Philippa Kaur

Szulkin, M. et al. How to quantify urbanization when testing for urban evolution?. Urban Evol. Biol. https://doi.org/10.1093/oso/9780198836841.003.0002 (2020).Article 

Google Scholar 
Slabbekoorn, H. Songs of the city: Noise-dependent spectral plasticity in the acoustic phenotype of urban birds. Anim. Behav. https://doi.org/10.1016/j.anbehav.2013.01.021 (2013).Article 

Google Scholar 
Christiansen, N. A., Fryirs, K. A., Green, T. J. & Hose, G. C. The impact of urbanisation on community structure, gene abundance and transcription rates of microbes in upland swamps of Eastern Australia. PLoS ONE https://doi.org/10.1371/journal.pone.0213275 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Alberti, M. et al. Global urban signatures of phenotypic change in animal and plant populations. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1606034114 (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
McFall-Ngai, M. M. et al. Animals in a bacterial world, a new imperative for the life sciences. Proc. Natl. Acad. Sci. https://doi.org/10.1073/pnas.1218525110 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Zilber-Rosenberg, I. & Rosenberg, E. Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution. FEMS Microbiol. Rev. https://doi.org/10.1111/j.1574-6976.2008.00123.x (2008).Article 
PubMed 

Google Scholar 
Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: A call for the consideration of host-associated microbiota in wildlife management practices. Proc. R. Soc. B Biol. Sci. https://doi.org/10.1098/rspb.2018.2448 (2019).Article 

Google Scholar 
Jarrett, C., Powell, L. L., McDevitt, H., Helm, B. & Welch, A. J. Bitter fruits of hard labour: diet metabarcoding and telemetry reveal that urban songbirds travel further for lower-quality food. Oecologia https://doi.org/10.1007/s00442-020-04678-w (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Zollinger, S. A. et al. Traffic noise exposure depresses plasma corticosterone and delays offspring growth in breeding zebra finches. Conserv. Physiol. https://doi.org/10.1093/conphys/coz056 (2019).Article 
PubMed 
PubMed Central 

Google Scholar 
Sprau, P., Mouchet, A. & Dingemanse, N. J. Multidimensional environmental predictors of variation in avian forest and city life histories. Behav. Ecol. https://doi.org/10.1093/beheco/arw130 (2017).Article 

Google Scholar 
Teyssier, A. et al. Inside the guts of the city: Urban-induced alterations of the gut microbiota in a wild passerine. Sci. Total Environ. https://doi.org/10.1016/j.scitotenv.2017.09.035 (2018).Article 
PubMed 

Google Scholar 
Murray, M. H. et al. Gut microbiome shifts with urbanization and potentially facilitates a zoonotic pathogen in a wading bird. PLoS ONE https://doi.org/10.1371/journal.pone.0220926 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Fuirst, M., Veit, R. R., Hahn, M., Dheilly, N. & Thorne, L. H. Effects of urbanization on the foraging ecology and microbiota of the generalist seabird Larus argentatus. PLoS ONE https://doi.org/10.1371/journal.pone.0209200 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Phillips, J. N., Berlow, M. & Derryberry, E. P. The effects of landscape urbanization on the gut microbiome: An exploration into the gut of urban and rural white-crowned sparrows. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00148 (2018).Article 

Google Scholar 
Berlow, M., Phillips, J. N. & Derryberry, E. P. Effects of urbanization and landscape on gut microbiomes in white-crowned sparrows. Microb. Ecol. https://doi.org/10.1007/s00248-020-01569-8 (2020).Article 
PubMed 

Google Scholar 
Cox, L. M. et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell https://doi.org/10.1016/j.cell.2014.05.052 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Knutie, S. A., Wilkinson, C. L., Kohl, K. D. & Rohr, J. R. Early-life disruption of amphibian microbiota decreases later-life resistance to parasites. Nat. Commun. 8, 1–8 (2017).CAS 
Article 

Google Scholar 
Sudyka, J., Di Lecce, I., Wojas, L., Rowiński, P. & Szulkin, M. Nest-boxes alter the reproductive ecology of urban cavity-nesters in a species-dependent way. https://doi.org/10.32942/OSF.IO/WP9MN.
Maziarz, M., Broughton, R. K. & Wesołowski, T. Microclimate in tree cavities and nest-boxes: Implications for hole-nesting birds. For. Ecol. Manag. https://doi.org/10.1016/j.foreco.2017.01.001 (2017).Article 

Google Scholar 
Thompson, M. J., Capilla-Lasheras, P., Dominoni, D. M., Réale, D. & Charmantier, A. Phenotypic variation in urban environments: mechanisms and implications. Trends Ecol. Evol. 37, 171–182 (2022).CAS 
Article 

Google Scholar 
Salmón, P. et al. Continent-wide genomic signatures of adaptation to urbanisation in a songbird across Europe. Nat. Commun. 12, 1–14 (2021).ADS 
Article 

Google Scholar 
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. https://doi.org/10.1186/s13059-014-0550-8 (2014).Article 
PubMed 
PubMed Central 

Google Scholar 
Sackey, B. A., Mensah, P., Collison, E. & Sakyi-Dawson, E. Campylobacter, Salmonella, Shigella and Escherichia coli in live and dressed poultry from metropolitan Accra. Int. J. Food Microbiol. https://doi.org/10.1016/S0168-1605(01)00595-5 (2001).Article 
PubMed 

Google Scholar 
Benskin, C. M. W. H., Wilson, K., Jones, K. & Hartley, I. R. Bacterial pathogens in wild birds: A review of the frequency and effects of infection. Biol. Rev. https://doi.org/10.1111/j.1469-185X.2008.00076.x (2009).Article 
PubMed 

Google Scholar 
Hansell, M. & Overhill, R. Bird nests and construction behaviour. Bird Nests Constr. Behav. https://doi.org/10.1017/cbo9781139106788 (2000).Article 

Google Scholar 
Siddiqui, S. H., Khan, M., Kang, D., Choi, H. W. & Shim, K. Meta-analysis and systematic review of the thermal stress response: Gallus gallus domesticus show low immune responses during heat stress. Front. Physiol. 13, 31 (2022).Article 

Google Scholar 
Sepulveda, J. & Moeller, A. H. The effects of temperature on animal gut microbiomes. Front. Microbiol. https://doi.org/10.3389/fmicb.2020.00384 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Kohl, K. D. & Yahn, J. Effects of environmental temperature on the gut microbial communities of tadpoles. Environ. Microbiol. https://doi.org/10.1111/1462-2920.13255 (2016).Article 
PubMed 

Google Scholar 
Teyssier, A. et al. Diet contributes to urban-induced alterations in gut microbiota: Experimental evidence from a wild passerine. Proc. R. Soc. B Biol. Sci. https://doi.org/10.1098/rspb.2019.2182 (2020).Article 

Google Scholar 
Benskin, C. M. W. H., Rhodes, G., Pickup, R. W., Wilson, K. & Hartley, I. R. Diversity and temporal stability of bacterial communities in a model passerine bird, the zebra finch. Mol. Ecol. https://doi.org/10.1111/j.1365-294X.2010.04892.x (2010).Article 
PubMed 

Google Scholar 
Garrett, W. S. et al. Enterobacteriaceae Act in concert with the gut microbiota to induce spontaneous and maternally transmitted colitis. Cell Host Microbe https://doi.org/10.1016/j.chom.2010.08.004 (2010).Article 
PubMed 
PubMed Central 

Google Scholar 
Videvall, E. et al. Early-life gut dysbiosis linked to juvenile mortality in ostriches. BMC Microbiome 8, 1–13 (2020).Article 

Google Scholar 
Hooper, L. V. & MacPherson, A. J. Immune adaptations that maintain homeostasis with the intestinal microbiota. Nat. Rev. Immunol. https://doi.org/10.1038/nri2710 (2010).Article 
PubMed 

Google Scholar 
Borre, Y. E. et al. Microbiota and neurodevelopmental windows: Implications for brain disorders. Trends Mol. Med. https://doi.org/10.1016/j.molmed.2014.05.002 (2014).Article 
PubMed 

Google Scholar 
Jones, E. L. & Leather, S. R. Invertebrates in urban areas: A review. Eur. J. Entomol. https://doi.org/10.14411/eje.2012.060 (2012).Article 

Google Scholar 
Wilkin, T. A., King, L. E. & Sheldon, B. C. Habitat quality, nestling diet, and provisioning behaviour in great tits Parus major. J. Avian Biol. https://doi.org/10.1111/j.1600-048X.2009.04362.x (2009).Article 

Google Scholar 
Pollock, C. J., Capilla-Lasheras, P., McGill, R. A. R., Helm, B. & Dominoni, D. M. Integrated behavioural and stable isotope data reveal altered diet linked to low breeding success in urban-dwelling blue tits (Cyanistes caeruleus). Sci. Rep. https://doi.org/10.1038/s41598-017-04575-y (2017).Article 
PubMed 
PubMed Central 

Google Scholar 
Davidson, G. L. et al. Diet induces parallel changes to the gut microbiota and problem solving performance in a wild bird. Sci. Rep. https://doi.org/10.1038/s41598-020-77256-y (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Bodawatta, K. H. et al. Flexibility and resilience of great tit (Parus major) gut microbiomes to changing diets. Anim. Microbiome 2021(3), 1–14 (2021).
Google Scholar 
Baniel, A. et al. Seasonal shifts in the gut microbiome indicate plastic responses to diet in wild geladas. Microbiome 9, 1–20 (2021).Article 

Google Scholar 
Sullam, K. E. et al. Environmental and ecological factors that shape the gut bacterial communities of fish: A meta-analysis. Mol. Ecol. https://doi.org/10.1111/j.1365-294X.2012.05552.x (2012).Article 
PubMed 
PubMed Central 

Google Scholar 
Martiny, J. B. H. et al. Microbial biogeography: Putting microorganisms on the map. Nat. Rev. Microbiol. https://doi.org/10.1038/nrmicro1341 (2006).Article 
PubMed 

Google Scholar 
Lucass, C., Eens, M. & Müller, W. When ambient noise impairs parent-offspring communication. Environ. Pollut. https://doi.org/10.1016/j.envpol.2016.03.015 (2016).Article 
PubMed 

Google Scholar 
Kight, C. R. & Swaddle, J. P. How and why environmental noise impacts animals: An integrative, mechanistic review. Ecol. Lett. https://doi.org/10.1111/j.1461-0248.2011.01664.x (2011).Article 
PubMed 

Google Scholar 
Cui, B., Gai, Z., She, X., Wang, R. & Xi, Z. Effects of chronic noise on glucose metabolism and gut microbiota-host inflammatory homeostasis in rats. Sci. Rep. https://doi.org/10.1038/srep36693 (2016).Article 
PubMed 
PubMed Central 

Google Scholar 
Campo, J. L., Gil, M. G. & Dávila, S. G. Effects of specific noise and music stimuli on stress and fear levels of laying hens of several breeds. Appl. Anim. Behav. Sci. https://doi.org/10.1016/j.applanim.2004.08.028 (2005).Article 

Google Scholar 
Injaian, A. S., Taff, C. C. & Patricelli, G. L. Experimental anthropogenic noise impacts avian parental behaviour, nestling growth and nestling oxidative stress. Anim. Behav. https://doi.org/10.1016/j.anbehav.2017.12.003 (2018).Article 

Google Scholar 
Cui, B. et al. Effects of chronic noise exposure on the microbiome-gut-brain axis in senescence-accelerated prone mice: Implications for Alzheimer’s disease. J. Neuroinflammation https://doi.org/10.1186/s12974-018-1223-4 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Wei, L. et al. Constant light exposure alters gut microbiota and promotes the progression of steatohepatitis in high fat diet rats. Front. Microbiol. https://doi.org/10.3389/fmicb.2020.01975 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Chatelain, M. et al. Replicated, urban-driven exposure to metallic trace elements in two passerines. Sci. Rep. 11, 1–10 (2021).Article 

Google Scholar 
Chatelain, M. et al. Urban metal pollution explains variation in reproductive outputs in great tits and blue tits. Sci. Total Environ. 776, 145966 (2021).ADS 
CAS 
Article 

Google Scholar 
Rosenfeld, C. S. Gut dysbiosis in animals due to environmental chemical exposures. Front. Cell. Infect. Microbiol. 7, 396 (2017).Article 

Google Scholar 
Sommer, F. & Bäckhed, F. The gut microbiota-masters of host development and physiology. Nat. Rev. Microbiol. https://doi.org/10.1038/nrmicro2974 (2013).Article 
PubMed 

Google Scholar 
Tomiałojć, L. & Wesołowski, T. Diversity of the Białowieza forest avifauna in space and time. J. Ornithol. https://doi.org/10.1007/s10336-003-0017-2 (2004).Article 

