Ecology

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Rockström, J. et al. Sustainable intensification of agriculture for human prosperity and global sustainability. Ambio 46, 4–17 (2017).Article 

Google Scholar 
Steffen, W. et al. Planetary boundaries: guiding human development on a changing planet. Science 347, 1259855 (2015).Article 
CAS 

Google Scholar 
Campbell, B. M. et al. Agriculture production as a major driver of the Earth system exceeding planetary boundaries. Ecol. Soc. 22, 8 (2017).Article 

Google Scholar 
Hazell, P. & Wood, S. Drivers of change in global agriculture. Philos. Trans. R. Soc. B 363, 495–515 (2008).Article 

Google Scholar 
Lehmann, P. et al. Complex responses of global insect pests to climate warming. Front. Ecol. Environ. 18, 141–150 (2020).Article 

Google Scholar 
Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).CAS 
Article 

Google Scholar 
Springmann, M. et al. Options for keeping the food system within environmental limits. Nature 562, 519–525 (2018).CAS 
Article 

Google Scholar 
Hunter, M. C., Smith, R. G., Schipanski, M. E., Atwood, L. W. & Mortensen, D. A. Agriculture in 2050: recalibrating targets for sustainable intensification. Bioscience 67, 386–391 (2017).Article 

Google Scholar 
Ecosystems and Human Well-being: Synthesis (Millenium Ecosystem Assessment, 2005); http://www.millenniumassessment.org/documents/document.356.aspx.pdfBommarco, R., Kleijn, D. & Potts, S. G. Ecological intensification: harnessing ecosystem services for food security. Trends Ecol. Evol. 28, 230–238 (2013).Article 

Google Scholar 
Kleijn, D. et al. Ecological intensification: bridging the gap between science and practice. Trends Ecol. Evol. 34, 154–166 (2018).Article 

Google Scholar 
Pingali, P. L. Green revolution: impacts, limits, and the path ahead. Proc. Natl Acad. Sci. USA 109, 12302–12308 (2012).CAS 
Article 

Google Scholar 
Wezel, A. et al. Agroecology as a science, a movement and a practice. Sustain. Agric. 2, 27–43 (2009).
Google Scholar 
Garnett, T. et al. Sustainable intensification in agriculture: premises and policies. Science 341, 33–34 (2013).CAS 
Article 

Google Scholar 
Lipper, L. et al. Climate-smart agriculture for food security. Nat. Clim. Change 4, 1068–1072 (2014).Article 

Google Scholar 
Tittonell, P. Ecological intensification of agriculture—sustainable by nature. Curr. Opin. Environ. Sustain. 8, 53–61 (2014).Article 

Google Scholar 
Jenkinson, D. S. The impact of humans on the nitrogen cycle, with focus on temperate arable agriculture. Plant Soil 228, 3–15 (2001).CAS 
Article 

Google Scholar 
Verheijen, F. G. A., Jones, R. J. A., Rickson, R. J. & Smith, C. J. Tolerable versus actual soil erosion rates in Europe. Earth Sci. Rev. 94, 23–38 (2009).Article 

Google Scholar 
Peoples, M. B. et al. in Agroecosystem Diversity: Reconciling Contemporary Agriculture and Environmental Quality (eds Lemaire, G. et al.) 123–142 (Academic Press, 2019); https://doi.org/10.1016/B978-0-12-811050-8.00008-XStorkey, J., Bruce, T., McMillan, V. & Neve, P. in Agroecosystem Diversity: Reconciling Contemporary Agriculture and Environmental Quality (eds Lemaire, G. et al.) 199–209 (Academic Press, 2019); https://doi.org/10.1016/B978-0-12-811050-8.00012-1Schröder, J. Revisiting the agronomic benefits of manure: a correct assessment and exploitation of its fertilizer value spares the environment. Bioresour. Technol. 96, 253–261 (2005).Article 
CAS 

Google Scholar 
Mhlanga, B., Ercoli, L., Pellegrino, E., Onofri, A. & Thierfelder, C. The crucial role of mulch to enhance the stability and resilience of cropping systems in southern Africa. Agron. Sustain. Dev. 41, 29–43 (2021).Article 

Google Scholar 
Barrett, C. B. & Bevis, L. E. M. The self-reinforcing feedback between low soil fertility and chronic poverty. Nat. Geosci. 8, 907–912 (2015).CAS 
Article 

Google Scholar 
Tittonell, P. & Giller, K. E. When yield gaps are poverty traps: the paradigm of ecological intensification in African smallholder agriculture. Field Crops Res. 143, 76–90 (2013).Article 

Google Scholar 
Sandén, T. et al. European long-term field experiments: knowledge gained about alternative management practices. Soil Use Manage. 34, 167–176 (2018).Article 

Google Scholar 
Storkey, J. et al. The unique contribution of Rothamsted to ecological research at large temporal scales. Adv. Ecol. Res. 55, 3–42 (2016).Article 

Google Scholar 
Johnston, A. E. & Poulton, P. R. The importance of long-term experiments in agriculture: their management to ensure continued crop production and soil fertility; the Rothamsted experience. Eur. J. Soil Sci. 69, 113–125 (2018).CAS 
Article 

Google Scholar 
Bowles, T. M. et al. Long-term evidence shows that crop-rotation diversification increases agricultural resilience to adverse growing conditions in North America. One Earth 2, 284–293 (2020).Marini, L. et al. Crop rotations sustain cereal yields under a changing climate. Environ. Res. Lett. 15, 124011 (2020).Article 

Google Scholar 
Lal, R. Carbon emission from farm operations. Environ. Int. 30, 981–990 (2004).CAS 
Article 

Google Scholar 
Cordell, D., Drangert, J. O. & White, S. The story of phosphorus: global food security and food for thought. Glob. Environ. Change 19, 292–305 (2009).Article 

Google Scholar 
Lechenet, M., Dessaint, F., Py, G., Makowski, D. & Munier-Jolain, N. Reducing pesticide use while preserving crop productivity and profitability on arable farms. Nat. Plants 3, 17008 (2017).Article 

