
Barton, K. MuMIn: Multi-Model Inference. R package version 1.46.0. (2022).Cutler, T. L. & Swann, D. E. Using remote photography in wildlife ecology: A review. Wildl. Soc. Bull. 27, 571–581 (1999).
Google Scholar 
Richardson, C. T. & Miller, C. K. Recommendations for protecting raptors from human disturbance: A review. Wildl. Soc. Bull. 25, 634–638 (1997).
Google Scholar 
Balbontin, J., Penteriani, V. & Ferrer, M. Variations in the age of mates as an early warning signal of changes in population trends? The case of Bonelli’s eagle in Andalusia. Biol. Conserv. 109, 417–423 (2003).Article 

Google Scholar 
Martinez, J. A. et al. Breeding performance, age effects and territory occupancy in a Bonelli’s eagle Hieraaetus fasciatus population. Ibis 150, 223–233 (2008).Article 

Google Scholar 
Sánchez-Zapata, J., Calvo, J., Carrete, M. & Martínez, J. Age and breeding success of a Golden Eagle Aquila chrysaetos population in southeastern Spain. Bird Study 47, 235–237 (2000).Article 

Google Scholar 
Ferrer, M., Penteriani, V., Balbontin, J. & Pandolfi, M. The proportion of immature breeders as a reliable early warning signal of population decline: Evidence from the Spanish imperial eagle in Donana. Biol. Conserv. 114, 463–466 (2003).Article 

Google Scholar 
Cano, A. & Parrinder, E. Studies of less familiar birds, Bonelli’s Eagle. Br. Birds 54, 422–427 (1961).
Google Scholar 
Blondel, J., Coulon, L., Girerd, B. & Hortigue, M. Deux cents heures d’observation aupre‘s de l’aire de l’Aigle de Bonelli Hieraaetus fasciatus. Nos Oiseaux 30, 37–60 (1969).
Google Scholar 
Vaucher, C. Notes sur 1’ethologie de I’Aigle de Bonelli. Nos Oiseaux 31, 101–111 (1971).
Google Scholar 
Elósegui, J. Informe preliminar sobre alimentación de aves rapaces en Navarra y provincias limítrofes. Ardeola 19, 249–256 (1974).
Google Scholar 
Cheylan, G. L. place trophique de l’Aigle de Bonelli Hieraaetus fasciatus dans les biocénoses méditerranéennes. Alauda 45, 1–15 (1977).
Google Scholar 
Palma, L., Cancela da Fonseca, L. & Oliveira, L. L’alimentation de l’aigle de Bonelli Hieraaetus fasciatus dans la coˆte portugaise. Rapinyaires Mediterranis 2, 87–96 (1984).
Google Scholar 
Real, J. Biases in diet study methods in the Bonelli’s eagle. J. Wildl. Manag. 60, 632–638 (1996).Article 

Google Scholar 
Gil-Sánchez, J. M., Molino, F., Valenzuela, G. & Moleón, M. Demografía y alimentación del Águila-azor Perdicera (Hieraaetus fasciatus) en la provincia de Granada. Ardeola 47, 69–75 (2000).
Google Scholar 
Ontiveros, D., Pleguezuelos, J. M. & Caro, J. Prey density, prey detectability and food habits: The case of Bonelli’s eagle and the conservation measures. Biol. Conserv. 123, 19–25 (2005).Article 

Google Scholar 
Moleón, M. et al. Large-scale spatio-temporal shifts in the diet of a predator mediated by an emerging infectious disease of its main prey. J. Biogeogr. 36, 1502–1515 (2009).Article 

Google Scholar 
Resano-Mayor, J. et al. Diet–demography relationships in a long-lived predator: From territories to populations. Oikos 125, 262–270 (2016).Article 

Google Scholar 
Di Vittorio, M. et al. Long-term changes in the breeding period diet of Bonelli’s eagle (Aquila fasciata) in Sicily, Italy. Wildl. Res. 46, 409–414 (2019).Article 

Google Scholar  More

IPCC Climate Change The physical science basis. In Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (eds Masson-Delmotte, V. et al.) (Cambridge University Press, 2021).
Google Scholar 
Doney, S. C. et al. Climate change impacts on marine ecosystems. Annu. Rev. Mar. Sci. 4, 11–37 (2012).Article 
ADS 

Google Scholar 
Song, H. et al. Thresholds of temperature change for mass extinctions. Nat. Commun. 12, 4694 (2021).Article 
ADS 
CAS 

Google Scholar 
Free, C. M. et al. Impacts of historical warming on marine fisheries production. Science 363, 979–983 (2019).Article 
ADS 
CAS 

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

Google Scholar 
Harley, C. D. G. et al. The impacts of climate change in coastal marine systems: Climate change in coastal marine systems. Ecol. Lett. 9, 228–241 (2006).Article 
ADS 

Google Scholar 
Dahlke, F. T., Wohlrab, S., Butzin, M. & Pörtner, H.-O. Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science 369, 65–70 (2020).Article 
ADS 
CAS 

Google Scholar 
Hodgson, E. E., Essington, T. E. & Kaplan, I. C. Extending vulnerability assessment to include life stages considerations. PLoS ONE 11, e0158917 (2016).Article 

Google Scholar 
Peck, M. A., Reglero, P., Takahashi, M. & Catalán, I. A. Life cycle ecophysiology of small pelagic fish and climate-driven changes in populations. Prog. Oceanogr. 116, 220–245 (2013).Article 
ADS 

Google Scholar 
Tsoukali, S., Visser, A. W. & MacKenzie, B. R. Functional responses of North Atlantic fish eggs to increasing temperature. Mar. Ecol. Prog. Ser. 555, 151–165 (2016).Article 
ADS 

Google Scholar 
Pörtner, H. O. & Peck, M. A. Climate change effects on fishes and fisheries: Towards a cause-and-effect understanding. J. Fish Biol. 77, 1745–1779 (2010).Article 

Google Scholar 
Pankhurst, N. W. & Munday, P. L. Effects of climate change on fish reproduction and early life history stages. Mar. Freshw. Res. 62, 1015–1026 (2011).Article 
CAS 

Google Scholar 
Brauner, C. J. Acid-base balance. In Fish Larval physiology (eds Finn, R. N. & Kapoor, B. G.) 185–198 (Science Publishers, 2008).
Google Scholar 
Dahlke, F. T. et al. Effects of ocean acidification increase embryonic sensitivity to thermal extremes in Atlantic cod, Gadus morhua. Glob. Chang. Biol. 23, 1499–1510 (2017).Article 
ADS 

Google Scholar 
Shelbourne, J. E. Significance of the subdermal space in pelagic fish embryos and larvae. Nature 176, 743–744 (1955).Article 
ADS 

Google Scholar 
Sundby, S. & Kristiansen, T. The principles of buoyancy in marine fish eggs and their vertical distributions across the world oceans. PLoS ONE 10, e0138821 (2015).Article 

Google Scholar 
Shei, M., Mies, M. & Olivotto, I. Other demersal spawners and mouthbrooders. Marine ornamental species aquaculture, 223–250 (2017).Beaudreau, A. H. The predatory role of lingcod (Ophiodon elongatus) in the San Juan Archipelago, Washington. (University of Washington, 2009).Love, M. Certainly More Than You Want to Know About the Fishes of the Pacific Coast: A Postmodern Experience. (Really Big Press, 2011).Pauly, D. & Christensen, V. Primary production required to sustain global fisheries. Nature 374, 255–257 (1995).Article 
ADS 
CAS 

Google Scholar 
Reum, J. C. et al. Interpretation and design of ocean acidification experiments in upwelling systems in the context of carbonate chemistry co-variation with temperature and oxygen. ICES J. Mar. Sci. 73, 582–595 (2016).Article 

Google Scholar 
Cheresh, J. & Fiechter, J. Physical and biogeochemical drivers of alongshore pH and oxygen variability in the California Current System. Geophys. Res. Lett. 47, e2020089553 (2020).Article 
ADS 

Google Scholar 
Gruber, N. et al. Rapid progression of ocean acidification in the California Current System. Science 337, 220–223 (2012).Article 
ADS 
CAS 

Google Scholar 
Hauri, C. et al. Spatiotemporal variability and long-term trends of ocean acidification in the California Current System. Biogeosciences 10, 193–216 (2013).Article 
ADS 

Google Scholar 
Pepin, P. Effect of temperature and size on development, mortality, and survival rates of the pelagic early life history stages of marine fish. Can. J. Fish. Aquat. Sci. 48, 503–518 (1991).Article 

Google Scholar 
Lauel, B. J. & Blood, D. M. The Effects of Temperature on Hatching and Survival of Northern Rock Sole Larvae (Lepidopsetta polyxystra) (Springer, 2011).
Google Scholar 
Guevara-Fletcher, C., Alvarez, P., Sanchez, J. & Iglesias, J. Effect of temperature on the development and mortality of European hake (Merluccius merluccius L.) eggs from southern stock under laboratory conditions. J. Exp. Mar. Biol. Ecol. 476, 50–57 (2016).Article 

Google Scholar 
Collins, L. A. & Nelson, S. G. Effects of temperature on oxygen consumption, growth, and development of embryos and yolk-sac larvae of Siganus randalli (Pisces: Siganidae). Mar. Biol. 117, 195–204 (1993).Article 

Google Scholar 
Cook, M. A., Guthrie, K. M., Rust, M. B. & Plesha, P. D. Effects of salinity and temperature during incubation on hatching and development of lingcod Ophiodon elongatus Girard, embryos. Aquac. Res. 36, 1298–1303 (2005).Article 

Google Scholar 
Pörtner, H. Integrating climate-related stressor effects on marine organisms: Unifying principles linking molecule to ecosystem-level changes. Mar. Ecol. Prog. Ser. 470, 273–290 (2012).Article 
ADS 

Google Scholar 
Laurel, B. J., Copeman, L. A., Spencer, M. & Iseri, P. Comparative effects of temperature on rates of development and survival of eggs and yolk-sac larvae of Arctic cod (Boreogadus saida) and walleye pollock (Gadus chalcogrammus). ICES J. Mar. Sci. 75, 2403–2412 (2018).Article 

Google Scholar 
Jordaan, A., Hayhurst, S. E. & Kling, L. J. The influence of temperature on the stage at hatch of laboratory reared Gadus morhua and implications for comparisons of length and morphology. J. Fish Biol. 68, 7–24 (2006).Article 

Google Scholar 
Peña, R., Dumas, S., Zavala-Leal, I. & Contreras-Olguín, M. Effect of incubation temperature on the embryonic development and yolk-sac larvae of the Pacific red snapper Lutjanus peru (Nichols & Murphy, 1922). Aquac Res 45, 519–527 (2014).Article 

Google Scholar 
Breitburg, D. Effects of hypoxia, and the balance between hypoxia and enrichment, on coastal fishes and fisheries. Estuaries 25, 767–781 (2002).Article 

Google Scholar 
Hassell, K. L., Coutin, P. C. & Nugegoda, D. Hypoxia impairs embryo development and survival in black bream (Acanthopagrus butcheri). Mar. Pollut. Bull. 57, 302–306 (2008).Article 
CAS 

Google Scholar 
Giorgi, A. E. The Environmental Biology of the Embryos, Egg Masses and Nesting Sites of the Lingcod, Ophiodon elongatus. (University of Washington, 1981).Oseid, D. M. & Smith, L. L. Survival and hatching of walleye eggs at various dissolved oxygen levels. Progress. Fish-Cult. 33, 81–85 (1971).Article 
CAS 

Google Scholar 
Shumway, D. L., Warren, C. E. & Doudoroff, P. Influence of oxygen concentration and water movement on the growth of steelhead trout and coho salmon embryos. Trans. Am. Fish. Soc. 93, 342–356 (1964).Article 

Google Scholar 
Baumann, H., Talmage, S. C. & Gobler, C. J. Reduced early life growth and survival in a fish in direct response to increased carbon dioxide. Nat. Clim Change 2, 38–41 (2012).Article 
ADS 
CAS 

Google Scholar 
Faria, A. M. et al. Effects of high pCO2 on early life development of pelagic spawning marine fish. Mar. Freshw. Res. 68, 2106–2114 (2017).Article 
CAS 

Google Scholar 
Frommel, A. Y. et al. Severe tissue damage in Atlantic cod larvae under increasing ocean acidification. Nat. Clim. Change 2, 42–46 (2012).Article 
ADS 
CAS 

Google Scholar 
Munday, P. L. et al. Effects of elevated CO2 on early life history development of the yellowtail kingfish, Seriola lalandi, a large pelagic fish. ICES J. Mar. Sci. 73, 641–649 (2016).Article 

Google Scholar 
Hurst, T. P., Fernandez, E. R. & Mathis, J. T. Effects of ocean acidification on hatch size and larval growth of walleye pollock (Theragra chalcogramma). ICES J. Mar. Sci. 70, 812–822 (2013).Article 

Google Scholar 
Wang, X., Song, L., Chen, Y., Ran, H. & Song, J. Impact of ocean acidification on the early development and escape behavior of marine medaka (Oryzias melastigma). Mar. Environ. Res. 131, 10–18 (2017).Article 

