Ecology

CIAT Global Rural-Urban Mapping Project, v1 (GRUMPv1): Urban Extents Grid (NASA SEDAC, 2011).Global Status Report for Buildings and Construction: Towards a Zero-Emission, Efficient and Resilient Buildings and Construction Sector (UNEP, 2020).Harris, N. L. et al. Nat. Clim. Change 11, 234–240 (2021).Article 

Google Scholar 
Reid, W. V. et al. Ecosystems and Human Well-being: Biodiversity Synthesis (Millenium Ecosystem Assessment, World Resources Institute, 2005).Xu, C. et al. Resour. Conserv. Recycl. 151, 104478 (2019).Article 

Google Scholar 
Su, J., Friess, D. A. & Gasparatos, A. Nat. Commun. 12, 5050 (2021).CAS 
Article 

Google Scholar 
van den Berg, M. et al. Urban For. Urban Green. 14, 806–816 (2015).Article 

Google Scholar 
Aerts, R., Honnay, O. & Van Nieuwenhuyse, A. Br. Med. Bull. 127, 5–22 (2018).Article 

Google Scholar 
Lindenmayer, D. et al. Ecol. Lett. 11, 78–91 (2008).
Google Scholar 
Knapp, S., Jaganmohan, M. & Schwarz, N. in Atlas of Ecosystem Services: Drivers, Risks, and Societal Responses (eds Schröter, M. et al.) 167–172 (Springer, 2019).Kim, H. Y. Geomat. Nat. Hazards Risk 12, 1181–1194 (2021).Article 

Google Scholar 
Vargas-Hernández, J. G., Pallagst, K. & Zdunek-Wielgołaska, J. in Handbook of Engaged Sustainability (ed. Marques, J.) 885–916 (Springer, 2018).Manso, M. et al. Renew. Sustain. Energy Rev. 135, 110111 (2021).Article 

Google Scholar 
Assimakopoulos, M.-N. et al. Sustainability 12, 3772 (2020).CAS 
Article 

Google Scholar 
Mora-Melià, D. et al. Sustainability 10, 1130 (2018).Article 

Google Scholar 
IPBES. Curr. Opin. Environ. Sustain. 26, 7–16 (2017).
Google Scholar 
Schröpfer, T. & Menz, S. in Dense and Green Building Typologies: Research, Policy and Practice Perspectives (eds Schröpfer, T. & Menz, S.) 1–4 (Springer, 2019).Pedersen Zari, M. & Hecht, K. Biomimetics 5, 18 (2020).Article 

Google Scholar  More

IPCC Climate Change 2007: Synthesis Report (eds Pachauri, R. K. & Reisinger, A.) (IPCC, 2007).Boyd, J. & Banzhaf, S. Ecol. Econ. 63, 616–626 (2007).Article 

Google Scholar 
Ruhl, J. B. et al. Front. Ecol. Environ. 19, 519–525 (2021).Article 

Google Scholar 
Carleton, T. & Greenstone, M. Updating the United States Government’s Social Cost of Carbon Working Paper 2021-04 (Univ. Chicago, Becker Friedman Institute for Economics, 2021).Mandle, L. et al. Nat. Sustain. 4, 161–169 (2021).Article 

Google Scholar 
Druckenmiller, H. Estimating an Economic and Social Value of Forests: Evidence from Tree Mortality in the American West (Univ. California Berkeley, 2021).Burkett, V. R. et al. Ecol. Complexity 2, 357–394 (2005).Article 

Google Scholar 
Hanley, N. & Czajkowski, M. Rev. Environ. Econ. Policy 13, 248–266 (2019).Article 

Google Scholar 
Mendelsohn, R. Rev. Environ. Econ. Policy 13, 267–282 (2019).Article 

Google Scholar 
Fenichel, E. P. et al. Proc. Natl Acad. Sci. USA 113, 2382–2387 (2016).CAS 
Article 

Google Scholar 
Martin-Ortega, J. et al. Ecosyst. Serv. 50, 101327 (2021).Article 

Google Scholar 
Borrelli, P. et al. Proc. Natl Acad. Sci. USA 117, 21994–22001 (2020).CAS 
Article 

Google Scholar 
Tropek, R. et al. Science 344, 981–981 (2014).CAS 
Article 

Google Scholar 
Vardon, M., Burnett, P. & Dovers, S. Ecol. Econ. 124, 145–152 (2016).Article 

Google Scholar 
Bastien-Olvera, B. A. & Moore, F. C. Nat. Sustain. 4, 101–108 (2021).Article 

Google Scholar 
Beland, M. et al. For. Ecol. Manage. 450, 117484 (2019).Article 

Google Scholar 
Vargas, L., Willemen, L. & Hein, L. Environ. Manage. 63, 1–15 (2019).Article 

Google Scholar 
Hallgren, W. et al. Environ. Model. Softw. 76, 182–186 (2016).Article 

Google Scholar 
Rolf, E. et al. Nat. Commun. 12, 4392 (2021).CAS 
Article 

Google Scholar 
Chernozhukov, V. et al. NBER Working Paper 24678 (National Bureau of Economic Research, 2018). More

Pauly, D. Anecdotes and the shifting baseline syndrome of fisheries. Trends Ecol. Evol. 10, 430 (1995).CAS 
PubMed 

Google Scholar 
FAO. The State of World Fisheries and Aquaculture 2018—Meeting the Sustainable Development Goals. (2018).Teh, L. C. L. & Sumaila, U. R. Contribution of marine fisheries to worldwide employment. Fish Fish. 14, 77–88 (2013).
Google Scholar 
Halpern, B. S., Selkoe, K. A., Micheli, F. & Kappel, C. V. Evaluating and ranking the vulnerability of global marine ecosystems to anthropogenic threats. Conserv. Biol. 21, 1301–1315 (2007).PubMed 

Google Scholar 
Kaiser, M. J., Collie, J. S., Hall, S. J., Jennings, S. & Poiner, I. R. Modification of marine habitats by trawling activities: Prognosis and solutions. Fish Fish. 3, 114–136 (2002).
Google Scholar 
Hiddink, J. G. et al. Selection of indicators for assessing and managing the impacts of bottom trawling on seabed habitats. J. Appl. Ecol. 57, 1199–1209 (2020).
Google Scholar 
Funes, M., Marinao, C. & Galván, D. E. Does trawl fisheries affect the diet of fishes? A stable isotope analysis approach. Isotop. Environ. Health Stud. 10, 1–17 (2019).
Google Scholar 
Preciado, I. et al. Small-scale spatial variations of trawling impact on food web structure. Ecol. Ind. 98, 442–452 (2019).
Google Scholar 
Su, L. et al. Decadal-scale variation in mean trophic level in Beibu Gulf based on bottom-trawl survey data. Mar. Coast. Fish. 13, 174–182 (2021).
Google Scholar 
Jennings, S., van Hal, R., Hiddink, J. G. & Maxwell, T. A. D. Fishing effects on energy use by North Sea fishes. J. Sea Res. 60, 74–88 (2008).ADS 

Google Scholar 
de Ruiter, P. C., Neutel, A.-M. & Moore, J. C. Energetics, patterns of interaction strengths, and stability in real ecosystems. Science 269, 1257–1260 (1995).ADS 
PubMed 

Google Scholar 
Bascompte, J. Disentangling the web of life. Science 325, 416–419 (2009).ADS 
MathSciNet 
CAS 
PubMed 
MATH 

Google Scholar 
Wootton, K. L. Omnivory and stability in freshwater habitats: Does theory match reality?. Freshw. Biol. 62, 821–832 (2017).
Google Scholar 
Borrelli, J. J. & Ginzburg, L. R. Why there are so few trophic levels: Selection against instability explains the pattern. Food Webs 1, 10–17 (2014).
Google Scholar 
Stouffer, D. B. & Bascompte, J. Compartmentalization increases food-web persistence. Proc. Natl. Acad. Sci. USA 108, 3648–52 (2011).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Márquez-Velásquez, V., Raimundo, R. L. G., de Souza Rosa, R. & Navia, A. F. The use of ecological networks as tools for understanding and conserving marine biodiversity. In Marine Coastal Ecosystems Modelling and Conservation: Latin American Experiences, pp 179–202 (eds Ortiz, M. & Jordán, F.) (Springer, 2021). https://doi.org/10.1007/978-3-030-58211-1_9.Chapter 

Google Scholar 
Neutel, A.-M. & Thorne, M. A. S. Interaction strengths in balanced carbon cycles and the absence of a relation between ecosystem complexity and stability. Ecol. Lett. 17, 651–661 (2014).PubMed 
PubMed Central 

Google Scholar 
Neutel, A.-M. & Thorne, M. A. S. Beyond connectedness: Why pairwise metrics cannot capture community stability. Ecol. Evol. 6, 7199–7206 (2016).PubMed 
PubMed Central 

Google Scholar 
Saravia, L. A., Marina, T. I., Kristensen, N. P., De Troch, M. & Momo, F. R. Ecological network assembly: How the regional metaweb influences local food webs. J. Anim. Ecol. 3, 25 (2021).
Google Scholar 
Góngora, M. E., GonzalezZevallos, D., Pettovello, A. & Mendia, L. Caracterizacion de las principales pesquerias del golfo San Jorge Patagonia, Argentina. Latin Am. J. Aquat. Res. 40, 1–11 (2012).
Google Scholar 
Yorio, P. Marine protected areas, spatial scales, and governance: Implications for the conservation of breeding seabirds. Conserv. Lett. 2, 171–178 (2009).
Google Scholar 
Rincón-Díaz, M. P., Bovcon, N. D., Cochia, P. D., Góngora, M. E. & Galván, D. E. Fish functional diversity as an indicator of resilience to industrial fishing in Patagonia Argentina. J. Fish Biol. 99, 1650–1667 (2021).PubMed 

Google Scholar 
González-Zevallos, D. & Yorio, P. Consumption of discards and interactions between Black-browed Albatrosses (Thalassarche melanophrys) and Kelp Gulls (Larus dominicanus) at trawl fisheries in Golfo San Jorge, Argentina. J. Ornithol. 152, 827–838 (2011).
Google Scholar 
Vinuesa, J. H. & Varisco, M. Trophic ecology of the lobster krill Munida gregaria in San Jorge Gulf, Argentina. Investig. Mar. 35, 25–34 (2007).
Google Scholar 
Belleggia, M. et al. Trophic ecology of yellownose skate Zearaja chilensis, a top predator in the south-western Atlantic Ocean. J. Fish Biol. 88, 1070–1087 (2016).CAS 
PubMed 

