Ecology

(ECHA), E. C. A. Know more about the effects of the chemicals we use in Europe (ECHA/PR/16/01). https://echa.europa.eu/de/-/know-more-about-the-effects-of-the-chemicals-we-use-in-europe (2016).Liu, W. J., Nie, H. X., Liang, D. P., Bai, Y. & Liu, H. W. Phospholipid imaging of zebrafish exposed to fipronil using atmospheric pressure matrix-assisted laser desorption ionization mass spectrometry. Talanta https://doi.org/10.1016/j.talanta.2019.120357 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Sparvero, L. J. et al. Mapping of phospholipids by MALDI imaging (MALDI-MSI): Realities and expectations. Chem. Phys. Lipid. 165, 545–562. https://doi.org/10.1016/j.chemphyslip.2012.06.001 (2012).CAS 
Article 

Google Scholar 
Koizumi, S. et al. Imaging mass spectrometry revealed the production of lyso-phosphatidylcholine in the injured ischemic rat brain. Neuroscience 168(1), 219–225. https://doi.org/10.1016/j.neuroscience.2010.03.056 (2010).CAS 
Article 
PubMed 

Google Scholar 
Hankin, J. A. et al. MALDI mass spectrometric imaging of lipids in rat brain injury models. J. Am. Soc. Mass Spectrom. 22(6), 1014–1021. https://doi.org/10.1007/s13361-011-0122-z (2011).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Zhao, C. et al. MALDI-MS imaging reveals asymmetric spatial distribution of lipid metabolites from bisphenol s-induced nephrotoxicity. Anal. Chem. 90(5), 3196–3204. https://doi.org/10.1021/acs.analchem.7b04540 (2018).CAS 
Article 
PubMed 

Google Scholar 
Barbacci, D. C. et al. Mass spectrometric imaging of ceramide biomarkers tracks therapeutic response in traumatic brain injury. ACS Chem. Neurosci. 8(10), 2266–2274. https://doi.org/10.1021/acschemneuro.7b00189 (2017).CAS 
Article 
PubMed 

Google Scholar 
Rompp, A. et al. Histology by mass spectrometry: Label-free tissue characterization obtained from high-accuracy bioanalytical imaging. Angew. Chem. Int. Ed. 49, 3834–3838. https://doi.org/10.1002/anie.200905559 (2010).CAS 
Article 

Google Scholar 
Zemski Berry, K. A. et al. MALDI imaging of lipid biochemistry in tissues by mass spectrometry. Chem. Rev. 111, 6491–6512. https://doi.org/10.1021/cr200280p (2011).CAS 
Article 

Google Scholar 
Cornett, D. S., Reyzer, M. L., Chaurand, P. & Caprioli, R. M. MALDI imaging mass spectrometry: Molecular snapshots of biochemical systems. Nat. Methods 4, 828–833. https://doi.org/10.1038/nmeth1094 (2007).CAS 
Article 
PubMed 

Google Scholar 
Römpp, A. & Spengler, B. Mass spectrometry imaging with high resolution in mass and space. Histochem. Cell Biol. 139, 759–783. https://doi.org/10.1007/s00418-013-1097-6 (2013).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Monroe, E. B. et al. SIMS and MALDI MS imaging of the spinal cord. Proteomics 8(18), 3746-3754. https://doi.org/10.1002/pmic.200800127 (2008).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Chaurand, P., Cornett, D. S., Angel, P. M. & Caprioli, R. M. From whole-body sections down to cellular level, multiscale imaging of phospholipids by MALDI mass spectrometry. Mol. Cell. Proteom. https://doi.org/10.1074/mcp.O110.004259 (2011).Article 

Google Scholar 
Lee, H.-B. & Peart, T. E. Determination of bisphenol A in sewage effluent and sludge by solid-phase and supercritical fluid extraction and gas chromatography/mass spectrometry. J. AOAC Int. 83, 290–298. https://doi.org/10.1093/jaoac/83.2.290 (2000).CAS 
Article 
PubMed 

Google Scholar 
Desbenoit, N., Walch, A., Spengler, B., Brunelle, A. & Römpp, A. Correlative mass spectrometry imaging, applying time-of-flight secondary ion mass spectrometry and atmospheric pressure matrix-assisted laser desorption/ionization to a single tissue section. Rapid Commun. Mass Spectrometry 32, 159–166. https://doi.org/10.1002/rcm.8022 (2018).ADS 
CAS 
Article 

Google Scholar 
Meding, S. et al. Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging. J. Proteome Res. 11, 1996–2003. https://doi.org/10.1021/pr200784p (2012).CAS 
Article 
PubMed 

Google Scholar 
Ritschar, S. et al. Classification of target tissues of Eisenia fetida using sequential multimodal chemical analysis and machine learning. Histochem. Cell Biol. https://doi.org/10.1007/s00418-021-02037-1 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Altshuler, I. et al. An integrated multi-disciplinary approach for studying multiple stressors in freshwater ecosystems: Daphnia as a model organism. Integr. Comp. Biol. 51(4), 623–633. https://doi.org/10.1093/icb/icr103 (2011).CAS 
Article 
PubMed 

Google Scholar 
Bambino, K. & Chu, J. in Zebrafish at the Interface of Development and Disease Research Vol. 124 Current Topics in Developmental Biology (ed K. C. Sadler) 331–367 (2017).Seda, J. & Petrusek, A. Daphnia as a model organism in limnology and aquatic biology: Introductory remarks. J. Limnol. 70, 337–344. https://doi.org/10.4081/jlimnol.2011.337 (2011).Article 

Google Scholar 
de Souza Anselmo, C., Sardela, V. F., de Sousa, V. P. & Pereira, H. M. G. Zebrafish (Danio rerio): A valuable tool for predicting the metabolism of xenobiotics in humans? Comp. Biochem. Physiol. Part C: Toxicol. Pharmacol. 212, 34–46. https://doi.org/10.1016/j.cbpc.2018.06.005 (2018).CAS 
Article 

Google Scholar 
Panula, P. et al. The comparative neuroanatomy and neurochemistry of zebrafish CNS systems of relevance to human neuropsychiatric diseases. Neurobiol. Dis. 40, 46–57. https://doi.org/10.1016/j.nbd.2010.05.010 (2010).CAS 
Article 
PubMed 

Google Scholar 
Korn, H. & Faber, D. S. The Mauthner cell half a century later: A neurobiological model for decision-making?. Neuron 47, 13–28. https://doi.org/10.1016/j.neuron.2005.05.019 (2005).CAS 
Article 
PubMed 

Google Scholar 
Schirmer, E., Schuster, S. & Machnik, P. Bisphenols exert detrimental effects on neuronal signaling in mature vertebrate brains. Commun. Biol. https://doi.org/10.1038/s42003-021-01966-w (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Flößner, D. Book review: Cladocera: The genus Daphnia (including Daphniopsis). Int. Rev. Hydrobiol. 90, 637. https://doi.org/10.1002/iroh.200590003 (2005).Article 

Google Scholar 
OECD. Test No. 211: Daphnia magna Reproduction Test. (2012).Muyssen, B. T. A. & Janssen, C. R. Multigeneration zinc acclimation and tolerance in Daphnia magna: Implications for water-quality guidelines and ecological risk assessment. Environ. Toxicol. Chem. 20, 2053–2060. https://doi.org/10.1002/etc.5620200926 (2001).CAS 
Article 
PubMed 

Google Scholar 
Blewett, T. A. et al. Sublethal and reproductive effects of acute and chronic exposure to flowback and produced water from hydraulic fracturing on the water flea Daphnia magna. Environ. Sci. Technol. 51, 3032–3039. https://doi.org/10.1021/acs.est.6b05179 (2017).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Yang, J. H., Kim, H. J., Lee, S. M., Kim, B. M. & Seo, Y. R. Cadmium-induced biomarkers discovery and comparative network analysis in Daphnia magna. Mol. Cell. Toxicol. 13, 327–336. https://doi.org/10.1007/s13273-017-0036-3 (2017).CAS 
Article 

Google Scholar 
Ferain, A. et al. Body lipid composition modulates acute cadmium toxicity in Daphnia magna adults and juveniles. Chemosphere 205, 328–338. https://doi.org/10.1016/j.chemosphere.2018.04.091 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Ritschar, S., Narayana, V. K. B., Rabus, M. & Laforsch, C. Uncovering the chemistry behind inducible morphological defences in the crustacean Daphniamagna via micro-Raman spectroscopy. Sci. Rep. 10(1), 22408. https://doi.org/10.1038/s41598-020-79755-4 (2020).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Machnik, P., Schirmer, E., Glück, L. & Schuster, S. Recordings in an integrating central neuron provide a quick way for identifying appropriate anaesthetic use in fish. Sci. Rep. 8, 17541. https://doi.org/10.1038/s41598-018-36130-8 (2018).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Luzio, A. et al. Copper induced upregulation of apoptosis related genes in zebrafish (Danio rerio) gill. Aquat. Toxicol. 128, 183–189. https://doi.org/10.1016/j.aquatox.2012.12.018 (2013).CAS 
Article 
PubMed 

Google Scholar 
Macirella, R. & Brunelli, E. Morphofunctional alterations in zebrafish (Danio rerio) gills after exposure to mercury chloride. Int. J. Mol. Sci. https://doi.org/10.3390/ijms18040824 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Mansouri, B. & Johari, S. A. Effects of short-term exposure to sublethal concentrations of silver nanoparticles on histopathology and electron microscope ultrastructure of zebrafish (Danio rerio) gills. IJT 10, 15–20. https://doi.org/10.32598/IJT.10.1.60.4 (2016).CAS 
Article 

Google Scholar 
Perez, C. J., Tata, A., de Campos, M. L., Peng, C. & Ifa, D. R. Monitoring toxic ionic liquids in zebrafish (Danio rerio) with desorption electrospray ionization mass spectrometry imaging (DESI-MSI). J. Am. Soc. Mass Spectrom. 28, 1136–1148. https://doi.org/10.1007/s13361-016-1515-9 (2017).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Stutts, W. L. et al. Methods for cryosectioning and mass spectrometry imaging of whole-body zebrafish. J. Am. Soc. Mass Spectrom. 31, 768–772. https://doi.org/10.1021/jasms.9b00097 (2020).CAS 
Article 
PubMed 

Google Scholar 
Purves, D. & Williams, S. M. Neuroscience. 2nd edition. Vol. Chapter 11, Vision: The Eye (Sinauer Associates, 2001).
Google Scholar 
Strungaru, S. A. et al. Toxicity and chronic effects of deltamethrin exposure on zebrafish (Danio rerio) as a reference model for freshwater fish community. Ecotoxicol. Environ. Saf. 171, 854–862. https://doi.org/10.1016/j.ecoenv.2019.01.057 (2019).CAS 
Article 
PubMed 

