Ecology

Although Malar et al. “do not exclude the possibility that the genes identified by Mateus et al. are involved in mating,” they qualify the homology inference between genes differentially expressed in the co-inoculation treatment and genes involved in mating in other fungal species as “spurious evolutionary relationships” or “not the best ortholog”. Those statements imply that they attach no importance to the demonstrated sequence homology relationships identified in Mateus et al. Orthology does not necessarily imply conservation of gene function and genes with equivalent functions are not necessarily orthologs [3]. Therefore, it is misleading to assume that two genes have the same function when interpreting the role of a “best candidate ortholog” identified in silico. Moreover, relying only on an in silico search for exploring orthologs can lead to serious problems for inferring function as none of the search algorithms are free from bias if subfunctionalization or neofunctionalization events occurred among the homologs.Malar et al. have not considered, or have misunderstood, the experimental evidence on gene expression in interpreting their homology search. It is not surprising that their “best homologs” were not upregulated, because we already saw that those genes were not upregulated in the original dataset. Our approach comprised performing an experiment to identify genes that were specifically upregulated when two isolates coexisted in planta. We then identified their putative function by homology. We did not look at whether the genes were the closest orthologs. However, we discussed the limitations of an homology approach to identify gene function [2]. To our surprise, a consistent set of 20 genes was upregulated in the co-inoculation treatment in different host plants, and 9 of these 20 (upregulated in more than one host plant) shared the common feature of homology to genes involved in different steps of mating in other fungal species (Figs. 3 and 4 of Mateus et al.).Malar et al. claim the identification of hundreds of hits of the 18 genes differentially expressed in Mateus et al. “against the high-quality protein databases from the JGI Mycocosm Rhiir2” (referring to the protein database “Rhiir2” of R. irregularis). In fact, Malar et al. compared the 18 genes against “all protein gene catalogs of fungal species from the JGI fungal genomic resource” comprising 1318 taxa. The interpretation of the number of hits on a such large dataset is misleading because if a gene is highly conserved across the fungal kingdom, we would expect hundreds of hits in this database. In contrast, if an R. irregularis gene is highly specific to the Glomeromycotina taxa, we would expect very few hits (because there are less Glomeromycotina genomes in the database). Consequently, the number of hits in Table 1 from Malar et al. reflect the size of the database used and how conserved a given gene is, rather than whether a gene is from a large gene family. Malar et al. identified the so-called “closest ortholog” in R. irregularis of fungal mating genes from other fungal species by showing the “best hit” using OrthoMCL. However, differentiating paralogs from orthologs is a complicated task, in very distant species, especially if the organisms are highly paralogous. A more cautious analysis for each gene, including a confirmation that they are located in similar genomic locations, would lend more certitude that a given gene could be an ortholog. Consequently, the evaluation of RNA expression of their “best hit” remains incomplete in terms of the effort to find the best orthologs. More

1.Medic, G., Wille, M. & Hemels, M. Short- and long-term health consequences of sleep disruption. Nat. Sci. Sleep 9, 151–161 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
2.Randazzo, A. C., Muehlbach, M. J., Schweitzer, P. K. & Walsh, J. K. Cognitive function following acute sleep restriction in children ages 10–14. Sleep 21, 861–868 (1998).CAS 
PubMed 
PubMed Central 

Google Scholar 
3.Stickgold, R. Sleep-dependent memory consolidation. Nature 437, 1272–1278 (2005).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
4.Tononi, G. & Cirelli, C. Sleep and the price of plasticity: From synaptic and cellular homeostasis to memory consolidation and integration. Neuron 81, 12–34 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
5.Marshall, L. & Born, J. The contribution of sleep to hippocampus-dependent memory consolidation. Trends Cogn. Sci. 11, 442–450 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
6.Smith, C. Sleep states and memory processes in humans: Procedural versus declarative memory systems. Sleep Med. Rev. 5, 491–506 (2001).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
7.Johnston, T. D. In Selective Costs and Benefits in the Evolution of Learning. in Advances in the Study of Behavior (eds. Rosenblatt, J. S. et al.) 12, 65–106 (Academic Press, 1982).8.Hendricks, J. C. et al. Rest in Drosophila is a sleep-like state. Neuron 25, 129–138 (2000).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Campbell, S. S. & Tobler, I. Animal sleep: A review of sleep duration across phylogeny. Neurosci. Biobehav. Rev. 8, 269–300 (1984).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Shaw, P. J. Correlates of sleep and waking in Drosophila melanogaster. Science (80-). 287, 1834–1837 (2000).ADS 
CAS 
Article 

Google Scholar 
11.Hamblen, M. et al. Germ-line transformation involving DNA from the period locus in Drosophila melanogaster: Overlapping genomic fragments that restore circadian and ultradian rhythmicity to per 0 and per—mutants. J. Neurogenet. 3, 249–291 (1986).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
12.Kirszenblat, L. & van Swinderen, B. Sleep in Drosophila. In Handbook of Sleep Research, Vol. 30 (ed. Dringenberg, H. C.) 333–347 (Elsevier, 2019).13.Ly, S., Pack, A. I. & Naidoo, N. The neurobiological basis of sleep: Insights from Drosophila. Neurosci. Biobehav. Rev. 87, 67–86 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
14.Helfrich-Förster, C. Sleep in insects. Annu. Rev. Entomol. 63, 69–86 (2018).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
15.Le Glou, E., Seugnet, L., Shaw, P. J., Preat, T. & Goguel, V. Circadian modulation of consolidated memory retrieval following sleep deprivation in Drosophila. Sleep 35, 1377–1384 (2012).PubMed 
PubMed Central 
Article 

Google Scholar 
16.Li, X., Yu, F. & Guo, A. Sleep deprivation specifically impairs short-term olfactory memory in Drosophila. Sleep 32, 1417–1424 (2009).PubMed 
PubMed Central 
Article 

Google Scholar 
17.Rihel, J. & Bendor, D. Flies sleep on it, or Fuhgeddaboudit!. Cell 161, 1498–1500 (2015).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
18.Geissmann, Q., Beckwith, E. J. & Gilestro, G. F. Most sleep does not serve a vital function: Evidence from Drosophila melanogaster. Sci. Adv. 5, eaau8253 (2019).Article 
CAS 

Google Scholar 
19.Tougeron, K. & Abram, P. K. An ecological perspective on sleep disruption. Am. Nat. 190, E55–E66 (2017).PubMed 
Article 
PubMed Central 

Google Scholar 
20.Aulsebrook, A. E., Jones, T. M., Rattenborg, N. C., Roth, T. C. & Lesku, J. A. Sleep ecophysiology: Integrating neuroscience and ecology. Trends Ecol. Evol. 31, 590–599 (2016).PubMed 
Article 
PubMed Central 

Google Scholar 
21.Markow, T. A. Host use and host shifts in Drosophila. Curr. Opin. Insect Sci. 31, 139–145 (2019).PubMed 
Article 
PubMed Central 

Google Scholar 
22.Badel, L., Ohta, K., Tsuchimoto, Y. & Kazama, H. Decoding of context-dependent olfactory behavior in Drosophila. Neuron 91, 155–167 (2016).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
23.Knaden, M., Strutz, A., Ahsan, J., Sachse, S. & Hansson, B. S. Spatial representation of odorant valence in an insect brain. Cell Rep. 1, 392–399 (2012).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
24.Hopkins, A. A discussion of C.G. Hewitt’s paper on ‘Insect Behavior’. J. Econ. Entomol. 10, 92–93 (1917).
Google Scholar 
25.Davis, J. M. & Stamps, J. A. The effect of natal experience on habitat preferences. Trends Ecol. Evol. 19, 411–416 (2004).PubMed 
Article 
PubMed Central 

Google Scholar 
26.Barron, A. B. The life and death of Hopkins’ host selection principle. J. Insect Behav. 14, 725–737 (2001).Article 

Google Scholar 
27.van Emden, H. F. et al. Plant chemistry and aphid parasitoids (Hymenoptera: Braconidae): Imprinting and memory. Eur. J. Entomol. 105, 477–483 (2008).Article 

Google Scholar 
28.Liu, S. S., Li, Y. H., Liu, Y. Q. & Zalucki, M. P. Experience-induced preference for oviposition repellents derived from a non-host plant by a specialist herbivore. Ecol. Lett. 8, 722–729 (2005).Article 

Google Scholar 
29.Hamilton, C. E., Beresford, D. V. & Sutcliffe, J. F. Effects of natal habitat odour, reinforced by adult experience, on choice of oviposition site in the mosquito Aedes aegypti. Med. Vet. Entomol. 25, 428–435 (2011).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
30.Turlings, T. C. L., Wackers, F. L., Vet, L. E. M., Lewis, W. J. & Tumlinson, J. H. Learning of Host-Finding Cues by Hymenopterous parasitoids. In Insect Learning (eds. Papaj, D. R. & Lewis, W. J.) 51–78 (Springer US, 1993). https://doi.org/10.1007/978-1-4615-2814-2_331.Jaenike, J. Induction of host preference in Drosophila melanogaster. Oecologia 58, 320–325 (1983).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
32.Takemoto, H., Powell, W., Pickett, J., Kainoh, Y. & Takabayashi, J. Two-step learning involved in acquiring olfactory preferences for plant volatiles by parasitic wasps. Anim. Behav. 83, 1491–1496 (2012).Article 

Google Scholar 
33.Andretic, R. & Shaw, P. J. Essentials of sleep recordings in Drosophila: Moving beyond sleep time. Methods Enzymol. 393, 759–772 (2005).PubMed 
Article 
PubMed Central 

Google Scholar 
34.Garbe, D. S. et al. Context-specific comparison of sleep acquisition systems in Drosophila. Biol. Open 4, 1558–1568 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
35.Faraway, J. J. Extending the Linear Model with R (CRC Press, 2016). https://doi.org/10.1201/b21296.Book 
MATH 

Google Scholar 
36.Ho, K. S. & Sehgal, A. Drosophila melanogaster: An insect model for fundamental studies of sleep. Methods Enzymol. 393, 1834–1837 (2005).
Google Scholar 
37.Greenspan, R. J., Tononi, G., Cirelli, C. & Shaw, P. J. Sleep and the fruit fly. Trends Neurosci. 24, 142–145 (2001).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
38.Killgore, W. D. S. Sleep deprivation and behavioral risk-taking. In Modulation of Sleep by Obesity, Diabetes, Age, and Diet 279–287 (Elsevier, 2015). https://doi.org/10.1016/B978-0-12-420168-2.00030-2.39.Revadi, S. et al. Olfactory responses of Drosophila suzukii females to host plant volatiles. Physiol. Entomol. 40, 54–64 (2015).CAS 
Article 

Google Scholar 
40.Cirelli, C. & Tononi, G. Is sleep essential?. PLoS Biol. 6, 1605–1611 (2008).CAS 
Article 

Google Scholar 
41.Bateson, M., Desire, S., Gartside, S. E. & Wright, G. A. Agitated honeybees exhibit pessimistic cognitive biases. Curr. Biol. 21, 1070–1073 (2011).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
42.Wilkin, M. M., Waters, P., McCormick, C. M. & Menard, J. L. Intermittent physical stress during early- and mid-adolescence differentially alters rats’ anxiety- and depression-like behaviors in adulthood. Behav. Neurosci. 126, 344–360 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
43.Chaumet, G. et al. Confinement and sleep deprivation effects on propensity to take risks. Aviat. Space. Environ. Med. 80, 73–80 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
44.Killgore, W. D. S. Effects of sleep deprivation and morningness-eveningness traits on risk-taking. Psychol. Rep. 100, 613–626 (2007).PubMed 
Article 
PubMed Central 

Google Scholar 
45.Killgore, W. D. S. et al. Restoration of risk-propensity during sleep deprivation: Caffeine, dextroamphetamine, and modafinil. Aviat. Space. Environ. Med. 79, 867–874 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
46.Tversky, A. & Kahneman, D. Judgment under uncertainty: Heuristics and biases. Science (80-). 185, 1124–1131 (1974).ADS 
CAS 
Article 

Google Scholar 
47.Spieth, H. T. Courtship behavior in Drosophila. Annu. Rev. Entomol. 19, 385–405 (1974).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
48.Bartelt, R. J., Schaner, A. M. & Jackson, L. L. cis-Vaccenyl acetate as an aggregation pheromone in Drosophila melanogaster. J. Chem. Ecol. 11, 1747–1756 (1985).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
49.Cazalé-Debat, L., Houot, B., Farine, J. P., Everaerts, C. & Ferveur, J. F. Flying Drosophila show sex-specific attraction to fly-labelled food. Sci. Rep. 9, 1–13 (2019).Article 
CAS 

Google Scholar 
50.Malek, H. L. & Long, T. A. F. On the use of private versus social information in oviposition site choice decisions by Drosophila melanogaster females. Behav. Ecol. 31, 739–749 (2020).Article 

Google Scholar 
51.Inoue, I. et al. Impaired locomotor activity and exploratory behavior in mice lacking histamine H1 receptors. Proc. Natl. Acad. Sci. U. S. A. 93, 13316–13320 (1996).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
52.Daffner, K. R., Mesulam, M.-M., Cohen, L. G. & Scinto, L. F. M. Mechanisms underlying diminished novelty-seeking behavior in patients with probable Alzheimer’s disease. Neuropsychiatry Neuropsychol. Behav. Neurol. 12, 58–66 (1999).CAS 
PubMed 
PubMed Central 

Google Scholar 
53.Lee, A. C. H., Rahman, S., Hodges, J. R., Sahakian, B. J. & Graham, K. S. Associative and recognition memory for novel objects in dementia: Implications for diagnosis. Eur. J. Neurosci. 18, 1660–1670 (2003).PubMed 
Article 
PubMed Central 

Google Scholar 
54.Ju, Y.-E.S., Lucey, B. P. & Holtzman, D. M. Sleep and Alzheimer disease pathology—A bidirectional relationship. Nat. Rev. Neurol. 10, 115–119 (2014).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
55.Tabuchi, M. et al. Sleep interacts with aβ to modulate intrinsic neuronal excitability. Curr. Biol. 25, 702–712 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
56.Dissel, S. et al. Enhanced sleep reverses memory deficits and underlying pathology in drosophila models of Alzheimer’s disease. Neurobiol. Sleep Circadian Rhythm. 2, 15–26 (2017).Article 

Google Scholar 
57.Takano-Shimizu-Kouno, T. KYOTO Stock Center—Department of Drosophila Genomics and Genetic Resources (Kyoto Institute of Technology, 2015).58.Shaw, P. J., Tortoni, G., Greenspan, R. J. & Robinson, D. F. Stress response genes protect against lethal effects of sleep deprivation in Drosophila. Nature 417, 287–291 (2002).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
59.https://www.arduino.cc/. Accessed 6 Jan 202160.https://processing.org/. Accessed 6 Jan 2021 More