Google Scholar 
Pasti, A. T. et al. The diet of Mustelus schmitti in areas with and without commercial bottom trawling (Central Patagonia, Southwestern Atlantic): Is it evidence of trophic interaction with the Patagonian shrimp fishery?. Food Webs 29, e00214 (2021).
Google Scholar 
Yorio, P., Bertellotti, M., Gandini, P. & Frere, E. Kelp gulls Larus dominicanus breeding on the argentine coast: Population status and relationship with coastal management and conservation. Mar. Ornithol. 26, 11–18 (1998).
Google Scholar 
Dans, S. et al. El golfo san jorge como área prioritaria de investigación, manejo y conservación en el marco de la iniciativa pampa azul. Rev. Cie. Investig. 71, 21–43 (2021).
Google Scholar 
de la Garza, J. M., Ferníndez, M. & Ravalli, C. Langostino patagónico (Pleoticus muelleri). Inf. Campa 20, 20 (2013).
Google Scholar 
Varisco, M. & La Vinuesa, J. H. Alimentación de Munida gregaria (Fabricius, 1793) (Crustacea:Anomura:Galatheidae) en fondos de pesca del Golfo San Jorge, Argentina. Rev. Biol. Mar. Oceanogr. 42, 221–229 (2007).
Google Scholar 
Tschopp, A., Cristiani, F., García, N. A., Crespo, E. A. & Coscarella, M. A. Trophic niche partitioning of five skate species of genus Bathyraja in northern and central Patagonia, Argentina. J. Fish. Biol. 97, 656–667 (2020).PubMed 

Google Scholar 
Kasinsky, T., Yorio, P., Dell’Arciprete, P., Marinao, C. & Suárez, N. Geographical differences in sex-specific foraging behaviour and diet during the breeding season in the opportunistic Kelp Gull (Larus dominicanus). Mar. Biol. 168, 14 (2021).CAS 

Google Scholar 
González-Zevallos, D. & Yorio, P. Seabird use of discards and incidental captures at the Argentine hake trawl fishery in the Golfo San Jorge, Argentina. Mar. Ecol. Progress Ser. 316, 175–183 (2006).ADS 

Google Scholar 
Crespo, E. A. et al. Direct and indirect effects of the Highseas fisheries on the marine mammal populations in the northern and central Patagonian coast. J. Northw. Atl. Fish. Sci. 22, 189–207 (1997).
Google Scholar 
Gandini, P. A., Frere, E., Pettovello, A. D. & Cedrola, P. V. Interaction between Magellanic Penguins and Shrimp Fisheries in Patagonia, Argentina. Condor 101, 783–789 (1999).
Google Scholar 
Fu, C. et al. Making ecological indicators management ready: Assessing the specificity, sensitivity, and threshold response of ecological indicators. Ecol. Ind. 105, 16–28 (2019).
Google Scholar 
Olivier, P. et al. Exploring the temporal variability of a food web using long-term biomonitoring data. Ecography 42, 2107–2121 (2019).
Google Scholar 
Bersier, L.-F., Banašek-Richter, C. & Cattin, M.-F. Quantitative descriptors of food-web matrices. Ecology 83, 2394–2407 (2002).MATH 

Google Scholar 
Gellner, G. & McCann, K. Reconciling the omnivory-stability debate. Am. Nat. 179, 22–37 (2012).PubMed 

Google Scholar 
Newman, M. E. J. & Girvan, M. Finding and evaluating community structure in networks. Phys. Rev. E 69, 26113 (2004).ADS 
CAS 

Google Scholar 
Reichardt, J. & Bornholdt, S. Statistical mechanics of community detection. Phys. Rev. E 74, 16110 (2006).ADS 
MathSciNet 

Google Scholar 
Allesina, S. & Pascual, M. Network structure, predator-prey modules, and stability in large food webs. Theor. Ecol. 1, 55–64 (2008).
Google Scholar 
Strona, G., Nappo, D., Boccacci, F., Fattorini, S. & San-Miguel-Ayanz, J. A fast and unbiased procedure to randomize ecological binary matrices with fixed row and column totals. Nat. Commun. 5, 4114 (2014).ADS 
CAS 
PubMed 

Google Scholar 
Scholz, F. W. & Stephens, M. A. K-sample Anderson–Darling tests. J. Am. Stat. Assoc. 82, 918–924 (1987).MathSciNet 

Google Scholar 
Lakens, D. Calculating and reporting effect sizes to facilitate cumulative science: A practical primer for t-tests and ANOVAs. Front. Psychol. 4, 863 (2013).PubMed 
PubMed Central 

Google Scholar 
Saravia, L. A. Multiweb: An R Package for Multiple Interaction Ecological Networks (Zenodo, 2019). https://doi.org/10.5281/zenodo.3370397.Book 

Google Scholar 
Kortsch, S. et al. Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning. J. Anim. Ecol. 20, 20 (2021).
Google Scholar 
Marina, T. I. et al. Architecture of marine food webs: To be or not be a “small-world’’. PLoS One 13, 1–13 (2018).
Google Scholar 
Panel, E. P. A. Ecosystem-based Fishery Management: A Report to Congress by the Ecosystem Principles Advisory Panel. https://repository.library.noaa.gov/view/noaa/23730 (1998)Armoškaitė, A. et al. Establishing the links between marine ecosystem components, functions and services: An ecosystem service assessment tool. Ocean Coast. Manage. 193, 105229 (2020).
Google Scholar 
Navia, A. F., Cruz-Escalona, V. H., Giraldo, A. & Barausse, A. The structure of a marine tropical food web, and its implications for ecosystem-based fisheries management. Ecol. Model. 328, 23–33 (2016).
Google Scholar 
Agnetta, D. et al. Benthic-pelagic coupling mediates interactions in Mediterranean mixed fisheries: An ecosystem modeling approach. PLoS One 14, e0210659 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Baum, J. K. et al. Collapse and conservation of shark populations in the Northwest Atlantic. Sciencehttps://doi.org/10.1126/science.1079777 (2003).Article 
PubMed 

Google Scholar 
Bearzi, G. et al. Overfishing and the disappearance of short-beaked common dolphins from western Greece. Endang. Species Res. 5, 1–12 (2008).
Google Scholar 
Lotze, H. K., Coll, M., Magera, A. M., Ward-Paige, C. & Airoldi, L. Recovery of marine animal populations and ecosystems. Trends Ecol. Evol. 26, 595–605 (2011).PubMed 

Google Scholar 
Reyes, L. M. Cetaceans of Central Patagonia, Argentina. Aquat. Mammals 32, 20–30 (2006).
Google Scholar 
Lisnizer, N., Garcia-Borboroglu, P. & Yorio, P. Spatial and temporal variation in population trends of Kelp Gulls in northern Patagonia, Argentina. Emu Austral Ornithol. 111, 259–267 (2011).
Google Scholar 
Yorio, P. et al. Population trends of Imperial Cormorants (Leucocarbo atriceps) in northern coastal Argentine Patagonia over 26 years. Emu Austral Ornithol. 120, 114–122 (2020).
Google Scholar 
Irigoyen, A. & Trobbiani, G. Depletion of trophy large-sized sharks populations of the Argentinean coast, south-western Atlantic: Insights from fishers’ knowledge. Neotrop. Ichthyol. 14, 20 (2016).
Google Scholar 
Vasas, V., Lancelot, C., Rousseau, V. & Jordán, F. Eutrophication and overfishing in temperate nearshore pelagic food webs: A network perspective. Mar. Ecol. Prog. Ser. 336, 1–14 (2007).ADS 
CAS 

Google Scholar 
Gilarranz, L. J., Mora, C. & Bascompte, J. Anthropogenic effects are associated with a lower persistence of marine food webs. Nat. Commun. 7, 10737 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Bartley, T. J. et al. Food web rewiring in a changing world. Nat. Ecol. Evol. 3, 345–354 (2019).PubMed 

Google Scholar 
May, R. M. Stability and Complexity in Model Ecosystems Vol. 6 (Princeton University Press, 1974).
Google Scholar 
McCann, K. S. The diversity-stability debate. Nature 405, 228–233 (2000).CAS 
PubMed 

Google Scholar 
van Altena, C., Hemerik, L. & de Ruiter, P. C. Food web stability and weighted connectance: The complexity-stability debate revisited. Theor. Ecol. 9, 49–58 (2016).
Google Scholar 
Dougoud, M., Vinckenbosch, L., Rohr, R. P., Bersier, L.-F. & Mazza, C. The feasibility of equilibria in large ecosystems: A primary but neglected concept in the complexity-stability debate. PLoS Comput. Biol. 14, e1005988 (2018).PubMed 
PubMed Central 

Google Scholar 
McCann, K. & Hastings, A. Re-evaluating the omnivory-stability relationship in food webs. Proc. R. Soc. Lond. B 264, 1249–1254 (1997).ADS 

Google Scholar 
Pimm, S. L. & Lawton, J. H. On feeding on more than one trophic level. Nature 275, 542–544 (1978).ADS 

Google Scholar 
Link, J. Does food web theory work for marine ecosystems?. Mar. Ecol. Prog. Ser. 230, 1–9 (2002).ADS 

Google Scholar 
Bieg, C. et al. Linking humans to food webs: A framework for the classification of global fisheries. Front. Ecol. Environ. 16, 412–420 (2018).
Google Scholar 
Shephard, S. et al. Scavenging on trawled seabeds can modify trophic size structure of bottom-dwelling fish. ICES J. Mar. Sci. 71, 398–405 (2014).
Google Scholar 
Gilarranz, L. J., Rayfield, B., Liñán-Cembrano, G., Bascompte, J. & Gonzalez, A. Effects of network modularity on the spread of perturbation impact in experimental metapopulations. Science 357, 199–201 (2017).ADS 
CAS 
PubMed 

Google Scholar 
Danet, A., Mouchet, M., Bonnaffé, W., Thébault, E. & Fontaine, C. Species richness and food-web structure jointly drive community biomass and its temporal stability in fish communities. Ecol. Lett. 24, 2364–2377 (2021).PubMed 

Google Scholar 
Shanafelt, D. W. & Loreau, M. Stability trophic cascades in food chains. R. Soc. Open Sci. 5, 180995 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Barbier, M. & Loreau, M. Pyramids and cascades: A synthesis of food chain functioning and stability. Ecol. Lett. 22, 405–419 (2019).PubMed 

Google Scholar 
Sánchez, M. F. et al. Caracterización ecológica del Golfo San Jorge (Argentina) mediante modelación ecotrófica multiespecífica. 30 https://www.inidep.edu.ar/wordpress/?page_id=1959 (2009)Gaitán, E. N. Tramas Tróficas en Sistemas Frontales del Mar Argentino: Estructura, Dinámica y Complejidad Analizada Mediante Isótopos Estables (Universidad Nacional de Mar del Plata, Facultad de Ciencias Exactas y Naturales, 2012).
Google Scholar 
Pinnegar, J. K. & Polunin, N. V. C. Differential fractionation of 13C and 15N among fish tissues: Implications for the study of trophic interactions. Funct. Ecol. 13, 225–231 (1999).
Google Scholar 
Philippsen, J. S. & Benedito, E. Discrimination factor in the trophic ecology of fishes: A review about sources of variation and methods to obtain it. Oecol. Aust. 17, 205–2016 (2013).
Google Scholar 
Hussey, N. E. et al. Rescaling the trophic structure of marine food webs. Ecol. Lett. 17, 239–250 (2014).PubMed 