Google Scholar 
Bedoussac, L. et al. Ecological principles underlying the increase of productivity achieved by cereal-grain legume intercrops in organic farming. A review. Agron. Sustain. Dev. 35, 911–935 (2015).Article 

Google Scholar 
Storkey, J., Mead, A., Addy, J. & MacDonald, A. J. Agricultural intensification and climate change have increased the threat from weeds. Glob. Change Biol. 27, 2416–2425 (2021).Article 

Google Scholar 
Vanlauwe, B. et al. in Integrated Plant Nutrient Management in Sub-Saharan Africa: From Concept to Practice (eds Vanlauwe, B. et al.) 173–184 (CABI, 2002).Hijbeek, R. et al. Do organic inputs matter—a meta-analysis of additional yield effects for arable crops in Europe. Plant Soil 411, 293–303 (2017).CAS 
Article 

Google Scholar 
Thierfelder, C. & Wall, P. C. Effects of conservation agriculture techniques on infiltration and soil water content in Zambia and Zimbabwe. Soil Tillage Res. 105, 217–227 (2009).Article 

Google Scholar 
Gentile, R., Vanlauwe, B., Chivenge, P. & Six, J. Interactive effects from combining fertilizer and organic residue inputs on nitrogen transformations. Soil Biol. Biochem. 40, 2375–2384 (2008).CAS 
Article 

Google Scholar 
Mupangwa, W. et al. Maize yields from rotation and intercropping systems with different legumes under conservation agriculture in contrasting agro-ecologies. Agric. Ecosyst. Environ. 306, 107170 (2021).Article 

Google Scholar 
Pittelkow, C. M. et al. Productivity limits and potentials of the principles of conservation agriculture. Nature 517, 365–368 (2015).CAS 
Article 

Google Scholar 
Steward, P. R. et al. The adaptive capacity of maize-based conservation agriculture systems to climate stress in tropical and subtropical environments: a meta-regression of yields. Agric. Ecosyst. Environ. 251, 194–202 (2018).Article 

Google Scholar 
Pittelkow, C. M. et al. When does no-till yield more? A global meta-analysis. Field Crops Res. 183, 156–168 (2015).Article 

Google Scholar 
Sun, W. et al. Climate drives global soil carbon sequestration and crop yield changes under conservation agriculture. Glob. Change Biol. 26, 3325–3335 (2020).Article 

Google Scholar 
Kirkegaard, J. A. et al. Sense and nonsense in conservation agriculture: principles, pragmatism and productivity in Australian mixed farming systems. Agric. Ecosyst. Environ. 187, 133–145 (2014).Article 

Google Scholar 
Thierfelder, C. et al. Complementary practices supporting conservation agriculture in southern Africa. A review. Agron. Sustain. Dev. 38, 16–37 (2018).Article 

Google Scholar 
Alignier, A. et al. Configurational crop heterogeneity increases within-field plant diversity. J. Appl. Ecol. 57, 654–663 (2020).Article 

Google Scholar 
Liebman, M. et al. Ecologically sustainable weed management: how do we get from proof-of-concept to adoption? Ecol. Appl. 26, 1352–1369 (2016).Article 

Google Scholar 
Giller, K. E. The food security conundrum of sub-Saharan Africa. Glob. Food Sec. 26, 100431 (2020).Article 

Google Scholar 
Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

Google Scholar 
Addy, J. W. G., Ellis, R. H., Macdonald, A. J., Semenov, M. A. & Mead, A. Changes in agricultural climate in South-Eastern England from 1892 to 2016 and differences in cereal and permanent grassland yield. Agric. For. Meteorol. 308–309, 108560 (2021).Article 

Google Scholar 
Bates, D., Kliegl, R., Vasishth, S. & Baayen, H. Parsimonious mixed models. Preprint at https://arXiv.org/abs/1506.04967v2 (2018).MacLaren, C., Glendining, M., Poulton, P., Macdonald, A. & Clark, S. Woburn Ley-Arable Experiment: Yields of Wheat as First Test Crop, 1976–2018 (e-RA Rothamsted, 2022); https://doi.org/10.23637/wrn3-wheat7618-01 .Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means: R package version 1.7.2 https://CRAN.R-project.org/package=emmeans (2020).Viechtbauer, W. Conducting meta-analyses in R with the metafor package. J. Stat. Softw. 36, 1–48 (2010).Article 

Google Scholar 
Lajeunesse, M. J. On the meta-analysis of response ratios for studies with correlated and multi-group designs. Ecology 92, 2049–2055 (2011).Article 

Google Scholar 
Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).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  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

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

Poff, N. L. et al. The natural flow regime: A new paradigm for riverine conservation and restoration. Bioscience 47, 769–784 (1997).Article 

Google Scholar 
Bunn, S. E. & Arthington, A. H. Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ. Manage. 30(4), 492–507 (2002).PubMed 
Article 

Google Scholar 
Olden, J. D. et al. Are large-scale flow experiments informing the science and management of freshwater ecosystems?. Front. Ecol. Environ. 12, 176–185 (2014).Article 

Google Scholar 
Poff, N. L. Beyond the natural flow regime? Broadening the hydro-ecological foundation to meet environmental flows challenges in a non-stationary world. Freshw. Biol. 63, 1011–1021 (2018).Article 

Google Scholar 
Acreman, M. Ethical aspects of water and ecosystems. Water Policy 3, 257–265 (2001).Article 

Google Scholar 
Olden, J. D. & Naiman, R. J. Incorporating thermal regimes into environmental flows assessments: Modifying dam operations to restore freshwater ecosystem integrity. Freshw. Biol. 55, 86–107 (2010).Article 

Google Scholar 
Poff, N. L. & Zimmerman, J. K. H. Ecological responses to altered flow regimes: A literature review to inform the science and management of environmental flow. Freshw. Biol. 55, 194–205 (2010).Article 