Google Scholar 
Franke, A. & Clemmesen, C. Effect of ocean acidification on early life stages of Atlantic herring (Clupea harengus L.). Biogeosciences 8, 3697–3707 (2011).Article 
ADS 
CAS 

Google Scholar 
Forsgren, E., Dupont, S., Jutfelt, F. & Amundsen, T. Elevated CO 2 affects embryonic development and larval phototaxis in a temperate marine fish. Ecol. Evol. 3, 3637–3646 (2013).Article 

Google Scholar 
Bromhead, D. et al. The potential impact of ocean acidification upon eggs and larvae of yellowfin tuna (Thunnus albacares). Deep Sea Res. II 113, 268–279 (2015).Article 
CAS 

Google Scholar 
Garrido, S. et al. Born small, die young: Intrinsic, size-selective mortality in marine larval fish. Sci. Rep. 5, 17065 (2015).Article 
ADS 
CAS 

Google Scholar 
Sampaio, E. et al. Impacts of hypoxic events surpass those of future ocean warming and acidification. Nat. Ecol. Evol. 5, 311–321 (2021).Article 

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

Google Scholar 
Pörtner, H. O. Synergistic effects of temperature extremes, hypoxia, and increases in CO2 on marine animals: From Earth history to global change. J. Geophys. Res. 110, 0910 (2005).Article 

Google Scholar 
Piggott, J. J., Townsend, C. R. & Matthaei, C. D. Reconceptualizing synergism and antagonism among multiple stressors. Ecol. Evol. 5, 1538–1547 (2015).Article 

Google Scholar 
Boyd, P. W. et al. Experimental strategies to assess the biological ramifications of multiple drivers of global ocean change: A review. Glob. Change Biol 24, 2239–2261 (2018).Article 
ADS 

Google Scholar 
Giorgi, A. E. & Congleton, J. L. Effects of current velocity on development and survival of lingcod, Ophiodon elongatus, embryos. Environ. Biol. Fish 10, 15–27 (1984).Article 

Google Scholar 
Liu, G., Zhu, S., Liu, D. & Ye, Z. Effect of the C/N ratio on inorganic nitrogen control and the growth and physiological parameters of tilapia s fingerlings, Oreochromis niloticu reared in biofloc systems. Aquac. Res. 49, 2429–2439 (2018).Article 
CAS 

Google Scholar 
Houde, E. D. Fish early life dynamics and recruitment variability. Am. Fish. Soc. Symp. 2, 17–29 (1987).ADS 

Google Scholar 
Miller, T. J., Crowder, L. B., Rice, J. A. & Marschall, E. A. Larval size and recruitment mechanisms in fishes: Toward a conceptual framework. Can. J. Fish. Aquat. Sci. 45, 1657–1670 (1988).Article 

Google Scholar 
Doi, H., Akamatsu, F. & González, A. L. Starvation effects on nitrogen and carbon stable isotopes of animals: An insight from meta-analysis of fasting experiments. R. Soc. open sci. 4, 170633 (2017).Article 
ADS 

Google Scholar 
Pimentel, M. S. et al. Defective skeletogenesis and oversized otoliths in fish early stages in a changing ocean. J. Exp. Biol. 1, 092635. https://doi.org/10.1242/jeb.092635 (2014).Article 

Google Scholar 
Politis, S. N., Dahlke, F. T., Butts, I. A., Peck, M. A. & Trippel, E. A. Temperature, paternity and asynchronous hatching influence early developmental characteristics of larval Atlantic cod, Gadus morhua. J. Exp. Mar. Biol. Ecol. 459, 70–79 (2014).Article 

Google Scholar 
Appelbaum, S. et al. Studies on rearing of lingcod Ophiodon elongatus. Aquaculture 135, 219–227 (1995).Article 

Google Scholar 
Hempel, G. Early life history of marine fish: The egg stage. Washington Sea Grant. (University of Washington Press, 1979)Gadomski, D. M. & Caddell, S. M. Effects of temperature on the development and survival of eggs of four coastal California fishes. Fish. Bull. 94, 41–48 (1996).
Google Scholar 
Parker, L. M. et al. Adult exposure influences offspring response to ocean acidification in oysters. Glob. Change Biol. 18, 82–92 (2012).Article 
ADS 

Google Scholar 
Rombough, P. The effects of temperature on embryonic and larval development. In Global Warming: Implications for Freshwater and Marine Fish (Society for Experimental Biology Seminar Series) (eds Wood, C. & McDonald, D.) 177–224 (Cambridge University Press, 1997).Chapter 

Google Scholar 
Bownds, C., Wilson, R. & Marshall, D. J. Why do colder mothers produce larger eggs? An optimality approach. J. Exp. Biol. 213, 3796–3801 (2010).Article 

Google Scholar 
Longo, G. C. et al. Strong population differentiation in lingcod ( Ophiodon elongatus ) is driven by a small portion of the genome. Evol. Appl. 13, 2536–2554 (2020).Article 
CAS 

Google Scholar 
Silberberg, K. R., Laidig, T. E., Adams, P. B. & Albin, D. Analysis of maturity in lingcod, Ophiodon elongatus. California Fish Game 87, 139–152 (2001).
Google Scholar 
Palumbi, S. R. Why mothers matter. Nature 430, 621–622 (2004).Article 
ADS 
CAS 

Google Scholar 
Berkeley, S. A., Chapman, C. & Sogard, S. M. Maternal age as a determinant of larval growth and survival in a marine fish, Sebastes melanops. Ecology 85, 1258–1264 (2004).Article 

Google Scholar 
Miller, D. J., & Geibel, J. J. Summary of Blue Rockfish and Lingcod Life Histories, a Reef Ecology Study, and Giant Kelp, Macrocystis Pyrifera, Experiments in Monterey Bay, California. (State of California, Resources Agency, Department of Fish and Game, 1973).Low, C. J. & Beamish, R. J. A study of the nesting behavior of lingcod (Ophiodon elongatus) in the strait of Georgia, British Columbia. Can. Fish. Mar. Serv. Tech. Rep. 843, 1–10 (1978).
Google Scholar 
King, J. R. & Withler, R. E. Male nest site fidelity and female serial polyandry in lingcod (Ophiodon elongatus, Hexagrammidae): Lingcod nest site fidelity. Mol. Ecol. 14, 653–660 (2005).Article 

Google Scholar 
Withler, R. E. et al. Polygamous mating and high levels of genetic variation in lingcod, Ophiodon elongatus of the Strait of Georgia, British Columbia. In Genetics of Subpolar Fish and Invertebrates 345–357 (Springer, 2004).
Google Scholar 
Perkins, M. J. et al. Application of nitrogen and carbon stable isotopes (δ15N and δ13C) to quantify food chain length and trophic structure. PLoS ONE 9, e93281 (2014).Article 
ADS 

Google Scholar 
Earth Systems Research Laboratory (ESRL). NOAA’s Ocean Climate Change Web Portal. http://www.esrl.noaa.gov/psd/ipcc/ocn/ (2019).Feely, R., Doney, S. & Cooley, S. Ocean acidification: Present conditions and future changes in a high-CO2 world. Oceanography 22, 36–47 (2009).Article 

Google Scholar 
Frieder, C. A., Nam, S. H., Martz, T. R. & Levin, L. A. High temporal and spatial variability of dissolved oxygen and pH in a nearshore California kelp forest. Biogeosciences 9, 3917–3930 (2012).Article 
ADS 
CAS 

Google Scholar 
Olito, C., White, C. R., Marshall, D. J. & Barneche, D. R. Estimating monotonic rates from biological data using local linear regression. J. Exp. Biol. 1, 148775. https://doi.org/10.1242/jeb.148775 (2017).Article 

Google Scholar 
Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R J. 9(2), 378–400 (2017).Article 

Google Scholar  More

Soil studies were carried out on 115,896.2 hectares of agricultural lands in fifteen villages of the municipal district obtained by subtracting from the available area of the village industrial lands, populated areas, forest plots occupied by water, etc.As a result of the land reform and redistribution of land for various purposes for the period from 1972 to 2021, the area of agricultural land decreased by 12.7% compared to the data of the previous survey.In the research area, the largest territories are occupied by black soils, which amount to 52,826.24 ha, including bleached soils—42,605.9 ha, alkaline – 6983.8 ha and shortened – 3236.54 ha. Slightly inferior to the black soils are dark gray forest soils with an area of 37,043.63 hectares, alluvial—12,287.4 hectares, gray forest—6371.96 hectares and forest soils of a rooted profile – 5058.94 hectares. The share of sod-carbonate soils accounts for 7792.7 hectares of land, which is 6.2%. The gradation did not include the soils of the ravine-beam complex, sand and gravel masses, existing ravines and disturbed lands, and quarries that occupy 5,452.4 hectares of territory (4.3%).One of the important indicators of soils, especially used in agricultural production, is the humus state. Thus, over 49 years there has been a slight decrease in the area under obese (high-humus) soils in the hectare ratio, due to a general decrease in the area of farmland, but in the context of the security group, they have increased by 1.3% (Table 1). The remaining levels of security have remained almost at the same level. The increase in the amount of fat chernozems was facilitated by the withdrawal of arable land from circulation and their transfer to perennial plantations. Earlier researches conducted on experimental fields of the Bashkir State Agrarian University identified and revealed changes in the quantitative and qualitative composition of organic matter from 15 to 30% when introducing a land plot for arable land26. To preserve and improve soil fertility, it is recommended to carry out a complex of agrotechnical, agrochemical and reclamation measures and the use of various meliorants, organic and mineral fertilizers27.Studies of the capacity of the humus horizon have shown that low–sized soils have become the most widespread—69,660.2 hectares or 60.1% of the total area of agricultural land (Fig. 2). A smaller area is occupied by medium-sized soils – 38,128.7 hectares (32.9%), not included in the gradation – 8107.3 hectares or 7.0%, respectively. It should be noted that the specific gravity of the soil of the ravine-beam complex, sand and gravel masses, active ravines and disturbed lands, and quarries increased by 2.5%.Figure 2Distribution of soils by humus horizon thickness by region.Full size imageThe granulometric composition of the soil is also of great agronomic importance28. Physical, physico-chemical, physico-mechanical properties and water, air, and nutrient regimes of soils depend on it29,30. In the Salavatskiy district there were practically no changes in soil areas in terms of granulometric composition, mainly clay soil varieties predominate. According to the mechanical composition of the soil there were distributed as follows: light clay – 71,807.38 ha or 62% (in 1972, 86,375 ha or 65.1%) of the total area of agricultural land and heavy loamy – 34,745.24 ha (30%) (in 1972—39,614 ha or 29.8%). The share of medium-loamy varieties accounts for 0.8% (in 1972—0.84%) (Fig. 3).Figure 3Distribution of Salavatskiy district soil areas by granulometric composition, %.Full size imageThe gradation did not include 8362.27 hectares of land. Heavy loamy, medium clay, sandy loam and sandy soils have not been identified.All arable soils of the analyzed territory are slightly susceptible to erosion processes, the processes of water and, to a lesser extent, wind erosion have developed. 67,445.21 hectares of land, or 58.2% (in 1972, 77,702 hectares) of the total area of agricultural lands are occupied under lightly washed soils, the share of medium and heavily washed accounts for 3.9% and 0.1%, respectively. Unwashed soils are distributed on 36,985.46 hectares (31.9%) (Table 2).Table 2 Soil areas by category of erosion feature (Salavatskiy district of the Republic of Bashkortostan).Full size tableAccording to the results of the field research and laboratory agrochemical analyses of soils, land refinements related to agricultural land were carried out. The basis for correcting and digitizing the contours of soil varieties were in the maps made in 1972 (Fig. 4).Figure 4Soil map within the boundaries of the Salavatskiy district of the Republic of Bashkortostan, 1972.Full size imageDigitization included scanning the topographic basis, then assigning coordinates to a raster image, decrypting and digitizing orthophotos (Fig. 5).Figure 5Orthophotoplan within the boundaries of the Salavatskiy district of the Republic of Bashkortostan, 2007.Full size imageAfter the carried-out activities, a soil map was obtained in the digital format of the Mapinfo program, after which it was converted into a raster basis with reference to the local coordinate system MSK 02 zone 1. The digitization of the 1972 soil map was carried out manually by outlining the contours of the topographic base and the scanned map.During digitization, information partially lost due to its wear and distortion during scanning was restored. A necessary condition is the use of the originals of the soil maps of the previous survey (1972).As a planned basis on which the created layers can be opened and information on soils can be obtained, a raster basis was ordinated into a local coordinate system (Fig. 6).Figure 6Completed soil map within the boundaries of the Salavat district of the Republic of Belarus, 2021.Full size imageThe result of the conducted research is the developed electronic digital soil map of the municipal district of Salavatskiy district which unites 15 rural settlements. The electronic soil map is presented in the form of a complex of electronic layers with the names of the type and subtype of soils, soil variety, mechanical or granulometric composition, soil-forming and underlying rocks. It also includes indicators of organic carbon, humus, mobile phosphorus, exchangeable potassium, soil acidity by pH value and the capacity of the humus-accumulative horizon. More