Google Scholar 
Mishra, A. & Devi, Y. Histopathological alterations in the brain (optic tectum) of the fresh water teleost Channa punctatus in response to acute and subchronic exposure to the pesticide Chlorpyrifos. Acta Histochem. 116, 176–181. https://doi.org/10.1016/j.acthis.2013.07.001 (2014).CAS 
Article 
PubMed 

Google Scholar 
Jia, W., Mao, L., Zhang, L., Zhang, Y. & Jiang, H. Effects of two strobilurins (azoxystrobin and picoxystrobin) on embryonic development and enzyme activities in juveniles and adult fish livers of zebrafish (Danio rerio). Chemosphere 207, 573–580. https://doi.org/10.1016/j.chemosphere.2018.05.138 (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Seyoum, A., Pradhan, A., Jass, J. & Olsson, P. E. Perfluorinated alkyl substances impede growth, reproduction, lipid metabolism and lifespan in Daphnia magna. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2020.139682 (2020).Article 
PubMed 

Google Scholar 
Scanlan, L. D. et al. Gene transcription, metabolite and lipid profiling in eco-indicator Daphnia magna indicate diverse mechanisms of toxicity by legacy and emerging flame-retardants. Environ. Sci. Technol. 49, 7400–7410. https://doi.org/10.1021/acs.est.5b00977 (2015).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Heinlaan, M. et al. Changes in the Daphnia magna midgut upon ingestion of copper oxide nanoparticles: A transmission electron microscopy study. Water Res. 45, 179–190. https://doi.org/10.1016/j.watres.2010.08.026 (2011).CAS 
Article 
PubMed 

Google Scholar 
Abe, T., Saito, H., Niikura, Y., Shigeoka, T. & Nakano, Y. Embryonic development assay with Daphnia magna: Application to toxicity of aniline derivatives. Chemosphere 45, 487–495. https://doi.org/10.1016/s0045-6535(01)00049-2 (2001).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Sengupta, N., Gerard, P. D. & Baldwin, W. S. Perturbations in polar lipids, starvation survival and reproduction following exposure to unsaturated fatty acids or environmental toxicants in Daphnia magna. Chemosphere 144, 2302–2311. https://doi.org/10.1016/j.chemosphere.2015.11.015 (2016).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Huber, K. et al. Approaching cellular resolution and reliable identification in mass spectrometry imaging of tryptic peptides. Anal. Bioanal. Chem. 410, 5825–5837. https://doi.org/10.1007/s00216-018-1199-z (2018).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
White, R. M. et al. Transparent adult zebrafish as a tool for in vivo transplantation analysis. Cell Stem Cell 2, 183–189. https://doi.org/10.1016/j.stem.2007.11.002 (2008).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Nagayoshi, S. et al. Insertional mutagenesis by the Tol2 transposon-mediated enhancer trap approach generated mutations in two developmental genes: tcf7 and synembryn-like. Development 135, 159–169. https://doi.org/10.1242/dev.009050 (2008).CAS 
Article 
PubMed 

Google Scholar 
Perciedu Sert, N. et al. The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research. Exp. Physiol. 105, 1459–1466. https://doi.org/10.1113/EP088870 (2020).Article 

Google Scholar 
Elendt, B. P. Selenium deficiency in Crustacea. Protoplasma 154, 25–33. https://doi.org/10.1007/BF01349532 (1990).CAS 
Article 

Google Scholar 
Sud, M. et al. LMSD: LIPID MAPS structure database. Nucleic Acids Res. 35, D527–D532. https://doi.org/10.1093/nar/gkl838 (2007).CAS 
Article 
PubMed 

Google Scholar 
Race, A. M., Styles, I. B. & Bunch, J. Inclusive sharing of mass spectrometry imaging data requires a converter for all. J. Proteom. 75, 5111–5112. https://doi.org/10.1016/j.jprot.2012.05.035 (2012).CAS 
Article 

Google Scholar 
Robichaud, G., Garrard, K. P., Barry, J. A. & Muddiman, D. C. MSiReader: An open-source interface to view and analyze high resolving power MS imaging files on Matlab platform. J. Am. Soc. Mass Spectrom. 24, 718–721. https://doi.org/10.1007/s13361-013-0607-z (2013).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar  More

Schimel, J. P., Bennett, J. & Fierer, N. Microbial community composition and soil nitrogen cycling: is there really a connection? In Biological Diversity and Function in Soils Ecological Reviews (eds Bardgett, R. et al.) 171–188 (Cambridge University Press, 2005).
Google Scholar 
Hatzenpichler, R. Diversity, physiology, and niche differentiation of ammonia-oxidizing archaea. Appl. Environ. Microbiol. 78, 7501–7510 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Kowalchuk, G. A. & Stephen, J. R. Ammonia-oxidizing bacteria: A model for molecular microbial ecology. Annu. Rev. Microbiol. 55, 485–529 (2001).CAS 
PubMed 

Google Scholar 
Daims, H. et al. Complete nitrification by Nitrospira bacteria. Nature 528, 504–509 (2015).CAS 
PubMed 
PubMed Central 

Google Scholar 
Shi, X. et al. Niche separation of comammox Nitrospira and canonical ammonia oxidizers in an acidic subtropical forest soil under long-term nitrogen deposition. Soil Biol. Biochem. 126, 114–122 (2018).CAS 

Google Scholar 
van Kessel, M. A. H. J. et al. Complete nitrification by a single microorganism. Nature 528, 555–559 (2015).PubMed 
PubMed Central 

Google Scholar 
Wang, X. et al. Comammox bacterial abundance, activity, and contribution in agricultural rhizosphere soils. Sci. Total Environ. 727, 138563 (2020).CAS 
PubMed 

Google Scholar 
Wang, F., Liang, X., Ma, S., Liu, L. & Wang, J. Ammonia-oxidizing archaea are dominant over comammox in soil nitrification under long-term nitrogen fertilization. J. Soils Sediments 21, 1800–1814 (2021).CAS 

Google Scholar 
Rotthauwe, J.-H., Witzel, K.-P. & Liesack, W. The ammonia monooxygenase structural gene amoA as a functional marker: Molecular fine-scale analysis of natural ammonia-oxidizing populations. Appl. Environ. Microbiol. 63, 4704–4712 (1997).CAS 
PubMed 
PubMed Central 

Google Scholar 
Spang, A. et al. Distinct gene set in two different lineages of ammonia-oxidizing archaea supports the phylum Thaumarchaeota. Trends Microbiol. 18, 331–340 (2010).CAS 
PubMed 

Google Scholar 
Schleper, C. & Nicol, G. W. Ammonia-oxidising archaea—Physiology, ecology and evolution. Adv. Microb. Physiol. 57, 1–41 (2010).CAS 
PubMed 

Google Scholar 
Prosser, J. I. & Nicol, G. W. Archaeal and bacterial ammonia-oxidisers in soil: The quest for niche specialisation and differentiation. Trends Microbiol. 20, 523–531 (2012).CAS 
PubMed 

Google Scholar 
Amin, S. A. et al. Copper requirements of the ammonia-oxidizing archaeon Nitrosopumilus maritimus SCM1 and implications for nitrification in the marine environment. Limnol. Oceanogr. 58, 2037–2045 (2013).CAS 

Google Scholar 
Jenkins, S. N., Murphy, D. V., Waite, I. S., Rushton, S. P. & O’Donnell, A. G. Ancient landscapes and the relationship with microbial nitrification. Sci. Rep. 6, 30733 (2016).CAS 
PubMed 
PubMed Central 

Google Scholar 
Gubry-Rangin, C. et al. Niche specialization of terrestrial archaeal ammonia oxidizers. Proc. Natl. Acad. Sci. U.S.A. 108, 21206–21211 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Lehtovirta-Morley, L. E., Stoecker, K., Vilcinskas, A., Prosser, J. I. & Nicol, G. W. Cultivation of an obligate acidophilic ammonia oxidizer from a nitrifying acid soil. Proc. Natl. Acad. Sci. U.S.A. 108, 15892–15897 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Banning, N. C., Maccarone, L. D., Fisk, L. M. & Murphy, D. V. Ammonia-oxidising bacteria not archaea dominate nitrification activity in semi-arid agricultural soil. Sci. Rep. 5, 11146 (2015).PubMed 
PubMed Central 

Google Scholar 
Di, H. J. et al. Ammonia-oxidizing bacteria and archaea grow under contrasting soil nitrogen conditions. FEMS Microbiol. Ecol. 72, 386–394 (2010).CAS 
PubMed 

Google Scholar 
Wang, J., Wang, J., Rhodes, G., He, J. Z. & Ge, Y. Adaptive responses of comammox Nitrospira and canonical ammonia oxidizers to long-term fertilizations: Implications for the relative contributions of different ammonia oxidizers to soil nitrogen cycling. Sci. Total Environ. 668, 224–233 (2019).CAS 
PubMed 

Google Scholar 
Ouyang, Y., Evans, S. E., Friesen, M. L. & Tiemann, L. K. Effect of nitrogen fertilization on the abundance of nitrogen cycling genes in agricultural soils: A meta-analysis of field studies. Soil Biol. Biochem. 127, 71–78 (2018).CAS 

Google Scholar 
Verhamme, D. T., Prosser, J. I. & Nicol, G. W. Ammonia concentration determines differential growth of ammonia-oxidising archaea and bacteria in soil microcosms. ISME J. 5, 1067–1071 (2011).CAS 
PubMed 
PubMed Central 

Google Scholar 
Wardle, D. A. Controls of temporal variability of the soil microbial biomass: A global-scale synthesis. Soil Biol. Biochem. 30, 1627–1637 (1998).CAS 

Google Scholar 
Adair, K. L. & Schwartz, E. Evidence that ammonia-oxidizing archaea are more abundant than ammonia-oxidizing bacteria in semiarid soils of northern Arizona, USA. Microb. Ecol. 56, 420–426 (2008).CAS 
PubMed 

Google Scholar 
Taylor, A. E., Zeglin, L. H., Wanzek, T. A., Myrold, D. D. & Bottomley, P. J. Dynamics of ammonia-oxidizing archaea and bacteria populations and contributions to soil nitrification potentials. ISME J. 6, 2024–2032 (2012).CAS 
PubMed 
PubMed Central 

Google Scholar 
Hayatsu, M., Katsuyama, C. & Tago, K. Overview of recent researches on nitrifying microorganisms in soil. Soil Sci. Plant Nutr. 67, 1–14 (2021).
Google Scholar 
Sher, Y., Zaady, E. & Nejidat, A. Spatial and temporal diversity and abundance of ammonia oxidizers in semi-arid and arid soils: Indications for a differential seasonal effect on archaeal and bacterial ammonia oxidizers. FEMS Microbiol. Ecol 86, 544–556 (2013).CAS 
PubMed 