Google Scholar 
Corsini, M. et al. Growing in the city: Urban evolutionary ecology of avian growth rates. Evol. Appl. https://doi.org/10.1111/eva.13081 (2021).Article 
PubMed 

Google Scholar 
Teyssier, A., Lens, L., Matthysen, E. & White, J. Dynamics of gut microbiota diversity during the early development of an avian host: Evidence from a cross-foster experiment. Front. Microbiol. https://doi.org/10.3389/fmicb.2018.01524 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Tremblay, I., Thomas, D., Blondel, J., Perret, P. & Lambrechts, M. M. The effect of habitat quality on foraging patterns, provisioning rate and nestling growth in Corsican Blue Tits Parus caeruleus. Ibis (Lond 1859). 147, 17–24 (2005).Article 

Google Scholar 
Corsini, M., Marrot, P. & Szulkin, M. Quantifying human presence in a heterogeneous urban landscape. Behav. Ecol. https://doi.org/10.1093/beheco/arz128 (2019).Article 

Google Scholar 
Corsini, M., Dubiec, A., Marrot, P. & Szulkin, M. Humans and tits in the city: Quantifying the effects of human presence on great tit and blue tit reproductive trait variation. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2017.00082 (2017).Article 

Google Scholar 
Kyba, C. C. M. et al. High-resolution imagery of earth at night: New sources, opportunities and challenges. Remote Sens. https://doi.org/10.3390/rs70100001 (2015).Article 

Google Scholar 
Maraci, Ö. et al. The gut microbial composition is species-specific and individual-specific in two species of estrildid finches, the Bengalese finch and the zebra finch. Front. Microbiol. https://doi.org/10.3389/fmicb.2021.619141 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Engel, K. et al. Individual- and species-specific skin microbiomes in three different estrildid finch species revealed by 16S amplicon sequencing. Microb. Ecol. https://doi.org/10.1007/s00248-017-1130-8 (2017).Article 
PubMed 

Google Scholar 
Magoč, T. & Salzberg, S. L. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics https://doi.org/10.1093/bioinformatics/btr507 (2011).Article 
PubMed 
PubMed Central 

Google Scholar 
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal https://doi.org/10.14806/ej.17.1.200 (2011).Article 

Google Scholar 
Schloss, P. D. et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. https://doi.org/10.1128/AEM.01541-09 (2009).Article 
PubMed 
PubMed Central 

Google Scholar 
Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics https://doi.org/10.1093/bioinformatics/btq461 (2010).Article 
PubMed 

Google Scholar 
Quast, C. et al. The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Res. https://doi.org/10.1093/nar/gks1219 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
R Core Team. R: A language and environment for statistical computing (R Foundation for Statistical Computing, 2020).
Google Scholar 
Clarke, K. R., Gorley, R., Somerfield, P. & Warwick, R. Change in Marine Communities: an Approach to Statistical Analysis and Interpretation 3rd edn (Prim. Plymouth, 2014).Shannon, C. E. The mathematical theory of communication. MD Comput. https://doi.org/10.2307/410457 (1997).Article 
PubMed 

Google Scholar 
Faith, D. P. Conservation evaluation and phylogenetic diversity. Biol. Conserv. https://doi.org/10.1016/0006-3207(92)91201-3 (1992).Article 

Google Scholar 
Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. https://doi.org/10.18637/jss.v067.i01 (2015).Article 

Google Scholar 
Fox, J. et al. The car Package. R (2012).Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. https://doi.org/10.1111/j.2041-210x.2009.00001.x (2010).Article 

Google Scholar 
DHARMa: Residual diagnostics for hierarchical (multi-level/mixed) regression models. https://cran.r-project.org/web/packages/DHARMa/vignettes/DHARMa.html.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2009).Book 

Google Scholar 
McMurdie, P. J. & Holmes, S. Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE https://doi.org/10.1371/journal.pone.0061217 (2013).Article 
PubMed 
PubMed Central 

Google Scholar 
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B https://doi.org/10.1111/j.2517-6161.1995.tb02031.x (1995).Article 
MATH 

Google Scholar 
Whittaker, R. H. Vegetation of the Siskiyou mountains Oregon and California. Ecol. Monogr. https://doi.org/10.2307/1948435 (1960).Article 

Google Scholar 
Paulson, J. metagenomeSeq: Statistical analysis for sparse high-throughput sequencing. Bioconductor.Jp (2014).Bray, J. R. & Curtis, J. T. An ordination of the upland forest communities of southern Wisconsin. Ecol. Monogr. https://doi.org/10.2307/1942268 (1957).Article 

Google Scholar 
Lozupone, C. A., Hamady, M., Kelley, S. T. & Knight, R. Quantitative and qualitative β diversity measures lead to different insights into factors that structure microbial communities. Appl. Environ. Microbiol. https://doi.org/10.1128/AEM.01996-06 (2007).Article 
PubMed 
PubMed Central 

Google Scholar 
Oksanen, J. et al. Package ‘vegan’ Title Community Ecology Package Version 2.5-6. cran.ism.ac.jp (2019).Anderson, M. J. & Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. https://doi.org/10.1046/j.1442-9993.2001.01070.x (2001).Article 

Google Scholar 
Clarke, K. R. & Ainsworth, M. A method of linking multivariate community structure to environmental variables. Mar. Ecol. Prog. Ser. https://doi.org/10.3354/meps092205 (1993).Article 

Google Scholar 
QGIS Development Team. QGIS Geographic Information System (Open Source Geospatial Foundation, 2019).
Google Scholar  More

Stibig, H. J., Achard, F., Carboni, S., Raši, R. & Miettinen, J. Change in tropical forest cover of Southeast Asia from 1990 to 2010. Biogeosciences 11, 247–258. https://doi.org/10.5194/bg-11-247-2014 (2014).ADS 
Article 

Google Scholar 
Wilcove, D. S., Giam, X., Edwards, D. P., Fisher, B. & Koh, L. P. Navjot’s nightmare revisited: Logging, agriculture, and biodiversity in Southeast Asia. Trends Ecol. Evol. 28, 531–540. https://doi.org/10.1016/j.tree.2013.04.005 (2013).Article 
PubMed 

Google Scholar 
Zeng, Z. et al. Highland cropland expansion and forest loss in Southeast Asia in the twenty-first century. Nat. Geosci. 11, 556–562. https://doi.org/10.1038/s41561-018-0166-9 (2018).ADS 
CAS 
Article 

Google Scholar 
Imai, N., Furukawa, T., Tsujino, R., Kitamura, S. & Yumoto, T. Correction: Factors affecting forest area change in Southeast Asia during 1980–2010. PLoS ONE 13, e0199908. https://doi.org/10.1371/journal.pone.0199908 (2018).Article 
PubMed 
PubMed Central 

Google Scholar 
Allen, C. D. et al. A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For. Ecol. Manag. 259, 660–684. https://doi.org/10.1016/j.foreco.2009.09.001 (2010).Article 

Google Scholar 
McDowell, N. G. et al. Multi-scale predictions of massive conifer mortality due to chronic temperature rise. Nat. Clim. Change 6, 295–300. https://doi.org/10.1038/nclimate2873 (2015).ADS 
Article 

Google Scholar 
Reichstein, M. et al. Climate extremes and the carbon cycle. Nature 500, 287–295. https://doi.org/10.1038/nature12350 (2013).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Barbeta, A. et al. The combined effects of a long-term experimental drought and an extreme drought on the use of plant-water sources in a Mediterranean forest. Global Change Biol. 21, 1213–1225. https://doi.org/10.1111/gcb.12785 (2015).ADS 
Article 

Google Scholar 
Mueller, R. C. et al. Differential tree mortality in response to severe drought: Evidence for long-term vegetation shifts. J. Ecol. 93, 1085–1093. https://doi.org/10.1111/j.1365-2745.2005.01042.x (2005).Article 

Google Scholar 
Carnicer, J. et al. Widespread crown condition decline, food web disruption, and amplified tree mortality with increased climate change-type drought. Proc. Natl. Acad. Sci. USA 108, 1474–1478. https://doi.org/10.1073/pnas.1010070108 (2011).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Shaw, J. D., Steed, B. E. & DeBlander, L. T. Forest Inventory and Analysis (FIA) annual inventory answers the question: What is happening to pinyon-juniper woodlands?. J. For. 103, 280–285 (2005).
Google Scholar 
Lebrija-Trejos, E., Pérez-García, E. A., Meave, J. A., Poorter, L. & Bongers, F. Environmental changes during secondary succession in a tropical dry forest in Mexico. J. Trop. Ecol. 27, 477–489. https://doi.org/10.1017/s0266467411000253 (2011).Article 

Google Scholar 
Lee, Y. K. et al. Differences of tree species composition and microclimate between a mahogany(swietenia macrophyllaking) plantation and a secondary forest in Mt. Makiling, Philippines. For. Sci. Technol. 2, 1–12. https://doi.org/10.1080/21580103.2006.9656293 (2006).CAS 
Article 

Google Scholar 
Lebrija-Trejos, E., Perez-Garcia, E. A., Meave, J. A., Bongers, F. & Poorter, L. Functional traits and environmental filtering drive community assembly in a species-rich tropical system. Ecology 91, 386–398. https://doi.org/10.1890/08-1449.1 (2010).Article 
PubMed 

Google Scholar 
Heithecker, T. D. & Halpern, C. B. Edge-related gradients in microclimate in forest aggregates following structural retention harvests in western Washington. For. Ecol. Manag. 248, 163–173. https://doi.org/10.1016/j.foreco.2007.05.003 (2007).Article 

Google Scholar 
Marthews, T. R., Burslem, D. F. R. P., Paton, S. R., Yangüez, F. & Mullins, C. E. Soil drying in a tropical forest: Three distinct environments controlled by gap size. Ecol. Model. 216, 369–384. https://doi.org/10.1016/j.ecolmodel.2008.05.011 (2008).Article 

Google Scholar 
Pineda-Garcia, F., Paz, H. & Meinzer, F. C. Drought resistance in early and late secondary successional species from a tropical dry forest: The interplay between xylem resistance to embolism, sapwood water storage and leaf shedding. Plant Cell Environ. 36, 405–418. https://doi.org/10.1111/j.1365-3040.2012.02582.x (2013).Article 
PubMed 

Google Scholar 
Bretfeld, M., Ewers, B. E. & Hall, J. S. Plant water use responses along secondary forest succession during the 2015–2016 El Nino drought in Panama. New Phytol. 219, 885–899. https://doi.org/10.1111/nph.15071 (2018).Article 
PubMed 

Google Scholar 
Matheny, A. M. et al. Contrasting strategies of hydraulic control in two codominant temperate tree species. Ecohydrology https://doi.org/10.1002/eco.1815 (2016).Article 

Google Scholar 
Pineda-Garcia, F., Paz, H., Meinzer, F. C. & Angeles, G. Exploiting water versus tolerating drought: Water-use strategies of trees in a secondary successional tropical dry forest. Tree Physiol. 36, 208–217. https://doi.org/10.1093/treephys/tpv124 (2016).Article 
PubMed 

Google Scholar 
Powell, T. L. et al. Differences in xylem and leaf hydraulic traits explain differences in drought tolerance among mature Amazon rainforest trees. Global Change Biol. 23, 4280–4293. https://doi.org/10.1111/gcb.13731 (2017).ADS 
Article 

Google Scholar 
Ruiz-Benito, P. et al. Climate- and successional-related changes in functional composition of European forests are strongly driven by tree mortality. Global Change Biol. 23, 4162–4176. https://doi.org/10.1111/gcb.13728 (2017).ADS 
Article 

Google Scholar 
Choat, B. et al. Triggers of tree mortality under drought. Nature 558, 531–539. https://doi.org/10.1038/s41586-018-0240-x (2018).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Sevanto, S., McDowell, N. G., Dickman, L. T., Pangle, R. & Pockman, W. T. How do trees die? A test of the hydraulic failure and carbon starvation hypotheses. Plant Cell Environ. 37, 153–161. https://doi.org/10.1111/pce.12141 (2014).CAS 
Article 
PubMed 

Google Scholar 
McDowell, N. et al. Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought?. New Phytol. 178, 719–739. https://doi.org/10.1111/j.1469-8137.2008.02436.x (2008).Article 
PubMed 

Google Scholar 
Rowland, L. et al. Death from drought in tropical forests is triggered by hydraulics not carbon starvation. Nature 528, 119–122. https://doi.org/10.1038/nature15539 (2015).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Lazar, T., Taiz, L. & Zeiger, E. Plant physiology. 3rd edn. Ann. Bot. 91, 750–751. https://doi.org/10.1093/aob/mcg079 (2003).Article 
PubMed Central 

Google Scholar 
Steppe, K. The potential of the tree water potential. Tree Physiol. 38, 937–940. https://doi.org/10.1093/treephys/tpy064 (2018).Article 
PubMed 

