Philippa Kaur

Ma, Z., Xue, L. & Du, S. Theory and Technology of High-Efficient Use of Water and Fertilizer for Watermelon and Melon in Gravel-Mulched Field 59–62 (Science Press, Beijing, 2018).
Google Scholar 
Qiu, Y., Xie, Z., Wang, Y., Malhi, S. S. & Ren, J. Long-term effects of gravel—Sand mulch on soil organic carbon and nitrogen in the Loess Plateau of northwestern China. J. Arid. Land 7, 46–53. https://doi.org/10.1007/s40333-014-0076-7 (2015).Article 

Google Scholar 
Zhang, K., Zhang, W., Tan, L., An, Z. & Zhang, H. Effects of gravel mulch on aeolian transport: A field wind tunnel simulation. J. Arid. Land 7, 296–303. https://doi.org/10.1007/s40333-015-0121-1 (2015).Article 

Google Scholar 
Yamanaka, T., Inoue, M. & Kaihotsu, I. Effects of gravel mulch on water vapor transfer above and below the soil surface. Agric. Water Manag. 67, 145–155. https://doi.org/10.1016/j.agwat.2004.01.002 (2004).Article 

Google Scholar 
Wang, J., Xie, Z., Guo, Z. & Wang, Y. Simulating the effect of gravel-sand mulched field degradation on soil temperature and evaporation. J. Desert Res. 30, 6 (2010).
Google Scholar 
Kaseke, K. F. et al. The effects of desert pavements (gravel mulch) on soil micro-hydrology. Pure Appl. Geophys. 169, 873–880. https://doi.org/10.1007/s00024-011-0367-2 (2012).ADS 
Article 

Google Scholar 
Inagaki, M. N. How does a stone mulch increase transpiration and grain yield in wheat under soil water deficit stress?. Cereal Res. Commun. 40, 486–493 (2012).CAS 
Article 

Google Scholar 
Abdelfattah, M. A. Pedogenesis, land management and soil classification in hyper-arid environments: Results and implications from a case study in the United Arab Emirates. Soil Use Manag. 29, 279–294 (2013).Article 

Google Scholar 
Lightfoot, D. The cultural ecology of Puebloan pebble-mulch gardens. Hum. Ecol. 21, 115–143. https://doi.org/10.1007/BF00889356 (1993).Article 

Google Scholar 
Graf, A., Kuttler, W. & Werner, J. Mulching as a means of exploiting dew for arid agriculture?. Atmos. Res. 87, 369–376 (2008).Article 

Google Scholar 
Shao Ping, D. U., Ma, Z. M. & Xue, L. Distribution characteristics of soil aggregates and their associated organic carbon in gravel-mulched land with different cultivation years. Ying Yong Sheng Tai Xue Bao 28, 1619–1625 (2017).
Google Scholar 
Zhong-Ming, M. A., Shao-Ping, D. U. & Xue, L. Influences of sand-mulching years on soil temperature, water content, and growth and water use efficiency of watermelon. J. Desert Res. 33, 1433–1439 (2013).
Google Scholar 
Pang, L. et al. Effect of different gravel mulched years on soil microflora and physicochemical properties in gravel-sand mulched field. Agric. Res. Arid Areas (2017).Hao, H. et al. Effects of gravel-sand mulching on soil bacterial community and metabolic capability in the semi-arid Loess Plateau, China. World J. Microbiol. Biotechnol. 33, 209 (2017).PubMed 
Article 
CAS 

Google Scholar 
Gregorich, E. G., Carter, M. R., Angers, D. A., Monreal, C. & Ellert, B. H. Towards a minimum data set to assess soil organic matter quality in agricultural soils. Can. J. Soil Sci. 74, 367–385 (1994).CAS 
Article 

Google Scholar 
Jandl, R. et al. Current status, uncertainty and future needs in soil organic carbon monitoring. Sci. Total Environ. 468–469, 376–383 (2014).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Lal, R. Enhancing crop yields in the developing countries through restoration of the soil organic carbon pool in agricultural lands. Land Degrad. Dev. 17, 197–209 (2010).Article 

Google Scholar 
Razafimbelo, T. M. et al. Aggregate associated-C and physical protection in a tropical clayey soil under Malagasy conventional and no-tillage systems. Soil Tillage Res. 98(2), 140–149 (2007).Article 

Google Scholar 
Hongbing, Z. et al. Effect of long-term tillage on soil aggregates and aggregate-associated carbon in black soil of Northeast China. PLoS ONE 13, e0199523 (2018).Article 
CAS 

Google Scholar 
Bajracharya, R. M., Lal, R. & Kimble, J. M. Soil organic carbon distribution in aggregates and primary particle fractions as influenced by erosion phases and landscape position. In Soil Processes & the Carbon Cycle (eds Lal, R. et al.) (CRC Press, 1998).
Google Scholar 
Sekaran, U., Sagar, K. L. & Kumar, S. Soil aggregates, aggregate-associated carbon and nitrogen, and water retention as influenced by short and long-term no-till systems. Soil Tillage Res. 208, 104885 (2020).Article 

Google Scholar 
Tang, X., Liu, S., Liu, J. & Zhou, G. Effects of vegetation restoration and slope positions on soil aggregation and soil carbon accumulation on heavily eroded tropical land of Southern China. J. Soils Sediments 10, 505–513 (2010).CAS 
Article 

Google Scholar 
Wang, Y. et al. 23-Year manure and fertilizer application increases soil organic carbon sequestration of a rice–barley cropping system. Biol. Fertil. Soils 51(5), 583–591 (2015).Article 

Google Scholar 
Zhou, H., Fang, H., Mooney, S. J. & Peng, X. Effects of long-term inorganic and organic fertilizations on the soil micro and macro structures of rice paddies. Geoderma 266, 66–74 (2016).ADS 
CAS 
Article 

Google Scholar 
Congreves, K. A., Hooker, D. C., Hayes, A., Verhallen, E. A. & Eerd, L. V. Interaction of long-term nitrogen fertilizer application, crop rotation, and tillage system on soil carbon and nitrogen dynamics. Plant Soil 410, 113–127 (2017).CAS 
Article 

Google Scholar 
Tang, H., Xiao, X., Chao, L., Ke, W. & Pan, X. Impact of long-term fertilization practices on the soil aggregation and humic substances under double-cropped rice fields. Environ. Sci. Pollut. Res. Int. 25, 11034–11044 (2018).CAS 
PubMed 
Article 

Google Scholar 
Rong, Y., Su, Y. Z., Wang, T. & Qin, Y. Effect of chemical and organic fertilization on soil carbon and nitrogen accumulation in a newly cultivated farmland. J. Integr. Agric. 15, 658–666 (2019).
Google Scholar 
Chen, Y. et al. Rotation and organic fertilizers stabilize soil water-stable aggregates and their associated carbon and nitrogen in flue-cured tobacco production. J. Soil Sci. Plant Nutr. 20, 192–205 (2020).Article 
CAS 

Google Scholar 
Li, T. et al. Contrasting impacts of manure and inorganic fertilizer applications for nine years on soil organic carbon and its labile fractions in bulk soil and soil aggregates. CATENA 194, 104739. https://doi.org/10.1016/j.catena.2020.104739 (2020).CAS 
Article 

Google Scholar 
Hati, K. M. et al. 50 Years of continuous no-tillage, stubble retention and nitrogen fertilization enhanced macro-aggregate formation and stabilisation in a Vertisol. Soil Tillage Res. 214, 105163. https://doi.org/10.1016/j.still.2021.105163 (2021).Article 

Google Scholar 
Ma, P. et al. Macroaggregation is promoted more effectively by organic than inorganic fertilizers in farmland ecosystems of China—A meta-analysis. Soil Tillage Res. 221, 105394. https://doi.org/10.1016/j.still.2022.105394 (2022).Article 

Google Scholar 
Lu, R. Chemical Analysis Methods of Soil and Agriculture (China Agricultural Science and Technology Press, 2000).
Google Scholar 
Dorodnikov, M., Blagodatskaya, E., Blagodatsky, S., Marhan, S. & Kuzyakov, Y. Stimulation of microbial extracellular enzyme activities by elevated CO2 depends on soil aggregate size. Glob. Change Biol. 15, 1603–1614 (2010).ADS 
Article 

Google Scholar 
Kemper, W. D. & Rosenau, R. C. Aggregate stability and size distribution. In Methods of Soil Analysis: Part 1 Physical and Mineralogical Methods. Agronomy Monograph No. 9, ASA and SSSA 2nd edn (ed. Klute, A.) 425–442 (Wiley, 1986).
Google Scholar 
Jones, J. B. Laboratory Guide for Conducting Soil Tests and Plant Analysis (Nurse Educ, 2001).Book 

Google Scholar 
Blair, G., Lefroy, R. & Lisle, L. Soil carbon fractions based on their degree of oxidation, and the development of a carbon management index for agricultural systems. Aust. J. Agric. Res. 46, 393–406 (1995).Article 

Google Scholar 
Li, W., Zheng, Z., Li, T. & Liu, M. Distribution characteristics of soil aggregates and its organic carbon in different tea plantation age. Acta Ecol. Sin. 34, 6326–6336 (2014).
Google Scholar 
Matos, E. S., Freese, D., Böhm, C., Quinkenstein, A. & Hüttl, R. Organic matter dynamics in reclaimed lignite mine soils under Robinia pseudoacacia L. plantations of different ages in Germany. Commun. Soil Sci. Plant Anal. 43, 745–755 (2012).CAS 
Article 

Google Scholar 
Zádorová, T., Jakšík, O., Kodešová, R. & Penížek, V. Influence of terrain attributes and soil properties on soil aggregate stability. Soil Water Res. 6, 111–119 (2011).Article 

Google Scholar 
Sajjadi, S. A. & Mahmoodabadi, M. Aggregate breakdown and surface seal development influenced by rain intensity, slope gradient and soil particle size. Solid Earth 6(1), 311–321 (2015).ADS 
Article 

Google Scholar 
Yang, W. et al. Mechanical properties and soil stability affected by fertilizer treatments for an Ultisol in subtropical China. Plant Soil 363(1), 157–174 (2013).CAS 
Article 

Google Scholar 
Lal, R. Soil health and carbon management. Food Energy Secur. 5, 212–222 (2016).Article 

Google Scholar 
Jagadamma, S., Lal, R., Hoeft, R. G., Nafziger, E. D. & Adee, E. A. Nitrogen fertilization and cropping systems effects on soil organic carbon and total nitrogen pools under chisel-plow tillage in Illinois. Soil Tillage Res. 95, 348–356 (2007).Article 

Google Scholar 
Yang, X. M. et al. Long-term effects of fertilization on soil organic carbon changes in continuous corn of northeast China: RothC model simulations. Environ. Manage. 32, 459–465 (2003).CAS 
PubMed 
Article 