1.Yadav, G. S. et al. Energy budget and carbon footprint in a no-till and mulch based rice–mustard cropping system. J. Clean. Prod. 191, 144–157 (2018).Article 

Google Scholar 
2.Fleming-Muñoz, D. A., Preston, K. & Arratia-Solar, A. Value and impact of publicly funded climate change agricultural mitigation research: Insights from New Zealand. J. Clean. Prod. 248, 119249 (2020).Article 

Google Scholar 
3.IPCC. Climate Change 2014: Mitigation of Climate Change (Cambridge University Press, 2014).
Google Scholar 
4.Wang, Z. B. et al. Lowering carbon footprint of winter wheat by improving management practices in North China Plain. J. Clean. Prod. 112, 149–157 (2016).CAS 
Article 

Google Scholar 
5.Grassini, P. & Cassman, K. G. High-yield maize with large net energy yield and small global warming intensity. Proc. Natl. Acad. Sci. 109, 1074–1079 (2012).ADS 
CAS 
PubMed 
Article 

Google Scholar 
6.Gao, B. et al. Chinese cropping systems are a net source of greenhouse gases despite soil carbon sequestration. Glob. Change Biol. 24, 5590–5606 (2018).Article 

Google Scholar 
7.Xue, J. F. et al. Carbon footprint of dryland winter wheat under film mulching during summer-fallow season and sowing method on the Loess Plateau. Ecol. Indic. 95, 12–20 (2018).CAS 
Article 

Google Scholar 
8.Yuan, S., Peng, S. B., Wang, D. & Man, J. G. Evaluation of the energy budget and energy use efficiency in wheat production under various crop management practices in China. Energy 160, 184–191 (2018).Article 

Google Scholar 
9.Qi, J. Y. et al. Response of carbon footprint of spring maize production to cultivation patterns in the Loess Plateau, China. J. Clean. Prod. 187, 525–536 (2018).CAS 
Article 

Google Scholar 
10.Lu, X. L. & Liao, Y. C. Effect of tillage practices on net carbon flux and economic parameters from farmland on the Loess Plateau in China. J. Clean. Prod. 162, 1617–1624 (2017).CAS 
Article 

Google Scholar 
11.Tan, Y. C., Wu, D., Bol, R., Wu, W. L. & Meng, F. Q. Conservation farming practices in winter wheat–summer maize cropping reduce GHG emissions and maintain high yields. Agric. Ecosyst. Environ. 272, 266–275 (2019).CAS 
Article 

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

Google Scholar 
13.Wang, X. L. et al. Emergy analysis of grain production systems on large-scale farms in the North China Plain based on LCA. Agric. Syst. 128, 66–78 (2014).Article 

Google Scholar 
14.Chen, X. Z. et al. Environmental impact assessment of water-saving irrigation systems across 60 irrigation construction projects in northern China. J. Clean. Prod. 245, 118883 (2020).Article 

Google Scholar 
15.Racette, K., Zurweller, B., Tillman, B. & Rowland, D. Transgenerational stress memory of water deficit in peanut production. Field Crop. Res. 248, 107712 (2020).Article 

Google Scholar 
16.Xie, J. H. et al. Subsoiling increases grain yield, water use efficiency, and economic return of maize under a fully mulched ridge-furrow system in a semiarid environment in China. Soil. Till. Res. 199, 104584 (2020).Article 

Google Scholar 
17.Li, R., Hou, X. Q., Jia, Z. K. & Han, Q. F. Soil environment and maize productivity in semi-humid regions prone to drought of Weibei Highland are improved by ridge-and-furrow tillage with mulching. Soil. Till. Res. 196, 104476 (2020).Article 

Google Scholar 
18.Zhang, X. D. et al. Optimizing fertilization under ridge-furrow rainfall harvesting system to improve foxtail millet yield and water use in a semiarid region, China. Agric. Water Manag. 227, 105852 (2020).Article 

Google Scholar 
19.Nishimura, S., Komada, M., Takebe, M., Yonemura, S. & Kato, N. Nitrous oxide evolved from soil covered with plastic mulch film in horticultural field. Biol. Fertil. Soils 48, 787–795 (2012).CAS 
Article 

Google Scholar 
20.Xiong, L., Liang, C., Ma, B., Shah, F. & Wu, W. Carbon footprint and yield performance assessment under plastic film mulching for winter wheat production. J. Clean. Prod. 270, 122468 (2020).CAS 
Article 

Google Scholar 
21.Zhang, F., Zhang, W. J., Qi, J. G. & Li, F. M. A regional evaluation of plastic film mulching for improving crop yields on the Loess Plateau of China. Agric. Forest Meteorol. 248, 458–468 (2018).ADS 
Article 

Google Scholar 
22.Peng, X. Y., Wu, X. H., Wu, F. Q., Wang, X. Q. & Tong, X. G. Life cycle assessment of winter wheat-summer maize rotation system in Guanzhong region of shaanxi province. J. Agro-Environ. Sci. 34, 809–816 (2015).CAS 

Google Scholar 
23.Li, C. J. et al. Ridge-furrow with plastic film mulching practice improves maize productivity and resource use efficiency under the wheat-maize double-cropping system in dry semi-humid areas. Field Crop. Res. 203, 201–211 (2017).Article 

Google Scholar 
24.Tang, J. J., Folmer, H. & Xue, J. H. Technical and allocative efficiency of irrigation water use in the Guanzhong Plain. China. Food Policy 50, 43–52 (2015).Article 

Google Scholar 
25.Liu, Y., Zhang, X. L., Xi, L. Y., Liao, Y. C. & Han, J. Ridge-furrow planting promotes wheat grain yield and water productivity in the irrigated sub-humid region of China. Agric. Water Manag. 231, 105935 (2020).Article 

Google Scholar 
26.Li, Y. Z. et al. Combined ditch buried straw return technology in a ridge–furrow plastic film mulch system: Implications for crop yield and soil organic matter dynamics. Soil. Till. Res. 199, 104596 (2020).Article 

Google Scholar 
27.Wart, J. V., Kersebaum, K. C., Peng, S. B., Maribeth, M. & Cassman, K. G. Estimating crop yield potential at regional to national scales. Field Crops Res. 143, 34–43 (2013).Article 

Google Scholar 
28.Hu, Y. J. et al. Exploring optimal soil mulching for the wheat-maize cropping system in sub-humid drought-prone regions in China. Agric. Water Manag. 219, 59–71 (2019).Article 

Google Scholar 
29.Cui, J. X. et al. Integrated assessment of economic and environmental consequences of shifting cropping system from wheat-maize to monocropped maize in the North China Plain. J. Clean. Prod. 193, 524–532 (2018).Article 

Google Scholar 
30.Yin, W. et al. Wheat-maize intercropping with reduced tillage and straw retention: A step towards enhancing economic and environmental benefits in arid areas. Front. Plant Sci. 9, 1328 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
31.Zheng, J. F. et al. Biochar compound fertilizer increases nitrogen productivity and economic benefits but decreases carbon emission of maize production. Agric. Ecosyst. Environ. 241, 70–78 (2017).CAS 
Article 

Google Scholar 
32.Liang, L. et al. A multi-indicator assessment of peri-urban agricultural production in Beijing, China. Ecol. Indic. 97, 350–362 (2019).CAS 
Article 

Google Scholar 
33.Moitzi, G., Neugschwandtner, R. W., Kaul, H. P. & Wagentristl, H. Energy efficiency of winter wheat in a long-term tillage experiment under Pannonian climate conditions. Eur. J. Agron. 103, 24–31 (2019).Article 

Google Scholar 
34.Nasseri, A. Energy use and economic analysis for wheat production by conservation tillage along with sprinkler irrigation. Sci. Total Environ. 648, 450–459 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
35.Sahabi, H., Feizi, H. & Karbasi, A. Is saffron more energy and economic efficient than wheat in crop rotation systems in northeast Iran?. Sustain. Prod. Consum. 5, 29–35 (2016).Article 

Google Scholar 
36.Mondani, F., Aleagha, S., Khoramivafa, M. & Ghobadi, R. Evaluation of greenhouse gases emission based on energy consumption in wheat agroecosystems. Energy Rep. 3, 37–45 (2017).Article 

Google Scholar 
37.Bertocco, M., Basso, B., Sartori, L. & Martin, E. C. Evaluating energy efficiency of site-specific tillage in maize in NE Italy. Bioresour. Technol. 99, 6957–6965 (2008).CAS 
PubMed 
Article 

Google Scholar 
38.Amaducci, S., Colauzzi, M., Battini, F., Fracasso, A. & Perego, A. Effect of irrigation and nitrogen fertilization on the production of biogas from maize and sorghum in a water limited environment. Eur. J. Agron. 76, 54–65 (2016).ADS 
CAS 
Article 

Google Scholar 
39.Qiu, G. Y., Zhang, X., Yu, X. & Zou, Z. The increasing effects in energy and GHG emission caused by groundwater level declines in North China’s main food production plain. Agr. Water Manag. 203, 138–150 (2018).Article 

Google Scholar 
40.Arvidsson, J. Energy use efficiency in different tillage systems for winter wheat on a clay and silt loam in Sweden. Eur. J. Agron. 33, 250–256 (2010).Article 

Google Scholar 
41.Singh, R. J. et al. Energy budgeting and emergy synthesis of rainfed maize–wheat rotation system with different soil amendment applications. Ecol. Indic. 61, 753–765 (2016).CAS 
Article 

Google Scholar 
42.Zhang, Y. et al. Effects of different fertilizer strategies on soil water utilization and maize yield in the ridge and furrow rainfall harvesting system in semiarid regions of China. Agric. Water Manag. 208, 414–421 (2018).Article 

Google Scholar 
43.Cheng, K. et al. Carbon footprint of China’s crop production–An estimation using agro-statistics data over 1993–2007. Agr. Ecosyst. Environ. 142, 231–237 (2011).Article 

Google Scholar 
44.Hillier, J. et al. The carbon footprints of food crop production. Int. J. Agric. Sustain. 7, 107–118 (2009).Article 

Google Scholar 
45.Su, B., Su, Z. & Shangguan, Z. Trade-off analyses of plant biomass and soil moisture relations on the Loess Plateau. CATENA 197, 104946 (2020).Article 

Google Scholar 
46.Prata, J. C. et al. Solutions and integrated strategies for the control and mitigation of plastic and microplastic pollution. Int. J. Environ. Res. Public Health 16, 2411 (2019).PubMed Central 
Article 
PubMed 

Google Scholar 
47.Sardon, H. & Dove, A. P. Plastics recycling with a difference. Science 360, 380–381 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
48.Qin, W., Hu, C. & Oenema, O. Soil mulching significantly enhances yields and water and nitrogen use efficiencies of maize and wheat: A metaeanalysis. Sci. Rep. 5, 16210 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
49.Sun, M. et al. Maize and rice double cropping benefits carbon footprint and soil carbon budget in paddy field. Field Crops Res. 243, 107620 (2019).Article 

Google Scholar 
50.Choudhary, M. et al. Energy budgeting and carbon footprint of pearl millet e mustard cropping system under conventional and conservation agriculture in rainfed semi-arid agro-ecosystem. Energy 141, 1052–1058 (2017).Article 

Google Scholar 
51.Bai, J. et al. Straw returning and one-time application of a mixture of controlled release and solid granular urea to reduce carbon footprint of plastic film mulching spring maize. J. Clean. Prod. 280, 124478 (2021).CAS 
Article 

Google Scholar 
52.Li, C. J. et al. Towards the highly effective use of precipitation by ridge-furrow with plastic film mulching instead of relying on irrigation resources in a dry semi-humid area. Field Crops Res. 188, 62–73 (2016).ADS 
Article 

Google Scholar 
53.Reisinger, A., Ledgard, S. F. & Falconer, S. J. Sensitivity of the carbon footprint of New Zealand milk to greenhouse gas metrics. Ecol. Indic. 81, 74–82 (2017).CAS 
Article 

Google Scholar 
54.Chen, X. et al. Carbon footprint of a typical pomelo production region in China basedon farm survey data. J. Clean. Prod. 277, 124041 (2020).CAS 
Article 

Google Scholar 
55.Pratibha, G. et al. Impact of conservation agriculture practices on energy use efficiency and global warming potential in rainfed pigeonpea–castor systems. Eur. J. Agron. 66, 30–40 (2015).Article 

Google Scholar 
56.Wang, C., Li, X., Gong, T. & Zhang, H. Life cycle assessment of wheat-maize rotation system emphasizing high crop yield and high resource use efficiency in Quzhou County. J. Clean. Prod. 68, 56–63 (2014).CAS 
Article 

Google Scholar 
57.Li, S. et al. Effect of straw management on carbon sequestration and grain production in a maize–wheat cropping system in Anthrosol of the Guanzhong Plain. Soil Till. Res. 157, 43–51 (2016).Article 

Google Scholar 
58.Kong, A. Y. Y., Six, J., Bryant, D. C., Denison, R. F. & van Kessel, C. The relationship between carbon input, aggregation, and soil organic carbon stabilization in sustainable cropping systems. Soil Sci. Soc. Am. J. 69, 1078–1085 (2005).ADS 
CAS 
Article 

Google Scholar 
59.Zhu, Y. C. et al. Large-scale farming operations are win-win for grain production, soil carbon storage and mitigation of greenhouse gases. J. Clean. Prod. 172, 2143–2152 (2018).Article 

Google Scholar 
60.Wang, Z. B. et al. Comparison of greenhouse gas emissions of chemical fertilizer types in China’s crop production. J. Clean. Prod. 141, 1267–1274 (2017).CAS 
Article 

Google Scholar  More

1.Hughes, T. P. et al. Coral reefs in the Anthropocene. Nature 546, 82–90 (2017).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
2.de Groot, R. et al. Global estimates of the value of ecosystems and their services in monetary units. Ecosyst. Serv. 1, 50–61 (2012).Article 

Google Scholar 
3.Exton, D. A. et al. Artisanal fish fences pose broad and unexpected threats to the tropical coastal seascape. Nat. Commun. 10, 2100 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
4.Pandolfi, J. M. et al. Global trajectories of the long-term decline of coral reef ecosystems. Science (80-) 301, 955–958 (2003).ADS 
CAS 
Article 

Google Scholar 
5.Graham, N. A. J., Jennings, S., MacNeil, M. A., Mouillot, D. & Wilson, S. K. Predicting climate-driven regime shifts versus rebound potential in coral reefs. Nature 518, 94–97 (2015).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
6.Roff, G. & Mumby, P. J. Global disparity in the resilience of coral reefs. Trends Ecol. Evol. 27, 404–413 (2012).PubMed 
Article 
PubMed Central 

Google Scholar 
7.Jackson, J.B.C., Donovan, M.K., Cramer, K.L. and Lam, V.V. Status and trends of Caribbean coral reefs. Global Coral Reef Monitoring
Network, IUCN, Gland, Switzerland, pp.1970-2012. (2014).8.Alvarez-Filip, L., Dulvy, N. K., Gill, J. A., Côté, I. M. & Watkinson, A. R. Flattening of Caribbean coral reefs: region-wide declines in architectural complexity. Proc. R. Soc. B Biol. Sci. 276, 3019–3025 (2009).Article 