Direct injection method for ethylene and acetylene δ13C analyses by GC-C-IRMSFollowing the direct injection approach of classical ISARA12 with a few modifications, ARA samples with high ethylene yield ( > 500 ppmv) in 10% v/v acetylene were manually injected into a Thermo Scientific Trace GC Ultra-Isolink with an Agilent HP-PLOT/Q  capillary GC column (30 m, i.d. = 0.32 mm, f.t. = 20 μm) and a combustion reactor connected to a Thermo Scientific Delta V Plus isotope ratio mass spectrometer (GC-C-IRMS; Fig. 1a). Modifications include the replacement of silver ferrules in the GC oven with Valcon polymide (graphite reinforced polymer) ferrules to limit memory effects from acetylene. The combustion reactor was oxidized with pure oxygen for 1 h before each run and brief (15 min) seed oxidations were performed between measurement batches (i.e., required every ~ 6–8 ethylene injections, ~ 4–6 acetylene injections) to regenerate reactor oxidation capacity and minimize drift of δ13C values. See Supplementary Table S1a online for additional instrument settings.Ethylene Pre-Concentration (EPCon) methodARA samples with  More

Thermal requirements to develop PDWe examined the response of a wide spectrum of European grapevine varieties to XfPD infection in three independent experiments conducted in 2018, 2019, and 2020. Overall, 86.1% (n = 764) of 886 inoculated plants, comprising 36 varieties and 57 unique scion/rootstock combinations, developed PD symptoms 16 weeks after inoculation. European V. vinifera varieties exhibited significant differences in their susceptibility to XfPD (Supplementary Table S1). All varieties, however, showed PD symptoms to some extent, confirming previous field observations of general susceptibility to XfPD9,12,37. We also found significant differences in virulence (χ2 = 68.73, df = 1, P = 2.2 × 10−16) between two XfPD strains isolated from grapevines in Majorca across grapevine varieties (Supplementary Fig. S1). Full details on the results of the inoculation tests are available in “Methods”, Supplementary Note 1, Supplementary Table S1 and Supplementary Data 1.Growing degree days (GDD) have traditionally been used to describe and predict phenological events of plants and insect pests, but rarely in plant diseases58. We took advantage of data collated in the inoculation trials together with temperature to relate symptom development to the accumulated heat units at weeks eight, 10, 12, 14, and 16 after inoculation (Supplementary Data 1). Rather than counting GDDs linearly above a threshold temperature, we consider Xf ’s specific growth rate in vitro within its cardinal temperatures. The empirical growth rates come from the seminal work by Feil & Purcell38 shown in the inset of Fig. 1a. This Arrhenius plot was transformed, as explained in Supplementary Note 2A, to obtain a a piece-wise function f(T) Eq. (1). Our model and risk maps are based on f(T) (red line in Fig. 1a) because it provides the best fit to the experimental data when compared with the commonly used Beta function (blue line) for representing the thermal response in biological processes59,60. This Modified Growing Degree Day (MGDD) profile Eq. (1) enables to measure the thermal integral from hourly average temperatures, improving the prediction scale of the biological process61. MGDD also provides an excellent metric to link XfPD growth in culture with PD development as, once the pathogen is injected into the healthy vine, symptoms progression mainly depends upon the bacterial load (i.e., multiplication) and the movement through the xylem vessel network, which are fundamentally temperature-dependent processes38,62. Moreover, MGDD can be mathematically related to the exponential or logistic growth of the pathogen within the plant (Supplementary Note 2B).Fig. 1: Climatic and transmission layers composing the epidemiological model.a MGDD profile fitted to the in vitro data of Xf growth rate in Feil & Purcell 200138. The original Arrhenius plot in Kelvin degrees (inset) was converted to Celsius, as explained in (Supplementary Note 2A), to obtain the fit shown in the main plot red line; the blue line represents the fit with a Beta function. b Correlation between CDD and the average ({T}_{min }) of the coldest month between 1981 and 2019. Plotted black dots (worldwide) and yellow dots (main wine-producing zones) depict climatic data from 6,487,200 cells at 0.1∘ × 0.1∘ resolution, spread globally and retrieved from ERA5-Land dataset. The red solid line depicts the fitted exponential function for worldwide data and the blue solid line for main vineyard zones. c Nonlinear relationship between MGDD (red line) and CDD (blue line) and the likelihood of developing chronic infections. Black dots depict the cumulative proportion of grapevine plants in the population of 36 inoculated varieties showing five or more symptomatic leaves at each of the 15 MGDD levels (see Supplementary Information). Vertical bars are the 95% CI. d Combined ranges of MGDD and CDD on the likelihood of developing chronic infection. e Transmission layer in the dynamic equation (1) of the SIR compartmental model. f Relationship between the exponential growth of the number of infected plants with the risk index and their ranks.Full size imageInterannual infection survival in grapevines plays a relevant role when modelling PD epidemiology. In our model, we assumed a threshold of five or more symptomatic leaves for these chronic infections based on the relationship between the timing and severity of the infection during the growing season and the likelihood of winter recovery38,39,42. This five-leaf cut-off was grounded on: (i) the bimodal distribution in the frequency of the number of symptomatic leaves among the population of inoculated grapevines (Supplementary Fig. S1), whereby vines that generally show less than five symptomatic leaves at 12 weeks after inoculation remain so in the following weeks, while those that pass that threshold continue to produce symptomatic leaves, and (ii) the observed correlation between the acropetal and basipetal movement of Xf along the cane (Supplementary Fig. S1). The likelihood of developing chronic infections as a function of accumulated MGDD among the population of grapevine varieties was modelled using survival analysis with data fitted to a logistic distribution ({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}})). A minimum window of MGDD = 528 was needed to develop chronic infections (var. Tempranillo), about 975 for a median estimate, while a cumulative MGDD  > 1159 indicate over 90% probability within a growing season (red curve in Fig. 1c and “Methods”).Next, we intended to model the probability of disease recovery by exposure to cold temperatures. Previous works had specifically modelled cold curing on Pinot Noir and Cabernet Sauvignon varieties in California as the effect of temperature and duration39 by assuming a progressive elimination of the bacterial load with cold temperatures42. In the absence of appropriate empirical data to formulate a general average pattern of winter curing among grapevine varieties, we combined the approach of Lieth et al.39 and the empirical observations of Purcell on the distribution of PD in the US related to the average minimum temperature of the coldest month, Tmin, isolines41. To consider the accumulation of cold units in an analogy of the MGDD, we searched for a general correlation between Tmin and the cold degree days (CDDs) with base temperature = 6 ∘C (see “Methods”). We found an exponential relation, ({{{{{rm{CDD}}}}}} sim 230exp (-0.26cdot {T}_{min })), where specifically, CDD ≳ 306 correspond to ({T}_{min } < -1.{1},^{circ }{{{{{rm{C}}}}}}) (Fig. 1b). To transform this exponential relationship to a probabilistic function analogous to ({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}})), hereafter denoted ({{{{{{{mathcal{G}}}}}}}}({{{{{rm{CDD}}}}}})), ranging between 0 and 1, we considered the sigmoidal family of functions (f(x)=frac{A}{B+{x}^{C}}) with A = 9 × 106, B = A and C = 3 (Fig. 1c), fulfilling the limit ({{{{{{{mathcal{G}}}}}}}}({{{{{rm{CDD}}}}}}=0)=1), i.e., no winter curing when no cold accumulated, and a conservative 75% of the infected plants recovered at ({T}_{min }=-1.{1},^{circ }{{{{{rm{C}}}}}}) instead of 100% to reflect uncertainties on the effect of winter curing.MGDD/CDD distribution mapsMGDD were used to compute annual risk maps of developing PD during summer for the period 1981–2019 (see “Methods”). The resulting averaged map identifies all known areas with a recent history of severe PD in the US corresponding to ({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}}) , > , 90 %) (i.e., high-risk), such as the Gulf Coast states (Texas, Alabama, Mississippi, Louisiana, Florida), Georgia and Southern California sites (e.g., Temecula Valley) (Fig. 2a), while captures areas with a steep gradation of disease endemicity in the north coast of California (({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}} , > , 50 % )). Overall, more than 95% of confirmed PD sites (n = 155) in the US (Supplementary Data 2) fall in grid cells with ({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}}) , > , 50 %).Fig. 2: Average thermal-dependent maps for Pierce’s disease (PD) development and recovery in North America and Europe.PD development during the growing season based on average ({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}})) estimations between 1981 and 2019 in North America (a) and Europe (b) derived from the results of the inoculation experiments on 36 grapevine varieties. Large differences in the areal extension with favourable MGDDs can be observed between the US and Europe. The winter curing effect is reflected in the distribution of the average ({{{{{{{mathcal{G}}}}}}}}({{{{{rm{CDD}}}}}})) for the 1981–2019 period in the United States (c) and Europe (d). A snapshot of the temperature-driven probability of chronic infection averaged for the 1981–2019 period is obtained from the joint effect of MGDD and CDD in North America (e) and Europe (f). Warmer colours indicate more favourable conditions for chronic PD and the dashed line highlights the threshold of chronic infection probability being 0.5.Full size imageThe average MGDD-projected map for Europe during 1981–2019 spots a high risk for the coast, islands and major river valleys of the Mediterranean Basin, southern Spain, the Atlantic coast from Gibraltar to Oporto, and continental areas of central and southeast Europe (Fig. 2b). Of these, however, only some Mediterranean islands, such as Cyprus and Crete, show ({{{{{{{mathcal{F}}}}}}}}({{{{{rm{MGDD}}}}}}) , > , 99 %) comparable to areas with high disease incidence in the Gulf Coast states of the US and California. Almost all the Atlantic coast from Oporto (Portugal) to Denmark are below suitable MGDD, with an important exception in the Garonne river basin in France (Bordeaux Area) with low to moderate MGDD (Fig. 2b).Figure 2a shows how the area with high-risk MGDD values extends further north of the current known PD distribution in the southeastern US, suggesting that winter temperatures limit the expansion of PD northwards9. A comparison between MGDD and CDD maps (Fig. 2a vs. Fig. 2c, Fig. 2e) further supports the idea that winter curing is restricting PD northward migration from the southeastern US. However, consistent with growing concern among Midwest states winegrowers on PD northward migration led by climate change63, we found a mean increase of 0.12% y−1 in the areal extent with CDD  0.075) in 22.3% of the vineyards in Europe. However, no vineyard is in epidemic-risk zones with a high-risk index and only 2.9% of the vineyard surface is at moderate risk (Supplementary Table S8). The areas with the highest risk index (r(t) between 0.70 and 0.88) are mainly located in the Mediterranean islands of Crete, Cyprus and the Balearic Islands or at pronounced peninsulas like Apulia (Italy) and Peloponnese (Greece) in the continent (Fig. 6a and Supplementary Table S8). Most vineyards are in non-risk zones (42.1%), whereas 35.6% are located in transition zones with presently non-risk but where XfPD could become established in the next decades causing some sporadic outbreaks. In Supplementary Data 4 and Supplementary Table S8, we provide full details of the total vineyard areas currently at risk for each country and region.Fig. 6: Intersection between Corine-land-cover vineyard distribution map and PD-risk maps for 2020 and 2050.Data were obtained from Corine-land-cover (2018) and the layer of climatic suitability forP. spumarius in Europe from35. The surface of the vineyard contour has been enlarged to improve the visualisation of the risk zones and disease-incidence growth-rate ranks. a PD risk map for 2019 and its projection for 2050 (b). Blue colours represent non-risk zones and transient risk zones for chronic PD (R0  More

Asevedo, L. et al. Palynological analysis of dental calculus from Pleistocene proboscideans of southern Brazil: a new approach for paleodiet and paleoenvironmental reconstructions. Palaeogeogr. Palaeoclimatol. Palaeoecol. 540, 109523 (2020).Article 

Google Scholar 
Cristiani, E. et al. Wild cereal grain consumption among Early Holocene foragers of the Balkans predates the arrival of agriculture. Elife 10, e72976 (2021).Article 
CAS 

Google Scholar 
Nava, A. et al. Multipronged dental analyses reveal dietary differences in last foragers and first farmers at Grotta Continenza, central Italy (15,500–7000 BP). Sci. Rep. 11, 1–14 (2021).Article 

Google Scholar 
Ottoni, C. et al. Tracking the transition to agriculture in Southern Europe through ancient DNA analysis of dental calculus. Proc. Natl. Acad. Sci. USA 118, e2102116118 (2021).Article 
CAS 

Google Scholar 
Cammidge, T. S., Kooyman, B. & Theodor, J. M. Diet reconstructions for end-Pleistocene Mammut americanum and Mammuthus based on comparative analysis of mesowear, microwear, and dental calculus in modern Loxodonta africana. Palaeogeogr. Palaeoclimatol. Palaeoecol. 538, 109403 (2020).Article 

Google Scholar 
de Oliveira, K. et al. From oral pathology to feeding ecology: the first dental calculus paleodiet study of a South American native megamammal. J. S. Am. Earth Sci. 109, 103281 (2021).Article 

Google Scholar 
Mothé, D. et al. The micro from mega: dental calculus description and the first record of fossilized oral bacteria from an extinct proboscidean. Int. J. Paleopathol. 33, 55–60 (2021).Article 