Google Scholar 
Stopnišek, N. et al. Thaumarchaeal ammonia oxidation in an acidic forest peat soil is not influenced by ammonium amendment. Appl. Environ. Microbiol. 76, 7626–7634 (2010).PubMed 
PubMed Central 

Google Scholar 
Habteselassie, M. Y., Xu, L. & Norton, J. M. Ammonia-oxidizer communities in an agricultural soil treated with contrasting nitrogen sources. Front. Microbiol. 4, 326 (2013).PubMed 
PubMed Central 

Google Scholar 
Wang, C. et al. Climate change amplifies gross nitrogen turnover in montane grasslands of Central Europe in both summer and winter seasons. Glob. Change Biol. 22, 2963–2978 (2016).
Google Scholar 
Wessén, E., Nyberg, K., Jansson, J. K. & Hallin, S. Responses of bacterial and archaeal ammonia oxidizers to soil organic and fertilizer amendments under long-term management. Appl. Soil Ecol. 45, 193–200 (2010).
Google Scholar 
Kong, A. Y. Y., Hristova, K., Scow, K. M. & Six, J. Impacts of different N management regimes on nitrifier and denitrifier communities and N cycling in soil microenvironments. Soil Biol. Biochem. 42, 1523–1533 (2010).CAS 
PubMed 
PubMed Central 

Google Scholar 
Harrison, P. & Pearce, F. AAAS Atlas of Population & Environment 204 (University of California Press, 2000).
Google Scholar 
Reynolds, J. F., Maestre, F. T., Kemp, P. R., Smith, D. M. S. & Lambin, E. F. Natural and human dimensions of land degradation in drylands: Causes and consequences. In Terrestrial Ecosystems in a Changing World Global Change—The IGBP Series (eds Canadell, J. G. et al.) 247–258 (Springer, 2007).
Google Scholar 
McArthur, W. M. Reference Soils of South-Western Australia 2nd edn. (Department of Agriculture, 2004).
Google Scholar 
Barton, L., Murphy, D. V. & Butterbach-Bahl, K. Influence of crop rotation and liming on greenhouse gas emissions from a semi-arid soil. Agric. Ecosyst. Environ. 167, 23–32 (2013).CAS 

Google Scholar 
Barton, L., Hoyle, F. C., Stefanova, K. T. & Murphy, D. V. Incorporating organic matter alters soil greenhouse gas emissions and increases grain yield in a semi-arid climate. Agric. Ecosyst. Environ. 231, 320–330 (2016).CAS 

Google Scholar 
Gubry-Rangin, C., Nicol, G. W. & Prosser, J. I. Archaea rather than bacteria control nitrification in two agricultural acidic soils. FEMS Microbiol. Ecol. 74, 566–574 (2010).CAS 
PubMed 

Google Scholar 
Gleeson, D. B. et al. Response of ammonia oxidizing archaea and bacteria to changing water filled pore space. Soil Biol. Biochem. 42, 1888–1891 (2010).CAS 

Google Scholar 
O’Sullivan, C. A., Wakelin, S. A., Fillery, I. R. P. & Roper, M. M. Factors affecting ammonia-oxidising microorganisms and potential nitrification rates in southern Australian agricultural soils. Soil Res. 51, 240–252 (2013).
Google Scholar 
Zhang, L.-M., Hu, H.-W., Shen, J.-P. & He, J.-Z. Ammonia-oxidizing archaea have more important role than ammonia-oxidizing bacteria in ammonia oxidation of strongly acidic soils. ISME J. 6, 1032–1045 (2012).CAS 
PubMed 

Google Scholar 
Wang, F. et al. Responses of soil ammonia-oxidizing bacteria and archaea to short-term warming and nitrogen input in a semi-arid grassland on the Loess Plateau. Eur. J. Soil Biol. 102, 103267 (2021).CAS 

Google Scholar 
Bolland, M. D. A. & Brennan, R. F. Phosphorus, copper and zinc requirements of no-till wheat crops and methods of collecting soil samples for soil testing. Aust. J. Exp. Agric. 46, 1051–1059 (2006).CAS 

Google Scholar 
Gilkes, B., Lee, S. & Singh, B. The imprinting of aridity upon a lateritic landscape: An illustration from southwestern Australia. C. R. Geosci. 335, 1207–1218 (2003).
Google Scholar 
Hoyle, F. C. & Murphy, D. V. Influence of organic residues and soil incorporation on temporal measures of microbial biomass and plant available nitrogen. Plant Soil 347, 53–64 (2011).CAS 

Google Scholar 
Noy-Meir, I. Desert ecosystems: Environment and producers. Annu. Rev. Ecol. Syst. 4, 25–51 (1973).
Google Scholar 
Petersen, D. G. et al. Abundance of microbial genes associated with nitrogen cycling as indices of biogeochemical process rates across a vegetation gradient in Alaska. Environ. Microbiol. 14, 993–1008 (2012).CAS 
PubMed 

Google Scholar 
Fisk, L. M., Barton, L., Jones, D. L., Glanville, H. C. & Murphy, D. V. Root exudate carbon mitigates nitrogen loss in a semi-arid soil. Soil Biol. Biochem. 88, 380–389 (2015).CAS 

Google Scholar 
Murphy, D. V., Sparling, G. P., Fillery, I. R. P., McNeill, A. M. & Braunberger, P. Mineralisation of soil organic nitrogen and microbial respiration after simulated summer rainfall events in an agricultural soil. Aust. J. Soil Res. 36, 231–246 (1998).
Google Scholar 
Anderson, G. C., Fillery, I. R. P., Dunin, F. X., Dolling, P. J. & Asseng, S. Nitrogen and water flows under pasture–wheat and lupin–wheat rotations in deep sands in Western Australia 2. Drainage and nitrate leaching. Aust. J. Agric. Res. 49, 345–361 (1998).CAS 

Google Scholar 
Nicholls, N. Local and remote causes of the southern Australian autumn-winter rainfall decline, 1958–2007. Clim. Dyn. 34, 835–845 (2010).
Google Scholar 
Delworth, T. L. & Zeng, F. Regional rainfall decline in Australia attributed to anthropogenic greenhouse gases and ozone levels. Nat. Geosci. 7, 583 (2014).CAS 

Google Scholar 
Alexander, L. V. et al. Trends in Australia’s climate means and extremes: A global context. Aust. Meteorol. Mag. 56, 1–18 (2007).
Google Scholar 
Austin, A. T. et al. Water pulses and biogeochemical cycles in arid and semiarid ecosystems. Oecologia 141, 221–235 (2004).PubMed 

Google Scholar 
Isbell, R. F. The Australian Soil Classification 2nd edn. (CSIRO Publishing, 2002).
Google Scholar 
IUSS Working Group WRB. World Reference Base for Soil Resources 2006, First Update 2007 203 (FAO, 2007).
Google Scholar 
Brookes, P. C., Landman, A., Pruden, G. & Jenkinson, D. S. Chloroform fumigation and the release of soil nitrogen: A rapid direct extraction method to measure microbial biomass nitrogen in soil. Soil Biol. Biochem. 17, 837–842 (1985).CAS 

Google Scholar 
Wu, J., Joergensen, R. G., Pommerening, B., Chaussod, R. & Brookes, P. C. Measurement of soil microbial biomass C by fumigation-extraction—An automated procedure. Soil Biol. Biochem. 22, 1167–1169 (1990).CAS 

Google Scholar 
Krom, M. D. Spectrophotometric determination of ammonia: A study of a modified Berthelot reaction using salicylate and dichloroisocyanurate. Analyst 105, 305–316 (1980).CAS 

Google Scholar 
Kamphake, L. J., Hannah, S. A. & Cohen, J. M. Automated analysis for nitrate by hydrazine reduction. Water Res. 1, 205–216 (1967).CAS 

Google Scholar 
Keeney, D. R. & Bremner, J. M. Comparison and evaluation of laboratory methods of obtaining an index of soil nitrogen availability. Agron. J. 58, 498–503 (1966).CAS 

Google Scholar 
Waring, S. A. & Bremner, J. M. Ammonium production in soil under waterlogged conditions as an index of nitrogen availability. Nature 201, 951–952 (1964).CAS 

Google Scholar 
Griffiths, R. I., Whiteley, A. S., O’Donnell, A. G. & Bailey, M. J. Rapid method for coextraction of DNA and RNA from natural environments for analysis of ribosomal DNA- and rRNA-based microbial community composition. Appl. Environ. Microbiol. 66, 5488–5491 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
Francis, C. A., Roberts, K. J., Beman, J. M., Santoro, A. E. & Oakley, B. B. Ubiquity and diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean. Proc. Natl. Acad. Sci. U.S.A. 102, 14683–14688 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
Barton, L., Gleeson, D. B., Maccarone, L. D., Zúñiga, L. P. & Murphy, D. V. Is liming soil a strategy for mitigating nitrous oxide emissions from semi-arid soils? Soil Biol. Biochem. 62, 28–35 (2013).CAS 

Google Scholar 
Akaike, H. Likelihood of a model and information criteria. J. Econom. 16, 3–14 (1981).MATH 

Google Scholar 
Cresswell, H. P. & Hamilton, G. J. Bulk density and pore space relations. In Soil Physical Measurement and Interpretation for Land Evaluation (eds McKenzie, N. et al.) 35–58 (CSIRO Publishing, 2002).
Google Scholar 
Rayment, G. E. & Lyons, D. J. Soil Chemical Methods—Australasia 495 (CSIRO Publishing, 2011).
Google Scholar  More

Meropol, S. B., Haupt, A. A. & Debanne, S. M. Incidence and outcomes of infections caused by multidrug-resistant Enterobacteriaceae in Children, 2007–2015. J. Pediatr. Infect. Dis. Soc. 7, 36–45 (2018).Article 

Google Scholar 
Moxon, C. A. & Paulus, S. Beta-lactamases in Enterobacteriaceae infections in children. J. Infect. 72, S41–S49 (2016).PubMed 
Article 

Google Scholar 
Morrissey, I. et al. A review of ten years of the study for monitoring antimicrobial resistance trends (SMART) from 2002 to 2011. Pharmaceuticals 6, 1335–1346 (2013).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Junnila, J. et al. Changing epidemiology of methicillin-resistant Staphylococcus aureus in a low endemicity area—new challenges for MRSA control. Eur. J. Clin. Microbiol. Infect. Dis. 39, 2299–2307 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Milstone, A. M. et al. Methicillin-resistant Staphylococcus aureus colonization and risk of subsequent infection in critically ill children: Importance of preventing nosocomial methicillin-resistant Staphylococcus aureus transmission. Clin. Infect. Dis. 53, 853–859 (2011).PubMed 
PubMed Central 
Article 