Google Scholar 
9.Elmqvist, T. et al. Response diversity, ecosystem change, and resilience. Front. Ecol. Environ. 1, 488–494 (2003).Article 

Google Scholar 
10.Sasaki, T., Furukawa, T., Iwasaki, Y., Seto, M. & Mori, A. S. Perspectives for ecosystem management based on ecosystem resilience and ecological thresholds against multiple and stochastic disturbances. Ecol. Ind. 57, 395–408 (2015).Article 

Google Scholar 
11.McCann, K. S. The diversity-stability debate. Nature 405, 228–233 (2000).CAS 
PubMed 
Article 

Google Scholar 
12.Bellwood, D. R., Hughes, T. P., Folke, C. & Nyström, M. Confronting the coral reef crisis. Nature 429, 827–833 (2004).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.Mumby, P. J., Hastings, A. & Edwards, H. J. Thresholds and the resilience of Caribbean coral reefs. Nature 450, 98–101 (2007).ADS 
CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
14.Hughes, T. P., Graham, N. A. J., Jackson, J. B. C., Mumby, P. J. & Steneck, R. S. Rising to the challenge of sustaining coral reef resilience. Trends Ecol. Evol. 25, 633–642 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
15.Solandt, J. L. & Campbell, A. C. Macroalgal feeding characteristics of the sea urchin Diadema antillarum Philippi at Discovery Bay, Jamaica. Caribb. J. Sci. 37, 227–238 (2001).
Google Scholar 
16.Chiappone, M., Rutten, L. M., Miller, S. L. & Swanson, D. W. Recent trends (1999–2011) in population density and size of the echinoid Diadema antillarum in the Florida Keys. Florida Sci. 76, 23–35 (2013).
Google Scholar 
17.Lessios, H. A. The great Diadema antillarum die-off: 30 years later. Annu. Rev. Mar. Sci. 8, 267–283 (2016).ADS 
CAS 
Article 

Google Scholar 
18.Bruno, J. F., Sweatman, H., Precht, W. F., Selig, E. R. & Schutte, V. G. W. Assessing evidence of phase shifts from coral to macroalgal dominance on coral reefs. Ecol. Soc. Am. 90, 1478–1484 (2009).
Google Scholar 
19Miller, M. W., Szmant, A. M. & Precht, W. F. Lessons learned from experimental key-species restoration. In Coral Reef Restoration Handbook, 219–234 (ed. Precht, W. F.) (Taylor & Francis, 2006).
Google Scholar 
20.Mumby, P. J., Hedley, J. D., Zychaluk, K., Harborne, A. R. & Blackwell, P. G. Revisiting the catastrophic die-off of the urchin Diadema antillarum on Caribbean coral reefs: fresh insights on resilience from a simulation model. Ecol. Modell. 196, 131–148 (2006).Article 

Google Scholar 
21.Myhre, S. & Acevedo-Gutiérrez, A. Recovery of sea urchin Diadema antillarum populations is correlated to increased coral and reduced macroalgal cover. Mar. Ecol. Prog. Ser. 329, 205–210 (2007).ADS 
Article 

Google Scholar 
22.Carpenter, R. C. Predator and population density control of homing behavior in the Caribbean echinoid Diadema antillarum. Mar. Biol. 82, 101–108 (1984).Article 

Google Scholar 
23.Edmunds, P. J. & Carpenter, R. C. Recovery of Diadema antillarum reduces macroalgal cover and increases abundance of juvenile corals on a Caribbean reef. Proc. Natl. Acad. Sci. U. S. A. 98, 5067–5071 (2001).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
24.Wanders, J. B. W. The role of benthic algae in the shallow reef of Curaçao (Netherlands Antilles) III: the significance of grazing. Aquat. Bot. 3, 357–390 (1977).Article 

Google Scholar 
25.Bak, R. P. M., Carpay, M. J. E. & de Ruyter van Steveninck, E. D. Densities of the sea urchin Diadema antillarum before and after mass mortalities on the coral reefs of Curacao. Mar. Ecol. Prog. Ser. 17, 105–108 (1984).ADS 
Article 

Google Scholar 
26.Levitan, D. R. Algal-urchin biomass responses following mass mortality of Diadema antillarum Philippi at Saint John, U.S. Virgin Islands. J. Exp. Mar. Biol. Ecol. 119, 167–178 (1988).Article 

Google Scholar 
27.Chiappone, M., Rutten, L., Swanson, D. & Miller, S. Population status of the urchin Diadema antillarum in the Florida Keys 25 years after the Caribbean mass mortality. In Proceedings of 11th International Coral Reef Symposium 706–710 (2008).28.Bodmer, M. D. V., Rogers, A., Speight, M. R., Lubbock, N. & Exton, D. A. Using an isolated population boom to explore barriers to recovery in the keystone Caribbean coral reef herbivore Diadema antillarum. Coral Reefs 34, 1011–1021 (2015).ADS 
Article 

Google Scholar 
29.Lessios, H. A., Robertson, D. R. & Cubit, J. D. Spread of Diadema mass mortality through the Caribbean. Science (80-) 226, 335–337 (1984).ADS 
CAS 
Article 

Google Scholar 
30.Liddell, W. D. & Ohlhorst, S. L. Changes in benthic community composition following the mass mortality of Diadema at Jamaica. J. Exp. Mar. Biol. Ecol. 95, 271–278 (1986).Article 

Google Scholar 
31.Betchel, J. D., Gayle, P. & Kaufman, L. The return of Diadema antillarum to Discovery Bay: patterns of distribution and abundance. In Proceedings of 10th International Coral Reef Symposium 367–375 (2006).32.Robertson, D. R. Increases in surgeonfish populations after mass mortality of the sea urchin Diadema antillarum in Panamá indicate food limitation. Mar. Biol. 111, 437–444 (1991).Article 

Google Scholar 
33.Lessios, H. A. Diadema antillarum populations in Panama 20 years following mass mortality. Coral Reefs 24, 125–127 (2005).Article 

Google Scholar 
34.Hunte, W. & Younglao, D. Recruitment and population recovery of Diadema antillarum (Echinodermata; Echinoidea) in Barbados. Mar. Ecol. Prog. Ser. 45, 109–119 (1988).ADS 
Article 

Google Scholar 
35.Noriega, N., Pauls, S. M. & del Mónaco, C. Abundancia de Diadema antillarum (Echinodermata: Echinoidea) en las costas de Venezuela. Rev. Biol. Trop. 54, 793–802 (2006).PubMed 
Article 
PubMed Central 

Google Scholar 
36.Debrot, A. O. & Nagelkerken, I. Recovery of the long-spined sea urchin Diadema antillarum in Curacao (Netherlands Antilles) linked to lagoonal and wave sheltered shallow rocky habitats. Bull. Mar. Sci. 72, 415–424 (2006).
Google Scholar 
37.Vermeij, M. J. A., Debrot, A. O., van der Hal, N., Bakker, J. & Bak, R. P. M. Increased recruitment rates indicate recovering populations of the sea urchin Diadema antillarum on Curaçao. Bull. Mar. Sci. 86, 719–725 (2010).
Google Scholar 
38.Carpenter, K. E. et al. One-third of reef-building corals face elevated extinction risk from climate change and local impacts. Science (80-) 321, 560–563 (2008).ADS 
CAS 
Article 

Google Scholar 
39.Gardner, T. A., Côté, I. M., Gill, J. A., Grant, A. & Watkinson, A. R. Long-term region-wide declines in Caribbean corals. Science (80-) 301, 958–960 (2003).ADS 
CAS 
Article 

Google Scholar 
40.Pennington, J. T. The ecology of fertilization of echinoid eggs: the consequences of sperm dilution, adult aggregation, and synchronous spawning. Biol. Bull. 169, 417–430 (1985).PubMed 
Article 
PubMed Central 

Google Scholar 
41.Levitan, D. R. Influence of body size and population density on fertilization success and reproductive output in a free-spawning invertebrate. Biol. Bull. 181, 261–268 (1991).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
42.Levitan, D. R., Edmunds, P. J. & Levitan, K. E. What makes a species common? No evidence of density-dependent recruitment or mortality of the sea urchin Diadema antillarum after the 1983–1984 mass mortality. Oecologia 175, 117–128 (2014).ADS 
PubMed 
Article 
PubMed Central 

Google Scholar 
43.Lacey, E. A., Fourqurean, J. W. & Collado-Vides, L. Increased algal dominance despite presence of Diadema antillarum populations on a Caribbean coral reef. Bull. Mar. Sci. 89, 603–620 (2013).Article 

Google Scholar 
44.Dumas, P., Kulbicki, M., Chifflet, S., Fichez, R. & Ferraris, J. Environmental factors influencing urchin spatial distributions on disturbed coral reefs (New Caledonia, South Pacific). J. Exp. Mar. Biol. Ecol. 344, 88–100 (2007).Article 

Google Scholar 
45.Rogers, A. & Lorenzen, K. Does slow and variable recovery of Diadema antillarum on Caribbean fore-reefs reflect density-dependent habitat selection? Front. Mar. Sci. 3, 63 (2016).Article 

Google Scholar 
46.Alvarado, J. J., Cortés, J., Guzman, H. & Reyes-Bonilla, H. Density, size, and biomass of Diadema mexicanum (Echinoidea) in Eastern Tropical Pacific coral reefs. Aquat. Biol. 24, 151–161 (2016).Article 

Google Scholar 
47.Ogden, J. C. & Carpenter, R. C. Long-spined black sea urchin. Biol. Rep. 82, 1–17 (1987).
Google Scholar 
48.Bodmer, M. D. V. et al. Interacting effects of temperature, habitat and phenotype on predator avoidance behaviour in Diadema antillarum: implications for restorative conservation. Mar. Ecol. Prog. Ser. 566, 105–115 (2017).ADS 
Article 

Google Scholar 
49.Andradi-Brown, D. A., Gress, E., Wright, G., Exton, D. A. & Rogers, A. D. Reef fish community biomass and trophic structure changes across shallow to upper-mesophotic reefs in the mesoamerican barrier reef, Caribbean. PLoS ONE 11, 1–19 (2016).
Google Scholar 
50.Rodríguez-Barreras, R., Pérez, M. E., Mercado-Molina, A. E. & Sabat, A. M. Arrested recovery of Diadema antillarum population: survival or recruitment limitation? Estuar. Coast. Shelf Sci. 163, 167–174 (2015).ADS 
Article 

Google Scholar 
51.Risk, M. J. Fish diversity on a coral reef in the Virgin Islands. Atoll Res. Bull. 153, 1–4 (1972).Article 

Google Scholar 
52.Figueira, W. et al. Accuracy and precision of habitat structural complexity metrics derived from underwater photogrammetry. Remote Sens. 7, 16883–16900 (2015).ADS 
Article 

Google Scholar 
53.Leon, J. X., Roelfsema, C. M., Saunders, M. I. & Phinn, S. R. Measuring coral reef terrain roughness using ‘Structure-from-Motion’ close-range photogrammetry. Geomorphology 242, 21–28 (2015).ADS 
Article 

Google Scholar 
54.Storlazzi, C. D., Dartnell, P., Hatcher, G. A. & Gibbs, A. E. End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology. Coral Reefs 35, 889–894 (2016).ADS 
Article 

Google Scholar 
55.Young, G. C., Dey, S., Rogers, A. D. & Exton, D. A. Cost and time-effective method for multiscale measures of rugosity, fractal dimension, and vector dispersion from coral reef 3D models. PLoS ONE 12, e0175341 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
56.Zawada, D. G. & Brock, J. C. A multiscale analysis of coral reef topographic complexity using lidar-derived bathymetry. J. Coast. Res. 2009, 6–16 (2009).Article 

Google Scholar 
57.Randall, J. E., Schroeder, R. E. & Starck, W. A. Notes on the biology of the echinoid Diadema antillarum. Caribb. J. Sci. 4, 421–433 (1964).
Google Scholar 
58.Hunt, C. L. et al. Aggregating behaviour in invasive Caribbean lionfish is driven by habitat complexity. Sci. Rep. 9, 783 (2019).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
59.Millott, N. & Yoshida, M. The shadow reaction of Diadema antillarum Philippi I: the spine response and its relation to the stimulus. J. Exp. Biol. 37, 363–375 (1960).Article 

Google Scholar 
60.Millott, N. & Yoshida, M. The shadow reaction of Diadema antillarum Philippi II: inhibition by light. J. Exp. Biol. 37, 376–389 (1960).Article 

Google Scholar 
61.Raible, F. et al. Opsins and clusters of sensory G-protein-coupled receptors in the sea urchin genome. Dev. Biol. 300, 461–475 (2006).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
62.Ullrich-Lüter, E. M., D’Aniello, S. & Arnone, M. I. C-opsin expressing photoreceptors in echinoderms. Integr. Comp. Biol. 53, 27–38 (2013).PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
63.Yoshida, M. On the light response of the chromatophore of the sea-urchin, Diadema setosum (Leske). J. Exp. Biol. 33, 119–123 (1956).Article 

Google Scholar 
64.JPL MUR MEaSUREs. GHRSST Level 4 MUR global foundation sea surface temperature analysis. Version 4.1 PO.DAAC, CA, USA. Dataset accessed 23 Jan 2021 at https://doi.org/10.5067/GHGMR-4FJ04 (2015).65.Pickering, H., Whitmarsh, D. & Jensen, A. Artificial reefs as a tool to aid rehabilitation of coastal ecosystems: investigating the potential. Mar. Pollut. Bull. 37, 505–514 (1999).Article 

Google Scholar 
66.Fitzhardinge, R. C. & Bailey-Brock, J. H. Colonization of artificial reef materials by corals and other sessile organisms. Bull. Mar. Sci. 44, 567–579 (1989).
Google Scholar 
67.R Core Team. R: A Language and Environment for Statistical Computing. Vienna. https://www.r-project.org/. (2016).68.RStudio Team. RStudio: Integrated Development for R (2015).69.Dinno, A. conover.test: Conover-Iman test of multiple comparisons using rank sums. R Package Version 1.1.5. (2017).70.Scheibling, R. E. & Robinson, M. C. Settlement behaviour and early post-settlement predation of the sea urchin Strongylocentrotus droebachiensis. J. Exp. Mar. Biol. Ecol. 365, 59–66 (2008).Article 

Google Scholar 
71.Kintzing, M. D. & Butler, M. J. The influence of shelter, conspecifics, and threat of predation on the behavior of the long-spined sea urchin (Diadema antillarum). J. Shellfish Res. 33, 781–785 (2014).Article 

Google Scholar 
72.Clemente, S., Hernández, J. C., Toledo, K. & Brito, A. Predation upon Diadema aff. antillarum in barren grounds in the Canary Islands. Sci. Mar. 71, 745–754 (2007).Article 