Google Scholar 
Eglinton, G. & Logan, G. A. Molecular preservation. Philosophical Transactions of the Royal Society of London. Philos. Trans. R. Soc. Lond., B, Biol. Sci. 333, 315–328 (1991).CAS 

Google Scholar 
Romanowski, G., Lorenz, M. G. & Wackernagel, W. Adsorption of plasmid DNA to mineral surfaces and protection against Dnase I. Appl. Environ. Microbiol. 57, 1057–1061 (1991).Article 
CAS 

Google Scholar 
Milanesi, C. et al. Ultrastructural study of archaeological Vitis vinifera L. seeds using rapid-freeze fixation and substitution. Tissue Cell 41, 443–447 (2009).Article 
CAS 

Google Scholar 
Power, R. C., Salazar-García, D. C., Wittig, R. M., Freiberg, M., & Henry, A. G. Dental calculus evidence of Taï Forest chimpanzee plant consumption and life history transitions. Sci. Rep. 5, 15161 (2015).Goude, G. et al. A multidisciplinary approach to Neolithic life reconstruction. J. Archaeol. Method Theory 26, 537–560 (2019).Article 

Google Scholar 
Farrer, A. G. et al. Effectiveness of decontamination protocols when analyzing ancient DNA preserved in dental calculus. Sci. Rep. 11, 1–14 (2021).Article 

Google Scholar 
Weyrich, L. S., Dobney, K. & Cooper, A. Ancient DNA analysis of dental calculus. J. Hum. Evol. 79, 119–124 (2015).Article 

Google Scholar 
Ozga, A. T. et al. Successful enrichment and recovery of whole mitochondrial genomes from ancient human dental calculus. Am. J. Phys. Anthropol. 160, 220–228 (2016).Article 

Google Scholar 
Mann, A. E. et al. Do I have something in my teeth? The trouble with genetic analyses of diet from archaeological dental calculus. Quat. Int. https://doi.org/10.1016/j.quaint.2020.11.019 (2020).Wright, S. L., Dobney, K. & Weyrich, L. S. Advancing and refining archaeological dental calculus research using multiomic frameworks. Sci. Technol. Archaeol. Res. 7, 13–30 (2021).
Google Scholar 
Sawafuji, R., Saso, A., Suda, W., Hattori, M. & Ueda, S. Ancient DNA analysis of food remains in human dental calculus from the Edo period, Japan. PLoS One 15, e0226654 (2020).Article 
CAS 

Google Scholar 
Weyrich, L. S. et al. Neanderthal behaviour, diet, and disease inferred from ancient DNA in dental calculus. Nature 544, 357–361 (2017).Article 
CAS 

Google Scholar 
Ottoni, C. et al. Metagenomic analysis of dental calculus in ancient Egyptian baboons. Sci. Rep. 9, 1–10 (2019).Article 

Google Scholar 
Hollingsworth, P. M., Graham, S. W. & Little, D. P. Choosing and using a Plant DNA barcode. PLoS One 6, 1–13 (2011).Article 

Google Scholar 
Gismondi, A., Fanali, F., Labarga, J. M. M., Caiola, M. G. & Canini, A. Crocus sativus L. genomics and different DNA barcode applications. Plant Syst. Evol. 299, 1859–1863 (2013).Article 
CAS 

Google Scholar 
ICSN. The international code for starch nomenclature, accessed 15 September 2021; http://fossilfarm.org/ICSN/Code.html (2011).Gismondi, A. et al. Starch granules: a data collection of 40 food species. Plant Biosyst. 153, 273–279 (2019).Article 

Google Scholar 
Henry, A. G., Brooks, A. S. & Piperno, D. R. Plant foods and the dietary ecology of Neanderthals and early modern humans. J. Hum. Evol. 69, 44–54 (2014).Article 

Google Scholar 
PalDat. A palynological database (2000 onwards), accessed 19 January 2022; https://www.paldat.org/ (2019).Berglund, B. E. & Ralska-Jasiewiczowa, M. Pollen analysis and pollen diagrams. In Handbook of Holocene Palaeoecology and Palaeohydrology (ed. Berglund, B. E.) 455–484 (Wiley, 1986).Faegri, K. & Iversen, J. Textbook of Pollen analysis, 4th edn (eds Faegri, K. et al.) (John Wiley and Sons-Chichester, 1989).Grímsson, F. et al. Fagaceae pollen from the early Cenozoic of West Greenland: revisiting Engler’s and Chaney’s Arcto-Tertiary hypotheses. Plant Syst. Evol. 301, 809–832 (2015).Article 

Google Scholar 
Denk, T. & Tekleva, M. V. Pollen morphology and ultrastructure of Quercus with focus on Group Ilex (= Quercus Subgenus Heterobalanus (Oerst.) Menitsky): Implications for oak systematics and evolution. Grana 53, 255–282 (2014).Article 

Google Scholar 
Grímsson, F. & Zetter, R. Combined LM and SEM study of the middle Miocene (Sarmatian) palynofora from the Lavanttal Basin, Austria: Part II. Pinophyta (Cupressaceae, Pinaceae and Sciadopityaceae). Grana 50, 262–310 (2011).Article 

Google Scholar 
Mohanty, R. P., Buchheim, M. A., Portman, R. & Levetin, E. Molecular and ultrastructural detection of plastids in Juniperus (Cupressaceae) pollen. Phytologia 98, 298–310 (2016).
Google Scholar 
Martin, A. C. & Harvey, W. J. The Global Pollen Project: a new tool for pollen identifcation and the dissemination of physical reference collections. Methods Ecol. Evol. 8, 892–897 (2017).Article 

Google Scholar 
Maciejewska-Rutkowska, I., Bocianowski, J. & Wrońska-Pilarek, D. Pollen morphology and variability of Polish native species from genus Salix L. PLoS One 16, e0243993 (2021).Article 
CAS 

Google Scholar 
Abreu, I., Costa, I., Oliveira, M., Cunha, M. & De Castro, R. Ultrastructure and germination of Vitis vinifera cv. Loureiro pollen. Protoplasma 228, 131–135 (2006).Article 
CAS 

Google Scholar 
Nagels, A. et al. Palynological diversity and major evolutionary trends in Cyperaceae. Plant Syst. Evol. 277, 117 (2009).Article 

Google Scholar 
El Ghazali, G. E. Pollen morphological studies in Amaranthaceae s. lat. (incl. Chenopodiaceae) and their taxonomic significance: a review. Grana 61, 1–7 (2022).Article 

Google Scholar 
Petraco, N., & Kubic, T. Color Atlas and Manual of Microscopy for Criminalists, Chemists, and Conservators (Boca Raton-CRC Press, 2003).D’Agostino, A. et al. Environmental implications and evidence of natural products from dental calculi of a Neolithic–Chalcolithic community (central Italy). Sci. Rep. 11, 1–13 (2021).Article 

Google Scholar 
Frangiote-Pallone, S. & de Souza, L. A. Pappus and cypsela ontogeny in Asteraceae: structural considerations of the tribal category. Rev. Mex. Biodivers. 85, 62–77 (2014).Article 

Google Scholar 
Eglinton, G., Gonzalez, A. G., Hamilton, R. J. & Raphael, R. A. Hydrocarbon constituents of the wax coatings of plant leaves: a taxonomic survey. Phytochemistry 1, 89–102 (1962).Article 
CAS 

Google Scholar 
Buckley, S. A., Stott, A. W. & Evershed, R. P. Studies of organic residues from ancient Egyptian mummies using high temperature-gas chromatography-mass spectrometry and sequential thermal desorption-gas chromatography-mass spectrometry and pyrolysis-gas chromatography-mass spectrometry. Analyst 124, 443–452 (1999).Article 
CAS 

Google Scholar 
Hardy, K. et al. Neanderthal medics? Evidence for food, cooking, and medicinal plants entrapped in dental calculus. Naturwissenschaften 99, 617–626 (2012).Article 
CAS 

Google Scholar 
Luong, S., Tocheri, M. W., Sutikna, T., Saptomo, E. W. & Roberts, R. G. Incorporating terpenes, monoterpenoids and alkanes into multiresidue organic biomarker analysis of archaeological stone artefacts from Liang Bua (Flores, Indonesia). J. Archaeol. Sci. Rep. 19, 189–199 (2018).
Google Scholar 
Luong, S. et al. Combined organic biomarker and use-wear analyses of stone artefacts from Liang Bua, Flores, Indonesia. Sci. Rep. 9, 1–17 (2019).Article 
CAS 

Google Scholar 
Dabney, J., Meyer, M. & Pääbo, S. Ancient DNA damage. Cold Spring Harb. Perspect. Biol. 5, a012567 (2013).Article 

Google Scholar 
Mann, A. E. et al. Differential preservation of endogenous human and microbial DNA in dental calculus and dentin. Sci. Rep. 8, 1–15 (2018).Article 

Google Scholar 
Horrocks, M., Nieuwoudt, M. K., Kinaston, R., Buckley, H. & Bedford, S. Microfossil and Fourier Transform InfraRed analyses of Lapita and post-Lapita human dental calculus from Vanuatu, Southwest Pacific. J. R. Soc. N. Z. 44, 17–33 (2014).Article 

Google Scholar 
Radini, A., Nikita, E., Buckley, S., Copeland, L. & Hardy, K. Beyond food: the multiple pathways for inclusion of materials into ancient dental calculus. Am. J. Phys. Anthropol. 162, 71–83 (2017).Article 

Google Scholar 
Henry, A. G. Other microparticles: volcanic glass, minerals, insect remains, feathers, and other plant parts. In Handbook for the Analysis of Micro-Particles in Archaeological Samples 289–295 (Springer, Cham, 2020).MacKenzie, L., Speller, C. F., Holst, M., Keefe, K., & Radini, A. Dental calculus in the industrial age: human dental calculus in the Post-Medieval period, a case study from industrial Manchester. Quat. Int. https://doi.org/10.1016/j.quaint.2021.09.020 (2021).Radini, A., & Nikita, E. Beyond dirty teeth: Integrating dental calculus studies with osteoarchaeological parameters. Quat. Int. https://doi.org/10.1016/j.quaint.2022.03.003 (2022).Dobney, K. & Brothwell, D. A scanning electron microscope study of archaeological dental calculus. In Scanning Electron Microscopy in Archaeology BAR International Series (ed. & Olsen S), vol. 452, pp. 372–385 (Oxford, UK: BAR, 1988).Henry, A. G. & Piperno, D. R. Using plant microfossils from dental calculus to recover human diet: a case study from Tell al-Raqā’i, Syria. J. Archaeol. Sci. 35, 1943–1950 (2008).Article 

Google Scholar 
Wesolowski, V., de Souza, S. M. F. M., Reinhard, K. J. & Ceccantini, G. Evaluating microfossil content of dental calculus from Brazilian sambaquis. J. Archaeol. Sci. 37, 1326–1338 (2010).Article 

Google Scholar 
González-Guarda, E. et al. Multiproxy evidence for leaf-browsing and closed habitats in extinct proboscideans (Mammalia, Proboscidea) from Central Chile. Proc. Natl. Acad. Sci. USA 115, 9258–9263 (2018).Article 

Google Scholar 
Radley, J. A. Starch and its Derivatives (Chapman and Hall, London, 1968).Power, R. C., Salazar-García, D. C., Wittig, R. M. & Henry, A. G. Assessing use and suitability of scanning electron microscopy in the analysis of micro remains in dental calculus. J. Archaeol. Sci. 49, 160–169 (2014).Article 
CAS 

Google Scholar 
Rottoli, M. & Castiglioni, E. Prehistory of plant growing and collecting in northern Italy, based on seed remains from the early Neolithic to the Chalcolithic (c. 5600–2100 cal BC). Veg. Hist. Archaeobot. 18, 91–103 (2009).Article 

Google Scholar 
Fiorentino, G. et al. Climate changes and human–environment interactions in the Apulia region of southeastern Italy during the Neolithic period. Holocene 23, 1297–1316 (2013).Article 

Google Scholar 
Rottoli, M., & Pessina, A. Neolithic agriculture in Italy: an update of archaeobotanical data with particular emphasis on northern settlements. In The Origins and Spread of Domestic Plants in Southwest Asia and Europe 157–170 (Routledge, 2016).Arobba, D., Panelli, C., Caramiello, R., Gabriele, M. & Maggi, R. Cereal remains, plant impressions and 14C direct dating from the Neolithic pottery of Arene Candide Cave (Finale Ligure, NW Italy). J. Archaeol. Sci. Rep. 12, 395–404 (2017).
Google Scholar 
Ucchesu, M., Sau, S. & Lugliè, C. Crop and wild plant exploitation in Italy during the Neolithic period: New data from Su Mulinu Mannu, Middle Neolithic site of Sardinia. J. Archaeol. Sci. Rep. 14, 1–11 (2017).
Google Scholar 
Scorrano, G. et al. Effect of Neolithic transition on an Italian community: Mora Cavorso (Jenne, Rome). Archaeol. Anthropol. Sci. 11, 1443–1459 (2019).Article 

Google Scholar 
De Angelis, F. et al. Exploring mobility in Italian Neolithic and Copper Age communities. Sci. Rep. 11, 1–14 (2021).Article 

Google Scholar 
Oxilia, G. et al. Exploring late Paleolithic and Mesolithic diet in the Eastern Alpine region of Italy through multiple proxies. Am. J. Phys. Anthropol. 174, 232–253 (2021).Article 

