Philippa Kaur

Hu, C.-H. in Introduction to Roadside Geology of Ten Field Geology Excursion Routes in Northern Taiwan (ed Taiwan Normal University Department of Earth Science) 63–100 (Taiwan Normal University, 1987).Hu, C.-H. Fossil molluscs of Tongxiao Formation (Pleistocene), Longgang area, Miaoli County. Atlas Fossil Mollusca Taiwan 2, 689–754 (1992).
Google Scholar 
Hu, C.-H. Fossil molluscs of Tongxiao Formation (Pleistocene) in Baishatun and Touwo, Tongxiao village, Miaoli County. Atlas Fossil Mollusca Taiwan 1, 175–314 (1991).
Google Scholar 
Hayasaka, I. & Morishita, A. Notes on some fossil echinoids of Taiwan, II. Acta Geol. Taiwan. 1, 93–110 (1947).
Google Scholar 
Lin, Y.-J., Fang, J.-N., Chang, C.-C., Cheng, C.-C. & Lin, J. P. Stereomic microstructure of Clypeasteroida in thin section based on new material from Pleistocene strata in Taiwan. Terr. Atmos. Ocean. Sci. J. https://doi.org/10.3319/TAO.2021.07.28.01 (2021).Article 

Google Scholar 
Morishita, A. in Contributions to Celebrate Prof. Ichiro Hayasaka’s 76th Birthday 109–116 (1967).Wang, C.-C., Lin, C.-F. & Li, L.-C. Measurements on Late Pleistocene sand dollar Scaphechinus mirabilis from northern Taiwan. Annu. Rep. Central Geol. Surv. 72, 49–56 (1984).
Google Scholar 
Nisiyama, S. The echinoid fauna from Japan and adjacent regions. Part 2. Palaeontol. Soc. Jpn. Spec. Pap. 13, 1–491 (1968).
Google Scholar 
Kashenko, S. D. Effects of extreme changes of sea water temperature and salinity on the development of the sand dollar Scaphechinus mirabilis. Russ. J. Mar. Biol. 35, 422–430. https://doi.org/10.1134/s1063074009050083 (2009).Article 

Google Scholar 
Davies, A. J. & John, C. M. The clumped (13C–18O) isotope composition of echinoid calcite: Further evidence for “vital effects” in the clumped isotope proxy. Geochim. Cosmochim. Acta 245, 172–189. https://doi.org/10.1016/j.gca.2018.07.038 (2019).ADS 
CAS 
Article 

Google Scholar 
Chen, W.-S., Yeh, J.-J. & Syu, S.-J. Late Cenozoic exhumation and erosion of the Taiwan orogenic belt: New insights from petrographic analysis of foreland basin sediments and thermochronological dating on the metamorphic orogenic wedge. Tectonophysics 750, 56–69. https://doi.org/10.1016/j.tecto.2018.09.003 (2019).ADS 
Article 

Google Scholar 
Peng, T.-R., Wang, C.-H. & Chen, C. T. A. Oxygen and carbon isotopic studies of fossil Mollusca in the Kuokang Shell Bed, Paishatung, Miaoli. Spec. Publ. Central Geol. Surv. 4, 307–322 (1990).
Google Scholar 
Lee, C.-L. Biostratigraphy and sedimentary environments of Toukoshan Formation in Baishatun area, Miaoli MS thesis, National Central University (2000).Locarnini, R. A. et al. World Ocean Atlas 2018, Volume 1: Temperature. 1–52 (NOAA, 2019).Liew, P.-M. Quaternary stratigraphy in western Taiwan: Palynological correlation. Proc. Geol. Soc. China 31, 169–180 (1988).
Google Scholar 
Siddall, M., Rohling, E. J., Thompson, W. G. & Waelbroeck, C. Marine isotope stage 3 sea level fluctuations: Data synthesis and new outlook. Rev. Geophys. https://doi.org/10.1029/2007rg000226 (2008).Article 

Google Scholar 
LeGrande, A. N. & Schmidt, G. A. Global gridded data set of the oxygen isotopic composition in seawater. Geophys. Res. Lett. https://doi.org/10.1029/2006gl026011 (2006).Article 

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

Google Scholar 
Epstein, S., Buchsbaum, R., Lowenstam, H. A. & Urey, H. C. Revised carbonate-water isotopic temperature scale. Bull. Geol. Soc. Am. 64, 1315–1326 (1963).Article 

Google Scholar 
Weber, J. N. & Raup, D. M. Fractionation of the stable isotopes of carbon and oxygen in marine calcareous organisms—the Echinoidea. Part II. Environmental and genetic factors. Geochim. Cosmochim. Acta 30, 705–736 (1966).ADS 
CAS 
Article 

Google Scholar 
Eiler, J. M. Paleoclimate reconstruction using carbonate clumped isotope thermometry. Quatern. Sci. Rev. 30, 3575–3588. https://doi.org/10.1016/j.quascirev.2011.09.001 (2011).ADS 
Article 

Google Scholar 
Takeda, S. Mechanism maintaining dense beds of the sand dollar Scaphechinus mirabilis in northern Japan. J. Exp. Mar. Biol. Ecol. 363, 21–27. https://doi.org/10.1016/j.jembe.2008.06.010 (2008).Article 

Google Scholar 
Takatsu, T., Nakatani, T., Miyamoto, T., Kooka, K. & Takahashi, T. Spatial distribution and feeding habits of Pacific cod (Gadus macrocephalus) larvae in Mutsu Bay, Japan. Fish. Oceanogr. 11, 90–101 (2002).Article 

Google Scholar 
Zhao, M., Huang, C.-Y. & Wei, K.-Y. A 28,000 year U37 K’ sea-surface temperature record of ODP Site 1202B, the southern Okinawa Trough. TAO 16, 45–56 (2005).ADS 
Article 

Google Scholar 
Jan, S., Tseng, Y.-H. & Dietrich, D. E. Sources of water in the Taiwan Strait. J. Oceanogr. 66, 211–221 (2010).Article 

Google Scholar 
Liao, E., Oey, L. Y., Yan, X.-H., Li, L. & Jiang, Y. The deflection of the China Coastal Current over the Taiwan Bank in winter. J. Phys. Oceanogr. 48, 1433–1450. https://doi.org/10.1175/jpo-d-17-0037.1 (2018).ADS 
Article 

Google Scholar 
Hu, J., Kawamura, H., Li, C., Hong, H. & Jiang, Y. Review on current and seawater volume transport through the Taiwan Strait. J. Oceanogr. 66, 591–610 (2010).Article 

Google Scholar 
Pico, T., Mitrovica, J. X., Ferrier, K. L. & Braun, J. Global ice volume during MIS 3 inferred from a sea-level analysis of sedimentary core records in the Yellow River Delta. Quatern. Sci. Rev. 152, 72–79. https://doi.org/10.1016/j.quascirev.2016.09.012 (2016).ADS 
Article 

Google Scholar 
Klein, R. T., Lohmann, K. C. & Kennedy, G. L. Elemental and isotopic proxies of paleotemperature and paleosalinity: Climate reconstruction of the marginal northeast Pacific ca. 80 ka. Geology 25, 363–366 (1997).ADS 
CAS 
Article 

Google Scholar 
Jarvis, I., Trabucho-Alexandre, J., Gröcke, D. R., Uličný, D. & Laurin, J. Intercontinental correlation of organic carbon and carbonate stable isotope records: Evidence of climate and sea-level change during the Turonian (Cretaceous). Depos. Rec. 1, 53–90. https://doi.org/10.1002/dep2.6 (2016).Article 

Google Scholar 
Chen, P. S. M. A study of the stratigraphy and molluscan fossils of the Tunghsiao area, Miaoli, Taiwan, R.O.C.. Bull. Malacol. Republic of China 4, 63–78 (1977).
Google Scholar 
Chen, W.-S. & Hsu, W.-J. The Pleistocene paleoenvironmental significance of the unearthed megafauna strata in Taiwan. Bull. Central Geol. Surv. 23, 137–163 (2010).
Google Scholar 
Chang, C. H. et al. The first archaic Homo from Taiwan. Nat. Commun. 6, 6037. https://doi.org/10.1038/ncomms7037 (2015).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Cai, B.-Q. Fossil human humerus of Late Pleistocene from the Taiwan Straits. Acta Antrhopologica Sinica 20, 178–185 (2001).
Google Scholar 
Tong, H. & Patou-Mathis, M. Mammoth and other proboscideans in China during the Late Pleistocene. Deinsea 9, 421–428 (2003).
Google Scholar 
Koch, P. L. & Barnosky, A. D. Late quaternary extinctions: State of the debate. Annu. Rev. Ecol. Evol. Syst. 37, 215–250. https://doi.org/10.1146/annurev.ecolsys.34.011802.132415 (2006).Article 

Google Scholar 
Brook, B. W. & Bowman, D. M. J. S. Explaining the Pleistocene megafaunal extinctions: Models, chronologies, and assumptions. PNAS 99, 14624–14627 (2002).ADS 
CAS 
Article 

Google Scholar 
Barnosky, A. D., Koch, P. L., Feranec, R. S., Wing, S. L. & Shabel, A. B. Assessing the causes of Late Pleistocene extinctions on the continents. Science 306, 70–75 (2004).ADS 
CAS 
Article 

Google Scholar 
Ugan, A. & Byers, D. A global perspective on the spatiotemporal pattern of the Late Pleistocene human and woolly mammoth radiocarbon record. Quatern. Int. 191, 69–81. https://doi.org/10.1016/j.quaint.2007.09.035 (2008).Article 

Google Scholar 
Adlan, Q., Davies, A. J. & John, C. M. Effects of oxygen plasma ashing treatment on carbonate clumped isotopes. Rapid Commun. Mass Spectrom. 34, e8802. https://doi.org/10.1002/rcm.8802 (2020).CAS 
Article 
PubMed 

Google Scholar 
John, C. M. & Bowen, D. Community software for challenging isotope analysis: First applications of “Easotope” to clumped isotopes. Rapid Commun. Mass Spectrom. 30, 2285–2300 (2016).ADS 
CAS 
Article 

Google Scholar 
Bernasconi, S. M. et al. Background effects on Faraday collectors in gas-source mass spectrometry and implications for clumped isotope measurements. Rapid Commun. Mass Spectrom. 27, 603–612. https://doi.org/10.1002/rcm.6490 (2013).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Bernasconi, S. M. et al. InterCarb: A community effort to improve interlaboratory standardization of the carbonate clumped isotope thermometer using carbonate standards. Geochem. Geophys. Geosyst. 22, e2020GC009588. https://doi.org/10.1029/2020GC009588 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Anderson, N. T. et al. Unified clumped isotope thermometer calibration (0.5–1,100°C) using carbonate-based standardization. Geophys. Res. Lett. 48, e2020GL092069 (2021).ADS 
CAS 
Article 

Google Scholar 
Lee, H. et al. Young colonization history of a widespread sand dollar (Echinodermata; Clypeasteroida) in western Taiwan. Quatern. Int. 528, 120–129 (2019).Article 

Google Scholar 
Reimer, P. J. et al. IntCal13 and Marine13 radiocarbon age calibration curves 0–50,000 years cal BP. Radiocarbon 55, 1869–1887 (2013).CAS 
Article 

Google Scholar  More

Baker, R. W. Membrane Technology and Applications. 3rd edn. ISBN 9780470743720. (Wiley, 2012).Wang, L. K., Chen, J. P., Hung, Y.-T., Shammas, N. K. Membrane and Desalination Technologies. ISBN 978-1-58829-940-6. (Humana Press, 2011).Mahmoudi, E. et al. Enhancing morphology and separation performance of polyamide 6,6 membranes by minimal incorporation of silver decorated graphene oxide nanoparticles. Sci. Rep. 9, 1216. https://doi.org/10.1038/s41598-018-38060-x (2019).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Penkova, A. V., Dmitrenko, M. E., Ermakov, S. S., Toikka, A. M. & Roizard, D. Novel green PVA-fullerenol mixed matrix supported membranes for separating water-THF mixtures by pervaporation. Environ. Sci. Pollut. Res. 25, 20354–20362. https://doi.org/10.1007/s11356-017-9063-9 (2018).CAS 
Article 

Google Scholar 
Atlaskin, A. A. et al. Comprehensive experimental study of membrane cascades type of “continuous membrane column” for gases high-purification. J. Membr. Sci. 572, 92–101. https://doi.org/10.1016/j.memsci.2018.10.079 (2019).CAS 
Article 

Google Scholar 
Koyuncu, I., Sengur, R., Turken, T., Guclu, S., & Pasaoglu, M.E. Advances in water treatment by microfiltration, ultrafiltration, and nanofiltration. in Advances in Membrane Technologies for Water Treatment (eds. Basile, A., Cassano, A., Rastogi, N. K.). 83–128. (Elsevier, 2015).Van der Bruggen, B. Microfiltration, ultrafiltration, nanofiltration, reverse osmosis, and forward osmosis in Fundamental Modelling of Membrane Systems, Membrane and Process Performance (ed. Luis, P.). 25–70. (Elsevier, 2018).Al Aani, S., Mustafa, T. N. & Hilal, N. Ultrafiltration membranes for wastewater and water process engineering: A comprehensive statistical review over the past decade. J. Water Process Eng. 35, 101241. https://doi.org/10.1016/j.jwpe.2020.101241 (2020).Article 

Google Scholar 
Polotskaya, G. A., Goikhman, M. Y., Podeshvo, I. V., Polotsky, A. E. & Cherkasov, A. N. Polybenzoxazinoneimides and their prepolymers as promising membrane materials. Desalination 200, 46–48 (2006).CAS 
Article 

Google Scholar 
Ulbricht, M. Advanced functional polymer membranes. Polymer 47, 2217–2262. https://doi.org/10.1016/j.polymer.2006.01.084 (2006).CAS 
Article 

Google Scholar 
Siagian, U. W. R. et al. High-performance ultrafiltration membrane: Recent progress and its application for wastewater treatment. Curr. Pollut. Rep. 7, 448–462. https://doi.org/10.1007/s40726-021-00204-5 (2021).CAS 
Article 

Google Scholar 
Polotskaya, G. A., Meleshko, T. K., Gofman, I. V., Polotsky, A. E. & Cherkasov, A. N. Polyimide ultrafiltration membranes with high thermal stability and chemical durability. Sep. Sci. Technol. 44, 3814–3831. https://doi.org/10.1080/01496390903256166 (2009).CAS 
Article 