Google Scholar 
73.Jennings, L. B. & Hunt, H. L. Settlement, recruitment and potential predators and competitors of juvenile echinoderms in the rocky subtidal zone. Mar. Biol. 157, 307–316 (2010).Article 

Google Scholar 
74.Rodríguez-Barreras, R. Demographic implications of predatory wrasses on low-density Diadema antillarum populations. Mar. Biol. Res. 14, 383–391 (2018).Article 

Google Scholar 
75.Delgado, G. A. & Sharp, W. C. Does artificial shelter have a place in Diadema antillarum restoration in the Florida Keys? Tests of habitat manipulation and sheltering behavior. Glob. Ecol. Conserv. 26, e01502 (2021).Article 

Google Scholar 
76.Sammarco, P. W. & Williams, A. H. Damselfish territoriality: influence on Diadema antillarum distribution and implications for coral community structure. Mar. Ecol. Prog. Ser. 8, 53–59 (1982).ADS 
Article 

Google Scholar 
77.Nedimyer, K. & Moe, M. A. 2003. Techniques development for the reestablishment of the long-spined sea urchin, Diadema antillarum, on two small patch reefs in the upper Florida Keys. 2002–2003 Sanctuary Science Report: An Ecosystem Report Card After Five Years of Marine Zoning.78.Idjadi, J., Haring, R. & Precht, W. Recovery of the sea urchin Diadema antillarum promotes scleractinian coral growth and survivorship on shallow Jamaican reefs. Mar. Ecol. Prog. Ser. 403, 91–100 (2010).ADS 
Article 

Google Scholar 
79.Macia, S., Robinson, M. P. & Nalevanko, A. Experimental dispersal of recovering Diadema antillarum increases grazing intensity and reduces macroalgal abundance on a coral reef. Mar. Ecol. Prog. Ser. 348, 173–182 (2007).ADS 
Article 

Google Scholar  More

1.EU. Communication from the Commission. Ports: an engine for growth (2013).2.EU. Directive (EU) 2019/883 of the European Parliament and of the Council of 17 April 2019. 2019(March), 116–142 (2019).3.Chao, M. & Rodríguez, M. New trends in port managing: towards the e-port. J. Marit. Res. 3(2), 35–42 (2006).
Google Scholar 
4.Paiano, A., Crovella, T. & Lagioia, G. Managing sustainable practices in cruise tourism: the assessment of carbon footprint and waste of water and beverage packaging. Tour. Manag. 77(October 2019), 104016. https://doi.org/10.1016/j.tourman.2019.104016 (2020).Article 

Google Scholar 
5.Kovačić, M. & Silveira, L. Nautical tourism in Croatia and in Portugal in the late 2010’s: issues and perspectives. Pomorstvo 32(2), 281–289. https://doi.org/10.31217/p.32.2.13 (2018).Article 

Google Scholar 
6.Pérez Labajos, C. & Blanco Rojo, B. Leisure ports planning. J. Marit. Res. 3(2), 67–82 (2006).
Google Scholar 
7.BOE. Real Decreto Legislativo 2/2011, de 5 de septiembre, por el que se aprueba el Texto Refundido de la Ley de Puertos del Estado y de la Marina Mercante. Span. Off. Bull. 255, 11. https://www.boe.es/buscar/pdf/2011/BOE-A-2011-16467-consolidado.pdf (2011).8.Gómez, A. G., Valdor, P. F., Ondiviela, B., Díaz, J. L. & Juanes, J. A. Mapping the environmental risk assessment of marinas on water quality: the Atlas of the Spanish coast. Mar. Pollut. Bull. 139(January), 355–365. https://doi.org/10.1016/j.marpolbul.2019.01.008 (2019).CAS 
Article 
PubMed 

Google Scholar 
9.Sofiev, M. et al. Cleaner fuels for ships provide public health benefits with climate tradeoffs. Nat. Commun. 9(1), 1–12. https://doi.org/10.1038/s41467-017-02774-9 (2018).CAS 
Article 

Google Scholar 
10.Chen, C., Saikawa, E., Comer, B., Mao, X. & Rutherford, D. Ship emission impacts on air quality and human health in the Pearl River Delta (PRD) Region, China, in 2015, with projections to 2030. GeoHealth 3(9), 284–306. https://doi.org/10.1029/2019GH000183 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
11.Mateos, M. R. Los puertos deportivos como infraestructuras de soporte de las actividades náuticas de recreo en Andalucía. Mar. Infrastruct. Supports Naut. Recreat. Act. Andal. 54, 335–360 (2010).
Google Scholar 
12.Nursey-Bray, M. et al. Vulnerabilities and adaptation of ports to climate change. J. Environ. Plan. Manag. 56(7), 1021–1045. https://doi.org/10.1080/09640568.2012.716363 (2013).Article 

Google Scholar 
13.Antequera, P. D., Jaime, D. & Abel, L. Tourism, transport and climate change: the carbon footprint of international air traffic on Islands. Sustainability 13(4), 1795. https://doi.org/10.3390/su13041795 (2021).CAS 
Article 

Google Scholar 
14.Hadjikakou, M., Chenoweth, J. & Miller, G. Estimating the direct and indirect water use of tourism in the eastern Mediterranean. J. Environ. Manag. 114, 548–556. https://doi.org/10.1016/j.jenvman.2012.11.002 (2013).Article 

Google Scholar 
15.Annis, G. M. et al. Designing coastal conservation to deliver ecosystem and human well-being benefits. PLoS ONE 12(2), 1–21. https://doi.org/10.1371/journal.pone.0172458 (2017).CAS 
Article 

Google Scholar 
16.Kizielewicz, J. & Lukovic, T. The phenomenon of the marina development to support the European model of economic development. TransNav Int. J. Mar. Navig. Saf. Sea Transp. 7(3), 461–466. https://doi.org/10.12716/1001.07.03.19 (2013).Article 

Google Scholar 
17.Ridolfi, E., Pujol, D. S., Ippolito, A., Saradakou, E. & Salvati, L. An urban political ecology approach to local development in fast-growing, tourism-specialized coastal cities. Tourismos 12(1), 171–204 (2017).
Google Scholar 
18.Sevinç, F. & Güzel, T. Sustainable Yacht tourism practices. Manag. Mark. XV(1), 61–76 (2017).
Google Scholar 
19.Lam-González, Y. E., León, C. J. & González-Hernández, M. M. Determinants of the European Yachtsmen´s satisfaction with the ports of call of the Canary Islands (Spain). Études Caribéennes https://doi.org/10.4000/etudescaribeennes.10584 (2017).Article 

Google Scholar 
20.Novales, A., Martínez Martín, M. I., Castro Núñez, R. B., Cazcarro Castellano, I. & Santero Sánchez, R. El impacto económico de la Náutica de Recreo 99 (Universidad Complutense de Madrid, 2018).
Google Scholar 
21.Cámara de Comercio e Industria de Marsella. Náutica de recreo en el Mediterráneo 114 (Etinet, 2011).
Google Scholar 
22.Mensa, J. A., Vasallo, P. & Fabiano, M. JMarinas: a simple tool for the environmentally sound management of small marinas. J. Environ. Manag. 92, 67–77 (2011).CAS 
Article 

Google Scholar 
23.Benton, T. G. From castaways to throwaways: marine litter in the Pitcairn Islands. Biol. J. Lin. Soc. 56, 415–422 (1995).Article 

Google Scholar 
24.Chainho, P. et al. Non-indigenous species in Portuguese coastal areas, coastal lagoons, estuaries and islands. Estuar. Coast. Shelf Sci. 167, 199–211. https://doi.org/10.1016/j.ecss.2015.06.019 (2015).ADS 
Article 

Google Scholar 
25.Styhre, L., Winnes, H., Black, J., Lee, J. & Le-Griffin, H. Greenhouse gas emissions from ships in ports: case studies in four continents. Transp. Res. Part D Transp. Environ. 54, 212–224. https://doi.org/10.1016/j.trd.2017.04.033 (2017).Article 

Google Scholar 
26.Yang, Y. C. Operating strategies of CO2 reduction for a container terminal based on carbon footprint perspective. J. Clean. Prod. 141, 472–480. https://doi.org/10.1016/j.jclepro.2016.09.132 (2017).CAS 
Article 

Google Scholar 
27.Giunta, M., Bressi, S. & D’Angelo, G. Life cycle cost assessment of bitumen stabilised ballast: a novel maintenance strategy for railway track-bed. Constr. Build. Mater. 172, 751–759. https://doi.org/10.1016/j.conbuildmat.2018.04.020 (2018).Article 

Google Scholar 
28.Hickmann, T. Voluntary global business initiatives and the international climate negotiations: a case study of the Greenhouse Gas Protocol. J. Clean. Prod. 169, 94–104. https://doi.org/10.1016/j.jclepro.2017.06.183 (2017).Article 

Google Scholar 
29.Garcia, R. & Freire, F. Carbon footprint of particleboard: a comparison between ISO/TS 14067, GHG protocol, PAS 2050 and climate declaration. J. Clean. Prod. 66, 199–209. https://doi.org/10.1016/j.jclepro.2013.11.073 (2014).CAS 
Article 

Google Scholar 
30.Ingrid, M.-M., Pablo, C.-M., Jose, V.-C. & Miguel Ángel, P.-G. Economic impact of a port on the hinterland: application to Santander’s port. Int. J. Shipp. Transp. Logist. 4, 235–249 (2012).Article 

Google Scholar 
31.Abdul-azeez, I. A. Development of carbon dioxide emission assessment tool towards promoting sustainability in UTM Malaysia. Open J. Energy Effic. https://doi.org/10.4236/ojee.2018.72004 (2018).Article 

Google Scholar 
32.Jeswani, H. K. & Azapagic, A. Water footprint: methodologies and a case study for assessing the impacts of water use. J. Clean. Prod. 19(12), 1288–1299. https://doi.org/10.1016/j.jclepro.2011.04.003 (2011).Article 

Google Scholar 
33.Zhuo, La., Mekonnen, M. M. & Hoekstra, A. Y. Consumptive water footprint and virtual water trade scenarios for China: with a focus on crop production, consumption and trade. Environ. Int. 94, 211–223 (2016).Article 

Google Scholar 
34.Arto, I., Andreoni, V. & Rueda-Cantuche, J. M. Global use of water resources: a multiregional analysis of water use, water footprint and water trade balance. Water Resour. Econ. 15, 1–14. https://doi.org/10.1016/j.wre.2016.04.002 (2016).Article 

Google Scholar 
35.Zhi, Y., Yang, Z., Yin, X., Hamilton, P. B. & Zhang, L. Using gray water footprint to verify economic sectors’ consumption of assimilative capacity in a river basin: model and a case study in the Haihe River Basin, China. J. Clean. Prod. 92, 267–273. https://doi.org/10.1016/j.jclepro.2014.12.058 (2015).Article 

Google Scholar 
36.Norén, A., Karlfeldt Fedje, K., Strömvall, A. M., Rauch, S. & Andersson-Sköld, Y. Integrated assessment of management strategies for metal-contaminated dredged sediments: what are the best approaches for ports, marinas and waterways?. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2019.135510 (2020).Article 
PubMed 

Google Scholar 
37.Kenworthy, J. M., Rolland, G., Samadi, S. & Lejeusne, C. Local variation within marinas: effects of pollutants and implications for invasive species. Mar. Pollut. Bull. 133(March), 96–106. https://doi.org/10.1016/j.marpolbul.2018.05.001 (2018).CAS 
Article 
PubMed 

Google Scholar 
38.Veettil, A. V. & Mishra, A. K. Water security assessment using blue and green water footprint concepts. J. Hydrol. 542, 589–602. https://doi.org/10.1016/j.jhydrol.2016.09.032 (2016).ADS 
Article 

Google Scholar 
39.Gu, Y., Li, Y., Wang, H. & Li, F. Gray water footprint: taking quality, quantity, and time effect into consideration. Water Resour. Manag. 28(11), 3871–3874. https://doi.org/10.1007/s11269-014-0695-y (2014).Article 

Google Scholar 
40.Duvat, V. K. E. et al. Trajectories of exposure and vulnerability of small islands to climate change. Rev. Clim. Change https://doi.org/10.1002/wcc.478 (2017).Article 

Google Scholar 
41.Millán, M. M. Extreme hydrometeorological events and climate change predictions in Europe. J. Hydrol. 518(PB), 206–224. https://doi.org/10.1016/j.jhydrol.2013.12.041 (2014).ADS 
CAS 
Article 

Google Scholar 
42.Smith, J. B. et al. Assessing dangerous climate change through an update of the Intergovernmental Panel on Climate Change (IPCC) “‘reasons for concern’”. Proc. Natl. Acad. Sci. U.S.A. 106(11), 4133–4137. https://doi.org/10.1073/pnas.0812355106 (2009).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
43.IPCC. Climate change 2014: impacts, adaptation and vulnerability (2014).44.Ciscar, J. C. et al. Physical and economic consequences of climate change in Europe. Proc. Natl. Acad. Sci. U.S.A. 108(7), 2678–2683. https://doi.org/10.1073/pnas.1011612108 (2011).ADS 
Article 
PubMed 
PubMed Central 

Google Scholar 
45.Melo, N., Santos, B. F. & Leandro, J. A prototype tool for dynamic pluvial-flood emergency planning. Urban Water J. 12(1), 79–88. https://doi.org/10.1080/1573062X.2014.975725 (2015).Article 

Google Scholar 
46.Lazrus, H. Sea change: Island communities and climate change. Annu. Rev. Anthropol. 41, 285–301. https://doi.org/10.1146/annurev-anthro-092611-145730 (2012).Article 

Google Scholar 
47.Reid, S., Johnston, N. & Patiar, A. Coastal resorts setting the pace: an evaluation of sustainable hotel practices. J. Hosp. Tour. Manag. 33, 11–22. https://doi.org/10.1016/j.jhtm.2017.07.001 (2017).Article 

Google Scholar 
48.Vargas-Amelin, E. & Pindado, P. The challenge of climate change in Spain: water resources, agriculture and land. J. Hydrol. 518(PB), 243–249. https://doi.org/10.1016/j.jhydrol.2013.11.035 (2014).ADS 
Article 

Google Scholar 
49.Fagerberg, J., Laestadius, S. & Martin, B. R. The triple challenge for Europe: the economy, climate change, and governance. Innov. Econ. Dev. Policy Sel. Essays 59(3), 384–410. https://doi.org/10.1080/05775132.2016.1171668 (2018).Article 

Google Scholar 
50.UNCTAD. Maritime transport in small island developing states. Rev. Marit. Transp. https://doi.org/10.1017/CBO9781107415324.004 (2014).Article 

Google Scholar 
51.Hinkey, L. M., Zaidi, B. R., Volson, B. & Rodriguez, N. J. Identifying sources and distributions of sediment contaminants at two US Virgin Islands marinas. Mar. Pollut. Bull. 50, 1244–1250. https://doi.org/10.1016/j.marpolbul.2005.04.035 (2005).CAS 
Article 
PubMed 