Google Scholar 
Russell, A. E., Laird, D. A., Parkin, T. B. & Mallarino, A. P. Impact of nitrogen fertilization and cropping system on carbon sequestration in Midwestern mollisols. Soil Sci. Soc. Am. J. 69, 413–422 (2005).ADS 
CAS 
Article 

Google Scholar 
Hartwig, N. L. Cover crop and living mulches. Weed Sci. 50, 688–699 (2002).CAS 
Article 

Google Scholar 
Yu, H. et al. Effects of long-term compost and fertilizer application on stability of aggregate-associated organic carbon in an intensively cultivated sandy loam soil. Biol. Fertil. Soils 48, 325–336 (2012).CAS 
Article 

Google Scholar 
Li, C., Yan, L. & Tang, L. The effects of long-term fertilization on the accumulation of organic carbon in the deep soil profile of an oasis farmland. Plant Soil 369, 645–656 (2013).CAS 
Article 

Google Scholar 
Puget, P., Chenu, C. & Balesdent, J. Dynamics of soil organic matter associated with particle-size fractions of water-stable aggregates. Eur. J. Soil Sci. 51, 595–605 (2000).Article 

Google Scholar 
Ashman, M. R., Hallett, P. D. & Brookes, P. C. Are the links between soil aggregate size class, soil organic matter and respiration rate artefacts of the fractionation procedure?. Soil Biol. Biochem. 35, 435–444 (2003).CAS 
Article 

Google Scholar 
Six, J., Elliott, E. T. & Paustian, K. Soil macroaggregate turnover and microaggregate formation: a mechanism for C sequestration under no-tillage agriculture. Soil Biol. Biochem. 32, 2099–2103 (2000).CAS 
Article 

Google Scholar 
Chivenge, P. P., Murwira, H. K., Giller, K. E., Mapfumo, P. & Six, J. Long-term impact of reduced tillage and residue management on soil carbon stabilization: Implications for conservation agriculture on contrasting soils. Soil Tillage Res. 94, 328–337 (2006).Article 

Google Scholar 
Kölbl, A. & Knabner, I. K. Content and composition of free and occluded particulate organic matter in a differently textured arable Cambisol as revealed by solid-state 13C NMR spectroscopy. J. Plant Nutr. Soil Sci. 167, 45–53 (2004).Article 
CAS 

Google Scholar 
Tong, L. et al. Response of organic carbon fractions and microbial community composition of soil aggregates to long-term fertilizations in an intensive greenhouse system. J. Soils Sediments 20, 641–652. https://doi.org/10.1007/s11368-019-02436-x (2020).CAS 
Article 

Google Scholar 
Li, C., Li, Y. & Tang, L. The effects of long-term fertilization on the accumulation of organic carbon in the deep soil profile of an oasis farmland. Plant Soil 369, 645–656. https://doi.org/10.1007/s11104-013-1605-4 (2013).CAS 
Article 

Google Scholar 
Su, Y. Z., Wang, F., Suo, D. R., Zhang, Z. H. & Du, M. W. Long-term effect of fertilizer and manure application on soil-carbon sequestration and soil fertility under the wheat–wheat–maize cropping system in northwest China. Nutr. Cycl. Agroecosyst. 75, 285–295 (2006).CAS 
Article 

Google Scholar 
Du, S. P., Ma, Z. M. & Xue, L. Effect of manure combined with chemical fertilizers on fruit yield, fruit quality and water and nitrogen use efficiency in watermelon grown in gravel-mulched field. J. Fruit Sci. 37, 10. https://doi.org/10.13925/j.cnki.gsxb.20190380 (2020).CAS 
Article 

Google Scholar 
Zhengchao, Z., Zhuoting, G., Zhouping, S. & Fuping, Z. Effects of long-term repeated mineral and organic fertilizer applications on soil organic carbon and total nitrogen in a semi-arid cropland. Eur. J. Agron. 45, 20–26. https://doi.org/10.1016/j.eja.2012.11.002 (2013).CAS 
Article 

Google Scholar 
Lv, W. et al. Effects of organic fertilizers on continuous cropping watermelon growth and soil microflora. Acta Agric. Shanghai 22, 96–98 (2006).
Google Scholar 
Zhong, W. et al. The effects of mineral fertilizer and organic manure on soil microbial community and diversity. Plant Soil 326, 511–522 (2010).CAS 
Article 

Google Scholar  More

Kuzyakov Y, Razavi BS. Rhizosphere size and shape: Temporal dynamics and spatial stationarity. Soil Biol Biochem. 2019;135:343–60.CAS 
Article 

Google Scholar 
Teixeira PJ, Colaianni NR, Fitzpatrick CR, Dangl JL. Beyond pathogens: Microbiota interactions with the plant immune system. Curr Opin Microbiol. 2019;49:7–17.CAS 
PubMed 
Article 

Google Scholar 
Alirezaeizanjani Z, Großmann R, Pfeifer V, Hintsche M, Beta C. Chemotaxis strategies of bacteria with multiple run modes. Sci Adv. 2020;6:eaaz6153.PubMed 
PubMed Central 
Article 

Google Scholar 
Gao S, Wu H, Yu X, Qian L, Gao X. Swarming motility plays the major role in migration during tomato root colonization by Bacillus subtilis SWR01. Biol Control. 2016;98:11–17.CAS 
Article 

Google Scholar 
Mitchell JG, Kogure K. Bacterial Motility: Links to the environment and a driving force for microbial physics. FEMS Microbiol Ecol. 2006;55:3–16.CAS 
PubMed 
Article 

Google Scholar 
Kalamara M, Spacapan M, Mandic-Mulec I, Stanley-Wall NR. Social behaviours by Bacillus subtilis: Quorum sensing, kin discrimination and beyond. Mol Microbiol. 2018;110:863–78.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Posada LF, Álvarez JC, Romero-Tabarez M, de-Bashan L, Villegas-Escobar V. Enhanced molecular visualization of root colonization and growth promotion by Bacillus subtilis EA-CB0575 in different growth systems. Microbiol Res. 2018;217:69–80.CAS 
PubMed 
Article 

Google Scholar 
Beauregard PB, Yunrong C, Vlamakis H, Losick R, Kolter R. Bacillus subtilis Biofilm induction by plant polysaccharides. Proc Natl Acad Sci USA. 2013;110:1621–30.Article 

Google Scholar 
Allard-Massicotte R, Tessier L, Lécuyer F, Lakshmanan V, Lucier J. Bacillus subtilis early colonization of Arabidopsis thaliana roots involves multiple chemotaxis receptors. mBio 2016;7:1–10.Article 

Google Scholar 
Massalha H, Korenblum E, Malitsky S, Shapiro OH, Aharoni A. Live imaging of root-bacteria interactions in a microfluidics setup. Proc Natl Acad Sci USA. 2017;114:4549–54.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Koch DL, Subramanian G. Collective hydrodynamics of swimming microorganisms: Living fluids. Annu Rev Fluid Mech. 2011;43:637–59.Article 

Google Scholar 
Wioland H, Lushi E, Goldstein RE. Directed collective motion of bacteria under channel confinement. New J Phys. 2016;18:eaaz6153.Article 

Google Scholar 
Petroff A, Libchaber A. Erratum: Hydrodynamics and collective behavior of the tethered bacterium Thiovulum majus. Proc Natl Acad Sci USA. 2016;111:5. E537-E545
Google Scholar 
Kearns DB. A field guide to bacterial swarming motility. Nat Rev Microbiol. 2010;8:634–44.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Bais HP, Fall R, Vivanco JM. Biocontrol of Bacillus subtilis against infection of arabidopsis roots by Pseudomonas syringae is facilitated by biofilm formation and surfactin production. Plant Physiol. 2004;134:307–19.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
De Souza R, Ambrosini A, Passaglia LMP. Plant growth-promoting bacteria as inoculants in agricultural soils. Genet Mol Biol. 2015;38:401–19.PubMed 
PubMed Central 
Article 

Google Scholar 
Roy K, Ghosh D, DeBruyn JM, Dasgupta T, Wommack KE, Liang X, et al. Temporal dynamics of soil virus and bacterial populations in agricultural and early plant successional soils. Front Microbiol. 2020;11:1–13.Article 

Google Scholar 
Liu Y, Patko D, Engelhardt IC, George TS, Stanley-Wall NP, Ladmiral V. et al. Whole plant-environment microscopy reveals how Bacillus subtilis utilises the soil pore space to colonise plant roots. Proc Natl Acad Sci USA. 2021;118:e2109176118.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Einstein A. On the motion of small particles suspended in liquids at rest required by the molecular-kinetic theory of heat. Ann Phys. 1905;17:549–60.CAS 
Article 

Google Scholar 
Shellard A, Mayor R. Rules of Collective Migration: From the wildebeest to the neural crest: Rules of neural crest migration. Philos Trans R Soc B Biol Sci. 2020;375:1–9.Article 

Google Scholar 
Torney CJ, Lamont M, Debell L, Angohiatok RJ, Leclerc LM, Berdahl AM. Inferring the rules of social interaction in migrating caribou. Philos Trans R Soc B Biol Sci. 2018;373:20170385.Article 

Google Scholar 
Ballerini MN, Cabibbo R, Candelier A, Cavagna E, Cisbani I, Giardina V, et al. Interaction ruling animal collective behavior depends on topological rather than metric distance: Evidence from a field study. Proc Natl Acad Sci USA. 2008;105:1232–37.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cavagna A, Cimarelli A, Giardina I, Parisi G, Santagati R, Stefanini F, et al. Scale-free correlations in starling flocks. Proc Natl Acad Sci USA. 2010;107:11865–70.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Katz Y, Tunstrøm C, Ioannou CC, Huepe C, Couzin ID. Inferring the structure and dynamics of interactions in schooling fish. Proc Natl Acad Sci USA. 2011;108:18720–25.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Buhl JD, Sumpter JT, Couzin ID, Hale JJ, Despland E, Miller ER, et al. From disorder to order in marching locusts. Science 2006;312:1402–6.CAS 
PubMed 
Article 

Google Scholar 
Seeley TD, Visscher PK. Quorum Sensing during nest-site selection by honeybee swarms. Behav Ecol Sociobiol. 2004;56:594–601.Article 

Google Scholar 
Zhang HP, Be’er A, Florin EL, Swinney HL. Collective motion and density fluctuations in bacterial colonies. Proc Natl Acad Sci USA. 2010;107:13626–30.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hughey LF, Hein AM, Strandburg-Peshkin A, Jensen FH. Challenges and solutions for studying collective animal behaviour in the wild. Philos Trans R Soc B Biol Sci. 2018;373:1–13.Article 

Google Scholar 
Nadell CD, Xavier JB, Foster KR. The sociobiology of biofilms. FEMS Microbiol Rev. 2009;33:206–24.CAS 
PubMed 
Article 

Google Scholar 
Velicer GJ, Vos M. Sociobiology of the myxobacteria. Ann Rev Microbiol. 2009;63:599–623.CAS 
Article 