Google Scholar 
Lakhundi, S. & Zhang, K. Methicillin-resistant Staphylococcus aureus: Molecular characterization, evolution, and epidemiology. Clin. Microbiol. Rev. 31, e00020-18 (2018).PubMed 
PubMed Central 
Article 

Google Scholar 
Schlesinger, Y. et al. Methicillin-resistant nasal colonization in children in Jerusalem: Community vs. chronic care institutions. Isr. Med. Assoc. J. 5, 847–851 (2003).PubMed 

Google Scholar 
Liang, B. et al. Active surveillance, drug resistance, and genotypic profiling of Staphylococcus aureus among school-age children in China. Front. Med. 8, 701494 (2021).Article 

Google Scholar 
Del Rosal, T. et al. Staphylococcus aureus nasal colonization in Spanish children. The COSACO Nationwide Surveillance Study. Infect. Drug Resist. 13, 4643–4651 (2020).PubMed 
PubMed Central 
Article 

Google Scholar 
Feudtner, C., Feinstein, J. A., Zhong, W., Hall, M. & Dai, D. Pediatric complex chronic conditions classification system version 2: Updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr. 14, 199 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Climent Alcalá, F. J., García Fernández de Villalta, M., Escosa García, L., Rodríguez Alonso, A. & Albajara Velasco, L. A. Unidad de niños con patología crónica compleja. Un modelo necesario en nuestros hospitales. Anales de Pediatría 88, 12–18 (2018).PubMed 
Article 

Google Scholar 
Gesualdo, F. et al. Methicillin-resistant Staphylococcus aureus nasal colonization in a department of pediatrics: A cross-sectional study. Ital. J. Pediatr. 40, 3 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Yamamoto, M. et al. Effective surveillance to identify the surgical patients carrying methicillin-resistant Staphylococcus aureus on admission in a pediatric ward. Osaka City Med. J. 62, 1–9 (2016).PubMed 

Google Scholar 
Lukac, P. J., Bonomo, R. A. & Logan, L. K. Extended-spectrum-lactamase-producing Enterobacteriaceae in children: Old foe, emerging threat. Clin. Infect. Dis. https://doi.org/10.1093/cid/civ020 (2015).Article 
PubMed 
PubMed Central 

Google Scholar 
Fedler, K. A., Biedenbach, D. J. & Jones, R. N. Assessment of pathogen frequency and resistance patterns among pediatric patient isolates: Report from the 2004 SENTRY Antimicrobial Surveillance Program on 3 continents. Diagn. Microbiol. Infect. Dis. 56, 427–436 (2006).CAS 
PubMed 
Article 

Google Scholar 
Caselli, D. et al. Incidence of colonization and bloodstream infection with carbapenem-resistant Enterobacteriaceae in children receiving antineoplastic chemotherapy in Italy. Infect. Dis. 48, 152–155 (2016).Article 

Google Scholar 
Logan, L. K. et al. Multidrug- and Carbapenem-Resistant Pseudomonas aeruginosa in Children, United States, 1999–2012. JPIDSJ piw064 (2016) https://doi.org/10.1093/jpids/piw064.Flokas, M. E., Alevizakos, M., Shehadeh, F., Andreatos, N. & Mylonakis, E. Extended-spectrum β-lactamase-producing Enterobacteriaceae colonisation in long-term care facilities: A systematic review and meta-analysis. Int. J. Antimicrob. Agents 50, 649–656 (2017).CAS 
PubMed 
Article 

Google Scholar 
Bharadwaj, R. et al. Drug-resistant Enterobacteriaceae colonization is associated with healthcare utilization and antimicrobial use among inpatients in Pune, India. BMC Infect. Dis. 18, 504 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Logan, L. K. Carbapenem-resistant Enterobacteriaceae: An emerging problem in children. Clin. Infect. Dis. 55, 852–859 (2012).CAS 
PubMed 
Article 

Google Scholar 
Badal, R. E. et al. Etiology, extended-spectrum β-lactamase rates and antimicrobial susceptibility of gram-negative bacilli causing intra-abdominal infections in patients in general pediatric and pediatric intensive care units—global data from the Study for Monitoring Antimicrobial Resistance Trends 2008 to 2010. Pediatr. Infect. Dis. J. 32, 636–640 (2013).PubMed 
Article 

Google Scholar 
Wang, Q. et al. Risk factors and clinical outcomes for carbapenem-resistant Enterobacteriaceae nosocomial infections. Eur. J. Clin. Microbiol. Infect. Dis. 35, 1679–1689 (2016).CAS 
PubMed 
Article 

Google Scholar 
Sahbudak Bal, Z. et al. The prospective evaluation of risk factors and clinical influence of carbapenem resistance in children with gram-negative bacteria infection. Am. J. Infect. Control 46, 147–153 (2018).CAS 
PubMed 
Article 

Google Scholar 
Simon, T. D. et al. Pediatric medical complexity algorithm: A new method to stratify children by medical complexity. Pediatrics 133, e1647–e1654 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
Román, F. et al. Characterization of methicillin-resistant Staphylococcus aureus strains colonizing the nostrils of Spanish children. MicrobiologyOpen 10, e1235 (2021).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
EUCAST. European committee on antimicrobial susceptibility testing breakpoint tables for interpretation of MICs and zone diameters. The European Committee on Antimicrobial Susceptibility Testing. (2018).Oteo, J. et al. Prospective multicenter study of carbapenemase-producing Enterobacteriaceae from 83 hospitals in Spain reveals high in vitro susceptibility to colistin and meropenem. Antimicrob. Agents Chemother. 59, 3406–3412 (2015).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Maseda, E. et al. Risk factors for colonization by carbapenemase-producing enterobacteria at admission to a Surgical ICU: A retrospective study. Enferm. Infecc. Microbiol. Clin. 35, 333–337 (2017).PubMed 
Article 

Google Scholar 
Bassetti, M., Nicco, E. & Mikulska, M. Why is community-associated MRSA spreading across the world and how will it change clinical practice?. Int. J. Antimicrob. Agents 34, S15–S19 (2009).CAS 
PubMed 
Article 

Google Scholar 
El Cheikh, M. R., Barbosa, J. M., Caixêta, J. A. S. & Avelino, M. A. G. Microbiology of tracheal secretions: What to expect with children and adolescents with tracheostomies. Int. Arch. Otorhinolaryngol. 22, 50–54 (2018).PubMed 
Article 

Google Scholar 
González-Del Castillo, J. et al. BAHNG score: Predictive model for detection of subjects with the oropharynx colonized by uncommon microorganisms. Rev. Esp Quimioter. 30, 422–428 (2017).PubMed 

Google Scholar 
Hu, X. et al. Risk factors for methicillin-resistant Staphylococcus aureus colonization and infection in patients with human immunodeficiency virus infection: A systematic review and meta-analysis. J. Int. Med. Res. 50, 3000605211063019 (2022).CAS 
PubMed 

Google Scholar 
Gleeson, A., Larkin, P., Walsh, C. & O’Sullivan, N. Methicillin-resistant Staphylococcus aureus: Prevalence, incidence, risk factors, and effects on survival of patients in a specialist palliative care unit: A prospective observational study. Palliat. Med. 30, 374–381 (2016).PubMed 
Article 

Google Scholar 
Hogardt, M. et al. Current prevalence of multidrug-resistant organisms in long-term care facilities in the Rhine-Main district, Germany, 2013. Euro Surveill. 20, 21171 (2015).PubMed 
Article 

Google Scholar 
Warren, D. K. et al. Epidemiology of methicillin-resistant Staphylococcus aureus colonization in a surgical intensive care unit. Infect. Control Hosp. Epidemiol. 27, 1032–1040 (2006).PubMed 
Article 

Google Scholar 
Folgori, L. et al. Healthcare-associated infections in pediatric and neonatal intensive care units: Impact of underlying risk factors and antimicrobial resistance on 30-day case-fatality in Italy and Brazil. Infect. Control Hosp. Epidemiol. 37, 1302–1309 (2016).PubMed 
Article 

Google Scholar 
Béranger, A. et al. Early bacterial infections after pediatric liver transplantation in the era of multidrug-resistant bacteria: Nine-year single-center retrospective experience. Pediatr. Infect. Dis. J. 39, e169–e175 (2020).PubMed 
Article 

Google Scholar 
Bouras, D. et al. Staphylococcus aureus osteoarticular infections in children: An 8-year review of molecular microbiology, antibiotic resistance and clinical characteristics. J. Med. Microbiol. 67, 1753–1760 (2018).MathSciNet 
CAS 
PubMed 
Article 

Google Scholar 
Rodriguez, M., Hogan, P. G., Krauss, M., Warren, D. K. & Fritz, S. A. Measurement and impact of Staphylococcus aureus colonization pressure in households. J. Pediatr. Infect. Dis. Soc. 2, 147–154 (2013).Article 

Google Scholar 
Messina, N. L., Williamson, D. A., Robins-Browne, R., Bryant, P. A. & Curtis, N. Risk factors for carriage of antibiotic-resistant bacteria in healthy children in the community: A systematic review. Pediatr. Infect. Dis. J. 39, 397–405 (2020).PubMed 
Article 

Google Scholar 
Dualleh, N. et al. Colonization with multiresistant bacteria in acute hospital care: The association of prior antibiotic consumption as a risk factor. J. Antimicrob. Chemother. 75, 3675–3681 (2020).CAS 
PubMed 
Article 

Google Scholar 
Daskalaki, M. et al. Panton-Valentine leukocidin-positive Staphylococcus aureus skin and soft tissue infections among children in an emergency department in Madrid, Spain. Clin. Microbiol. Infect. 16, 74–77 (2010).CAS 
PubMed 
Article 

Google Scholar 
Aguilera-Alonso, D., Escosa-García, L., Saavedra-Lozano, J., Cercenado, E. & Baquero-Artigao, F. Carbapenem-resistant gram-negative bacterial infections in children. Antimicrob. Agents Chemother. 64, e02183-e2219 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Phichaphop, C. et al. High prevalence of multidrug-resistant gram-negative bacterial infection following pediatric liver transplantation. Medicine 99, e23169 (2020).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Tacconelli, E. et al. ESCMID guidelines for the management of the infection control measures to reduce transmission of multidrug-resistant Gram-negative bacteria in hospitalized patients. Clin. Microbiol. Infect. 20, 1–55 (2014).PubMed 
Article 

Google Scholar 
McConville, T. H., Sullivan, S. B., Gomez-Simmonds, A., Whittier, S. & Uhlemann, A.-C. Carbapenem-resistant Enterobacteriaceae colonization (CRE) and subsequent risk of infection and 90-day mortality in critically ill patients, an observational study. PLoS ONE 12, e0186195 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Tamma, P. D. et al. The likelihood of developing a carbapenem-resistant Enterobacteriaceae Infection during a hospital stay. Antimicrob. Agents Chemother. 63, e00757-e819 (2019).CAS 
PubMed 
PubMed Central 