Google Scholar 
52.Marín, J. C. et al. Properties of particulate pollution in the port city of Valparaiso, Chile. Atmos. Environ. 171, 301–316. https://doi.org/10.1016/j.atmosenv.2017.09.044 (2017).ADS 
CAS 
Article 

Google Scholar 
53.Tóvar-Sánchez, A., Sánchez-Quiles, D. & Rodríguez-Romero, A. Massive coastal tourism influx to the Mediterranean Sea: the environmental risk of sunscreens. Sci. Total Environ. 656, 316–321 (2019).ADS 
Article 

Google Scholar 
54.Uche-Soria, M. & Rodríguez-Monroy, C. Solutions to marine pollution in Canary Islands’ ports: alternatives and optimization of energy management. Resources https://doi.org/10.3390/resources8020059 (2019).Article 

Google Scholar 
55.Bosch, N. E., Gonçalves, J. M. S., Tuya, F. & Erzini, K. Marinas as habitats for nearshore fish assemblages: comparative analysis of underwater visual census, baited cameras and fish traps. Sci. Mar. 81(2), 159. https://doi.org/10.3989/scimar.04540.20a (2017).Article 

Google Scholar 
56.Di Franco, A. et al. Do small marinas drive habitat specific impacts? A case study from Mediterranean Sea. Mar. Pollut. Bull. 62, 926–933. https://doi.org/10.1016/j.marpolbul.2011.02.053 (2011).CAS 
Article 
PubMed 

Google Scholar 
57.Pasetto, M. & Partl, M. N. in Lecture Notes in Civil Engineering Proceedings of the 5th International Symposium on Asphalt Pavements & Environment (APE). http://www.springer.com/series/15087 (2020)58.Praticò, F. G., Giunta, M., Mistretta, M. & Gulotta, T. M. Energy and environmental life cycle assessment of sustainable pavement materials and technologies for urban roads. Sustainability (Switzerland) https://doi.org/10.3390/su12020704 (2020).Article 

Google Scholar 
59.Hertwich, E. G. & Wood, R. The growing importance of scope 3 greenhouse gas emissions from industry. Environ. Res. Lett. https://doi.org/10.1088/1748-9326/aae19a (2018).Article 

Google Scholar 
60.Di Vaio, A., Varriale, L. & Alvino, F. Key performance indicators for developing environmentally sustainable and energy efficient ports: evidence from Italy. Energy Policy 122(July), 229–240. https://doi.org/10.1016/j.enpol.2018.07.046 (2018).Article 

Google Scholar 
61.Corrigan, S., Kay, A., Ryan, M., Brazil, B. & Ward, M. E. Human factors & safety culture: challenges & opportunities for the port environment. Saf. Sci. 125, 14. https://doi.org/10.1016/j.ssci.2018.02.030 (2020).Article 

Google Scholar 
62.Mali, M., Dell’Anna, M. M., Mastrorilli, P., Damiani, L. & Piccinni, A. F. Assessment and source identification of pollution risk for touristic ports: heavy metals and polycyclic aromatic hydrocarbons in sediments of 4 marinas of the Apulia region (Italy). Mar. Pollut. Bull. 114(2), 768–777. https://doi.org/10.1016/j.marpolbul.2016.10.063 (2017).CAS 
Article 
PubMed 

Google Scholar 
63.Cutroneo, L., Reboa, A., Besio, G., Borgogno, F., Canesi, L., Canuto, S., Dara, M., Enrile, F., Forioso, I., Greco, G., Lenoble, V., Malatesta, A., Mounier, S., Petrillo, M., Rovetta, R., Stocchino, A., Tesan, J., Vagge, G., & Capello, M. Correction to: Microplastics in seawater: sampling strategies, laboratory methodologies, and identification techniques applied to port environment (Environmental Science and Pollution Research, (2020), 27, 9, (8938–8952), https://doi.org/10.1007/s11356-020-07783-8). Environ. Sci. Pollut. Res. 27(16), 20571. https://doi.org/https://doi.org/10.1007/s11356-020-08704-5 (2020)64.Kotowska, I. & Kubowicz, D. The role of ports in reduction of road transport pollution in port cities. Transp. Res. Procedia 39, 212–220. https://doi.org/10.1016/j.trpro.2019.06.023 (2019).Article 

Google Scholar 
65.Coronado Mondragon, A. E., Lalwani, C. S., Coronado Mondragon, E. S., Coronado Mondragon, C. E. & Pawar, K. S. Intelligent transport systems in multimodal logistics: a case of role and contribution through wireless vehicular networks in a sea port location. Int. J. Prod. Econ. 137, 165–175. https://doi.org/10.1016/j.ijpe.2011.11.006 (2012).Article 

Google Scholar 
66.Caballini, C., Rebecchi, I. & Sacone, S. Combining multiple trips in a port environment for empty movements minimization. Transp. Res. Procedia 10, 694–703. https://doi.org/10.1016/j.trpro.2015.09.023 (2015).Article 

Google Scholar 
67.Sifakis, N. & Tsoutsos, T. Planning zero-emissions ports through the nearly zero energy port concept. J. Clean. Prod. 286, 20. https://doi.org/10.1016/j.jclepro.2020.125448 (2021).Article 

Google Scholar 
68.Karimpour, R., Ballini, F. & Ölcer, A. I. Circular economy approach to facilitate the transition of the port cities into self-sustainable energy ports: a case study in Copenhagen-Malmö Port (CMP). WMU J. Marit. Aff. 18(2), 225–247. https://doi.org/10.1007/s13437-019-00170-2 (2019).Article 

Google Scholar 
69.Babrowski, S., Heinrichs, H., Jochem, P. & Fichtner, W. Load shift potential of electric vehicles in Europe. J. Power Sources 255, 283–293. https://doi.org/10.1016/j.jpowsour.2014.01.019 (2014).ADS 
CAS 
Article 

Google Scholar 
70.Azarkamand, S., Ferré, G. & Darbra, R. M. Calculating the carbon footprint in ports by using a standardized tool. Sci. Total Environ. 734, 139407. https://doi.org/10.1016/j.scitotenv.2020.139407 (2020).ADS 
CAS 
Article 
PubMed 

Google Scholar 
71.Carballo-Penela, A., Mateo-Mantecón, I., Doménech, J. L. & Coto-Millán, P. From the motorways of the sea to the green corridors’ carbon footprint: the case of a port in Spain. J. Environ. Plan. Manag. 55(6), 765–782. https://doi.org/10.1080/09640568.2011.627422 (2012).Article 

Google Scholar 
72.Paska, J. & Surma, T. Electricity generation from renewable energy sources in Poland. Renew. Energy 71, 286–294 (2014).Article 

Google Scholar 
73.Trujillo-Baute, E., del Río, P. & Mir-Artigues, P. Analysing the impact of renewable energy regulation on retail electricity prices. Energy Policy 114, 153–164 (2018).Article 

Google Scholar 
74.Ruiz-Romero, S., Colmenar-Santos, A., Gil-Ortego, R. & Molina-Bonilla, A. Distributed generation: the definitive boost for renewable energy in Spain. Renew. Energy 53, 354–364 (2013).Article 

Google Scholar 
75.Burgos-Payán, M., Roldán-Fernández, J. M., Trigo-García, Á. L., Bermúdez-Ríos, J. M. & Riquelme-Santos, J. M. Costs and benefits of the renewable production of electricity in Spain. Energy Policy 56, 259–270 (2013).Article 

Google Scholar 
76.Taliotis, C. et al. Renewable energy technology integration for the island of Cyprus: a cost-optimization approach. Energy 137(2017), 31–41. https://doi.org/10.1016/j.energy.2017.07.015 (2017).Article 

Google Scholar 
77.Deyà-Tortella, B., Garcia, C., Nilsson, W. & Tirado, D. The effect of the water tariff structures on the water consumption in Mallorcan hotels. Water Resour. Res. 52(8), 6386–6403. https://doi.org/10.1002/2016WR018621 (2016).ADS 
Article 

Google Scholar 
78.Liu, J. et al. A global and spatially explicit assessment of climate change impacts on crop production and consumptive water use. PLoS ONE https://doi.org/10.1371/journal.pone.0057750 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
79.Hof, A. & Schmitt, T. Urban and tourist land use patterns and water consumption: evidence from Mallorca, Balearic Islands. Land Use Policy 28, 792–804 (2011).Article 

Google Scholar 
80.Urban water consumption in the Balearic islands. The water portal: http://www.caib.es/sites/aigua/es/consumo_agua/81.García, C., Mestre-Runge, C., Morán-Tejeda, E., Lorenzo-Lacruz, J., Tirado, D. (2020). Impact of Cruise Activity on Freshwater Use in the Port of Palma (Mallorca, Spain): Water 12, 1088.82.Yves Tramblay, Aristeidis Koutroulis, Luis Samaniego, Sergio Vicente-Serrano, Florence Volaire, et al. Challenges for drought assessment in the Mediterranean region under future climate scenarios. EarthScience Reviews, Elsevier, 2020, 210, pp.103348. https://doi.org/10.1016/j.earscirev.2020.103348f More

1.DeVries SL, Zhang P. Antibiotics and the Terrestrial Nitrogen Cycle: a review. Curr Pollut Rep. 2016;2:51–67.CAS 
Article 

Google Scholar 
2.Kümmerer K. Antibiotics in the aquatic environment – A review – Part I. Chemosphere. 2009;75:417–34.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
3.Franklin AM, Aga DS, Cytryn E, Durso LM, McLain JE, Pruden A, et al. Antibiotics in Agroecosystems: introduction to the Special Section. J Environ Qual. 2016;45:377–93.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
4.Roose-Amsaleg C, Laverman AM. Do antibiotics have environmental side-effects? Impact of synthetic antibiotics on biogeochemical processes. Environ Sci Pollut Res. 2016;23:4000–12.CAS 
Article 

Google Scholar 
5.Grenni P, Ancona V, Barra, Caracciolo A. Ecological effects of antibiotics on natural ecosystems: a review. Microchemical J. 2018;136:25–39.CAS 
Article 

Google Scholar 
6.Chee-Sanford JC, Mackie RI, Koike S, Krapac IG, Lin Y-F, Yannarell AC, et al. Fate and Transport of Antibiotic Residues and Antibiotic Resistance Genes following Land Application of Manure Waste. J Environ Qual. 2009;38:1086.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
7.Mehrtens A, Licha T, Broers HP, Burke V. Tracing veterinary antibiotics in the subsurface – A long-term field experiment with spiked manure. Environ Pollut. 2020;265:114930.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
8.Kivits T, Broers HP, Beeltje H, van Vliet M, Griffioen J. Presence and fate of veterinary antibiotics in age-dated groundwater in areas with intensive livestock farming. Environ Pollut. 2018;241:988–98.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
9.Gros M, Mas-Pla J, Boy-Roura M, Geli I, Domingo F, Petrović M. Veterinary pharmaceuticals and antibiotics in manure and slurry and their fate in amended agricultural soils: Findings from an experimental field site (Baix Empordà, NE Catalonia). Sci Total Environ. 2019;654:1337–49.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
10.Baquero F, Negri M-C. Challenges: selective compartments for resistant microorganisms in antibiotic gradients. BioEssays. 1997;19:731–6.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
11.Hermsen R, Deris JB, Hwa T. On the rapidity of antibiotic resistance evolution facilitated by a concentration gradient. Proc Natl Acad Sci. 2012;109:10775–80.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
12.Andersson DI, Hughes D. Microbiological effects of sublethal levels of antibiotics. Nat Rev Microbiol. 2014;12:465–78.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
13.Levin-Reisman I, Ronin I, Gefen O, Braniss I, Shoresh N, Balaban NQ. Antibiotic tolerance facilitates the evolution of resistance. Science. 2017;355:826–30.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
14.Cohen NR, Lobritz MA, Collins JJ. Microbial Persistence and the Road to Drug Resistance. Cell Host Microbe. 2013;13:632–42.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
15.Hughes D, Andersson DI. Environmental and genetic modulation of the phenotypic expression of antibiotic resistance. FEMS Microbiol Rev. 2017;41:374–91.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
16.Venter H, Arzanlou M, Chai WC, Venter H. Intrinsic, adaptive and acquired antimicrobial resistance in Gram-negative bacteria. Essays Biochem. 2017;61:49–59.PubMed 
Article 
PubMed Central 

Google Scholar 
17.Alcalde RE, Michelson K, Zhou L, Schmitz EV, Deng J, Sanford RA, et al. Motility of Shewanella oneidensis MR-1 Allows for Nitrate Reduction in the Toxic Region of a Ciprofloxacin Concentration Gradient in a Microfluidic Reactor. Environ Sci Technol. 2019;53:2778–87.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
18.Hol FJH, Hubert B, Dekker C, Keymer JE. Density-dependent adaptive resistance allows swimming bacteria to colonize an antibiotic gradient. ISME J. 2016;10:30–38.CAS 
PubMed 
Article 
PubMed Central 

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

Google Scholar 
20.Steel H, Papachristodoulou A. The effect of spatiotemporal antibiotic inhomogeneities on the evolution of resistance. J Theor Biol. 2020;486:110077.PubMed 
Article 
PubMed Central 

Google Scholar 
21.Lai S, Tremblay J, Déziel E. Swarming motility: a multicellular behaviour conferring antimicrobial resistance. Environ Microbiol. 2009;11:126–36.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
22.Zhang Q, Lambert G, Liao D, Kim H, Robin K, Tung C-k, et al. Acceleration of Emergence of Bacterial Antibiotic Resistance in Connected Microenvironments. Science. 2011;333:1764–7.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
23.Wu A, Loutherback K, Lambert G, Estevez-Salmeron L, Tlsty TD, Austin RH, et al. Cell motility and drug gradients in the emergence of resistance to chemotherapy. Proc Natl Acad Sci. 2013;110:16103–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
24.Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, et al. Spatiotemporal microbial evolution on antibiotic landscapes. Science. 2016;353:1147–51.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
25.Alexandre G, Greer-Phillips S, Zhulin IB. Ecological role of energy taxis in microorganisms. FEMS Microbiol Rev. 2004;28:113–26.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
26.Fenchel T. Microbial Behavior in a Heterogeneous World. Science. 2002;296:1068–71.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
27.Groh JL, Luo Q, Ballard JD, Krumholz LR. Genes That Enhance the Ecological Fitness of Shewanella oneidensis MR-1 in Sediments Reveal the Value of Antibiotic Resistance. Appl Environ Microbiol. 2007;73:492–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
28.Blair JM, Piddock LJ. Structure, function and inhibition of RND efflux pumps in Gram-negative bacteria: an update. Curr Opin Microbiol. 2009;12:512–9.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
29.Fernández L, Hancock REW. Adaptive and mutational resistance: role of porins and efflux pumps in drug resistance. Clin Microbiol Rev. 2012;25:661–81.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
30.Alvarez-Ortega C, Olivares J, Martinez JL. RND multidrug efflux pumps: what are they good for? Front Microbiol. 2013;4:7.PubMed 
PubMed Central 
Article 