Google Scholar 
Fahmy, A. G. E. Palaeoethnobotanical studies of the Neolithic settlement in Hidden Valley, Farafra Oasis, Egypt. Veg. Hist. Archaeobot. 10, 235–246 (2001).Article 

Google Scholar 
Reed, K. From the field to the hearth: plant remains from Neolithic Croatia (ca. 6000–4000 cal bc). Veg. Hist. Archaeobot. 24, 601–619 (2015).Article 

Google Scholar 
Lucarini, G., Radini, A., Barton, H. & Barker, G. The exploitation of wild plants in Neolithic North Africa. Use-wear and residue analysis on non-knapped stone tools from the Haua Fteah cave, Cyrenaica, Libya. Quat. Int. 410, 77–92 (2016).Article 

Google Scholar 
García-Granero, J. J., Urem-Kotsou, D., Bogaard, A. & Kotsos, S. Cooking plant foods in the northern Aegean: microbotanical evidence from Neolithic Stavroupoli (Thessaloniki, Greece). Quat. Int. 496, 140–151 (2018).Article 

Google Scholar 
Bouby, L. et al. Early Neolithic (ca. 5850-4500 cal BC) agricultural diffusion in the Western Mediterranean: an update of archaeobotanical data in SW France. PLoS One 15, e0230731 (2020).Article 
CAS 

Google Scholar 
Delhon, C., Binder, D., Verdin, P. & Mazuy, A. Phytoliths as a seasonality indicator? The example of the Neolithic site of Pendimoun, south-eastern France. Veg. Hist. Archaeobot. 29, 229–240 (2020).Article 

Google Scholar 
Lu, H. et al. Phytoliths analysis for the discrimination of foxtail millet (Setaria italica) and common millet (Panicum miliaceum). PLoS One 4, e4448 (2009).Article 

Google Scholar 
Celant, A. Indagini paleobotaniche su macroresti vegetali dai siti neo-eneolitici del territorio di Roma. In Roma prima del mito. Abitati e necropoli dal Neolitico alla prima età dei Metalli nel territorio di Roma (VI-III millennio a.C.) (eds Anzidei, A. P. & Carboni, C.) Vol. 2, 687–704 (Archaeopress Archaeol., 2020).Carra, M. et al. Plant foods in the Late Palaeolithic of Southern Italy and Sicily: Integrating carpological and dental calculus evidence. Quat. Int. https://doi.org/10.1016/j.quaint.2022.06.007 (2022) .Bednar, G. E. et al. Starch and fiber fractions in selected food and feed ingredients affect their small intestinal digestibility and fermentability and their large bowel fermentability in vitro in a canine model. J. Nutr. 131, 276–286 (2001).Article 
CAS 

Google Scholar 
Hoover, R., Hughes, T., Chung, H. J. & Liu, Q. Composition, molecular structure, properties, and modification of pulse starches: a review. Food Res. Int. 43, 399–413 (2010).Article 
CAS 

Google Scholar 
Wani, I. A. et al. Isolation, composition, and physicochemical properties of starch from legumes: a review. Starch‐Stärke 68, 834–845 (2016).Article 
CAS 

Google Scholar 
Tayade, R., Kulkarni, K. P., Jo, H., Song, J. T. & Lee, J. D. Insight into the prospects for the improvement of seed starch in legume—a review. Front. Plant Sci. 10, 1213 (2019).Article 

Google Scholar 
Stafford, H. A. Distribution of tartaric acid in the leaves of certain angiosperms. Am. J. Bot. 46, 347–352 (1959).Article 
CAS 

Google Scholar 
DeBolt, S., Cook, D. R. & Ford, C. M. L-Tartaric acid synthesis from vitamin C in higher plants. Proc. Natl. Acad. Sci. USA 103, 5608–5613 (2006).Article 
CAS 

Google Scholar 
Fernández-García, E. et al. Carotenoids bioavailability from foods: from plant pigments to efficient biological activities. Food Res. Int. 46, 438–450 (2012).Article 

Google Scholar 
Gliszczyńska, A. & Brodelius, P. E. Sesquiterpene coumarins. Phytochem. Rev. 11, 77–96 (2012).Article 

Google Scholar 
Eerkens, J. The preservation and identification of Piñon resins by GC‐MS in pottery from the Western Great Basin. Archaeometry 44, 95–105 (2002).Article 
CAS 

Google Scholar 
Barnard, H. et al. Mixed results of seven methods for organic residue analysis applied to one vessel with the residue of a known foodstuff. J. Archaeol. Sci. 34, 28–37 (2007).Article 

Google Scholar 
Wysocka, W., Przybył, A. & Brukwicki, T. The structure of angustifoline, an alkaloid of Lupinus angustifolius, in solution. Monatsh. Chem. 125, 1267–1272 (1994).Article 
CAS 

Google Scholar 
Ohmiya, S., Saito, K., & Murakoshi, I. Lupine alkaloids. In The alkaloids: Chemistry and Pharmacology Vol. 47, 1–114) (Academic Press, 1995).Mancinotti, D., Frick, K. M. & Geu-Flores, F. Biosynthesis of quinolizidine alkaloids in lupins: mechanistic considerations and prospects for pathway elucidation. Nat. Prod. Rep. 39, 1423–1437 (2022).Article 
CAS 

Google Scholar 
Silvestri, L., Achino, K. F., Gatta, M., Rolfo, M. F. & Salari, L. Grotta Mora Cavorso: physical, material and symbolic boundaries of life and death practices in a Neolithic cave of central Italy. Quat. Int. 539, 29–38 (2020).Article 

Google Scholar 
Steele, V. J., Stern, B. & Stott, A. W. Olive oil or lard?: distinguishing plant oils from animal fats in the archaeological record of the eastern Mediterranean using gas chromatography/combustion/isotope ratio mass spectrometry. Rapid Commun. Mass Spectrom. 24, 3478–3484 (2010).Article 
CAS 

Google Scholar 
Buonasera, T. Investigating the presence of ancient absorbed organic residues in groundstone using GC–MS and other analytical techniques: a residue study of several prehistoric milling tools from central California. J. Archaeol. Sci. 34, 1379–1390 (2007).Article 

Google Scholar 
Luong, S. et al. Development and application of a comprehensive analytical workflow for the quantification of non-volatile low molecular weight lipids on archaeological stone tools. Anal. Met. 9, 4349–4362 (2017).Article 
CAS 

Google Scholar 
Baeten, J., Jervis, B., De Vos, D. & Waelkens, M. Molecular evidence for the mixing of Meat, Fish and Vegetables in Anglo‐Saxon coarseware from Hamwic, UK. Archaeometry 55, 1150–1174 (2013).Article 
CAS 

Google Scholar 
Evershed, R. P. Chemical composition of a bog body adipocere. Archaeometry 34, 253–265 (1992).Article 
CAS 

Google Scholar 
Garnier, N., Bernal-Casasola, D., Driard, C. & Pinto, I. V. Looking for ancient fish products through invisible biomolecular residues in the roman production vats from the Atlantic. Coast J. Marit. Archaeol. 13, 285–328 (2018).Article 

Google Scholar 
Copley, M. S., Bland, H. A., Rose, P., Horton, M. & Evershed, R. P. Gas chromatographic, mass spectrometric and stable carbon isotopic investigations of organic residues of plant oils and animal fats employed as illuminants in archaeological lamps from Egypt. Analyst 130, 860–871 (2005).Article 
CAS 

Google Scholar 
Reber, E. A. & Hart, J. P. Pine resins and pottery sealing: analysis of absorbed and visible pottery residues from central New York State. Archaeometry 50, 999–1017 (2008).Article 
CAS 

Google Scholar 
Simopoulos, A. P. Omega‐3 fatty acids in wild plants, nuts and seeds. Asia Pac. J. Clin. Nutr. 11, S163–S173 (2002).Article 
CAS 

Google Scholar 
Harris, W. S. et al. Stearidonic acid-enriched soybean oil increased the omega-3 index, an emerging cardiovascular risk marker. Lipids 43, 805–811 (2008).Article 
CAS 

Google Scholar 
Gismondi, A., Rolfo, M. F., Leonardi, D., Rickards, O. & Canini, A. Identification of ancient Olea europaea L. and Cornus mas L. seeds by DNA barcoding. C. R. Biol. 335, 472–479 (2012).Article 
CAS 

Google Scholar 
Steffens, W. & Wirth, M. Freshwater fish-an important source of n-3 polyunsaturated fatty acids: a review. Fish. Aquat. Sci. 13, 5–16 (2005).
Google Scholar 
Swanson, D., Block, R. & Mousa, S. A. Omega-3 fatty acids EPA and DHA: health benefits throughout life. Adv. Nutr. 3, 1–7 (2012).Article 
CAS 

Google Scholar 
Wiermann, R., & Gubatz, S. Pollen wall and sporopollenin. In International Review of Cytology 35–72 (Academic Press, 1992).Cristiani, E., Radini, A., Edinborough, M. & Borić, D. Dental calculus reveals Mesolithic foragers in the Balkans consumed domesticated plant foods. Proc. Natl. Acad. Sci. USA 113, 10298–10303 (2016).Article 
CAS 

Google Scholar 
Hardy, K. et al. Dental calculus reveals potential respiratory irritants and ingestion of essential plant-based nutrients at Lower Palaeolithic Qesem Cave Israel. Quat. Int. 398, 129–135 (2016).Article 

Google Scholar 
Radini, A. et al. Neanderthals, trees and dental calculus: new evidence from El Sidrón. Antiquity 90, 290–301 (2016).Article 

Google Scholar 
Lippi, M. M., Pisaneschi, L., Sarti, L., Lari, M. & Moggi-Cecchi, J. Insights into the Copper-Bronze Age diet in central Italy: plant microremains in dental calculus from Grotta dello Scoglietto (Southern Tuscany, Italy). J. Archaeol. Sci. Rep. 15, 30–39 (2017).
Google Scholar 
Modi, A. et al. Combined metagenomic and archaeobotanical analyses on human dental calculus: a cross-section of lifestyle conditions in a Copper Age population of central Italy. Quat. Int. https://doi.org/10.1016/j.quaint.2021.12.003 (2021).Warinner, C. et al. Pathogens and host immunity in the ancient human oral cavity. Nat. Genet. https://doi.org/10.1038/ng.2906 (2014).Lieverse, A. R. Diet and the aetiology of dental calculus. Int. J. Osteoarchaeol. 9, 219–232 (1999).Article 

Google Scholar 
Lukacs, J. R. & Largaespada, L. L. Explaining sex differences in dental caries prevalence: saliva, hormones, and “life‐history” etiologies. Am. J. Hum. Biol. 18, 540–555 (2006).Article 

Google Scholar 
Moore, P. D., Webb, J. A., & Collison, M. E. Pollen Analysis (Blackwell Scientific Publications, 1991).Borojević, K., Forenbaher, S., Kaiser, T. & Berna, F. Plant use at Grapčeva cave and in the eastern Adriatic Neolithic. J. Field Archaeol. 33, 279–303 (2008).Article 

Google Scholar 
Martin, L., Jacomet, S. & Tiebault, S. Plant economy during the Neolithic in a mountain context: the case of “Le Chenet des Pierres” in the French Alps (Bozel-Savoie, France). Veg. Hist. Archaeobot. 17, 113–122 (2008).Article 

Google Scholar 
Moser, D., Di Pasquale, G., Scarciglia, F. & Nelle, O. Holocene mountain forest changes in central Mediterranean: soil charcoal data from the Sila Massif (Calabria, southern Italy). Quat. Int. 457, 113–130 (2017).Article 

Google Scholar 
D’Agostino, A. et al. Pollen record of the Late Pleistocene–Holocene stratigraphic sequence and current plant biodiversity from Grotta Mora Cavorso (Simbruini Mountains, Central Italy). Ecol. Evol. 12, e9486 (2022).Radaeski, J. N., Bauermann, S. G. & Pereira, A. B. Poaceae pollen from Southern Brazil: distinguishing grasslands (campos) from forests by analyzing a diverse range of Poaceae species. Front. Plant Sci. 7, 1833 (2016).Article 

Google Scholar 
Turner, S. D. & Brown, A. G. Vitis pollen dispersal in and from organic vineyards: I. Pollen trap and soil pollen data. Rev. Palaeobot. Palynol. 129, 117–132 (2004).Article 

Google Scholar 
Marvelli, S., De’Siena, S., Rizzoli, E. & Marchesini, M. The origin of grapevine cultivation in Italy: the archaeobotanical evidence. Ann. Bot. 3, 155–163 (2013).
Google Scholar 
Riaz, S. et al. Genetic diversity analysis of cultivated and wild grapevine (Vitis vinifera L.) accessions around the Mediterranean basin and Central Asia. BMC Plant Biol. 18, 1–14 (2018).Article 

Google Scholar 
Arnold, C., Gillet, F., & Gobat, J. M. Situation de la vigne sauvage Vitis vinifera subsp. silvestris en Europe. Vitis 159–170 (1998).Terral, J. F. et al. Evolution and history of grapevine (Vitis vinifera) under domestication: new morphometric perspectives to understand seed domestication syndrome and reveal origins of ancient European cultivars. Ann. Bot. 105, 443–455 (2010).Article 