Google Scholar 
Ohya, H., Kudryavtsev, V. V., & Semenova, S. I. Polyimide Membranes. Vol. 314. (Gordon & Breach Publishers, 1996).Liu, R., Qiao, X. & Chung, T.-S. The development of high performance P84 co-polyimide hollow fibers for pervaporation dehydration of isopropanol. Chem. Eng. Sci. 60, 6674–6686. https://doi.org/10.1016/j.ces.2005.05.066 (2005).CAS 
Article 

Google Scholar 
Yang, C. et al. Preparation and characterization of acid and solvent resistant polyimide ultrafiltration membrane. Appl. Surf. Sci. 483, 278–284. https://doi.org/10.1016/j.apsusc.2019.03.226 (2019).ADS 
CAS 
Article 

Google Scholar 
Pulyalina, AYu., Polotskaya, G. A. & Toikka, A. M. Membrane materials based on polyheteroarylenes and their application for pervaporation. Russ. Chem. Rev. 85(1), 81–98 (2016).ADS 
CAS 
Article 

Google Scholar 
Volgin, I. V. et al. Transport properties of thermoplastic R-BAPB polyimide: Molecular dynamics simulations and experiment. Polymers 11, 1775. https://doi.org/10.3390/polym11111775 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Pulyalina, A. et al. Preparation and characterization of methanol selective membranes based on polyheteroarylene–Cu(I) complexes for purification of methyl tertiary butyl ether. Polym. Int. 66(12), 1873–1882. https://doi.org/10.1002/pi.5463 (2017).CAS 
Article 

Google Scholar 
Pulyalina, A. et al. Sorption and transport of aqueous isopropanol solutions in polyimide-poly(aniline-co-anthranilic acid) composites. Russ. J. Appl. Chem. 84(5), 840–846. https://doi.org/10.1134/S107042721105017X (2011).CAS 
Article 

Google Scholar 
Pulyalina, A. et al. Novel approach to determination of sorption in pervaporation process: A case study of isopropanol dehydration by polyamidoimide urea membranes. Sci. Rep. 7, 8415. https://doi.org/10.1038/s41598-017-08420-0 (2017).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Helali, N., Shamaei, L., Rastgar, M. & Sadrzadeh, M. Development of layer-by-layer assembled polyamide-imide membranes for oil sands produced water treatment. Sci. Rep. 11, 8098. https://doi.org/10.1038/s41598-021-87601-4 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Polotskaya, G. et al. Asymmetric membranes based on copolyheteroarylenes with imide, biquinoline, and oxazinone units: Formation and characterization. Polymers 11(10), 1542. https://doi.org/10.3390/polym11101542 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
Volgin, I. V. Transport properties of thermoplastic R-BAPB polyimide: Molecular dynamics simulations and experiment. Polymers 11(11), 1775. https://doi.org/10.3390/polym11111775 (2019).CAS 
Article 
PubMed Central 

Google Scholar 
White, L. S. Transport properties of a polyimide solvent resistant nanofiltration membrane. J. Membr. Sci. 205, 191–202 (2005).Article 

Google Scholar 
Barsema, J. N., Kapantaidakis, G. C., van der Vegt, N. F. A., Koops, G. H. & Wessling, M. Preparation and characterization of highly selective dense and hollow fiber asymmetric membranes based on BTDA-TDI/MDI co-polyimide. J. Membr. Sci. 216, 195–205. https://doi.org/10.1016/S0376-7388(03)00071-1 (2003).CAS 
Article 

Google Scholar 
Pulyalina, A., Polotskaya, G., Rostovtseva, V., Pientka, Z. & Toikka, A. Improved hydrogen separation using hybrid membrane composed of nanodiamonds and P84 copolyimide. Polymers 10, 828. https://doi.org/10.3390/polym10080828 (2018).CAS 
Article 
PubMed Central 

Google Scholar 
Qiao, X. & Chung, T.-S. Fundamental characteristics of sorption, swelling, and permeation of P84 co-polyimide membranes for pervaporation dehydration of alcohols. Ind. Eng. Chem. Res. 44, 8938–8943. https://doi.org/10.1021/ie050836g (2005).CAS 
Article 

Google Scholar 
Mangindaan, D. W., Shi, G. M. & Chung, T.-S. Pervaporation dehydration of acetone using P84 co-polyimide flat sheet membranes modified by vapor phase crosslinking. J. Membr. Sci. 458, 76–85 (2014).CAS 
Article 

Google Scholar 
Hua, D., Ong, Y. K., Wang, Y., Yang, T. & Chung, T.-S. ZIF-90/P84 mixed matrix membranes for pervaporation dehydration of isopropanol. J. Membr. Sci. 453, 155–167. https://doi.org/10.1016/j.memsci.2013.10.059 (2014).CAS 
Article 

Google Scholar 
Pulyalina, AYu., Putintseva, M. N., Polotskaya, G. A., Rostovtseva, V. A. & Toikka, A. M. Pervaporation purification of oxygenate from an ethyl tert-butyl ether/ethanol azeotropic mixture. Membr. Membr. Technol. 1(2), 99–106. https://doi.org/10.1134/S2517751619020082 (2019).CAS 
Article 

Google Scholar 
Ren, J. & Li, Z. Development of asymmetric BTDA-TDI/MDI (P84) copolyimide flat sheet and hollow fiber membranes for ultrafiltration: Morphology transition and membrane performance. Desalination 285, 336–344. https://doi.org/10.1016/j.desal.2011.10.024 (2012).CAS 
Article 

Google Scholar 
Ren, J., Li, Z., Wong, F.-S. & Li, D. Development of asymmetric BTDA-TDI/MDI (P84) co-polyimide hollow fiber membranes for ultrafiltration: The influence of shear rate and approaching ratio on membrane morphology and performance. J. Membr. Sci. 248, 177–188. https://doi.org/10.1016/j.memsci.2004.09.031 (2005).CAS 
Article 

Google Scholar 
Yusoff, I. I. et al. Durable pressure filtration membranes based on polyaniline-polyimide P84 blends. Polym. Eng. Sci. 5(S1), E82–E92 (2019).Article 

Google Scholar 
Grosso, V. et al. Polymeric and mixed matrix polyimide membranes. Sep. Purif. Technol. 132, 684–696 (2014).CAS 
Article 

Google Scholar 
Renner, R. Ionic liquids: An industrial cleanup solution. Environ. Sci. Technol. 35, 410a–413a (2001).ADS 
CAS 
Article 

Google Scholar 
Wanga, H. H. A novel green solvent alternative for polymeric membrane preparation via nonsolvent-induced phase separation (NIPS). J. Membr. Sci. 574, 44–54 (2019).Article 

Google Scholar 
Lessan, F. & Foudazi, R. Effect of [EMIM][BF4] ionic liquid on the properties of ultrafiltration membranes. Polymer 210, 122977 (2020).CAS 
Article 

Google Scholar 
Xing, D. Y., Peng, N. & Chung, T.-S. Formation of cellulose acetate membranes via phase inversion using ionic liquid, [BMIM]SCN, as the solvent. Ind. Eng. Chem. Res. 49, 8761–8769 (2010).CAS 
Article 

Google Scholar 
Durmaz, E. N. & Çulfaz-Emecen, P. Z. Cellulose-based membranes via phase inversion using [EMIM]OAc-DMSO mixtures as solvent. Chem. Eng. Sci. 178, 93–103 (2018).CAS 
Article 

Google Scholar 
Grekov, K. B. Electronic Waste and Safety Problems (in Rus.). ISBN 9785891601796. (SUT, 2018).Svittsov, A. A. & Abylgaziev, TZh. Micellarly enhanced (reagent) ultrafiltration. Russ. Chem. Rev. 60(11), 1280–1283 (1991).ADS 
Article 

Google Scholar 
Petrov, S. & Stoichev, P. A. Reagent ultrafiltration purification of water contaminated with reactive dyes. Filtr. Sep. https://doi.org/10.1016/S0015-1882(02)80229-4 (2002).Article 

Google Scholar 
Leonard, M. A. & West, T. S. Chelating reactions of 1,2-dihydroxyanthraquinon-3-ylmethyl-amine-NN-diacetic acid with metal cations in aqueous media. J. Chem. Soc. 866, 4477–4486. https://doi.org/10.1039/jr9600004477 (1960).Article 

Google Scholar 
Marczenko, Z., & Balcerzak, M. Fluorine. in Separation, Preconcentration and Spectrophotometry in Inorganic Analysis (ed. Kloczko, E.). 189–197. (Elsevier, 2000).Chai, J.-D. & Head-Gordon, M. Long-range corrected hybrid density functionals with damped atom–atom dispersion corrections. Phys. Chem. Chem. Phys. 10, 6615–6620. https://doi.org/10.1039/B810189B (2008).CAS 
Article 
PubMed 

Google Scholar 
Frisch, M. J. et al. Gaussian 09, Revision C.01. (Gaussian, Inc., 2010).Ochterski, J. W. Thermochemistry in Gaussian. https://gaussian.com/thermo/ (2000).Cherkasov, A. N. A rapid analysis of ultrafiltration membrane structure. Sep. Sci. Tech. 40, 2775–2801. https://doi.org/10.1080/01496390500333111 (2005).CAS 
Article 

Google Scholar 
Zheng, Q.-Z. The relationship between porosity and kinetics parameter of membrane formation in PSF ultrafiltration membrane. J. Membr. Sci. 286, 7–11 (2006).CAS 
Article 

Google Scholar 
Barton, A. F. M. CRC Handbook of Solubility Parameter. Vol. 768. (CRC Press, 1991).Tan, X. & Rodrigue, D. A review on porous polymeric membrane preparation. Part I: Production techniques with polysulfone and poly (vinylidene fluoride). Polymers 11, 1160 (2019).Article 

Google Scholar 
Mulder, M. H. V. Phase Inversion Membranes. Membrane Preparation. Vol. 3331. (Academic Press, 2000).Quijada-Maldonado, E. Pilot plant study on the extractive distillation of toluene–methylcyclohexane mixtures using NMP and the ionic liquid [hmim][TCB] as solvents. Sep. Purif. Technol. 166, 196–204 (2016).CAS 
Article 

Google Scholar 
Polotskaya, G. A. et al. Aromatic copolyamides with anthrazoline units in the backbone: Synthesis, characterization, pervaporation application. Polymers 8(10), 362. https://doi.org/10.3390/polym8100362 (2016).CAS 
Article 
PubMed Central 

Google Scholar 
Mao, J. X. Interactions in 1-ethyl-3-methyl imidazolium tetracyanoborate ion pair: Spectroscopic and density functional study. J. Mol. Struct. 1038, 12–18 (2013).ADS 
CAS 
Article 

Google Scholar  More

Wedding, L. M. et al. From principles to practice: a spatial approach to systematic conservation planning in the deep sea. Proc. R. Soc. B Biol. Sci. 280, 20131684 (2013).CAS 
Article 

Google Scholar 
Kaiser, S., Smith, C. R. & MartínezArbizu, P. Editorial: Biodiversity of the Clarion Clipperton Fracture Zone. Mar. Biodivers. 47, 259–264 (2017).Article 

Google Scholar 
Bluhm, H. Monitoring megabenthic communities in abyssal manganese nodule sites of the East Pacific Ocean in association with commercial deep-sea mining. Aquat. Conserv. Mar. Freshw. Ecosyst. 4, 187–201 (1994).Article 

Google Scholar 
Simon-Lledó, E. et al. Multi-scale variations in invertebrate and fish megafauna in the mid-eastern Clarion Clipperton Zone. Prog. Oceanogr. 187, 102405 (2020).Article 

Google Scholar 
Simon-Lledó, E. et al. Megafaunal variation in the abyssal landscape of the Clarion Clipperton Zone. Prog. Oceanogr. 170, 119–133 (2019).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hein, J. R., Mizell, K., Koschinsky, A. & Conrad, T. A. Deep-ocean mineral deposits as a source of critical metals for high- and green-technology applications: Comparison with land-based resources. Ore Geol. Rev. 51, 1–14 (2013).Article 

Google Scholar 
Kuhn, T., Wegorzewski, A., Rühlemann, C. & Vink, A. Composition, formation, and occurrence of polymetallic nodules. In Deep-Sea Mining: Resource Potential Technical and Environmental Considerations (ed. Sharma, R.) 23–63 (Springer, 2017). https://doi.org/10.1007/978-3-319-52557-0_2.Chapter 

Google Scholar 
Simon-Lledó, E. et al. Ecology of a polymetallic nodule occurrence gradient: Implications for deep-sea mining. Limnol. Oceanogr. 64, 1883–1894 (2019).ADS 
PubMed 
PubMed Central 
Article 

Google Scholar 
International Seabed Authority. Deep Seabed Minerals Contractors. https://www.isa.org.jm/deep-seabed-minerals-contractors?qt-contractors_tabs_alt=0#qt-contractors_tabs_alt (2020).Jones, D. O. B. et al. Biological responses to disturbance from simulated deep-sea polymetallic nodule mining. PLoS ONE 12, e0171750 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Niner, H. J. et al. Deep-sea mining with no net loss of biodiversity: An impossible aim. Front. Mar. Sci. 5, 53 (2018).ADS 
Article 

Google Scholar 
Kuhn, T., Uhlenkott, K., Vink, A., Rühlemann, C. & MartínezArbizu, P. Manganese nodule fields from the Northeast Pacific as benthic habitats. In Seafloor Geomorphology as Benthic Habitat: GeoHab Atlas of Seafloor Geomorphic Features and Benthic Habitats (eds Harris, P. T. & Baker, E.) 933–947 (Elsevier, 2020).Chapter 

Google Scholar 
Vanreusel, A., Hilario, A., Ribeiro, P. A., Menot, L. & Martínez Arbizu, P. Threatened by mining, polymetallic nodules are required to preserve abyssal epifauna. Sci. Rep. 6, 26808 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Amon, D. J. et al. Insights into the abundance and diversity of abyssal megafauna in a polymetallic-nodule region in the eastern Clarion-Clipperton Zone. Sci. Rep. 6, 30492 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
De Forges, B. R., Koslow, J. A. & Poore, G. C. B. Diversity and endemism of the benthic seamount fauna in the southwest Pacific. Nature 405, 944–947 (2000).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Lodge, M. et al. Seabed mining: International Seabed Authority environmental management plan for the Clarion-Clipperton Zone: A partnership approach. Mar. Policy 49, 66–72 (2014).Article 