Google Scholar 
Branda SS, González-Pastor JE, Ben-Yehuda S, Losick R, Kolter R. Fruiting body formation by Bacillus subtilis. Proc Natl Acad Sci USA. 2001;98:11621–26.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Cordero OX, Wildschutte H, Kirkup B, Proehl S, Ngo L, Hussain F, et al. Antibiotic production and resistance. Sci Rep. 2012;337:1228–31.CAS 

Google Scholar 
Muñoz-Dorado J, Marcos-Torres FJ, García-Bravo E, Moraleda-Muñoz A, Pérez J. Myxobacteria: Moving, killing, feeding, and surviving together. Front Microbiol. 2016;7:1–18.Article 

Google Scholar 
Li C, Hurley A, Hu W, Warrick JW, Lozano GL, Ayuso JM, et al. Social motility of biofilm-like microcolonies in a gliding bacterium. Nat Commun. 2021;12:1–12.Article 
CAS 

Google Scholar 
Sokolov A, Aranson IS, Kessler JO, Goldstein RE. Concentration dependence of the collective dynamics of swimming bacteria. Phys Rev Lett. 2007;98:158102.PubMed 
Article 
CAS 

Google Scholar 
Cisneros LH, Cortez R, Dombrowski C, Goldstein RE, Kessler JO. Fluid dynamics of self-propelled microorganisms, from individuals to concentrated populations. Exp Fluids. 2007;43:737–53.Article 

Google Scholar 
Tuval I, Cisneros L, Dombrowski C, Wolgemuth CW, Kessler JO, Goldstein RE. Bacterial swimming and oxygen transport near contact lines. Proc Natl Acad Sci USA. 2005;102:2277–82.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Li G, Tam L, Tang JX. Amplified effect of brownian motion in bacterial near-surface swimming. Proc Natl Acad Sci USA. 2008;105:18355–59.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Lushi E, Wioland H, Goldstein RE. Fluid flows created by swimming bacteria drive self-organization in confined suspensions. Proc Natl Acad Sci USA. 2014;111:9733–38.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ryan SD, Sokolov A, Berlyand L, Aranson IS. Correlation properties of collective motion in bacterial suspensions. New J Phys. 2013;15:105021.Article 

Google Scholar 
Damton NC, Turner L, Rojevsky S, Berg HC. Dynamics of bacterial swarming. Biophys J. 2010;98:2082–90.Article 
CAS 

Google Scholar 
Ingham CJ, Jacob EB. Swarming and complex pattern formation in Paenibacillus vortex studied by imaging and tracking cells. BMC Microbiol. 2008;8:1–16.Article 
CAS 

Google Scholar 
Ariel G, Rabani A, Benisty S, Partridge JD, Harshey RM, Be’Er A. Swarming bacteria migrate by lévy walk. Nat Commun. 2015;6:8396.CAS 
PubMed 
Article 

Google Scholar 
Hamze K, Autret S, Hinc K, Laalami S, Julkowska D, Briandet R, et al. Single-cell analysis in situ in a Bacillus subtilis swarming community identifies distinct spatially separated subpopulations differentially expressing Hag (Flagellin), including specialized swarmers. Microbiol. 2011;157:2456–69.CAS 
Article 

Google Scholar 
Ghelardi E, Salvetti S, Ceragioli M, Gueye SA, Celandroni F, Senesi S. Contribution of surfactin and swrA to flagellin expression, swimming, and surface motility in Bacillus subtilis. Appl Environ Microbiol. 2012;78:6540–44.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Wilde A, Mullineaux CW. Light-controlled motility in prokaryotes and the problem of directional light perception. FEMS Microbiol Rev. 2017;41:900–22.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Zhang J, Luo Y, Poh CL. Blue light-directed cell migration, aggregation, and patterning. J Mol Biol. 2020;432:3137–48.CAS 
PubMed 
Article 

Google Scholar 
Tian T, Sun B, Shi H, Gao T, He Y, Li Y, et al. Sucrose triggers a novel signalling cascade promoting Bacillus subtilis rhizosphere colonization. ISME J 2021;15:2723–37.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Harshey RM, Partridge JD. Shelter in a swarm. J Mol Biol. 2015;427:3683–94.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Burdett IDJ, Kirkwood TBL, Whalley JB. Growth kinetics of individual Bacillus subtilis cells and correlation with nucleoid extension. J Bacteriol. 1986;167:219–30.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Sharpe ME, Hauser PM, Sharpe RG, Errington J. Bacillus subtilis cell cycle as studied by fluorescence microscopy: Constancy of cell length at initiation of DNA replication and evidence for active nucleoid partitioning. J Bacteriol. 1998;180:547–55.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rousk J, Bååth E. Growth of saprotrophic fungi and bacteria in soil. FEMS Microbiol Ecol. 2011;78:17–30.CAS 
PubMed 
Article 

Google Scholar 
Bennett RA, Lynch JM. Bacterial growth and development in the rhizosphere of gnotobiotic cereal plants. Microbiol. 1981;125:95–102.Article 

Google Scholar 
Felici C, Vettori L, Giraldi E, Forino LMC, Toffanin A, Tagliasacchi AM, et al. Single and co-inoculation of Bacillus subtilis and Azospirillum brasilense on Lycopersicon Esculentum: Effects on plant growth and rhizosphere microbial community. Appl Soil Ecol. 2008;40:260–70.Article 

Google Scholar 
Arkhipova TN, Galimsyanova NF, Kuzmina LY, Vysotskaya LB, Sidorova LV, Gabbasova IM, et al. Effect of seed bacterization with plant growth-promoting bacteria on wheat productivity and phosphorus mobility in the rhizosphere. Plant Soil Environ. 2019;65:313–19.CAS 
Article 

Google Scholar 
Marschner P, Crowley D, Rengel Z. Rhizosphere interactions between microorganisms and plants govern iron and phosphorus acquisition along the root axis – model and research methods. Soil Biol Biochem. 2011;43:883–94.CAS 
Article 

Google Scholar 
Lagos ML, Maruyama F, Nannipieri P, Mora ML, Jorquera MA. Current Overview on the study of bacteria in the rhizosphere by modern molecular techniques: A Mini-Review. J Soil Sci Plant Nutr. 2015;15:504–23.
Google Scholar 
Gerwig J, Kiley TB, Gunka K, Stanley-Wall N, Stülke J. The protein tyrosine kinases epsB and ptkA differentially affect biofilm formation in Bacillus Subtilis. Microbiol. 2014;160:682–91.CAS 
Article 

Google Scholar 
Shoesmith JG. The measurement of bacterial motility. J Gen Microbiol. 1960;22:528–35.Article 

Google Scholar 
Schneider WR, Doetsch RN. Effect of viscosity on bacterial motility. J Bacteriol. 1974;117:696–701.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Kaiser GE, Doetsch RN. Enhanced translational motion of Leptospira in viscous environments. Nature 1975;255:656–57.CAS 
PubMed 
Article 

Google Scholar 
Ryan SD, Haines BM, Berlyand L, Ziebert F, Aranson IS. Viscosity of bacterial suspensions: Hydrodynamic interactions and self-induced noise. Phys Rev E Stat Nonlin Soft Matter Phys. 2011;E83:050904.Article 
CAS 

Google Scholar 
López HM, Gachelin J, Douarche C, Auradou H, Clément E. Turning bacteria suspensions into superfluids. Phys Rev Lett. 2015;115:028301.PubMed 
Article 
CAS 

Google Scholar 
Butler MT, Wang Q, Harshey RM. Cell density and mobility protect swarming bacteria against antibiotics. Proc Natl Acad Sci USA. 2010;107:3776–81.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Erktan A, Or D, Scheu S. The physical structure of soil: Determinant and consequence of trophic interactions. Soil Biol Biochem. 2020;148:107876.CAS 
Article 

Google Scholar 
Rønn R, Thomsen IK, Jensen B. Naked amoebae, flagellates and nematodes in soil of different texture. Eur J Soil Biol. 1995;31:135–41.
Google Scholar 
Downie H, Holden N, Otten W, Spiers AJ, Valentine TA, Dupuy LX. Transparent soil for imaging the rhizosphere. PLoS ONE. 2012;7:1–6.Article 
CAS 

Google Scholar 
Mills AL. Keeping in Touch: Microbial life on soil particle surfaces. Adv Agron. 2003;78:1–43.Article 

Google Scholar 
Downie HF, Valentine TA, Otten W, Spiers AJ, Dupuy LX. Transparent soil microcosms allow 3D spatial quantification of soil microbiological processes in vivo. Plant Signal Behav. 2014;9:e970421.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
O’Callaghan FE, Braga RA, Neilson R, MacFarlane SA, Dupuy LX. New live screening of plant-nematode interactions in the rhizosphere. Sci Rep. 2018;8:1–17.Article 
CAS 

Google Scholar 
Sharma K, Palatinszky M, Nikolov G, Berry D, Shank EA. Transparent soil microcosms for live-cell imaging and non-destructive stable isotope probing of soil microorganisms. ELife 2020;9:1–28.
Google Scholar 
Bickel S, Or D. Soil bacterial diversity mediated by microscale aqueous-phase processes across biomes. Nat Commun. 2020;11:1–9.Article 
CAS 

Google Scholar 
Farré M, Sanchís J, Barceló D. Analysis and assessment of the occurrence, the fate and the behavior of nanomaterials in the environment. Trends Anal Chem. 2011;30:517–27.Article 
CAS 

Google Scholar 
Verhamme DT, Kiley TB, Stanley-Wall NR. DegU co-ordinates multicellular behaviour exhibited by Bacillus subtilis. Mol Microbiol. 2007;65:554–68.CAS 
PubMed 
Article 

Google Scholar 
Konkol MA, Blair KM, Kearns DB. Plasmid-encoded comi inhibits competence in the ancestral 3610 strain of Bacillus subtilis. J Bacteriol. 2013;195:4085–93.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Stanley NR, Lazazzera BA. Defining the genetic differences between wild and domestic strains of Bacillus subtilis that affect poly-γ-DL-glutamic acid production and biofilm formation. Mol Microbiol. 2005;57:1143–58.CAS 
PubMed 
Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2020. URL https://www.R-project.org/.Schindelin J, Arganda-Carreras I, Frise E, Kaynig V, Longair M, Pietzsch T, et al. (2012) Fiji: an open-source platform for biological-image analysis. Nat Methods. 2012;9:676–82.CAS 
PubMed 
Article 