Google Scholar 
Richter, B. D. & Thomas, G. A. Restoring environmental flows by modifying dam operations. Ecol. Soc. 12(1), 12 (2007).Article 

Google Scholar 
Tharme, R. E. A global perspective on environmental flow assessment: emerging trends in the development and application of environmental flow methodologies for rivers. River Res. Appl. 19, 397–441 (2003).Article 

Google Scholar 
Vӧrӧsmarty, C. J. et al. Global threats to human water security and river biodiversity. Nature 468, 334–334 (2010).Article 

Google Scholar 
Acreman, M. C. & Ferguson, A. J. D. Environmental flows and the European water framework directive. Freshw. Biol. 55, 32–48 (2010).Article 

Google Scholar 
Poff, N. L. & Matthews, J. H. Environmental flows in the Anthropocence: Past progress and future prospects. Curr. Opin. Environ. Sustain. 5, 667–675 (2003).Article 

Google Scholar 
Theodoropoulos, C. & Skoulikidis, N. Environmental flows: The European approach through the Water Framework Directive 2000/60/EC. In Proceedings of the 10th International Congress of the Hellenic Geographical Society 1140–1152 (2015).The Brisbane Declaration. Environmental flows are essential for freshwater ecosystem health and human well-being. In Declaration of the 10th International River Symposium 3–6 (Brisbane, Australia, 2007).Arthington, A. H. et al. The brisbane declaration and global action agenda on environmental flows. Front. Environ. Sci. 6, 45 (2018).Article 

Google Scholar 
European Commission. Ecological flows in the implementation of the Water Framework Directive. WFD CIS Guidance Document No. 31 (2015).Hirzel, A. H. & Le Lay, G. Habitat suitability modelling and niche theory. J. Appl. Ecol. 45, 1372–1381 (2008).Article 

Google Scholar 
Soberon, J. Grinnellian and Eltonian niches and geographic distributions of species. Ecol. Lett. 10(12), 1115–1123 (2007).PubMed 
Article 

Google Scholar 
Ahmadi-Nedushan, B. et al. A review on statistical methods for the evaluation of the aquatic habitat suitability for instream flow assessment. River Res. Applic. 22, 503–523 (2006).Article 

Google Scholar 
Dolédec, S., Lamouroux, N., Fuchs, U. & Mérigoux, S. Modelling the hydraulic preferences of benthic macroinvertebrates in small European stream. Freshw. Biol. 52, 145–164 (2007).Article 

Google Scholar 
Katopodis, C. Case studies of instream flow modelling for fish habitat in Canadian Prairie Rivers. Can. Water Resour. J. 28, 199–216 (2003).Article 

Google Scholar 
Parasiewicz, P. Application of MesoHABSIM and target fish community approaches to restoration of the Quinebaug River, Connecticut and Massachusetts, U.S.A. River. Res. Appl. 24, 459–471 (2008).Article 

Google Scholar 
Piniweski, M. et al. Estimation of environmental flows in semi-natural lowland rivers – the Narew basin case study. Pol. J. Environ. Stud. 20(5), 1281–1293 (2011).
Google Scholar 
Theodoropoulos, C., Vourka, A., Skoulikidis, N., Rutschmann, P. & Stamou, A. Evaluating the performance of habitat models for predicting the environmental flow requirements of benthic macroinvertebrates. J. Ecohydraul. 3(1), 30–44 (2018).Article 

Google Scholar 
Yi, Y. et al. Evaluating the ecological influence of hydraulic projects: A review of aquatic habitat suitability models. Renew. Sustain. Energy Rev. 68, 748–762 (2017).Article 

Google Scholar 
Theodoropoulos, C., Skoulikidis, N., Rutschmann, P. & Stamou, A. Ecosystem-based environmental flow assessment in a Greek regulated river with the use of 2D hydrodynamic habitat modelling. River Res. Appl. 34(6), 538–547 (2018).Article 

Google Scholar 
Huryn, A. D. & Wallace, J. B. Life history and production of stream insects. Annu. Rev. Entomol. 45(1), 83–110 (2000).CAS 
PubMed 
Article 

Google Scholar 
Wallace, J. B. & Webster, J. R. The role of macroinvertebrates in stream ecosystem function. Annu. Rev. Entomol. 41, 115–139 (1996).CAS 
PubMed 
Article 

Google Scholar 
Cummins, K. W. Structure and function of stream ecosystems. Bioscience 24, 631–641 (1974).Article 

Google Scholar 
Covich, A. P., Palmer, M. A. & Crowl, T. A. The role of benthic invertebrates species in freshwater ecosystems. Bioscience 49(2), 119–127 (1999).Article 

Google Scholar 
Dolédec, S., Statzner, B. & Bournaud, M. Species traits for future biomonitoring across ecoregions: Patterns along a human-impacted river. Freshw. Biol. 42, 737–758 (1999).Article 

Google Scholar 
Marzin, N. et al. Ecological assessment of running waters: Do macrophytes, macroinvertebrates, diatoms and fish show similar responses to human pressures?. Ecol. Ind. 23, 56–65 (2012).CAS 
Article 

Google Scholar 
Statzner, B., Bady, P., Dolédec, S. & Schöll, F. Invertebrate traits for the biomonitoring of large European rivers: An initial assessment of trait patterns in least impacted river reaches. Freshw. Biol. 50, 2136–2161 (2005).Article 

Google Scholar 
Jowett, I. G. Hydraulic constraints on habitat suitability for benthic invertebrates in gravel-bed rivers. River Res. Appl. 19, 495–507 (2003).Article 

Google Scholar 
Dewson, Z. S., James, A. B. W. & Death, R. G. A review of the consequences of decreased flow for instream habitat and macroinvertebrates. J. North Am. Benthol. Soc. 26, 401–415 (2007).Article 

Google Scholar 
Wood, P. J. & Armitage, P. D. Biological effects of fine sediment in the lotic environment. Environ. Manage. 21(2), 203–217 (1997).CAS 
PubMed 
Article 