Google Scholar 
Cuvelier, D. et al. Are seamounts refuge areas for fauna from polymetallic nodule fields?. Biogeosciences 17, 2657–2680 (2020).ADS 
Article 

Google Scholar 
Wedding, L. M. et al. Managing mining of the deep seabed. Science 349, 144–145 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
International Seabed Authority. Decision of the Council of the International Seabed Authority relating to amendments to the Regulations on the Prospecting and Exploration for Polymetallic Nodules in the Area and related matters. (2013).International Seabed Authority. Recommendations for the guidance of contractors for the assessment of the possible environmental impacts arising from exploration for marine minerals in the Area. (2020).Jones, D. O. B., Ardron, J. A., Colaço, A. & Durden, J. M. Environmental considerations for impact and preservation reference zones for deep-sea polymetallic nodule mining. Mar. Policy 118, 103312 (2020).Article 

Google Scholar 
Uhlenkott, K., Vink, A., Kuhn, T. & Martínez Arbizu, P. Predicting meiofauna abundance to define preservation and impact zones in a deep-sea mining context using random forest modelling. J. Appl. Ecol. 57, 1210–1221 (2020).Article 

Google Scholar 
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 
Article 

Google Scholar 
Ostmann, A. & Martínez Arbizu, P. Predictive models using random forest regression for distribution patterns of meiofauna in Icelandic waters. Mar. Biodivers. 48, 719–735 (2018).Article 

Google Scholar 
Uhlenkott, K., Vink, A., Kuhn, T., Gillard, B. & Martínez Arbizu, P. Meiofauna in a potential deep-sea mining area: Influence of temporal and spatial variability on small scale abundance models. Diversity 13, 3 (2021).CAS 
Article 

Google Scholar 
Gazis, I.-Z., Schoening, T., Alevizos, E. & Greinert, J. Quantitative mapping and predictive modeling of Mn nodules’ distribution from hydroacoustic and optical AUV data linked by random forests machine learning. Biogeosciences 15, 7347–7377 (2018).ADS 
Article 

Google Scholar 
Ellis, N., Smith, S. J. & Pitcher, C. R. Gradient forests: Calculating importance gradients on physical predictors. Ecology 93, 156–168 (2012).PubMed 
Article 

Google Scholar 
Miljutina, M. A., Miljutin, D. M., Mahatma, R. & Galéron, J. Deep-sea nematode assemblages of the Clarion-Clipperton Nodule Province (Tropical North-Eastern Pacific). Mar. Biodivers. 40, 1–15 (2010).Article 

Google Scholar 
Miljutin, D., Miljutina, M. & Messié, M. Changes in abundance and community structure of nematodes from the abyssal polymetallic nodule field, Tropical Northeast Pacific. Deep Sea Res. Oceanogr. Res. Pap. 106, 126–135 (2015).ADS 
Article 

Google Scholar 
Pape, E., Bezerra, T. N., Hauquier, F. & Vanreusel, A. Limited spatial and temporal variability in meiofauna and nematode communities at distant but environmentally similar sites in an area of interest for deep-sea mining. Front. Mar. Sci. 4, 205 (2017).Article 

Google Scholar 
Hauquier, F. et al. Distribution of free-living marine nematodes in the Clarion-Clipperton Zone: Implications for future deep-sea mining scenarios. Biogeosciences 16, 3475–3489 (2019).ADS 
CAS 
Article 

Google Scholar 
Uhlenkott, K., Vink, A., Kuhn, T. & Martínez Arbizu, P. Meiofauna abundance and distribution predicted with random forest regression in the German exploration area for polymetallic nodule mining, Clarion Clipperton Fracture Zone, Pacific. (2020).Calinski, T. & Harabasz, J. A dendrite method for cluster analysis. Commun. Stat. Theory Methods 3, 1–27 (1974).MathSciNet 
MATH 
Article 

Google Scholar 
Thiel, H. et al. The large-scale environmental impact experiment DISCOL: Reflection and foresight. Deep Sea Res. 48, 3869–3882 (2001).ADS 
Article 

Google Scholar 
Brown, A., Wright, R., Mevenkamp, L. & Hauton, C. A comparative experimental approach to ecotoxicology in shallow-water and deep-sea holothurians suggests similar behavioural responses. Aquat. Toxicol. 191, 10–16 (2017).CAS 
PubMed 
Article 

Google Scholar 
McClain, C. R. Seamounts: identity crisis or split personality?. J. Biogeogr. 34, 2001–2008 (2007).Article 

Google Scholar 
Rogers, A. D. The biology of seamounts: 25 years on. In Advances in Marine Biology Vol. 79 (ed. Sheppard, C.) 137–224 (Academic Press, 2018).
Google Scholar 
Durden, J. M., Bett, B. J., Jones, D. O. B., Huvenne, V. A. I. & Ruhl, H. A. Abyssal hills–hidden source of increased habitat heterogeneity, benthic megafaunal biomass and diversity in the deep sea. Prog. Oceanogr. 137, 209–218 (2015).ADS 
Article 

Google Scholar 
Durden, J. M. et al. Megafaunal ecology of the western Clarion Clipperton Zone. Front. Mar. Sci. 8, 671062 (2021).ADS 
Article 

Google Scholar 
Jones, D. O. B. et al. Environment, ecology, and potential effectiveness of an area protected from deep-sea mining (Clarion Clipperton Zone, abyssal Pacific). Prog. Oceanogr. 197, 102653 (2021).Article 

Google Scholar 
Lutz, M. J., Caldeira, K., Dunbar, R. B. & Behrenfeld, M. J. Seasonal rhythms of net primary production and particulate organic carbon flux to depth describe the efficiency of biological pump in the global ocean. J. Geophys. Res. Oceans 112, C10011 (2007).ADS 
Article 
CAS 

Google Scholar 
Volz, J. B. et al. Natural spatial variability of depositional conditions, biogeochemical processes and element fluxes in sediments of the eastern Clarion-Clipperton Zone. Pacific Ocean. Deep Sea Res. 140, 159–172 (2018).CAS 
Article 

Google Scholar 
Smith, C. R., De Leo, F. C., Bernardino, A. F., Sweetman, A. K. & Martínez Arbizu, P. Abyssal food limitation, ecosystem structure and climate change. Trends Ecol. Evol. 23, 518–528 (2008).PubMed 
Article 

Google Scholar 
Ramirez-Llodra, E. et al. Deep, diverse and definitely different: unique attributes of the world’s largest ecosystem. Biogeosciences 7, 2851–2899 (2010).ADS 
Article 

Google Scholar 
Kharbush, J. J. et al. Particulate organic carbon deconstructed: Molecular and chemical composition of particulate organic carbon in the ocean. Front. Mar. Sci. 7, 518 (2020).Article 

Google Scholar 
Smith, C. R. et al. Latitudinal variations in benthic processes in the abyssal equatorial Pacific: Control by biogenic particle flux. Deep Sea Res. 44, 2295–2317 (1997).ADS 
CAS 
Article 

Google Scholar 
Kuhn, T. & Rühlemann, C. Exploration of polymetallic nodules and resource assessment: A case study from the German contract area in the Clarion-Clipperton Zone of the tropical Northeast Pacific. Minerals 11, 618 (2021).ADS 
CAS 
Article 

Google Scholar 
Christodoulou, M. et al. Unexpected high abyssal ophiuroid diversity in polymetallic nodule fields of the northeast Pacific Ocean and implications for conservation. Biogeosciences 17, 1845–1876 (2020).ADS 
CAS 
Article 

Google Scholar 
Valavi, R., Elith, J., Lahoz-Monfort, J. J. & Guillera-Arroita, G. Modelling species presence-only data with random forests. Ecography 44, 1731–1742 (2021).Article 

Google Scholar 
Wiedicke-Hombach, M. & Shipboard Scientific Party. Campaign “MANGAN 2008” with R/V Kilo Moana. (2009).Hijmans, R. J. raster: Geographic Data Analysis and Modeling. (2017).Kaufman, L. & Rousseeuw, P. J. Clustering Large Applications (Program CLARA). in Finding Groups in Data 126–163 (Wiley, 1990). https://doi.org/10.1002/9780470316801.ch3.Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M. & Hornik, K. cluster. (2019).Langenkämper, D., Zurowietz, M., Schoening, T. & Nattkemper, T. W. BIIGLE 2.0: Browsing and annotating large marine image collections. Front. Mar. Sci. 4, 83 (2017).Article 

Google Scholar 
Simon-Lledó, E. et al. Preliminary observations of the abyssal megafauna of Kiribati. Front. Mar. Sci. 6, 605 (2019).Article 

Google Scholar 
Amon, D. J. et al. Megafauna of the UKSRL exploration contract area and eastern Clarion-Clipperton Zone in the Pacific Ocean: Annelida, Arthropoda, Bryozoa, Chordata, Ctenophora, Mollusca. Biodivers. Data J. 5, e14598 (2017).Article 

Google Scholar 
Molodtsova, T. N. & Opresko, D. M. Black corals (Anthozoa: Antipatharia) of the Clarion-Clipperton Fracture Zone. Mar. Biodivers. 47, 349–365 (2017).Article 

Google Scholar 
Kersken, D., Janussen, D. & MartínezArbizu, P. Deep-sea glass sponges (Hexactinellida) from polymetallic nodule fields in the Clarion-Clipperton Fracture Zone (CCFZ), northeastern Pacific: Part II—Hexasterophora. Mar. Biodivers. 49, 947–987 (2019).Article 

Google Scholar 
Horton, T. et al. Recommendations for the standardisation of open taxonomic nomenclature for image-based identifications. Front. Mar. Sci. 8, 620702 (2021).Article 

Google Scholar 
Hughes, J. A. & Gooday, A. J. Associations between living benthic foraminifera and dead tests of Syringammina fragilissima (Xenophyophorea) in the Darwin Mounds region (NE Atlantic). Deep Sea Res. 51, 1741–1758 (2004).Article 

Google Scholar 
Liaw, A. & Wiener, M. Classification and regression by random Forest. R News 2, 18–22 (2002).
Google Scholar 
Oksanen, J. et al. vegan: Community Ecology Package. (2019).R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2019).Wickham, H. Reshaping data with the reshape package. J. Stat. Softw. 21, 1–20 (2007).Article 

Google Scholar 
Wickham, H. The split-apply-combine strategy for data analysis. J. Stat. Softw. 40, 1–29 (2011).
Google Scholar 
Garnier, S. viridisLite: Default Color Maps from ‘matplotlib’ (Lite Version). (2018).Rabosky, A. R. D. et al. Coral snakes predict the evolution of mimicry across New World snakes. Nat. Commun. 7, 1–9 (2016).
Google Scholar 
Smith, M. R. Ternary: An R package for creating ternary plots. Zenodo https://doi.org/10.5281/zenodo.1068996 (2017). More

Bowman, D. M. J. S. et al. Vegetation fires in the Anthropocene. Nat. Rev. Earth Environ. 1, 500–515 (2020).ADS 
Article 

Google Scholar 
Andela, N. et al. A human-driven decline in global burned area. Science 356, 1356–1362 (2017).ADS 
CAS 
Article 

Google Scholar 
United Nations Environment Programme. Spreading like Wildfire–The Rising Threat of Extraordinary Landscape Fires. A UNEP Rapid Response Assessment. (United Nations Environment Programme, Nairobi, 2022).Williams, A. P. et al. Observed impacts of anthropogenic climate change on wildfire in California. Earth’s Future 7, 892–910 (2019).ADS 
Article 

Google Scholar 
Abatzoglou, J. T. & Williams, A. P. Impact of anthropogenic climate change on wildfire across western US forests. Proc. Natl Acad. Sci. USA 113, 11770–11775 (2016).ADS 
CAS 
Article 

Google Scholar 
Dennison, P. E., Brewer, S. C., Arnold, J. D. & Moritz, M. A. Large wildfire trends in the western United States, 1984–2011. Geophys. Res. Lett. 41, 2928–2933 (2014).ADS 
Article 

Google Scholar 
Westerling, A. L. Increasing western US forest wildfire activity: sensitivity to changes in the timing of spring. Philos. Trans. R. Soc. B: Biol. Sci. 371, 20150178 (2016).Article 

Google Scholar 
Pyne, S. J. Fire in America: A Cultural History of Wildland and Rural Fire. (University of Washington Press, 2017).Fire and Resource Assessment Program. Fire Perimeters. Available: https://frap.fire.ca.gov/frap-projects/fire-perimeters/. (California Department of Forestry & Fire Protection, 2018).Westerling, A. L., Hidalgo, H. G., Cayan, D. R. & Swetnam, T. W. Warming and earlier spring increase Western U.S. forest wildfire activity. Science 313, 940–943 (2006).ADS 
CAS 
Article 

Google Scholar 
Starrs, C. F., Butsic, V., Stephens, C. & Stewart, W. The impact of land ownership, firefighting, and reserve status on fire probability in California. Environ. Res. Lett. 13, 034025 (2018).ADS 
Article 

Google Scholar 
Lydersen, J. M. et al. Evidence of fuels management and fire weather influencing fire severity in an extreme fire event. Ecol. Appl. 27, 2013–2030 (2017).Article 

Google Scholar 
Parsons, D. J. & DeBenedetti, S. H. Impact of fire suppression on a mixed-conifer forest. For. Ecol. Manag. 2, 21–33 (1979).Article 

Google Scholar 
Vose, R., Easterling, D. R., Kunkel, K. & Wehner, M. Temperature Changes in the United States. (NASA, 2017).Balch, J. K. et al. Human-started wildfires expand the fire niche across the United States. Proc. Natl Acad. Sci. USA 114, 2946–2951 (2017).ADS 
CAS 
Article 

Google Scholar 
Stephens, S. L., Martin, R. E. & Clinton, N. E. Prehistoric fire area and emissions from California’s forests, woodlands, shrublands, and grasslands. For. Ecol. Manag. 251, 205–216 (2007).Article 

Google Scholar 
Sugihara, N. G., Van Wagtendonk, J. W., Fites-Kaufman, J., Shaffer, K. E. & Thode, A. E. Fire in California’s Ecosystems. (University of California Press, 2006).Jin, Y. et al. Identification of two distinct fire regimes in Southern California: implications for economic impact and future change. Environ. Res. Lett. 10, 094005 (2015).ADS 
Article 