Google Scholar  More

Historical changes and current status of the Dongzhaigang mangrove areaBased on the literature and remote sensing data, we calculated the changes in the area of mangrove forests in Dongzhaigang since the 1950s presented in Fig. 2. In the last 60 years, the area of mangrove forests in Dongzhaigang has experienced large fluctuations mainly due to human destruction and protection activities such as mariculture reclamation, cofferdams, and restoration: it decreased from 3416 hm2 in 195617 to 3213 hm2 in 195919,29 and then decreased sharply to 1733 hm2 in 1983 and to 1537 hm2 in 198720,30. Since the establishment of the national nature reserve in 1986, the decline in area of Dongzhaigang mangrove has stopped19, which are now protected and restored owing to the law and regulations that prohibit human activities from destroying the mangrove resource. In 1988, the area was restored to 1809 hm2, and since the 1990s, it has no longer decreased, remaining constant at approximately 1711 hm2 (in the range of 1575–1812 hm2) based on the literature)18,20,31,32,33,34 (Fig. 2). The area of the Dongzhaigang mangrove forest in 2019 was estimated to be 1842 hm2 based on the latest 2 m resolution remote sensing data21. Hence, we wonder how SLR has impacted Dongzhaigang mangrove in the past decades. However, it is very difficult to analyze how SLR has historically impacted the spatial changes in the Dongzhaigang mangrove; the same can be said regarding the influence of human activities, such as destruction before mid-1980s and protection after 1990s. However, the dynamic changes among low plant edges in the intertidal zone can be used to analyze the impact of natural driving forces such as SLR35, based on the latest remote sensing data for the period of 1986–2020. Thus, we analyzed the dynamic changes in low mangrove edges (hereafter, the edges), which are mainly impacted by natural impact drivers, as shown in Fig. 3. The dynamic low mangrove edges represented by 1986, 2000, and 2020 reveal the changes in spatial distribution of Dongzhaigang mangrove. As shown in Fig. 3. Most of the edges along the coast of Dongzhaigang between 1986 and 2020 migrated landward, but not significantly. However, if we look at the changes in detail, some edges such as those in Daoxue, Sanjiang (purple circles in Figs. 3a,b–d,e–g) more clearly retreated landward compared to other places. Besides, some edges of Luodou along the northeastern coast of Dongzhaigang outside the reserve and an unnamed small island (pruple circles in Fig. 3a,h–j) also migrated landward very distinctly. On the contrary, the two smaller shore lines (black circles) in the northern part of Yangfeng and Daxue districts showed seaward expansion (Fig. 3a).Figure 2Changes in the mangrove area in Dongzhaigang from 1956 to 2019. The equation in the upper-right-hand corner of the plot refers to the fitting equation of historical changes in the total area of Dongzhaigang mangrove.Full size imageFigure 3The dynamic changes in low mangrove edges in Dongzhaigang from 1986 to 2020. Maps generated in ArcMap v10.0 (https://www.esri.com/en-us/home).Full size imageVertical rate of sediment accretion in mangrove wetlandsThe vertical rate of sediment accumulation in mangrove wetlands can reflect whether the mangroves can adjust the soil surface elevation change through sediment trapping to adapt to SLR6,11. The vertical sediment accretion rates at two sites of Dongzhaigang mangrove (i.e., Linshi and Daoxue villages in Fig. 1b) can be obtained from historical documents, which are 0.41 cm year−1 at LS and 0.64 cm year−1 at DX, respectively27,28. Since historical data may not be enough to reflect the vertical sediment accretion rates in time and space, we conducted a supplementary investigation on the sediment accumulation rates at site HG in Yanfeng and SJ site in Sanjiang farms, respectively (Fig. 1b), based on the assumption that they can reflect the sediment supplies from main reivers such as Yanfeng West River and Yanzhou River, respectively. Sediment accretion rates measured using 210Pbex specific activity in the cores from sites HG and SJ showed that 210Pbex decayed exponentially with increasing depth, and the R2 values of both cores were approximately 0.80 after curve fitting. This analysis resulted in vertical sediment accretion rates of 0.53 and 0.40 cm year−1 at HG and SJ, respectively (Fig. 4). Therefore, the locations of sediment cores at sites LS, DX, HG, and SJ can basically represent the whole Dongzhaigang mangrove forest area.Figure 4210Pbex activity profiles in selected cores such as from (a) station HG and (b) station SJ.Full size imageRate of relative sea level rise in Dongzhaigang mangroveThe global mean sea level (GMSL) is accelerating due to global warming-induced thermal expansion of the oceans and melting of land-based glaciers and ice caps into the sea36. Between 1901 and 2010, the GMSL rose by 0.19 m9. Coastal China is among the regions that experience the highest levels of SLR23. The rate of RSLR along China’s coast from 1980 to 2019 was 3.4 mm year−1, higher than the global average23. In the future, under the premise of increasing anthropogenic GHG emissions, global sea levels will rise rapidly, and it is projected that the GMSL may rise by 0.84 m (0.61–1.10 m) relative to the current levels by the end of the twenty-first century9. Based on the observations from the tide gauge stations in the Haikou area and model data from the Coupled Model Intercomparison Projection 5 (CMIP5), the rate of RSLR around Dongzhaigang reached 4.6 mm year−1 from 1980 to 2018. This rate is much higher than the global and China’s average values23,25 and will likely accelerate further in the future. Based on the results of the CMIP5 model simulations under different GHG emission scenarios24, the RSLR in coastal Haikou waters, including in Dongzhaigang, is expected to be significant by 2030, 2050, and 2100 for the low, intermediate, and very high GHG emission scenarios RCPs 2.6, 4.5, and 8.5, respectively (Table 1, Fig. 5). Under RCPs 2.6, 4.5, and 8.5, the sea level will rise by 65 (42–90, likely range), 75 (51–102, likely range), and 96 (70–125, likely range) cm by 2100, respectively, with the average RSLR rates of 6.84 (4.42–9.47, likely range), 7.89 (5.37–10.74, likely range), and 10.1 (7.37–13.12, likely range) mm year−1, respectively.Table 1 Estimated coastal relative sea level rise (cm) and its rate (mm year−1) in the Haikou area under different GHG emission scenarios (data from Kopp et al.24).Full size tableFigure 5Historical and future relative sea level changes along coastal Dongzhaigang, Haikou City from 1980 to 2100; the 5–95% uncertainty ranges are shaded for RCPs 2.6, 4.5, and 8.5, respectively.Full size imageImpact of relative sea level rise on Dongzhaigang mangroveMangroves cannot easily adapt to rising sea levels if the rate of GMSL rise exceeds 6.1 mm year−1 ( > 90% probability, very likely), whereas the survival threshold for mangroves is extremely likely to be exceeded ( > 95% probability, extremely likely) when the rate of GMSL exceeds 7.6 mm year−17. Although these values are based on global levels7, they still reflect the threat of SLR to local mangroves. In view of this, we further analyzed the potential impact and risks to Dongzhaigang mangrove from future SLR under different climate scenarios.Based on the predicted future rates of SLR under RCPs 2.6, 4.5, and 8.5 and on the vertical sediment accretion rates of Dongzhaigang mangrove wetlands, the mangroves are likely to be affected by rising sea levels by 2030, 2050, and 2100, respectively (Table 2, Fig. 6). Under the low GHG emission scenario (RCP 2.6), the area of the Dongzhaigang mangrove forest will only experience a small reduction: 16.40% (1.20–16.95%, likely range), 302 hm2 (22–312 hm2, likely range); 16.73% (1.20–17.82%, likely range), 308 hm2 (22–328 hm2, likely range); and 17.60% (1.14–31.02%, likely range), 324 hm2 (21–571 hm2, likely range) by 2030, 2050, and 2100, respectively (Table 2, Fig. 6a). This is because the vertical sediment accretion rate of Dongzhaigang mangrove will remain largely constant with increasing RSLR rate. Moreover, it should be noted that compared with 2030, the increase areas of mangroves inundation caused by SLR will be small by 2050 under three RCPs scenarios (Table 2). In contrast, under the intermediate and very high GHG emission scenarios (RCPs 4.5 and 8.5), Dongzhaigang mangrove is expected to be more significantly affected by SLR. Under RCP 4.5, 26.56% (16.19–40.74%, likely range) or 489 hm2 (298–750 hm2, likely range) of mangrove forest will likely be lost by the end of the century (Table 3, Fig. 6b). Under RCP 8.5, it is projected that 31.99% (18.14–50.73%, likely range) or 589 hm2 (334–934 hm2, likely range) of mangrove forest will be lost by 2100 (Table 2, Fig. 6c). Therefore, under RCPs 4.5 and 8.5, the impact of SLR on mangrove wetlands by 2100 is much higher than that of RCP 2.6, and is likely to result in  > 26% of mangroves being lost, whereas under RCP 2.6, only 17% of mangroves are likely to be lost.Table 2 Area (hm2) and percentage of future mangrove loss in Dongzhaigang under different climate scenarios (RCPs 2.6, 4.5, and 8.5) (likely ranges).Full size tableFigure 6Potential loss of mangrove forests in Dongzhaigang under different climate scenarios (RCPs 2.6, 4.5, and 8.5). Maps generated in ArcMap v10.0 (https://www.esri.com/en-us/home).Full size imageTable 3 Core stations and depths.Full size tableUnder RCP 2.6, the rate of RSLR around Dongzhaigang will reach 0.72 cm year−1 in 2030 and then decrease in 2050 and 2080 to 0.69 and 0.68 cm year−1, respectively (Table 1). However, under RCP 4.5 (8.5), by 2030, 2050, and 2100, the rate of RSLR will reach 0.72 (0.72), 0.73 (0.80), and 0.79 (10.1) cm year−1, respectively. By 2100, some mangroves in the northern part of Tashi village, the eastern part of Yanfeng, the northern part of Daoxue Village, and the northeastern part of the Sanjiang farm will likely be lost owing to SLR, and other coastal wetlands will also be impacted. Since the rate of RSLR around Dongzhaigang is higher than the global average survival threshold for mangroves (i.e., the SLR rate exceeds 7.0 mm year−1), the Dongzhaigang mangrove will be significantly affected by SLR, with a potential loss of 31–32%; however, the survival threshold will not increase (Table 2, Fig. 6). More

Scott Baker, C. & Clapham, P. J. Modelling the past and future of whales and whaling. Trends Ecol. Evol. 19, 365–371. https://doi.org/10.1016/j.tree.2004.05.005 (2004).CAS 
Article 
PubMed 

Google Scholar 
Clapham, P. J. & Baker, C. S. in Encyclopedia of Marine Mammals (eds W. F. Perrin, B. Würsig, & J. G. M. Thewissen) Ch. Modern Whaling, 1328–1332 (Academic Press, 2002).International Whaling Commission. Twenty-Eighth Report of the International Whaling Commission. (International Whaling Commission, Cambridge, 1978).International Whaling Commission. Thirty-Sixth Report of the International Whaling Commission. (International Whaling Commission, Cambridge, 1986).Leaper, R. & Miller, C. Management of Antarctic baleen whales amid past exploitation, current threats and complex marine ecosystems. Antarct. Sci. 23, 503–529. https://doi.org/10.1017/s0954102011000708 (2011).ADS 
Article 

Google Scholar 
Tulloch, V. J. D., Plagányi, É. E., Matear, R., Brown, C. J. & Richardson, A. J. Ecosystem modelling to quantify the impact of historical whaling on Southern Hemisphere baleen whales. Fish Fish. 19, 117–137. https://doi.org/10.1111/faf.12241 (2018).Article 