Google Scholar 
Johnson, D., Katul, G. G. & Domec, J. C. Catastrophic hydraulic failure and tipping points in plants. Plant Cell Environ. (2022).Adams, H. D. et al. A multi-species synthesis of physiological mechanisms in drought-induced tree mortality. Nat. Ecol. Evol. 1, 1285–1291. https://doi.org/10.1038/s41559-017-0248-x (2017).Article 
PubMed 

Google Scholar 
Skelton, R. P., West, A. G. & Dawson, T. E. Predicting plant vulnerability to drought in biodiverse regions using functional traits. Proc. Natl. Acad. Sci. USA 112, 5744–5749. https://doi.org/10.1073/pnas.1503376112 (2015).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Domec, J.-C. et al. Conversion of natural forests to managed forest plantations decreases tree resistance to prolonged droughts. For. Ecol. Manag. 355, 58–71. https://doi.org/10.1016/j.foreco.2015.04.012 (2015).Article 

Google Scholar 
Maherali, H., Pockman, W. T. & Jackson, R. B. Adaptive variation in the vulnerability of woody plants to xylem cavitation. Ecology 85, 2184–2199. https://doi.org/10.1890/02-0538 (2004).Article 

Google Scholar 
Barros, F. V. et al. Hydraulic traits explain differential responses of Amazonian forests to the 2015 El Nino-induced drought. New Phytol. 223, 1253–1266. https://doi.org/10.1111/nph.15909 (2019).CAS 
Article 
PubMed 

Google Scholar 
Bittencourt, P. R. L. et al. Amazonia trees have limited capacity to acclimate plant hydraulic properties in response to long-term drought. Global Change Biol. 26, 3569–3584. https://doi.org/10.1111/gcb.15040 (2020).ADS 
Article 

Google Scholar 
Nolf, M. et al. Stem and leaf hydraulic properties are finely coordinated in three tropical rain forest tree species. Plant Cell Environ. 38, 2652–2661. https://doi.org/10.1111/pce.12581 (2015).CAS 
Article 
PubMed 

Google Scholar 
Trueba, S. et al. Vulnerability to xylem embolism as a major correlate of the environmental distribution of rain forest species on a tropical island. Plant, Cell Environ. 40, 277–289. https://doi.org/10.1111/pce.12859 (2017).CAS 
Article 

Google Scholar 
Zhu, S. D., Chen, Y. J., Fu, P. L. & Cao, K. F. Different hydraulic traits of woody plants from tropical forests with contrasting soil water availability. Tree Physiol. 37, 1469–1477. https://doi.org/10.1093/treephys/tpx094 (2017).Article 
PubMed 

Google Scholar 
Chen, Y. J. et al. Physiological regulation and efficient xylem water transport regulate diurnal water and carbon balances of tropical lianas. Funct. Ecol. 31, 306–317. https://doi.org/10.1111/1365-2435.12724 (2016).Article 

Google Scholar 
Tan, F.-S. et al. Hydraulic safety margins of co-occurring woody plants in a tropical karst forest experiencing frequent extreme droughts. Agr. Forest Meteorol. https://doi.org/10.1016/j.agrformet.2020.108107 (2020).Article 

Google Scholar 
Markesteijn, L., Iraipi, J., Bongers, F. & Poorter, L. Seasonal variation in soil and plant water potentials in a Bolivian tropical moist and dry forest. J. Trop. Ecol. 26, 497–508. https://doi.org/10.1017/s0266467410000271 (2010).Article 

Google Scholar 
Mitchell, P. J., Veneklaas, E. J., Lambers, H. & Burgess, S. S. Leaf water relations during summer water deficit: Differential responses in turgor maintenance and variation in leaf structure among different plant communities in south-western Australia. Plant Cell Environ. 31, 1791–1802. https://doi.org/10.1111/j.1365-3040.2008.01882.x (2008).Article 
PubMed 

Google Scholar 
Baltzer, J. L., Davies, S. J., Bunyavejchewin, S. & Noor, N. S. M. The role of desiccation tolerance in determining tree species distributions along the Malay-Thai Peninsula. Funct. Ecol. 22, 221–231. https://doi.org/10.1111/j.1365-2435.2007.01374.x (2008).Article 

Google Scholar 
Kursar, T. A. et al. Tolerance to low leaf water status of tropical tree seedlings is related to drought performance and distribution. Funct. Ecol. 23, 93–102. https://doi.org/10.1111/j.1365-2435.2008.01483.x (2009).Article 

Google Scholar 
Engelbrecht, B. M. J., Tyree, M. T. & Kursar, T. A. Visual assessment of wilting as a measure of leaf water potential and seedling drought survival. J. Trop. Ecol. 23, 497–500. https://doi.org/10.1017/s026646740700421x (2007).Article 

Google Scholar 
Blackman, C. J. et al. Drought response strategies and hydraulic traits contribute to mechanistic understanding of plant dry-down to hydraulic failure. Tree Physiol. 39, 910–924. https://doi.org/10.1093/treephys/tpz016 (2019).CAS 
Article 
PubMed 

Google Scholar 
Bucci, S. J. et al. Mechanisms contributing to seasonal homeostasis of minimum leaf water potential and predawn disequilibrium between soil and plant water potential in Neotropical savanna trees. Trees 19, 296–304. https://doi.org/10.1007/s00468-004-0391-2 (2004).Article 

Google Scholar 
Prado, C. H. B. A., Wenhui, Z., Cardoza Rojas, M. H. & Souza, G. M. Seasonal leaf gas exchange and water potential in a woody cerrado species community. Braz. J. Plant Physiol. 16, 7–16. https://doi.org/10.1590/s1677-04202004000100002 (2004).Article 

Google Scholar 
Fetcher, N., Oberbauer, S. F. & Strain, B. R. Vegetation effects on microclimate in lowland tropical forest in Costa Rica. Int. J. Biometeorol. 29, 145–155. https://doi.org/10.1007/bf02189035 (1985).ADS 
Article 

Google Scholar 
McCarthy, J. Gap dynamics of forest trees: A review with particular attention to boreal forests. Environ. Rev. 9, 1–59. https://doi.org/10.1139/a00-012 (2001).Article 

Google Scholar 
Zhu, S.-D. & Cao, K.-F. Hydraulic properties and photosynthetic rates in co-occurring lianas and trees in a seasonal tropical rainforest in southwestern China. Plant Ecol. 204, 295–304. https://doi.org/10.1007/s11258-009-9592-5 (2009).Article 

Google Scholar 
Sperry, J. S., Hacke, U. G., Oren, R. & Comstock, J. P. Water deficits and hydraulic limits to leaf water supply. Plant Cell Environ. 25, 251–263. https://doi.org/10.1046/j.0016-8025.2001.00799.x (2002).Article 
PubMed 

Google Scholar 
Choat, B., Sack, L. & Holbrook, N. M. Diversity of hydraulic traits in nine Cordia species growing in tropical forests with contrasting precipitation. New Phytol. 175, 686–698. https://doi.org/10.1111/j.1469-8137.2007.02137.x (2007).Article 
PubMed 

Google Scholar 
Vinya, R. et al. Xylem cavitation vulnerability influences tree species’ habitat preferences in miombo woodlands. Oecologia 173, 711–720. https://doi.org/10.1007/s00442-013-2671-2 (2013).ADS 
Article 
PubMed 

Google Scholar 
Vander Willigen, C., Sherwin, H. W. & Pammenter, N. W. Xylem hydraulic characteristics of subtropical trees from contrasting habitats grown under identical environmental conditions. New Phytol. 145, 51–59. https://doi.org/10.1046/j.1469-8137.2000.00549.x (2000).Article 

Google Scholar 
Domec, J. C. et al. Diurnal and seasonal variation in root xylem embolism in neotropical savanna woody species: Impact on stomatal control of plant water status. Plant Cell Environ. 29, 26–35. https://doi.org/10.1111/j.1365-3040.2005.01397.x (2006).CAS 
Article 
PubMed 

Google Scholar 
Barnard, D. M. et al. Climate-related trends in sapwood biophysical properties in two conifers: Avoidance of hydraulic dysfunction through coordinated adjustments in xylem efficiency, safety and capacitance. Plant Cell Environ. 34, 643–654. https://doi.org/10.1111/j.1365-3040.2010.02269.x (2011).Article 
PubMed 

Google Scholar 
Rosner, S., Heinze, B., Savi, T. & Dalla-Salda, G. Prediction of hydraulic conductivity loss from relative water loss: New insights into water storage of tree stems and branches. Physiol. Plant. 165, 843–854. https://doi.org/10.1111/ppl.12790 (2019).CAS 
Article 
PubMed 

Google Scholar 
Markesteijn, L., Poorter, L., Paz, H., Sack, L. & Bongers, F. Ecological differentiation in xylem cavitation resistance is associated with stem and leaf structural traits. Plant Cell Environ. 34, 137–148. https://doi.org/10.1111/j.1365-3040.2010.02231.x (2011).Article 
PubMed 

Google Scholar 
Cartwright, J. M., Littlefield, C. E., Michalak, J. L., Lawler, J. J. & Dobrowski, S. Z. Topographic, soil, and climate drivers of drought sensitivity in forests and shrublands of the Pacific Northwest, USA. Sci. Rep. 10, 18486. https://doi.org/10.1038/s41598-020-75273-5 (2020).CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Choat, B., Ball, M. C., Luly, J. G. & Holtum, J. A. M. Hydraulic architecture of deciduous and evergreen dry rainforest tree species from north-eastern Australia. Trees 19, 305–311. https://doi.org/10.1007/s00468-004-0392-1 (2004).Article 

Google Scholar 
Krober, W., Zhang, S., Ehmig, M. & Bruelheide, H. Linking xylem hydraulic conductivity and vulnerability to the leaf economics spectrum–a cross-species study of 39 evergreen and deciduous broadleaved subtropical tree species. PLoS ONE 9, e109211. https://doi.org/10.1371/journal.pone.0109211 (2014).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Brockelman, W. Y., Nathalang, A. & Maxwell, J. F. Mo Singto Forest Dynamics Plot: Flora and Ecology (National Science and Technology Development Agency, 2017).
Google Scholar 
Zhang, Q. W., Zhu, S. D., Jansen, S., Cao, K. F. & McCulloh, K. Topography strongly affects drought stress and xylem embolism resistance in woody plants from a karst forest in Southwest China. Funct. Ecol. 35, 566–577. https://doi.org/10.1111/1365-2435.13731 (2020).Article 

Google Scholar 
Ishida, A. et al. Seasonal variations of gas exchange and water relations in deciduous and evergreen trees in monsoonal dry forests of Thailand. Tree Physiol. 30, 935–945. https://doi.org/10.1093/treephys/tpq025 (2010).Article 
PubMed 

Google Scholar 
Nardini, A., Battistuzzo, M. & Savi, T. Shoot desiccation and hydraulic failure in temperate woody angiosperms during an extreme summer drought. New Phytol. 200, 322–329. https://doi.org/10.1111/nph.12288 (2013).CAS 
Article 
PubMed 

Google Scholar 
Choat, B. et al. Global convergence in the vulnerability of forests to drought. Nature 491, 752–755. https://doi.org/10.1038/nature11688 (2012).ADS 
CAS 
Article 
PubMed 

Google Scholar 
Brodribb, T. J. Progressing from “functional” to mechanistic traits. New Phytol. 215, 9–11. https://doi.org/10.1111/nph.14620 (2017).Article 
PubMed 

Google Scholar 
Oliveira, R. S. et al. Embolism resistance drives the distribution of Amazonian rainforest tree species along hydro-topographic gradients. New Phytol. 221, 1457–1465. https://doi.org/10.1111/nph.15463 (2019).Article 
PubMed 

Google Scholar 
Popradit, A. et al. Anthropogenic effects on a tropical forest according to the distance from human settlements. Sci. Rep. 5, 14689. https://doi.org/10.1038/srep14689 (2015).ADS 
CAS 
Article 
PubMed 
PubMed Central 

Google Scholar 
Hérault, B. & Gourlet-Fleury, S. In Climate Change and Agriculture Worldwide (ed. Torquebiau, E.) 183–196 (Springer, 2016).Chapter 

Google Scholar 
Elliott, S. et al. Selecting framework tree species for restoring seasonally dry tropical forests in northern Thailand based on field performance. For. Ecol. Manag. 184, 177–191. https://doi.org/10.1016/s0378-1127(03)00211-1 (2003).Article 

Google Scholar 
Vieira, D. L. M. & Scariot, A. Principles of natural regeneration of tropical dry forests for restoration. Restor. Ecol. 14, 11–20. https://doi.org/10.1111/j.1526-100X.2006.00100.x (2006).Article 

