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    Spatial and temporal variation in New Hampshire bat diets

    Whitaker, J. O., McCracken, G. F. & Siemers, B. M. Food habits analysis of insectivorous bats. in Ecological and Behavioral Methods for the Study of Bats. 567–592. (2011).Clare, E. L., Barber, B. R., Sweeney, B. W., Hebert, P. D. N. & Fenton, M. B. Eating local: Influences of habitat on the diet of little brown bats (Myotis lucifugus). Mol. Ecol. 20(8), 1772–1780. https://doi.org/10.1111/j.1365-294X.2011.05040.x (2011).CAS 
    Article 
    PubMed 

    Google Scholar 
    Clare, E. L. et al. The diet of Myotis lucifugus across Canada: Assessing foraging quality and diet variability. Mol. Ecol. 23(15), 3618–3632. https://doi.org/10.1111/mec.12542 (2014).Article 
    PubMed 

    Google Scholar 
    Wray, A. K. et al. Predator preferences shape the diets of arthropodivorous bats more than quantitative local prey abundance. Mol. Ecol. https://doi.org/10.1111/mec.15769 (2020).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Agosta, S. J., Morton, D. & Kuhn, K. M. Feeding ecology of the bat Eptesicus fuscus: ‘Preferred’ prey abundance as one factor influencing prey selection and diet breadth. J. Zool. 260(2), 169–177. https://doi.org/10.1017/S0952836903003601 (2003).Article 

    Google Scholar 
    Clare, E. L., Symondson, W. O. C. & Fenton, M. B. An inordinate fondness for beetles? Variation in seasonal dietary preferences of night-roosting big brown bats (Eptesicus fuscus). Mol. Ecol. 23(15), 3633–3647. https://doi.org/10.1111/mec.12519 (2014).Article 
    PubMed 

    Google Scholar 
    O’Rourke, D. R. et al. Lord of the Diptera (and moths and a spider): Molecular diet analyses and foraging ecology of Indiana bats in Illinois. Front. Ecol. Evol. 9, 12 (2021).ADS 

    Google Scholar 
    Hope, P. R. et al. Second generation sequencing and morphological faecal analysis reveal unexpected foraging behaviour by Myotis nattereri (Chiroptera, Vespertilionidae) in winter. Front. Zool. 11(1), 39. https://doi.org/10.1186/1742-9994-11-39 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vesterinen, E. J., Puisto, A. I. E., Blomberg, A. S. & Lilley, T. M. Table for five, please: Dietary partitioning in boreal bats. Ecol. Evol. 8, 10914–10937 (2018).Article 

    Google Scholar 
    Vesterinen, E. J. et al. What you need is what you eat? Prey selection by the bat Myotis daubentonii. Mol. Ecol. 25, 1581–1594 (2016).CAS 
    Article 

    Google Scholar 
    Barclay, R. M. R. Population structure of temperate zone insectivorous bats in relation to foraging behaviour and energy demand. J. Anim. Ecol. 60(1), 165. https://doi.org/10.2307/5452 (1991).Article 

    Google Scholar 
    Fraser, E. E. & Fenton, M. B. Age and food hardness affect food handling by insectivorous bats. Can. J. Zool. 85, 985–993 (2007).Article 

    Google Scholar 
    von Frenckell, B. & Barclay, R. M. R. Bat activity over calm and turbulent water. Can. J. Zool. 65, 219–222 (1987).Article 

    Google Scholar 
    Kaupas, L. A. & Barclay, R. M. R. Temperature-dependent consumption of spiders by little brown bats (Myotis lucifugus), but not northern long-eared bats (M. septentrionalis), in northern Canada. Can. J. Zool. 96(3), 261 (2018).Article 

    Google Scholar 
    Alberdi, A., Aizpurua, O., Gilbert, M. T. P. & Bohmann, K. Scrutinizing key steps for reliable metabarcoding of environmental samples. Methods Ecol. Evol. 9, 134–147 (2018).Article 

    Google Scholar 
    Nielsen, J. M., Clare, E. L., Hayden, B., Brett, M. T. & Kratina, P. Diet tracing in ecology: Method comparison and selection. Methods Ecol. Evol. 9, 278–291 (2018).Article 