Google Scholar 
Lefebvre, S. & Dubois, S. The stony road to understand isotopic enrichment and turnover rates: Insight into the metabolic part. Vie Milieu-life Environ. 66, 305–314 (2016).
Google Scholar 
Funes, M., Irigoyen, A. J., Trobbiani, G. A. & Galván, D. E. Stable isotopes reveal different dependencies on benthic and pelagic pathways between Munida gregaria ecotypes. Food Webs 17, e00101 (2018).
Google Scholar 
Santos, B. & Villarino, M. F. Evaluación del Estado de Explotación del Efectivo sur de 41 S de la Merluza (Merluccius hubbsi) y Estimación de la Captura Biológicamente Aceptable Para 2014. Informe Técnico Oficial INIDEP. 1–30 (2013).Belleggia, M., Giberto, D. & Bremec, C. Adaptation of diet in a changed environment: Increased consumption of lobster krill Munida gregaria (Fabricius, 1793) by Argentine hake. Mar. Ecol. 38, e12445 (2017).ADS 

Google Scholar 
Diez, M. J., Cabreira, A. G., Madirolas, A. & Lovrich, G. A. Hydroacoustical evidence of the expansion of pelagic swarms of Munida gregaria (Decapoda, Munididae) in the Beagle Channel and the Argentine Patagonian Shelf, and its relationship with habitat features. J. Sea Res. 114, 1–12 (2016).ADS 

Google Scholar 
Ravalli, C., De La Garza, J. & Greco, L. L. Distribución de los morfotipos gregaria y subrugosa de la langostilla Munida gregaria (Decapoda, Galatheidae) en el Golfo San Jorge en la campaña de verano AE-01/2011. Integración de resultados con las campañas 2009 y 2010. Rev. Invest. Desarr. Pesq. 22, 29–41 (2013).
Google Scholar 
Belleggia, M. et al. Are hakes truly opportunistic feeders? A case of prey selection by the Argentine hake Merluccius hubbsi off southwestern Atlantic. Fish. Res. 214, 166–174 (2019).
Google Scholar 
Roux, A., Piñero, R., Moriondo, P. & Fernández, M. Diet of the red shrimp Pleoticus muelleri (Bate, 1888) in Patagonian fishing grounds, Argentine. Rev. Biol. Mar. Oceanogr. 44, 25 (2009).
Google Scholar 
de la Garza, J. et al. An Overview of the Argentine Red Shrimp (Pleoticus muelleri, Decapoda, Solenoceridae) Fishery in Argentina: Biology, Fishing, Management and Ecological Interactions (Instituto Nacional de Investigación y Desarrollo Pesquero (INIDEP), 2017).
Google Scholar 
Sánchez, M. F. & Prenski, L. B. Ecología trófica de peces demersales en el Golfo San Jorge. Trophic Ecol. Demersal Fish San Jorge Gulf 10, 57–71 (1996).
Google Scholar 
Copello, S., Quintana, F. & Pérez, F. Diet of the southern giant petrel in Patagonia: Fishery-related items and natural prey. Endang. Species Res. 6, 15–23 (2008).
Google Scholar 
Alonso, R. B. et al. The opportunistic sense: The diet of Argentine hake Merluccius hubbsi reflects changes in prey availability. Region. Stud. Mar. Sci. 27, 100540 (2019).
Google Scholar 
Marón, C. F. et al. Increased wounding of southern right whale (Eubalaena australis) calves by kelp gulls (Larus dominicanus) at Península Valdés, Argentina. PLoS One 10, e0139291 (2015).PubMed 
PubMed Central 

Google Scholar 
Fazio, A., Argüelles, M. B. & Bertellotti, M. Change in southern right whale breathing behavior in response to gull attacks. Mar. Biol. 162, 267–273 (2015).
Google Scholar 
Pocock, M. J. O., Evans, D. M. & Memmott, J. The robustness and restoration of a network of ecological networks. Science 335, 973–977 (2012).ADS 
CAS 
PubMed 

Google Scholar 
Kéfi, S. et al. Network structure beyond food webs: Mapping non-trophic and trophic interactions on Chilean rocky shores. Ecology 96, 291–303 (2015).
Google Scholar 
Mougi, A. The roles of amensalistic and commensalistic interactions in large ecological network stability. Sci. Rep. 6, 29929 (2016).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Mougi, A. & Kondoh, M. Diversity of interaction types and ecological community stability. Science 337, 349–351 (2012).ADS 
MathSciNet 
CAS 
PubMed 
MATH 

Google Scholar 
Kéfi, S., Miele, V., Wieters, E. A., Navarrete, S. A. & Berlow, E. L. How structured is the entangled bank? The surprisingly simple organization of multiplex ecological networks leads to increased persistence and resilience. PLoS Biol. 14, e1002527 (2016).PubMed 
PubMed Central 

Google Scholar  More

May, R. M. Biological populations with nonoverlapping generations: stable points, stable cycles, and chaos. Science 186, 645–647 (1974).CAS 
PubMed 
Article 

Google Scholar 
Beddington, J. R., Free, C. A. & Lawton, J. H. Dynamic complexity in predator–prey models framed in difference equations. Nature 255, 58–60 (1975).Article 

Google Scholar 
Hastings, A., Hom, C. L., Ellner, S., Turchin, P. & Godfray, H. C. J. Chaos in ecology: is Mother Nature a strange attractor? Annu. Rev. Ecol. Syst. 24, 1–33 (1993).Article 

Google Scholar 
Cressie, N. & Wikle, C. K. Statistics for Spatio-Temporal Data (John Wiley & Sons, 2011).The State of World Fisheries and Aquaculture 2020 (FAO, 2020).Hastings, A. & Powell, T. Chaos in a three-species food chain. Ecology 72, 896–903 (1991).Article 

Google Scholar 
Huisman, J. & Weissing, F. J. Biodiversity of plankton by species oscillations and chaos. Nature 402, 407–410 (1999).Article 

Google Scholar 
Doebeli, M. & Ispolatov, I. Chaos and unpredictability in evolution. Evolution 68, 1365–1373 (2014).PubMed 
Article 

Google Scholar 
Pearce, M. T., Agarwala, A. & Fisher, D. S. Stabilization of extensive fine-scale diversity by ecologically driven spatiotemporal chaos. Proc. Natl Acad. Sci. USA 117, 14572–14583 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Costantino, R. F., Desharnais, R. A., Cushing, J. M. & Dennis, B. Chaotic dynamics in an insect population. Science 275, 389–391 (1997).CAS 
PubMed 
Article 

Google Scholar 
Becks, L., Hilker, F. M., Malchow, H., Jürgens, K. & Arndt, H. Experimental demonstration of chaos in a microbial food web. Nature 435, 1226–1229 (2005).CAS 
PubMed 
Article 

Google Scholar 
Benincá, E. et al. Chaos in a long-term experiment with a plankton community. Nature 451, 822–825 (2008).PubMed 
Article 
CAS 

Google Scholar 
Tilman, D. & Wedin, D. Oscillations and chaos in the dynamics of a perennial grass. Nature 353, 653–655 (1991).Article 

Google Scholar 
Turchin, P. & Ellner, S. P. Living on the edge of chaos: population dynamics of fennoscandian voles. Ecology 81, 3099–3116 (2000).Article 

Google Scholar 
Ferrari, M. J. et al. The dynamics of measles in sub-Saharan Africa. Nature 451, 679–684 (2008).CAS 
PubMed 
Article 

Google Scholar 
Benincà, E., Ballantine, B., Ellner, S. P. & Huisman, J. Species fluctuations sustained by a cyclic succession at the edge of chaos. Proc. Natl Acad. Sci. USA 112, 6389–6394 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Hassell, M. P., Lawton, J. H. & May, R. M. Patterns of dynamical behaviour in single-species populations. J. Anim. Ecol. 45, 471–486 (1976).Article 

Google Scholar 
Sibly, R. M., Barker, D., Hone, J. & Pagel, M. On the stability of populations of mammals, birds, fish and insects. Ecol. Lett. 10, 970–976 (2007).PubMed 
Article 

Google Scholar 
Shelton, A. O. & Mangel, M. Fluctuations of fish populations and the magnifying effects of fishing. Proc. Natl Acad. Sci USA. 108, 7075–7080 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Salvidio, S. Stability and annual return rates in amphibian populations. Amphib. Reptil. 32, 119–124 (2011).Article 

Google Scholar 
Snell, T. W. & Serra, M. Dynamics of natural rotifer populations. Hydrobiologia 368, 29–35 (1998).Article 

Google Scholar 
Gross, T., Ebenhöh, W. & Feudel, U. Long food chains are in general chaotic. Oikos 109, 135–144 (2005).Article 

Google Scholar 
Ispolatov, I., Madhok, V., Allende, S. & Doebeli, M. Chaos in high-dimensional dissipative dynamical systems. Sci. Rep. 5, 12506 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Clark, T. J. & Luis, A. D. Nonlinear population dynamics are ubiquitous in animals. Nat. Ecol. Evol. 4, 75–81 (2020).CAS 
PubMed 
Article 

Google Scholar 
Sivakumar, B., Berndtsson, R., Olsson, J. & Jinno, K. Evidence of chaos in the rainfall-runoff process. Hydrol. Sci. J. 46, 131–145 (2001).CAS 
Article 

Google Scholar 
Hanski, I., Turchin, P., Korpimäki, E. & Henttonen, H. Population oscillations of boreal rodents: regulation by mustelid predators leads to chaos. Nature 364, 232–235 (1993).CAS 
PubMed 
Article 

Google Scholar 
Turchin, P. & Taylor, A. D. Complex dynamics in ecological time series. Ecology 73, 289–305 (1992).Article 

Google Scholar 
Munch, S. B., Brias, A., Sugihara, G. & Rogers, T. L. Frequently asked questions about nonlinear dynamics and empirical dynamic modelling. ICES J. Mar. Sci. 77, 1463–1479 (2020).Article 

Google Scholar 
Sugihara, G. & May, R. M. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature 344, 734–741 (1990).CAS 
PubMed 
Article 

Google Scholar 
Ellner, S. P. & Turchin, P. Chaos in a noisy world: new methods and evidence from time-series analysis. Am. Nat. 145, 343–375 (1995).Article 