Google Scholar 
Hérault, B. & Piponiot, C. Key drivers of ecosystem recovery after disturbance in a neotropical forest. For. Ecosyst. 5, 2. https://doi.org/10.1186/s40663-017-0126-7 (2018).Article 

Google Scholar 
Davies, S. J. et al. ForestGEO: Understanding forest diversity and dynamics through a global observatory network. Biol. Conserv. 253, 108907. https://doi.org/10.1016/j.biocon.2020.108907 (2021).Article 

Google Scholar 
Chanthorn, W. et al. Viewing tropical forest succession as a three-dimensional dynamical system. Theor. Ecol. 9, 163–172. https://doi.org/10.1007/s12080-015-0278-4 (2015).Article 

Google Scholar 
Chanthorn, W., Hartig, F. & Brockelman, W. Y. Structure and community composition in a tropical forest suggest a change of ecological processes during stand development. For. Ecol. Manag. 404, 100–107. https://doi.org/10.1016/j.foreco.2017.08.001 (2017).Article 

Google Scholar 
Rodtassana, C. et al. Different responses of soil respiration to environmental factors across forest stages in a Southeast Asian forest. Ecol. Evol. 11, 15430–15443. https://doi.org/10.1002/ece3.8248 (2021).Article 
PubMed 
PubMed Central 

Google Scholar 
Tor-ngern, P. et al. Variation of leaf-level gas exchange rates and leaf functional traits of dominant trees across three successional stages in a Southeast Asian tropical forest. For. Ecol. Manag. https://doi.org/10.1016/j.foreco.2021.119101 (2021).Article 

Google Scholar 
Zhu, S. D., Song, J. J., Li, R. H. & Ye, Q. Plant hydraulics and photosynthesis of 34 woody species from different successional stages of subtropical forests. Plant Cell Environ. 36, 879–891. https://doi.org/10.1111/pce.12024 (2013).CAS 
Article 
PubMed 

Google Scholar 
Martin-StPaul, N. K. et al. How reliable are methods to assess xylem vulnerability to cavitation? The issue of “open vessel” artifact in oaks. Tree Physiol. 34, 894–905. https://doi.org/10.1093/treephys/tpu059 (2014).CAS 
Article 
PubMed 

Google Scholar 
Ennajeh, M., Simoes, F., Khemira, H. & Cochard, H. How reliable is the double-ended pressure sleeve technique for assessing xylem vulnerability to cavitation in woody angiosperms?. Physiol. Plant. 142, 205–210. https://doi.org/10.1111/j.1399-3054.2011.01470.x (2011).CAS 
Article 
PubMed 

Google Scholar 
Pérez-Harguindeguy, N. et al. Corrigendum to: New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 64, 715–716. https://doi.org/10.1071/bt12225_co (2016).Article 

Google Scholar 
Ewers, F. W. & Fisher, J. B. Techniques for measuring vessel lengths and diameters in stems of woody plants. Am. J. Bot. 76, 645–656. https://doi.org/10.1002/j.1537-2197.1989.tb11360.x (1989).Article 

Google Scholar 
Gao, H. et al. Vessel-length determination using silicone and air injection: Are there artifacts?. Tree Physiol. 39, 1783–1791. https://doi.org/10.1093/treephys/tpz064 (2019).CAS 
Article 
PubMed 

Google Scholar 
Sperry, J. S. & Saliendra, N. Z. Intra- and inter-plant variation in xylem cavitation in Betula occidentalis. Plant Cell Environ. 17, 1233–1241. https://doi.org/10.1111/j.1365-3040.1994.tb02021.x (1994).Article 

Google Scholar 
Melcher, P. J. et al. Measurements of stem xylem hydraulic conductivity in the laboratory and field. Methods Ecol. Evol. 3, 685–694. https://doi.org/10.1111/j.2041-210X.2012.00204.x (2012).Article 

Google Scholar 
Edwards, W. R. N. & Jarvis, P. G. Relations between water content, potential and permeability in stems of conifers. Plant Cell Environ. 5, 271–277. https://doi.org/10.1111/1365-3040.ep11572656 (1982).Article 

Google Scholar 
Sperry, J. S. & Ikeda, T. Xylem cavitation in roots and stems of Douglas-fir and white fir. Tree Physiol. 17, 275–280. https://doi.org/10.1093/treephys/17.4.275 (1997).CAS 
Article 
PubMed 

Google Scholar 
Pammenter, N. W. & Vander Willigen, C. A mathematical and statistical analysis of the curves illustrating vulnerability of xylem to cavitation. Tree Physiol. 18, 589–593. https://doi.org/10.1093/treephys/18.8-9.589 (1998).Article 
PubMed 

Google Scholar 
Domec, J.-C. & Gartner, B. L. Cavitation and water storage capacity in bole xylem segments of mature and young Douglas-fir trees. Trees 15, 204–214. https://doi.org/10.1007/s004680100095 (2001).Article 

Google Scholar  More

Atkinson, C. T. & Van Riper, C. Pathogenicity and epizootiology of avian haematozoa: Plasmodium, Leucocytozoon, and Haemoproteus. Bird-Parasite Interact. 2, 19–48 (1991).
Google Scholar 
Sorci, G. & Moller, A. P. Comparative evidence for a positive correlation between haematozoan prevalence and mortality in waterfowl. J. Evol. Biol. 10, 731–741 (1997).
Google Scholar 
Merino, S., Moreno, J., Sanz, J. J. & Arriero, E. Are avian blood parasites pathogenic in the wild? A medication experiment in blue tits (Parus caeruleus). Proc. Biol. Sci. 267, 2507–2510 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar 
Asghar, M. et al. Hidden costs of infection: Chronic malaria accelerates telomere degradation and senescence in wild birds. Science 347, 436–438 (2015).ADS 
CAS 
PubMed 

Google Scholar 
Quillfeldt, P., Arriero, E., Martínez, J., Masello, J. F. & Merino, S. Prevalence of blood parasites in seabirds – A review. Front. Zool. 8, 26 (2011).PubMed 
PubMed Central 

Google Scholar 
Piersma, T. Do global patterns of habitat use and migration strategies co-evolve with relative investments in immunocompetence due to spatial variation in parasite pressure?. Oikos 80, 623 (1997).
Google Scholar 
Mendes, L., Piersma, T., Lecoq, M., Spaans, B. & Ricklefs, R. E. Disease-limited distributions? Contrasts in the prevalence of avian malaria in shorebird species using marine and freshwater habitats. Oikos 109, 396–404 (2005).
Google Scholar 
Martínez-Abraín, A., Esparza, B. & Oro, D. Lack of blood parasites in bird species: Does absence of blood parasite vectors explain it all?. Ardeola 51, 225–232 (2004).
Google Scholar 
Campioni, L. et al. Absence of haemosporidian parasite infections in the long-lived Cory’s shearwater: Evidence from molecular analyses and review of the literature. Parasitol. Res. 117, 323–329 (2018).PubMed 

Google Scholar 
Osorio-Beristain, M. & Drummond, H. Non-aggressive mate guarding by the blue-footed booby: A balance of female and male control. Behav. Ecol. Sociobiol. 43, 307–315 (1998).
Google Scholar 
Nelson, J. B. Pelicans, Cormorants and Their Relatives: The Pelecaniformes (Oxford University Press, 2006).
Google Scholar 
Kim, S. Y., Torres, R., Domínguez, C. A. & Drummond, H. Lifetime philopatry in the blue-footed booby: A longitudinal study. Behav. Ecol. 18, 1132–1138 (2007).
Google Scholar 
Drummond, H. & Rodríguez, C. Viability of booby offspring is maximized by having one young parent and one old parent. PLoS ONE 10, e0133213 (2015).PubMed 
PubMed Central 

Google Scholar 
Lee-Cruz, L. et al. Prevalence of Haemoproteus sp. in Galápagos blue-footed boobies: Effects on health and reproduction. Parasitol. Open 2 (2016).Santiago-Alarcon, D., Palinauskas, V. & Schaefer, H. M. Diptera vectors of avian Haemosporidian parasites: Untangling parasite life cycles and their taxonomy. Biol. Rev. 87, 928–964 (2012).PubMed 

Google Scholar 
Bond, J. G. et al. Diversity of mosquitoes and the aquatic insects associated with their oviposition sites along the Pacific coast of Mexico. Parasit. Vectors 7, 41 (2014).PubMed 
PubMed Central 

Google Scholar 
Ibañez-Bernal, S. Informe Final del Proyecto Actualización del Catálogo de Autoridad Taxonómica del Orden Diptera (Insecta) de México CONABIO (JE006). (2017).Levin, I. I. et al. Hippoboscid-transmitted Haemoproteus parasites (Haemosporida) infect Galapagos Pelecaniform birds: Evidence from molecular and morphological studies, with a description of Haemoproteus iwa. Int. J. Parasitol. 41, 1019–1027 (2011).PubMed 

Google Scholar 
Madsen, V. et al. Testosterone levels and gular pouch coloration in courting magnificent frigatebird (Fregata magnificens): Variation with age-class, visited status and blood parasite infection. Horm. Behav. 51, 156–163 (2007).CAS 
PubMed 

Google Scholar 
Clark, G. W. & Swinehart, B. Avian haematozoa from the offshore islands of northern Mexico. Wildl. Dis. 5, 111–112 (1969).CAS 
PubMed 

Google Scholar 
Quillfeldt, P. et al. Hemosporidian blood parasites in seabirds—A comparative genetic study of species from Antarctic to tropical habitats. Naturwissenschaften 97, 809–817 (2010).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Merino, S. et al. Infection by haemoproteus parasites in four species of frigatebirds and the description of a new species of Haemoproteus (Haemosporida: Haemoproteidae). J. Parasitol. 98, 388–397 (2012).PubMed 

Google Scholar 
Svensson, L. M. E. & Ricklefs, R. E. Low diversity and high intra-island variation in prevalence of avian Haemoproteus parasites on Barbados, Lesser Antilles. Parasitology 136, 1121–1131 (2009).PubMed 

Google Scholar 
Loiseau, C. et al. Spatial variation of haemosporidian parasite infection in african rainforest bird species. J. Parasitol. 96, 21–29 (2010).PubMed 

Google Scholar 
Madsen, V. Female Mate Choice in the Magnificent Frigatebird (Fregata magnificens) (Universidad Nacional Autónoma de México, 2004).
Google Scholar 
Super, P. E. & van Riper, C. A comparison of avian hematozoan epizootiology in two California coastal scrub communities. J. Wildl. Dis. 31, 447–461 (1995).CAS 
PubMed 

Google Scholar 
CONANP. Programa de Conservación y Manejo del Parque Nacional Isla Isabel. (2005).Ancona, S., Drummond, H., Rodríguez, C. & Zúñiga-Vega, J. J. Long-term population dynamics reveal that survival and recruitment of tropical boobies improve after a hurricane. J. Avian Biol. 48, 320–332 (2017).
Google Scholar 
Martínez-de la Puente, J., Martinez, J., Rivero-de Aguilar, J., Herrero, J. & Merino, S. On the specificity of avian blood parasites: Revealing specific and generalist relationships between haemosporidians and biting midges. Mol. Ecol. 20, 3275–3287 (2011).PubMed 

Google Scholar 
Bastien, M., Jaeger, A., Le Corre, M., Tortosa, P. & Lebarbenchon, C. Haemoproteus iwa in Great Frigatebirds (Fregata minor) in the Islands of the Western Indian Ocean. PLoS ONE 9, e97185 (2014).ADS 
PubMed 
PubMed Central 

Google Scholar 
Maa, T. C. Records of Hippoboscidae (diptera) from the Central Pacific. J. Med. Ent. 3, 325–328 (1968).
Google Scholar 
Levin, I. I. & Parker, P. G. Comparative host–parasite population genetic structures: Obligate fly ectoparasites on Galapagos seabirds. Parasitology 140, 1061–1069 (2013).CAS 
PubMed 

Google Scholar 
Ramos-González, A. Hábitat y Edad de los Bobos de Patas Azules: Factores Importantes Para la Paternidad y Abundancia de Garrapatas. Primera edición. 88. (Universidad Nacional Autónoma de México, 2019). Print ISBN 978-607-30-1489-2.Bensch, S. et al. Contaminations contaminate common databases. Mol. Ecol. Resour. 21, 355–362 (2021).CAS 
PubMed 

Google Scholar 
Taylor, S. A., Maclagan, L., Anderson, D. J. & Friesen, V. L. Could specialization to cold-water upwelling systems influence gene flow and population differentiation in marine organisms? A case study using the blue-footed booby, Sula nebouxii. J. Biogeogr. 38, 883–893 (2011).
Google Scholar 
Kalbe, M. & Kurtz, J. Local differences in immunocompetence reflect resistance of sticklebacks against the eye fluke Diplostomum pseudospathaceum. Parasitology 132, 105–116 (2006).CAS 
PubMed 