Google Scholar 
Trollope, W. in Ecological Effects of Fire In South African Ecosystems. 199–217 (Springer, 1984).Byram, G. M. in Forest Fire: Control and Use (ed. Davis, K. P.) 155–182 (McGraw-Hill, 1959).McLauchlan, K. K. et al. Fire as a fundamental ecological process: Research advances and frontiers. J. Ecol. https://doi.org/10.1111/1365-2745.13403 (2020).Brando, P. M. et al. Abrupt increases in Amazonian tree mortality due to drought–fire interactions. Proc. Natl Acad. Sci. USA 111, 6347–6352 (2014).ADS 
CAS 
Article 

Google Scholar 
Schroeder, W., Oliva, P., Giglio, L. & Csiszar, I. A. The New VIIRS 375m active fire detection data product: Algorithm description and initial assessment. Remote Sens. Environ. 143, 85–96 (2014).ADS 
Article 

Google Scholar 
Rothermel, R. C. A Mathematical Model for Predicting Fire Spread in Wildland Fuels (USFS, 1972).Hood, S. M., Varner, J. M., van Mantgem, P. & Cansler, C. A. Fire and tree death: understanding and improving modeling of fire-induced tree mortality. Environ. Res. Lett. 13, 113004 (2018).ADS 
Article 

Google Scholar 
Cattau, M. E., Wessman, C., Mahood, A., Balch, J. K. & Poulter, B. Anthropogenic and lightning‐started fires are becoming larger and more frequent over a longer season length in the USA. Glob. Ecol. Biogeogr. 29, 668–681 (2020).Article 

Google Scholar 
Abatzoglou, J. T., Balch, J. K., Bradley, B. A. & Kolden, C. A. Human-related ignitions concurrent with high winds promote large wildfires across the USA. Int. J. Wildland Fire 27, 377–386 (2018).Article 

Google Scholar 
Fried, J. S. et al. Predicting the effect of climate change on wildfire behavior and initial attack success. Clim. Change 87, 251–264 (2008).Article 

Google Scholar 
van Wagtendonk, J. W. The history and evolution of wildland fire use. Fire Ecol. 3, 3–17 (2007).Article 

Google Scholar 
Sullivan, A. L. Wildland surface fire spread modelling, 1990–2007. 2: Empirical and quasi-empirical models. Int. J. Wildland Fire 18, 369–386 (2009).Article 

Google Scholar 
Wang, X. et al. Projected changes in fire size from daily spread potential in Canada over the 21st century. Environ. Res. Lett. 15, 104048 (2020).ADS 
Article 

Google Scholar 
Parks, S. A. et al. High-severity fire: evaluating its key drivers and mapping its probability across western US forests. Environ. Res. Lett. 13, 044037 (2018).ADS 
Article 

Google Scholar 
Hantson, S. et al. The status and challenge of global fire modelling. Biogeosciences 13, 3359–3375 (2016).ADS 
Article 

Google Scholar 
Reinhardt, E. D. First Order Fire Effects Model: FOFEM 4.0, User’s Guide. (Intermountain Forest and Range Experiment Station, Forest Service, US …, 1997).Jolly, W. M. et al. Climate-induced variations in global wildfire danger from 1979 to 2013. Nat. Commun. 6, 1–11 (2015).CAS 
Article 

Google Scholar 
Pateiro-Lopez, B. & Rodriguez-Casal, A. alphahull: Generalization of the Convex Hull of a Sample of Points in the Plane v. R package version 2.2 (2019).Edelsbrunner, H., Kirkpatrick, D. & Seidel, R. On the shape of a set of points in the plane. IEEE Trans. Inf. theory 29, 551–559 (1983).MathSciNet 
Article 

Google Scholar 
Rodríguez Casal, A. & Pateiro López, B. Generalizing the Convex Hull of A Sample: the R Package alphahull. (2010).Bell, D. M. et al. Multiscale divergence between Landsat-and lidar-based biomass mapping is related to regional variation in canopy cover and composition. Carbon Balance Manag. 13, 15 (2018).Article 

Google Scholar 
Abatzoglou, J. T. Development of gridded surface meteorological data for ecological applications and modelling. Int. J. Climatol. 33, 121–131 (2013).Article 

Google Scholar 
MTBS. Monitoring Trends in Burn Severity Data Access: Fire Level Geospatial Data. (MTBS). (2018).Miller, J. D. et al. Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA. Remote Sens. Environ. 113, 645–656 (2009).ADS 
Article 

Google Scholar 
Homer, C. et al. Completion of the 2011 National Land Cover Database for the conterminous United States–representing a decade of land cover change information. Photogrammetric Eng. Remote Sens. 81, 345–354 (2015).
Google Scholar  More

Sol, D., Bacher, S., Reader, S. M. & Lefebvre, L. Brain size predicts the success of mammal species introduced into novel environments. Am. Nat. 172(Suppl. 1), S63–S71 (2008).PubMed 
Article 

Google Scholar 
González-Lagos, C., Sol, D. & Reader, S. M. Large-brained mammals live longer. J. Evol. Biol. 23, 1064–1074 (2010).PubMed 
Article 

Google Scholar 
Gonda, A., Herczeg, G. & Merilä, J. Evolutionary ecology of intraspecific brain size variation: A review. Ecol. Evol. 3(8), 2751–2764 (2013).PubMed 
PubMed Central 
Article 

Google Scholar 
Benson-Amram, S., Dantzer, B., Stricker, G., Swanson, E. M. & Holekamp, K. E. Brain size predicts problem-solving ability in mammalian carnivores. PNAS 113(9), 2532–2537 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Näslund, J., Aarestrup, K., Thomassen, S. T. & Johnsson, J. I. Early enrichment effects on brain development in hatchery-reared Atlantic salmon (Salmo salar): No evidence for a critical period. Can. J. Fish. Aquat. Sci. 69(9), 1481–1490 (2012).Article 

Google Scholar 
Logan, C. J., Kruuk, L. E. B., Stanley, R., Thompson, A. M. & Clutton-Brock, T. H. Endocranial volume is heritable and is associated with longevity and fitness in a wild mammal. R. Soc. Open Sci. 3(12), 160622 (2016).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Yamaguchi, N., Kitchener, A. C., Gilissen, E. & MacDonald, D. W. Brain size of the lion (Panthera leo) and the tiger (P. tigris): Implications for intrageneric phylogeny, intraspecific differences and the effects of captivity. Biol. J. Linn. Soc. 98, 85–93 (2009).Article 

Google Scholar 
Turschwell, M. P. & White, C. R. The effects of laboratory housing and spatial enrichment on brain size and metabolic rate in the eastern mosquitofish Gambusia holbrooki. Biol. Open. 5(3), 205–210 (2016).PubMed 
PubMed Central 
Article 

Google Scholar 
Welniak-Kaminska, M. et al. Volumes of brain structures in captive wild-type and laboratory rats: 7T magnetic resonance in vivo automatic atlas-based study. PLoS ONE 14(4), e0215348 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Guay, P. J., Parrott, M. & Selwood, L. Captive breeding does not alter brain volume in a marsupial over a few generations. Zoo Biol. 31, 82–86 (2012).PubMed 
Article 

Google Scholar 
Isler, K. et al. Endocranial volumes of primate species: Scaling analyses using a comprehensive and reliable data set. J. Hum. Evol. 55(6), 967–978 (2008).PubMed 
Article 

Google Scholar 
Burns, J. G., Saravanan, A. & Rodd, F. H. Rearing environment affects the brain size of guppies: Lab-reared guppies have smaller brains than wild-caught guppies. Ethol. 115(2), 122–133 (2009).Article 

Google Scholar 
Kruska, D. On the evolutionary significance of encephalization in some eutherian mammals: Effects of adaptive radiation, domestication, and feralization. Brain Behav. Evol. 65(2), 73–108 (2005).PubMed 
Article 

Google Scholar 
Logan, C. J. & Clutton-Brock, T. H. Validating methods for estimating endocranial volume in individual red deer (Cervus elaphus). Behav. Processes. 92, 143–146 (2013).PubMed 
Article 

Google Scholar 
Colby, A. E., Kimock, C. M. & Higham, J. P. Endocranial volume is variable and heritable, but not related to fitness, in a free-ranging primate. Sci. Rep. 11, 1–11 (2021).Article 
CAS 

Google Scholar 
Stuermer, I. W. & Wetzel, W. Early experience and domestication affect auditory discrimination learning, open field behaviour and brain size in wild Mongolian gerbils and domesticated Laboratory gerbils (Meriones unguiculatus forma domestica). Behav. Brain Res. 173, 11–21 (2006).PubMed 
Article 

Google Scholar 
Agnvall, B., Bélteky, J. & Jensen, P. Brain size is reduced by selection for tameness in red junglefowl-correlated effects in vital organs. Sci. Rep. 7(3306), 1–7 (2017).CAS 

Google Scholar 
Röhrs, M. & Ebinger, P. Wild is not really wild: Brain weight of wild and domestic mammals. Berl. Munch. Tierarztliche Wochenschrift. 112(6–7), 234–238 (1999).
Google Scholar 
Smith, B. P., Lucas, T. A., Norris, R. M. & Henneberg, M. Brain size/body weight in the dingo (Canis dingo): Comparisons with domestic and wild canids. Aust. J. Zool. 65(5), 292–301 (2017).Article 

Google Scholar 
Roberts, T., McGreevy, P. & Valenzuela, M. Human induced rotation and reorganization of the brain of domestic dogs. PLoS ONE 5(7), e11946 (2010).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Pollen, A. A. et al. Environmental complexity and social organization sculpt the brain in Lake Tanganyikan cichlid fish. Brain Behav. Evol. 70, 21–39 (2007).PubMed 
Article 

Google Scholar 
Kihslinger, R. L., Lema, S. C. & Nevitt, G. A. Environmental rearing conditions produce forebrain differences in wild Chinook salmon Oncorhynchus tshawytscha. Comp. Biochem. Physiol. 145(2), 145–151 (2006).CAS 
Article 

Google Scholar 
Guay, P. J. & Iwaniuk, A. N. Captive breeding reduces brain volume in waterfowl (Anseriformes). Condor 110(2), 276–284 (2008).Article 

Google Scholar 
Diamond, M. C., Ingham, C. A., Johnson, R. E., Bennett, E. L. & Rosenzweig, M. R. Effects of environment on morphology of rat cerebral cortex and hippocampus. J. Neurobiol. 7, 75–85 (1976).CAS 
PubMed 
Article 

Google Scholar 
Courtney Jones, S. K., Munn, A. J. & Byrne, P. G. Effect of captivity on morphology: Negligible changes in external morphology mask significant changes in internal morphology. R. Soc. Open Sci. 5(5), 1–13 (2018).Article 

Google Scholar 
Kruska, D. & Röhrs, M. Comparative-quantitative investigations on brains of feral pigs from the Galapagos Islands and of European domestic pigs. Z. Anat. Entwicklungsgesch. 144(1), 61–73 (1974).CAS 
PubMed 
Article 

Google Scholar 
Kruska, D. Changes of brain size in Tylopoda during phylogeny and caused by domestication. Verh. Dtsch. Zool. Ges. 75, 173–183 (1982).
Google Scholar 
Groves, C. P. Skull-changes due to captivity in certain Equidae. Z. Säugetierkd. 31, 44–46 (1966).
Google Scholar 
Groves, C. P. The skulls of Asian rhinoceroses: Wild and captive. Zoo Biol. 1, 251–261 (1982).Article 

Google Scholar 
Hollister, N. Some effects of environment and habit on captive lions. Proc. US. Natl. Mus. 53, 177–193 (1917).Article 

Google Scholar 
Price, E. O. Behavioral development in animals undergoing domestication. Appl. Anim. Behav. Sci. 65(3), 245–271 (1999).Article 

Google Scholar 
Wolff, J. Das Gesetz der Transformation der Knochen (A. Hirchwild, 1892).
Google Scholar 
Herring, S. W. Formation of the vertebrate face: Epigenetic and functional influences. Am. Zool. 33, 472–483 (1993).Article 

Google Scholar 
Wroe, S. & Milne, N. Convergence and remarkably consistent constraint in the evolution of carnivore skull shape. Evol. 61(5), 1251–1260 (2007).Article 

Google Scholar 
Damasceno, E. M., Hingst-Zaher, E. & Astúa, D. Bite force and encephalization in the Canidae (Mammalia: Carnivora). J. Zool. 290(4), 246–254 (2013).Article 

Google Scholar 
Van Valkenburgh, B. Deja vu: the evolution of feeding morphologies in the Carnivora. Integr. Comp. Biol. 47, 147–163 (2007).PubMed 
Article 

Google Scholar 
Van Valkenburgh, B. Carnivore dental adaptations and diet: A study of trophic diversity within guilds in Carnivore behavior, ecology, and evolution (ed. Gittleman, J. L.) 410–436 (Springer Science & Business Media, 1989).Slater, G. J., Dumont, E. R. & Van Valkenburgh, B. Implications of predatory specialization for cranial form and function in canids. J. Zool. 278(3), 181–188 (2009).Article 

Google Scholar 
Michaud, M., Veron, G. & Fabre, A. C. Phenotypic integration in feliform carnivores: Covariation patterns and disparity in hypercarnivores versus generalists. Evol. 74(12), 2681–2702 (2020).Article 

Google Scholar 
O’Regan, H. J. & Kitchener, A. C. The effects of captivity on the morphology of captive, domesticated and feral mammals. Mamm. Rev. 35, 215–230 (2005).Article 

Google Scholar 
Kapoor, V., Antonelli, T., Parkinson, J. A. & Hartstone-Rose, A. Oral health correlates of captivity. Res. Vet. Sci. 107, 213–219 (2016).PubMed 
Article 

Google Scholar 
Mitchell, D. R., Wroe, S., Ravosa, M. J. & Menegaz, R. A. More challenging diets sustain feeding performance: Applications toward the captive rearing of wildlife. Integr. Org. Biol. 3, 1–13 (2021).
Google Scholar 
Curtis, A. A., Orke, M., Tetradis, S. & Van Valkenburgh, B. Diet-related differences in craniodental morphology between captive-reared and wild coyotes, Canis latrans (Carnivora: Canidae). Biol. J. Linn. Soc. 123(3), 677–693 (2018).Article 