Google Scholar 
Kemp, S. & Bennett, A. G. On the distribution and movements of whales on the South Georgia and South Shetland whaling grounds. Discov. Rep. 6, 165–190 (1932).
Google Scholar 
Branch, T. A. & Butterworth, D. S. Estimates of abundance south of 60°S for cetacean species sighted frequently on the 1978/79 to 1997/98 IWC/IDCR-SOWER sighting surveys. J. Cetac. Res. Manag. 3, 251–270 (2001).
Google Scholar 
Reilly, S. et al. Biomass and energy transfer to baleen whales in the South Atlantic sector of the Southern Ocean. Deep Sea Res. Part II 51, 1397–1409. https://doi.org/10.1016/s0967-0645(04)00087-6 (2004).ADS 
Article 

Google Scholar 
Cooke, J. G. Balaenoptera physalus. The IUCN Red List of Threatened Species 2018, e.T2478A50349982. https://doi.org/10.2305/IUCN.UK.2018-2.RLTS.T2478A50349982.en (2018).Santora, J. A., Schroeder, I. D. & Loeb, V. J. Spatial assessment of fin whale hotspots and their association with krill within an important Antarctic feeding and fishing ground. Mar. Biol. 161, 2293–2305. https://doi.org/10.1007/s00227-014-2506-7 (2014).Article 

Google Scholar 
Santora, J. A., Reiss, C. S., Loeb, V. J. & Veit, R. R. Spatial association between hotspots of baleen whales and demographic patterns of Antarctic krill Euphausia superba suggests size-dependent predation. Mar. Ecol. Prog. Ser. 405, 255–269. https://doi.org/10.3354/meps08513 (2010).ADS 
Article 

Google Scholar 
Burkhardt, E. et al. Seasonal and diel cycles of fin whale acoustic occurrence near Elephant Island, Antarctica. R Soc. Open Sci. 8, 201142. https://doi.org/10.1098/rsos.201142 (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Joiris, C. R. & Dochy, O. A major autumn feeding ground for fin whales, southern fulmars and grey-headed albatrosses around the South Shetland Islands, Antarctica. Polar Biol. 36, 1649–1658. https://doi.org/10.1007/s00300-013-1383-8 (2013).Article 

Google Scholar 
Herr, H. et al. Horizontal niche partitioning of humpback and fin whales around the West Antarctic Peninsula: Evidence from a concurrent whale and krill survey. Polar Biol. 39, 799–818. https://doi.org/10.1007/s00300-016-1927-9 (2016).Article 

Google Scholar 
Viquerat, S. & Herr, H. Mid-summer abundance estimates of fin whales Balaenoptera physalus around the South Orkney Islands and Elephant Island. Endanger. Spec. Res. 32, 515–524. https://doi.org/10.3354/esr00832 (2017).Article 

Google Scholar 
Meyer, B. & Wessels, W. The Expedition PS112 of the Research Vessel POLARSTERN to the Antarctic Peninsula Region in 2018. 125 p. (Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, 2018). https://doi.org/10.2312/BzPM_0722_2018Knust, R. Polar research and supply vessel POLARSTERN operated by the Alfred-Wegener-Institute. J. Large-Scale Res. Facil. JLSRF 3, A119. https://doi.org/10.17815/jlsrf-3-163 (2017).Article 

Google Scholar 
Buckland, S. T. et al. Introduction to Distance Sampling: Estimating Abundance of Biological Populations (Oxford University Press, 2001).MATH 

Google Scholar 
Herr, H. et al. Aerial surveys for Antarctic minke whales (Balaenoptera bonaerensis) reveal sea ice dependent distribution patterns. Ecol Evol 9, 5664–5682. https://doi.org/10.1002/ece3.5149 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Dorschel, B. et al. Environmental information for a marine ecosystem research approach for the northern Antarctic Peninsula (RV Polarstern expedition PS81, ANT-XXIX/3). Polar Biol. 39, 765–787. https://doi.org/10.1007/s00300-015-1861-2 (2015).Article 

Google Scholar 
Miller, D. L., Burt, M. L., Rexstad, E. A., Thomas, L. & Gimenez, O. Spatial models for distance sampling data: recent developments and future directions. Methods Ecol. Evol. 4, 1001–1010. https://doi.org/10.1111/2041-210x.12105 (2013).Article 

Google Scholar 
Hedley, S. L. & Buckland, S. T. Spatial models for line transect sampling. J. Agric. Biol. Environ. Stat. 9, 181–199. https://doi.org/10.1198/1085711043578 (2004).Article 

Google Scholar 
Hammond, P. S. et al. Estimating the abundance of marine mammal populations. Front. Mar. Sci. https://doi.org/10.3389/fmars.2021.735770 (2021).Article 

Google Scholar 
Buckland, S. T. et al. Advanced Distance Sampling (Oxford University Press, 2007).
Google Scholar 
Miller, D. L., Rexstad, E., Thomas, L., Marshall, L. & Laake, J. L. Distance sampling in R. J. Stat. Softw. 89, 1–28. https://doi.org/10.18637/jss.v089.i01 (2019).Article 

Google Scholar 
Marques, F. F. C. & Buckland, S. T. in Advanced Distance Sampling (eds S. T. Buckland et al.) 31–47 (Oxford University Press, 2004).Akaike, H. A new look at the statistical model identification. IEEE Trans. Autom. Control 19, 716–723 (1974).ADS 
MathSciNet 
Article 

Google Scholar 
Wood, S. N. Fast stable restricted maximum likelihood and marginal likelihood estimation of semparametric generalized linear models. J. R. Stat. Soc. (B) 73, 3–36. https://doi.org/10.1111/j.1467-9868.2010.00749.x (2011).Article 
MATH 

Google Scholar 
Wood, S. N., Pya, N. & Saefken, B. Smoothing parameter and model selection for general smooth models (with discussion). J. Am. Stat. Assoc. 111, 1548–1575. https://doi.org/10.1080/01621459.2016.1180986 (2016).CAS 
Article 

Google Scholar 
Dorschel, B. et al. The International Bathymetric Chart of the Southern Ocean Version 2 (IBCSO v2). Scientific Data. https://doi.org/10.1038/s41597-022-01366-7 (2022).Article 

Google Scholar 
Wilson, M. F. J., O’Connell, B., Brown, C., Guinan, J. C. & Grehan, A. J. Multiscale terrain analysis of multibeam bathymetry data for habitat mapping on the continental slope. Mar. Geod. 30, 3–35. https://doi.org/10.1080/01490410701295962 (2007).Article 

Google Scholar 
raster: Geographic Data Analysis and Modelling. R package version 3.4–5 (2020).Shelton, A. O., Thorson, J. T., Ward, E. J., Feist, B. E. & Cooper, A. Spatial semiparametric models improve estimates of species abundance and distribution. Can. J. Fish. Aquat. Sci. 71, 1655–1666. https://doi.org/10.1139/cjfas-2013-0508 (2014).CAS 
Article 

Google Scholar 
Dunn, P. K. & Smyth, G. K. Series evaluation of Tweedie exponential dispersion model densities. Statiustics Comput. 15, 267–280 (2005).MathSciNet 
Article 

Google Scholar 
Gu, C. & Wahba, G. Minimizing GCV/GML scores with multiple smoothing parameters via the newton method. SIAM J. Sci. Stat. Comput. 12, 383–398. https://doi.org/10.1137/0912021 (1991).MathSciNet 
Article 
MATH 

Google Scholar 
Hobson, E. S. Feeding behaviour in three species of sharks. Pac. Sci. 17, 171–194 (1963).
Google Scholar 
Weeks, S., Magno-Canto, M., Jaine, F., Brodie, J. & Richardson, A. Unique sequence of events triggers manta ray feeding frenzy in the Southern Great Barrier Reef, Australia. Remote Sens. 7, 3138–3152. https://doi.org/10.3390/rs70303138 (2015).ADS 
Article 

Google Scholar 
Montero-Quintana, A. N., Ocampo-Valdez, C. F., Vázquez-Haikin, J. A., Sosa-Nishizaki, O. & Osorio-Beristain, M. Whale shark (Rhincodon typus) predatory flexible feeding behaviors on schooling fish. J. Ethol. 39, 399–410. https://doi.org/10.1007/s10164-021-00717-y (2021).Article 

Google Scholar 
Findlay, K. P. et al. Humpback whale “super-groups”—A novel low-latitude feeding behaviour of Southern Hemisphere humpback whales (Megaptera novaeangliae) in the Benguela Upwelling System. PLoS ONE 12, e0172002. https://doi.org/10.1371/journal.pone.0172002 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Pirotta, V., Owen, K., Donnelly, D., Brasier, M. J. & Harcourt, R. First evidence of bubble-net feeding and the formation of ‘super-groups’ by the east Australian population of humpback whales during their southward migration. Aquat. Conserv. Mar. Freshwat. Ecosyst. 31, 2412–2419. https://doi.org/10.1002/aqc.3621 (2021).Article 

Google Scholar 
Baines, M., Reichelt, M. & Griffin, D. An autumn aggregation of fin (Balaenoptera physalus) and blue whales (B. musculus) in the Porcupine Seabight, southwest of Ireland. Deep Sea Res. Part II Top. Stud. Oceanogr. 141, 168–177, https://doi.org/10.1016/j.dsr2.2017.03.007 (2017).Ladrón de Guevara P., P., Lavaniegos, B. E. & Heckel, G. Fin whales (Balaenoptera physalus) foraging on daytime surface swarms of the euphausiid Nyctiphanes simplex in Ballenas Channel, Gulf of California, Mexico. J. Mammal. 89, 559–566 (2008).Bruce, W. S. Some observations on Antarctic cetacea. In: Report on the Scientific results of the voyage of S.Y. ‘Scotia’ during the years 1902, 1903, and 1904, under the leadership of William S. Bruce, 491–505 (1915).Mackintosh, N. A. & Wheeler, J. F. G. Southern blue and fin whales. Discov. Rep. I, 257–540 (1929).Jackson, J. A. et al. Have whales returned to a historical hotspot of industrial whaling? The pattern of southern right whale Eubalaena australis recovery at South Georgia. Endang. Spec. Res. 43, 323–339. https://doi.org/10.3354/esr01072 (2020).Article 

Google Scholar 
Goldbogen, J. A., Pyenson, N. D. & Shadwick, R. E. Big gulps require high drag for fin whale lunge feeding. Mar. Ecol. Prog. Ser. 349, 289–301. https://doi.org/10.3354/meps07066 (2007).ADS 
Article 

Google Scholar 
Goldbogen, J. A. et al. Scaling of lunge-feeding performance in rorqual whales: mass-specific energy expenditure increases with body size and progressively limits diving capacity. Funct. Ecol. 26, 216–226. https://doi.org/10.1111/j.1365-2435.2011.01905.x (2012).Article 