Google Scholar 
Martin, L. B., Gilliam, J., Han, P., Lee, K. & Wikelski, M. Corticosterone suppresses cutaneous immune function in temperate but not tropical house sparrows Passer domesticus. Gen. Comp. Endocrinol. 140, 126–135 (2005).CAS 

Google Scholar 
Becker, D. J. et al. Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence. J. Anim. Ecol. 89, 972–995 (2020).PubMed 
PubMed Central 

Google Scholar 
Ting, J. et al. Malaria parasites and related haemosporidians cause mortality in cranes: A study on the parasites diversity, prevalence and distribution in Beijing Zoo. Malar. J. 17, 234 (2018).
Google Scholar 
Grilo, M. L. et al. Malaria in penguins – Current perceptions. Avian Pathol. 45, 393–407 (2016).CAS 
PubMed 

Google Scholar 
Jovani, R. & Tella, J. L. Parasite prevalence and sample size: misconceptions and solutions. Trends Parasitol. 22, 214–218 (2006).PubMed 

Google Scholar 
Bensch, S. et al. Temporal dynamics and diversity of avian malaria parasites in a single host species. J. Anim. Ecol. 76, 112–122 (2007).MathSciNet 
PubMed 

Google Scholar 
Lachish, S., Knowles, S. C., Alves, R., Wood, M. J. & Sheldon, B. C. Infection dynamics of endemic malaria in a wild bird population: Parasite species-dependent drivers of spatial and temporal variation in transmission rates. J. Anim. Ecol. 80, 1207–1216 (2011).PubMed 

Google Scholar 
Lopes, V. L. et al. High fidelity defines the temporal consistency of host-parasite interactions in a tropical coastal ecosystem. Sci. Rep. 10, 16839 (2020).ADS 
CAS 
PubMed 
PubMed Central 

Google Scholar 
Valkiunas, G. et al. A comparative analysis of microscopy and PCR-based detection methods for blood parasites. J. Parasitol. 94, 1395–1401 (2008).CAS 
PubMed 

Google Scholar 
Santiago-Alarcon, D. et al. Parasites in space and time: A case study of haemosporidian spatiotemporal prevalence in urban birds. Int. J. Parasitol. 49, 235–246 (2019).PubMed 

Google Scholar 
Ancona, S., Sánchez-Colón, S., Rodríguez, C. & Drummond, H. E. Niño in the warm tropics: Local sea temperature predicts breeding parameters and growth of blue-footed boobies. J. Anim. Ecol. 80, 799–808 (2011).PubMed 

Google Scholar 
Drummond, H., Torres, R. & Krishnan, V. V. Buffered development: Resilience after aggressive subordination in infancy. Am. Nat. 161, 794–807 (2003).PubMed 

Google Scholar 
Merino, S. & Potti, J. High prevalence of hematozoa in nestlings of a passerine species, the pied flycatcher (Ficedula hypoleuca). Auk 112, 1041–1043 (1995).
Google Scholar 
Gutiérrez-López, R. et al. Low prevalence of blood parasites in a long-distance migratory raptor: The importance of host habitat. Parasit. Vectors 8, 189 (2015).PubMed 
PubMed Central 

Google Scholar 
Hellgren, O., Waldenström, J. & Bensch, S. A new PCR assay for simultaneous studies of Leucocytozoon, Plasmodium, and Haemoproteus from avian blood. J. Parasitol. 90, 797–802 (2004).CAS 
PubMed 

Google Scholar 
Bensch, S. et al. Host specificity in avian blood parasites: A study of Plasmodium and Haemoproteus mitochondrial DNA amplified from birds. Proc. Biol. Sci. 267, 1583–1589 (2000).CAS 
PubMed 
PubMed Central 

Google Scholar  More

Pandolfi JM, Connolly SR, Marshall DJ, Cohen AL. Projecting coral reef futures under global warming and ocean acidification. Science. 2011;333:418–22.CAS 
Article 

Google Scholar 
Baird AH, Marshall PA. Mortality, growth and reproduction in scleractinian corals following bleaching on the Great Barrier Reef. Mar Ecol Prog Ser. 2002;237:133–41.Article 

Google Scholar 
Lewis CL, Coffroth MA. The acquisition of exogenous algal symbionts by an octocoral after bleaching. Science. 2004;304:1490–2.CAS 
Article 

Google Scholar 
Matsuda SB, Chakravarti LJ, Cunning R, Huffmyer AS, Nelson CE, Gates RD, et al. Temperature mediated acquisition of rare heterologous symbionts promotes survival of coral larvae under ocean warming. Glob Chang Biol. 2022;28:2006–25.Article 

Google Scholar 
Thornhill DJ, Howells EJ, Wham DC, Steury TD, Santos SR. Population genetics of reef coral endosymbionts (Symbiodinium, Dinophyceae). Mol Ecol 2017;26:2640–59.CAS 
Article 

Google Scholar 
Diaz-Almeyda EM, Prada C, Ohdera AH, Moran H, Civitello DJ, Iglesias-Prieto R, et al. Intraspecific and interspecific variation in thermotolerance and photoacclimation in Symbiodinium dinoflagellates. Proc R Soc B. 2017;284:20171767.Article 

Google Scholar 
Howells EJ, Beltran VH, Larsen NW, Bay LK, Willis BL, van Oppen MJH. Coral thermal tolerance shaped by local adaptation of photosymbionts. Nat Clim Change. 2012;2:116–20.Article 

Google Scholar 
Voolstra CR, Buitrago-Lopez C, Perna G, Cardenas A, Hume BCC, Radecker N, et al. Standardized short-term acute heat stress assays resolve historical differences in coral thermotolerance across microhabitat reef sites. Glob Change Biol. 2020;26:4328–43.Article 

Google Scholar 
Behrendt L, Salek MM, Trampe EL, Fernandez VI, Lee KS, Kuhl M, et al. Phenochip: a single-cell phenomic platform for high-throughput photophysiological analyses of microalgae. Sci Adv. 2020;6:eabb2754.CAS 
Article 

Google Scholar 
Torda G, Donelson JM, Aranda M, Barshis DJ, Bay L, Berumen ML, et al. Rapid adaptive responses to climate change in corals. Nat Clim Change. 2017;7:627–36.Article 

Google Scholar 
Buerger P, Alvarez-Roa C, Coppin CW, Pearce SL, Chakravarti LJ, Oakeshott JG, et al. Heat-evolved microalgal symbionts increase coral bleaching tolerance. Sci Adv. 2020;6:eaba2498.CAS 
Article 

Google Scholar 
Kavousi J, Denis V, Sharp V, Reimer JD, Nakamura T, Parkinson JE. Unique combinations of coral host and algal symbiont genotypes reflect intraspecific variation in heat stress responses among colonies of the reef-building coral, Montipora digitata. Mar Biol. 2020;167:23.CAS 
Article 

Google Scholar 
Parkinson JE, Baums IB. The extended phenotypes of marine symbioses: ecological and evolutionary consequences of intraspecific genetic diversity in coral–algal associations. Front Microbiol. 2014;5:445.Article 

Google Scholar 
Andersson M, Johansson S, Bergman H, Xiao L, Behrendt L, Tenje M. A microscopy-compatible temperature regulation system for single-cell phenotype analysis— demonstrated by thermoresponse mapping of microalgae. Lab Chip. 2021;21:1694–705.CAS 
Article 

Google Scholar 
Hume B, D’Angelo C, Burt J, Baker AC, Riegl B, Wiedenmann J. Corals from the Persian/Arabian Gulf as models for thermotolerant reef-builders: prevalence of clade C3 Symbiodinium, host fluorescence and ex situ temperature tolerance. Mar Pollut Bull. 2013;72:313–22.CAS 
Article 

Google Scholar 
Karim W, Nakaema S, Hidaka M. Temperature effects on the growth rates and photosynthetic activities of Symbiodinium cells. J Mar Sci Eng. 2015;3:368–81.Article 

Google Scholar 
Takahashi S, Yoshioka-Nishimura M, Nanba D, Badger MR. Thermal acclimation of the symbiotic alga Symbiodinium spp. alleviates photobleaching under heat stress. Plant Physiol. 2013;161:477–85.CAS 
Article 

Google Scholar 
Robison JD, Warner ME. Differential impacts of photoacclimation and thermal stress on the photobiology of four different phylotypes of Symbiodinium (Pyrrhophyta). J Phycol. 2006;42:568–79.CAS 
Article 

Google Scholar 
Calabrese F, Voloshynoyska I, Musat F, Thullner M, Schlomann M, Richnow HH, et al. Quantitation and comparison of phenotypic heterogeneity among single cells of monoclonal microbial populations. Front Microbiol. 2019;10:2814.Article 

Google Scholar 
Martins BMC, Locke JOW. Microbial individuality: How single-cell heterogeneity enables population level strategies. Curr Opin Microbiol. 2015;24:104–12.CAS 
Article 