Google Scholar 
Buckley, S., Usai, D., Jakob, T., Radini, A. & Hardy, K. Dental calculus reveals unique insights into food items, cooking and plant processing in prehistoric central Sudan. PLoS One 9, e100808 (2014).Article 

Google Scholar 
Petrov, P. R., Popova, E. D. & Zlatanova, D. P. Niche partitioning among the red fox Vulpes vulpes (L.), stone marten Martes foina (Erxleben) and pine marten Martes martes (L.) in two mountains in Bulgaria. Acta Zool. Bulg. 68, 375–390 (2016).
Google Scholar 
Mikrjukov, K. A. Revision of genera and species composition of lower Centroheliozoa. II. Family Raphidiophryidae n. tam. Arch. Protistenkd. 147, 205–212 (1996).Article 

Google Scholar 
Cavalier-Smith, T. & von der Heyden, S. Molecular phylogeny, scale evolution and taxonomy of centrohelid heliozoa. Mol. Phylogen. Evol. 44, 1186–1203 (2007).Article 
CAS 

Google Scholar 
Mertens, K. N., Rengefors, K., Moestrup, Ø. & Ellegaard, M. A review of recent freshwater dinoflagellate cysts: taxonomy, phylogeny, ecology and palaeocology. Phycologia 51, 612–619 (2012).Article 

Google Scholar 
Zlatogursky, V. V. Raphidiophrys heterophryoidea sp. nov. (Centrohelida: Raphidiophryidae), the first heliozoan species with a combination of siliceous and organic skeletal elements. Eur. J. Protist. 48, 9–16 (2012).Article 

Google Scholar 
Prokina, K. I. & Mylnikov, A. P. Centrohelid heliozoans from freshwater habitats of different types of South Patagonia and Tierra del Fuego, Chile. Inland Water Biol. 12, 10–20 (2019).Article 

Google Scholar 
Siemensma, F. J. & Roijackers, M. M. A study of new and little- known acanthocystid heliozoans, and a proposed division of the genus Acanthocystis (Actinopoda, Heliozoea). Arch. Protistenkd. 135, 197 (1988a).Article 

Google Scholar 
Siemensma, F. J. & Roijackers, M. M. The genus Raphidiophrys (Actinopoda, Heliozoea): scale morphology and species distinctions. Arch. Protistenkd. 136 237–248 (1988).Taylor, W.D. & Sanders, R. W. PROTOZOA. In Ecology and Classification of North American Freshwater Invertebrates (eds Thorp, J. H. & Covich, A. P.) 43–96 (Academic Press, 2001).Manconi, R., & Pronzato, R. Global diversity of sponges (Porifera: Spongillina) in freshwater. In Freshwater Animal Diversity Assessment 27–33 (Springer, Dordrecht, 2007).Malone, C. & Stoddart, S. The neolithic site of San Marco, Gubbio (Perugia), Umbria: survey and excavation 1985–7. Pap. Br. Sch. Rome 60, 1–69 (1992).Article 

Google Scholar 
Rottoli, M. La Marmotta, Anguillara Sabazia (RM). Scavi 1989. Analisi paletnobotaniche: prime risultanze, Appendice 1 M.A. In La Marmotta” (Anguillara Sabazia, RM). Scavi 1989. Un abitato perilacustre di età neolitica (eds. Fugazzola Delpino, M. A., D’Eugenio, G. & Pessina, A.) Bullettino di Paletnologia Italiana 84, 305–315 (1993).Pini, R. Late Neolithic vegetation history at the pile‐dwelling site of Palù di Livenza (northeastern Italy). J. Quat. Sci. 19, 769–781 (2004).Article 

Google Scholar 
Tinner, W. et al. Holocene environmental and climatic changes at Gorgo Basso, a coastal lake in southern Sicily, Italy. Quat. Sci. Rev. 28, 1498–1510 (2009).Article 

Google Scholar 
Bieniek, A. Archaeobotanical analysis of some early Neolithic settlements in the Kujawy region, central Poland, with potential plant gathering activities emphasized. Veg. Hist. Archaeobot. 11, 33–40 (2002).Article 

Google Scholar 
Tolar, T., Jacomet, S., Velušček, A. & Čufar, K. Plant economy at a late Neolithic lake dwelling site in Slovenia at the time of the Alpine Iceman. Veg. Hist. Archaeobot. 20, 207–222 (2011).Article 

Google Scholar 
D’Agostino, A. et al. Investigating plant micro-remains embedded in dental calculus of the Phoenician inhabitants of Motya (Sicily, Italy). Plants 9, 1395 (2020).Article 

Google Scholar 
Mercader, J. et al. Exaggerated expectations in ancient starch research and the need for new taphonomic and authenticity criteria. Facets 3, 777–798 (2018).Article 

Google Scholar 
Adojoh, O., Fabienne, M., Duller, R. & Osterloff, P. Taxonomy and phytoecology of palynomorphs and non-pollen palynomorphs: a refined compendium from the West Africa Margin. Biodivers. Int. J. 3, 188–200 (2019).Article 

Google Scholar 
Knapp, M., Clarke, A. C., Horsburgh, K. A. & Matisoo-Smith, E. A. Setting the stage building and working in an ancient DNA laboratory. Ann. Anat. 194, 3 (2012).Article 
CAS 

Google Scholar 
Knapp, M., Lalueza-Fox, C. & Hofreiter, M. Re-inventing ancient human DNA. Investig. Genet. 6, 1 (2015).Article 

Google Scholar 
Gismondi, A. et al. Grapevine carpological remains revealed the existence of a Neolithic domesticated Vitis vinifera L. specimen containing ancient DNA partially preserved in modern ecotypes. J. Archaeol. Sci. 69, 75–84 (2016).Article 
CAS 

Google Scholar 
Llamas, B. et al. From the field to the laboratory: controlling DNA contamination in human ancient DNA research in the high-throughput sequencing era. Sci. Technol. Archaeol. Res. 3, 1–14 (2017).Le Moyne, C. & Crowther, A. Effects of chemical pre-treatments on modified starch granules: recommendations for dental calculus decalcification for ancient starch research. J. Archaeol. Sci. Rep. 35, 102762 (2021).
Google Scholar 
Rolfo, M. F., Achino, K. F., Fusco, I., Salari, L. & Silvestri, L. Reassessing human occupation patterns in the inner central Apennines in prehistory: the case-study of Grotta Mora Cavorso. J. Archaeol. Sci. Rep. 7, 358–367 (2016).
Google Scholar  More

IPBES. Global assessment report of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES secretariat, 2019).Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).Article 
ADS 
CAS 

Google Scholar 
IPCC. Summary for Policymakers. in Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2022).Travis, J. M. J. Climate change and habitat destruction: a deadly anthropogenic cocktail. P. R. Soc. B. 270, 467–473 (2003).Article 
CAS 

Google Scholar 
Newbold, T. Future effects of climate and land-use change on terrestrial vertebrate community diversity under different scenarios. P. R. Soc. B. 285, 20180792 (2018).Article 

Google Scholar 
Anderson, K. J., Allen, A. P., Gillooly, J. F. & Brown, J. H. Temperature-dependence of biomass accumulation rates during secondary succession. Ecol. Lett. 9, 673–682 (2006).Article 

Google Scholar 
Fridley, J. D. & Wright, J. P. Temperature accelerates the rate fields become forests. Proc. Natl Acad. Sci. USA 115, 4702–4706 (2018).Article 
ADS 
CAS 

Google Scholar 
Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).Article 
ADS 
CAS 

Google Scholar 
Auffret, A. G., Kimberley, A., Plue, J. & Waldén, E. Super-regional land-use change and effects on the grassland specialist flora. Nat. Commun. 9, 3464 (2018).Article 
ADS 

Google Scholar 
Auffret, A. G. & Thomas, C. D. Synergistic and antagonistic effects of land use and non-native species on community responses to climate change. Glob. Change Biol. 25, 4303–4314 (2019).Article 
ADS 

Google Scholar 
Hill, M. O. Local frequency as a key to interpreting species occurrence data when recording effort is not known. Methods Ecol. Evol. 3, 195–205 (2012).Article 

Google Scholar 
Isaac, N. J. B., Strien, A. J., van, August, T. A., Zeeuw, M. Pde & Roy, D. B. Statistics for citizen science: extracting signals of change from noisy ecological data. Methods Ecol. Evol. 5, 1052–1060 (2014).Article 

Google Scholar 
Tyler, T., Herbertsson, L., Olofsson, J. & Olsson, P. A. Ecological indicator and traits values for Swedish vascular plants. Ecol. Indic. 120, 106923 (2021).Article 
CAS 

Google Scholar 
Jiang, M., Bullock, J. M. & Hooftman, D. A. P. Mapping ecosystem service and biodiversity changes over 70 years in a rural English county. J. Appl. Ecol. 50, 841–850 (2013).Article 

Google Scholar 
IPCC. Summary for Policymakers. in Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2021).Van Calster, H. et al. Unexpectedly high 20th century floristic losses in a rural landscape in northern France. J. Ecol. 96, 927–936 (2008).Article 

Google Scholar 
Staude, I. R. et al. Replacements of small- by large-ranged species scale up to diversity loss in Europe’s temperate forest biome. Nat. Ecol. Evol. 4, 802–808 (2020).Article 

Google Scholar 
Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).Article 
ADS 
CAS 

Google Scholar 
Lenoir, J. et al. Species better track climate warming in the oceans than on land. Nat. Ecol. Evol. 4, 1044–1059 (2020).Article 

Google Scholar 
Platts, P. J. et al. Habitat availability explains variation in climate-driven range shifts across multiple taxonomic groups. Sci. Rep. 9, 1–10 (2019).Article 
ADS 
MathSciNet 
CAS 

Google Scholar 
Macgregor, C. J. et al. Climate-induced phenology shifts linked to range expansions in species with multiple reproductive cycles per year. Nat. Commun. 10, 4455 (2019).Article 
ADS 

Google Scholar 
Dullinger, S. et al. Extinction debt of high-mountain plants under twenty-first-century climate change. Nat. Clim. Change 2, 619–622 (2012).Article 
ADS 

Google Scholar 
Svenning, J.-C. & Sandel, B. Disequilibrium vegetation dynamics under future climate change. Am. J. Bot. 100, 1266–1286 (2013).Article 

Google Scholar 
Cannone, N. & Pignatti, S. Ecological responses of plant species and communities to climate warming: upward shift or range filling processes? Climatic Change 123, 201–214 (2014).Article 
ADS 

Google Scholar 
Wiens, J. J. Climate-Related Local Extinctions Are Already Widespread among Plant and Animal Species. PLOS Biol. 14, e2001104 (2016).Article 

Google Scholar 
Hill, M. O. & Preston, C. D. Disappearance of boreal plants in southern Britain: habitat loss or climate change? Biol. J. Linn. Soc. 115, 598–610 (2015).Article 

Google Scholar 
Lynn, J. S., Klanderud, K., Telford, R. J., Goldberg, D. E. & Vandvik, V. Macroecological context predicts species’ responses to climate warming. Glob. Change Biol. 27, 2088–2101 (2021).Article 
ADS 
CAS 

Google Scholar 
Liu, D. et al. Species selection under long-term experimental warming and drought explained by climatic distributions. N. Phytol. 217, 1494–1506 (2018).Article 

Google Scholar 
Buitenwerf, R., Sandel, B., Normand, S., Mimet, A. & Svenning, J.-C. Land surface greening suggests vigorous woody regrowth throughout European semi-natural vegetation. Glob. Change Biol. 24, 5789–5801 (2018).Article 

Google Scholar 
Suggitt, A. J. et al. Extinction risk from climate change is reduced by microclimatic buffering. Nat. Clim. Change 8, 713–717 (2018).Article 
ADS 

Google Scholar 
De Frenne, P. et al. Latitudinal gradients as natural laboratories to infer species’ responses to temperature. J. Ecol. 101, 784–795 (2013).Article 

Google Scholar 
Ash, J. D., Givnish, T. J. & Waller, D. M. Tracking lags in historical plant species’ shifts in relation to regional climate change. Glob. Change Biol. 23, 1305–1315 (2017).Article 
ADS 

Google Scholar 
Savage, J. & Vellend, M. Elevational shifts, biotic homogenization and time lags in vegetation change during 40 years of climate warming. Ecography 38, 546–555 (2015).Article 

Google Scholar 
Gerstner, K., Dormann, C. F., Stein, A., Manceur, A. M. & Seppelt, R. Effects of land use on plant diversity—a global meta-analysis. J. Appl. Ecol. 51, 1690–1700 (2014).Article 

Google Scholar 
Kempel, A. et al. Nationwide revisitation reveals thousands of local extinctions across the ranges of 713 threatened and rare plant species. Conserv. Lett. 13, e12749 (2020).Article 

Google Scholar 
Bilz, M., Kell, S. P., Maxted, N. & Lansdown, R. V. European Red List of Vascular Plants (Publications Office of the EU, 2011).Timmermann, A., Damgaard, C., Strandberg, M. T. & Svenning, J.-C. Pervasive early 21st-century vegetation changes across Danish semi-natural ecosystems: more losers than winners and a shift towards competitive, tall-growing species. J. Appl. Ecol. 52, 21–30 (2015).Article 