Google Scholar 
Rolls, R. J., Leigh, C. & Sheldon, F. Mechanistic effects of low-flow hydrology on riverine ecosystems: Ecological principles and consequences of alteration. Freshw. Sci. 31, 1163–1186 (2012).Article 

Google Scholar 
Graeber, D., Pusch, M. T., Lorenz, S. & Brauns, M. Cascading effects of flow reduction on the benthic invertebrate community in a lowland river. Hydrobiologia 717, 147–159 (2013).CAS 
Article 

Google Scholar 
González, J. M., Recuerda, M. & Elosegi, A. Crowded waters: short-term response of invertebrate drift to water abstraction. Hydrobiologia 819, 39–51 (2018).Article 

Google Scholar 
Jowett, I. G., Richardson, J., Biggs, B. J. F., Hickey, C. W. & Quinn, J. M. Microhabitat preferences of benthic invertebrates and the development of generalised Deleatidium spp habitat suitability curves, applied to four New Zealand rivers. N. Z. J. Mar. Freshw. Res. 25(2), 187–199 (1991).Article 

Google Scholar 
Lamouroux, N. et al. The generality of abundance-environment relationships in microhabitats: A comment on Lancaster and Downes (2009). River Res. Appl. 26, 915–920 (2010).Article 

Google Scholar 
Mérigoux, S. & Dolédec, S. Hydraulic requirements of stream communities: A case study on invertebrates. Freshw. Biol. 49, 600–613 (2004).Article 

Google Scholar 
Lancaster, J. & Downes, B. J. Linking the hydraulic world of individual organisms to ecological processes: Putting ecology into ecohydraulics. River Res. Appl. 26, 385–403 (2009).Article 

Google Scholar 
Lancaster, J. & Hildrew, A. G. Flow refugia and the microdistribution of lotic macroinvertebrates. J. N. Am. Benthol. Soc. 12(4), 385–393 (1993).Article 

Google Scholar 
Chen, W. & Olden, J. D. Evaluating transferability of flow–ecology relationships across space, time and taxonomy. Freshw. Biol. 63, 817–830 (2017).Article 

Google Scholar 
Li, F., Cai, Q., Fu, X. & Liu, J. Construction of habitat suitability models (HSMs) for benthic macroinvertebrate and their applications to instream environmental flows: A case study in Xiangxi River of Three Gorges Reservior region China. Prog. Nat. Sci. 19, 359–367 (2009).Article 

Google Scholar 
Growns, I. O. & Davis, J. A. Longitudinal changes in near-bed flows and macroinvertebrate communities in a western Australian stream. J. North Am. Benthol. Soc. 13, 417–438 (1994).Article 

Google Scholar 
Shearer, K. A., Hayes, J. W., Jowett, I. G. & Olsen, D. A. Habitat suitability curves for benthic macroinvertebrates from a small New Zealand river. N. Z. J. Mar. Freshw. Res. 49, 178–191 (2015).Article 

Google Scholar 
Bovee, K. D. et al. Stream Habitat Analysis using the Instream Flow Incremental Methodology. USGS Inf. Technol. Rep. 1998–0004, 1–130 (1998).
Google Scholar 
Conallin, J., Boegh, E. & Jensen, J. K. Instream physical habitat modelling types: An analysis as stream hydromorphological modelling tools for EU water resource managers. Int. J. River Basin Manag. 8, 93–107 (2010).Article 

Google Scholar 
Poff, N. L., Tharme, R. E. & Arthington, A. H. Evolution of environmental flows assessment science, principles, and methodologies. In Water for the Environment: Policy, Science, and Integrated Management (eds Horne, A. et al.) 203–236 (Elsevier Press, Amsterdam, 2017).Chapter 

Google Scholar 
Bovee, K.D. Development and evaluation of habitat suitability criteria for use in the instream flow incremental methodology. Washington (DC): USDI Fish and Wildlife Service. Instream Flow Information Paper #21 FWS/OBS-86/7.Geological Survey, Biological Resources Division, Mid-Continent Ecological Science Centre, Fort Collins, Colorado (1986).Vismara, R., Azzellino, A., Bosi, R., Crosa, G. & Gentili, G. Preference curves for brown trout (Salmo trutta fario L.) in the River Adda, Northern Italy: comparing univariate and multivariate approaches. Regul. River 17, 37–50 (2001).Article 

Google Scholar 
Nestler, J. M., Milhous, R. T., Payne, T. R. & Smith, D. L. History and review of the habitat suitability criteria curve in applied aquatic ecology. River Res. Appl. 35, 1155–1180 (2019).Article 

Google Scholar 
Theodoropoulos, C., Skoulikidis, N., Stamou, A. & Dimitriou, E. Spatiotemporal variation in benthic-invertebrates-based physical Habitat modelling: Can we use generic instead of local and season-specific habitat suitability criteria?. Water 10, 1508 (2018).Article 

Google Scholar 
Gąbka, M., Jakubas, E., Janiak, T. & Golski, J. Rzeki Wełna i Flinta – charakterystyka obiektów badań, ich położenie i granice zlewni. In Koncepcja lasu Modelowego w Zarządzaniu i Ochronie Różnorodności Biologicznej rzek Wełny i Flinty(Wielkopolska (eds Batora, J. et al.) 21–30 (Bogucki Wydawnictwo Naukowe, Poznań, 2014).
Google Scholar 
Bartkowski, T. Rozwój polodowcowej sieci hydrograficznej w Wielkopolsce Środkowej (Zeszyty Naukowe UAM 8, 1957).Paluch, J. Wpływ działalności spółek wodnych istniejących w XIX i na początku wieku XX na terenie zlewni rzeki Wełny na stan jej hydrografii i stosunków wodnych. In Proceedings of the conference “Ecological problems of the Vełna River basin – status and directions of measures 2–26 (Wągrowiec, 2009).Jakubas, E. et al. Ocena stanu ekologicznego i zmian hydromorfologicznych rzek Wełny i Flinty. In Koncepcja lasu Modelowego w Zarządzaniu i Ochronie Różnorodności Biologicznej rzek Wełny i Flinty (Wielkopolska) (eds Batora, J. et al.) 141–150 (Bogucki Wydawnictwo Naukowe, Poznań, 2014).
Google Scholar 
Szoszkiewicz, K. et al. Podręcznik oceny wód płynących w oparciu o Hydromorfologiczny Indeks Rzeczny (Inspekcja Ochrony Środowiska, Biblioteka Monitoringu Środowiska, 2017).Emery, J. C. et al. Classifying the hydraulic performance of riffle–pool bedforms for habitat assessment and river rehabilitation design. River Res. Appl. 19, 533–549 (2003).Article 