Google Scholar  More

Link activationContingency tables corresponding to the three cases described in the “Methods” section are shown in Table 1. This Table is quite revealing in several ways. The most interesting aspect is that the highest probability of link establishment occurs when an agreement is activated (Operational Activation in t).Table 1 Contingency tables.Full size tableIn this case, the probability of activation of a new link is 8.8%—namely, the ratio of new activation 7.3% to the total number of links that were not active at year t-1 (82.6%)—which is significantly higher than in the case of links not covered by a commercial agreement (No Trade Agreement), amounting to 1.4%.Therefore, the findings show that operational activation is associated with creating new trade relations between two particular countries. The third set, which considers links where a trade agreement exists in both years (t-1) and t (Trade Agreement in t-1 and t), also shows a consistent activation probability of 6%. This result confirms the assumption that the coverage of a commercial agreement, and not only its implementation, encourages the genesis of new links.Moreover, Table 1 suggests some interesting considerations on trade persistence. To establish these probabilities, we focus on the row totals in which a trade relationship is present at year (t-1), i.e., 28.8% in the case Trade Agreement in t-1 and t. The presence of an agreement influences in a positive way the probability of maintaining a trade relationship. In fact, when a trade agreement is present in both years, (t-1) and t, the probability of preserving the trade relationship is 87.1% ((frac{25.1}{28.8}times {100})), while when a trade agreement is activated at year t, the probability slightly decreases to 81.6%. In cases where trade agreements are missing (No Trade Agreement in t) we observe the probability of retaining a relationship decreases to 77.3%.Another interesting aspect concerns the probability of link deactivation. Once more, the coverage of a trade agreement favors a lower likelihood of deactivation of existing links. The ratio of the percentage of links that were active at year (t-1) and are no more active at year t to the total is 22.7% ((frac{1}{4.4}times {100})) in the case of a lack of agreement. This probability decreases to 18.4% ((frac{3.2}{17.4}times {100})) if we consider only the year of activation of the agreement (Operational Activation), and drops to 12.8% ((frac{3.7}{28.8}times {100})) when looking at agreements present in both years.Together, these results provide insights into the role of trade agreements in the network topology of cereal trade. While the establishment of a trade agreement promotes the potential for new trade links, the presence of the agreement in two consecutive years allows both to maintain an existing relationship and reduce the likelihood of link shutdowns.Flow variationsIn this second part, we study the impact of trade agreements on existing trade flows, analyzing the relationship between the flows at time t and the flows at time (t-1) in each of the three cases described in the “Methods” section—i.e., No trade agreements, Operational Activation in t, and Trade agreement in t-1 and t—measured in US$, Kcal and m(^3) of virtual water.Figure 3Kernel Density scatterplot between trade flows of cereals at time t (on the y-axis) and time (t-1) (on the x-axis) for the three different sets: No trade agreements (column a), Operational Activation in t (b), and Trade agreement in (t-1) and t (c). Panels in the first, second and third row refer to flows in US$, Kcal, and virtual water (m(^3)), respectively. Flow values are shown on a logarithmic scale. The color bar indicates probability densities, and the bisector is highlighted. Notice (i) the higher volumes in the case of flows covered by trade agreement and (ii) a a less relevant increase in volume when the flows are seen in the virtual water lens.Full size imageFigure 3 shows three different scatterplots for each unit of measure (US$ and Kcal and m(^3)). The scatterplots are colored by Kernel Density Estimation (KDE), a non-parametric technique for probability density functions. KDE aims to take a finite sample of data and infer the underlying probability density function. Figure 3 relates the flows at time (t-1) with the flows at time t, both reported on a logarithmic scale since the quantities span several orders of magnitude. Let’s start focusing on flows in terms of dollars and kilocalories. What stands out from the figure is the displacement of the flows toward higher values when they are covered by trade agreements (Trade Agreement in t-1 and t), compared to the case where flows have no trade agreement.We have quantitative evidence of this result by looking at Table 2 where the average flows in both years are shown. The average values of flows in both US$ and Kcal are much higher when there is a trade agreement over time (Trade agreement in t-1 and t). Flows have an average value of (6.13times 10^{7})$, larger than the mean of (3.05times 10^{7})$ achieved by flows not covered by a trade agreement. By comparing the distributions of the two distinct sets with different dimensions by applying the non-parametric Mann-Whitney test, we stand to evaluate this result as extremely significant (p-value approximately 0).Table 2 Average values of trade flows and flow variation index (rho _{ij}) for each of the three sets, in US$ (a), Kcal (b), and Virtual water (VW, m(^3)). The bar indicates the average operator.Full size tableAlso, while operational activation plays a crucial role in creating new links in the global cereal trade, it does not appear to hold central importance in driving flow increases. The average value of flows in both years (t-1) and t are, in fact, smaller than those not covered by trade agreements.The view appears slightly different when we look at the values in terms of virtual water (VW, m(^3)), i.e., the sum of the blue and green components. Flows with a commercial agreement show higher averages values than those not covered by agreements (see panel (c) of Table 2), but the increase is significantly lower than the one recorded in the other two units (US$ and Kcal). The increase recorded in dollars is about 100%, while in terms of virtual water this increase is less than 30%. In the next subsection, we will focus on this peculiar behavior, which reveals a different water content of the goods traded along links covered or not by agreements.Another significant result that emerges from Fig. 3 is the smaller amplitude (around the bisector) of the cloud in the case of link covered by agreements in both years (t-1) and t. This is confirmed by comparing the weighted average of the absolute value of the inter-annual flow variation index (overline{rho _{ij}}_{w}) (weights are the flows traded in the year (t-1)). The index (rho _{ij}) is used to highlight cases where the activation or the presence of the agreement generates a significant flow increase.Larger (rho _{ij}) values correspond to larger average variations from year (t-1) to year t. Accordingly, we observe that in the presence of trade agreement at time (t-1) and t a smaller (rho _{ij}) value of 24.79 percentage points (p.p) is found (see panel (a) of Table 2).Considering all the units (US$, Kcal, and m(^3)), this value is about half of the average inter-annual variation that occurs when there is no trade agreement. Hence, the presence of a commercial agreement over time reduces large fluctuations, stabilizing the year-to-year variations.To shed light on the response of water flows to the occurrence of the agreement, we refer to water productivity (WP)34, both in economic and nutritional terms. Table 3 shows that the Nutritional WP for the total virtual water is, on average, 35% higher in the flows under a trade agreement than in flows that are not under any treaty, while the Economic WP is 62% higher. We also analyze the two virtual water components, blue and green, separately.Interestingly, for blue water in the presence of a trade agreement, the Nutritional WP and the Economic WP for the flows covered by trade agreement are, on average, 68% and 93% higher than for the flows not covered by agreements. In other words, for one cubic meter of water used for grain production, more kilo-calories and dollars are exchanged when an agreement is in place, and this difference is even more significant in terms of blue water.Table 3 Average of nutritional ((mathrm {kcal/m^3})) and economic ((mathrm {US$/m^3})) water productivity (WP) for the total, blue and green virtual water.Full size tableWe also investigate in detail which products contribute most to the imbalance between flows in terms of kcal or water. To this aim, Fig. 4 reports the nutritional WP for each grain item distinguishing whether or not there is a commercial agreement (similar results occur if the economic WP is considered).The figure highlights that the nutritional WP is generally higher in the case where flows are covered by trade agreements (green bars). The most noticeable cases are Maize and Wheat, which are also the most traded products: the value of nutritional WP increases from 1978 (mathrm {kcal/m^3}) (No trade agreement) to 2851 (mathrm {kcal/m^3}) in case of a trade agreement for Wheat, and from 4471 (mathrm {kcal/m^3}) to 5026 for Maize.Figure 4The bar chart shows the nutritional WP for each cereal product in the two sets of Trade agreement in t-1 and t (in green) and No trade agreement (in red). The number over the bars represents the percentage of kcal traded for each product compared to the total kcal of all cereals. Note that green bars are higher than the red ones in 80% of cases.Full size imageA few products have a higher nutritional WP value when the flows are not involved in any treaty, e.g., Rye. This behavior can be traced back to a few flows that dominate the market between countries not linked by trade agreements. For example, trade in Rye in 2014 is attributable to just two major flows in terms of caloric intake relative to water quantity (notably, one between Germany and Japan, the other between Russia and Turkey).Figure 4 clearly shows that grains characterized by greater water efficiency generally move along the links covered by agreements.Performance of trade agreements in increasing flowOur results show that links covered by agreements exhibit larger flows than links not covered by treaties. We also intend to obtain information about the possible flow increase under a specific agreement.As mentioned in the “Methods” section, we selected only those operating links when the agreement came into force to evaluate the variation index ((rho _a)) under a specific treaty. Consequently, since there are trade agreements that came into force before the time interval considered, these are excluded from this analysis. As a result, the total number of agreements selected for this analysis is 99, 61 of which show an increase (positive (rho _{a}) values), while the remaining 38 exhibits a decrease in the flux intensities compared to the overall global trend. We present in Table 5 the results for positive (rho _{a}) variations, while trade agreements with negative (rho _{a}) values are reported in Supplementary Material (5). We provide this analysis in terms of economic flows (US$), but very similar results are obtained if calories (kcal) or virtual water (m(^3)) are chosen as the unit of measure.Table 4 Flow values in millions of dollars in year t and percent changes (rho _{a}) from (t-1) to t for each trade agreement.Full size tableWhat stands out in Table 4 is that most of the positive percentage changes occur in Europe and Central Asia regions. This may be due to long-term commercial activities in Europe, which are supported by the geographical proximity of the countries, as well as the wide variety of political and economic treaties among them. Europe, in fact, is characterized by a fourfold increase in cereal production since the 1960s due to the adoption of the Common Agricultural Policy, which has intensified trade in Europe and towards external markets30.A closer inspection of Table 4 shows that among the agreements with the most significant flows that showed the greatest increases, we find EEA (European Economic Area) in Europe and Central Asia, Japan-ASEAN in East Asia and Pacific, and COMESA in Sub-Saharan Africa.With lower flow values but large increases ((rho _{a})) due to the entry into force of trade agreements, the India-Sri Lanka agreement in South Asia stands out above all others. Also, the treaty signed in 2013 between EU-Colombia and Peru shows significant variations in terms of the percentage of flow increase, but the volume of the corresponding flow is inferior when compared with other trade agreements. On the other hand, the North American Free Trade Agreement (NAFTA), which became effective in 1994, has a lower (rho _{a}) value, but the flows on which the variation is calculated are significantly higher. More

Speciation models, conditional and intrinsic stability constants and EDH model parametersThe complete set of analytical results for the Zn(II)/ligand systems, including conditional stability constants (logβ) for the formation of hydrolysed Zn(II)–ligand complexes, of zinc hydroxide complexes and of Zn(II)–ligand complexes as well as acidity constants for citrate and DFOB at different ionic strength in NaCl and T = 298.1 K are reported in Table 1 and SI Table 2. Also shown are the values for the optimised parameter C and the intrinsic association constants (logβ0). SI Table 1 lists all the reactions included in the speciation models used to fit the potentiometric titrations and SI Fig. 2 shows single crystal X-ray structures for some of the proposed structures including ZnH2Cit2, Zn2Cit2(H2O)2 and ZnCit22− taken from the Cambridge Crystallographic Data Base. Figure 3 displays the experimentally determined conditional Zn(II)–ligand stability constants and the corresponding EDH model from this study. Also shown are logb values from the literature for [Zn(HCit)] and [Zn(Cit)]− for the Zn(II)/Cit system and [Zn(H2DFOB)]+, [Zn(HDFOB)] and [Zn(DFOB)]− for the Zn(II)/DFOB system. Examples of titration curves and manually fitted models along with the speciation model considered and the experimental conditions are included in the supporting information (see SI Figs. 3 and 4). Only models that fitted the experimental data with sigma values below 5 were considered. Examples of Hyperquad files showing titrations and model fits for Zn(II)/Cit and Zn(II)/DFOB systems and of Excel calculation files for the application of the EDH model to the Zn(II)/DFOB experimental data set, including error calculation for C and logβ0 are uploaded to the Zenodo repository (https://doi.org/10.5281/zenodo.4548162). Errors reported for measured logβ and calculated (modelled) logβ0 and C values have no detectable effect on subsequent speciation calculations. The errors reported on C are slightly larger than in comparable studies22, however, a sensitivity analysis on the two Zn(II)–ligand species with the largest relative error on C found that logβ0 remains within its error range even when logβ0 was recalculated for the maximum and minimum possible C values. The stability constant we report for specific Zn(II)–L complexes at specific ion strengths are in line with literature reports (Fig. 3). For example, the logβ for the formation of [Zn(Cit)]− in 0.15 mol dm−3 NaCl shows good agreement with the value reported by Cigala and co-workers in 0.15 mol dm−3 NaCl; 4.79 vs. 4.7126. We note, however, also significant variations within reported conditional logβ values as seen Fig. 3, with published values for the formation of [Zn(HCit)] and [Zn(Cit)]− in different 1:1 electrolytes differing over two orders of magnitudes. This highlights the analytical challenges associated with accurate and precise logβ determinations of low affinity metal–ligand complexes, in low ion strength solutions33.Figure 3Experimental Zn(II)–ligand conditional stability constants (logβ) for (a) citrate and (b) DFOB at 0.05, 0.15, 0.3, 0.5 and 1 mol dm−3 in NaCl solution (open circles) determined using potentiometric titrations. For each species, the Extended Debye-Hückel (EDH) model has been parameterised using the experimental data (see Table 1 for C and logβ0) and the corresponding model is shown as a solid line. Literature data is included in the figure for comparison (closed circles) from Cigala et al. (2015, NaNO3 and NaCl), Capone et al. (1986, KNO3), Daniele et al. (1988, KNO3), Field et al. (1975, KNO3), Matsushima et al. (1963, NaCl) and Li et al. 1959, NaCl) for the Zn–H–Cit system and from Schijf et al. (2015, NaClO4), Farkas et al. (1997, KCl) and Hernlem et al. (1996, KNO3) for the Zn-H-DFOB system. Note the large variability reported for the Zn–Cit system at 0.1 and 0.15 mol dm−3. We find good agreement with the data published by Sammartano and co-workers26,69.Full size imageThe final speciation scheme with the best statistical fits and with chemically sensible species are given in Table 1. From the eight Zn-Cit species initially considered (SI Table 1), the inclusion of five species resulted in model fits with sigma values below 5. For the Zn(II)/Cit system, the dominant species are [Zn(Cit)]−, [Zn(HCit)], and [Zn2(Cit)2(OH)2]4−. We report also the presence of a [Zn(Cit)(OH)3]4− complex above pH 9 in significant amounts ( > 20%) and we confirm the presence of [Zn(Cit)2]4− if citrate is present in large excess26,31. The presence of [Zn(Cit)]−, [Zn(HCit)] and [Zn(Cit)2]4− were confirmed in pH 6 solutions by mass spectrometry. To confirm the presence of [Zn(Cit)(OH)3]4−, further investigations are warranted. SI Fig. 5 shows the species distributions in the Zn(II)–Cit system with different Zn:L molar ratios (1:1, 1:2 and 1:10) and different concentrations (between 10–6 and 10–3 for Zn and 10–5 and 10–3 for citrate). We find that [Zn(Cit)]− dominates (i.e., formation relative to total Zn is above 50%) between pH 5 and 7.5, [Zn2(Cit)2(OH)2]4− dominates between pH 7.5 and 10 and [Zn(Cit)(OH)3]4− dominates at pH values above 10. We find the formation of [Zn(Cit)2]4− only at Zn:Cit molar ratio of 1:10 and [Zn] and [L] concentrations of 10–4 and 10–3 mol dm−3, respectively. The species [Zn(Cit)(OH)]2− and Zn(Cit)(OH))2]3− possibly form at higher pH but were excluded from the final model. We noted that for titrations of solutions with Zn:Cit molar ratios below 1:3, it was not possible to refine the stepwise stability constant (logK) for [Zn(Cit)2]4− to within ± 0.09 log units, indicating that it is an unstable species that forms at negligible concentrations. The stability constants for zinc complexation with citrate decrease with increasing ionic strength. Table 1 shows that the most significant change is seen between 0.05 and 0.15 mol dm−3 NaCl, where there is approximately a 0.5 to 1.5 log unit change. In dilute solutions, stability constants are sensitive to small increases in ionic strength because changes in the effective concentration (activity) of ions are large.For the Zn(II)–DFOB system, all the stability constants measured during this study are in good agreement with those reported in the literature50,51,53. For example, the stability constant we report for [Zn(HDFOB)] in 0.5 mol dm−3 NaCl is 19.34. This is within ~ 0.5 log units of the stability constant reported by Schijf and co-workers in 0.7 mol dm−3 NaClO4 solutions53. The speciation scheme we report differs slightly from that predicted by Schijf based on a three-step model. Our model does not include the bidentate species [Zn(H3DFOB)]2+, the weakest and least stable Zn(II)–DFOB species. In Table 1, we report stability constants for hexadentate [Zn(DFOB)]− and [Zn(HDFOB)] and tetradentate [Zn(H2DFOB)]+. We observe that as the denticity of the complex increases, so does the strength of the stability constant. The stepwise stability constant (K) differs by approximately 2 log units between the formation of the three different DFOB:Zn:H species (7.75, 9.88, 11.67, see Table 1). DFOB complexation of Zn(II) shows the same pattern of ionic strength dependence as citrate, with the greatest decrease of logβ occurring between 0.05 and 0.15 mol dm−3 NaCl, the region of most importance to the rhizosphere.The absolute decrease in [ZnL] and [Zn(HL)] stability constants between 0.05 and 0.15 mol dm−3 is approximately equal for citrate and DFOB species, average 1.58 vs. 1.73, respectively. This is explained by the effect of ionic strength primarily depending on the charge of the ions involved and free citrate and DFOB having the same electrostatic charge (−3). The ionic strength dependent parameter C shows no systematic change for neither citrate nor DFOB species. The good agreement between literature50,51,52,54,68,69,70 and our speciation models as well as the conditional logβ and pKa values validates the use of a single analytical method for the determination of the LEP. We note that the proposed formation of the trihydroxy Zn(II) citrate complex at pH above 10, needs to be investigated in greater detail using supplementary techniques. However, the formation of this species is not relevant for the pH range of interest in our study. As discussed below the main prevailing species in solution are those of 1:1:0 and 2:2:−2 stoichiometry for Zn:Cit:H.Figure 4 shows intrinsic stability constants for the formation of [Zn(Cit)]− and [Zn(HCit)] determined (i) using the Davies equation and the conditional association constants determined at different ionic strengths and (ii) fitting the parameterised EDH equation to the full ionic strength dataset. We find statistically significant (p  More