    Google Scholar 
    Kunz, T. H. & Whitaker, J. O. An evaluation of fecal analysis for determining food habits of insectivorous bats. Can. J. Zool. 61, 1317–1321 (1983).Article 

    Google Scholar 
    Hamilton, I. M. & Barclay, R. M. R. Diets of juvenile, yearling, and adult big brown bats (Eptesicus fuscus) in Southeastern Alberta. J. Mammal. 79(3), 764. https://doi.org/10.2307/1383087 (1998).Article 

    Google Scholar 
    Moosman, P. R., Thomas, H. H. & Veilleux, J. P. Food habits of eastern small-footed bats (Myotis leibii) in New Hampshire. Am. Midl. Nat. 158(2), 354–360 (2007).Article 

    Google Scholar 
    Ober, H. K. & Hayes, J. P. Prey selection by bats in forests of Western Oregon. J. Mammal. 89(5), 1191–1200. https://doi.org/10.1644/08-MAMM-A-025.1 (2008).Article 

    Google Scholar 
    Long, B. L., Kurta, A. & Clemans, D. L. Analysis of DNA from feces to identify prey of big brown bats (Eptesicus fuscus) caught in apple orchards. Am. Midl. Nat. 170(2), 287–297 (2013).Article 

    Google Scholar 
    Gordon, R. et al. Molecular diet analysis finds an insectivorous desert bat community dominated by resource sharing despite diverse echolocation and foraging strategies. Ecol. Evol. 9, 3117–3129 (2019).Article 

    Google Scholar 
    Alberdi, A. et al. Promises and pitfalls of using high-throughput sequencing for diet analysis. Mol. Ecol. Resour. 19, 327–348 (2019).Article 

    Google Scholar 
    Clare, E. L. Molecular detection of trophic interactions: Emerging trends, distinct advantages, significant considerations and conservation applications. Evol. Appl. 7, 1144–1157 (2014).Article 

    Google Scholar 
    Blehert, D. S. et al. Bat white-nose syndrome: An emerging fungal pathogen?. Science 323(5911), 227–227. https://doi.org/10.1126/science.1163874 (2009).CAS 
    Article 
    PubMed 

    Google Scholar 
    Frick, W. F. et al. Disease alters macroecological patterns of North American bats: Disease alters macroecology of bats. Glob. Ecol. Biogeogr. 24(7), 741–749. https://doi.org/10.1111/geb.12290 (2015).Article 

    Google Scholar 
    Hallmann, C. A. et al. More than 75 percent decline over 27 years in total flying insect biomass in protected areas. PLoS ONE 12, e0185809 (2017).Article 

    Google Scholar 
    Sánchez-Bayo, F. & Wyckhuys, K. A. G. Worldwide decline of the entomofauna: A review of its drivers. Biol. Conserv. 232, 8–27 (2019).Article 

    Google Scholar 
    Anthony, E. L. P. & Kunz, T. H. Feeding strategies of the little brown bat, Myotis lucifugus, Southern New Hampshire. Ecology 58(4), 775–786. https://doi.org/10.2307/1936213 (1977).Article 

    Google Scholar 
    Pompanon, F. et al. Who is eating what: diet assessment using next generation sequencing. Mol. Ecol. 21, 1931–1950 (2012).CAS 
    Article 

    Google Scholar 
    Jusino, M. A. et al. An improved method for utilizing high-throughput amplicon sequencing to determine the diets of insectivorous animals. Mol. Ecol. Resour. 19, 176–190 (2019).CAS 
    Article 

    Google Scholar 
    O’Rourke, D. R., Bokulich, N. A., Jusino, M. A., MacManes, M. D., & Foster, J. T. A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses. Ecol. Evolut. https://doi.org/10.1002/ece3.6594 (2020).Langwig, K. E. et al. Resistance in persisting bat populations after white-nose syndrome invasion. Philos. Trans. R. Soc. B Biol. Sci. 372, 2160044 (2017).Article 