Google Scholar 
Mueller, M., Pander, J. & Geist, J. Taxonomic sufficiency in freshwater ecosystems: Effects of taxonomic resolution, functional traits, and data transformation. Freshw. Sci. 32(3), 762–778 (2013).Article 

Google Scholar 
Schmidt-Kloiber, A., Graf, W., Lorenz, A. & Moog, O. The AQEM/STAR taxalist – a pan-European macro-invertebrate ecological database and taxa inventory. Hydrobiologia 566, 325–342 (2006).Article 

Google Scholar 
Clarke, K. R. & Warwick, R. M. Changes in Marine Communities: An Approach to Statistical Analysis and Interpretation 2nd edn. (Plymout, PRIMER-E (Plymouth Marine Laboratory, 2001).
Google Scholar 
Vimos-Lojano, D., Hampel, H., Vázquez, R. F. & Martínez-Capel, F. Community structure and functional feeding groups of macroinvertebrates in pristine Andean streams under different vegetation cover. Ecohydrol. Hydrobiol. 20(3), 357–368 (2020).Article 

Google Scholar 
Clarke, K. & Gorley, R. PRIMER v6: User Manual/Tutorial (Plymouth Marine Laboratory, Plymouth, 2006).
Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria (https://www.R-project.org/, 2020)Oksanen, F. J., et al. Vegan: Community Ecology Package. R package Version 2.4–3. (https://CRAN.R-project.org/package=vegan, 2017)Jowett, I.G., Hayes, J.W. & Duncan, M.J. A guide to instream habitat survey methods and analysis. NIWA Science and Technology Series No. 54 (2008).Manly, B. F. J., McDonald, L. L. & Thomas, D. L. Resource Selection by Animals (Chapman and Hall, London, 1993).Book 

Google Scholar 
Bis, B. & Mikulec, A. Przewodnik do oceny stanu ekologicznego rzek na podstawie makrobezkręgowców bentosowych (Biblioteka Monitoringu Środowiska, 2013).Grygoruk, M. et al. Revealing the influence of hyporheic water exchange on the composition and abundance of bottom-dwelling macroinvertebrates in a temperate lowland river. Knowl. Manag. Aquat. Ecosyst. 442, 37. https://doi.org/10.1051/kmae/2021036 (2021).Article 

Google Scholar 
Degani, G. et al. Relationships between current velocity, depth and the invertebrate community in a stable river system. Hydrobiologia 263, 163–172 (1993).Article 

Google Scholar 
Lamberti, G. A., Entrekin, S. A., Griffiths, N. & Tiegs, S. Coarse Particulate Organic Matter: Storage, Transport, and Retention. In Methods Ecosystem Function Vol. 2 (eds Lamberti, G. A. & Hauer, F. R.) 55–69 (Elsevier Academic Press, Amsterdam, 2017).
Google Scholar 
Bell, N., Riis, T., Suren, A. M. & Baattrup-Pedersen, A. Distribution of invertebrates within beds of two morphologically contrasting stream macrophyte species. Fundam. Appl. Limnol. 183(4), 309–321 (2013).Article 

Google Scholar 
Wolters, J., Verdonschot, R. C. M., Schoelynck, J., Verdonschot, P. F. M. & Meire, P. The role of macrophyte structural complexity and water flow velocity in determining the epiphytic macroinvertebrate community composition in a lowland stream. Hydrobiologia 806, 157–173 (2018).CAS 
Article 

Google Scholar 
Gore, J. A. & Nestler, J. M. Instream flow studies in perspective. Regul. Rivers Res. Manage. 2, 93–101 (1988).Article 

Google Scholar 
Hudson, H. R., Byrom, A. E. & Chadderton, W. L. A Critique of IFIM —Instream Habitat Simulation in the New Zealand Context (Department of Conservation, 2003).Stamou, A. et al. Determination of environmental flows in rivers using an integrated hydrological-hydrodynamic-habitat modelling approach. J. Environ. Manage. 209, 273–285 (2018).CAS 
PubMed 
Article 

Google Scholar 
Wright, J. F., Blackburn, J. H., Clarke, R. T. & Furse, M. T. Macroinvertebrate-habitat associations in lowland rivers and their relevance to conservations. Int. Ver. Theor. Angew. Limnol. Verh. 25, 1515–1518 (1994).
Google Scholar 
Leszczyńska, J., Głowacki, Ł & Grzybkowska, M. Factors shaping species richness and biodiversity of riverine macroinvertebrate assemblages at the local and regional scale. Community Ecol. 18(3), 227–236 (2017).Article 

Google Scholar 
Gore, J. A., Crawford, D. J. & Addison, D. S. An analysis of artificial riffles and enhancement of benthic community diversity by Physical Habitat Simulation (PHABSIM) and direct observation. Regul. Rivers Res. Manage. 14(1), 69–77 (1998).Article 

Google Scholar 
Anderson, N. H. & Sedell, J. R. Detritus processing by macroinvertebrates in stream ecosystems. Ann. Rev. Entomol. 24, 351–377 (1979).Article 

Google Scholar 
Dunbar, M. J. et al. River discharge and local-scale physical habitat influence macroinvertebrate LIFE scores. Freshw. Biol. 55, 226–242 (2010).Article 