Google Scholar 
Nychka, D., Ellner, S., Gallant, A. R. & McCaffrey, D. Finding chaos in noisy systems. J. R. Stat. Soc. B 54, 399–426 (1992).
Google Scholar 
Webber, C. L. & Zbilut, J. P. Dynamical assessment of physiological systems and states using recurrence plot strategies. J. Appl. Physiol. 76, 965–973 (1994).PubMed 
Article 

Google Scholar 
Bandt, C. & Pompe, B. Permutation entropy: a natural complexity measure for time series. Phys. Rev. Lett. 88, 174102 (2002).PubMed 
Article 
CAS 

Google Scholar 
Luque, B., Lacasa, L., Ballesteros, F. & Luque, J. Horizontal visibility graphs: exact results for random time series. Phys. Rev. E 80, 46103 (2009).CAS 
Article 

Google Scholar 
Toker, D., Sommer, F. T. & D’Esposito, M. A simple method for detecting chaos in nature. Commun. Biol. 3, 11 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pikovsky, A. & Politi, A. Lyapunov Exponents: A Tool to Explore Complex Dynamics (Cambridge Univ. Press, 2016).Rosenstein, M. T., Collins, J. J. & De Luca, C. J. A practical method for calculating largest Lyapunov exponents from small data sets. Physica D 65, 117–134 (1993).Article 

Google Scholar 
Dämmig, M. & Mitschke, F. Estimation of Lyapunov exponents from time series: the stochastic case. Phys. Lett. A 178, 385–394 (1993).Article 

Google Scholar 
Prendergast, J., Bazeley-White, E., Smith, O., Lawton, J. & Inchausti, P. The Global Population Dynamics Database (KNB, 2010); https://doi.org/10.5063/F1BZ63Z8Thibaut, L. M. & Connolly, S. R. Hierarchical modeling strengthens evidence for density dependence in observational time series of population dynamics. Ecology 101, e02893 (2020).PubMed 
Article 

Google Scholar 
Knape, J. & de Valpine, P. Are patterns of density dependence in the Global Population Dynamics Database driven by uncertainty about population abundance? Ecol. Lett. 15, 17–23 (2012).PubMed 
Article 

Google Scholar 
Takens, F. in Dynamical Systems and Turbulence (eds Rand, D. A. & Young, L. S.) 366–381 (Springer, 1981).Sugihara, G. Nonlinear forecasting for the classification of natural time series. Philos. Trans. R. Soc. A 348, 477–495 (1994).
Google Scholar 
Loh, J. et al. The Living Planet Index: using species population time series to track trends in biodiversity. Philos. Trans. R. Soc. B 360, 289–295 (2005).Article 

Google Scholar 
Kendall, B. E. Cycles chaos, and noise in predator–prey dynamics. Chaos Solitons Fractals 12, 321–332 (2001).Article 

Google Scholar 
Anderson, C. N. K. et al. Why fishing magnifies fluctuations in fish abundance. Nature 452, 835–839 (2008).CAS 
PubMed 
Article 

Google Scholar 
Anderson, D. M. & Gillooly, J. F. Allometric scaling of Lyapunov exponents in chaotic populations. Popul. Ecol. 62, 364–369 (2020).Article 

Google Scholar 
Graham, D. W. et al. Experimental demonstration of chaotic instability in biological nitrification. ISME J. 1, 385–393 (2007).CAS 
PubMed 
Article 

Google Scholar 
Turchin, P. Nonlinear time-series modeling of vole population fluctuations. Res. Popul. Ecol. 38, 121–132 (1996).Article 

Google Scholar 
Becks, L. & Arndt, H. Different types of synchrony in chaotic and cyclic communities. Nat. Commun. 4, 1359 (2013).PubMed 
Article 
CAS 

Google Scholar 
Becks, L. & Arndt, H. Transitions from stable equilibria to chaos, and back, in an experimental food web. Ecology 89, 3222–3226 (2008).PubMed 
Article 

Google Scholar 
Rezende, E. L., Albert, E. M., Fortuna, M. A. & Bascompte, J. Compartments in a marine food web associated with phylogeny, body mass, and habitat structure. Ecol. Lett. 12, 779–788 (2009).PubMed 
Article 

Google Scholar 
Krause, A. E., Frank, K. A., Mason, D. M., Ulanowicz, R. E. & Taylor, W. W. Compartments revealed in food-web structure. Nature 426, 282–285 (2003).CAS 
PubMed 
Article 

Google Scholar 
The IUCN Red List of Threatened Species Version 2020-2 (IUCN, 2020); https://www.iucnredlist.orgFreckleton, R. P. & Watkinson, A. R. Are weed population dynamics chaotic? J. Appl. Ecol. 39, 699–707 (2002).Article 

Google Scholar 
May, R. M. Simple mathematical models with very complicated dynamics. Nature 261, 459–467 (1976).CAS 
PubMed 
Article 

Google Scholar 
Mora, C., Tittensor, D. P., Adl, S., Simpson, A. G. B. & Worm, B. How many species are there on Earth and in the ocean? PLoS Biol. 9, e1001127 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Munch, S. B., Giron-Nava, A. & Sugihara, G. Nonlinear dynamics and noise in fisheries recruitment: a global meta-analysis. Fish Fish. 19, 964–973 (2018).Article 

Google Scholar 
Boettiger, C., Harte, T., Chamberlain, S. & Ram, K. rgpdd: R Interface to the Global Population Dynamics Database. https://docs.ropensci.org/rgpdd, https://github.com/ropensci/rgpdd (2019).Brook, B. W., Traill, L. W. & Bradshaw, C. J. A. Minimum viable population sizes and global extinction risk are unrelated. Ecol. Lett. 9, 375–382 (2006).PubMed 
Article 

Google Scholar 
Baars, J. W. M. Autecological investigations of marine diatoms, 2. Generation times of 50 species. Hydrobiol. Bull. 15, 137–151 (1981).Article 

Google Scholar 
Lavigne, A. S., Sunesen, I. & Sar, E. A. Morphological, taxonomic and nomenclatural analysis of species of Odontella, Trieres and Zygoceros (Triceratiaceae, Bacillariophyta) from Anegada Bay (Province of Buenos Aires, Argentina). Diatom Res. 30, 307–331 (2015).Article 

Google Scholar 
Anderson, D. M. & Gillooly, J. F. Physiological constraints on long-term population cycles: a broad-scale view. Evol. Ecol. Res. 18, 693–707 (2017).
Google Scholar 
Janes, M. J. Oviposition studies on the chinch bug, Blissus leucopterus (Say). Ann. Entomol. Soc. Am. 28, 109–120 (1935).Article 

Google Scholar 
Cook, L. M. Food-plant specialization in the moth Panaxia dominula L. Evolution 15, 478–485 (1961).Article 

Google Scholar 
Casey, T. M. Flight energetics of sphinx moths: power input during hovering flight. J. Exp. Biol. 64, 529–543 (1976).CAS 
PubMed 
Article 

Google Scholar 
Kobayashi, A., Tanaka, Y. & Shimada, M. Genetic variation of sex allocation in the parasitoid wasp Heterospilus prosopidis. Evolution 57, 2659–2664 (2003).PubMed 
Article 

Google Scholar 
Hozumi, N. & Miyatake, T. Body-size dependent difference in death-feigning behavior of adult Callosobruchus chinensis. J. Insect Behav. 18, 557–566 (2005).Article 

Google Scholar 
Huntley, M. E. & Lopez, M. D. G. Temperature-dependent production of marine copepods: a global synthesis. Am. Nat. 140, 201–242 (1992).CAS 
PubMed 
Article 

Google Scholar 
Cohen, R. E. & Lough, R. G. Length–weight relationships for several copepods dominant in the Georges Bank–Gulf of Maine area. J. Northwest Atl. Fish. Sci. 2, 47–52 (1981).Article 

Google Scholar 
World Register of Marine Species (WoRMS, accessed 1 November 2020); https://doi.org/10.14284/170Nakamura, Y. Growth and grazing of a large heterotrophic dinoflagellate, Noctiluca scintillans, in laboratory cultures. J. Plankton Res. 20, 1711–1720 (1998).Article 

Google Scholar 
Boulding, E. G. & Platt, T. Variation in photosynthetic rates among individual cells of a marine dinoflagellate. Mar. Ecol. Prog. Ser. 29, 199–203 (1986).CAS 
Article 

Google Scholar 
Rimet, F. et al. The Observatory on LAkes (OLA) database: sixty years of environmental data accessible to the public. J. Limnol. https://doi.org/10.4081/jlimnol.2020.1944 (2020).Rudstam, L. Zooplankton Survey of Oneida Lake, New York, 1964 to Present (KNB, 2020); https://knb.ecoinformatics.org/view/kgordon.17.99https://knb.ecoinformatics.org/knb/metacat/kgordon.17.67/defaultDumont, H. J., Van de Velde, I. & Dumont, S. The dry weight estimate of biomass in a selection of Cladocera, Copepoda and Rotifera from the plankton, periphyton and benthos of continental waters. Oecologia 19, 75–97 (1975).PubMed 
Article 

Google Scholar 
Geller, W. & Müller, H. Seasonal variability in the relationship between body length and individual dry weight as related to food abundance and clutch size in two coexisting Daphnia species. J. Plankton Res. 7, 1–18 (1985).Article 

Google Scholar 
Branstrator, D. K. Contrasting life histories of the predatory cladocerans Leptodora kindtii and Bythotrephes longimanus. J. Plankton Res. 27, 569–585 (2005).Article 

Google Scholar 
Rosen, R. A. Length–dry weight relationships of some freshwater zooplankton. J. Freshw. Ecol. 1, 225–229 (1981).Article 

Google Scholar 
Peters, R. H. & Downing, J. A. Empirical analysis of zooplankton filtering and feeding rates. Limnol. Oceanogr. 29, 763–784 (1984).Article 

Google Scholar 
Eckmann, J. P., Kamphorst, S. O. & Ruelle, D. Recurrence plots of dynamical systems. Europhys. Lett. 4, 973–977 (1987).Article 

Google Scholar 
Luque, B., Lacasa, L., Ballesteros, F. J. & Robledo, A. Analytical properties of horizontal visibility graphs in the Feigenbaum scenario. Chaos 22, 013109 (2012).PubMed 
Article 

Google Scholar 
McCaffrey, D. F., Ellner, S., Gallant, A. R. & Nychka, D. W. Estimating the Lyapunov exponent of a chaotic system with nonparametric regression. J. Am. Stat. Assoc. 87, 682–695 (1992).Article 

Google Scholar 
Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).Article 

Google Scholar 
Ricker, W. E. Stock and recruitment. J. Fish. Board Can. 11, 559–623 (1954).Article 