Google Scholar 
Siciliano-Martina, L., Light, J. E. & Lawing, A. M. Cranial morphology of captive mammals: A meta-analysis. Front. Zool. 18(4), 1–13 (2021).
Google Scholar 
Corruccini, R. S. & Beecher, R. M. Occlusal variation related to soft diet in a nonhuman primate. Science 218, 74–75 (1982).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ramirez Rozzi, F. V., González-José, R. & Pucciarelli, H. M. Cranial growth in normal and low-protein-fed Saimiri An environmental heterochrony. J. Hum. Evol. 49(4), 515–535 (2005).PubMed 
Article 

Google Scholar 
Taylor, A. B. & van Schaik, C. P. Variation in brain size and ecology in Pongo. J. Hum. Evol. 52, 59–71 (2007).PubMed 
Article 

Google Scholar 
AZA Canid TAG. Large Canid (Canidae) Care Manual. (Association of Zoos and Aquariums, 2012).Mexican Wolf Species Survival Plan. Mexican Gray Wolf Husbandry Manual: Guidelines for Captive Management (2009 edition). (Mexican Wolf Species Survival Plan and U.S. Fish and Wildlife Service, 2009).Carrera, R. et al. Comparison of Mexican wolf and coyote diets in Arizona and New Mexico. The J. Wildl. Manag. 72(2), 376–381 (2008).Article 

Google Scholar 
Reed, J. E. et al. Diets of free-ranging Mexican gray wolves in Arizona and New Mexico. Wildl. Soc. Bull. 34(4), 1127–1133 (2006).Article 

Google Scholar 
Kazimierska, K., Biel, W. & Witkowicz, R. Mineral composition of cereal and cereal-free dry dog foods versus nutritional guidelines. Molecules 25(21), 1–24 (2020).Article 
CAS 

Google Scholar 
Pezzali, J. G. & Aldrich, C. G. Effect of ancient grains and grain-free carbohydrate sources on extrusion parameters and nutrient utilization by dogs. J. Anim. Sci. 98(2), 3758–3767 (2019).Article 

Google Scholar 
Hartstone-Rose, A., Selvey, H., Villari, J. R., Atwell, M. & Schmidt, T. The three-dimensional morphological effects of captivity. PLoS ONE 9(11), 1–15 (2014).Article 
CAS 

Google Scholar 
Siciliano-Martina, L., Light, J. E. & Lawing, A. M. Changes in canid cranial morphology induced by captivity and conservation implications. Biol. Conserv. 257, 109143 (2021).Article 

Google Scholar 
Hedrick, P. W. & Fredrickson, R. Genetic rescue guidelines with examples from Mexican wolves and Florida panthers. Conserv. Genet. 11(2), 615–626 (2010).Article 

Google Scholar 
Greely, S. E. Mexican Wolf, Canis lupus baileyi, International Studbook 2018. Palm Desert, California. (2018).Kalinowski, S. T., Hedrick, P. W. & Miller, P. S. No inbreeding depression observed in Mexican and red wolf captive breeding programs. Conserv. Biol. 13(6), 1371–1377 (1999).Article 

Google Scholar 
Sakai, S. T., Whitt, B., Arsznov, B. M. & Lundrigan, B. L. Endocranial development in the coyote (Canis latrans) and gray wolf (Canis lupus): A computed tomographic study. Brain Behav. Evol. 91(2), 1–18 (2018).Article 

Google Scholar 
Van Valkenburgh, B. Skeletal and dental predictors of body mass in carnivores in Body size in mammalian paleobiology: estimation and biological implications (eds. Damuth, J. & MacFadden, B. J.) (Cambridge University Press, 1990).Rohlf, F. J. TPSDig2: a program for landmark development and analysis (2001).Siciliano-Martina, L., Light, J. E., Riley, D. G. & Lawing, A. M. One of these wolves is not like the other: morphological effects and conservation implications of captivity in Mexican wolves. Anim. Conserv. 25, 77–90 (2021).Article 

Google Scholar 
Zelditch, M. L., Donald, L., Swiderski, H., Sheets, D. & Fink, W. L. Geometric morphometrics for biologists: a primer. (Elsevier Academic Press, 2004).Coster, A. pedigree: Pedigree functions. R package version 1.4 (2013).Traylor-Holzer, K. (ed.). PMx user’s manual. Version 1.0. Apple Valley, MN: IUCN SSC Conservation Breeding Specialist Group. (2011).Thomason, J. J. Cranial strength in relation to estimated biting forces in some Mammals. Can. J. Zool. 69, 2326–2333 (1991).Article 

Google Scholar 
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods. 9(7), 676–682 (2012).CAS 
PubMed 
Article 

Google Scholar 
R Core Team R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. (2020).Cofran, Z. Brain size growth in wild and captive chimpanzees (Pan troglodytes). Am. J. Primat. 80(7), 1–8 (2018).Article 

Google Scholar 
Witzenberger, K. A. & Hochkirch, A. Ex situ conservation genetics: A review of molecular studies on the genetic consequences of captive breeding programmes for endangered animal species. Biodivers. Conserv. 20(9), 1843–1861 (2011).Article 

Google Scholar 
Gómez-Sánchez, D. et al. On the path to extinction: Inbreeding and admixture in a declining grey wolf population. Mole. Ecol. 27(18), 3599–3612 (2018).Article 

Google Scholar 
Elbroch, M. Animal skulls: a guide to North American species. (Stackpole Books, 2006).Conde, D. A., Flesness, N., Colchero, F., Jones, O. R. & Scheuerlein, A. An emerging role of zoos to conserve biodiversity. Science 331, 1390–1391 (2011).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Prado, E. L. & Dewey, K. G. Nutrition and brain development in early life. Nutr. Rev. 72(4), 267–284 (2014).PubMed 
Article 

Google Scholar 
Hecht, E. E. et al. Neuromorphological changes following selection for tameness and aggression in the Russian farm-fox experiment. J. Neurosci. 41(28), 6144–6156 (2021).CAS 
PubMed Central 
Article 

Google Scholar 
Bennett, E. L., Rosenzweig, M. R. & Diamond, M. C. Rat brain: Effects of environmental enrichment on wet and dry weights. Science 163(3869), 825–826 (1969).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Cummins, R. A., Walsh, R. N., Budtz-Olsen, O. E., Konstantinos, T. & Horsfall, C. R. Environmentally-induced changes in the brains of elderly rats. Nature 243(5409), 516–518 (1973).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Welch, B. L., Brown, D. G., Welch, A. S. & Lin, D. C. Isolation, restrictive confinement or crowding of rats for one year. I. Weight, nucleic acids and protein of brain regions. Brain Res. 75, 71–84 (1974).CAS 
PubMed 
Article 

Google Scholar  More

All research methods included in this study were performed in accordance with the relevant guidelines and regulations, under ZA/LP/81996 research permit, with ethical approval from the Animal Welfare Ethical Review Board (AWERB) at Durham University. The authors confirm the study was carried out in compliance with ARRIVE guidelines.All inter-individual association data was collected between June 2018 and June 2019 on a wild habituated group of Afro-montane chacma baboons in the western Soutpansberg Mountains, South Africa (central coordinates S29.44031°, E23.02217°) (for study site description see2). The study group was habituated circa 2005 and was the focus of intermittent research attention until 2014. The study area experienced long-term anthropogenic activities (local farming, forestry, and residences) prior to 2005, as such, consistent interactions with humans have been ongoing with this population for some time. From 2007 onwards numerous researchers were able to collect expansive datasets on the study group (e.g. Refs.17,18), indicating that habituation was at a typical level found elsewhere (also validated by AA and RH, who had researched chacma baboons elsewhere). From 2014 the group received full day (dawn until dusk) follows 3–4 days a week, with occasional gaps of up to 5 weeks in duration. These gaps did not appear to effect habituation levels, likely due to the presence of other researchers at the field site who always tried to act benignly when encountering the habituated group. The follow schedule was designed so that the study group retained as much of their natural interactions with predators as possible by ensuring the baboons spent significant time without observers who may influence the frequency and nature of predator–prey interactions19.The study site was located in a private nature reserve and the study group was not hunted during observation gaps or engaged in any conflict with humans, other than occasionally being scared (chasing, yelling, throwing stones etc.) from a small plantation by local workers, usually resulting in alarm barks and fleeing responses. However, the study group appeared adept at recognising the differences between researchers and these threats20. The majority of the study group’s home-range typically overlapped with the core area of the Lajuma Research Centre, and as a result, interactions with staff living in the area, unfamiliar researchers, and tourists were frequent. However, the baboons had not engaged in ‘raiding’ residences, threatening humans, or any other potentially negative symptom of habituation before the end of this study.Sampling methodology for proximity associations30-s focal sampling was used to collect proximity associations between all group members (excluding infants). All data was collected between June and December 2018 and January and June 2019; the majority of 2018s data was collected during the wet season, whilst most of 2019s data was collected during the dry season. To account for time of day, each day was split into four time-periods that were seasonally adjusted ensuring each period accounted for 25% of the current day length. A randomly ordered list of individuals was produced for each day, the first individual identified from the top 15 (approx. 20% of group size) individuals on the list was sampled immediately. Individuals could only be sampled once per time period per day, and a maximum of twice total per day. All individuals received at least 14 focal observations per time period (56 total) across the study period (see below for how we handled uneven sampling for some individuals). A video camera was used by AA (the only observer to collect this data) to record all focal observations (Panasonic HC-W580 Camcorder). At the end of the 30-s focal observation the identities of all neighbouring conspecifics within 5 m, 2.5 m, 1 m, and touching the focal animal were recorded (audibly by AA). We chose the end of the focal observation to record this data as this was most likely to reflect the conditions during the focal, i.e., the observer had been in proximity for at least 30 s.Neighbour information was extracted from video footage and entered manually by AA and AW. Data was split into separate years to reflect an observation gap of several weeks and to understand whether there was consistency in the hypothesized effects through time and to reflect underlying differences in environmental conditions during the two study periods; during the dry season fruits and seeds are scarce and day lengths are several hours shorter than in the wet season such that day journey lengths are often shorter in the dry season and animals are much more sedentary which could impact inter-individual spacings. In 2018 each individual was sampled between 28 and 30 times; 28 focals were randomly selected from each individual to make sampling even. For 2019 there were between 25 and 27 focals per individual; 25 samples of each individual were randomly selected. Observations were undertaken at a range of distances. For both years the median end observer distance was 4.5 m; data was thus split into close focal observations of less than or equal to 4.5 m (2018: n = 918, 2019: n = 809), and observations greater than 4.5 m (2018: n = 902 2019: n = 816). See supporting information Table S1 for summary statistics of the observation distances of each individual.We did not make any attempt to record our focal data evenly across the various habitats at our field site (see Supporting information text S1 for complete habitat descriptions) as our previous research indicated there was little difference in general spatial cohesion/inter-individual proximity patterns across these habitats (see Supporting information text S2 and Table S2). As a result, we considered it unlikely that there were fundamental differences in inter-individual association patterns across habitats, or that observers struggled to reliably detect or identify neighbours in dense habitats. We do acknowledge, however, that there will always be an element of bias with such methods, as observations were avoided, aborted, or excluded if visual obstructions (e.g., cliffs, rocks, walls, buildings, very dense vegetation etc.) prohibited accurate assessments; the observations used in the current study are from occasions when these factors were not an issue.During this study the group contained between 85 and 92 individuals. Age-sex class was defined according to secondary sexual characteristics (e.g., testes descending/enlarging, sexual swelling, canine eruption) and changes in pelage throughout juvenile development (see Supporting information text S3 for full descriptions). All 65 non-infant individuals that were present during 2017 (when displacement tolerances were calculated) and still remaining in the group by the end of 2019 were used in this study (4 individuals from the prior FID study were no longer present). There were a high number of births between 2018 and 2019, but none were independent by the time either of our sampling periods begun in 2018 or 2019. There was no immigration of foreign individuals, but two individuals disappeared, both during the 2018 focal sampling period. As a result, we had a very consistent pool of individuals to sample from during this study. We removed all data associated with the two individuals who disappeared as their occurrences as neighbours would have been poorly sampled (due to missing more than half the study) relative to the rest of the group which would have led to statistical biases21.Flight initiation distance procedureIndividual displacement tolerance estimates were previously quantified in our previous research2 using a flight initiation distance (FID) procedure22 that was completed between October 2017 and April 2018, prior and independent to the commencement of proximity association focal sampling in June 2018. Individual baboons were approached by an observer, and the distance at which the animal displaced away from the observer measured (see Supporting information Table S2 for summary statistics). This procedure was repeated 24 times for each individual baboon, with approaches spread evenly across two observers differing in familiarity. At the beginning of each approach we also recorded several behavioural, social, and environmental factors that could have hypothetically influenced an individual’s FID2 including whether the animal was engaged (e.g., digging or grooming) or not engaged (e.g., resting, chewing food, being groomed), habitat type (open/closed: see Supporting text S1), whether the animal was on the ground or sat on a low branch or rock within 50 cm of the ground, the number of conspecifics within 5 m of the focal animal, and whether there had been any external events within the preceding 5 min (e.g., alarm calls, aggressions, encountering another group or predator). During the approach, we also recorded the visual orientation distance (the distance at which the focal animal directed its line of vision towards the head of the approaching observer) and whether one of the focal animal’s neighbours had displaced/fled before the focal animal. Although all but neighbour flee first and external events showed some importance for predicting looking (see Table S4), FID was found to be distinct amongst individuals and repeatable within each individual, evidence that displacement tolerance may be an individual level trait2. Full details of methods, statistical analysis, and results (including comparison to the original model) for this updated model are in Supporting information text S4, with model summary results for the previous and updated models in Tables S3 and S4.The notion of an observer approaching a habituated primate may be considered atypical or likely to result in habituation/sensitization effects or agonistic behaviours being directed towards the approaching observers. However, our previous study2 showed that almost all approaches resulted in the animal passively relocating (98.85%), a very benign response identical to the behaviours of subordinate baboons displacing away from dominant conspecifics. This suggests that in this group, observers may be considered equivalent to a high-level social threat2. Throughout observation periods on habituated animals, observers are likely to approach or displace animals either incidentally or accidentally multiple times throughout the day, especially during lengthy focal observations. As such, the approach methodology is unlikely to represent a stimulus outside of the norm for our study animals. This may explain why displacement responses were so passive and why there was no evidence of habituation or sensitization effects across the group or individually through a range of temporal periods2 or after life-threatening events20. As a result, our situation was possible without risk of causing stress or anxiety in the study subjects, eliciting agonistic behaviours towards observers, or interfering with their prior habituation levels.Statistical analysisInfluence of tolerance and observer distance on inter-individual association patternsQuantifying displacement toleranceTo quantify displacement tolerance towards observers we extracted the individual conditional modes from the updated FID model using the ranef function in brms. Conditional modes are often referred to as Best Linear Unbiased Predictors (BLUPs) and are the difference between the predicted mean population-level response for a given set of treatments (i.e., population-level effects) and the predicted responses for each individual, and therefore infer the extent to which each individual differs from the population mean. The conditional modes and their associated standard deviations can be found in supporting information Table S5.To validate that the conditional modes from the updated model were both representative of the individual’s flight responses and in line with the estimates produced from our previous study2 we performed additional tests. Firstly, we performed a Pearson’s correlation between the conditional modes from the updated model and the conditional modes from the previous article. Individual tolerance estimates were consistent (r(63) = 0.915, p  More