Google Scholar 
31.Anes J, McCusker MP, Fanning S, Martins M. The ins and outs of RND efflux pumps in Escherichia coli. Front Microbiol. 2015;6:587.PubMed 
PubMed Central 
Article 

Google Scholar 
32.Ma D, Alberti M, Lynch C, Nikaido H, Hearst JE. The local repressor AcrR plays a modulating role in the regulation of acrAB genes of Escherichia coli by global stress signals. Mol Microbiol. 1996;19:101–12.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
33.Nies DH. Efflux-mediated heavy metal resistance in prokaryotes. FEMS Microbiol Rev. 2003;27:313–39.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
34.Fraud S, Poole K. Oxidative Stress Induction of the MexXY Multidrug Efflux Genes and Promotion of Aminoglycoside Resistance Development in Pseudomonas aeruginosa. Antimicrobial Agents Chemother. 2011;55:1068–74.CAS 
Article 

Google Scholar 
35.El Garch F, Lismond A, Piddock LJV, Courvalin P, Tulkens PM, Van Bambeke F. Fluoroquinolones induce the expression of patA and patB, which encode ABC efflux pumps in Streptococcus pneumoniae. J Antimicrob Chemother. 2010;65:2076–82.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
36.Zhang L, Mah T-F. Involvement of a Novel Efflux System in Biofilm-Specific Resistance to Antibiotics. J Bacteriol. 2008;190:4447–52.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
37.El Meouche I, Siu Y, Dunlop MJ. Stochastic expression of a multiple antibiotic resistance activator confers transient resistance in single cells. Scientific Rep. 2016;6:1–9.Article 
CAS 

Google Scholar 
38.Frade VMF, Dias M, Teixeira ACSC, Palma MSA, Frade VMF, Dias M. et al. Environmental contamination by fluoroquinolones. Braz J Pharm Sci. 2014;50:41–54.Article 

Google Scholar 
39.Riaz L, Mahmood T, Yang Q, Coyne MS, D’Angelo E. Bacteria-assisted removal of fluoroquinolones from wheat rhizospheres in an agricultural soil. Chemosphere. 2019;226:8–16.CAS 
PubMed 
Article 

Google Scholar 
40.Llanes C, Köhler T, Patry I, Dehecq B, Delden C, van, Plésiat P. Role of the MexEF-OprN Efflux System in Low-Level Resistance of Pseudomonas aeruginosa to Ciprofloxacin. Antimicrobial Agents Chemother. 2011;55:5676–84.CAS 
Article 

Google Scholar 
41.Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
42.Deatherage DE, Barrick JE. Identification of mutations in laboratory evolved microbes from next-generation sequencing data using breseq. Methods Mol Biol. 2014;1151:165–88.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
43.Saltikov CW, Newman DK. Genetic identification of a respiratory arsenate reductase. PNAS. 2003;100:10983–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
44.Engler C, Kandzia R, Marillonnet S. A One Pot, One Step, Precision Cloning Method with High Throughput Capability. PLOS ONE. 2008;3:e3647.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
45.European Committee for Antimicrobial Susceptibility Testing (EUCAST) of the European Society of Clinical Microbiology and Infectious Diseases (ESCMID). Determination of minimum inhibitory concentrations (MICs) of antibacterial agents by broth dilution. Clin Microbiol Infect. 2003;9:ix–xv.Article 

Google Scholar 
46.Lambert RJ, Pearson J. Susceptibility testing: accurate and reproducible minimum inhibitory concentration (MIC) and non-inhibitory concentration (NIC) values. J Appl Microbiol. 2000;88:784–90.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
47.Sonnet P, Izard D, Mullié C. Prevalence of efflux-mediated ciprofloxacin and levofloxacin resistance in recent clinical isolates of Pseudomonas aeruginosa and its reversal by the efflux pump inhibitors 1-(1-naphthylmethyl)-piperazine and phenylalanine-arginine-β-naphthylamide. Int J Antimicrobial Agents. 2012;39:77–80.CAS 
Article 

Google Scholar 
48.Lindgren PK, Karlsson Å, Hughes D. Mutation Rate and Evolution of Fluoroquinolone Resistance in Escherichia coli Isolates from Patients with Urinary Tract Infections. Antimicrobial Agents Chemother. 2003;47:3222–32.CAS 
Article 

Google Scholar 
49.Klaus W, Ross A, Gsell B, Senn H. Backbone resonance assignment of the N-terminal 24 kDa fragment of the gyrase B subunit from S. aureus complexed with novobiocin. J Biomol NMR. 2000;16:357–8.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
50.Müller RT, Pos KM. The assembly and disassembly of the AcrAB-TolC three-component multidrug efflux pump. Biol Chem. 2015;396:1083–9.PubMed 
Article 
CAS 
PubMed Central 

Google Scholar 
51.Oethinger M, Podglajen I, Kern WV, Levy SB. Overexpression of the marA or soxS Regulatory Gene in Clinical Topoisomerase Mutants of Escherichia coli. Antimicrob Agents Chemother. 1998;42:2089–94.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
52.Praski Alzrigat L, Huseby DL, Brandis G, Hughes D. Fitness cost constrains the spectrum of marR mutations in ciprofloxacin-resistant Escherichia coli. J Antimicrob Chemother. 2017;72:3016–24.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
53.Srikumar R, Paul CJ, Poole K. Influence of Mutations in the mexR Repressor Gene on Expression of the MexA-MexB-OprM Multidrug Efflux System of Pseudomonas aeruginosa. J Bacteriol. 2000;182:1410–4.CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
54.Sánchez P, Rojo F, Martı́nez JL. Transcriptional regulation of mexR, the repressor of Pseudomonas aeruginosa mexAB-oprM multidrug efflux pump. FEMS Microbiol Lett. 2002;207:63–68.PubMed 
Article 
PubMed Central 

Google Scholar 
55.Fukuda H, Hosaka M, Hirai K, Iyobe S. New norfloxacin resistance gene in Pseudomonas aeruginosa PAO. Antimicrobial Agents Chemother. 1990;34:1757–61.CAS 
Article 

Google Scholar 
56.Fukuda H, Hosaka M, Iyobe S, Gotoh N, Nishino T, Hirai K. nfxC-type quinolone resistance in a clinical isolate of Pseudomonas aeruginosa. Antimicrobial Agents Chemother. 1995;39:790–2.CAS 
Article 

Google Scholar 
57.Fetar H, Gilmour C, Klinoski R, Daigle DM, Dean CR, Poole K. mexEF-oprN Multidrug Efflux Operon of Pseudomonas aeruginosa: Regulation by the MexT Activator in Response to Nitrosative Stress and Chloramphenicol. Antimicrobial Agents Chemother. 2011;55:508–14.CAS 
Article 

Google Scholar 
58.Köhler T, Michea-Hamzehpour M, Plesiat P, Kahr AL, Pechere JC. Differential selection of multidrug efflux systems by quinolones in Pseudomonas aeruginosa. Antimicrob Agents Chemother. 1997;41:2540–3.PubMed 
PubMed Central 
Article 

Google Scholar 
59.Galajda P, Keymer J, Dalland J, Park S, Kou S, Austin R. Funnel ratchets in biology at low Reynolds number: choanotaxis. J Mod Opt. 2008;55:3413–22.CAS 
Article 

Google Scholar 
60.Alcalde-Rico M, Hernando-Amado S, Blanco P, Martínez JL. Multidrug Efflux Pumps at the Crossroad between Antibiotic Resistance and Bacterial Virulence. Front Microbiol. 2016;7:1483.PubMed 
PubMed Central 
Article 

Google Scholar 
61.Lomovskaya O, Warren MS, Lee A, Galazzo J, Fronko R, Lee M, et al. Identification and Characterization of Inhibitors of Multidrug Resistance Efflux Pumps in Pseudomonas aeruginosa: novel Agents for Combination Therapy. Antimicrobial Agents Chemother. 2001;45:105–16.CAS 
Article 

Google Scholar 
62.Pannek S, Higgins PG, Steinke P, Jonas D, Akova M, Bohnert JA, et al. Multidrug efflux inhibition in Acinetobacter baumannii: comparison between 1-(1-naphthylmethyl)-piperazine and phenyl-arginine-beta-naphthylamide. J Antimicrob Chemother. 2006;57:970–4.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
63.Deng J, Zhou L, Sanford RA, Shechtman LA, Dong Y, Alcalde RE, et al. Adaptive Evolution of Escherichia coli to Ciprofloxacin in Controlled Stress Environments: Contrasting Patterns of Resistance in Spatially Varying versus Uniformly Mixed Concentration Conditions. Environ Sci Technol. 2019;53:7996–8005.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
64.Olivares J, Álvarez-Ortega C, Martinez JL. Metabolic Compensation of Fitness Costs Associated with Overexpression of the Multidrug Efflux Pump MexEF-OprN in Pseudomonas aeruginosa. Antimicrob Agents Chemother. 2014;58:3904–13.PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
65.Barbosa TM, Levy SB. The impact of antibiotic use on resistance development and persistence. Drug Resist Updates. 2000;3:303–11.Article 

Google Scholar 
66.Chia HE, Marsh ENG, Biteen JS. Extending fluorescence microscopy into anaerobic environments. Curr Opin Chem Biol. 2019;51:98–104.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
67.Laverman AM, Cazier T, Yan C, Roose-Amsaleg C, Petit F, Garnier J, et al. Exposure to vancomycin causes a shift in the microbial community structure without affecting nitrate reduction rates in river sediments. Environ Sci Pollut Res. 2015;22:13702–9.CAS 
Article 

Google Scholar 
68.Li J, Romine MF, Ward MJ. Identification and analysis of a highly conserved chemotaxis gene cluster in Shewanella species. FEMS Microbiol Lett. 2007;273:180–6.CAS 
PubMed 
Article 
PubMed Central 

Google Scholar  More

1.Parmesan, C. & Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 421, 37–42 (2003).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
2.Cohen, J. M., Lajeunesse, M. J. & Rohr, J. R. A global synthesis of animal phenological responses to climate change. Nat. Clim. Change 8, 224–228 (2018).Article 

Google Scholar 
3.Thackeray, S. J. et al. Phenological sensitivity to climate across taxa and trophic levels. Nature 535, 241–245 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
4.Both, C., van Asch, M., Bijlsma, R. G., van den Burg, A. B. & Visser, M. E. Climate change and unequal phenological changes across four trophic levels: constraints or adaptations? J. Anim. Ecol. 78, 73–83 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
5.Visser, M. E., van Noordwijk, A. J., Tinbergen, J. M. & Lessells, C. M. Warmer springs lead to mistimed reproduction in great tits (Parus major). Proc. R. Soc. B 265, 1867–1870 (1998).Article 

Google Scholar 
6.Stenseth, N. C. & Mysterud, A. Climate, changing phenology, and other life history traits: nonlinearity and match–mismatch to the environment. Proc. Natl Acad. Sci. USA 99, 13379–13381 (2002).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
7.Blackford, C., Germain, R. M. & Gilbert, B. Species differences in phenology shape coexistence. Am. Nat. 195, E168–E180 (2020).PubMed 
Article 
PubMed Central 

Google Scholar 
8.Møller, A. P., Rubolini, D. & Lehikoinen, E. Populations of migratory bird species that did not show a phenological response to climate change are declining. Proc. Natl Acad. Sci. USA 105, 16195–16200 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
9.Rudolf, V. H. W. The role of seasonal timing and phenological shifts for species coexistence. Ecol. Lett. 22, 1324–1338 (2019).PubMed 
PubMed Central 

Google Scholar 
10.Mynott, J. Birds in the Ancient World: Winged Words (Oxford Univ. Press, 2018).11.Hurlbert, A. H. & Liang, Z. Spatiotemporal variation in avian migration phenology: citizen science reveals effects of climate change. PLoS ONE 7, e31662 (2012).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
12.Mayor, S. J. et al. Increasing phenological asynchrony between spring green-up and arrival of migratory birds. Sci. Rep. 7, 1902 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
13.Horton, K. G. et al. Phenology of nocturnal avian migration has shifted at the continental scale. Nat. Clim. Change 10, 63–68 (2020).Article 

Google Scholar 
14.Rosenberg, K. V. et al. Decline of the North American avifauna. Science 366, 120–124 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
15.Sullivan, B. L. et al. The eBird enterprise: an integrated approach to development and application of citizen science. Biol. Conserv. 169, 31–40 (2014).Article 

Google Scholar 
16.Friedl, M., Gray, J. & Sulla-Menashe, D. MCD12Q2 MODIS/Terra+Aqua Land Cover Dynamics Yearly L3 Global 500m SIN Grid v.6 (NASA EOSDIS Land Processes DAAC, accessed 26 March 2020); https://doi.org/10.5067/MODIS/MCD12Q2.00617.Richardson, A. D., Hufkens, K., Milliman, T. & Frolking, S. Intercomparison of phenological transition dates derived from the PhenoCam Dataset V1.0 and MODIS satellite remote sensing. Sci. Rep. 8, 5679 (2018).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
18.Cole, E. F., Long, P. R., Zelazowski, P., Szulkin, M. & Sheldon, B. C. Predicting bird phenology from space: satellite-derived vegetation green-up signal uncovers spatial variation in phenological synchrony between birds and their environment. Ecol. Evol. 5, 5057–5074 (2015).PubMed 
PubMed Central 
Article 

Google Scholar 
19.Pettorelli, N. et al. The normalized difference vegetation index (NDVI): unforeseen successes in animal ecology. Clim. Res. 46, 15–27 (2011).Article 

Google Scholar 
20.Winger, B. M., Auteri, G. G., Pegan, T. M. & Weeks, B. C. A long winter for the Red Queen: rethinking the evolution of seasonal migration. Biol. Rev. 94, 737–752 (2019).21.Åkesson, S. et al. Timing avian long-distance migration: from internal clock mechanisms to global flights. Philos. Trans. R. Soc. B 372, 20160252 (2017).Article 

Google Scholar 
22.Helm, B. et al. Two sides of a coin: ecological and chronobiological perspectives of timing in the wild. Philos. Trans. R. Soc. B 372, 20160246 (2017).Article 

Google Scholar 
23.Haest, B., Hüppop, O. & Bairlein, F. The influence of weather on avian spring migration phenology: what, where and when? Glob. Change Biol. 24, 5769–5788 (2018).Article 

Google Scholar 
24.Studds, C. E. & Marra, P. P. Rainfall-induced changes in food availability modify the spring departure programme of a migratory bird. Proc. R. Soc. B 278, 3437–3443 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
25.Thorup, K. et al. Resource tracking within and across continents in long-distance bird migrants. Sci. Adv. 3, e1601360 (2017).PubMed 
PubMed Central 
Article 