Google Scholar 
Acreman, M. et al. Environmental flows for natural, hybrid, and novel riverine ecosystems in a changing world. Front. Ecol. Environ. 12(8), 466–473 (2014).Article 

Google Scholar 
Jourdan, J. et al. Effects of changing climate on European stream invertebrate communities: a long-term data analysis. Sci. Total Environ. 621, 588–599 (2018).CAS 
PubMed 
Article 

Google Scholar 
Sarremejane, R. et al. Climate-driven hydrological variability determines inter-annual changes in stream invertebrate community assembly. Oikos 127, 1586–1595 (2018).Article 

Google Scholar 
Floury, M., Usseglio-Polatera, P., Ferreol, M., Delattre, C. & Souchon, Y. Global climate change in large European rivers: Long-term effects on macroinvertebrate communities and potential local confounding factors. Glob. Change Biol. 19, 1085–1099 (2013).Article 

Google Scholar 
Domisch, S., Jähnig, S. C. & Haase, P. Climate-change winners and losers: Stream macroinvertebrates of a submontane region in Central Europe. Freshw. Biol. 56, 2009–2020 (2011).Article 

Google Scholar  More

Lavelle, P. et al. Soil invertebrates and ecosystem services. Eur. J. Soil Biol. 42, S3–S15 (2006).Article 

Google Scholar 
André, H. M., Noti, M. I. & Lebrun, P. The soil fauna: The other last biotic frontier. Biodiv. Conserv. 3, 45–56 (1994).Article 

Google Scholar 
Decaëns, T. Macroecological patterns in soil communities. Glob. Ecol. Biogeogr. 19, 287–302 (2010).Article 

Google Scholar 
IPCC. Global Warming of 1.5 °C. Summary for Policymakers. (World Meteorological Organization, 2018).Cardinale, B. J. et al. Biodiversity loss and its impact on humanity. Nature 486, 59–67 (2012).CAS 
PubMed 
Article 

Google Scholar 
Kardol, P., Reynolds, W. N., Norby, R. J. & Classen, A. T. Climate change effects on soil microarthropod abundance and community structure. Appl. Soil Ecol. 47, 37–44 (2011).Article 

Google Scholar 
Kaspari, M., Clay, N. A., Lucas, J., Yanoviak, S. P. & Kay, A. Thermal adaptation generates a diversity of thermal limits in a rainforest ant community. Glob. Change Biol. 21, 1092–1102 (2015).Article 

Google Scholar 
Baird, D. J. & Hajibabaei, M. Biomonitoring 2.0: A new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. Mol. Ecol. 21, 2039–2044 (2012).PubMed 
Article 

Google Scholar 
Leray, M. & Knowlton, N. DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity. PNAS 112, 2076–2081 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Beng, K. C. et al. The utility of DNA metabarcoding for studying the response of arthropod diversity and composition to land-use change in the tropics. Sci. Rep. 6, 1–13. https://doi.org/10.1038/srep24965 (2016).CAS 
Article 

Google Scholar 
Zhang, K. et al. Plant diversity accurately predicts insect diversity in two tropical landscapes. Mol. Ecol. 25, 4407–4419 (2016).PubMed 
Article 

Google Scholar 
Hebert, P. D., Cywinska, A., Ball, S. L. & Dewaard, J. R. Biological identifications through DNA barcodes. Proc. R. Soc. Lond. B 270, 313–321 (2003).CAS 
Article 

Google Scholar 
Hajibabaei, M., Janzen, D. H., Burns, J. M., Hallwachs, W. & Hebert, P. D. DNA barcodes distinguish species of tropical Lepidoptera. PNAS 103, 968–971 (2006).PubMed 
PubMed Central 
Article 

Google Scholar 
Ratnasingham, S. & Hebert, P. D. N. A DNA-based registry for all animal species: The Barcode Index Number (BIN) system. PLoS ONE 8, e66213. https://doi.org/10.1371/journal.pone.0066213 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Shendure, J. & Ji, H. Next-generation DNA sequencing. Nat. Biotechnol. 26, 1135–1145 (2008).CAS 
PubMed 
Article 

Google Scholar 
Porter, T. M. & Hajibabaei, M. Scaling up: A guide to high-throughput genomic approaches for biodiversity analysis. Mol. Ecol. 27, 313–338 (2018).PubMed 
Article 

Google Scholar 
Tang, M. et al. High-throughput monitoring of wild bee diversity and abundance via mitogenomics. Methods Ecol. Evol. 6, 1034–1043 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
Arribas, P., Andújar, C., Hopkins, K., Shepherd, M. & Vogler, A. P. Metabarcoding and mitochondrial metagenomics of endogean arthropods to unveil the mesofauna of the soil. Methods Ecol. Evol. 7, 1071–1081 (2016).Article 

Google Scholar 
Arribas, P., Andújar, C., Salces-Castellano, A., Emerson, B. C. & Vogler, A. P. The limited spatial scale of dispersal in soil arthropods revealed with whole-community haplotype-level metabarcoding. Mol. Ecol. 30, 48–61 (2021).PubMed 
Article 

Google Scholar 
Oliverio, A. M., Gan, H., Wickings, K. & Fierer, N. A DNA metabarcoding approach to characterize soil arthropod communities. Soil Biol. Biochem. 125, 37–43 (2018).CAS 
Article 

Google Scholar 
Zinger, L. et al. Body size determines soil community assembly in a tropical forest. Mol. Ecol. 28, 528–543 (2019).CAS 
PubMed 
Article 

Google Scholar 
McGee, K. M., Porter, T. M., Wright, M. & Hajibabaei, M. Drivers of tropical soil invertebrate community composition and richness across tropical secondary forests using DNA metasystematics. Sci. Rep. 10, 18429. https://doi.org/10.1038/s41598-020-75452-4 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hajibabaei, M., Spall, J. L., Shokralla, S. & van Konynenburg, S. Assessing biodiversity of a freshwater benthic macroinvertebrate community through non-destructive environmental barcoding of DNA from preservative ethanol. BMC Ecol. 12, 28. https://doi.org/10.1186/1472-6785-12-28 (2012).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Gibson, J. et al. Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics. PNAS 111, 8007–8012 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lamb, P. D. et al. How quantitative is metabarcoding: A meta-analytical approach. Mol. Ecol. 28, 420–430 (2019).PubMed 
Article 