Ternes, T. A. Occurrence of drugs in German sewage treatment plants and rivers. Water Res. 32, 3245–3260 (1998).CAS 
Article 

Google Scholar 
Heberer, T. Occurrence, fate, and removal of pharmaceutical residues in the aquatic environment: A review of recent research data. Toxicol. Lett. 131, 5–17 (2002).CAS 
PubMed 
Article 

Google Scholar 
Luo, Y. et al. A review on the occurrence of micropollutants in the aquatic environment and their fate and removal during wastewater treatment. Sci. Total Environ. 473–474, 619–641 (2014).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Ternes, T., Joss, A. & Oehlmann, J. Occurrence, fate, removal and assessment of emerging contaminants in water in the water cycle (from wastewater to drinking water). Water Res. 72, 1–2 (2015).CAS 
PubMed 
Article 

Google Scholar 
Zorita, S., Mårtensson, L. & Mathiasson, L. Occurrence and removal of pharmaceuticals in a municipal sewage treatment system in the south of Sweden. Sci. Total Environ. 407, 2760–2770 (2009).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Yang, Y., Ok, Y. S., Kim, K.-H., Kwon, E. E. & Tsang, Y. F. Occurrences and removal of pharmaceuticals and personal care products (PPCPs) in drinking water and water/sewage treatment plants: A review. Sci. Total Environ. 596–597, 303–320 (2017).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Eggen, R. I. L., Hollender, J., Joss, A., Schärer, M. & Stamm, C. Reducing the discharge of micropollutants in the aquatic environment: The benefits of upgrading wastewater treatment plants. Environ. Sci. Technol. 48, 7683–7689 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Kümmerer, K., Dionysiou, D. D., Olsson, O. & Fatta-Kassinos, D. Reducing aquatic micropollutants: Increasing the focus on input prevention and integrated emission management. Sci. Total Environ. 652, 836–850 (2019).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Love, A. C., Crooks, N. & Ford, A. T. The effects of wastewater effluent on multiple behaviours in the amphipod. Gammarus pulex. Environ. Pollut. 267, 115386 (2020).CAS 
PubMed 
Article 

Google Scholar 
Rodrigues, C., Guimarães, L. & Vieira, N. Combining biomarker and community approaches using benthic macroinvertebrates can improve the assessment of the ecological status of rivers. Hydrobiolgia 839, 1–24 (2019).CAS 
Article 

Google Scholar 
Previšić, A. et al. Aquatic macroinvertebrates under stress: Bioaccumulation of emerging contaminants and metabolomics implications. Sci. Total Environ. 704, 135333 (2020).ADS 
PubMed 
Article 
CAS 

Google Scholar 
De Castro-Català, N., Muñoz, I., Riera, J. L. & Ford, A. T. Evidence of low dose effects of the antidepressant fluoxetine and the fungicide prochloraz on the behavior of the keystone freshwater invertebrate Gammarus pulex. Environ. Pollut. 231, 406–414 (2017).PubMed 
Article 
CAS 

Google Scholar 
Pisa, L. W. et al. Effects of neonicotinoids and fipronil on non-target invertebrates. Environ. Sci. Pollut. Res. 22, 68–102 (2015).CAS 
Article 

Google Scholar 
Jonsson, M., Fick, J., Klaminder, J. & Brodin, T. Antihistamines and aquatic insects: Bioconcentration and impacts on behavior in damselfly larvae (Zygoptera). Sci. Total Environ. 472, 108–111 (2014).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Stoks, R. & Córdoba-Aguilar, A. Evolutionary ecology of odonata: A complex life cycle perspective. Annu. Rev. Entomol. 57, 249–265 (2012).CAS 
PubMed 
Article 

Google Scholar 
Janssens, L. & Stoks, R. Stronger effects of Roundup than its active ingredient glyphosate in damselfly larvae. Aquat. Toxicol. 193, 210–216 (2017).CAS 
PubMed 
Article 

Google Scholar 
Brodin, T. & Johansson, F. Conflicting selection pressures on the growth/predation-risk trade-off in a damselfly. Ecology 85, 2927–2932 (2004).Article 

Google Scholar 
Smith, B. R. & Blumstein, D. T. Fitness consequences of personality: A meta-analysis. Behav. Ecol. 19, 448–455 (2008).Article 

Google Scholar 
Monserrat, J. M. et al. Pollution biomarkers in estuarine animals: Critical review and new perspectives. Comp. Biochem. Physiol. Part C 146, 221–234 (2007).
Google Scholar 
Ågerstrand, M. et al. Emerging investigator series: Use of behavioural endpoints in the regulation of chemicals. Environ. Sci. Process. Impacts 22, 49–65 (2020).PubMed 
Article 

Google Scholar 
Sardo, A. M. & Soares, A. M. V. M. Assessment of the effects of the pesticide imidacloprid on the behaviour of the aquatic oligochaete Lumbriculus variegatus. Arch. Environ. Contam. Toxicol. 58, 648–656 (2010).CAS 
PubMed 
Article 

Google Scholar 
Bossus, M. C., Guler, Y. Z., Short, S. J., Morrison, E. R. & Ford, A. T. Behavioural and transcriptional changes in the amphipod Echinogammarus marinus exposed to two antidepressants, fluoxetine and sertraline. Aquat. Toxicol. 151, 46–56 (2014).CAS 
PubMed 
Article 

Google Scholar 
Rodrigues, A. C. M. et al. Behavioural responses of freshwater planarians after short-term exposure to the insecticide chlorantraniliprole. Aquat. Toxicol. 170, 371–376 (2016).CAS 
PubMed 
Article 

Google Scholar 
Nielsen, M. E. & Roslev, P. Behavioral responses and starvation survival of Daphnia magna exposed to fluoxetine and propranolol. Chemosphere 211, 978–985 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Al-Badran, A. A., Fujiwara, M. & Mora, M. A. Effects of insecticides, fipronil and imidacloprid, on the growth, survival, and behavior of brown shrimp Farfantepenaeus aztecus. PLoS ONE 14, e0223641 (2019).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Leonard, J. A., Cope, W. G., Barnhart, M. C. & Bringolf, R. B. Metabolomic, behavioral, and reproductive effects of the synthetic estrogen 17 α-ethinylestradiol on the unionid mussel Lampsilis fasciola. Aquat. Toxicol. 150, 103–116 (2014).CAS 
PubMed 
Article 

Google Scholar 
Robert Michaud, M. et al. Metabolomics reveals unique and shared metabolic changes in response to heat shock, freezing and desiccation in the Antarctic midge, Belgica antarctica. J. Insect Physiol. 54, 645–655 (2008).CAS 
PubMed 
Article 

Google Scholar 
Chou, H., Pathmasiri, W., Deese-Spruill, J., Sumner, S. & Buchwalter, D. B. Metabolomics reveal physiological changes in mayfly larvae (Neocloeon triangulifer) at ecological upper thermal limits. J. Insect Physiol. 101, 107–112 (2017).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Hidalgo, K., Beaugeard, E., Renault, D., Dedeine, F. & Lécureuil, C. Physiological and biochemical responses to thermal stress vary among genotypes in the parasitic wasp Nasonia vitripennis. J. Insect Physiol. 117, 103909 (2019).PubMed 
Article 
CAS 

Google Scholar 
Hines, A., Oladiran, G. S., Bignell, J. P., Stentiford, G. D. & Viant, M. R. Direct sampling of organisms from the field and knowledge of their phenotype: Key recommendations for environmental metabolomics. Environ. Sci. Technol. 41, 3375–3381 (2007).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Agbo, S. O. et al. Changes in Lumbriculus variegatus metabolites under hypoxic exposure to benzo(a)pyrene, chlorpyrifos and pentachlorophenol: Consequences on biotransformation. Chemosphere 93, 302–310 (2013).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Venter, L. et al. Uncovering the metabolic response of abalone (Haliotis midae) to environmental hypoxia through metabolomics. Metabolomics 14, 49 (2018).PubMed 
Article 
CAS 

Google Scholar 
Melvin, S. D. Short-term exposure to municipal wastewater influences energy, growth, and swimming performance in juvenile Empire Gudgeons (Hypseleotris compressa). Aquat. Toxicol. Amst. Neth. 170, 271–278 (2016).CAS 
Article 

Google Scholar 
Du, S. N. N. et al. Metabolic costs of exposure to wastewater effluent lead to compensatory adjustments in respiratory physiology in bluegill sunfish. Environ. Sci. Technol. 52, 801–811 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Mehdi, H., Dickson, F. H., Bragg, L. M., Servos, M. R. & Craig, P. M. Impacts of wastewater treatment plant effluent on energetics and stress response of rainbow darter (Etheostoma caeruleum) in the Grand River watershed. Comp. Biochem. Physiol. B 224, 270–279 (2018).CAS 
PubMed 
Article 

Google Scholar 
Simmons, D. B. D. et al. Altered expression of metabolites and proteins in wild and caged fish exposed to wastewater effluents in situ. Sci. Rep. 7, 17000 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
McCallum, E. S. et al. Exposure to wastewater effluent affects fish behaviour and tissue-specific uptake of pharmaceuticals. Sci. Total Environ. 605–606, 578–588 (2017).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Simmons, D. B. D. et al. Reduced anxiety is associated with the accumulation of six serotonin reuptake inhibitors in wastewater treatment effluent exposed goldfish Carassius auratus. Sci. Rep. 7, 17001 (2017).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gauthier, P. T. & Vijayan, M. M. Municipal wastewater effluent exposure disrupts early development, larval behavior, and stress response in zebrafish. Environ. Pollut. 259, 113757 (2020).CAS 
PubMed 
Article 

Google Scholar 
Finotello, S., Feckler, A., Bundschuh, M. & Johansson, F. Repeated pulse exposures to lambda-cyhalothrin affect the behavior, physiology, and survival of the damselfly larvae Ischnura graellsii (Insecta; Odonata). Ecotoxicol. Environ. Saf. 144, 107–114 (2017).CAS 
PubMed 
Article 

Google Scholar 
Späth, J. et al. Novel metabolomic method to assess the effect-based removal efficiency of advanced wastewater treatment techniques. Environ. Chem. https://doi.org/10.1071/EN19270 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Späth, J. et al. Oxylipins at intermediate larval stages of damselfly Coenagrion hastulatum as biochemical biomarkers for anthropogenic pollution. Environ. Sci. Pollut. Res. https://doi.org/10.1007/s11356-021-12503-x (2021).Article 

Google Scholar 
Späth, J. et al. Metabolomics reveals changes in metabolite profiles due to growth and metamorphosis during the on. J. Insect Physiol. 136, 104341 (2022).PubMed 
Article 
CAS 

Google Scholar 
Rodriguez, A. et al. ToxTrac: A fast and robust software for tracking organisms. Methods Ecol. Evol. 9, 460–464 (2018).Article 