    Google Scholar 
    Maslo, B., Valent, M., Gumbs, J. F. & Frick, W. F. Conservation implications of ameliorating survival of little brown bats with white-nose syndrome. Ecol. Appl. 25, 1832–1840 (2015).Article 

    Google Scholar 
    Frick, W. F. et al. An emerging disease causes regional population collapse of a common North American bat species. Science 329(5992), 679–682. https://doi.org/10.1126/science.1188594 (2010).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Turner, G. G., Reeder, D. M. & Coleman, J. T. H. A five-year assessment of mortality and geographic spread of white-nose syndrome in North American bats and a look to the future. Bat Res. News 52, 13–27 (2011).
    Google Scholar 
    Coleman, J. et al. A National Plan for Assisting States, Federal Agencies, and Tribes in Managing White-Nose Syndrome in Bats. https://s3.us-west-2.amazonaws.com/prod-is-cms-assets/wns/prod/b0634260-77d3-11e8-b37b-4f3513704a5e-white-nose_syndrome_national_plan_may_2011.pdf (2011).Szymanski, J. A., Runge, M. C., Parkin, M. J. & Armstrong, M. White-Nose Syndrome Management: Report on Structured Decision Making Initiative. Vol. 51. http://pubs.er.usgs.gov/publication/70003465 (2009).Kunz, T. H., Braun de Torrez, E., Bauer, D., Lobova, T. & Fleming, T. H. Ecosystem services provided by bats. Ann. N. Y. Acad. Sci. 1223, 1–38 (2011).ADS 
    Article 

    Google Scholar 
    Boyles, J. G., Cryan, P. M., McCracken, G. F. & Kunz, T. H. Economic importance of bats in agriculture. Science 332(6025), 41–42. https://doi.org/10.1126/science.1201366 (2011).ADS 
    Article 
    PubMed 

    Google Scholar 
    Agosta, S. J. & Morton, D. Diet of the big brown bat, Eptesicus fuscus, from Pennsylvania and Western Maryland. Northeast. Nat. 10(1), 89–104 (2003).Article 

    Google Scholar 
    Brown, V. A., Braun de Torrez, E. & McCracken, G. F. Crop pests eaten by bats in organic pecan orchards. Crop Prot. 67, 66–71 (2015).Article 

    Google Scholar 
    Williams-Guillén, K., Perfecto, I. & Vandermeer, J. Bats limit insects in a Neotropical agroforestry system. Science 320(5872), 70–70. https://doi.org/10.1126/science.1152944 (2008).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Held, D. W. & Ray, C. H. Asiatic garden beetle Maladera castanea (Coleoptera: Scarabaeidae) grubs found in damaged turf in Alabama. Fla. Entomol. 92(4), 670–672 (2009).Article 

    Google Scholar 
    Forschler, B. T. & Gardner, W. A. A review of the scientific literature on the biology and distribution of the genus Phyllophaga (Coleoptera: Scarabaeidae) in the Southeastern United States. J. Entomol. Sci. 25(4), 628–651. https://doi.org/10.18474/0749-8004-25.4.628 (1990).Article 

    Google Scholar 
    United States Forest Service. White Grubs in Forest Tree Nurseries and Plantations. Vol. 4. https://www.fs.usda.gov/Internet/FSE_DOCUMENTS/fsbdev2_043588.pdf (1961).Chandler, D. University of New Hampshire—Entomology Collection. UNH Insect and Arachnid Collections. https://duncan.unh.edu/ento/home.php (2020).United States Forest Service. The Early Warning System for Forest Health Threads in the United States. https://www.fs.fed.us/foresthealth/publications/EWS_final_draft.pdf (2004).Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K., & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79(17), 5112–5120. https://doi.org/10.1128/AEM.01043-13 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).Article 

    Google Scholar 
    Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
    Article 

    Google Scholar 
    Callahan, B. J. et al. DADA2: High-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
    Article 

    Google Scholar 
    Ratnasingham, S. & Hebert, P. D. N. bold: The barcode of life data system. http://www.barcodinglife.org. Mol. Ecol. Notes 7, 355–364 (2007).Robeson, M. S. et al. RESCRIPt: Reproducible sequence taxonomy reference database management for the masses. bioRxiv. https://doi.org/10.1101/2020.10.05.326504 (2020).Article 