Google Scholar 
Piñol, J., Senar, M. A. & Symondson, W. O. The choice of universal primers and the characteristics of the species mixture determine when DNA metabarcoding can be quantitative. Mol. Ecol. 28, 407–419 (2019).PubMed 
Article 

Google Scholar 
Creedy, T. J., Ng, W. S. & Vogler, A. P. Toward accurate species-level metabarcoding of arthropod communities from the tropical forest canopy. Ecol. Evol. 9, 3105–3116 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Lach, L., Parr, C., Abbott, K. Ant Ecology (Oxford University Press, 2010).Palacios-Vargas, J. G. & Castaño-Meneses, G. Seasonality and community composition of springtails in Mexican forest. In Arthropods of Tropical Forests. Spatio-Temporal Dynamics and Resource Use in the Canopy (eds. Basset, Y. et al.) 159–169 (Cambridge University Press, 2003).Bignell, D. E. & Eggleton, P. Termites in ecosystems. In Termites: Evolution, Sociality, Symbiosis, Ecology (eds Abe, T., Bignell, D. E. & Higashi, M.) 363–387 (Kluwer Academic Publishers, 2000).Anderson-Teixeira, K. J. et al. CTFS-Forest GEO: A worldwide network monitoring forests in an era of global change. Glob. Change Biol. 21, 528–549 (2015).Article 

Google Scholar 
Lamarre, G. P. et al. Monitoring tropical insects in the 21st century. Adv. Ecol. Res. 62, 295–330 (2020).Article 

Google Scholar 
Basset, Y. et al. Enemy-free space and the distribution of ants, springtails and termites in the soil of one tropical rainforest. Eur. J. Soil Biol. 99, 103193. https://doi.org/10.1016/j.ejsobi.2020.103193 (2020).Article 

Google Scholar 
Agosti, D., Majer, J. D., Alonso, L. E. & Schultz, T. R. Ants. Standards Methods for Measuring and Monitoring Biodiversity (Smithsonian Institution Press, 2000).Bourguignon, T., Leponce, M. & Roisin, Y. Insights into the termite assemblage of a neotropical rainforest from the spatio-temporal distribution of flying alates. Insect. Conserv. Divers. 2, 153–162 (2009).Article 

Google Scholar 
Yu, D. W. et al. Biodiversity soup: Metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods Ecol. Evol. 3, 613–623 (2012).Article 

Google Scholar 
Gaston, K. J. & Lawton, J. H. Patterns in the distribution and abundance of insect populations. Nature 331, 709–712 (1988).Article 

Google Scholar 
Liu, M., Clarke, L. J., Baker, S. C., Jordan, G. J. & Burridge, C. P. A practical guide to DNA metabarcoding for entomological ecologists. Ecol. Entomol. 45, 373–385 (2019).Article 

Google Scholar 
Zinger, L. et al. DNA metabarcoding—Need for robust experimental designs to draw sound ecological conclusions. Mol. Ecol. 28, 1857–1862 (2019).PubMed 
Article 

Google Scholar 
Ficetola, G. F. et al. Replication levels, false presences and the estimation of the presence/absence from eDNA metabarcoding data. Mol. Ecol. Res. 15, 543–556 (2015).CAS 
Article 

Google Scholar 
Porter, T. M. & Hajibabaei, M. Automated high throughput animal CO1 metabarcode classification. Sci. Rep. 8, 1–10. https://doi.org/10.1038/s41598-018-22505-4 (2018).CAS 
Article 

Google Scholar 
Marquina, D., Esparza-Salas, R., Roslin, T. & Ronquist, F. Establishing arthropod community composition using metabarcoding: Surprising inconsistencies between soil samples and preservative ethanol and homogenate from Malaise trap catches. Mol. Ecol. Res. 19, 1516–1530 (2019).CAS 
Article 

Google Scholar 
Porter, T. M. et al. Variations in terrestrial arthropod DNA metabarcoding methods recovers robust beta diversity but variable richness and site indicators. Sci. Rep. 9, 1–11. https://doi.org/10.1038/s41598-019-54532-0 (2019).CAS 
Article 

Google Scholar 
Basset, Y. et al. Cross-continental comparisons of butterfly assemblages in tropical rainforests: Implications for biological monitoring. Insect. Conserv. Divers 6, 223–233 (2013).Article 

Google Scholar 
Ryder Wilkie, K. T., Mertl, A. L. & Traniello, J. F. A. Biodiversity below ground: Probing the subterranean ant fauna of Amazonia. Naturwissenschaften 94, 725–731 (2007).CAS 
PubMed 
Article 

Google Scholar 
André, H. M., Ducarme, X. & Lebrun, P. Soil biodiversity: Myth, reality or conning?. Oikos 96, 3–24 (2002).Article 

Google Scholar 
Wilson, J. J. DNA barcodes for insects. In DNA Barcodes: Methods and Protocols (eds Kress, W. J. & Erickson, D. L.) 17–46 (Springer, 2012).Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Mol. Mar. Biol. Biotechnol. 3, 294–299 (1994).CAS 
PubMed 

Google Scholar 
Gibson, J. F. et al. Large-scale biomonitoring of remote and threatened ecosystems via high-throughput sequencing. PLoS ONE 10, e0138432. https://doi.org/10.1371/journal.pone.0138432 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hajibabaei, M., Porter, T. M., Wright, M. & Rudar, J. COI metabarcoding primer choice affects richness and recovery of indicator taxa in freshwater systems. PLoS One 14, e0220953. https://doi.org/10.1371/journal.pone.0220953 (2019).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bush, A. et al. DNA metabarcoding reveals metacommunity dynamics in a threatened boreal wetland wilderness. PNAS 117, 8539–8545 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Calderón-Sanou, I. et al. From environmental DNA sequences to ecological conclusions: How strong is the influence of methodological choices?. J. Biogeogr. 47, 193–206 (2020).Article 