Google Scholar 
Detsis, M., Karanika, S. & Mylonakis, E. ICU acquisition rate, risk factors, and clinical significance of digestive tract colonization with extended-spectrum beta-lactamase-producing Enterobacteriaceae: A systematic review and meta-analysis. Crit. Care Med. 45, 705–714 (2017).PubMed 
Article 

Google Scholar  More

The haplotype networks, PCoA analysis and STRUCTURE analysis based on the six nuclear loci confirm that S. longifolium is a hybrid between S. emersum and S. gramineum, providing molecular support for previous morphological analyses5. Furthermore, all individuals with intermediate admixture coefficient (Fig. 2b) and private haplotypes only present in one out of six nuclear loci (Fig. 1) suggest that S. longifolium is most likely a F1 hybrid. We thus hypothesized that S. emersum and S. gramineum could likely maintain their species boundary through the post-zygote reproductive isolation mechanism of F1 generation sterility. This hypothesis is possible based on the observations from hybrids in European Russia. The pollen viability was checked in S. longifolium samples from Vysokovskoe Lake and Sabro Lake, and the vast majority of checked pollens were sterile5. In addition, flowering plants of S. longifolium often do not form seeds, or the seeds are puny and significantly inferior to normal seeds in size5. However, the hypothesis is only based on our limited sampling, which is contrary to the conclusion inferred from morphological characteristics that it is fertile and may backcross with parental species1. Further studies with extensive sampling are necessary to test our hypothesis.The chloroplast DNA fragment trnH-psbA was used to infer the direction of hybridization between S. emersum and S. gramineum because chloroplast DNA is maternal inheritance in Sparganium3,4. The hybrid S. longifolium shared haplotypes with S. emersum and S. gramineum simultaneously (Fig. 1). This finding clearly indicates that bidirectional hybridization exists between S. emersum and S. gramineum. At the same time, the different frequency of these two haplotypes in the hybrid (H1, 19.1% vs. H2, 80.9%) means that the direction of hybridization is asymmetric. A variety of factors can lead to asymmetry in natural hybridization, such as flowering time, preference of pollinators, quality and quantity of pollen, cross incompatibility and the abundance of parent species7,8. Rare species usually act as maternal species relative to abundant species9,10. S. gramineum is confined to oligotrophic lakes and its abundance is obviously lower than that of S. emersum1,11. The relatively scarcity combined with the ecology of S. gramineum make it more often act as maternal species when hybridizing with S. emersum.As described by5, the morphological diversification of S. longifolium was also observed in this study. For example, individuals of S. longifolium with emergent and floating-leaved life forms occur concurrently in Zaozer’ye Lake (Supplementary Fig. S2). However, all individuals had the same haplotype H2 as S. gramineum (Fig. 1), suggesting that the direction of hybridization do not determine life form of S. longifolium. In addition, all individuals of S. longifolium sampled here are likely F1 hybrid. Their variable phenotypes could not be associated with traits segregation due to F2 generation or backcross. Detailed ecological investigation combining with research at the genomic level are essential to find out the potential factors leading to morphological diversification of S. longifolium.Here, using sequences of six nuclear loci and one chloroplast DNA fragment, we confirmed that S. longifolium is the hybrid between S. emersum and S. gramineum. The natural hybridization between S. emersum and S. gramineum is bidirectional but the latter mainly acts as maternal species. We also found that all samples of S. longifolium were F1 generations, indicating that S. emersum and S. gramineum could maintain their species boundary through the post-zygote reproductive isolation mechanism of F1 generation sterility. More

Miyata, T., Miyazawa, S. & Yasunaga, T. Two types of amino acid substitutions in protein evolution. J. Mol. Evol. 12, 219–236 (1979).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Li, W.-H., Wu, C.-I. & Luo, C.-C. A new method for estimating synonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes. Mol. Biol. Evol. 2, 150–174 (1985).PubMed 

Google Scholar 
Bielawski, J. P. & Yang, Z. Positive and negative selection in the DAZ gene family. Mol. Biol. Evol. 18, 523–529 (2001).CAS 
PubMed 
Article 

Google Scholar 
Ohta, T. Slightly deleterious mutant substitutions in evolution. Nature 246, 96–98 (1973).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ohta, T. The nearly neutral theory of molecular evolution. Annu. Rev. Ecol. Evol. Syst. 23, 263–286 (1992).Article 

Google Scholar 
Johnson, K. P. & Seger, J. Elevated rates of nonsynonymous substitution in island birds. Mol. Biol. Evol. 18, 874–881 (2001).CAS 
PubMed 
Article 

Google Scholar 
Woolfit, M. & Bromham, L. Population size and molecular evolution on islands. Proc. Biol. Sci. 272, 2277–2282 (2005).CAS 
PubMed 
PubMed Central 

Google Scholar 
Ross, L., Hardy, N. B., Okusu, A. & Normark, B. B. Large population size predicts the distribution of asexuality in scale insects. Evolution 67, 196–206 (2013).PubMed 
Article 

Google Scholar 
Weber, C. C., Nabholz, B., Romiguier, J. & Ellegren, H. Kr/Kc but not dN/dS correlates positively with body mass in birds, raising implications for inferring lineage-specific selection. Genome Biol. 15, 542 (2014).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Brandt, A. et al. Effective purifying selection in ancient asexual oribatid mites. Nat. Commun. 8, 873 (2017).ADS 
PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Figuet, E. et al. Life history traits, protein evolution, and the nearly neutral theory in amniotes. Mol. Biol. Evol. 33(6), 1517–1527 (2016).CAS 
PubMed 
Article 

Google Scholar 
Saclier, N. et al. Life history traits impact the nuclear rate of substitution but not the mitochondrial rate in isopods. Mol. Biol. Evol. 35, 2900–2912 (2018).CAS 
PubMed 
Article 

Google Scholar 
Hebert, P. D. The Daphnia of North America: An Illustrated Fauna (on CD-ROM) (CyberNatural Software, Guelph, 1995).
Google Scholar 
Colbourne, J. K. et al. Phylogenetics and evolution of a circumarctic species complex (Cladocera: Daphnia pulex). Biol. J. Linn. Soc. 65, 347–365 (1998).
Google Scholar 
Crease, T. J., Omilian, A. R., Costanzo, K. S. & Taylor, D. J. Transcontinental phylogeography of the Daphnia pulex species complex. PLoS ONE 7, e46620 (2012).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Mergeay, J., Verschuren, D. & De Meester, L. Cryptic invasion and dispersal of an American Daphnia in East Africa. Limnol. Oceanogr. 50, 1278–1283 (2005).ADS 
CAS 
Article 

Google Scholar 
Ma, X. et al. Lineage diversity and reproductive modes of the Daphnia pulex group in Chinese lakes and reservoirs. Mol. Phylogenet. Evol. 130, 424–433 (2019).PubMed 
Article 

Google Scholar 
So, M. et al. Invasion and molecular evolution of Daphnia pulex in Japan. Limnol. Oceanogr. 60, 1129–1138 (2015).ADS 
Article 

Google Scholar 
Duggan, I. C. et al. Identifying invertebrate invasions using morphological and molecular analyses: North American Daphnia ‘pulex’ in New Zealand fresh waters. Aquat. Invasions 7, 585–590 (2012).Article 

Google Scholar 
Ye, Z. et al. The rapid, mass invasion of New Zealand by North American Daphnia “pulex”. Limnol. Oceanogr. 66, 2673–2683 (2021).ADS 
Article 

Google Scholar 
Paland, S., Colbourne, J. K. & Lynch, M. Evolutionary history of contagious asexuality in Daphnia pulex. Evolution 59, 800–813 (2005).CAS 
PubMed 
Article 

Google Scholar 
Muller, H. J. The relation of recombination to mutational advance. Mutat. Res. 106, 2–9 (1964).CAS 
PubMed 
Article 

Google Scholar 
Felsenstein, J. The evolutionary advantage of recombination. Genetics 78, 737–756 (1974).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Paland, S. & Lynch, M. Transitions to asexuality result in excess amino acid substitutions. Science 311, 990–992 (2006).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Johnson, S. G. & Howard, R. S. Contrasting patterns of synonymous and nonsynonymous sequence evolution in asexual and sexual freshwater snail lineages. Evolution 61, 2728–2735 (2007).PubMed 
Article 

Google Scholar 
Neiman, M. et al. Accelerated mutation accumulation in asexual lineages of a freshwater snail. Mol. Biol. Evol. 27, 954–963 (2010).CAS 
PubMed 
Article 

Google Scholar 
Henry, L., Schwander, T. & Crespi, B. J. Deleterious mutation accumulation in asexual Timema stick insects. Mol. Biol. Evol. 29, 401–408 (2012).CAS 
PubMed 
Article 

Google Scholar 
Tucker, A. E. et al. Population-genomic insights into the evolutionary origin and fate of obligately asexual Daphnia pulex. Proc. Natl. Acad. Sci. 110, 15740–15745 (2013).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Colbourne, J. K. et al. The ecoresponsive genome of Daphnia pulex. Science 331, 555–561 (2011).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Ye, Z. et al. A new reference genome assembly for the microcrustacean Daphnia pulex. G3 (Bethesda) 7, 1405–1416 (2017).CAS 
Article 

Google Scholar 
Keith, N. et al. High mutational rates of large-scale duplication and deletion in Daphnia pulex. Genome Res. 26, 60–69 (2016).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hall, D. J. An experimental approach to the dynamics of a natural population of Daphnia galeata mendotae. Ecology 45, 94–112 (1964).Article 

Google Scholar 
McCauley, E., Murdoch, W. W. & Nisbet, R. M. Growth, reproduction, and mortality of Daphnia pulex Leydig: Life at low food. Ecology 4, 505–514 (1990).
Google Scholar 
Xu, S. et al. High mutation rates in the mitochondrial genomes of Daphnia pulex. Mol. Biol. Evol. 29, 763–769 (2012).CAS 
PubMed 
Article 

Google Scholar 
Zheng, Y., Peng, R., Kuro-o, M. & Zeng, X. Exploring patterns and extent of bias in estimating divergence time from mitochondrial DNA sequence data in a particular lineage: A case study of salamanders (Order Caudata). Mol. Biol. Evol. 28, 2521–2535 (2011).CAS 
PubMed 
Article 

Google Scholar 
Zaret, T. M. Predation and Freshwater Communities (Yale University Press, New Haven, 1980).
Google Scholar 
Lynch, M. Predation, competition, and zooplankton community structure: An experimental study. Limnol. Oceanogr. 24, 253–272 (1979).ADS 
Article 

Google Scholar 
Mills, E. L. & Forney, J. L. Impact on Daphnia pulex of predation by young yellow perch in Oneida Lake, New York. Trans. Am. Fish. Soc. 112(2A), 154–161 (1983).Article 