Google Scholar  More

Presence of mucin stabilizes survival of both the bacterium and the phage during 16 weeks of co-cultureAn overview of our main experimental setup is shown in Fig. 1. To avoid population bottlenecks, our sampling was based on the weekly collecting 20% of the cultures and replacing with the same volume of fresh medium. Long term co-existence of both F. columnare B245 and its phage V156 was observed in all treatments. In lake water with (LW + M) or without mucin (LW), the closest approximations of natural conditions for F. columnare, the phage titers remained similar until week 9, after which LW + M showed a significant decline in phage numbers compared to LW (LM, t1,46 = −2.737, P = 0.0088) with roughly a ten-fold difference at week 16 (Fig. 2a, Supplementary Fig. 1a). Bacterial population densities in these treatments were opposite and more dramatic, with an average of 45-fold higher numbers in LW + M than in LM across all time points after an initial spike at week 1 (LM, t1,77 = 4.836, P  More

Daims H, Lücker S, Wagner M. A new perspective on microbes formerly known as nitrite-oxidizing bacteria. Trends Microbiol. 2016;24:699–712.CAS 
Article 

Google Scholar 
Ehrich S, Behrens D, Lebedeva E, Ludwig W, Bock E. A new obligately chemolithoautotrophic, nitrite-oxidizing bacterium, Nitrospira moscoviensis sp. nov. and its phylogenetic relationship. Arch Microbiol. 1995;164:16–23.CAS 
Article 

Google Scholar 
Koch H, Galushko A, Albertsen M, Schintlmeister A, Gruber-Dorninger C, Lücker S, et al. Growth of nitrite-oxidizing bacteria by aerobic hydrogen oxidation. Science. 2014;345:1052–4.CAS 
Article 

Google Scholar 
Koch H, Lücker S, Albertsen M, Kitzinger K, Herbold C, Spieck E, et al. Expanded metabolic versatility of ubiquitous nitrite-oxidizing bacteria from the genus Nitrospira. Proc Natl Acad Sci USA. 2015;112:11371–6.CAS 
Article 

Google Scholar 
Daims H, Lebedeva EV, Pjevac P, Han P, Herbold C, Albertsen M, et al. Complete nitrification by Nitrospira bacteria. Nature. 2015;528:504–9.CAS 
Article 

Google Scholar 
van Kessel MAHJ, Speth DR, Albertsen M, Nielsen PH, Op den Camp HJM, Kartal B, et al. Complete nitrification by a single microorganism. Nature. 2015;528:555–9.Article 

Google Scholar 
Lücker S, Wagner M, Maixner F, Pelletier E, Koch H, Vacherie B, et al. A Nitrospira metagenome illuminates the physiology and evolution of globally important nitrite-oxidizing bacteria. Proc Natl Acad Sci USA. 2010;107:13479–84.Article 

Google Scholar 
Mundinger AB, Lawson CE, Jetten MSM, Koch H, Lücker S. Cultivation and transcriptional analysis of a canonical Nitrospira under stable growth conditions. Front Microbiol. 2019;10:1325.Morita RY. Is H2 the universal energy source for long-term survival? Micro Ecol. 1999;38:307–20.CAS 
Article 

Google Scholar 
Bay SK, Dong X, Bradley JA, Leung PM, Grinter R, Jirapanjawat T, et al. Trace gas oxidizers are widespread and active members of soil microbial communities. Nat Microbiol. 2021;6:246–56.CAS 
Article 

Google Scholar 
Constant P, Poissant L, Villemur R. Isolation of Streptomyces sp. PCB7, the first microorganism demonstrating high-affinity uptake of tropospheric H2. ISME J. 2008;2:1066–76.CAS 
Article 

Google Scholar 
Greening C, Carere CR, Rushton-Green R, Harold LK, Hards K, Taylor MC, et al. Persistence of the dominant soil phylum Acidobacteria by trace gas scavenging. Proc Natl Acad Sci USA. 2015;112:10497–502.CAS 
Article 

Google Scholar 
Islam ZF, Cordero PRF, Feng J, Chen Y-J, Bay SK, Jirapanjawat T, et al. Two Chloroflexi classes independently evolved the ability to persist on atmospheric hydrogen and carbon monoxide. ISME J. 2019;13:1801.CAS 
Article 

Google Scholar 
Islam ZF, Welsh C, Bayly K, Grinter R, Southam G, Gagen EJ, et al. A widely distributed hydrogenase oxidises atmospheric H2 during bacterial growth. ISME J. 2020;14:2649–58.CAS 
Article 

Google Scholar 
Schmitz RA, Pol A, Mohammadi SS, Hogendoorn C, van Gelder AH, Jetten MSM, et al. The thermoacidophilic methanotroph Methylacidiphilum fumariolicum SolV oxidizes subatmospheric H2 with a high-affinity, membrane-associated [NiFe] hydrogenase. ISME J. 2020;14:1223–32.CAS 
Article 

Google Scholar 
Ortiz M, Leung PM, Shelley G, Jirapanjawat T, Nauer PA, Van Goethem M, et al. Multiple energy sources and metabolic strategies sustain microbial diversity in Antarctic desert soils. Proc Natl Acad Sci. 2021;118:e2025322118.CAS 
Article 

Google Scholar 
Greening C, Berney M, Hards K, Cook GM, Conrad R. A soil actinobacterium scavenges atmospheric H2 using two membrane-associated, oxygen-dependent [NiFe] hydrogenases. Proc Natl Acad Sci USA. 2014;111:4257–61.CAS 
Article 

Google Scholar 
Myers MR, King GMY. Isolation and characterization of Acidobacterium ailaaui sp. nov., a novel member of Acidobacteria subdivision 1, from a geothermally heated Hawaiian microbial mat. Int J Syst Evol Microbiol. 2016;66:5328–35.CAS 
Article 

Google Scholar 
Cordero PRF, Grinter R, Hards K, Cryle MJ, Warr CG, Cook GM, et al. Two uptake hydrogenases differentially interact with the aerobic respiratory chain during mycobacterial growth and persistence. J Biol Chem. 2019;294:18980–91.CAS 
Article 

Google Scholar 
Sander R. Compilation of Henry’s law constants (version 4.0) for water as solvent. Atmos Chem Phys. 2015;15:4399–981.CAS 
Article 

Google Scholar 
Cox J, Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol. 2008;26:1367–72.CAS 
Article 

Google Scholar 
Cox J, Neuhauser N, Michalski A, Scheltema RA, Olsen JV, Mann M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res. 2011;10:1794–805.CAS 
Article 

Google Scholar 
Shah AD, Goode RJA, Huang C, Powell DR, Schittenhelm RB. LFQ-Analyst: an easy-to-use interactive web platform to analyze and visualize label-free proteomics data preprocessed with MaxQuant. J Proteome Res. 2020;19:204–11.CAS 
Article 

Google Scholar 
Nowka B, Daims H, Spieck E. Comparative oxidation kinetics of nitrite-oxidizing bacteria: nitrite availability as key factor for niche differentiation. Appl Environ Microbiol. 2014;81:745–53.Thauer RK, Jungermann K, Decker K. Energy conservation in chemotrophic anaerobic bacteria. Bacteriol Rev. 1977;41:809.Article 

Google Scholar 
Greening C, Villas-Bôas SG, Robson JR, Berney M, Cook GM. The growth and survival of Mycobacterium smegmatis is enhanced by co-metabolism of atmospheric H2. PLoS ONE. 2014;9:e103034.Article 

Google Scholar 
Constant P, Chowdhury SP, Pratscher J, Conrad R. Streptomycetes contributing to atmospheric molecular hydrogen soil uptake are widespread and encode a putative high-affinity [NiFe]-hydrogenase. Environ Microbiol. 2010;12:821–9.CAS 
Article 

Google Scholar 
Häring V, Conrad R. Demonstration of two different H2-oxidizing activities in soil using an H2 consumption and a tritium exchange assay. Biol Fertil Soils. 1994;17:125–8.Article 

Google Scholar 
Yang Y, Daims H, Liu Y, Herbold CW, Pjevac P, Lin J-G, et al. Activity and metabolic versatility of complete ammonia oxidizers in full-scale wastewater treatment systems. mBio. 2020;11:e03175–19.Chadwick GL, Hemp J, Fischer WW, Orphan VJ. Convergent evolution of unusual complex I homologs with increased proton pumping capacity: energetic and ecological implications. ISME J. 2018;12:2668–80.CAS 
Article 

Google Scholar 
Alberty RA. Standard apparent reduction potentials of biochemical half reactions and thermodynamic data on the species involved. Biophys Chem. 2004;111:115–22.CAS 
Article 

Google Scholar 
Burns LC, Stevens RJ, Smith RV, Cooper JE. The occurrence and possible sources of nitrite in a grazed, fertilized, grassland soil. Soil Biol Biochem. 1995;27:47–59.CAS 
Article 

Google Scholar 
Zhang M, Yuan D, Chen G, Li Q, Zhang Z, Liang Y. Simultaneous determination of nitrite and nitrate at nanomolar level in seawater using on-line solid phase extraction hyphenated with liquid waveguide capillary cell for spectrophotometric detection. Microchim Acta. 2009;165:427–35.CAS 
Article 

Google Scholar 
Daims H, Nielsen JL, Nielsen PH, Schleifer K-H, Wagner M. In situ characterization of Nitrospira-like nitrite-oxidizing bacteria active in wastewater treatment plants. Appl Environ Microbiol. 2001;67:5273–84.CAS 
Article 

Google Scholar 
Lebedeva EV, Alawi M, Maixner F, Jozsa P-G, Daims H, Spieck E. Physiological and phylogenetic characterization of a novel lithoautotrophic nitrite-oxidizing bacterium, ‘Candidatus Nitrospira bockiana’. Int J Syst Evol Microbiol. 2008;58:242–50.CAS 
Article 

Google Scholar 
Lebedeva EV, Off S, Zumbrägel S, Kruse M, Shagzhina A, Lücker S, et al. Isolation and characterization of a moderately thermophilic nitrite-oxidizing bacterium from a geothermal spring. FEMS Microbiol Ecol. 2011;75:195–204.CAS 
Article 

Google Scholar 
Watson SW, Bock E, Valois FW, Waterbury JB, Schlosser U. Nitrospira marina gen. nov. sp. nov.: a chemolithotrophic nitrite-oxidizing bacterium. Arch Microbiol. 1986;144:1–7.Article 

Google Scholar 
Maixner F, Noguera DR, Anneser B, Stoecker K, Wegl G, Wagner M, et al. Nitrite concentration influences the population structure of Nitrospira-like bacteria. Environ Microbiol. 2006;8:1487–95.CAS 
Article 

Google Scholar 
Sorokin DY, Lucker S, Vejmelkova D, Kostrikina NA, Kleerebezem R, Rijpstra WIC, et al. Nitrification expanded: discovery, physiology and genomics of a nitrite-oxidizing bacterium from the phylum Chloroflexi. ISME J. 2012;6:2245–56.CAS 
Article 