Ehrlich, P. R. & Raven, P. H. Butterflies and plants: A study in coevolution. Evolution 18, 586 (1964).Article 

Google Scholar 
Raguso, R. A. et al. The raison d’être of chemical ecology. Ecology 96, 617–630 (2015).PubMed 
Article 

Google Scholar 
Kariyat, R. R. & Portman, S. L. Plant–herbivore interactions: Thinking beyond larval growth and mortality. Am. J. Bot. 103, 789–791 (2016).PubMed 
Article 

Google Scholar 
Raubenheimer, D. & Simpson, S. J. Nutritional ecology and foraging theory. Curr. Opin. Insect Sci. 27, 38–45 (2018).PubMed 
Article 

Google Scholar 
Goehring, L. & Oberhauser, K. S. Effects of photoperiod, temperature, and host plant age on induction of reproductive diapause and development time in Danaus plexippus. Ecol. Entomol. 27, 674–685 (2002).Article 

Google Scholar 
Hahn, D. A. Larval nutrition affects lipid storage and growth, but not protein or carbohydrate storage in newly eclosed adults of the grasshopper Schistocerca americana. J. Insect Physiol. 51, 1210–1219 (2005).CAS 
PubMed 
Article 

Google Scholar 
Portman, S. L., Kariyat, R. R., Johnston, M. A., Stephenson, A. G. & Marden, J. H. Cascading effects of host plant inbreeding on the larval growth, muscle molecular composition, and flight capacity of an adult herbivorous insect. Funct. Ecol. 29, 328–337 (2015).Article 

Google Scholar 
Johnson, C. G. Physiological factors in insect migration by flight. Nature 198, 423–427 (1963).Article 

Google Scholar 
Harrison, R. G. Dispersal polymorphisms in insects. Annu. Rev. Ecol. Syst. 11, 95–118 (1980).Article 

Google Scholar 
Zera, A. J. & Denno, R. F. Physiology and ecology of dispersal polymorphism in insects. Annu. Rev. Entomol. 42, 207–231 (1997).CAS 
PubMed 
Article 

Google Scholar 
Marden, J. H. et al. Weight and nutrition affect pre-mRNA splicing of a muscle gene associated with performance, energetics and life history. J. Exp. Biol. 211, 3653–3660 (2008).CAS 
PubMed 
Article 

Google Scholar 
Raguso, R. A., Ojeda-Avila, T., Desai, S., Jurkiewicz, M. A. & Arthur Woods, H. The influence of larval diet on adult feeding behaviour in the tobacco hornworm moth, Manduca sexta. J. Insect Physiol. 53, 923–932 (2007).CAS 
PubMed 
Article 

Google Scholar 
Cease, A. J. et al. Nutritional imbalance suppresses migratory phenotypes of the Mongolian locust (Oedaleus asiaticus). R. Soc. Open Sci. 4, https://doi.org/10.1098/rsos.161039 (2017).Reichstein, T., Von Euw, J., Parsons, J. A. & Rothschild, M. Heart poisons in the monarch butterfly. Science 161, 861–866 (1968).CAS 
PubMed 
Article 

Google Scholar 
Brower, L. P., Ryerson, W. N., Coppinger, L. L. & Glazier, S. C. Ecological chemistry and the palatability spectrum. Science 161, 1349–1351 (1968).CAS 
PubMed 
Article 

Google Scholar 
Young, A. M. An evolutionary-ecological model of the evolution of migratory behavior in the Monarch Butterfly, and its absence in the Queen Butterfly. Acta Biotheor. 31, 219–237 (1982).Article 

Google Scholar 
Agrawal, A. A. Monarchs and Milkweed: A Migrating Butterfly, a Poisonous Plant, and Their Remarkable Story of Coevolution. (Princeton University Press, 2017).Batalden, R. V. & Oberhauser, K. S. Potential changes in eastern north American monarch migration in response to an introduced Milkweed, Asclepias curassavica. in Monarchs in a Changing World: Biology and Conservation of an Iconic Butterfly 215–224 (2015).Tyler Flockhart, D. T. et al. Tracking multi-generational colonization of the breeding grounds by monarch butterflies in eastern North America. Proc. R. Soc. B Biol. Sci. 280, 20131087 (2013).Saunders, S. P., Ries, L., Oberhauser, K. S., Thogmartin, W. E. & Zipkin, E. F. Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus. Ecography. 41, 278–290 (2018).Article 

Google Scholar 
Pleasants, J. M. & Oberhauser, K. S. Milkweed loss in agricultural fields because of herbicide use: Effect on the monarch butterfly population. Insect Conserv. Divers. 6, 135–144 (2013).Article 

Google Scholar 
Borders, B. & Lee-Mäder, B. B. Project milkweed. in Monarchs in a Changing World: Biology and Conservation of an Iconic Butterfly. pp.190-196 (Cornell University press, 2015).Agrawal, A. A., Petschenka, G., Bingham, R. A., Weber, M. G. & Rasmann, S. Toxic cardenolides: Chemical ecology and coevolution of specialized plant-herbivore interactions. N. Phytologist 194, 28–45 (2012).CAS 
Article 

Google Scholar 
Malcolm, S. B. Milkweeds, monarch butterflies and the ecological significance of cardenolides. Chemoecology 5–6, 101–117 (1994).Article 

Google Scholar 
Pocius, V. M., Debinski, D. M., Bidne, K. G., Hellmich, R. L. & Hunter, F. K. Performance of early Instar Monarch Butterflies (Danaus plexippus L.) on nine Milkweed species native to Iowa. J. Lepid. Soc. 71, 153–161 (2017).
Google Scholar 
Ali, J. G. & Agrawal, A. A. Specialist versus generalist insect herbivores and plant defense. Trends Plant Sci. 17, 293–302 (2012).CAS 
PubMed 
Article 

Google Scholar 
Zalucki, M. P., Brower, L. P. & Alonso-M, A. Detrimental effects of latex and cardiac glycosides on survival and growth of first-instar monarch butterfly larvae Danaus plexippus feeding on the sandhill milkweed Asclepias humistrata. Ecol. Entomol. 26, 212–224 (2001).Article 

Google Scholar 
Agrawal, A. A., Hastings, A. P., Patrick, E. T. & Knight, A. C. Specificity of herbivore-induced hormonal signaling and defensive traits in five closely related milkweeds (Asclepias spp.). J. Chem. Ecol. 40, 717–729 (2014).CAS 
PubMed 
Article 

Google Scholar 
Agrawal, A. A., Ali, J. G., Rasmann, S. & Fishbein, M. Macroevolutionary trends in the defense of milkweeds against monarchs. Monarch. a Chang. World Biol. Conserv. Iconic Insect. Cornell University Press, Ithaca, NY. pp. 47–59 (2011).Pocius, V. M. et al. Milkweed matters: Monarch butterfly (Lepidoptera: Nymphalidae) survival and development on nine midwestern milkweed species. Environ. Entomol. 46, 1098–1105 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Petschenka, G. et al. Stepwise evolution of resistance to toxic cardenolides via genetic substitutions in the na+/k+-atpase of milkweed butterflies (lepidoptera: Danaini). Evolution (N. Y). 67, 2753–2761 (2013).CAS 

Google Scholar 
Agrawal, A. A. et al. Cardenolides, toxicity, and the costs of sequestration in the coevolutionary interaction between monarchs and milkweeds. Proc. Natl Acad. Sci. USA 118, e2024463118 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Marden, J. H. Variability in the size, composition, and function of insect flight muscles. Annu. Rev. Physiol. 62, 157–178 (2000).CAS 
PubMed 
Article 

Google Scholar 
Bicudo, J. E. P. W., Buttemer, W. A., Chappell, M. A., Pearson, J. T. & Bech, C. Ecological and Environmental Physiology of Birds. Ecological and Environmental Physiology of Birds 3 (Oxford University Press, 2010).Bailey, E. Biochemistry of Insect Flight. in Insect Biochemistry and Function. pp. 89–176 (Springer, 1975).Dudley, R. The biomechanics of insect flight: form, function, evolution. Annals of the Entomological Society of America 93 (Princeton University Press, 2000).Solensky, M. J. Overview of monarch migration. in The Monarch Butterfly: Biology and Conservation 79–83 (2004).Urquhart, F. A. & Urquhart, N. R. Monarch butterfly (Danaus plexippus L.) overwintering population in Mexico (Lep. Danaidae). Atalanta 7, 56–61 (1976).
Google Scholar 
Brower, L. P. Understanding and misunderstanding the migration of the monarch butterfly (Nymphalidae) in North America: 1857–1995. J. – Lepid. Soc. 49, 304–385 (1995).
Google Scholar 
Fisher, K. E., Adelman, J. S. & Bradbury, S. P. Employing Very High Frequency (VHF) radio telemetry to recreate monarch butterfly flight paths. Environ. Entomol. 49, 312–323 (2020).PubMed 
Article 

Google Scholar 
Reppert, S. M. & de Roode, J. C. Demystifying monarch butterfly migration. Curr. Biol. 28, R1009–R1022 (2018).CAS 
PubMed 
Article 

Google Scholar 
Zhu, H., Gegear, R. J., Casselman, A., Kanginakudru, S. & Reppert, S. M. Defining behavioral and molecular differences between summer and migratory monarch butterflies. BMC Biol. 7, 1–14 (2009).Heinze, S. & Reppert, S. M. Anatomical basis of sun compass navigation I: The general layout of the monarch butterfly brain. J. Comp. Neurol. 520, 1599–1628 (2012).PubMed 
Article 

Google Scholar 
Zhan, S. et al. The genetics of monarch butterfly migration and warning colouration. Nature 514, 317–321 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Soule, A. J., Decker, L. E. & Hunter, M. D. Effects of diet and temperature on monarch butterfly wing morphology and flight ability. J. Insect Conserv. 24, 961–975 (2020).Article 

Google Scholar 
Decker, L. E., Soule, A. J., de Roode, J. C. & Hunter, M. D. Phytochemical changes in milkweed induced by elevated CO2 alter wing morphology but not toxin sequestration in monarch butterflies. Funct. Ecol. 33, 411–421 (2019).Article 

Google Scholar 
Heinrich, B. Temperature regulation of the sphinx moth, Manduca sexta. I. Flight energetics and body temperature during free and tethered flight. J. Exp. Biol. 54, 141–152 (1971).CAS 
PubMed 
Article 

Google Scholar 
Nicolson, S. W. & Louw, G. N. Simultaneous measurement of evaporative water loss, oxygen consumption, and thoracic temperature during flight in a carpenter bee. J. Exp. Zool. 222, 287–296 (1982).Article 

Google Scholar 
Rothe, U. & Nachtigall, W. Flight of the honey bee IV. J. Comp. Physiol. B 158, 711–718 (1989).Article 

Google Scholar 
Nachtigall, W., Hanauer-Thieser, U. & Mörz, M. Flight of the honey bee VII: Metabolic power versus flight speed relation. J. Comp. Physiol. B 165, 484–489 (1995).Article 

Google Scholar 
Niven, J. E. & Scharlemann, J. P. W. Do insect metabolic rates at rest and during flight scale with body mass? Biol. Lett. 1, 346–349 (2005).PubMed 
PubMed Central 
Article 

Google Scholar 
Zalucki, M. P., Parry, H. R. & Zalucki, J. M. Movement and egg laying in Monarchs: To move or not to move, that is the equation. Austral. Ecol. 41, 154–167 (2016).Article 

Google Scholar 
Marden, J. H. & Chai, Peng Aerial predation and butterfly design: How palatability, mimicry, and the need for evasive flight constrain mass allocation. Am. Nat. 138, 15–36 (1991).Article 

Google Scholar 
Levin, E., Lopez-Martinez, G., Fane, B. & Davidowitz, G. Hawkmoths use nectar sugar to reduce oxidative damage from flight. Science 355, 733–735 (2017).CAS 
PubMed 
Article 

Google Scholar 
Petschenka, G. & Agrawal, A. A. Milkweed butterfly resistance to plant toxins is linked to sequestration, not coping with a toxic diet. Proc. R. Soc. B Biol. Sci. 282, 20151865 (2015).Petschenka, G. & Agrawal, A. A. How herbivores coopt plant defenses: Natural selection, specialization, and sequestration. Curr. Opin. Insect Sci. 14, 17–24 (2016).PubMed 
Article 

Google Scholar 
Tan, W. H., Tao, L., Hoang, K. M., Hunter, M. D. & de Roode, J. C. The effects of milkweed induced defense on parasite resistance in monarch butterflies, Danaus plexippus. J. Chem. Ecol. 44, 1040–1044 (2018).CAS 
PubMed 
Article 

Google Scholar 
Brower, L. P. & Glazier, S. C. Localization of heart poisons in the monarch butterfly. Science 188, 19–25 (1975).CAS 
PubMed 
Article 

Google Scholar 
Zalucki, M. P. et al. It’s the first bites that count: Survival of first-instar monarchs on milkweeds. Austral. Ecol. 26, 547–555 (2001).Article 

Google Scholar 
Zalucki, M. P., Malcolm, S. B., Hanlon, C. C. & Paine, T. D. First-instar monarch larval growth and survival on milkweeds in Southern California: Effects of latex, leaf hairs and cardenolides. Chemoecology 22, 75–88 (2012).Article 

Google Scholar 
Ziegler, R. & Van Antwerpen, R. Lipid uptake by insect oocytes. Insect Biochem. Mol. Biol. 36, 264–272 (2006).Beenakkers, A. M. T., Van der Horst, D. J. & Van Marrewijk, W. J. A. Insect flight muscle metabolism. Insect Biochem. 14, 243–260 (1984).CAS 
Article 