Google Scholar 
Craddock, D. R. Effects of increased water temperature on Daphnia pulex. Fish. Bull. 74, 403–408 (1976).
Google Scholar 
Maruoka, N. & Urabe, J. Inter and intraspecific competitive abilities and the distribution ranges of two Daphnia species in Eurasian continental islands. Popul. Ecol. 62, 353–363 (2020).Article 

Google Scholar 
Dodson, S. I. & Hanazato, T. Commentary on effects of anthropogenic and natural organic chemicals on development, swimming behavior, and reproduction of Daphnia, a key member of aquatic ecosystems. Environ. Health Perspect. 103(Suppl 4), 7–11 (1995).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Claska, M. E. & Gilbert, J. J. The effect of temperature on the response of Daphnia to toxic cyanobacteria. Freshw. Biol. 39, 221–232 (1998).Article 

Google Scholar 
Bast, J. et al. Consequences of asexuality in natural populations: Insights from stick insects. Mol. Biol. Evol. 35, 1668–1677 (2018).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hartfield, M. Evolutionary genetic consequences of facultative sex and outcrossing. J Evol Biol 29, 5–22 (2016).CAS 
PubMed 
Article 

Google Scholar 
Hörandl, E. et al. Genome evolution of asexual organisms and the paradox of sex in eukaryotes. In Evolutionary Biology—A Transdisciplinary Approach (ed. Pontarotti, P.) (Springer, Cham, 2020). https://doi.org/10.1007/978-3-030-57246-4_7.Chapter 

Google Scholar 
Lynch, M., Bürger, R., Butcher, D. & Gabriel, W. The mutational meltdown in asexual populations. J. Hered. 84, 339–344 (1993).CAS 
PubMed 
Article 

Google Scholar 
Gordo, I. & Charlesworth, B. The degeneration of asexual haploid populations and the speed of Muller’s ratchet. Genetics 154, 1379–1387 (2000).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Downing, J. A. et al. The global abundance and size distribution of lakes, ponds, and impoundments. Limnol. Oceanogr. 51, 2388–2397 (2006).ADS 
Article 

Google Scholar 
McDonald, C. P., Rover, J. A., Stets, E. G. & Striegl, R. G. The regional abundance and size distribution of lakes and reservoirs in the United States and implications for estimates of global lake extent. Limnol. Oceanogr. 57, 597–606 (2012).ADS 
Article 

Google Scholar 
De Meester, L., Góme, A., Okamura, B. & Schwenk, K. The monopolization hypothesis and the dispersal-gene flow paradox in aquatic organisms. Acta Oecol. 23, 121–135 (2002).ADS 
Article 

Google Scholar 
Fukami, T., Bezemer, T. M., Mortimer, S. R. & Van Der Putten, W. H. Species divergence and trait convergence in experimental plant community assembly. Ecol. Lett. 8, 1283–1290 (2005).Article 

Google Scholar 
Makino, T. & Kawata, M. Invasive invertebrates associated with highly duplicated gene content. Mol. Ecol. 28, 1652–1663 (2019).CAS 
PubMed 
Article 

Google Scholar 
Kondrashov, F. A. Gene duplication as a mechanism of genomic adaptation to a changing environment. Proc. R. Soc. Lond. B Biol. Sci. 279, 5048–5057 (2012).
Google Scholar 
Barrick, J. E. & Lenski, R. E. Genome dynamics during experimental evolution. Nat. Rev. Genet. 14, 827–839 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Rocha, E. P. C. Neutral theory, microbial practice: Challenges in bacterial population genetics. Mol. Biol. Evol. 35, 1338–1347 (2018).CAS 
PubMed 
Article 

Google Scholar 
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30, 772–780 (2013).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Tanabe, A. S. Kakusan4 and Aminosan: Two programs for comparing nonpartitioned, proportional and separate models for combined molecular phylogenetic analyses of multilocus sequence data. Mol. Ecol. Resour. 11, 914–921 (2011).PubMed 
Article 

Google Scholar 
Stamatakis, A. RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312–1313 (2014).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Tian, X., Ohtsuki, H. & Urabe, J. Evolution of asexual Daphnia pulex in Japan: Variations and covariations of the digestive, morphological and life history traits. BMC Evol. Biol. 19, 122 (2019).PubMed 
PubMed Central 
Article 

Google Scholar 
Chen, Y. et al. SOAPnuke: A MapReduce acceleration-supported software for integrated quality control and preprocessing of high-throughput sequencing data. Gigascience 7, 1–6 (2018).ADS 
PubMed 
PubMed Central 

Google Scholar 
Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2019).Article 
CAS 

Google Scholar 
Lee, T. H. et al. SNPhylo: A pipeline to construct a phylogenetic tree from huge SNP data. BMC Genomics 15, 162 (2014).PubMed 
PubMed Central 
Article 

Google Scholar 
R Core Team, R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, Austria, 2019). https://www.R-project.org/ More