Google Scholar 
Greening C, Biswas A, Carere CR, Jackson CJ, Taylor MC, Stott MB, et al. Genomic and metagenomic surveys of hydrogenase distribution indicate H2 is a widely utilised energy source for microbial growth and survival. ISME J. 2016;10:761–77.CAS 
Article 

Google Scholar 
Daebeler A, Kitzinger K, Koch H, Herbold CW, Steinfeder M, Schwarz J, et al. Exploring the upper pH limits of nitrite oxidation: diversity, ecophysiology, and adaptive traits of haloalkalitolerant. Nitrospira ISME J. 2020;14:2967–79.CAS 
Article 

Google Scholar 
Suarez C, Sedlacek CJ, Gustavsson DJI, Eiler A, Modin O, Hermansson M, et al. Disturbance-based management of ecosystem services and disservices in partial nitritation anammox biofilms. 2021. https://www.biorxiv.org/content/10.1101/2021.07.05.451122v1. More

Edelist, D., Rilov, G., Golani, D., Carlton, J. T. & Spanier, E. Restructuring the Sea: profound shifts in the world’s most invaded marine ecosystem. Divers. Distrib. 19, 69–77, https://doi.org/10.1111/ddi.12002 (2013).Article 

Google Scholar 
Parravicini, V., Azzurro, E., Kulbicki, M. & Belmaker, J. Niche shift can impair the ability to predict invasion risk in the marine realm: an illustration using Mediterranean fish invaders. Ecol. Lett. 18, 246–253, https://doi.org/10.1111/ele.12401 (2015).Article 
PubMed 

Google Scholar 
Galil, B. S. et al. International arrivals: widespread bioinvasions in European Seas. Ethol. Ecol. Evol. 26, 152–171, https://doi.org/10.1080/03949370.2014.897651 (2014).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Golani, D. & Fricke, R. Checklist of the Red Sea Fishes with delineation of the Gulf of Suez, Gulf of Aqaba, endemism and Lessepsian migrants. Zootaxa 4509, 1–215, https://doi.org/10.11646/zootaxa.4509.1.1 (2018).Article 
PubMed 

Google Scholar 
Zenetos, A. et al. Uncertainties and validation of alien species catalogues: The Mediterranean as an example. Estuar. Coast. Shelf Sci. 191, 171–187, https://doi.org/10.1016/j.ecss.2017.03.031 (2017).Article 

Google Scholar 
Katsanevakis, S. et al. Advancing marine conservation in European and contiguous seas with the MarCons Action. Res. Ideas Outcomes 3, e11884, https://doi.org/10.3897/rio.3.e11884 (2017).Article 

Google Scholar 
Schroeder, K., Chiggiato, J., Bryden, H. L., Borghini, M. & Ben Ismail, S. Abrupt climate shift in the Western Mediterranean Sea. Sci. Rep. 6, 23009, https://doi.org/10.1038/srep23009 (2016).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Vargas-Yáñez, M. et al. Warming trends and decadal variability in the Western Mediterranean shelf. Glob. Planet. Change 63, 177–184, https://doi.org/10.1016/j.gloplacha.2007.09.001 (2008).Article 

Google Scholar 
D’Amen, M. & Azzurro, E. Lessepsian fish invasion in Mediterranean marine protected areas: a risk assessment under climate change scenarios. ICES J. Mar. Sci. 77, 388–397, https://doi.org/10.1093/icesjms/fsz207 (2020).Article 

Google Scholar 
Golani, D., Azzurro, E., Dulčić, J., Massutí, E. & Orsi-Relini, L. Atlas of Exotic Species in the Mediterranean Sea. F. Briand, Ed. 365 pages. CIESM Publishers, Paris, Monaco (2021).Editorial Board. AquaNIS. Information system on Aquatic Non-Indigenous and Cryptogenic Species. World Wide Web electronic publication. Version 2.36+ (2015).Roy, D. et al. DAISIE – Inventory of alien invasive species in Europe. https://doi.org/10.15468/ybwd3x (2020).European Commission – Joint Research Centre – European Alien Species Information Network (EASIN).Uludag, A, Scalera, R., Trichkova, T., Tomov, R. & Rat, M. East and South European Network for Invasive Alien Species (ESENIAS): Development, networking and role in the invasive alien species research and policy-making in Europe. (2016).Zenetos, A. et al. ELNAIS: A collaborative network on Aquatic Alien Species in Hellas (Greece). REABIC 6, 185–196, https://doi.org/10.3391/mbi.2015.6.2.09 (2015).Article 

Google Scholar 
European Network on Invasive Alien Species. NOBANIS (Gateway to information on Invasive Alien species in North and Central Europe) (2013).MAMIAS – Marine Mediterranean Invasive Alien Species. (2014).MedMIS – Mediterranean Marine Invasive SpeciesKatsanevakis, S. et al. Identifying where vulnerable species occur in a data-poor context: combining satellite imaging and underwater occupancy surveys. Mar. Ecol. Prog. Ser. 577, 17–32, https://doi.org/10.3354/meps12232 (2017).Article 

Google Scholar 
Galil, B. S. Alien species in the Mediterranean Sea—which, when, where, why? In Challenges to Marine Ecosystems (eds. Davenport, J. et al.) 105–116, https://doi.org/10.1007/978-1-4020-8808-7_10 (Springer Netherlands (2008).Galil, B. S. Taking stock: inventory of alien species in the Mediterranean sea. Biol. Invasions 11, 359–372, https://doi.org/10.1007/s10530-008-9253-y (2009).Article 

Google Scholar 
Nunes, A. L., Orizaola, G., Laurila, A. & Rebelo, R. Rapid evolution of constitutive and inducible defenses against an invasive predator. Ecology 95, 1520–1530, https://doi.org/10.1890/13-1380.1 (2014).Article 
PubMed 

Google Scholar 
Zenetos, A. et al. Annotated list of marine alien species in the Mediterranean with records of the worst invasive species. Mediterr. Mar. Sci. 6, 63–118, https://doi.org/10.12681/mms.186 (2005).Article 

Google Scholar 
Zenetos, A. et al. Additions to the annotated list of marine alien biota in the Mediterranean with special emphasis on Foraminifera and Parasites. Mediterr. Mar. Sci. 9, 119–166, https://doi.org/10.12681/mms.146 (2008).Article 

Google Scholar 
Zenetos, A. et al. Alien species in the Mediterranean sea by 2010. A contribution to the application of european union’s marine strategy framework directive (MSFD). Part I. Spatial distribution. https://doi.org/10.12681/mms.87 (2010)Zenetos, Α et al. Alien species in the Mediterranean Sea by 2012. A contribution to the application of European Union’s Marine Strategy Framework Directive (MSFD). Part 2. Introduction trends and pathways. Mediterr. Mar. Sci. 13, 328–352, https://doi.org/10.12681/mms.327 (2012).Article 

Google Scholar 
Dimitriadis, C. et al. Updating the occurrences of Pterois miles in the Mediterranean Sea, with considerations on thermal boundaries and future range expansion. Mediterr. Mar. Sci. 21, 62–69, https://doi.org/10.12681/mms.21845 (2020).Article 

Google Scholar 
Carlton, J. T. Pattern, process, and prediction in marine invasion ecology. Biol. Conserv. 78, 97–106, https://doi.org/10.1016/0006-3207(96)00020-1 (1996).Article 

Google Scholar 
Olenin, S., Minchin, D., Daunys, D. & Zaiko, A. Pathways of aquatic invasions in Europe. Atlas of biodiversity risk 138–139 (2010).Essl, F. et al. A Conceptual Framework for Range-Expanding Species that Track Human-Induced Environmental Change. BioScience 69, 908–919 (2019).Article 

Google Scholar 
Golani, D., Orsi-Relini, L., Massuti, E. & Quignard, J. P. CIESM Atlas of Exotic Species in the Mediterranean. vol. 1 (2002).D’Amen, M. & Azzurro, E. Integrating univariate niche dynamics in species distribution models: A step forward for marine research on biological invasions. J. Biogeogr. 47, 686–697, https://doi.org/10.1111/jbi.13761 (2020).Article 

Google Scholar 
Azzurro, E., Smeraldo, S. & D’Amen, M. ORMEF: Occurrence Records of Mediterranean Exotic Fishes database. SEANOE. https://doi.org/10.17882/84182 (2021).Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3, 160018, https://doi.org/10.1038/sdata.2016.18 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Fricke, R., Eschmeyer, W. N. & Van Der Laan, R. Eschmeyer’s Catalog of Fishes: genera, species, references. California Academy of Sciences (2022).Azzurro, E., Goren, M., Diamant, A., Galil, B. & Bernardi, G. Establishing the identity and assessing the dynamics of invasion in the Mediterranean Sea by the dusky sweeper, Pempheris homboidei Kossmann & Räuber, 1877 (Pempheridae, Perciformes). Biol. Invasions 17, 815–826, https://doi.org/10.1007/s10530-014-0836-5 (2015).Article 

Google Scholar 
Evans, J. & Schembri, P. On the occurrence of Cephalopholis hemistiktos and C. taeniops (Actinopterygii, Perciformes, Serranidae) in Malta, with corrections of previous misidentifications. Acta Ichthyol. Piscat. 47, 197–200, https://doi.org/10.3750/AIEP/02064 (2017).Article 

Google Scholar 
Dragicevic, B. et al. New Mediterranean Biodiversity Records (December 2019). https://doi.org/10.12681/mms.20913 (2019).UNEP/MAP – United Nation Environment Programme – Mediterranean Action Plan. Integrated Monitoring and Assessment Programme of the Mediterranean Sea and Coast and Related Assessment Criteria (IMAP). (2016). More

Hewitt, G. M. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).CAS 
PubMed 
Article 
ADS 

Google Scholar 
Drovetski, S. V. et al. A test of the European Pleistocene refugial paradigm, using a Western Palaearctic endemic bird species. Proc. R. Soc. B 285, 20181606 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Hewitt, G. M. Quaternary phylogeography: the roots of hybrid zones. Genetica 139, 617–638 (2011).PubMed 
Article 

Google Scholar 
Nadachowska-Brzyska, K., Li, C., Smeds, L., Zhang, G. & Ellegren, H. Temporal dynamics of avian populations during Pleistocene revealed by whole-genome sequences. Curr. Biol. 25, 1375–1380 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Newton, I. Speciation and Biogeography of Birds (Academic Press, 2003).
Google Scholar 
Pellegrino, I. et al. Phylogeography and Pleistocene refugia of the Little Owl Athene noctua inferred from mtDNA sequence data. Ibis 156, 639–657 (2014).Article 

Google Scholar 
Tietze, D. T. Bird Species: How they Arise, Modify and Vanish (Springer Nature, 2018).Book 