Google Scholar 
Staude, I. R. et al. Directional turnover towards larger-ranged plants over time and across habitats. Ecol. Lett. 25, 466–482 (2022).Article 

Google Scholar 
Finderup Nielsen, T., Sand‐Jensen, K., Dornelas, M. & Bruun, H. H. More is less: net gain in species richness, but biotic homogenization over 140 years. Ecol. Lett. 22, 1650–1657 (2019).Article 

Google Scholar 
Christiansen, D. M., Iversen, L. L., Ehrlén, J. & Hylander, K. Changes in forest structure drive temperature preferences of boreal understorey plant communities. J. Ecol. 110, 631–643 (2022).Article 

Google Scholar 
Gossner, M. M. et al. Land-use intensification causes multitrophic homogenization of grassland communities. Nature 540, 266–269 (2016).Article 
ADS 
CAS 

Google Scholar 
Duprè, C. et al. Changes in species richness and composition in European acidic grasslands over the past 70 years: the contribution of cumulative atmospheric nitrogen deposition. Glob. Change Biol. 16, 344–357 (2010).Article 
ADS 

Google Scholar 
Tyler, T. et al. Climate warming and land‐use changes drive broad‐scale floristic changes in Southern Sweden. Glob. Change Biol. 24, 2607–2621 (2018).Article 
ADS 

Google Scholar 
Steinbauer, M. J. et al. Accelerated increase in plant species richness on mountain summits is linked to warming. Nature 556, 231 (2018).Article 
ADS 
CAS 

Google Scholar 
Halley, J. M., Monokrousos, N., Mazaris, A. D., Newmark, W. D. & Vokou, D. Dynamics of extinction debt across five taxonomic groups. Nat. Commun. 7, 12283 (2016).Article 
ADS 
CAS 

Google Scholar 
Bertrand, R. et al. Changes in plant community composition lag behind climate warming in lowland forests. Nature 479, 517–520 (2011).Article 
ADS 
CAS 

Google Scholar 
Kuussaari, M. et al. Extinction debt: a challenge for biodiversity conservation. Trends Ecol. Evol. 24, 564–571 (2009).Article 

Google Scholar 
Plue, J. et al. Buffering effects of soil seed banks on plant community composition in response to land use and climate. Glob. Ecol. Biogeogr. 30, 128–139 (2021).Article 

Google Scholar 
Honnay, O. & Bossuyt, B. Prolonged clonal growth: escape route or route to extinction? Oikos 108, 427–432 (2005).Article 

Google Scholar 
Ozinga, W. A. et al. Dispersal failure contributes to plant losses in NW Europe. Ecol. Lett. 12, 66–74 (2009).Article 

Google Scholar 
Svenning, J.-C., Normand, S. & Skov, F. Postglacial dispersal limitation of widespread forest plant species in nemoral Europe. Ecography 31, 316–326 (2008).Article 

Google Scholar 
Lenoir, J., Gégout, J. C., Marquet, P. A., de Ruffray, P. & Brisse, H. A significant upward shift in plant species optimum elevation during the 20th century. Science 320, 1768–1771 (2008).Article 
ADS 
CAS 

Google Scholar 
Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).Article 
ADS 
CAS 

Google Scholar 
Warren, R., Price, J., Graham, E., Forstenhaeusler, N. & VanDerWal, J. The projected effect on insects, vertebrates, and plants of limiting global warming to 1.5 °C rather than 2 °C. Science 360, 791–795 (2018).Article 
CAS 

Google Scholar 
Garrido, P. et al. Experimental rewilding may restore abandoned wood-pastures if policy allows. Ambio 50, 101–112 (2021).Article 

Google Scholar 
Kowalczyk, R., Kamiński, T. & Borowik, T. Do large herbivores maintain open habitats in temperate forests? For. Ecol. Manag. 494, 119310 (2021).Article 

Google Scholar 
Auffret, A. G., Schmucki, R., Reimark, J. & Cousins, S. A. O. Grazing networks provide useful functional connectivity for plants in fragmented systems. J. Veg. Sci. 23, 970–977 (2012).Article 

Google Scholar 
Fricke, E. C., Ordonez, A., Rogers, H. S. & Svenning, J.-C. The effects of defaunation on plants’ capacity to track climate change. Science 375, 210–214 (2022).Article 
ADS 
CAS 

Google Scholar 
Blomgren, E., Falk, E. & Herloff, B. Bohusläns Flora (Föreningen Bohusläns Flora, 2011).Fries, H. Göteborgs och Bohus Läns Fanerogamer och Ormbunkar (Elanders Boktryckeri, 1945).Lidberg, R. & Lindström, H. Medelpads Flora (The vascular plants of Medelpad) (SBF Förlaget, 2010).Sterner, R. Flora der insel Öland Vol. IX (Almqvist & Wiksells, 1938).Almquist, E. Upplands vegetation och flora. Acta Phytogeogr. Suec. 1, 1–622 (1929).
Google Scholar 
Jonsell, L. Upplands Flora (SBF Förlaget, 2010).Maad, J., Sundberg, S., Stolpe, P. & Jonsell, L. Floraförändringar i Uppland under 1900-talet—en analys från Projekt Upplands flora [Floristic changes during the 20th century in Uppland, east central Sweden; with English summary]. Sven. Botanisk Tidskr. 103, 67–104 (2009).
Google Scholar 
Auffret, A. G. et al. HistMapR: Rapid digitization of historical land-use maps in R. Methods Ecol. Evol. 8, 1453–1457 (2017).Article 

Google Scholar 
August, T. et al. sparta: Trend analysis for unstructured data. R package version 0.1.44 (2018).Eichenberg, D. et al. Widespread decline in Central European plant diversity across six decades. Glob. Change Biol. 27, 1097–1110 (2021).Article 
ADS 
CAS 

Google Scholar 
Redhead, J. W. et al. Potential landscape-scale pollinator networks across Great Britain: structure, stability and influence of agricultural land cover. Ecol. Lett. 21, 1821–1832 (2018).Article 

Google Scholar 
Gillings, S. et al. Breeding and wintering bird distributions in Britain and Ireland from citizen science bird atlases. Glob. Ecol. Biogeogr. 28, 866–874 (2019).Article 

Google Scholar 
Stroh, P. A., Walker, K. J., Humphrey, T. A., Pescott, O. L. & Burkmar, R. J. Plant Atlas 2020: Mapping Changes in the Distribution of the British and Irish Flora (Princeton, planned publication date: 21/03/2023).Pearce-Higgins, J. W., Ausden, M. A., Beale, C. M., Oliver, T. H. & Crick, H. Q. P. Research on the assessment of risks & opportunities for species in England as a result of climate change – NECR175. Natural England Commissioned Reports Vol. 175 (2015).R. Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).Telfer, M. G., Preston, C. D. & Rothery, P. A general method for measuring relative change in range size from biological atlas data. Biol. Conserv. 107, 99–109 (2002).Article 

Google Scholar 
Bates, D., Maechler, M., Bolker, B. M. & Walker, S. lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-7. http://CRAN.R-project.org/package=lme4 (2014).Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2009).Article 

Google Scholar 
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).Article 

Google Scholar 
Schielzeth, H. Simple means to improve the interpretability of regression coefficients. Methods Ecol. Evol. 1, 103–113 (2010).Article 

Google Scholar 
Nakagawa, S. & Schielzeth, H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4, 133–142 (2013).Article 

Google Scholar 
Borcard, D. & Legendre, P. All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecol. Model. 153, 51–68 (2002).Article 

Google Scholar 
Oksanen, J. et al. vegan: Community ecology package. R package version 2.3-5. http://CRAN.R-project.org/package=vegan (2016).Meineri, E. & Hylander, K. Fine-grain, large-domain climate models based on climate station and comprehensive topographic information improve microrefugia detection. Ecography 40, 1003–1013 (2017).Article 

Google Scholar 
Lüdecke, D., Ben-Shachar, M. S., Patil, I., Waggoner, P. & Makowski, D. performance: an R package for assessment, comparison and testing of statistical models. J. Open Source Softw. 6, 3139 (2021).Article 
ADS 

Google Scholar 
Breheny, P. & Burchett, W. Visualization of regression models using visreg. R. J. 9, 57–71 (2017).Article 

Google Scholar 
Hijmans, R. J. raster: Geographic data analysis and modeling. R package version 2.5-8. http://CRAN.R-project.org/package=raster (2016). More

Orr, M. R. & Smith, T. B. Ecology and speciation. Trends Ecol. Evol. 13, 502–506 (1998).Article 
CAS 

Google Scholar 
Coyne, J. A. & Orr, H. A. Speciation (Sinauer Associates, 2004).
Google Scholar 
Gillespie, R. G. Adaptive radiation: Convergence and non-equilibrium. Curr. Biol. 23, R71–R74 (2013).Article 
CAS 

Google Scholar 
Price, T. Speciation in Birds (Roberts and Company Publishers, 2008).
Google Scholar 
Schluter, D. Evidence for ecological speciation and its alternative. Science 323, 737–741 (2009).Article 
ADS 
CAS 

Google Scholar 
Stroud, J. T. & Losos, J. B. Ecological opportunity and adaptive radiation. Annu. Rev. Ecol. Evol. Syst. 47, 507–532 (2016).Article 

Google Scholar 
Jønsson, K. A. et al. Ecological and evolutionary determinants for the adaptive radiation of the Madagascan vangas. Proc. Natl. Acad. Sci. 109, 6620–6625 (2012).Article 
ADS 

Google Scholar 
Wiens, J. J. Speciation and ecology revisited: Phylogenetic niche conservatism and the origin of species. Evolution 58, 193–197 (2004).
Google Scholar 
Barve, N. et al. The crucial role of the accessible area in ecological niche modeling and species distribution modeling. Ecol. Model. 222, 1810–1819 (2011).Article 

Google Scholar 
Wiens, J. J. & Graham, C. H. Niche Conservatism: Integrating evolution, ecology, and conservation biology. Annu. Rev. Ecol. Evol. Syst. 36, 519–539 (2005).Article 

Google Scholar 
Petitpierre, B. et al. Climatic niche shifts are rare among terrestrial plant invaders. Science 335, 1344–1348 (2012).Article 
ADS 
CAS 

Google Scholar 
Winger, B. M., Barker, F. K. & Ree, R. H. Temperate origins of long-distance seasonal migration in New World songbirds. Proc. Natl. Acad. Sci. 111, 12115–12120 (2014).Article 
ADS 
CAS 

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

Google Scholar 
Gómez, C., Tenorio, E. A., Montoya, P. & Cadena, C. D. Niche-tracking migrants and niche-switching residents: Evolution of climatic niches in New World warblers (Parulidae). Proc. R. Soc. B Biol. Sci. 283, 20152458 (2016).Article 

Google Scholar 
Menchaca, A., Arteaga, M. C., Medellin, R. A. & Jones, G. Conservation units and historical matrilineal structure in the tequila bat (Leptonycteris yerbabuenae). Glob. Ecol. Conserv. 23, e01164 (2020).Article 

Google Scholar 
Medellín, R. A. et al. Follow me: Foraging distances of Leptonycteris yerbabuenae (Chiroptera: Phyllostomidae) in Sonora determined by fluorescent powder. J. Mammal. 99, 306–311 (2018).Article 

Google Scholar 
Broennimann, O. et al. Evidence of climatic niche shift during biological invasion. Ecol. Lett. 10, 701–709 (2007).Article 
CAS 

Google Scholar 
Martínez-Meyer, E., Peterson, A. T. & Hargrove, W. W. Ecological niches as stable distributional constraints on mammal species, with implications for Pleistocene extinctions and climate change projections for biodiversity. Glob. Ecol. Biogeogr. 13, 305–314 (2004).Article 

Google Scholar 
Soto-Centeno, J. A. & Steadman, D. W. Fossils reject climate change as the cause of extinction of Caribbean bats. Sci. Rep. 5, 7971 (2015).Article 
ADS 
CAS 

Google Scholar 
Avise, J. C. Phylogeography: The History and Formation of Species (Harvard University Press, 2000).Book 

Google Scholar 
Hickerson, M. J. et al. Phylogeography’s past, present, and future: 10 years after Avise, 2000. Mol. Phylogenet. Evol. 54, 291–301 (2010).Article 
CAS 

Google Scholar 
Pahad, G., Montgelard, C. & Jansen van Vuuren, B. Phylogeography and niche modelling: Reciprocal enlightenment. Mammalia 84, 10–25 (2019).Article 

Google Scholar 
Flanders, J. et al. Phylogeography of the greater horseshoe bat, Rhinolophus ferrumequinum: Contrasting results from mitochondrial and microsatellite data. Mol. Ecol. 18, 306–318 (2009).Article 
CAS 

Google Scholar 
Machado, A. F. et al. Integrating phylogeography and ecological niche modelling to test diversification hypotheses using a Neotropical rodent. Evol. Ecol. 33, 111–148 (2019).Article 