Influence of the PLHP on water depth distributionThe hydrodynamic process of Poyang Lake with and without the PLHP is simulated by M1 and M2, respectively. By comparing and analyzing the simulation results, we obtain the changes of the water depth, i.e., the water depth in M2 minus the water depth in M1, in Poyang Lake. Figure 5 shows the mean monthly water depth differences during September and October in three typical years. The water depth in Poyang Lake has increased obviously in most cases after the operation of the project. Combining the water level processes in Fig. 4 and the water depth differences in Fig. 5, the area of the changes in the water depth is seen to be mainly controlled by the Higher Water Levels (HWL) between M1 and M2. While the magnitude of the changes is mainly controlled by the Differences in Water Levels (DWL) between M1 and M2.Figure 5Water depth variation during September and October in the typical years. The figure was generated by Tecplot2020 (https://www.tecplot.com/).Full size imageAs shown in the water level variations processes in Fig. 4a, in the low-water-level year (2006), where the natural inflow is relatively small, the water level in M2 is much higher than that in M1 and reaches the peak value around 10th of October. The DWL also reaches maximum in this time and then gradually decreases. As a consequence, the water depth increases the most in October 2006. As shown in Fig. 5d, in most areas of Poyang Lake, the Xiuhe River and the Ganjiang River, the water depth is increased by more than 1 m. Especially in the main channel from the PLHP to Tangyin and Wucheng, the increase can exceed 4 m, as shown in the red parts in Fig. 5d. While over the surrounding flooded land, the increase ranges from 1 to 3 m. The increase in the water depth during September was essentially the same as that in October, but the area and magnitude of the changes are slightly reduced. The maximum increase is about 3.1 m, which is mainly concentrated in the main channel on the north of Songmen Mountain.In the medium-water-level year (2018), the water level in M1 is constantly lower than that in M2 during September and October, which can be seen in Fig. 4b. Both the HWL and DWL first increase and then decrease, reaching their maximum values in early September and late September, respectively. Furthermore, the mean monthly HWL and DWL in September are slightly greater than those in October. As a consequence, the area and magnitude of the changes in Fig. 5b are larger than those in Fig. 5e. In September 2018, almost the entire main lake region becomes influenced by the PLHP and the increase in water depth ranges from 0 to 3.4 m. While in October 2018, the increase in water depth ranges from 0 to 3.2 m, and the significant increase is mainly concentrated in the main channel on the north of Songmen Mountain.In the high-water-level year (2010), as shown in Fig. 4c, the HWL rises and the DWL decreases as compared to those in other years. During the first 35 days, the hydrodynamic conditions in M2 are exactly the same as that in M1, so the PLHP has no effect on the water depth in the lake region in September (Fig. 5c). However, after the 6th of October, the water level in M2 begins to be higher than that in M1 under the regulation of the PLHP. Although the DWL is small during this time, the HWL is relatively high and thus results in large areas of water depth increase, as shown in Fig. 5f. The maximum increase in water depth is approximately 1.1 m.In these two months, the northeastern parts of the two national nature reserves are observably influenced., The area of the changes is greatest in September 2018, there has been a marked increase in water depth in most areas of the reserves, with the maximum increase reaching about 2.8 m. While in other periods during September and October, with the exception of September 2010, the water depth is increased significantly in about 1/3 ~ 1/2 area of the reserves, with the maximum increase reaching about 2.6 m. In the meantime, the water depth in the southwestern part of these two reserves remains essentially the same as before the operation of the PLHP, with an increase of less than 0.25 m as shown in the grey parts in Fig. 5.Influence of the PLHP on habitat suitability of Vallisneria natansAccording to the relationship between the habitat suitability of Vallisneria natans and the water depth as mentioned in Fig. 3, the water depth results can be translated into the habitat suitability of Vallisneria natans, as shown in Fig. 6. The first and third rows are the distributions of the habitat suitability during September and October, respectively, in the three typical years before the operation of the PLHP, while the second and fourth rows are distributions of the habitat suitability after the operation of the PLHP. The grey parts in Fig. 6 indicate that the habitat suitability is 0, implying that the area is dry or the water depth is greater than 4 m.Figure 6Distributions of the habitat suitability of Vallisneria natans in typical years without (the first and third rows) and with (the second and fourth rows) the PLHP. The figure was generated by Tecplot2020 (https://www.tecplot.com/).Full size imageAs shown in Fig. 6, the suitable area for the growth of Vallisneria natans is mainly concentrated over the flooded land. As the water depth in the main channel is generally more than 4 m, so the habitat suitability is usually 0 there.Before the operation of the PLHP (M1), the water level in 2010 is higher than that those in 2006 and 2018. Therefore, there are more areas covered by water in 2010, and the habitat suitability in Fig. 6c is greater than those in Fig. 6a,b. Similarly, the habitat suitability in Fig. 6i is greater than those in Fig. 6g,h. Because the lake bed is lower in northeastern part than that in the southwestern part, the water depth generally decreases from northeast to southwest. During September and October in 2006 and 2018, large areas of bed in the northeastern part are covered by water, and the water depth is less than 4 m, which is suitable for the growth of Vallisneria natans. While large areas in the southwestern part of the lake are dry, and thus the habitat suitability is 0, as shown in the grey parts in the southwestern part of the main lake region in Fig. 6a,b,g,h. However, because the water level is relatively high during September and October in 2010, there are almost no dry areas in the lake region. As a result, with the exception of the main channel, where the water depth is greater than 4 m, most of the areas in the lake region are suitable for the growth of Vallisneria natans. The most suitable areas for Vallisneria natans vary between these two months, as the water depth in September 2010 is greater than that in October 2010. As shown in Fig. 6c, the red parts are mainly concentrated in the southwestern part of the lake, because there are large areas of flooded region with water depths ranging from 1 to 2 m, which is ideal for the growth of Vallisneria natans. On the contrary, the water depth in the northeastern flood land is usually between 2-4 m. In Fig. 6i, however, the red parts are mainly concentrated in the northeastern part of the lake, because the water depth there is usually between 1 and 2 m, and the water depth in the southwestern flood land is now usually less than 1 m.After the operation of the PLHP (M2), with the rise of the water level in the lake region, the suitable area for the growth of Vallisneria natans is increased greatly, and the variation is proportional to the DWL during the same period. The increase is most obvious in the low-water-level year (2006), followed by the medium water level year (2018), and becomes insignificant in the high-water-level year (2010). Such a trend is consistent with the previously mentioned variation in the water depth.Since the DWL is relatively small during September and October in 2010, the habitat suitability in this period is changed little between M1 and M2 (Fig. 6). The distribution of the habitat suitability is completely the same between Fig. 6c,f, while the difference in the distributions of habitat suitability between Fig. 6i,l is subtle. As the water level in M1 is relatively low during September and October in 2006 and 2018, the suitable area for the growth of Vallisneria natans in M2 is expanded from northeast to southwest under the influence of the PLHP. In addition, the habitat suitability is increased greatly in Wucheng National Nature Reserve and Nanji National Nature Reserve. Before the operation of the PLHP, there are large areas of dry land in the two reserves, and thus the habitat suitability in these dry areas is 0. After the operation of the PLHP, according the previous research, more than 1/3 of area in the two reserves sees apparent increases in water depth. The water depth is increased to 1 ~ 2 m and thus the habitat suitability is increased to 1.0 in the northeastern part of the reserves. In the southwestern part of the reserves, although the increase of water depth is not significant, most of the lake bed has changed its status from being dry to being wet and the habitat suitability is correspondingly increased from 0 to 0.1 ~ 0.2, as shown in Figs. 6d,e,j,k. This means that the two nature reserves will be more suitable for the growth of Vallisneria natans after the operation of the PLHP, and there it will be easier for Siberian Crane to find food here.Changes in habitat area of Vallisneria natansOn the basis of formula (6), we calculate the habitat area from 1st of September to 31st of October in three typical years, as shown in Fig. 7 and Table 3. In 2006, the habitat area is increased greatly, and the impact of the PLHP on habitat area is most evident in October. Compared with M1, the mean monthly habitat area in M2 is increased by 190.92%. Especially around the 10th of October, the increase can reach about 867.79 km2, accounting for about 1/4 of the total area of the lake. Compared with 2006, the increase of habitat area in 2018 is smaller. The mean monthly habitat area in M2 is increased by 57.07% in September and by 145.27% in October. The largest change occurs in late September, with an increase of about 841.43 km2, which is basically the same as in 2006. While in 2010, compared with M1, the habitat area in M2 is completely the same in September and the average increase in October is only 18.07%, indicating that when the water level is relatively high the operation of the PLHP will make little change to the habitat area.Figure 7Variations of habitat areas of Vallisneria natans in M1 (without the PLHP) and M2 (with the PLHP) and the resulting differences (grey columns).Full size imageTable 3 Mean monthly habitat areas of Vallisneria natans and changes between M1 and M2.Full size tableAfter the operation of the PLHP, the habitat area can reach more than 1000 km2 during the most time of September and October in three typical years, accounting for about 1/3 of the total area of the lake region. In other words, the latest official regulatory scheme of the PLHP is beneficial for the growth of Vallisneria natans in September and October. It means that, whether it is a low-water-level year, medium-water-level year or high-water-level year, before Siberian Crane fly to Poyang Lake for winter, Vallisneria natans will occupy large areas of the flooded land under the regulation of the PLHP. It will ensure that Siberian Crane can consume abundant tubers of Vallisneria natans as food in winter, allowing them to better survive and reproduce in the wetlands of Poyang Lake.In this research, the habitat suitability model of Vallisneria natans in Poyang Lake is established based on the previous research of Chen et al.16. This model only considers the effect of water depth, which mainly influences the growth of aquatic plant by changing the degree of light attenuation34. In fact, temperature and flow velocity can also influence the growth of Vallisneria natans according the relevant studies. However, temperature only plays a decisive role in the germination period38 and is rarely considered as an influencing factor during the growth period of Vallisneria natans. While high flow velocity may adversely affect the growth of Vallisneria natans during the seedling period, adult Vallisneria plants have an extensive root–rhizome system and long ribbon-like leaves to prevent them from being torn apart in rapid water39. Vallisneria natans often begin to sprout in March, reaching the tillering stage in June or July in Poyang Lake region. As a consequence, the temperature and flow velocity will have little effect on the growth of Vallisneria natans during the study period in this research (September and October). Therefore, the water depth can be regarded as the main factor affecting the suitability of Vallisneria natans during the mature period.There have been several scholars who have studied the effect of water depth on the growth of Vallisneria natans in other areas. Xiao et al.40 reported that Vallisneria natans grow rapidly with depths of 110–160 cm, while the growth is severely retarded with a depth of 250 cm. Cao et al.34 carried out experiments in turbid water and reported that the water depth of about 130 cm is most suitable for the growth of Vallisneria natans, while higher water depth will be less favorable for the growth. The inconsistency between these findings and the habitat suitability curve proposed by Chen et al.16 may be explained by the climate differences in different regions, as well as the different degrees of turbidity in water. According to the above analysis, the habitat suitability model of Vallisneria natans in this paper is established based on the habitat suitability curve proposed by Chen et al. (2020) as it represents to the growth characteristics of Vallisneria natans in Poyang Lake region.According to the above analysis, the latest regulatory scheme of the PLHP will effectively increase the water level in the lake region and expand the habitat area of Vallisneria natans, especially in low-water-level years. This finding is different from some of the previous research. Zhu et al.15 used the average water depth during the growing period of Vallisneria natans (from March to October) to reflect the availability of this food resource for Siberian Crane. They found that the PLHP had few influences on Vallisneria natans. This was because the PLHP remain completely open from April to August and it takes effect only in March, September and October during the growing period of Vallisneria natans. Therefore, the average water depth during March to October differs little whether with or without the PLHP, which would certainly underestimate the impact of the PLHP. The present study focuses on September and October, and uses the mean monthly water depth to reflect the habitat suitability of Vallisneria natans. In this period, the natural water level is relatively low in M1, and the operation of the PLHP increases the water level and inundates large areas of otherwise dry land. As a result, the habitat areas of Vallisneria natans observe an increase. More