Google Scholar 
Acevedo-Gutierrez, A., Croll, D. A. & Tershy, B. R. High feeding costs limit dive time in the largest whales. J Exp Biol 205, 1747–1753. https://doi.org/10.1242/jeb.205.12.1747 (2002).CAS 
Article 
PubMed 

Google Scholar 
Keen, E. M. Aggregative and feeding thresholds of sympatric rorqual whales within a fjord system. Ecosphere 8, e01702. https://doi.org/10.1002/ecs2.1702 (2017).Article 

Google Scholar 
Veit, R. R. & Harrison, N. M. Positive interactions among foraging seabirds, marine mammals and fishes and implications for their conservation. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2017.00121 (2017).Article 

Google Scholar 
Laran, S. et al. A comprehensive survey of pelagic megafauna: their distribution, densities, and taxonomic richness in the tropical Southwest Indian Ocean. Front. Mar. Sci. https://doi.org/10.3389/fmars.2017.00139 (2017).Article 

Google Scholar 
Campbell, G. S. et al. Inter-annual and seasonal trends in cetacean distribution, density and abundance off southern California. Deep Sea Res. Part II Top. Stud. Oceanogr. 112, 143–157. https://doi.org/10.1016/j.dsr2.2014.10.008 (2015).ADS 
Article 

Google Scholar 
Heide-Jørgensen, M. P. et al. Estimates of large whale abundance in West Greenland waters from an aerial survey in 2005. J. Cetac. Res. Manag. 10, 119–129 (2008).
Google Scholar 
Panigada, S. et al. Estimating cetacean density and abundance in the Central and Western Mediterranean Sea through aerial surveys: Implications for management. Deep Sea Res. Part II Top. Stud. Oceanogr. 141, 41–58. https://doi.org/10.1016/j.dsr2.2017.04.018 (2017).ADS 
Article 

Google Scholar 
Forcada, J., Aguilar, A., Hammond, P., Pastor, X. & Aguilar, R. Distribution and abundance of fin whales (Balaenoptera physalus) in the western Mediterranean sea during the summer. J. Zool. 238, 23–34. https://doi.org/10.1111/j.1469-7998.1996.tb05377.x (2009).Article 

Google Scholar 
Clapham, P. J., Aguilar, A. & Hatch, L. T. Determining spatial and temporal scales for management: lessons from whaling. Mar. Mamm. Sci. 24, 183–201. https://doi.org/10.1111/j.1748-7692.2007.00175.x (2008).Article 

Google Scholar 
Baker, C. S. et al. Strong maternal fidelity and natal philopatry shape genetic structure in North Pacific humpback whales. Mar. Ecol. Prog. Ser. 494, 291–306. https://doi.org/10.3354/meps10508 (2013).ADS 
Article 

Google Scholar 
Carroll, E. L. et al. Cultural traditions across a migratory network shape the genetic structure of southern right whales around Australia and New Zealand. Sci. Rep. 5, 16182. https://doi.org/10.1038/srep16182 (2015).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Valenzuela, L. O., Sironi, M., Rowntree, V. J. & Seger, J. Isotopic and genetic evidence for culturally inherited site fidelity to feeding grounds in southern right whales (Eubalaena australis). Mol. Ecol. 18, 782–791. https://doi.org/10.1111/j.1365-294X.2008.04069.x (2009).CAS 
Article 
PubMed 

Google Scholar 
Barendse, J., Best, P. B., Carvalho, I. & Pomilla, C. Mother knows best: occurrence and associations of resighted humpback whales suggest maternally derived fidelity to a Southern Hemisphere coastal feeding ground. PLoS ONE 8, e81238. https://doi.org/10.1371/journal.pone.0081238 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Richard, G. et al. Cultural transmission of fine-scale fidelity to feeding sites may shape humpback whale genetic diversity in Russian Pacific waters. J. Hered. 109, 724–734. https://doi.org/10.1093/jhered/esy033 (2018).CAS 
Article 
PubMed 

Google Scholar 
Carroll, E. L. et al. Reestablishment of former wintering grounds by New Zealand southern right whales. Mar. Mamm. Sci. 30, 206–220. https://doi.org/10.1111/mms.12031 (2014).Article 

Google Scholar 
Calderan, S. V. et al. South Georgia blue whales five decades after the end of whaling. Endang. Spec. Res. 43, 359–373. https://doi.org/10.3354/esr01077 (2020).Article 

Google Scholar 
Santora, J. A. & Veit, R. R. Spatio-temporal persistence of top predator hotspots near the Antarctic Peninsula. Mar. Ecol. Prog. Ser. 487, 287–304. https://doi.org/10.3354/meps10350 (2013).ADS 
Article 

Google Scholar 
Scheidat, M. et al. Cetacean surveys in the Southern Ocean using icebreaker-supported helicopters. Polar Biol. 34, 1513–1522. https://doi.org/10.1007/s00300-011-1010-5 (2011).Article 

Google Scholar 
Williams, R., Hedley, S. L. & Hammond, P. S. Modeling distribution and abundance of Antarctic baleen whales using ships of opportunity. Ecol. Soc. 11, [online] http://www.ecologyandsociety.org/vol11/iss11/art11/ (2006).Secchi, E. et al. Encounter rates of whales around the Antarctic peninsula with special reference to humpback whales, Megaptera novaeangliae, in the Gerlache Strait 1997–98 to 1999–2000. Mem. Qld. Mus. 47, 571–578 (2001).
Google Scholar 
Thiele, D. et al. Seasonal variability in whale encounters in the Western Antarctic Peninsula. Deep Sea Res. Part II Top. Stud. Oceanogr. 51, 2311–2325. https://doi.org/10.1016/j.dsr2.2004.07.007 (2004).ADS 
Article 

Google Scholar 
Johnston, D. W., Friedlaender, A. S., Read, A. J. & Nowacek, D. P. Initial density estimates of humpback whales Megaptera novaeangliae in the inshore waters of the western Antarctic Peninsula during the late autumn. Endang. Spec. Res. 18, 63–71. https://doi.org/10.3354/esr00395 (2012).Article 

Google Scholar 
Zerbini, A. N. et al. Assessing the recovery of an Antarctic predator from historical exploitation. R Soc Open Sci 6, 190368. https://doi.org/10.1098/rsos.190368 (2019).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Mackintosh, N. A. The distribution of southern blue and fin whales, in Whales, dolphins, and porpoises. (ed K. S. Norris) Ch. 8, 125–144 (University of California Press, 1966).Schmitt, N. et al. Mixed-stock analysis of humpback whales (Megaptera novaeangliae) on Antarctic feeding grounds. J. Cetac. Res. Manag. 14, 141–157 (2014).
Google Scholar 
Schall, E. et al. Humpback whale song recordings suggest common feeding ground occupation by multiple populations. Sci. Rep. 11, 18806. https://doi.org/10.1038/s41598-021-98295-z (2021).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Archer, F. I. et al. Revision of fin whale Balaenoptera physalus (Linnaeus, 1758) subspecies using genetics. J. Mammal. 100, 1653–1670. https://doi.org/10.1093/jmammal/gyz121 (2019).Article 

Google Scholar 
Archer, F. I. et al. Mitogenomic phylogenetics of fin whales (Balaenoptera physalus spp.): Genetic evidence for revision of subspecies. PLoS ONE 8, e63396. https://doi.org/10.1371/journal.pone.0063396 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Cabrera, A. A. et al. Fin whale (Balaenoptera physalus) mitogenomics: A cautionary tale of defining sub-species from mitochondrial sequence monophyly. Mol. Phylogenet. Evol. 135, 86–97. https://doi.org/10.1016/j.ympev.2019.02.003 (2019).Article 
PubMed 

Google Scholar 
Edwards, E. F., Hall, C., Moore, T. J., Sheredy, C. & Redfern, J. V. Global distribution of fin whales Balaenoptera physalus in the post-whaling era (1980–2012). Mammal. Rev. 45, 197–214. https://doi.org/10.1111/mam.12048 (2015).Article 

Google Scholar 
Knox, G. A. The key role of krill in the ecosystem of the Southern Ocean with special reference to the Convention on the Conservation of Antarctic Marine Living Resources. Ocean Manag. 9, 113–156 (1984).Article 

Google Scholar 
Ducklow, H. W. et al. Marine pelagic ecosystems: the west Antarctic Peninsula. Philos. Trans. R. Soc. Lond. B Biol. Sci. 362, 67–94. https://doi.org/10.1098/rstb.2006.1955 (2007).Article 
PubMed 

Google Scholar 
Atkinson, A. et al. Krill (Euphausia superba) distribution contracts southward during rapid regional warming. Nat. Clim. Change 9, 142–147. https://doi.org/10.1038/s41558-018-0370-z (2019).ADS 
Article 

Google Scholar 
Benton, M. J., Tverdokhlebov, V. P. & Surkov, M. V. Ecosystem remodelling among vertebrates at the Permian-Triassic boundary in Russia. Nature 432, 97–100. https://doi.org/10.1038/nature02950 (2004).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Siegel, V., Reiss, C. S., Dietrich, K. S., Haraldsson, M. & Rohardt, G. Distribution and abundance of Antarctic krill (Euphausia superba) along the Antarctic Peninsula. Deep Sea Res. Part I Oceanogr. Res. Pap. 77, 63–74. https://doi.org/10.1016/j.dsr.2013.02.005 (2013).ADS 
Article 

Google Scholar 
Siegel, V. & Watkins, L. Distribution, Biomass and Demography of Antarctic Krill, Euphausia superba, in Biology and Ecology of Antarctic Krill Advances in Polar Ecology (ed Volker Siegel) Ch. 2, 21–101 (Springer, 2016).Roman, J. et al. Whales as marine ecosystem engineers. Front. Ecol. Environ. 12, 377–385. https://doi.org/10.1890/130220 (2014).Article 

Google Scholar 
Savoca, M. S. et al. Baleen whale prey consumption based on high-resolution foraging measurements. Nature 599, 85–90. https://doi.org/10.1038/s41586-021-03991-5 (2021).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Atkinson, A., Siegel, V., Pakhomov, E. A., Jessopp, M. J. & Loeb, V. A re-appraisal of the total biomass and annual production of Antarctic krill. Deep Sea Res. Part I Oceangr. Res. Pap. 56, 727–740. https://doi.org/10.1016/j.dsr.2008.12.007 (2009).ADS 
Article 

Google Scholar 
Nicol, S. et al. Southern Ocean iron fertilization by baleen whales and Antarctic krill. Fish Fish. 11, 203–209. https://doi.org/10.1111/j.1467-2979.2010.00356.x (2010).Article 

Google Scholar 
Lavery, T. J. et al. Whales sustain fisheries: Blue whales stimulate primary production in the Southern Ocean. Mar. Mamm. Sci. 30, 888–904. https://doi.org/10.1111/mms.12108 (2014).CAS 
Article 