Google Scholar 
26.Post, E., Steinman, B. A. & Mann, M. E. Acceleration of phenological advance and warming with latitude over the past century. Sci. Rep. 8, 3927 (2018).27.Van der Graaf, A., Stahl, J., Klimkowska, A., Bakker, J. P. & Drent, R. H. Surfing on a green wave—how plant growth drives spring migration in the Barnacle Goose Branta leucopsis. Ardea Wagening. 94, 567 (2006).
Google Scholar 
28.Schmaljohann, H. & Both, C. The limits of modifying migration speed to adjust to climate change. Nat. Clim. Change 7, 573–576 (2017).Article 

Google Scholar 
29.Marra, P. P., Francis, C. M., Mulvihill, R. S. & Moore, F. R. The influence of climate on the timing and rate of spring bird migration. Oecologia 142, 307–315 (2005).PubMed 
Article 
PubMed Central 

Google Scholar 
30.Zurell, D., Gallien, L., Graham, C. H. & Zimmermann, N. E. Do long-distance migratory birds track their niche through seasons? J. Biogeogr. 45, 1459–1468 (2018).Article 

Google Scholar 
31.Horton, K. G. et al. Holding steady: little change in intensity or timing of bird migration over the Gulf of Mexico. Glob. Change Biol. 25, 1106–1118 (2019).Article 

Google Scholar 
32.Charmantier, A. et al. Adaptive phenotypic plasticity in response to climate change in a wild bird population. Science 320, 800–803 (2008).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
33.Curley, S. R., Manne, L. L. & Veit, R. R. Differential winter and breeding range shifts: implications for avian migration distances. Divers. Distrib. 26, 415–425 (2020).Article 

Google Scholar 
34.Root, T. Energy constraints on avian distributions and abundances. Ecology 69, 330–339 (1988).Article 

Google Scholar 
35.La Sorte, F. A., Fink, D., Hochachka, W. M., DeLong, J. P. & Kelling, S. Population-level scaling of avian migration speed with body size and migration distance for powered fliers. Ecology 94, 1839–1847 (2013).PubMed 
Article 
PubMed Central 

Google Scholar 
36.Somveille, M., Manica, A. & Rodrigues, A. S. L. Where the wild birds go: explaining the differences in migratory destinations across terrestrial bird species. Ecography 42, 225–236 (2019).Article 

Google Scholar 
37.Knudsen, E. et al. Challenging claims in the study of migratory birds and climate change. Biol. Rev. 86, 928–946 (2011).PubMed 
Article 
PubMed Central 

Google Scholar 
38.Allstadt, A. J. et al. Spring plant phenology and false springs in the conterminous US during the 21st century. Environ. Res. Lett. 10, 104008 (2015).Article 

Google Scholar 
39.Franks, S. E. et al. The sensitivity of breeding songbirds to changes in seasonal timing is linked to population change but cannot be directly attributed to the effects of trophic asynchrony on productivity. Glob. Change Biol. 24, 957–971 (2018).Article 

Google Scholar 
40.Both, C., Bouwhuis, S., Lessells, C. M. & Visser, M. E. Climate change and population declines in a long-distance migratory bird. Nature 441, 81–83 (2006).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
41.Kharouba, H. M. & Wolkovich, E. M. Disconnects between ecological theory and data in phenological mismatch research. Nat. Clim. Change 10, 406–415 (2020).Article 

Google Scholar 
42.Samplonius, J. M. et al. Strengthening the evidence base for temperature-mediated phenological asynchrony and its impacts. Nat. Ecol. Evol. 5, 155–164 (2021).PubMed 
Article 
PubMed Central 

Google Scholar 
43.Abdala‐Roberts, L. et al. Tri‐trophic interactions: bridging species, communities and ecosystems. Ecol. Lett. 22, 2151–2167 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
44.Burgess, M. D. et al. Tritrophic phenological match–mismatch in space and time. Nat. Ecol. Evol. 2, 970–975 (2018).PubMed 
Article 
PubMed Central 

Google Scholar 
45.Helm, B., Van Doren, B. M., Hoffmann, D. & Hoffmann, U. Evolutionary response to climate change in migratory pied flycatchers. Curr. Biol. 29, 3714–3719 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
46.Newson, S. E. et al. Long-term changes in the migration phenology of UK breeding birds detected by large-scale citizen science recording schemes. Ibis 158, 481–495 (2016).Article 

Google Scholar 
47.Townsend, A. K. et al. The interacting effects of food, spring temperature, and global climate cycles on population dynamics of a migratory songbird. Glob. Change Biol. 22, 544–555 (2016).Article 

Google Scholar 
48.Grüebler, M. U. & Naef-Daenzer, B. Fitness consequences of pre- and post-fledging timing decisions in a double-brooded passerine. Ecology 89, 2736–2745 (2008).PubMed 
Article 
PubMed Central 

Google Scholar 
49.Lany, N. K. et al. Breeding timed to maximumimize reproductive success for a migratory songbird: the importance of phenological asynchrony. Oikos 125, 656–666 (2016).Article 

Google Scholar 
50.Samplonius, J. M. & Both, C. Climate change may affect fatal competition between two bird species. Curr. Biol. 29, 327–331 (2019).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
51.Potvin, D. A., Välimäki, K. & Lehikoinen, A. Differences in shifts of wintering and breeding ranges lead to changing migration distances in European birds. J. Avian Biol. 47, 619–628 (2016).Article 

Google Scholar 
52.Bassett, F. & Cubie, D. Wintering hummingbirds in Alabama and Florida: species diversity, sex and age ratios, and site fidelity. J. Field Ornithol. 80, 154–162 (2009).Article 

Google Scholar 
53.Socolar, J. B., Epanchin, P. N., Beissinger, S. R. & Tingley, M. W. Phenological shifts conserve thermal niches in North American birds and reshape expectations for climate-driven range shifts. Proc. Natl Acad. Sci. USA 114, 12976–12981 (2017).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
54.Chmura, H. E. et al. The mechanisms of phenology: the patterns and processes of phenological shifts. Ecol. Monogr. 89, e01337 (2019).Article 

Google Scholar 
55.Kharouba, H. M. et al. Global shifts in the phenological synchrony of species interactions over recent decades. Proc. Natl Acad. Sci. USA 115, 5211–5216 (2018).CAS 
PubMed 
Article 
PubMed Central 

Google Scholar 
56.Cressie, N., Calder, C. A., Clark, J. S., Hoef, J. M. V. & Wikle, C. K. Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. Ecol. Appl. 19, 553–570 (2009).PubMed 
Article 
PubMed Central 

Google Scholar 
57.Miller-Rushing, A. J., Inouye, D. W. & Primack, R. B. How well do first flowering dates measure plant responses to climate change? The effects of population size and sampling frequency. J. Ecol. 96, 1289–1296 (2008).Article 

Google Scholar 
58.Miller-Rushing, A. J., Lloyd-Evans, T. L., Primack, R. B. & Satzinger, P. Bird migration times, climate change, and changing population sizes. Glob. Change Biol. 14, 1959–1972 (2008).Article 

Google Scholar 
59.Barnes, R. dggridR: Discrete global grids for R. R package version 0.1.12 https://github.com/r-barnes/dggri (2017).60.Data Zone (BirdLife International, 2019); http://datazone.birdlife.org/species/requestdis61.Sulla-Menashe, D. et al. Hierarchical mapping of Northern Eurasian land cover using MODIS data. Remote Sens. Environ. 115, 392–403 (2011).Article 

Google Scholar 
62.Friedl, M. & Sulla-Menashe, D. MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid v.6 (NASA EOSDIS Land Processes DAAC, accessed 26 February 2020); https://doi.org/10.5067/MODIS/MCD12Q2.00663.Wood, S. N. & Augustin, N. H. GAMs with integrated model selection using penalized regression splines and applications to environmental modelling. Ecol. Model. 157, 157–177 (2002).Article 

Google Scholar 
64.Fink, D. et al. Spatiotemporal exploratory models for broad-scale survey data. Ecol. Appl. 20, 2131–2147 (2010).PubMed 
Article 
PubMed Central 

Google Scholar 
65.Wood, S. N. Thin plate regression splines. J. R. Stat. Soc. B 65, 95–114 (2003).Article 

Google Scholar 
66.Lindén, A., Meller, K. & Knape, J. An empirical comparison of models for the phenology of bird migration. J. Avian Biol. 48, 255–265 (2017).Article 

Google Scholar 
67.Goodrich, B., Gabry, J., Ali, I. & Brilleman, S. rstanarm: Bayesian applied regression modeling via Stan. R package version 2.21.1 https://mc-stan.org/rstanarm (2020).68.Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. https://www.jstatsoft.org/v076/i01 (2017).69.Brooks, S. P. & Gelman, A. General methods for monitoring convergence of iterative simulations. J. Comput. Graph. Stat. 7, 434 (1998).
Google Scholar 
70.Besag, J. & Kooperberg, C. On conditional and intrinsic autoregression. Biometrika 82, 733 (1995).
Google Scholar 
71.Banerjee, S., Carlin, B. P. & Gelfand, A. E. Hierarchical Modeling and Analysis for Spatial Data (Chapman & Hall/CRC, 2004).72.Morris, M. et al. Bayesian hierarchical spatial models: implementing the Besag York Mollié model in stan. Spat. Spatiotemporal Epidemiol. 31, 100301 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
73.Stan Development Team. RStan: the R interface to Stan. R package version 2.17.3 http://mc-stan.org (2018).74.R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2019).75.Monnahan, C. C., Thorson, J. T. & Branch, T. A. Faster estimation of Bayesian models in ecology using Hamiltonian Monte Carlo. Methods Ecol. Evol. 8, 339–348 (2017).Article 

Google Scholar 
76.Gabry, J., Simpson, D., Vehtari, A., Betancourt, M. & Gelman, A. Visualization in Bayesian workflow. J. R. Stat. Soc. A 182, 389–402 (2019).Article 

Google Scholar 
77.Gelman, A., Carlin, J. B, Stern, H. S. & Rubin, D. B. Bayesian Data Analysis (Chapman & Hall/CRC, 2014).78.Finley, A. O. Comparing spatially-varying coefficients models for analysis of ecological data with non-stationary and anisotropic residual dependence: spatially-varying coefficients models. Methods Ecol. Evol. 2, 143–154 (2011).Article 

Google Scholar 
79.Stan Modeling Language Users Guide and Reference Manual v. 2.18.0 (Stan Development Team, 2018).80.Menzel, A., von Vopelius, J., Estrella, N., Schleip, C. & Dose, V. Farmers’ annual activities are not tracking the speed of climate change. Clim. Res. 32, 201–207 (2006).
Google Scholar  More

1.Pugh, P. Gelatinous zooplankton: the forgotten fauna. Sci. Prog. 14, 67–78 (1989).
Google Scholar 
2.Robison, B. H. Deep pelagic biology. J. Exp. Mar. Biol. Ecol. 300, 253–272. https://doi.org/10.1016/j.jembe.2004.01.012 (2004).Article 

Google Scholar 
3.Condon, R. H. et al. Questioning the rise of gelatinous zooplankton in the world’s oceans. Bioscience 62, 160–169. https://doi.org/10.1525/bio.2012.62.2.9 (2012).Article 

Google Scholar 
4.Haddock, S. H. D. A golden age of gelata: past and future research on planktonic ctenophores and cnidarians. Hydrobiologia 530, 549–556. https://doi.org/10.1007/s10750-004-2653-9 (2004).Article 

Google Scholar 
5.Lebrato, M. et al. Sinking of gelatinous zooplankton biomass increases deep carbon transfer efficiency globally. Glob. Biogeochem. Cycles 33, 1764–1783. https://doi.org/10.1029/2019GB006265 (2019).ADS 
CAS 
Article 

Google Scholar 
6.Luo, J. Y. et al. Gelatinous zooplankton-mediated carbon flows in the global oceans: a data-driven modeling study. Glob. Biogeochem. Cycles https://doi.org/10.1029/2020GB006704 (2020).Article 

Google Scholar 
7.Lucas, C. H. et al. Gelatinous zooplankton biomass in the global oceans: geographic variation and environmental drivers. Glob. Ecol. Biogeogr. 23, 701–714. https://doi.org/10.1111/geb.12169 (2014).Article 

Google Scholar 
8.Robison, B. H. Conservation of deep pelagic biodiversity. Conserv. Biol. 23, 847–858 (2009).Article 

Google Scholar 
9.Décima, M., Stukel, M. R., López-López, L. & Landry, M. R. The unique ecological role of pyrosomes in the Eastern Tropical Pacific. Limnol. Oceanogr. 64, 728–743. https://doi.org/10.1002/lno.11071 (2019).ADS 
Article 

Google Scholar 
10.Henschke, N. et al. Large vertical migrations of Pyrosoma atlanticum play an important role in active carbon transport. J. Geophys. Res. Biogeosci. https://doi.org/10.1029/2018jg004918 (2019).Article 

Google Scholar 
11.Sutherland, K. R., Sorensen, H. L., Blondheim, O. N., Brodeur, R. D. & Galloway, A. W. E. Range expansion of tropical pyrosomes in the northeast Pacific Ocean. Ecology 99, 2397–2399. https://doi.org/10.1002/ecy.2429 (2018).Article 
PubMed 

Google Scholar 
12.Perissinotto, R., Mayzaud, P., Nichols, P. D. & Labat, J. P. Grazing by Pyrosoma atlanticum (Tunicata, Thaliacea) in the south Indian Ocean. Mar. Ecol. Prog. Ser. 330, 1–11 (2007).ADS 
CAS 
Article 

Google Scholar 
13.van Soest, R. W. M. A monograph of the order Pyrosomatida (Tunicata, Thaliacea). J. Plankton Res. 3, 603–631. https://doi.org/10.1093/plankt/3.4.603 (1981).Article 

Google Scholar 
14.Drits, A. V., Arashkevich, E. G. & Semenova, T. N. Pyrosoma atlanticum (Tunicata, Thaliacea): grazing impact on phytoplankton standing stock and role in organic carbon flux. J. Plankton Res. 14, 799–809. https://doi.org/10.1093/plankt/14.6.799 (1992).Article 

Google Scholar 
15.Lebrato, M. & Jones, D. O. B. Mass deposition event of Pyrosoma atlanticum carcasses off Ivory Coast (West Africa). Limnol. Oceanogr. 54, 1197–1209. https://doi.org/10.4319/lo.2009.54.4.1197 (2009).ADS 
CAS 
Article 

Google Scholar 
16.Lebrato, M. et al. Sinking jelly-carbon unveils potential environmental variability along a continental margin. PLoS ONE 8, e82070. https://doi.org/10.1371/journal.pone.0082070 (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
17.Archer, S. K. et al. Pyrosome consumption by benthic organisms during blooms in the northeast Pacific and Gulf of Mexico. Ecology 99, 981–984. https://doi.org/10.1002/ecy.2097 (2018).Article 
PubMed 