The world’s population is rapidly urbanizing, particularly along coastlines, where population density is now three times higher than the global average1,2. According to the National Oceanic and Atmospheric Administration (NOAA), almost 40% of the United States (U.S.) population resides in coastal zones with population density being over five times greater in coastal shoreline counties than the national average. As a result, human encroachment on coastal ecosystems is significantly modifying natural landscapes and reducing intact coastal habitat. Along densely populated coastlines, residential development often involves unsustainable land-use planning and armoring of shorelines, where natural habitats such as saltmarshes, mangroves, seagrasses and oyster reefs, are replaced with artificial structures, including vertical bulkheads, seawalls, boat ramps, and other gray infrastructures3. In areas with dense residential development between 50–90% of shorelines can be armored, whereby, on average, 14% of all U.S. shorelines have been modified from their natural conditions and replaced with artificial structures3. This transition represents an extensive loss of natural coastal habitats and the critical ecosystem services they provide.As more ecologically harmful infrastructure is developed to meet the demands of human population growth, urbanization concurrently alters ecosystem services and functions by negatively impacting biodiversity, ecological conditions and environmental quality, specifically through a decrease in native habitat, increased water pollution, and creation of impervious surfaces4. Urbanization may also lead to less resilient and adaptable coastal communities against natural hazards and climate change threats, such as sea level rise and hurricanes. This is because in urban areas, ecosystem functioning is reduced and associated services are lost, resulting in increasing risk of shoreline erosion, saltwater intrusion, storm surges, and coastal flooding2,5.These human-environment interactions in coastal ecosystems can lead to, and at the same time be derived by, decisions that will shape the future structure, function, and sustainability of coastal ecosystems6. These social decisions (e.g., large-scale policies or individual level choices) can have long-lasting consequences for both the environment and society, especially as coastal development increases. Decisions that modify and change the biophysical nature of the environment (e.g., waterfront residents’ decision to use artificial structures for storm protection and shoreline stabilization) impact its ecological functionality7. At the same time, these alterations may change the degree of connectivity that individual humans have to their environments, which might extend to broader societies’ ecological knowledge8,9.Few studies provide evidence that the removal and lack of natural environments in urbanized environments reduces individuals’ environmental connectedness and ecological knowledge, and subsequently lowers pro-environmental behaviors10,11,12. This is of critical importance since a general lack of environmental connectedness, and in particular, a lack of ecological knowledge is a phenomenon often used to explain the non-appreciation of, and deleterious behaviors toward, the natural environment, even though many studies theorize these relationships opposed to empirically test them (e.g., see refs. 13,14 and the discussion in ref. 15 about “nature-deficit disorder”). Furthermore, if there exists a general lack of ecological knowledge, social decisions at the individual level that reflect these limited perceptions (e.g., utilitarian land-use decisions12 or waterfront homeowners’ preference to install a bulkhead) can often cascade to larger societal impacts through domino-effects, where individual decisions trigger similar, reactive decisions by neighbors leading to broader societal patterns16. For example, Gittman et al.17 found that one of the stronger predictors of an individual decision to have an armored shoreline was presence of armoring on a neighboring parcel. When considered across a community scale, such societal patterns can alter natural coastal habitats significantly.In this current study, we investigate the relationship between residents’ knowledge, or mental models, of human-environment interactions, their self-reported pro-environmental behavior, and how these perceptions and behaviors are associated with urbanization. A mental model is the cognitive internal representation of a system in the external world that articulates causal relationships among system components (i.e., abstract concepts)18,19. Mental models that represent causal knowledge can be graphically obtained through cognitive mapping techniques in the form of directed graphs, which are networks in which nodes represent concepts (i.e., system components) and graph edges (arrows) represent the causal relationships between the concepts20. We combine methods from social science, data science, and network science to conduct an analysis using mental models of coastal residents along an urbanization gradient to better understand the interconnections among urbanization, people’s knowledge of human-environment interactions, and their pro-environmental behavior.We surveyed residents across eight coastal states in the northeast U.S., including Maine, New Hampshire, Massachusetts, Rhode Island, Connecticut, New York, New Jersey, and Delaware. We used a fuzzy cognitive mapping (FCM) approach21 to elicit mental models of coastal ecosystems with a focus on environmental connectedness, ecosystem health, human wellbeing, climate, and sustainable coasts (see Methods). Here, we propose a concept, Urbanized Knowledge Syndrome (UKS), which represents recurring patterns in urban dwellers’ mental models about natural ecosystems – their internal understanding of how humans and environment interact. Here, syndrome should not be interpreted as a set of medical signs and symptoms which are associated with a particular disease or disorder. These recurring patterns include (1) diminished systems thinking (e.g., complexity of mental models decreases as degree of urban development increases) and (2) the erosion of cognitive diversity (i.e., diversity of mental models among residents decreases as degree of urban development increases). These patterns demonstrate a type of thinking that is simplified to some extent or otherwise limited or focused on fewer social-ecological relationships than exist in reality.Systems thinking – a holistic view that considers factors and interactions and how they result in a possible outcome – is an important skillset that helps people better understand complex systems and adapt to changes22. Individuals with higher degrees of systems thinking are more likely to consider interdependencies, identify leverage points to intervene within the system and produce desired outcomes23, better anticipate system function and emergence of patterns of behavior24, and avoid unintended consequences18. As such, systems thinking may help coastal residents develop mental models that enable more nuanced reasoning about diverse causal pathways between humans and natural coastal ecosystems25,26,27,28, which may lead to behaviors that are driven by more predominant cognition of complex feedbacks, trade-offs, and reciprocal interdependencies between humans and nature. In contrast, bounded systems thinking (or linear thinking) may lead humans to develop limited cognition of their surrounding world, reduce their ability to accurately and adequately perceive the complexity of the environment they inhabit and interact with22, and thus may give rise to counterproductive behaviors and decisions27,29. For example, a simple causal relationship might be that seawall construction increases coastal protection as a form of structural defense to control shoreline erosion; whereas a more complex relationship might be that seawalls lead to alterations in hydrodynamic processes, which reduces erosion locally and accelerates coastal erosion downstream30, and at the same time, shoreline armoring can also lead to losses of natural coastal habitats and their critical ecosystem functions3.While cities are beneficial to human development, working as engines of socioeconomic change, cultural transformation, and technological innovation, their psychological influences on people and how these influences drive urban residents’ perceptions and behavior must be noted. Firstly, the salience of ecosystem services is limited for inhabitants of more urbanized areas, as compared to rural areas. Exposure to nature provides multiple opportunities for cognitive development which increases the potential for stewardship of the environment and for a stronger recognition of ecosystem functions13. Urban residents, however, are more routinely exposed to built environment and gray infrastructure, such as armored shorelines and artificial structures along coastlines, as opposed to natural environment, and thus their local experience of, and connection to, ecosystem services can be limited31.Secondly, urbanization generally comes with complex technology and commerce, allowing individuals to meet their needs quickly and through many choices with less appreciation of, and first hand experience with, provisioning ecosystem services (e.g., food comes from many grocery stores not a farm or garden; fish comes over a counter not across a dock or the end of a spear; and potable water comes from a pipeline not a spring or well). This may cause the development of a wider gap in human perceptions of benefits received from natural ecosystems32, fostering the emergence of societies that are increasingly disconnected and seemingly independent from ecosystem services31.Finally, residents of urbanized areas may be exposed to a set of social norms, information, and perspectives that encourage anthropocentric values and thinking including human exemptionalism (“the tendency to see human systems as exempt from the constraints of natural environment”33) and human exceptionalism (“the tendency to see humans as biologically unique and discontinuous with the rest of the animal world”34), therefore limiting their understanding of the importance and substantiality of reciprocal interdependencies between humans and natural environment13,34. These urbanization aspects may spark what we call ‘limits to systems thinking’ in the social-ecological realm.Therefore, we hypothesize (H1) that in more urbanized areas, mental models are predominantly characterized by linear thinking of coastal ecosystems, as opposed to systems thinking, where components are connected mostly by simple causal patterns. This class of mental models is associated with limited cognition of synergies and trade-offs, emergence of global patterns from local relationships, reciprocal interdependencies, and feedback loops between humans and natural ecosystems, which may lead to a gap in residents’ perception of nonlinear complex structures. To test our hypothesis, we analyze the structure of causal relationships using the network structure and graph-theoretic metrics of cognitive maps (i.e., graphical representations of mental models). We use cluster analysis to identify predominant classes of mental models about coastal ecosystems. Distinct clusters of mental models represent archetypal cognitions that individuals develop to perceive human-environment interdependencies13,27. We then use network analyses to measure the complexity of causal structures in cognitive maps and determine the overall degree of systems thinking in each cluster (see Methods). Finally, we investigate the association between urbanization and the degree of systems thinking across those clusters.The second important feature that helps systems adapt to changes is diversity, ranging from ecosystems35 to economic systems36. There is also evidence that these same relationships between diversity and adaptability hold true for cultural knowledge systems, governance systems, and among diverse communities and social institutions that function more effectively as resilient collectives28,37,38.In contrast, as cultural homogenization theories explain, survival in cities depends on fitting in and adopting practices that are considered socially normal by the dominant culture39. Although cities are magnets for people from all corners of the world with seemingly more diverse composition of race and ethnicity compared to rural areas40, assimilation of diverse values, beliefs, cultural knowledge, and social norms into a universal, governing culture—sometimes referred to as “cultural colonialism” or “cultural normalization” – is a major component of urban societies41. This cultural normalization among urban dwellers is exacerbated by dominant exposure to the universal language and education system, greater access to the Internet, social media and news outlets, and market-driven policies and global standardizations for laws and finance41.In addition, an important characteristic of urbanization is the centralization of the population into cities, “where neighborhoods in different regions have similar patterns of roads, residential lots, commercial areas, and aquatic features”42. Such physical and environmental homogenization across urban areas, which is visually evident, is influenced by monocentric land-management and policies, economic pressures for land development and use, engineering necessities, codes and standards, and preferences for particular aesthetics and recreations. Prior studies have shown that this homogenization extends to ecological structure, meaning that across urbanized areas, similar built environment and landscape structures can lead to homogenized ecological characteristics, function, and the range of ecosystem services they can supply42,43.Here, we argue that homogenization in cultural, physical, and ecological systems also extends to residents’ perceptions and understanding of human-environment interactions. We, therefore, hypothesize (H2) that increased urbanization is associated with more homogenized mental models of coastal ecosystems. To test our second hypothesis, we measure the structural dissimilarity of individuals’ mental models (i.e., cognitive maps) using some of the widely used methods for comparing graphs44. We measure the mean of pairwise cognitive distances (i.e., a quantitative metric that represents the mean of graph dissimilarity between any two individual cognitive maps) and compare this metric across clusters of mental models, and thus, explore the correspondence between urbanization and mental model homogenization (i.e., testing the hypothesis that urbanization is associated with more similar mental models in terms of causal structures represented in cognitive maps) (see Methods). More

Farmers at a Great Green Wall site in Niger. Researchers have found that the project is not always benefiting the most vulnerable people.Credit: Boureima Hama/AFP/Getty

It’s now 15 years since the African Union gave its blessing to Africa’s Great Green Wall, one of the world’s most ambitious ecological-restoration schemes. The project is intended to combat desertification across the width of Africa, and spans some 8,000 kilometres, from Senegal to Djibouti. Its ambition is staggering: it aims to restore 100 million hectares of degraded land by 2030, capturing 250 million tonnes of carbon dioxide and creating 10 million jobs in the process. But it continues to struggle.An assessment two years ago by independent experts commissioned by the United Nations stated that somewhere between 4% and 20% of the restoration target had been achieved (go.nature.com/39zqgkr). That figure has not changed, according to the latest edition of Global Land Outlook (go.nature.com/3kdjtw5) from the UN Convention to Combat Desertification (UNCCD), out last week. Equally concerning is the fact that funding for the project continues to lag. Africa’s governments and international donors need to find around US$30 billion to reach the 100-million-hectare target. So far, $19 billion has been raised.A pandemic — and now a cost-of-living crisis — has placed demands on all governments, and that means countries might be expected to reduce their green-wall commitments. But the project continues to be weighed down by other difficulties, including the complex system through which it is funded and governed, as well as how its success is measured. These problems can and must be fixed, otherwise it will struggle to achieve its goals.One potential solution — improved metrics — comes from an analysis published last year by Matthew Turner at the University of Wisconsin–Madison and his colleagues (M. D. Turner et al. Land Use Policy 111, 105750; 2021). The researchers explored limitations in the Great Green Wall project metrics by assessing the impact of World Bank funding from 2006 to 2020. As their work indicates, definitions of success depend on which measure is used.In Niger, for example, green-wall projects could be said to be succeeding if measured by the area of eroded soil that has been recovered or by the number of trees that have been planted. But the authors report that these gains were not necessarily benefiting the most vulnerable people. In places, women were being excluded from employment in green-wall projects, and in some cases, local administrations looked to privatize restored land that might instead have been owned by everyone in a community.Broader problems with metrics are highlighted in the UN’s latest land-degradation report. This estimates that nearly half of the land that has been pledged for restoration worldwide will be planted predominantly with fast-growing trees and plants. This will provide only a fraction of the ecosystem services produced by forests that are allowed to naturally regenerate, including significantly less carbon storage, groundwater recharge and wildlife habitat.The Great Green Wall project also needs more predictable funding and more transparent governance. The project was conceived by Africa’s leaders for the benefit of the continent’s people, on the basis of warnings from scientists about the risks of desertification and land degradation. The original idea was not brought to Africa by international donors, as is often the case in international science-based development projects. But it still relies on donor financing, and lots of it — and that brings other problems, among them coordination challenges.The project is the responsibility of an organization set up by the African Union called the Pan African Agency of the Great Green Wall, based in Nouakchott, Mauritania. But some donors, such as the European Union and the World Bank, are not providing most of their Great Green Wall funding through this agency. Instead, they often deal directly with individual governments, because this gives them more control over how their money is spent. It is unfair to expect the Pan African Agency to coordinate a raft of donors doing one-on-one deals with individual countries. Bypassing the Pan African Agency also creates a problem for transparency, because it makes it harder for the African Union to determine precisely who is funding what.In January 2021, at an international biodiversity summit hosted by France, Emmanuel Macron, the French president, announced that the Great Green Wall would receive an extra $14 billion in funding for 5 years. He also said that a new body, called the Great Green Wall Accelerator, based in Bonn, Germany, would be responsible for pulling together funding pledges and tracking progress against targets. This is well-intentioned, but the accelerator needs to coordinate its work with the Pan African Agency. It is not yet clear how this will happen.A potentially more transformative solution was proposed two years ago by a group of UN-appointed experts. They recommended that a single trust fund be set up that all donors could contribute to and through which they could decide funding priorities together. Regrettably, this has not happened, and observers say it is not likely to happen in the current climate.This month, the international community will come together in Abidjan, Côte d’Ivoire, for the 15th conference of the parties to the UNCCD. The green wall’s funders and participating countries will all be there. If a single trust fund is off the table, they must work together to find a better way to coordinate their green-wall project activities. It is also essential that they study the findings of Turner and colleagues’ review. Along with a focus on existing metrics, the Great Green Wall needs evaluation criteria that take better account of the needs of all people in participating countries, particularly the most vulnerable. More