Google Scholar 
Beall, G. The fat content of a butterfly, Danaus Plexippus Linn., as affected by migration. Ecology 29, 80–94 (1948).Article 

Google Scholar 
James, D. G. Phenology of weight, moisture and energy reserves of Australian monarch butterflies, Danaus plexippus. Ecol. Entomol. 9, 421–428 (1984).Article 

Google Scholar 
Briegel, H. Metabolic relationship between female body size, reserves, and fecundity of Aedes aegypti. J. Insect Physiol. 36, 165–172 (1990).Article 

Google Scholar 
Hines, W. J. W. & Smith, M. J. H. Some aspects of intermediary metabolism in the desert locust (Schistocerca gregaria Forskål). J. Insect Physiol. 9, 463–468 (1963).CAS 
Article 

Google Scholar 
Inagaki, S. & Yamashita, O. Metabolic shift from lipogenesis to glycogenesis in the last instar larval fat body of the silkworm, Bombyx mori. Insect Biochem. 16, 327–331 (1986).CAS 
Article 

Google Scholar 
Venkatesh, K. & Morrison, P. E. Studies of weight changes and amount of food ingested by the stable fly, stomoxys calcitrans (Diptera: Muscidae). Can. Entomol. 112, 141–149 (1980).Article 

Google Scholar 
Arrese, E. L. & Soulages, J. L. Insect fat body: Energy, metabolism, and regulation. Annu. Rev. Entomol. 55, 207–225 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mevi-Schütz, J. & Erhardt, A. Larval nutrition affects female nectar amino acid preference in the map butterfly (Araschnia levana). Ecology 84, 2788–2794 (2003).Article 

Google Scholar 
Wassenaar, L. I. & Hobson, K. A. Natal origins of migratory monarch butterflies at wintering colonies in Mexico: New isotopic evidence. Proc. Natl Acad. Sci. USA 95, 15436–15439 (1998).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Majewska, A. A. & Altizer, S. Exposure to Non-Native Tropical Milkweed Promotes Reproductive Development in Migratory Monarch Butterflies. Insects 10, 253 (2019).Howard, E., Aschen, H. & Davis, A. K. Citizen science observations of monarch butterfly overwintering in the Southern United States. Psyche: A Journal of Entomology 2010, https://doi.org/10.1155/2010/689301 (2010).Satterfield, D. A., Maerz, J. C. & Altizer, S. Loss of migratory behaviour increases infection risk for a butterfly host. Proc. R. Soc. B Biol. Sci. 282, 20141734 (2015).Petschenka, G. et al. Relative selectivity of plant cardenolides for Na+/K+-ATPases from the monarch butterfly and non-resistant insects. Front. Plant Sci. 9, 1424 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Jones, P. L., Petschenka, G., Flacht, L. & Agrawal, A. A. Cardenolide intake, sequestration, and excretion by the monarch butterfly along gradients of plant toxicity and larval ontogeny. J. Chem. Ecol. 45, 264–277 (2019).CAS 
PubMed 
Article 

Google Scholar 
Tao, L., Hoang, K. M., Hunter, M. D. & de Roode, J. C. Fitness costs of animal medication: antiparasitic plant chemicals reduce fitness of monarch butterfly hosts. J. Anim. Ecol. 85, 1246–1254 (2016).PubMed 
Article 

Google Scholar 
Lederhouse, R. C. The effect of female mating frequency on egg fertility in the black swallowtail, Papilio polyxenes asterius (Papilionidae). J. Lepid. Soc. 35, 266–277 (1981).
Google Scholar 
Jones, R. E., Hart, J. R. & Bull, G. D. Temperature, size and egg production in the Cabbage Butterfly, Pieris rapae L. Aust. J. Zool. 30, 159–168 (1982).Article 

Google Scholar 
Haukioja, E. & Neuvonen, S. The relationship between size and reproductive potential in male and female Epirrita autumnata (Lep., Geometridae). Ecol. Entomol. 10, 267–270 (1985).Article 

Google Scholar 
Altizer, S. M., Oberhauser, K. S. & Brower, L. P. Associations between host migration and the prevalence of a protozoan parasite in natural populations of adult monarch butterflies. Ecol. Entomol. 25, 125–139 (2000).Article 

Google Scholar 
Masters, A. R., Malcolm, S. B. & Brower, L. P. Monarch butterfly (Danaus plexippus) thermoregulatory behavior and adaptations for overwintering in Mexico. Ecology 69, 458–467 (1988).Article 

Google Scholar 
Kammer, A. E. Thoracic temperature, shivering, and flight in the monarch butterfly, Danaus plexippus (L.). Z. Vgl. Physiol. 68, 334–344 (1970).Article 

Google Scholar 
Pendar, H. & Socha, J. J. Estimation of instantaneous gas exchange in flow-through respirometry systems: A modern revision of bartholomew’s ztransform method. PLoS One 10, e0139508 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Lighton, J. R. B. Measuring Metabolic Rates: A Manual for Scientists. (Oxford University Press, 2008).Alonso-Mejía, A., Rendon-Salinas, E., Montesinos-Patiño, E. & Brower, L. P. Use of lipid reserves by monarch butterflies overwintering in Mexico: Implications for conservation. Ecol. Appl. 7, 934–947 (1997).Article 

Google Scholar 
Diaz, R., Overholt, W. A., Hahn, D. & Samayoa, A. C. Diapause induction in Gratiana boliviana (Coleoptera: Chrysomelidae), a biological control agent of tropical soda apple in Florida. Ann. Entomol. Soc. Am. 104, 1319–1326 (2011).Article 

Google Scholar 
Tschinkel, W. R. Sociometry and sociogenesis of colonies of the fire ant Solenopsis invicta during one annual cycle. Ecol. Monogr. 63, 425–457 (1993).Article 

Google Scholar 
Fink, L. S. & Brower, L. P. Birds can overcome the cardenolide defence of monarch butterflies in Mexico. Nature 291, 67–70 (1981).CAS 
Article 

Google Scholar 
Ali, J. G. & Agrawal, A. A. Trade-offs and tritrophic consequences of host shifts in specialized root herbivores. Funct. Ecol. 31, 153–160 (2017).Article 

Google Scholar 
Woodson, R. E. The North American Species of Asclepias L. Ann. Mo. Bot. Gard. 41, 1 (1954).Article 

Google Scholar 
NRCS USDA. The PLANTS Database. National Plant Data Center. http://plants.usda.gov (2006).Agrawal, A. A., Salminen, J. P. & Fishbein, M. Phylogenetic trends in phenolic metabolism of milkweeds (Asclepias): Evidence for escalation. Evolution (N. Y). 63, 663–673 (2009).CAS 

Google Scholar 
Pocius, V. M. et al. Monarch butterflies show differential utilization of nine midwestern milkweed species. Front. Ecol. Evol. 6, 169 (2018).Pocius, V. M., Debinski, D. M., Pleasants, J. M., Bidne, K. G. & Hellmich, R. L. Monarch butterflies do not place all of their eggs in one basket: Oviposition on nine Midwestern milkweed species. Ecosphere 9, e02064 (2018).Article 

Google Scholar 
Ladner, D. T. & Altizer, S. Oviposition preference and larval performance of North American monarch butterflies on four Asclepias species. Entomol. Exp. Appl. 116, 9–20 (2005).Article 

Google Scholar 
Borders, B. A guide to the native milkweeds of Oregon. Xerces Soc. Invertebr. Conserv. www.xerces.org, 5, 12-23 (2012). More

Barrington, D. J. & Ghadouani, A. Application of hydrogen peroxide for the removal of toxic cyanobacteria and other phytoplankton from wastewater. Environ. Sci. Technol. 42, 8916–8921. https://doi.org/10.1021/es801717y (2008).CAS 
Article 
PubMed 

Google Scholar 
Vikrant, K. et al. Engineered/designer biochar for the removal of phosphate in water and wastewater. Sci. Total Environ. 616–617, 1242–1260. https://doi.org/10.1016/j.scitotenv.2017.10.193 (2018).CAS 
Article 
PubMed 

Google Scholar 
Merel, S. et al. State of knowledge and concerns on cyanobacterial blooms and cyanotoxins. Environ. Int. 59, 303–327. https://doi.org/10.1016/j.envint.2013.06.013 (2013).CAS 
Article 
PubMed 

Google Scholar 
Paerl, H. W. & Otten, T. G. Harmful cyanobacterial blooms: Causes, consequences, and controls. Microb. Ecol. 65, 995–1010. https://doi.org/10.1007/s00248-012-0159-y (2013).CAS 
Article 
PubMed 

Google Scholar 
Monchamp, M. E. et al. Homogenization of lake cyanobacterial communities over a century of climate change and eutrophication. Nat. Ecol. Evol. 2, 317–324. https://doi.org/10.1038/s41559-017-0407-0 (2018).Article 
PubMed 

Google Scholar 
Paerl, H. W. & Fulton, R. S. Ecology of harmful cyanobacteria. In Ecology of Harmful Algae (eds Granéli, E. & Turner, J. T.) 95–109 (Springer, 2006).Chapter 

Google Scholar 
Guan, Y., Zhang, M., Yang, Z., Shi, X. & Zhao, X. Intra-annual variation and correlations of functional traits in Microcystis and Dolichospermum in Lake Chaohu. Ecol. Indic. 111, 106052. https://doi.org/10.1016/j.ecolind.2019.106052 (2020).Article 

Google Scholar 
Zhang, M. et al. Spatial and seasonal shifts in bloom-forming cyanobacteria in Lake Chaohu: Patterns and driving factors. Phycol. Res. 64, 44–55. https://doi.org/10.1111/pre.12112 (2016).Article 

Google Scholar 
Krishnamurthy, T., Carmichael, W. W. & Sarver, E. W. Toxic peptides from freshwater cyanobacteria (blue-green algae) I. Isolation, purification and characterization of peptides from Microcystis aeruginosa and Anabaena flos-aquae. Toxicon 24, 865–873. https://doi.org/10.1016/0041-0101(86)90087-5 (1986).CAS 
Article 
PubMed 

Google Scholar 
Mahmood, N. A. & Carmichael, W. W. Anatoxin-a(s), an anticholinesterase from the cyanobacterium Anabaena flos-aquae NRC 525–17. Toxicon 25, 1221–1227. https://doi.org/10.1016/0041-0101(87)90140-1 (1987).CAS 
Article 
PubMed 

Google Scholar 
Li, X., Dreher, T. W. & Li, R. An overview of diversity, occurrence, genetics and toxin production of bloom-forming Dolichospermum (Anabaena) species. Harmful Algae 54, 54–68. https://doi.org/10.1016/j.hal.2015.10.015 (2016).CAS 
Article 
PubMed 

Google Scholar 
Buratti, F. M. et al. Cyanotoxins: Producing organisms, occurrence, toxicity, mechanism of action and human health toxicological risk evaluation. Arch. Toxicol. 91, 1049–1130. https://doi.org/10.1007/s00204-016-1913-6 (2017).CAS 
Article 
PubMed 

Google Scholar 
Iredale, R. S., McDonald, A. T. & Adams, D. G. A series of experiments aimed at clarifying the mode of action of barley straw in cyanobacterial growth control. Water Res. 46, 6095–6103. https://doi.org/10.1016/j.watres.2012.08.040 (2012).CAS 
Article 
PubMed 

Google Scholar 
Zhang, S. H., Zhang, S. Y. & Li, G. Acorus calamus root extracts to control harmful cyanobacteria blooms. Ecol. Eng. 94, 95–101. https://doi.org/10.1016/j.ecoleng.2016.05.053 (2016).Article 

Google Scholar 
Mecina, G. F. et al. Effect of flavonoids isolated from Tridax procumbens on the growth and toxin production of Microcystis aeruginosa. Aquat. Toxicol. 211, 81–91. https://doi.org/10.1016/j.aquatox.2019.03.011 (2019).CAS 
Article 
PubMed 

Google Scholar 
Yuan, R. et al. The allelopathic effects of aqueous extracts from Spartina alterniflora on controlling the Microcystis aeruginosa blooms. Sci. Total Environ. 712, 13622. https://doi.org/10.1016/j.scitotenv.2019.136332 (2020).CAS 
Article 

Google Scholar 
Tan, K. et al. A review of allelopathy on microalgae. Microbiology 165, 587–592. https://doi.org/10.1099/mic.0.000776 (2019).CAS 
Article 
PubMed 

Google Scholar 
Mecina, G. F. et al. Response of Microcystis aeruginosa BCCUSP 232 to barley (Hordeum vulgare L.) straw degradation extract and fractions. Sci. Total. Environ. 599–600, 1837–1847. https://doi.org/10.1016/j.scitotenv.2017.05.156 (2017).CAS 
Article 
PubMed 

Google Scholar 
Zhao, W., Zheng, Z., Zhang, J., Roger, S. F. & Luo, X. Allelopathically inhibitory effects of eucalyptus extracts on the growth of Microcystis aeruginosa. Chemosphere 225, 424–433. https://doi.org/10.1016/j.chemosphere.2019.03.070 (2019).CAS 
Article 
PubMed 

Google Scholar 
Bottino, F. et al. Effects of macrophyte leachate on Anabaena sp. and Chlamydomonas moewusii growth in freshwater tropical ecosystems. Limnology 19, 171–176. https://doi.org/10.1007/s10201-017-0532-0 (2018).CAS 
Article 

Google Scholar 
Zhang, K., Yu, M., Xu, P., Zhang, S. & Benoit, G. Physiological and morphological response of Aphanizomenon flos-aquae to watermelon (Citrullus lanatus) peel aqueous extract. Aquat. Toxicol. 225, 105548. https://doi.org/10.1016/j.aquatox.2020.105548 (2020).CAS 
Article 
PubMed 

Google Scholar 
Lichtenthaler, H. K. & Buschmann, C. Chlorophylls and carotenoids: Measurement and characterization by UV-VIS spectroscopy. Curr. Protoc. Food Anal. Chem. 1, F4.3.1-F4.38 (2001).Article 

Google Scholar 
Ozaki, K. et al. Electron microscopic study on lysis of a cyanobacterium Microcystis. J. Health Sci. 55, 578–585. https://doi.org/10.1248/jhs.55.578 (2009).CAS 
Article 

Google Scholar 
Staats, N., De Winder, B., Stal, L. J. & Mur, L. R. Isolation and characterization of extracellular polysaccharides from the epipelic diatoms Cylindrotheca closterium and Navicula salinarum. Eur. J. Phycol. 34, 161–169. https://doi.org/10.1080/09670269910001736212 (1999).Article 