Google Scholar 
Kalkvik, H. M., Stout, I. J., Doonan, T. J. & Parkinson, C. L. Investigating niche and lineage diversification in widely distributed taxa: Phylogeography and ecological niche modeling of the Peromyscus maniculatus species group. Ecography 35, 54–64 (2012).Article 

Google Scholar 
Wang, Y. et al. Ring distribution patterns—diversification or speciation? Comparative phylogeography of two small mammals in the mountains surrounding the Sichuan Basin. Mol. Ecol. 30, 2641–2658 (2021).Article 

Google Scholar 
Soto-Centeno, J. A., Barrow, L. N., Allen, J. M. & Reed, D. L. Reevaluation of a classic phylogeographic barrier: New techniques reveal the influence of microgeographic climate variation on population divergence. Ecol. Evol. 3, 1603–1613 (2013).Article 

Google Scholar 
Amador, L. I., Moyers Arévalo, R. L., Almeida, F. C., Catalano, S. A. & Giannini, N. P. Bat systematics in the light of unconstrained analyses of a comprehensive molecular supermatrix. J. Mamm. Evol. 25, 37–70 (2018).Article 

Google Scholar 
Rojas, D., Warsi, O. M. & Dávalos, L. M. Bats (Chiroptera: Noctilionoidea) challenge a recent origin of extant neotropical diversity. Syst. Biol. 65, 432–448 (2016).Article 

Google Scholar 
Shi, J. J. & Rabosky, D. L. Speciation dynamics during the global radiation of extant bats. Evolution 69, 1528–1545 (2015).Article 

Google Scholar 
Dumont, E. R. et al. Morphological innovation, diversification and invasion of a new adaptive zone. Proc. Biol. Sci. 279, 1797–1805 (2012).
Google Scholar 
Leiser-Miller, L. B. & Santana, S. E. Morphological diversity in the sensory system of phyllostomid bats: Implications for acoustic and dietary ecology. Funct. Ecol. 34, 1416–1427 (2020).Article 

Google Scholar 
Hedrick, B. P. & Dumont, E. R. Putting the leaf-nosed bats in context: A geometric morphometric analysis of three of the largest families of bats. J. Mammal. 99, 1042–1054 (2018).Article 

Google Scholar 
Clare, E. L. Cryptic species? Patterns of maternal and paternal gene flow in eight neotropical bats. PLoS One 6, e21460 (2011).Article 
ADS 
CAS 

Google Scholar 
Chaverri, G. et al. Unveiling the hidden bat diversity of a neotropical montane forest. PLoS One 11, e0162712 (2016).Article 

Google Scholar 
Calahorra-Oliart, A., Ospina-Garcés, S. M. & León-Paniagua, L. Cryptic species in Glossophaga soricina (Chiroptera: Phyllostomidae): Do morphological data support molecular evidence?. J. Mammal. 102, 54–68 (2021).Article 

Google Scholar 
Lim, B. K., Loureiro, L. O. & Garbino, G. S. T. Cryptic diversity and range extension in the big-eyed bat genus Chiroderma (Chiroptera, Phyllostomidae). Zookeys 918, 41–63 (2020).Article 

Google Scholar 
Loureiro, L. O., Engstrom, M., Lim, B., González, C. L. & Juste, J. Not all Molossus are created equal: Genetic variation in the mastiff bat reveals diversity masked by conservative morphology. Acta Chiropterologica 21, 51 (2019).Article 

Google Scholar 
Morales, A., Villalobos, F., Velazco, P. M., Simmons, N. B. & Piñero, D. Environmental niche drives genetic and morphometric structure in a widespread bat. J. Biogeogr. 43, 1057–1068 (2016).Article 

Google Scholar 
Hedrick, B. P. et al. Morphological diversification under high integration in a hyper diverse mammal clade. J. Mamm. Evol. 27, 563–575 (2020).Article 

Google Scholar 
Morales, A. E. & Carstens, B. C. Evidence that myotis lucifugus “subspecies” are five nonsister species, despite gene flow. Syst. Biol. 67, 756–769 (2018).Article 

Google Scholar 
Simmons, N. B. & Cirranello, A. L. Bat species of the world: A taxonomic and geographic database. https://batnames.org.Russell, A. L., Pinzari, C. A., Vonhof, M. J., Olival, K. J. & Bonaccorso, F. J. Two tickets to paradise: Multiple dispersal events in the founding of hoary bat populations in Hawai’i. PLoS One 10, 1–13 (2015).
Google Scholar 
Shump, K. A. & Shump, A. U. Lasiurus cinereus. Mamm. Species 185, 1–5 (1982).
Google Scholar 
Ziegler, A. C., Howarth, F. G. & Simmons, N. B. A second endemic land mammal for the Hawaiian Islands: A new genus and species of fossil bat (Chiroptera: Vespertilionidae). Am. Museum Novit. 1–52 (2016).Bonaccorso, F. J. & McGuire, L. P. Modeling the colonization of Hawaii by hoary bats (Lasiurus cinereus). In Bat Evolution, Ecology, and Conservation (eds Adams, R. A. & Pedersen, S. C.) 187–205 (Springer, 2013).Chapter 

Google Scholar 
Baird, A. B. et al. Molecular systematic revision of tree bats (Lasiurini): Doubling the native mammals of the Hawaiian Islands. J. Mammal. 96, 1255–1274 (2015).Article 

Google Scholar 
Jacobs, D. S. Morphological divergence in an insular bat, Lasiurus cinereus semotus. Funct. Ecol. 10, 622–630 (1996).Article 

Google Scholar 
Baird, A. B. et al. Nuclear and mtDNA phylogenetic analyses clarify the evolutionary history of two species of native Hawaiian bats and the taxonomy of Lasiurini (Mammalia: Chiroptera). PLoS One 12, e0186085 (2017).Article 

Google Scholar 
Kumar, S. & Subramanian, S. Mutation rates in mammalian genomes. Proc. Natl. Acad. Sci. U.S.A. 99, 803–808 (2002).Article 
ADS 
CAS 

Google Scholar 
Gillespie, R. G. et al. Comparing adaptive radiations across space, time, and taxa. J. Hered. 111, 1–20 (2020).Article 

Google Scholar 
Fišer, C., Robinson, C. T. & Malard, F. Cryptic species as a window into the paradigm shift of the species concept. Mol. Ecol. 27, 613–635 (2018).Article 

Google Scholar 
Espíndola, A. et al. Identifying cryptic diversity with predictive phylogeography. Proc. R. Soc. B Biol. Sci. 283, 20161529 (2016).Article 

Google Scholar 
Padial, J. M., Miralles, A., De la Riva, I. & Vences, M. The integrative future of taxonomy. Front. Zool. 7, 1–14 (2010).Article 

Google Scholar 
Fujita, M. K., Leaché, A. D., Burbrink, F. T., McGuire, J. A. & Moritz, C. Coalescent-based species delimitation in an integrative taxonomy. Trends Ecol. Evol. 27, 480–488 (2012).Article 

Google Scholar 
Solari, S., Sotero-Caio, C. G. & Baker, R. J. Advances in systematics of bats: Towards a consensus on species delimitation and classifications through integrative taxonomy. J. Mammal. 100, 838–851 (2018).Article 

Google Scholar 
Mayr, E. Geographical character gradients and climatic adaptation. Evolution 10, 105–108 (1956).
Google Scholar 
Morales, A. E., De-la-Mora, M. & Piñero, D. Spatial and environmental factors predict skull variation and genetic structure in the cosmopolitan bat Tadarida brasiliensis. J. Biogeogr. 45, 1529–1540 (2018).Article 

Google Scholar 
Pavan, A. C. & Marroig, G. Integrating multiple evidences in taxonomy: Species diversity and phylogeny of mustached bats (Mormoopidae: Pteronotus). Mol. Phylogenet. Evol. 103, 184–198 (2016).Article 

Google Scholar 
Kozlov, A. M., Darriba, D., Flouri, T., Morel, B. & Stamatakis, A. RAxML-NG: A fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference. Bioinformatics 35, 4453–4455 (2019).Article 
CAS 

Google Scholar 
Robinson, D. & Foulds, L. Comparison of phylogenetic trees. Math. Biosci. 53, 131–147 (1981).Article 
MathSciNet 
MATH 

Google Scholar 
Pattengale, N. D., Alipour, M., Bininda-Emonds, O. R., Moret, B. M. & Stamatakis, A. How many bootstrap replicates are necessary?. J. Comput. Biol. 17, 337–354 (2010).Article 
MathSciNet 
CAS 

Google Scholar 
Lemoine, F. et al. Renewing Felsenstein’s phylogenetic bootstrap in the era of big data. Nature 556, 452–456 (2018).Article 
ADS 
CAS 

Google Scholar 
Ronquist, F. et al. MrBayes 3.2: Efficient Bayesian phylogenetic inference and model choice across a large model space. Syst. Biol. 61, 539–542 (2012).Article 

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

Google Scholar 
Kapli, P. et al. Multi-rate Poisson Tree Processes for single-locus species delimitation under Maximum Likelihood and Markov Chain Monte Carlo. Bioinformatics 33, 1630–1638 (2017).CAS 

Google Scholar 
Yang, Z. & Rannala, B. Unguided species delimitation using DNA sequence data from multiple loci. Mol. Biol. Evol. 31, 3125–3135 (2014).Article 
CAS 

Google Scholar 
Flouri, T., Jiao, X., Rannala, B. & Yang, Z. Species tree inference with BPP using genomic sequences and the multispecies coalescent. Mol. Biol. Evol. 35, 2585–2593 (2018).Article 
CAS 

Google Scholar 
Van Buuren, S. & Groothuis-Oudshoorn, K. Multivariate imputation by chained equations. J. Stat. Softw. 45, 1–67 (2011).Article 

Google Scholar 
Penone, C. et al. Imputation of missing data in life-history trait datasets: Which approach performs the best?. Methods Ecol. Evol. 5, 961–970 (2014).Article 

Google Scholar 
Berner, D. Size correction in biology: How reliable are approaches based on (common) principal component analysis?. Oecologia 166, 961–971 (2011).Article 
ADS 

Google Scholar 
Simmons, N. B. Order Chiroptera. In Mammal Species of the World: A Taxonomic and Geographic Reference (eds Wilson, D. E. & Reeder, D. M.) 312–529 (The John Hopkins University Press, 2005).
Google Scholar 
Wilson, D. E. & Mittermeier, R. A. Handbook of the Mammals of the World. Vol. 9. Bats (Lynx Editions, 2019).
Google Scholar 
R Core Team. R: A language and environment for statistical computing (2022).Kuhn, M. caret: Classification and Regression Training. R package version 6.0-86. https://CRAN.R-project.org/package=caret (2020).Venables, W. N. & Ripley, B. D. Modern Applied Statistics with S (Springer, 2002).Book 
MATH 

Google Scholar 
Kuhn, M. & Johnson, K. Applied Predictive Modeling (Springer, 2013).Book 
MATH 

Google Scholar 
Fick, S. E. & Hijmans, R. J. WorldClim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar 
Hijmans, R. J. raster: Geographic Data Analysis and Modeling (2022).Barker, B. S., Rodríguez-Robles, J. A. & Cook, J. A. Climate as a driver of tropical insular diversity: Comparative phylogeography of two ecologically distinctive frogs in Puerto Rico. Ecography 38, 769–781 (2015).Article 

Google Scholar 
Petitpierre, B., Broennimann, O., Kueffer, C., Daehler, C. & Guisan, A. Selecting predictors to maximize the transferability of species distribution models: Lessons from cross-continental plant invasions. Glob. Ecol. Biogeogr. 26, 275–287 (2017).Article 

Google Scholar 
Akinwande, M. O., Dikko, H. G. & Samson, A. Variance inflation factor: As a condition for the inclusion of suppressor variable(s) in regression analysis. Open J. Stat. 05, 754–767 (2015).Article 

Google Scholar 
Izenman, A. J. Linear discriminant analysis. in Modern Multivariate Statistical Techniques 237–280 (2013).Lever, J., Krzywinski, M. & Altman, N. Points of significance: Principal component analysis. Nat. Methods 14, 641–642 (2017).Article 
CAS 

Google Scholar 
Guisan, A., Petitpierre, B., Broennimann, O., Daehler, C. & Kueffer, C. Unifying niche shift studies: Insights from biological invasions. Trends Ecol. Evol. 29, 260–269 (2014).Article 

Google Scholar 
Di Cola, V. et al. ecospat: An R package to support spatial analyses and modeling of species niches and distributions. Ecography 40, 774–787 (2017).Article 

Google Scholar 
Broennimann, O. et al. Measuring ecological niche overlap from occurrence and spatial environmental data. Glob. Ecol. Biogeogr. 21, 481–497 (2012).Article 

Google Scholar 
Liu, C., Wolter, C., Xian, W. & Jeschke, J. M. Most invasive species largely conserve their climatic niche. Proc. Natl. Acad. Sci. 117, 23643–23651 (2020).Article 
ADS 
CAS 

Google Scholar 
Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: Quantitative approaches to niche evolution. Evolution 62, 2868–2883 (2008).Article 

Google Scholar 
Warren, D. L., Glor, R. E. & Turelli, M. ENMTools: A toolbox for comparative studies of environmental niche models. Ecography 33, 607–611 (2010).
Google Scholar  More