    Google Scholar 
    Chamberlain, S. BOLD: Interface to BOLD Systems API. (2017).Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol. Biol. Evol. 30(4), 772–780. https://doi.org/10.1093/molbev/mst010 (2013).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Camacho, C. et al. BLAST+: architecture and applications. BMC Bioinformatics 10, 421 (2009).Article 

    Google Scholar 
    Beule, L. & Karlovsky, P. Improved normalization of species count data in ecology by scaling with ranked subsampling (SRS): application to microbial communities. PeerJ 8, e9593 (2020).Article 

    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package. (2018).McMurdie, P. J. & Holmes, S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8(4), e61217. https://doi.org/10.1371/journal.pone.0061217 (2013).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cáceres, M. D. & Legendre, P. Associations between species and groups of sites: indices and statistical inference. Ecology 90, 3566–3574 (2009).Article 

    Google Scholar 
    McKinney, W. Data structures for statistical computing in Python. Proc. Python Sci. Conf. https://doi.org/10.25080/Majora-92bf1922-00a (2010).Article 

    Google Scholar 
    McDonald, D. et al. The Biological Observation Matrix (BIOM) format or: How I learned to stop worrying and love the ome-ome. GigaScience 1, 7 (2012).Article 

    Google Scholar 
    Paradis, E., Claude, J. & Strimmer, K. APE: Analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).CAS 
    Article 

    Google Scholar 
    Battaglia, T. btools: A Suite of R Function for All Types of Microbial Diversity Analyses. (2020).Wilke, C. O. cowplot: Streamlined Plot Theme and Plot Annotations for ‘ggplot2’. (2017).Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A. & Callahan, B. J. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6, 226 (2018).Article 

    Google Scholar 
    Ogle, D. H. & Wheeler, P. FSA: Fisheries Stock Analysis. (2018).Bisanz, J. E. qiime2R: Importing QIIME2 Artifacts and Associated Data into R Sessions. (2018).Kahle, D. & Wickham, H. ggmap: Spatial visualization with ggplot2. R J. 5, 144–161 (2013).Article 

    Google Scholar 
    Kassambara, A. ggpubr: ‘ggplot2’ Based Publication Ready Plots. (2018).Slowikowski, K. ggrepel: Automatically Position Non-Overlapping Text Labels with ‘ggplot2’. (2018).Hesselbarth, M. H. K., Sciaini, M., With, K. A., Wiegand, K. & Nowosad, J. landscapemetrics: an open-source R tool to calculate landscape metrics. Ecography 42, 1648–1657 (2019).Article 

    Google Scholar 
    Grolemund, G., & Wickham, H. Dates and times made easy with lubridate. J. Stat. Softw. 40(3). https://www.jstatsoft.org/index.php/jss/article/view/v040i03/v40i03.pdf (2011).Makiyama, K. magicfor: Magic Functions to Obtain Results from for Loops. (2016).Bates, D. & Maechler, M. Matrix: Sparse and Dense Matrix Classes and Methods. (2018).Graves, S., Piepho, H.-P. & Selzer, L. multcompView: Visualizations of Paired Comparisons. (2019).Martinez Arbizu, P. pairwiseAdonis: Pairwise Multilevel Comparison using Adonis. (2017).Hijmans, R. J. raster: Geographic Data Analysis and Modeling. (2020).Wickham, H. Reshaping data with the reshape Package. J. Stat. Softw. 21(1), 1–20. https://doi.org/10.18637/jss.v021.i12 (2007).MathSciNet 
    Article 

    Google Scholar 
    Wickham, H. scales: Scale Functions for Visualization. (2018).Pebesma, E. Simple features for R: Standardized support for spatial vector data. R J. 10, 439 (2018).Article 

    Google Scholar 
    Wickham, H. et al. svglite: An ‘SVG’ Graphics Device. (2020).Wickham, H. tidyverse: Easily Install and Load the ‘Tidyverse’. (2017).Strochak, S., Ueyama, K. & Williams, A. urbnmapr: State and County Shapefiles in sf and Tibble Format. (2020).Bittinger, K. usedist: Distance Matrix Utilities. (2020). More