Google Scholar 
Smetacek, V. Are declining Antarctic krill stocks a result of global warming or of the decimation of the whales? in Effects of global warming on polar ecosystems (ed Carlos M. Duarte) (Fundación BBVA, 2008).Roman, J. & McCarthy, J. J. The whale pump: marine mammals enhance primary productivity in a coastal basin. PLoS ONE 5, e13255. https://doi.org/10.1371/journal.pone.0013255 (2010).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Smetacek, V. A whale of an appetite revealed by analysis of prey consumption. Nature 599, 33–34. https://doi.org/10.1038/d41586-021-02951-3 (2021).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Laws, R. M. Seals and whales of the Southern Ocean. Philios. Trans. R. Soc. Lond. B 279, 81–96 (1977).ADS 
Article 

Google Scholar 
Lavery, T. J. et al. Iron defecation by sperm whales stimulates carbon export in the Southern Ocean. Proc. Biol. Sci. 277, 3527–3531. https://doi.org/10.1098/rspb.2010.0863 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Cunningham, S. A. Transport and variability of the Antarctic Circumpolar Current in Drake Passage. J. Geophys. Res. https://doi.org/10.1029/2001jc001147 (2003).Article 

Google Scholar 
Frölicher, T. L. et al. Dominance of the Southern Ocean in Anthropogenic Carbon and Heat Uptake in CMIP5 Models. J. Clim. 28, 862–886. https://doi.org/10.1175/jcli-d-14-00117.1 (2015).ADS 
Article 

Google Scholar 
Landschutzer, P. et al. The reinvigoration of the Southern Ocean carbon sink. Science 349, 1221–1224. https://doi.org/10.1126/science.aab2620 (2015).ADS 
CAS 
Article 
PubMed 

Google Scholar  More

Díaz, S. et al. Set ambitious goals for biodiversity and sustainability. Science 370, 411–413 (2020).PubMed 
Article 

Google Scholar 
Sutherland, W. J. & Woodroof, H. J. The need for environmental horizon scanning. Trends Ecol. Evol. 24, 523–527 (2009).PubMed 
Article 

Google Scholar 
Sutherland, W. J. et al. Ten years on: a review of the first global conservation horizon scan. Trends Ecol. Evol. 34, 139–153 (2019).PubMed 
Article 

Google Scholar 
Sutherland, W. J. et al. A horizon scan of global conservation issues for 2010. Trends Ecol. Evol. 25, 1–7 (2010).PubMed 
Article 

Google Scholar 
Sutherland, W. J. et al. A horizon scan of global conservation issues for 2016. Trends Ecol. Evol. 31, 44–53 (2016).PubMed 
Article 

Google Scholar 
Sutherland, W. J. et al. A horizon scanning assessment of current and potential future threats facing migratory shorebirds. Ibis 154, 663–679 (2012).Article 

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

Google Scholar 
Tang, W. et al. Widespread phytoplankton blooms triggered by 2019–2020 Australian wildfires. Nature 597, 370–375 (2021).CAS 
PubMed 
Article 

Google Scholar 
Silva, L. G. M. et al. Mortality events resulting from Australia’s catastrophic fires threaten aquatic biota. Glob. Change Biol. 26, 5345–5350 (2020).Article 

Google Scholar 
Abram, N. J., Gagan, M. K., McCulloch, M. T., Chappell, J. & Hantoro, W. S. Coral reef death during the 1997 Indian Ocean Dipole linked to Indonesian wildfires. Science 301, 952–955 (2003).CAS 
PubMed 
Article 

Google Scholar 
Solomon, C. T. et al. Ecosystem consequences of changing inputs of terrestrial dissolved organic matter to lakes: current knowledge and future challenges. Ecosystems 18, 376–389 (2015).Article 

Google Scholar 
Sully, S. & van Woesik, R. Turbid reefs moderate coral bleaching under climate related temperature stress. Glob. Change Biol. 26, 1367–1373 (2021).Article 

Google Scholar 
Blain, C. O., Hansen, S. C. & Shears, N. T. Coastal darkening substantially limits the contribution of kelp to coastal carbon cycles. Glob. Change Biol. 27, 5547–5563 (2021).Article 

Google Scholar 
Stewart, B. D. et al. Metal pollution as a potential threat to shell strength and survival in marine bivalves. Sci. Total Environ. 755, 143019 (2021).CAS 
PubMed 
Article 

Google Scholar 
Roberts, D. A. et al. Ocean acidification increases the toxicity of contaminated sediments. Glob. Change Biol. 19, 340–351 (2013).Article 

Google Scholar 
Hauton, C. et al. Identifying toxic impact of metals potentially released during deep-sea mining—a synthesis of the challenges to quantifying risk. Front. Mar. Sci. 4, 368 (2017).Chaudhary, C. et al. Global warming is causing a more pronounced dip in marine species richness around the equator. Proc. Natl Acad. Sci. USA 118, e2015094118 (2021).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Burrows, M. T. et al. Geographical limits to species-range shifts are suggested by climate velocity. Nature 507, 492–495 (2014).CAS 
PubMed 
Article 

Google Scholar 
Yasuhara, M. et al. Past and future decline of tropical pelagic biodiversity. Proc. Natl Acad. Sci. USA 117, 12891–12896 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Pandolfi, J. M. et al. Are U.S. coral reefs on the slippery slope to slime? Science 307, 1725–1726 (2005).CAS 
PubMed 
Article 

Google Scholar 
Hixson, S. M. & Arts, M. T. Climate warming is predicted to reduce omega-3, long-chain, polyunsaturated fatty acid production in phytoplankton. Glob. Change Biol. 22, 2744–2755 (2016).Article 

Google Scholar 
Hicks, C. C. et al. Harnessing global fisheries to tackle micronutrient deficiencies. Nature 574, 95–98 (2019).CAS 
PubMed 
Article 

Google Scholar 
Colombo, S. M. et al. Projected declines in global DHA availability for human consumption as a result of global warming. Ambio 49, 865–880 (2020).CAS 
PubMed 
Article 

Google Scholar 
Lam, V. W. et al. Climate change, tropical fisheries and prospects for sustainable development. Nat. Rev. Earth Environ. 1, 440–454 (2020).Article 

Google Scholar 
Antacli, J. C. et al. Increase in unsaturated fatty acids in Antarctic phytoplankton under ocean warming and glacial melting scenarios. Sci. Total Environ. 790, 147879 (2021).CAS 
PubMed 
Article 

Google Scholar 
Maire, E. et al. Micronutrient supply from global marine fisheries under climate change and overfishing. Curr. Biol. 18, 4132–4138 (2021).Article 
CAS 

Google Scholar 
Lim, Y. S., Ok, Y. J., Hwang, S. Y., Kwak, J. Y. & Yoon, S. Marine collagen as a promising biomaterial for biomedical applications. Mar. Drugs 17, 467 (2019).CAS 
PubMed Central 
Article 

Google Scholar 
Xu, N. et al. Marine-derived collagen as biomaterials for human health. Front. Nutr. 8, 702108 (2021).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Vieira, H., Leal, M. C. & Calado, R. Fifty shades of blue: how blue biotechnology is shaping the bioeconomy. Trends Biotechnol. 38, 940–943 (2020).CAS 
PubMed 
Article 

Google Scholar 
Ben-Hasan, A. et al. China’s fish maw demand and its implications for fisheries in source countries. Mar. Policy 132, 104696 (2021).Article 

Google Scholar 
Sadovy de Mitcheson, Y., To, A. W. L., Wong, N. W., Kwan, H. Y. & Bud, W. S. Emerging from the murk: threats, challenges and opportunities for the global swim bladder trade. Rev. Fish. Biol. Fish. 29, 809–835 (2019).Article 

Google Scholar 
Brownell, R. L. Jr et al. Bycatch in gillnet fisheries threatens critically endangered small cetaceans and other aquatic megafauna. Endang. Species Res. 40, 285–296 (2019).Article 

Google Scholar 
Webb, T. J., Vanden Berghe, E. & O’Dor, R. K. Biodiversity’s big wet secret: the global distribution of marine biological records reveals chronic under-exploration of the deep pelagic ocean. PLoS ONE 5, e10223 (2010).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
St. John, M. A. et al. A dark hole in our understanding of marine ecosystems and their services: perspectives from the mesopelagic community. Front. Mar. Sci. 3, 31 (2016).
Google Scholar 
Thomsen, L. et al. The oceanic biological pump: rapid carbon transfer to depth at continental margins during winter. Sci. Rep. 7, 10763 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Roberts, C. M., Hawkins, J. P., Hindle, K., Wilson, R. W. & O’Leary, B. C. Entering the Twilight Zone: The Ecological Role and Importance of Mesopelagic Fishes (Blue Marine Foundation, 2020)Cavan, E. L., Laurenceau-Cornec, E. C., Bressac, M. & Boyd, P. W. Exploring the ecology of the mesopelagic biological pump. Prog. Oceanogr. 176, 102125 (2019).Article 

Google Scholar 
Levin, L. A. et al. Climate change considerations are fundamental to management of deep‐sea resource extraction. Glob. Change Biol. 26, 4664–4678 (2020).Article 

Google Scholar 
Li, Z. et al. Continuous electrical pumping membrane process for seawater lithium mining. Energy Environ. Sci. 14, 3152–3159 (2021).CAS 
Article 

Google Scholar 
Jin, M., Gai, Y., Guo, X., Hou, Y. & Zeng, R. Properties and applications of extremozymes from deep-sea extremophilic microorganisms: a mini review. Mar. Drugs 17, 656 (2019).CAS 
PubMed Central 
Article 

Google Scholar 
Mbow, C. et al. in IPCC Special Report on Climate Change and Land (eds Shukla, P.R. et al.) 437–550 (IPCC, 2019).Christie, N., Smyth, K., Barnes, R. & Elliott, M. Co-location of activities and designations: a means of solving or creating problems in marine spatial planning? Mar. Pol. 43, 254–261 (2014).Article 

Google Scholar 
Mayer-Pinto, M., Dafforn, K. A. & Johnston, E. L. A decision framework for coastal infrastructure to optimize biotic resistance and resilience in a changing climate. BioScience 69, 833–843 (2019).Article 

Google Scholar 
Wang, C. M. & Wang, B. T. in ICSCEA 2019 (eds Reddy, J. N. et al.) 3–29 (Springer, 2020).Ross, C. T. F. & McCullough, R. R. Conceptual design of a floating island city. J. Ocean Technol. 5, 120–121 (2010).
Google Scholar 
Dong, Y.-w, Huang, X.-w, Wang, W., Li, Y. & Wang, J. The marine ‘great wall’ of China: local- and broad-scale ecological impacts of coastal infrastructure on intertidal macrobenthic communities. Divers. Distrib. 22, 731–744 (2016).Article 

Google Scholar 
Flikkema, M. M. B., Lin, F.-Y., van der Plank, P. P. J., Koning, J. & Waals, O. Legal issues for artificial floating islands. Front. Mar. Sci. 8, 619462 (2021).Article 