Google Scholar 
Hellebust, J. & Craigie, J. (eds) Handbook of Phycological Methods. Physiological and Biochemical Methods (Cambridge University, 1978).
Google Scholar 
Roháček, K. & Barták, M. Technique of the modulated chlorophyll fluorescence: Basic concepts, useful parameters, and some applications. Photosynthetica 37, 339–363. https://doi.org/10.1023/A:1007172424619 (1999).Article 

Google Scholar 
Zhang, T. T., He, M., Wu, A. P. & Nie, L. W. Inhibitory effects and mechanisms of Hydrilla verticillata (Linn.f.) royle extracts on freshwater algae. Bull. Environ. Contam. Toxicol. 88, 477–481. https://doi.org/10.1007/s00128-011-0500-z (2012).CAS 
Article 
PubMed 

Google Scholar 
Zhao, S., Pan, W. & Ma, C. Stimulation and inhibition effects of algae-lytic products from Bacillus cereus strain L7 on Anabaena flos-aquae. J. Appl. Phycol. 24, 1015–1021. https://doi.org/10.1007/s10811-011-9725-9 (2012).CAS 
Article 

Google Scholar 
Kaminski, A. et al. Aquatic macrophyte Lemna trisulca (L.) as a natural factor for reducing anatoxin-a concentration in the aquatic environment and biomass of cyanobacterium Anabaena flos-aquae (Lyngb.) de Bréb. Algal Res. 9, 212–217. https://doi.org/10.1016/j.algal.2015.03.014 (2015).Article 

Google Scholar 
Gumbo, J. R., Cloete, T. E., van Zyl, G. J. J. & Sommerville, J. E. M. The viability assessment of Microcystis aeruginosa cells after co-culturing with Bacillus mycoides B16 using flow cytometry. Phys. Chem. Earth. 72–75, 24–33. https://doi.org/10.1016/j.pce.2014.09.004 (2014).Article 

Google Scholar 
Fan, J., Ho, L., Hobson, P. & Brookes, J. Evaluating the effectiveness of copper sulphate, chlorine, potassium permanganate, hydrogen peroxide and ozone on cyanobacterial cell integrity. Water Res. 47, 5153–5164. https://doi.org/10.1016/j.watres.2013.05.057 (2013).CAS 
Article 
PubMed 

Google Scholar 
Lu, Z. Studies on oxidative stress and programmed cell death of Microcystis aeruginosa induced by polyphenolic allelochemicals (D). Institute of Hydrobiology, Chinese Academy of Sciences (2014).Lu, Z. et al. Polyphenolic allelochemical pyrogallic acid induces caspase-3(like)-dependent programmed cell death in the cyanobacterium Microcystis aeruginosa. Algal Res. 21, 148–155. https://doi.org/10.1016/j.algal.2016.11.007 (2017).Article 

Google Scholar 
Chen, Y. et al. Vitamin C modulates Microcystis aeruginosa death and toxin release by induced Fenton reaction. J. Hazard. Mater. 321, 888–895. https://doi.org/10.1016/j.jhazmat.2016.10.010 (2017).CAS 
Article 
PubMed 

Google Scholar 
Latifi, A., Ruiz, M. & Zhang, C. C. Oxidative stress in cyanobacteria. FEMS Microbiol. Rev. 33, 258–278. https://doi.org/10.1111/j.1574-6976.2008.00134.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Shao, J. H., Wu, X. Q. & Li, R. H. Physiological responses of Microcystis aeruginosa PCC7806 to nonanoic acid stress. Environ. Toxicol. 24, 610–617. https://doi.org/10.1002/tox.20462 (2009).CAS 
Article 
PubMed 

Google Scholar 
Hua, Q. et al. Allelopathic effect of the rice straw aqueous extract on the growth of Microcystis aeruginosa. Ecotox. Environ. Safe. 148, 953–959. https://doi.org/10.1016/j.ecoenv.2017.11.049 (2018).CAS 
Article 

Google Scholar 
Chen, L., Wang, Y., Shi, L., Zhao, J. & Wang, W. Identification of allelochemicals from pomegranate peel and their effects on Microcystis aeruginosa growth. Environ. Sci. Pollut. Res. 26, 22389–22399. https://doi.org/10.1007/s11356-019-05507-1 (2019).CAS 
Article 

Google Scholar 
Zhang, S. H., Xu, P. Y. & Chang, J. J. Physiological responses of Aphanizomenon flos-aquae under the stress of Sagittaria sagittifolia extract. Bull. Environ. Contam. Toxicol. 97, 870–875. https://doi.org/10.1007/s00128-016-1948-7 (2016).CAS 
Article 
PubMed 

Google Scholar 
Li, J. et al. Growth inhibition and oxidative damage of Microcystis aeruginosa induced by crude extract of Sagittaria trifolia tubers. J. Environ. Sci. 43, 40–47. https://doi.org/10.1016/j.jes.2015.08.020 (2016).CAS 
Article 

Google Scholar 
Shao, J. et al. Inhibitory effects of sanguinarine against the cyanobacterium Microcystis aeruginosa NIES-843 and possible mechanisms of action. Aquat. Toxicol. 142–143, 257–263. https://doi.org/10.1016/j.aquatox.2013.08.019 (2013).CAS 
Article 
PubMed 

Google Scholar 
Apel, K. & Hirt, H. Reactive oxygen species: Metabolism, oxidative stress, and signal transduction. Annu. Rev. Plant. Biol. 55, 373–399. https://doi.org/10.1146/annurev.arplant.55.031903.141701 (2004).CAS 
Article 
PubMed 

Google Scholar 
Zhang, S. & Benoit, G. Comparative physiological tolerance of unicellular and colonial Microcystis aeruginosa to extract from Acorus calamus rhizome. Aquat. Toxicol. 215, 105271. https://doi.org/10.1016/j.aquatox.2019.105271 (2019).CAS 
Article 
PubMed 

Google Scholar 
Derks, A., Schaven, K. & Bruce, D. Diverse mechanisms for photoprotection in photosynthesis. Dynamic regulation of photosystem II excitation in response to rapid environmental change. BBA-Bioenergetics 1847, 468–485. https://doi.org/10.1016/j.bbabio.2015.02.008 (2015).CAS 
Article 
PubMed 

Google Scholar 
Jiang, H. & Qiu, B. Photosynthetic adaptation of a bloom-forming cyanobacterium Microcystis aeruginosa (cyanophyceae) to prolonged uv-b exposure. J. Phycol. 41, 983–992. https://doi.org/10.1111/j.1529-8817.2005.00126.x (2005).Article 

Google Scholar 
Azizullah, A., Richter, P. & Häder, D. P. Photosynthesis and photosynthetic pigments in the flagellate Euglena gracilis: As sensitive endpoints for toxicity evaluation of liquid detergents. J. Photochem. Photobiol. B Biol. 133, 18–26. https://doi.org/10.1016/j.jphotobiol.2014.02.011 (2014).CAS 
Article 

Google Scholar 
Singh, D. P., Khattar, J. I. S., Gupta, M. & Kaur, G. Evaluation of toxicological impact of cartap hydrochloride on some physiological activities of a non-heterocystous cyanobacterium Leptolyngbya foveolarum. Pestic. Biochem. Phys. 110, 63–70. https://doi.org/10.1016/j.pestbp.2014.03.002 (2014).CAS 
Article 

Google Scholar 
Movasaghi, Z., Rehman, S. & Rehman, I. U. Raman spectroscopy of biological tissues. Appl. Spectrosc. Rev. 42, 493–541. https://doi.org/10.1080/05704920701551530 (2007).CAS 
Article 

Google Scholar 
Li, K. et al. In vivo kinetics of lipids and astaxanthin evolution in Haematococcus pluvialis mutant under 15% CO2 using Raman microspectroscopy. Bioresource Technol. 244, 1439–1444. https://doi.org/10.1016/j.biortech.2017.04.116 (2017).CAS 
Article 

Google Scholar 
Beutner, S. et al. Quantitative assessment of antioxidant properties of natural colorants and phytochemicals: Carotenoids, flavonoids, phenols and indigoids. The role of beta-carotene in antioxidant functions. J. Sci. Food. Agric. 81, 559–568. https://doi.org/10.1002/jsfa.849 (2001).CAS 
Article 

Google Scholar 
Kelman, D., Ben-Amotz, A. & Berman-Frank, I. Carotenoids provide the major antioxidant defence in the globally significant N2-fixing marine cyanobacterium Trichodesmiumem. Environ. Microbiol. 11, 1897–1908. https://doi.org/10.1111/j.1462-2920.2009.01913.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Zhou, T. et al. Growth suppression and apoptosis-like cell death in Microcystis aeruginosa by H2O2: A new insight into extracellular and intracellular damage pathways. Chemosphere 211, 1098–1108. https://doi.org/10.1016/j.chemosphere.2018.08.042 (2018).CAS 
Article 
PubMed 

Google Scholar 
Schreiber, U., Quayle, P., Schmidt, S., Escher, B. I. & Mueller, J. F. Methodology and evaluation of a highly sensitive algae toxicity test based on multiwell chlorophyll fluorescence imaging. Biosens. Bioelectron. 22, 2554–2563. https://doi.org/10.1016/j.bios.2006.10.018 (2007).CAS 
Article 
PubMed 

Google Scholar 
Kumar, K. S. et al. Algal photosynthetic responses to toxic metals and herbicides assessed by chlorophyll a fluorescence. Ecotox. Environ. Safe. 104, 51–71. https://doi.org/10.1016/j.ecoenv.2014.01.042 (2014).CAS 
Article 

Google Scholar 
Maxwell, K. & Johnson, G. N. Chlorophyll fluorescence: A practical guide. J Exp Bot 51, 659–668. https://doi.org/10.1093/jxb/51.345.659 (2000).CAS 
Article 
PubMed 

Google Scholar 
Lürling, M. & Roessink, I. On the way to cyanobacterial blooms: Impact of the herbicide metribuzin on the competition between a green alga (Scenedesmus) and a cyanobacterium (Microcystis). Chemosphere 65, 618–626. https://doi.org/10.1016/j.chemosphere.2006.01.073 (2006).CAS 
Article 
PubMed 

Google Scholar 
Zhu, J. Y., Liu, B. Y., Wang, J., Gao, Y. N. & Wu, Z. B. Study on the mechanism of allelopathic influence on cyanobacteria and chlorophytes by submerged macrophyte (Myriophyllum spicatum) and its secretion. Aquat. Toxicol. 98, 196–203. https://doi.org/10.1016/j.aquatox.2010.02.011 (2010).CAS 
Article 
PubMed 

Google Scholar 
Wan, J., Guo, P., Peng, X. & Wen, K. Effect of erythromycin exposure on the growth, antioxidant system and photosynthesis of Microcystis flos-aquae. J. Hazard. Mater. 283, 778–786. https://doi.org/10.1016/j.jhazmat.2014.10.026 (2015).CAS 
Article 
PubMed 

Google Scholar 
Wang, R. et al. Evaluating the effects of allelochemical ferulic acid on Microcystis aeruginosa by pulse-amplitude-modulated (PAM) fluorometry and flow cytometry. Chemosphere 147, 264–271. https://doi.org/10.1016/j.chemosphere.2015.12.109 (2016).CAS 
Article 
PubMed 

Google Scholar 
Long, M. et al. Allelochemicals from Alexandrium minutum induce rapid inhibition of metabolism and modify the membranes from Chaetoceros muelleri. Algal Res. 35, 508–518. https://doi.org/10.1016/j.algal.2018.09.023 (2018).Article 

Google Scholar 
Cosgrove, J. & Borowitzka, M. A. Chloreophyll fluorescence terminology: An introduction. In Chlorophyll a Fluorescence in Aquatic Sciences: Methods and Applications, Developments in Applied Phycology Vol. 4 (eds Sugget, D. J. et al.) 1–18 (Springer, 2010).
Google Scholar 
Kumar, K. S. & Han, T. Physiological response of Lemna species toherbicides and its probable use in toxicity testing. Toxicol. Environ. Health Sci. 2, 39–49. https://doi.org/10.1007/BF03216512 (2010).Article 

Google Scholar 
Ricart, M. et al. Primary and complex stressors in polluted mediterranean rivers: Pesticide effects on biological communities. J. Hydrol. 383, 52–61. https://doi.org/10.1016/j.jhydrol.2009.08.014 (2010).CAS 
Article 

Google Scholar 
Deng, C., Pan, X. & Zhang, D. Influence of of loxacin on photosystems I and II activities of Microcystis aeruginosa and the potential role of cyclic electron flow. J. Biosci. Bioeng. 119, 159–164. https://doi.org/10.1016/j.jbiosc.2014.07.014 (2015).CAS 
Article 
PubMed 

Google Scholar 
Pereira, S. et al. Complexity of cyanobacterial exopolysaccharides: Composition, structures, inducing factors and putative genes involved in their biosynthesis and assembly. FEMS Microbiol. Rev. 33, 917–941. https://doi.org/10.1111/j.1574-6976.2009.00183.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Gao, L. et al. Extracellular polymeric substances buffer against the biocidal effect of H2O2 on the bloom-forming cyanobacterium Microcystis aeruginosa. Water Res. 69, 51–58. https://doi.org/10.1016/j.watres.2014.10.060 (2015).CAS 
Article 
PubMed 

Google Scholar 
Zhang, S. et al. Ameliorating effects of extracellular polymeric substances excreted by Thalassiosira pseudonana on algal toxicity of CdSe quantum dots. Aquat. Toxicol. 126, 214–223. https://doi.org/10.1016/j.aquatox.2012.11.012 (2013).CAS 
Article 
PubMed 

Google Scholar 
Henriques, I. D. S. & Love, N. G. The role of extracellular polymeric substances in the toxicity response of activated sludge bacteria to chemical toxins. Water Res. 41, 4177–4185. https://doi.org/10.1016/j.watres.2007.05.001 (2007).CAS 
Article 
PubMed 

Google Scholar 
Zheng, S. M. et al. Role of extracellular polymeric substances on the behavior and toxicity of silver nanoparticles and ions to green algae Chlorella vulgaris. Sci. Total Environ. 660, 1182–1190. https://doi.org/10.1016/j.scitotenv.2019.01.067 (2019).CAS 
Article 
PubMed 

Google Scholar  More