Google Scholar 
18.Harbison, G. R. in The Biology of Pelagic Tunicates (ed Q. Bone) Ch. 12, 186–214 (Oxford University Press, 1998).19.James, G. D. & Stahl, J. C. Diet of southern Buller’s albatross (Diomedea bulleri bulleri) and the importance of fishery discards during chick rearing. NZ J. Mar. Freshwat. Res. 34, 435–454. https://doi.org/10.1080/00288330.2000.9516946 (2000).Article 

Google Scholar 
20.Hedd, A. & Gales, R. The diet of shy albatrosses (Thalassarche cauta) at Albatross Island, Tasmania. J. Zool. 253, 69–90. https://doi.org/10.1017/S0952836901000073 (2001).Article 

Google Scholar 
21.Brodeur, R. et al. An unusual gelatinous plankton event in the NE Pacific: the great pyrosome bloom of 2017. PICES Press 26, 22–27 (2018).
Google Scholar 
22.Childerhouse, S., Dix, B. & Gales, N. Diet of New Zealand sea lions at the Auckland Islands. Wildl. Res. 28, 291–298. https://doi.org/10.1071/WR00063 (2001).Article 

Google Scholar 
23.Lindsay, D., Hunt, J. & Hayashi, K.-I. Associations in the midwater zone: The penaeid shrimp Funchalia sagamiensis FUJINO 1975 and pelagic tunicates (Order: Pyrosomatida). Marine Freshwater Behav. Phys. 34, 157–170. https://doi.org/10.1080/10236240109379069 (2001).Article 

Google Scholar 
24.Andersen, V. in The Biology of Pleagic Tunicates (ed Q. Bone) Ch. 7, 125–137 (Oxford University Press, 1998).25.Madin, L. P. Production, composition and sedimentation of salp fecal pellets in oceanic waters. Mar. Biol. 67, 39–45. https://doi.org/10.1007/BF00397092 (1982).Article 

Google Scholar 
26.Thomsen, P. F. & Willerslev, E. Environmental DNA: an emerging tool in conservation for monitoring past and present biodiversity. Biol. Cons. 183, 4–18. https://doi.org/10.1016/j.biocon.2014.11.019 (2015).Article 

Google Scholar 
27.Andruszkiewicz, E. A. et al. Biomonitoring of marine vertebrates in Monterey Bay using eDNA metabarcoding. PLoS ONE 12, e0176343. https://doi.org/10.1371/journal.pone.0176343 (2017).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
28.Doty, M. S. & Oguri, M. The Island mass effect. ICES J. Mar. Sci. 22, 33–37. https://doi.org/10.1093/icesjms/22.1.33 (1956).Article 

Google Scholar 
29.Gove, J. M. et al. Near-island biological hotspots in barren ocean basins. Nat. Commun. 7, 10581. https://doi.org/10.1038/ncomms10581 (2016).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
30.Faye, S., Lazar, A., Sow, B. & Gaye, A. A model study of the seasonality of sea surface temperature and circulation in the Atlantic North-eastern tropical upwelling system. Front. Phys. https://doi.org/10.3389/fphy.2015.00076 (2015).Article 

Google Scholar 
31.Schütte, F., Brandt, P. & Karstensen, J. Occurrence and characteristics of mesoscale eddies in the tropical northeastern Atlantic Ocean. Ocean Sci. 12, 663–685. https://doi.org/10.5194/os-12-663-2016 (2016).ADS 
Article 

Google Scholar 
32.Gilly, W. F., Beman, J. M., Litvin, S. Y. & Robison, B. H. Oceanographic and biological effects of shoaling of the oxygen minimum zone. Ann. Rev. Mar. Sci. 5, 393–420. https://doi.org/10.1146/annurev-marine-120710-100849 (2013).Article 
PubMed 

Google Scholar 
33.Schütte, F. et al. Characterization of “dead-zone” eddies in the eastern tropical North Atlantic. Biogeosciences 13, 5865–5881. https://doi.org/10.5194/bg-13-5865-2016 (2016).ADS 
Article 

Google Scholar 
34.GEOMAR Helmholtz-Zentrum für Ozeanforschung. CVOO Cape Verde Ocean Observatory, http://cvoo.geomar.de/ (n.d.).35.NASA Goddard Space Flight Center, O. E. L., Ocean Biology Processing Group. Moderate-resolution Imaging Spectroradiometer (MODIS) Aqua Chlorophyll Data. https://doi.org/10.5067/AQUA/MODIS/L3B/CHL/2018 (2019).36.Hoving, H. J. et al. The Pelagic in situ observation system (PELAGIOS) to reveal biodiversity, behavior, and ecology of elusive oceanic fauna. Ocean Sci. 15, 1327–1340. https://doi.org/10.5194/os-15-1327-2019 (2019).ADS 
CAS 
Article 

Google Scholar 
37.Schlining, B. & Stout, N. MBARI’s Video Annotation and reference system. Vol. 2006 (2006).38.O’Loughlin, J. H. et al. Implications of Pyrosoma atlanticum range expansion on phytoplankton standing stocks in the Northern California Current. Prog. Oceanogr. 188, 102424. https://doi.org/10.1016/j.pocean.2020.102424 (2020).Article 

Google Scholar 
39.Al-Mutairi, H. & Landry, M. R. Active export of carbon and nitrogen at Station ALOHA by diel migrant zooplankton. Deep Sea Res. Part II Top. Stud. Ocean. 48, 2083–2103. https://doi.org/10.1016/S0967-0645(00)00174-0 (2001).ADS 
CAS 
Article 

Google Scholar 
40.Mayzaud, P., Boutoute, M., Gasparini, S., Mousseau, L. & Lefevre, D. Respiration in marine zooplankton—the other side of the coin: CO2 production. Limnol. Oceanogr. 50, 291–298. https://doi.org/10.4319/lo.2005.50.1.0291 (2005).ADS 
CAS 
Article 

Google Scholar 
41.GEOMAR Helmholtz-Zentrum für Ozeanforschung, Hissmann, K. & Schauer, J. Manned submersible JAGO. J. Large-Scale Res. Facil. 3, 1–12, https://doi.org/10.17815/jlsrf-3-157 (2017).42.Lavaniegos, B. E. & Ohman, M. D. Long-term changes in pelagic tunicates of the California current. Deep Sea Res. Part II Top. Stud. Ocen. 50, 2473–2498. https://doi.org/10.1016/S0967-0645(03)00132-2 (2003).ADS 
CAS 
Article 

Google Scholar 
43.GEBCO Compilation Group. GEBCO 2019 Grid. https://doi.org/10.5285/836f016a-33be-6ddc-e053-6c86abc0788e (2019).44.Schram, J. B., Sorensen, H. L., Brodeur, R. D., Galloway, A. W. E. & Sutherland, K. R. Abundance, distribution, and feeding ecology of Pyrosoma atlanticum in the Northern California current. Mar. Ecol. Prog. Ser. 651, 97–110 (2020).ADS 
CAS 
Article 

Google Scholar 
45.Goy, J. Vertical migration of zooplankton. Résultats des Campagnes à la mer, GNEXO 13, 71–73 (1977).
Google Scholar 
46.Andersen, V. & Sardou, J. Pyrosoma atlanticum (Tunicata, Thaliacea): diel migration and vertical distribution as a function of colony size. J. Plankton Res. 16, 337–349. https://doi.org/10.1093/plankt/16.4.337 (1994).Article 

Google Scholar 
47.Andersen, V., Sardou, J. & Nival, P. The diel migrations and vertical distributions of zooplankton and micronekton in the Northwestern Mediterranean Sea. 2. Siphonophores, hydromedusae and pyrosomids. J. Plankton Res. 14, 1155–1169. https://doi.org/10.1093/plankt/14.8.1155 (1992).Article 

Google Scholar 
48.Roe, H. S. J. et al. Great Meteor East: a biological characterisation (Wormley, 1987).
Google Scholar 
49.Williamson, C. E., Fischer, J. M., Bollens, S. M., Overholt, E. P. & Breckenridge, J. K. Toward a more comprehensive theory of zooplankton diel vertical migration: Integrating ultraviolet radiation and water transparency into the biotic paradigm. Limnol. Oceanogr. 56, 1603–1623. https://doi.org/10.4319/lo.2011.56.5.1603 (2011).ADS 
Article 

Google Scholar 
50.Bianchi, D., Galbraith, E. D., Carozza, D. A., Mislan, K. A. S. & Stock, C. A. Intensification of open-ocean oxygen depletion by vertically migrating animals. Nat. Geosci. 6, 545–548. https://doi.org/10.1038/ngeo1837 (2013).ADS 
CAS 
Article 

Google Scholar 
51.Purcell, J. et al. in Coastal Hypoxia: Consequences for Living Resources and Ecosystems Vol. 58 77–100 (2001).52.Neitzel, P. The impact of the oxygen minimum zone on the vertical distribution and abundance of gelatinous macrozooplankton in the Eastern Tropical Atlantic, Christian-Albrechts-Universität Kiel, (2017).53.Hoving, H. J. T. et al. In situ observations show vertical community structure of pelagic fauna in the eastern tropical North Atlantic off Cape Verde. Sci. Rep. 10, 21798. https://doi.org/10.1038/s41598-020-78255-9 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
54.Thuesen, E. V. et al. Intragel oxygen promotes hypoxia tolerance of scyphomedusae. J. Exp. Biol. 208, 2475. https://doi.org/10.1242/jeb.01655 (2005).Article 
PubMed 

Google Scholar 
55.Keeling, R. F., Körtzinger, A. & Gruber, N. Ocean deoxygenation in a warming world. Ann. Rev. Mar. Sci. 2, 199–229. https://doi.org/10.1146/annurev.marine.010908.163855 (2009).Article 

Google Scholar 
56.Wiebe, P. H., Madin, L. P., Haury, L. R., Harbison, G. R. & Philbin, L. M. Diel vertical migration by Salpa aspera and its potential for large-scale particulate organic matter transport to the deep-sea. Mar. Biol. 53, 249–255. https://doi.org/10.1007/BF00952433 (1979).Article 

Google Scholar 
57.Ariza, A., Garijo, J. C., Landeira, J. M., Bordes, F. & Hernández-León, S. Migrant biomass and respiratory carbon flux by zooplankton and micronekton in the subtropical northeast Atlantic Ocean (Canary Islands). Prog. Oceanogr. 134, 330–342. https://doi.org/10.1016/j.pocean.2015.03.003 (2015).ADS 
Article 

Google Scholar 
58.Hernández-León, S. et al. Zooplankton and micronekton active flux across the tropical and subtropical Atlantic Ocean. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00535 (2019).Article 

Google Scholar 
59.Kiko, R. et al. Zooplankton-mediated fluxes in the eastern tropical North Atlantic. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.00358 (2020).Article 

Google Scholar 
60.Cascão, I., Domokos, R. K., Lammers, M. O., Santos, R. S. & Silva, M. N. A. Seamount effects on the diel vertical migration and spatial structure of micronekton. Prog. Ocean. 175, 1–13. https://doi.org/10.1016/j.pocean.2019.03.008 (2019).Article 

Google Scholar 
61.Fock, H., Matthiessen, B., Zidowitz, H. & Westernhagen, H. Diel and habitat-dependent resource utilisation of deep-sea fishes at the Great Meteor seamount (subtropical NE Atlantic): niche overlap and support for the sound-scattering layer-interception hypothesis. Mar. Ecol. Progr. Ser. 244, 219–233. https://doi.org/10.3354/meps244219 (2002).ADS 
Article 

Google Scholar 
62.Laval, P. Hyperiid amphipods as crustacean parasitoids associated with gelatinous zooplankton. Oceanogr. Mar. Biol. Annu. Rev. 18, 11–56 (1980).
Google Scholar 
63.Madin, L. P. & Harbison, G. R. The associations of Amphipoda Hyperiidea with gelatinous zooplankton—I Associations with Salpidae. Deep-Sea Res. 24, 449–463. https://doi.org/10.1016/0146-6291(77)90483-0 (1977).ADS 
Article 

Google Scholar 
64.Gasca, R., Hoover, R. & Haddock, S. H. D. New symbiotic associations of hyperiid amphipods (Peracarida) with gelatinous zooplankton in deep waters off California. J. Mar. Biol. Assoc. UK 95, 503–511. https://doi.org/10.1017/S0025315414001416 (2015).Article 

Google Scholar 
65.Harbison, G. R., Biggs, D. C. & Madin, L. P. The associations of Amphipoda Hyperiidea with gelatinous zooplankton—II. Associations with Cnidaria, Ctenophora and Radiolaria. Deep Sea Res. 24, 465–488. https://doi.org/10.1016/0146-6291(77)90484-2 (1977).ADS 
Article 

Google Scholar 
66.Harbison, G. R., Madin, L. P. & Swanberg, N. R. On the natural history and distribution of oceanic ctenophores. Deep-Sea Res. 25, 233–256 (1978).ADS 
Article 

Google Scholar 
67.Laval, P. The barrel of the pelagic amphipod Phronima sedentaria (Forsk.) (Crustacea: hyperiidea). J. Exp. Mar. Biol. Ecol. 33, 187–211. https://doi.org/10.1016/0022-0981(78)90008-4 (1978).Article 

Google Scholar 
68.Desmarest, A.-G. in Dictionnaire des Sciences Naturelles, 28. (ed F.G. Levrault) 138–425 (Paris and Strasbourg, 1823).69.Laval, P. Observations on biology of Phronima curvipes Voss (Amphipoda Hyperidae) and description of adult male. Cah. Biol. Mar. 9, 347–362 (1968).
Google Scholar 
70.Janssen, J. & Harbison, G. R. Fish in Salps: the Association of Squaretails (Tetragonurus Spp) with Pelagic Tunicates. J. Mar. Biol. Assoc. UK. 61, 917–927. https://doi.org/10.1017/S0025315400023055 (1981).Article 

Google Scholar 
71.Choy, C. A., Haddock, S. H. D. & Robison, B. H. Deep pelagic food web structure as revealed by in situ feeding observations. Proc. R. Soc. B Biol. Sci. 284, 20172116. https://doi.org/10.1098/rspb.2017.2116 (2017).Article 

Google Scholar 
72.Robison, B. H., Sherlock, R. E., Reisenbichler, K. R. & McGill, P. R. Running the gauntlet: assessing the threats to vertical migrators. Front. Mar. Sci. https://doi.org/10.3389/fmars.2020.00064 (2020).Article 

Google Scholar 
73.Hoving, H. J., Neitzel, P. & Robison, B. In situ observations lead to the discovery of the large ctenophore Kiyohimea usagi (Lobata: Eurhamphaeidae) in the eastern tropical Atlantic. Zootaxa 4526, 232–238. https://doi.org/10.11646/zootaxa.4526.2.8 (2018).Article 
PubMed 

Google Scholar 
74.Arai, M. N. Predation on pelagic coelenterates: a review. J. Mar. Biol. Assoc. UK. 85, 523–536. https://doi.org/10.1017/S0025315405011458 (2005).Article 

Google Scholar  More