Google Scholar 
Richir, J., Bray, S., McAleese, T. & Watson, G. J. Three decades of trace element sediment contamination: the mining of governmental databases and the need to address hidden sources for clean and healthy seas. Environ. Int. 149, 106362 (2021).CAS 
PubMed 
Article 

Google Scholar 
Zhao, Y. et al. A review on battery market trends, second-life reuse, and recycling. Sustain. Chem. 2, 167–205 (2021).CAS 
Article 

Google Scholar 
Li, W., Lee, S. & Manthiram, A. High‐Nickel NMA: a cobalt‐free alternative to NMC and NCA cathodes for lithium‐ion batteries. Adv. Mater. 32, 2002718 (2020).CAS 
Article 

Google Scholar 
Ghaffarivardavagh, R., Afzal, S. S., Rodriguez, O. & Adib, F. in SIGCOMM ’20 Proc. 19th ACM Workshop on Hot Topics in Networks 125–131 (Association for Computing Machinery, 2020).Hazen, E. L. et al. Ontogeny in marine tagging and tracking science: technologies and data gaps. Mar. Ecol. Prog. Ser. 457, 221–240 (2012).Article 

Google Scholar 
Davies, T. E. et al. Tracking data and the conservation of the high seas: opportunities and challenges. J. Appl. Ecol. 58, 2703–2710 (2021).Aracri, S. et al. Soft robots for ocean exploration and offshore operations: a perspective. Soft Robot. https://doi.org/10.1089/soro.2020.0011 (2021).Li, G. et al. Self-powered soft robot in the Mariana Trench. Nature 591, 66–71 (2021).CAS 
PubMed 
Article 

Google Scholar 
Philamore, H., Ieropoulos, I., Stinchcombe, A. & Rossiter, J. Toward energetically autonomous foraging soft robots. Soft Robot. 3, 186–197 (2016).Article 

Google Scholar 
Manfra, L. et al. Biodegradable polymers: a real opportunity to solve marine plastic pollution? J. Hazard. Mater. 416, 125763 (2021).CAS 
PubMed 
Article 

Google Scholar 
Kim, D., Kim, H. & An, Y. J. Effects of synthetic and natural microfibers on Daphnia magna: are they dependent on microfiber type? Aquat. Toxicol. 240, 105968 (2021).CAS 
PubMed 
Article 

Google Scholar 
Degli-Innocenti, F., Bellia, G., Tosin, M., Kapanen, A. & Itävaara, M. Detection of toxicity released by biodegradable plastics after composting in activated vermiculite. Polym. Degrad. Stab. 73, 101–106 (2001).CAS 
Article 

Google Scholar 
Macreadie, P. I. et al. The future of blue carbon science. Nat. Commun. 10, 3998 (2019).Short, R. E. et al. Harnessing the diversity of small-scale actors is key to the future of aquatic food systems. Nat. Food 2, 733–741 (2021).Article 

Google Scholar 
Watson, J. E. M. et al. Set a global target for ecosystems. Nature 578, 360–362 (2020).CAS 
PubMed 
Article 

Google Scholar 
Obura, D. O. et al. Integrate biodiversity targets from local to global levels. Science 373, 746 (2021).CAS 
PubMed 
Article 

Google Scholar 
Barnes, M. D., Glew, L., Wyborn, C. & Craigie, I. D. Prevent perverse outcomes from global protected area policy. Nat. Ecol. Evol. 2, 759–762 (2018).PubMed 
Article 

Google Scholar 
Grorud-Colvert, K. et al. The MPA Guide: a framework to achieve global goals for the ocean. Science 373, eabf0861 (2021).CAS 
PubMed 
Article 

Google Scholar 
Jefferson, R. L., McKinley, E., Griffin, H., Nimmo, A. & Fletcher, S. Public perceptions of the ocean: lessons for marine conservation from a global research review. Front. Mar. Sci. 8, 711245 (2021).Potts, T., Pita, C., O’Higgins, T. & Mee, L. Who cares? European attitudes towards marine and coastal environments. Mar. Pol. 72, 59–66 (2016).Article 

Google Scholar 
Bennett, N. J. et al. Towards a sustainable and equitable blue economy. Nat. Sustain. 2, 991–993 (2019).Article 

Google Scholar 
Jouffray, J.-B., Blasiak, R., Norström, A. V., Österblom, H. & Nyström, M. The blue acceleration: the trajectory of human expansion into the ocean. One Earth 2, 43–54 (2020).Article 

Google Scholar 
Zheng, Y. & Walsham, G. Inequality of what? An intersectional approach to digital inequality under Covid-19. Inf. Organ. 31, 100341 (2021).Article 

Google Scholar 
Blythe, J. L., Armitage, D., Bennett, N. J., Silver, J. J. & Song, A. M. The politics of ocean governance transformations. Front. Mar. Sci. 8, 634718 (2021).Article 

Google Scholar 
Brennan, C., Ashley, M. & Molloy, O. A system dynamics approach to increasing ocean literacy. Front. Mar. Sci. 6, 360 (2019).Article 

Google Scholar 
Stoll-Kleemann, S. Feasible options for behavior change toward more effective ocean literacy: a systematic review. Front. Mar. Sci. 6, 273 (2019).Article 

Google Scholar 
Bennett, N. J. et al. Advancing social equity in and through marine conservation. Front. Mar. Sci. 8, 711538 (2021).Article 

Google Scholar 
Short, R. E. et al. Review of the evidence for oceans and human health relationships in Europe: a systematic map. Environ. Int. 146, 106275 (2021).PubMed 
Article 

Google Scholar 
Mukherjee, N. et al. The Delphi technique in ecology and biological conservation: applications and guidelines. Methods Ecol. Evol. 6, 1097–1109 (2015).Article 

Google Scholar 
Sutherland, W. J. et al. A 2021 horizon scan of emerging global biological conservation issues. Trends Ecol. Evol. 36, 87–97 (2021).PubMed 
Article 

Google Scholar  More

Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
Provided by the Springer Nature SharedIt content-sharing initiative More

Data collectionThe present dataset was collected within the framework of the Atlantic Lobster Moult and Quality (ALMQ) project originally managed and implemented by the Atlantic Veterinary College Lobster Science Centre at the University of Prince Edward Island in collaboration with the Fishermen and Scientists Research Society. The Atlantic Lobster Moult and Quality project was initially funded through the Atlantic Innovation Fund program from the Atlantic Canada Opportunities Agency (ACOA) and transferred to the Fishermen and Scientists Research Society (FSRS) in 2012.Sampling took place every 2–3 weeks in eight lobster fishing areas (LFA) in Atlantic Canada from 2004 to 2014 (see Fig. 1, Table 1). The sampling followed the FSRS Lobster Moult and Quality sampling protocol and was conducted by technicians from the Atlantic Veterinary College and the Fishermen and Scientists Research Society in fixed locations from traps set the day before2. Locations based on targeted sampling (LFA 33 and 34) were chosen according to the fishing efforts in the respective areas and selected by a lobster science committee consisting of members from industry, academia, research and federal and provincial representatives. Other locations (LFA 24, 25, 26A, 35) were chosen based on proximity to the Atlantic Veterinary College and other projects with commercial fishers which allowed sampling.Table 1 Overview of sampling locations, surface areas (km2) and number of lobsters (N) sampled for the Atlantic Lobster Moult and Quality Project by AVC Lobster Science Centre from 2004–2015 in Atlantic Canada. (PEI = Prince Edward Island, NS = Nova Scotia).Full size tableFig. 1(a) Map of the lobster fishing areas (LFAs) in the Maritime Provinces in eastern Canada with the sampling locations (red) recorded by the AVC Lobster Science Centre for the Atlantic Lobster Moult and Quality project. (b) Enlarged map of LFA 33. (c) Enlarged map of LFAs on Prince Edward Island. The maps were created using QGIS (v. 3.18; https://qgis.org). Contours depict water depths in meters.Full size imageFor each sampling event, 40 commercial lobster traps with escape vents for lobsters below the minimum legal size were used. Legal sizes depend on size-at-maturity (size at which 50% of the population reach maturity) which differs between LFAs due to regional differences in water temperature that influence lobster growth. There were some differences in sampling procedure between lobster fishing season and off-season. During lobster fishing season sampling took place within 48 h post landing and only legal-sized lobsters were assessed. During off season, lobsters were sampled directly on board chartered boats and were returned to sea immediately after sampling. During non-fishing season sampling, lobsters below minimum legal size were also sampled but no egg-bearing females were targeted to minimize negative handling effects. Targeted sample size was 200 lobsters per sampling event before 2009 and 125 lobsters after 2009 due to budget constraints.On average, 3–4 lobsters of each sex were sampled in every 2 mm lobster size grouping. Lobster size was recorded as the carapace length in mm and determined using calipers rounding down to the nearest mm. The size distribution of sampled lobsters is presented in Fig. 2. Lobsters were assessed for general health (lesions, shell damage, liveliness/vigour) and shell hardness. Shell hardness was recorded as soft, medium or hard. A carapace of a soft-shelled lobster would be compressible at the ventral and dorsal (anterior and posterior) carapace, a medium-shelled lobster would only be compressible at the ventral carapace and a hard-shelled lobster would not be compressible at any carapace location.Fig. 2Lobster size (as carapace length in mm) distribution for all lobsters sampled during the sampling period (15 missing values).Full size imageTo estimate hemolymph protein levels, the ventral abdomen between the first pair of walking legs was sprayed with 70% ethanol and 3 ml of hemolymph were extracted with a 22 gauge needle and a 3 ml syringe. A few drops of hemolymph were placed on a handheld refractometer and the refractive index (“°Brix” value) was recorded and used as a proxy for total hemolymph levels. The distribution of hemolymph protein level is shown in Fig. 3. The moult stages were determined by pleopod stages under a stereomicroscope and recorded in pleopod stages (see Table 2). The stage determinations are shown in Table 2 and Fig. 46.Fig. 3Distribution of hemolymph protein level (measured in °Brix) for all lobsters sampled in the dataset (892 missing values).Full size imageTable 2 Description of premoult stages and pleopod stages in adult American lobster based on Aiken6. C: Intermoult, D: Premoult.Full size tableFig. 4Pleopod stages of lobsters at different times in their moult cycle. Illustrations by Lavallée et al.2.Full size imageIn total, 141,659 lobsters were sampled from 2004–2015 over 1,195 sampling events. Data were recorded manually on data sheets and re-checked before being entered into an Excel data sheet (Excel, Microsoft). More

Phycosphere pH of single phytoplankton cellsThe pH in the phycosphere of a single cell Chlamydomonas concordia (~5 µm diameter) exposed to 140 μmol photons m−2 s−1 was 8.27 ± 0.01 (179 measurements), while the pH of bulk seawater was 8.01 ± 0.01 (160 measurements) (Fig. 1c). The observed pH variation near the cell surface was 150 µmol m−2 s−1 [33]. At light intensities More