Google Scholar 
Carrera, L., Pavia, M., Peresani, M. & Romandini, M. Late Pleistocene fossil birds from Buso Doppio del Broion Cave (North-Eastern Italy): implications for palaeoecology, palaeoenvironment and palaeoclimate. Boll. Soc. Paleontol. I(57), 145–174 (2018).
Google Scholar 
Carrera, L., Pavia, M., Romandini, M. & Peresani, M. Avian fossil assemblages at the onset of the LGM in the eastern Alps: a palaecological contribution from the Rio Secco Cave (Italy). C. R. Palevol 17, 166–177 (2018).Article 

Google Scholar 
Carrera, L., Scarponi, D., Martini, F., Sarti, L. & Pavia, M. Mid-Late Pleistocene Neanderthal landscapes in southern Italy: paleoecological contributions of the avian assemblage from Grotta del Cavallo, Apulia, southern Italy. Palaeogeogr. Palaeocl. 567, 110256 (2021).Article 

Google Scholar 
Clark, P. U. et al. The last glacial maximum. Science 325, 710–714 (2009).CAS 
PubMed 
Article 
ADS 

Google Scholar 
Hampe, A. & Jump, A. S. Climate relicts: past, present, future. Annu. Rev. Ecol. Evol. S. 42, 313–333 (2011).Article 

Google Scholar 
Holm, S. R. & Svenning, J. C. 180,000 years of climate change in Europe: avifaunal responses and vegetation implications. PLoS ONE 9, e94021 (2014).PubMed 
PubMed Central 
Article 
ADS 
CAS 

Google Scholar 
Sanchez Marco, A. Avian zoogeographical patterns during the Quaternary in the Mediterranean region and paleoclimatic interpretation. Ardeola 51, 91–132 (2004).
Google Scholar 
Elith, J. & Leathwick, J. R. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. S. 40, 677–697 (2009).Article 

Google Scholar 
Gavin, D. G. et al. Climate refugia: joint inference from fossil records, species distribution models and phylogeography. New Phytol. 204, 37–54 (2014).PubMed 
Article 

Google Scholar 
Nogués-Bravo, D. Predicting the past distribution of species climatic niches. Glob. Ecol. Biogeogr. 18, 521–531 (2009).Article 

Google Scholar 
Svenning, J. C., Fløjgaard, C., Marske, K. A., Nogues-Bravo, D. & Normand, S. Applications of species distribution modeling to paleobiology. Quat. Sci. Rev. 30, 2930–2947 (2011).Article 
ADS 

Google Scholar 
Varela, S., Lobo, J. M. & Hortal, J. Using species distribution models in paleobiogeography: a matter of data, predictors and concepts. Palaeogeogr. Palaeocl. 310, 451–463 (2011).Article 

Google Scholar 
Arcones, A., Ponti, R., Ferrer, X. & Vieites, D. R. Pleistocene glacial cycles as drivers of allopatric differentiation in Arctic shorebirds. J. Biogeogr. 48, 747–759 (2021).Article 

Google Scholar 
Kozma, R., Melsted, P., Magnússon, K. P. & Höglund, J. Looking into the past–the reaction of three grouse species to climate change over the last million years using whole genome sequences. Mol. Ecol. 25, 570–580 (2016).PubMed 
Article 

Google Scholar 
Lagerholm, V. K. et al. Range shifts or extinction? Ancient DNA and distribution modelling reveal past and future responses to climate warming in cold-adapted birds. Glob. Change Biol. 23, 1425–1435 (2017).Article 
ADS 

Google Scholar 
Metcalf, J. L. et al. Integrating multiple lines of evidence into historical biogeography hypothesis testing: a Bison bison case study. Proc. R. Soc. B 281, 20132782. https://doi.org/10.1098/rspb.2013.2782 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Perktaş, U., Peterson, A. T. & Dyer, D. Integrating morphology, phylogeography, and ecological niche modeling to explore population differentiation in North African Common Chaffinches. J. Ornithol. 158, 1–13 (2017).Article 

Google Scholar 
Perktaş, U., De Silva, T. N., Quintero, E. & Tavşanoğlu, Ç. Adding ecology into phylogeography: ecological niche models and phylogeography in tandem reveals the demographic history of the subalpine warbler complex. Bird Study 66, 234–242 (2019).Article 

Google Scholar 
Fløjgaard, C., Normand, S., Skov, F. & Svenning, J. C. Ice age distributions of European small mammals: insights from species distribution modelling. J. Biogeogr. 36, 1152–1163 (2009).Article 

Google Scholar 
Lima-Ribeiro, M. S., Varela, S., Nogués-Bravo, D. & Diniz-Filho, J. A. F. Potential suitable areas of giant ground sloths dropped before its extinction in South America: the evidences from bioclimatic envelope modeling. Nat. Conserv. 10, 145–151 (2012).Article 

Google Scholar 
Lorenzen, E. D. et al. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature 479, 359–364 (2011).CAS 
PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
Martínez-Meyer, E., Townsend Peterson, A. & 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 
Nogués-Bravo, D., Rodríguez, J., Hortal, J., Batra, P. & Araújo, M. B. Climate change, humans, and the extinction of the woolly mammoth. PLoS Biol. 6, e79 (2008).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Waltari, E. et al. Locating Pleistocene refugia: comparing phylogeographic and ecological niche model predictions. PLoS ONE 2, e563 (2007).PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
Barrientos, R. et al. Refugia, colonization and diversification of an arid-adapted bird: coincident patterns between genetic data and ecological niche modelling. Mol. Ecol. 23, 390–407 (2014).PubMed 
Article 

Google Scholar 
Huntley, B. & Green, R. E. Bioclimatic models of the distributions of Gyrfalcons and ptarmigan. In Gyrfalcons and Ptarmigan in a Changing World Vol. II (eds Watson, R. T. et al.) 329–338 (The Peregrine Fund, 2011).
Google Scholar 
Huntley, B., Allen, J. R. M., Barnard, P., Collingham, Y. C. & Holliday, P. R. Species distribution models indicate contrasting late-Quaternary histories for Southern and Northern Hemisphere bird species. Glob. Ecol. Biogeogr. 22, 277–288 (2013).Article 

Google Scholar 
Kiss, O. et al. Past and future climate-driven shifts in the distribution of a warm-adapted bird species, the European Roller Coracias garrulus. Bird Study 67, 143–159 (2020).Article 

Google Scholar 
Koparde, P., Mehta, P., Mukherjee, S. & Robin, V. V. Quaternary climatic fluctuations and resulting climatically suitable areas for Eurasian owlets. Ecol. Evol. 9, 4864–4874 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Peterson, A. T. & Ammann, C. M. Global patterns of connectivity and isolation of populations of forest bird species in the late Pleistocene. Glob. Ecol. Biogeogr. 22, 596–606 (2013).Article 

Google Scholar 
Peterson, A. T., Martínez-Meyer, E. & González-Salazar, C. Reconstructing the Pleistocene geography of the Aphelocoma jays (Corvidae). Divers. Distrib. 10, 237–246 (2004).Article 

Google Scholar 
Ponti, R., Arcones, A., Ferrer, X. & Vieites, D. R. Lack of evidence of a Pleistocene migratory switch in current bird long-distance migrants between Eurasia and Africa. J. Biogeogr. 47, 1564–1573 (2020).Article 

Google Scholar 
Ruegg, K. C., Hijmans, R. J. & Moritz, C. Climate change and the origin of migratory pathways in the Swainson’s thrush Catharus ustulatus. J. Biogeogr. 33, 1172–1182 (2006).Article 

Google Scholar 
Smith, S. E., Gregory, R. D., Anderson, B. J. & Thomas, C. D. The past, present and potential future distributions of cold-adapted bird species. Divers. Distrib. 19, 352–362 (2013).Article 

Google Scholar 
Sutton, L. J. et al. Geographic range estimates and environmental requirements for the harpy eagle derived from spatial models of current and past distribution. Ecol. Evol. 11, 481–497 (2021).PubMed 
Article 

Google Scholar 
Varela, S., Lima-Ribeiro, M. S., Diniz-Filho, J. A. F. & Storch, D. Differential effects of temperature change and human impact on European Late Quaternary mammalian extinctions. Glob. Change Biol. 21, 1475–1481 (2015).Article 
ADS 

Google Scholar 
Scridel, D. et al. Thermal niche predicts recent changes in range size for bird species. Clim. Res. 73, 207–216 (2017).Article 

Google Scholar 
Barnagaud, J. Y. et al. Relating Habitat and Climatic Niches in Birds. PLoS Biol. 7, e32819 (2012).CAS 
ADS 

Google Scholar 
Devictor, V., Julliard, R., Jiguet, F. & Couvet, D. Birds are tracking climate warming, but not fast enough. Proc. R. Soc. Lond. [Biol.] 275, 2743–2748 (2008).
Google Scholar 
Gaüzère, P., Jiguet, F. & Devictor, V. Rapid adjustment of bird community compositions to local climatic variations and its functional consequences. Glob. Change Biol. 21, 3367–3378 (2015).Article 
ADS 

Google Scholar 
Jiguet, F., Gadot, A., Julliard, R., Newson, S. & Couvet, D. Climate envelope, life history traits and the resilience of birds facing global change. Glob. Change Biol. 13, 1673–1685 (2007).Article 
ADS 

Google Scholar 
Jiguet, F. et al. Bird population trends are linearly affected by climate change along species thermal ranges. Proc. R. Soc. Lond. [Biol.] 277, 3601–3608 (2010).
Google Scholar 
Jiguet, F. et al. Population trends of European common birds are predicted by characteristics of their climatic niche. Glob. Change Biol. 16, 497–505 (2010).Article 
ADS 

Google Scholar 
Lindström, Å., Green, M., Paulson, G., Smith, H. G. & Devictor, V. Rapid changes in bird community composition at multiple temporal and spatial scales in response to recent climate change. Ecography 36, 313–322 (2013).Article 

Google Scholar 
Pearce-Higgins, J. W., Eglington, S. M., Martay, B. & Chamberlain, D. E. Drivers of climate change impacts on bird communities. J. Anim. Ecol. 84, 943–954 (2015).PubMed 
Article 

Google Scholar 
Stephens, P. A. et al. Consistent response of bird populations to climate change on two continents. Science 352, 84–87 (2016).CAS 
PubMed 
Article 
ADS 