Google Scholar 
Treit, D. & Fundytus, M. Thigmotaxis as a test for anxiolytic activity in rats. Pharmacol. Biochem. Behav. 31, 959–962 (1988).CAS 
PubMed 
Article 

Google Scholar 
Brodin, T. Behavioral syndrome over the boundaries of life—carryovers from larvae to adult damselfly. Behav. Ecol. 20, 30–37 (2009).Article 

Google Scholar 
Jonsson, M. et al. High-speed imaging reveals how antihistamine exposure affects escape behaviours in aquatic insect prey. Sci. Total Environ. 648, 1257–1262 (2019).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Gullberg, J., Jonsson, P., Nordström, A., Sjöström, M. & Moritz, T. Design of experiments: An efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry. Anal. Biochem. 331, 283–295 (2004).CAS 
PubMed 
Article 

Google Scholar 
Teixeira, P. F. et al. A multi-step peptidolytic cascade for amino acid recovery in chloroplasts. Nat. Chem. Biol. 13, 15–17 (2017).CAS 
PubMed 
Article 

Google Scholar 
Rohart, F., Gautier, B., Singh, A. & Cao, K.-A.L. mixOmics: An R package for ‘omics feature selection and multiple data integration. PLOS Comput. Biol. 13, e1005752 (2017).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Gorrochategui, E., Jaumot, J., Lacorte, S. & Tauler, R. Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: Overview and workflow. TrAC Trends Anal. Chem. 82, 425–442 (2016).CAS 
Article 

Google Scholar 
Chong, J., Wishart, D. S. & Xia, J. Using MetaboAnalyst 40 for comprehensive and integrative metabolomics data analysis. Curr. Protoc. Bioinform. 68, e86 (2019).Article 

Google Scholar 
Van Gossum, H. et al. Behaviour of damselfly larvae (Enallagma cyathigerum) (Insecta, Odonata) after long-term exposure to PFOS. Environ. Pollut. 157, 1332–1336 (2009).PubMed 
Article 
CAS 

Google Scholar 
Bownik, A., Ślaska, B., Bochra, J., Gumieniak, K. & Gałek, K. Procaine penicillin alters swimming behaviour and physiological parameters of Daphnia magna. Environ. Sci. Pollut. Res. 26, 18662–18673 (2019).CAS 
Article 

Google Scholar 
Di Cicco, M. et al. Effects of diclofenac on the swimming behavior and antioxidant enzyme activities of the freshwater interstitial crustacean Bryocamptus pygmaeus (Crustacea, Harpacticoida). Sci. Total Environ. 799, 149461 (2021).ADS 
PubMed 
Article 
CAS 

Google Scholar 
Di Nica, V., González, A. B. M., Lencioni, V. & Villa, S. Behavioural and biochemical alterations by chlorpyrifos in aquatic insects: An emerging environmental concern for pristine Alpine habitats. Environ. Sci. Pollut. Res. 27, 30918–30926 (2020).Article 
CAS 

Google Scholar 
Cappello, T. et al. Sex steroids and metabolic responses in mussels Mytilus galloprovincialis exposed to drospirenone. Ecotoxicol. Environ. Saf. 143, 166–172 (2017).CAS 
PubMed 
Article 

Google Scholar 
Rodrigues, A. C. M. et al. Energetic costs and biochemical biomarkers associated with esfenvalerate exposure in Sericostoma vittatum. Chemosphere 189, 445–453 (2017).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Ji, C. et al. Proteomic and metabolomic analysis of earthworm Eisenia fetida exposed to different concentrations of 2,2′,4,4′-tetrabromodiphenyl ether. J. Proteom. 91, 405–416 (2013).CAS 
Article 

Google Scholar 
Felten, V. et al. Physiological and behavioural responses of Gammarus pulex (Crustacea: Amphipoda) exposed to cadmium. Aquat. Toxicol. 86, 413–425 (2008).CAS 
PubMed 
Article 

Google Scholar 
De Lange, H. J., Peeters, E. T. H. M. & Lürling, M. Changes in ventilation and locomotion of Gammarus pulex (Crustacea, Amphipoda) in response to low concentrations of pharmaceuticals. Hum. Ecol. Risk Assess. Int. J. 15, 111–120 (2009).Article 
CAS 

Google Scholar 
Ashauer, R., Caravatti, I., Hintermeister, A. & Escher, B. I. Bioaccumulation kinetics of organic xenobiotic pollutants in the freshwater invertebrate Gammarus pulex modeled with prediction intervals. Environ. Toxicol. Chem. 29, 1625–1636 (2010).CAS 
PubMed 
Article 

Google Scholar 
Schroeder-Spain, K., Fisher, L. L. & Smee, D. L. Uncoordinated: Effects of sublethal malathion and carbaryl exposures on juvenile and adult blue crabs (Callinectes sapidus). J. Exp. Mar. Biol. Ecol. 504, 1–9 (2018).CAS 
Article 

Google Scholar 
Janssens, L. & Stoks, R. Synergistic effects between pesticide stress and predator cues: Conflicting results from life history and physiology in the damselfly Enallagma cyathigerum. Aquat. Toxicol. 132–133, 92–99 (2013).PubMed 
Article 
CAS 

Google Scholar 
Ernest, S. K. M. Homeostasis. In Encyclopedia of Ecology (eds Jørgensen, S. E. & Fath, B. D.) 1879–1884 (Academic Press, 2008).Chapter 

Google Scholar 
Karanova, M. V. & Andreev, A. A. Free amino acids and reducing sugars in the freshwater shrimp Gammarus lacustris (Crustacea, Amphipoda) at the initial stage of preparation to winter season. J. Evol. Biochem. Physiol. 46, 335–340 (2010).CAS 
Article 

Google Scholar 
Maity, S. et al. Starvation causes disturbance in amino acid and fatty acid metabolism in Diporeia. Comp. Biochem. Physiol. B 161, 348–355 (2012).CAS 
PubMed 
Article 

Google Scholar 
Cappello, T. et al. Impact of environmental pollution on caged mussels Mytilus galloprovincialis using NMR-based metabolomics. Mar. Pollut. Bull. 77, 132–139 (2013).CAS 
PubMed 
Article 

Google Scholar 
Jiang, Y., Jiao, H., Sun, P., Yin, F. & Tang, B. Metabolic response of Scapharca subcrenata to heat stress using GC/MS-based metabolomics. PeerJ 8, e8445 (2020).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Roznere, I., Watters, G. T., Wolfe, B. A. & Daly, M. Effects of relocation on metabolic profiles of freshwater mussels: Metabolomics as a tool for improving conservation techniques. Aquat. Conserv. Mar. Freshw. Ecosyst. 27, 919–926 (2017).Article 

Google Scholar 
Cappello, T., Maisano, M., Mauceri, A. & Fasulo, S. 1H NMR-based metabolomics investigation on the effects of petrochemical contamination in posterior adductor muscles of caged mussel Mytilus galloprovincialis. Ecotoxicol. Environ. Saf. 142, 417–422 (2017).CAS 
PubMed 
Article 

Google Scholar 
Cao, C. & Wang, W.-X. Chronic effects of copper in oysters Crassostrea hongkongensis under different exposure regimes as shown by NMR-based metabolomics. Environ. Toxicol. Chem. 36, 2428–2435 (2017).CAS 
PubMed 
Article 

Google Scholar 
Aru, V., Sarais, G., Savorani, F., Engelsen, S. B. & Cesare Marincola, F. Metabolic responses of clams, Ruditapes decussatus and Ruditapes philippinarum, to short-term exposure to lead and zinc. Mar. Pollut. Bull. 107, 292–299 (2016).CAS 
PubMed 
Article 

Google Scholar 
Tufi, S., Stel, J. M., de Boer, J., Lamoree, M. H. & Leonards, P. E. G. Metabolomics to explore imidacloprid-induced toxicity in the central nervous system of the freshwater snail Lymnaea stagnalis. Environ. Sci. Technol. 49, 14529–14536 (2015).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Tanguy, A., Boutet, I. & Moraga, D. Molecular characterization of the glutamine synthetase gene in the Pacific oyster Crassostrea gigas: Expression study in response to xenobiotic exposure and developmental stage. Biochim. Biophys. Acta BBA 1681, 116–125 (2005).CAS 
PubMed 
Article 

Google Scholar 
Chen, X., Shi, X., Gan, F., Huang, D. & Huang, K. Glutamine starvation enhances PCV2 replication via the phosphorylation of p38 MAPK, as promoted by reducing glutathione levels. Vet. Res. 46, 32 (2015).PubMed 
PubMed Central 
Article 
CAS 

Google Scholar 
Leroy, D., Haubruge, E., De Pauw, E., Thomé, J. P. & Francis, F. Development of ecotoxicoproteomics on the freshwater amphipod Gammarus pulex: Identification of PCB biomarkers in glycolysis and glutamate pathways. Ecotoxicol. Environ. Saf. 73, 343–352 (2010).CAS 
PubMed 
Article 

Google Scholar 
Ch, R., Singh, A. K., Pandey, P., Saxena, P. N. & Mudiam, M. K. R. Identifying the metabolic perturbations in earthworm induced by cypermethrin using gas chromatography-mass spectrometry based metabolomics. Sci. Rep. 5, 15674 (2015).ADS 
CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Simpson, J. W., Allen, K. & Awapara, J. Free amino acids in some aquatic invertebrates. Biol. Bull. 117, 371–381 (1959).CAS 
Article 

Google Scholar 
Fu, Q., Scheidegger, A., Laczko, E. & Hollender, J. Metabolomic profiling and toxicokinetics modeling to assess the effects of the pharmaceutical diclofenac in the aquatic invertebrate Hyalella azteca. Environ. Sci. Technol. 55, 7920–7929 (2021).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Tikunov, A. P., Johnson, C. B., Lee, H., Stoskopf, M. K. & Macdonald, J. M. Metabolomic investigations of american oysters using 1H-NMR spectroscopy. Mar. Drugs 8, 2578–2596 (2010).CAS 
PubMed 
PubMed Central 
Article 

Google Scholar 
Gülçin, İ. Antioxidant and antiradical activities of l-carnitine. Life Sci. 78, 803–811 (2006).PubMed 
Article 
CAS 

Google Scholar 
Yuan, D. et al. Ancestral genetic complexity of arachidonic acid metabolism in Metazoa. Biochim. Biophys. Acta 1841, 1272–1284 (2014).CAS 
PubMed 
Article 

Google Scholar 
Garreta-Lara, E. et al. Effect of psychiatric drugs on Daphnia magna oxylipin profiles. Sci. Total Environ. 644, 1101–1109 (2018).ADS 
CAS 
PubMed 
Article 

Google Scholar 
Dwyer, G. K., Stoffels, R. J., Rees, G. N., Shackleton, M. E. & Silvester, E. A predicted change in the amino acid landscapes available to freshwater carnivores. Freshw. Sci. 37, 108–120 (2017).Article 

Google Scholar  More

Sutton, M. A. et al. The European Nitrogen Assessment: Sources, Effects and Policy Perspectives (Cambridge Univ. Press, 2011).Withers, P. J. A. & Haygarth, P. M. Agriculture, phosphorus and eutrophication: A European perspective. Soil Use Manag. 23, 1–4 (2007).Article 

Google Scholar 
Heffer, P. Assessment of Fertilizer Use by Crop at the Global Level (IFA, 2008).Wassen, M. J., Schrader, J., van Dijk, J. & Eppinga, M. B. Phosphorus fertilization is eradicating the niche of northern Eurasia’s threatened plant species. Nat. Ecol. Evol. 5, 67–73 (2021).Article 

Google Scholar 
Penuelas, J., Janssens, I. A., Ciais, P., Obersteiner, M. & Sardans, J. Anthropogenic global shifts in biospheric N and P concentrations and ratios and their impacts on biodiversity, ecosystem productivity, food security, and human health. Glob. Change Biol. 26, 1962–1985 (2020).Article 

Google Scholar 
Stokstad, E. Nitrogen crisis threatens Dutch environment — and economy. Science 366, 1180–1181 (2019).Article 

Google Scholar 
Dentener, F. et al. Nitrogen and sulfur deposition on regional and global scales: A multimodel evaluation. Global Biogeochem. Cycles 20, GB4003 (2006).Article 

Google Scholar 
Garske, B., Stubenrauch, J. & Ekardt, F. Sustainable phosphorus management in European agricultural and environmental law. RECIEL 29, 107–117 (2020).Article 

Google Scholar 
A Farm to Fork Strategy for a Fair, Healthy and Environmentally-friendly Food System (COM(2020) 381 final: European Commission, 2020); https://knowledge4policy.ec.europa.eu/publication/communication-com2020381-farm-fork-strategy-fair-healthy-environmentally-friendly-food_en More