Google Scholar 
Schloss, P. D. Reintroducing mothur: 10 years later. Appl. Env. Microbiol. 86, e02343-19. https://doi.org/10.1128/AEM.02343-19 (2020).Article 

Google Scholar 
Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Boyer, F. et al. Obitools: A unix-inspired software package for DNA metabarcoding. Mol. Ecol. Res. 16, 176–182 (2016).CAS 
Article 

Google Scholar 
Ratnasingham, S. mBRAVE: The multiplex barcode research and visualization environment. Biodivers. Inf. Sci. Stand. 3, e37986. https://doi.org/10.3897/biss.3.37986 (2019).Article 

Google Scholar 
Rognes, T., Flouri, T., Nichols, B., Quince, C. & Mahé, F. VSEARCH: A versatile open source tool for metagenomics. PeerJ 4, e2584. https://doi.org/10.7717/peerj.2584 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Edgar, R. C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).CAS 
PubMed 
Article 

Google Scholar 
Gaston, K. J. Rarity (Springer, 1994).Kaspari, M. Litter ant patchiness at the 1–m2 scale: Disturbance dynamics in three Neotropical forests. Oecologia 107, 265–273 (1996).PubMed 
Article 

Google Scholar 
Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: An R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).Article 

Google Scholar 
Foster, Z. S. L., Sharpton, T. J. & Grünwald, N. J. Metacoder: An R package for visualization and manipulation of community taxonomic diversity data. PLoS Comput. Biol. 13, e1005404. https://doi.org/10.1371/journal.pcbi.1005404 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5-3 (2018).Hyams, D. G. CurveExpert Professional. A Comprehensive Data Analysis Software System for Windows, Mac, and Linux. Version 1.2.2. www.curveexpert.net (2011). Accessed 1 Jan 2022.Deagle, B. E. et al. Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data?. Mol. Ecol. 28, 391–406 (2019).PubMed 
Article 

Google Scholar 
Ficetola, G. F. et al. An In Silico approach for the evaluation of DNA barcodes. BMC Genom. 11, 434. https://doi.org/10.1186/1471-2164-11-434 (2010).CAS 
Article 

Google Scholar 
Auer, L., Mariadassou, M., O’Donohue, M., Klopp, C. & Hernandez-Raquet, G. Analysis of large 16S rRNA Illumina data sets: Impact of singleton read filtering on microbial community description. Mol. Ecol. Res. 17, e122–e132. https://doi.org/10.1111/1755-0998.12700 (2017).CAS 
Article 

Google Scholar 
Novotný, V. & Basset, Y. Rare species in communities of tropical insect herbivores: Pondering the mystery of singletons. Oikos 89, 564–572 (2000).Article 

Google Scholar 
Seifert, B. & Goropashnaya, A. V. Ideal phenotypes and mismatching haplotypes-errors of mtDNA treeing in ants (Hymenoptera: Formicidae) detected by standardized morphometry. Org. Divers. Evol. 4, 295–305 (2004).Article 

Google Scholar 
Gotzek, D., Clarke, J. & Shoemaker, D. Mitochondrial genome evolution in fire ants (Hymenoptera: Formicidae). BMC Evol. Biol. 10, 300. https://doi.org/10.1186/1471-2148-10-300 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Meza-Lázaro, R. N., Poteaux, C., Bayona-Vásquez, N. J., Branstetter, M. G. & Zaldívar-Riverón, A. Extensive mitochondrial heteroplasmy in the neotropical ants of the Ectatomma ruidum complex (Formicidae: Ectatomminae). Mit. DNA Part A 29, 1203–1214 (2018).Article 

Google Scholar 
Saitoh, S. et al. A quantitative protocol for DNA metabarcoding of springtails (Collembola). Genome 59, 705–723 (2016).CAS 
PubMed 
Article 

Google Scholar 
Elbrecht, V. et al. Validation of COI metabarcoding primers for terrestrial arthropods. PeerJ 7, e7745. https://doi.org/10.7717/peerj.7745 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Schenk, J., Geisen, S., Kleinbölting, N. & Traunspurger, W. Metabarcoding data allow for reliable biomass estimates in the most abundant animals on earth. Metabarcoding Metagenom. 3, e46704. https://doi.org/10.3897/mbmg.3.46704 (2019).Article 

Google Scholar 
Elbrecht, V. & Leese, F. Can DNA-based ecosystem assessments quantify species abundance? Testing primer bias and biomass—Sequence relationships with an innovative metabarcoding protocol. PLoS One 10, e0130324. https://doi.org/10.1371/journal.pone.0130324 (2015).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Bista, I. et al. Performance of amplicon and shotgun sequencing for accurate biomass estimation in invertebrate community samples. Mol. Ecol. Res. 18, 1020–1034 (2018).CAS 
Article 

Google Scholar 
Ji, Y. et al. SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes. Mol. Ecol. Res. 20, 256–267 (2020).CAS 
Article 

Google Scholar 
Steiner, F. M. et al. Tetramorium tsushimae, a new invasive ant in North America. Biol. Invasions 8, 117–123 (2006).Article 

Google Scholar 
Wetterer, J. K. Worldwide spread of the penny ant, Tetramorium bicarinatum (Hymenoptera: Formicidae). Sociobiology 54, 811–830 (2009).
Google Scholar 
Roisin, Y. et al. Vertical stratification of the termite assemblage in a neotropical forest. Oecologia 149, 301–311 (2006).PubMed 
Article 

Google Scholar 
Basset, Y. et al. Methodological considerations for monitoring soil/litter arthropods in tropical rainforests using DNA metabarcoding, with a special emphasis on ants, springtails and termites. Metabarcoding Metagenom. 4, 151–163. https://doi.org/10.3897/mbmg.4.58572 (2020).Article 

Google Scholar  More