Google Scholar 
BirdLife International. Crex crex. The IUCN Red List of Threatened Species 2016: e.T22692543A86147127. https://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2016-3.RLTS.T22692543A86147127.en (2016).BirdLife International. Perdix perdix. The IUCN Red List of Threatened Species 2016: e.T22678911A85929015. https://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2016-3.RLTS.T22678911A85929015.en (2016).BirdLife International. Pyrrhocorax graculus. The IUCN Red List of Threatened Species 2016: e.T22705921A87386602. https://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2016-3.RLTS.T22705921A87386602.en (2016).BirdLife International. Coturnix coturnix. The IUCN Red List of Threatened Species 2018: e.T22678944A131904485. https://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2018-2.RLTS.T22678944A131904485.en (2018).BirdLife International. Athene noctua. The IUCN Red List of Threatened Species 2019: e.T22689328A155470112. https://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2019-3.RLTS.T22689328A155470112.en (2019).BirdLife International. Bubo scandiacus. The IUCN Red List of Threatened Species 2020: e.T22689055A181375387. https://dx.doi.org/https://doi.org/10.2305/IUCN.UK.2020-3.RLTS.T22689055A181375387.en (2020).Cramp, S. The Complete Birds of the Western Palearctic on CD-ROM (Oxford University Press, 1998).
Google Scholar 
Tyrberg, T. Pleistocene Birds of the Palearctic: A Catalogue. (Publications of the Nuttall Ornithological Club No. 27, 1998).Tyrberg, T. Pleistocene Birds of the Palaearctic. http://web.telia.com/~u11502098/pleistocene.pdf (2008).Pellegrino, I. et al. Evidence for strong genetic structure in European populations of the little owl Athene noctua. J. Avian Biol. 46, 462–475 (2015).Article 

Google Scholar 
van Nieuwenhuyse, D., Génot, J. C. & Johnson, D. H. The Little Owl: Conservation, Ecology and Behavior of Athene noctua (Cambridge University Press, 2008).
Google Scholar 
Dupont, L. M. Vegetation zones in NW Africa during the Brunhes chron reconstructed from marine palynological data. Quat. Sci. Rev. 12, 189–202 (1993).Article 
ADS 

Google Scholar 
Hoag, C. & Svenning, J. C. African environmental change from the Pleistocene to the Anthropocene. Annu. Rev. Env. Resour. 42, 27–54 (2017).Article 

Google Scholar 
Hoelzmann, P. et al. Palaeoenvironmental changes in the arid and sub arid belt (Sahara-Sahel-Arabian Peninsula) from 150 kyr to present. In Past Climate Variability Through Europe and Africa (eds Battarbee, R. W. et al.) 219–256 (Springer, 2004).Chapter 

Google Scholar 
Larrasoaña, J. C., Roberts, A. P. & Rohling, E. J. Dynamics of green Sahara periods and their role in hominin evolution. PLoS ONE 8, e76514 (2013).PubMed 
PubMed Central 
Article 
ADS 
CAS 

Google Scholar 
Bech, N., Novoa, C., Allienne, J. F., Boissier, J. & Bro, E. Quantifying genetic distance between wild and captive strains of the grey partridge Perdix perdix in France: conservation implications. Biodivers. Conserv. 29, 609–624 (2020).Article 

Google Scholar 
Liukkonen-Anttila, T., Uimaniemi, L., Orell, M. & Lumme, J. Mitochondrial DNA variation and the phylogeography of the grey partridge (Perdix perdix) in Europe: from Pleistocene history to present day populations. J. Evolut. Biol. 15, 971–982 (2002).CAS 
Article 

Google Scholar 
Potapova, O. Snowy owl Nyctea scandiaca (Aves: Strigiformes) in the Pleistocene of the Ural Mountains with notes on its ecology and distribution in the Northern Palearctic. Deinsea 8, 103–126 (2001).
Google Scholar 
Mourer-Chauviré, C. Les oiseaux du Pléistocène moyen et supérieur de France. Doc. Lab. Géol. Fac. Sci. Lyon 64, 1–624 (1975).
Google Scholar 
Mourer-Chauviré, C. Les oiseaux dans les habitats pale´olithiques: gibier des hommes ou proies des rapaces? In Animal and Archaeology: 2. Shell Middens, Fishes and Birds (eds Grigson, C. & Clutton-Brock, J.) 111–124 (British Archaeological Reports International Series 183, 1983).
Google Scholar 
Meijer, H. J., Pavia, M., Madurell-Malapeira, J. & Alba, D. M. A revision of fossil eagle owls (Aves: Strigiformes: Bubo) from Europe and the description of a new species, Bubo ibericus, from Cal Guardiola (NE Iberian Peninsula). Hist. Biol. 29, 822–832 (2017).Article 

Google Scholar 
Sanchez Marco, A. Aves fósiles de la Península Ibérica, Canarias y Baleares: balance de los estudios realizados. Investig. Rev. PH Inst. Andal. Patrim. Hist. 94, 154–181 (2018).
Google Scholar 
Sardella, R. et al. Grotta Romanelli (Southern Italy, Apulia): legacies and issues in excavating a key site for the Pleistocene of the Mediterranean. Riv. Ital. Paleontol. S. 124, 247–264 (2018).
Google Scholar 
Rustioni, M., Ferretti, M. P., Mazza, P., Pavia, M. & Varola, A. The vertebrate fauna from Cardamone (Apulia, southern Italy): an example of Mediterranean mammoth fauna. Deinsea 9, 395–404 (2003).
Google Scholar 
Bedetti, C. & Pavia, M. Reinterpretation of the Late Pleistocene Ingarano Cave deposit based on the fossil bird association (Apulia, South-eastern Italy). Riv. Ital. Paleontol. S. 113, 487–507 (2007).
Google Scholar 
Tyrberg, T. Arctic, montane and steppe birds as glacial relicts in West Palearctic. Ornithol. Verh. 25, 29–49 (1991).
Google Scholar 
Bruderer, B. & Salewski, V. Evolution of bird migration in a biogeographical context. J. Biogeogr. 35, 1951–1959 (2008).Article 

Google Scholar 
Finlayson, C. Avian Survivors. The History and Biogeography of Palearctic Birds (T. & A.D. Poyser, 2011).
Google Scholar 
Louchart, A. Emergence of long distance bird migrations: a new model integrating global climate changes. Naturwissenschaften 95, 1109–1119 (2008).CAS 
PubMed 
Article 
ADS 

Google Scholar 
Winger, B. M., Auteri, G. G., Pegan, T. M. & Weeks, B. C. A long winter for the Red Queen: rethinking the evolution of seasonal migration. Biol. Rev. 94, 737–752 (2019).PubMed 
Article 

Google Scholar 
Somveille, M. et al. Simulation-based reconstruction of global bird migration over the past 50,000 years. Nat. Commun. 11, 1–9 (2020).Article 
CAS 

Google Scholar 
Fiedler, W. Recent changes in migratory behaviour of birds: a compilation of field observations and ringing data. In Avian Migration (eds Berthold, P. et al.) 21–38 (Springer, 2003).Chapter 

Google Scholar 
Milá, B., Smith, T. B. & Wayne, R. K. Postglacial population expansion drives the evolution of long-distance migration in a songbird. Evolution 60, 2403–2409 (2006).PubMed 
Article 

Google Scholar 
Zink, R. M. The evolution of avian migration. Biol. J. Linn. Soc. 104, 237–250 (2011).Article 

Google Scholar 
Zink, R. M. & Gardner, A. S. Glaciation as a migratory switch. Sci. Adv. 3, e1603133 (2017).PubMed 
PubMed Central 
Article 
ADS 

Google Scholar 
Matthiesen, D. G. Avian medullary bone in the fossil record, an example from the Early Pleistocene of Olduvai Gorge, Tanzania. J. Vertebr. Paleontol. 9, 34A (1990).
Google Scholar 
Ponti, R., Arcones, A., Ferrer, X. & Vieites, D. R. Seasonal climatic niches diverge in migratory birds. Ibis 162, 318–330 (2020).Article 

Google Scholar 
Cohen, K. M. & Gibbard, P. L. Global chronostratigraphical correlation table for the last 2.7 million years, version 2019 QI-500. Quat. Int. 500, 20–31 (2019).Article 

Google Scholar 
Lisiecki, L. E. & Raymo, M. E. A Pliocene-Pleistocene stack of 57 globally distributed benthic δ18O records. Paleoceanography 20, PA1003. https://doi.org/10.1029/2004PA001071 (2005).Article 
ADS 

Google Scholar 
Vermeersch, P. M. Radiocarbon Palaeolithic Europe Database, Version 26. https://ees.kuleuven.be/geography/projects/14c-palaeolithic/index.html (2019).d’Errico, F., Banks, W. E., Vanhaeren, M., Laroulandie, V. & Langlais, M. PACEA geo-referenced radiocarbon database. Paleoanthropology https://doi.org/10.4207/PA.2011.ART40 (2011).Article 

Google Scholar 
Bronk Ramsey, C. Bayesian analysis of radiocarbon dates. Radiocarbon 51, 337–360. https://doi.org/10.1017/S0033822200033865 (2009).Article 

Google Scholar 
Reimer, P. J. et al. IntCal13 and Marine13 radiocarbon age calibration curves 0–50,000 years cal BP. Radiocarbon 55, 1869–1897. https://doi.org/10.2458/azu_js_rc.55.16947 (2013).CAS 
Article 

Google Scholar 
Serjeantson, D. Birds: a seasonal resource. Environ. Archaeol. 3, 23–33 (1998).Article 

Google Scholar 
Serjeantson, D. Birds. Cambridge Manuals in Archaeology (Cambridge University Press, 2009).
Google Scholar 
Lima-Ribeiro, M. S. et al. EcoClimate: a database of climate data from multiple models for past, present, and future for macroecologists and biogeographers. Biodivers. Inform. 10, 1–21 (2015).Article 

Google Scholar 
Varela, S., Lima-Ribeiro, M. S. & Terribile, L. C. A short guide to the climatic variables of the last glacial maximum for biogeographers. PLoS ONE 10, e0129037 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Elith, J. et al. Novel methods improve prediction of species’ distributions from occurrence data. Ecography 29, 129–151 (2006).Article 

Google Scholar 
Elith, J., Leathwick, J. R. & Hastie, T. A working guide to boosted regression trees. J. Anim. Ecol. 77, 802–813 (2008).CAS 
PubMed 
Article 

Google Scholar 
Leathwick, J. R., Elith, J., Francis, M. P., Hastie, T. & Taylor, P. Variation in demersal fish species richness in the oceans surrounding New Zealand: an analysis using boosted regression trees. Mar. Ecol. Prog. Ser. 321, 267–281 (2006).Article 
ADS 

Google Scholar 
Leathwick, J. R., Elith, J., Chadderton, W. L., Rowe, D. & Hastie, T. Dispersal, disturbance and the contrasting biogeographies of New Zealand’s diadromous and non-diadromous fish species. J. Biogeogr. 35, 1481–1497 (2008).Article 

Google Scholar 
Therneau, T. & Atkinson, B. Rpart: Recursive Partitioning and Regression Trees. R package version 4.1-15. https://CRAN.R-project.org/package=rpart (2019).Kuhn, M. Caret: Classification and Regression Training. R package version 6.0-88. https://CRAN.R-project.org/package=caret (2021). More