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    The European Green Deal misses Europe’s subterranean biodiversity hotspots

    European Commission. Communication From The Commission To The European Parliament, The European Council, The Council, The European Economic And Social Committee And The Committee Of The Regions: The European Green Deal (European Commission, 2019).European Commission. Communication From The Commission To The European Parliament, The Council, The European Economic And Social Committee And The Committee Of The Regions: EU Biodiversity Strategy for 2030 (European Commission, 2020).Fan, P. et al. Proc. Natl Acad. Sci. USA 119, e2108038119 (2022).CAS 
    Article 

    Google Scholar 
    Schwarz, U. Hydropower Projects on the Balkan Rivers – Update. RiverWatch & EuroNatur; https://balkanrivers.net/sites/default/files/Hydropower%20dams%20in%20the%20Balkan230915_FINAL_EdUS.pdf (2015).Knez, S., Štrbac, S. & Podbregar, I. Energy Sustain. Soc. 12, 1 (2022).Article 

    Google Scholar 
    Myers, N., Mittermeier, R. A., Mittermeier, C. G., da Fonseca, G. A. & Kent, J. Nature 403, 853–858 (2000).CAS 
    Article 

    Google Scholar 
    Zagmajster, M. et al. Glob. Ecol. Biogeogr. 23, 1135–1145 (2014).Article 

    Google Scholar 
    Borko, Š., Trontelj, P., Seehausen, O., Moškrič, A. & Fišer, C. Nat. Commun. 12, 3688 (2021).CAS 
    Article 

    Google Scholar 
    Bregović, P., Fišer, C. & Zagmajster, M. Ecol. Evol. 9, 11606–11618 (2019).Article 

    Google Scholar 
    Bilandžija, H., Morton, B., Podnar, M. & Cetković, H. Front. Zool. 10, 5 (2013).Article 

    Google Scholar 
    Griebler, C. & Avramov, M. Freshw. Sci. 34, 355–367 (2015).Article 

    Google Scholar 
    Mammola, S. et al. Bioscience 69, 641–650 (2019).Article 

    Google Scholar 
    Jaćimović, N. et al. Vodoprivreda 47, 29–40 (2015).
    Google Scholar 
    Borko, Š., Altermatt, F., Zagmajster, M. & Fišer, C. Divers. Distrib. https://doi.org/10.1111/ddi.13500 (2022).European Commission. Evaluation of the EU Biodiversity Strategy to 2020 (European Commission, 2020); https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/1832-Evaluation-of-the-EU-Biodiversity-Strategy-to-2020_en More

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    Pollen beetle offspring is more parasitized under moderate nitrogen fertilization of oilseed rape due to more attractive volatile signal

    Poelman, E. H., van Loon, J. J. A. & Dicke, M. Consequences of variation in plant defense for biodiversity at higher trophic levels. Trends Plant Sci. 13, 534–541 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Degenhardt, J. et al. Restoring a maize root signal that attracts insect-killing nematodes to control a major pest. Proc. Natl. Acad. Sci. USA 106, 13213–13218 (2009).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Dicke, M. Behavioural and community ecology of plants that cry for help. Plant. Cell Environ. 32, 654–665 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Himanen, S. J. et al. Effects of elevated carbon dioxide and ozone on volatile terpenoid emissions and multitrophic communication of transgenic insecticidal oilseed rape (Brassica napus). New Phytol. 181, 174–186 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Girling, R. D. et al. Parasitoids select plants more heavily infested with their caterpillar hosts: A new approach to aid interpretation of plant headspace volatiles. Proc. Biol. Sci. 278, 2646–2653 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tamiru, A. et al. Maize landraces recruit egg and larval parasitoids in response to egg deposition by a herbivore. Ecol. Lett. 14, 1075–1083 (2011).PubMed 
    Article 

    Google Scholar 
    Njihia, T. N. et al. Identification of kairomones of second instar nymphs of the variegated coffee bug Antestiopsis thunbergii (Heteroptera: Pentatomidae). Chemoecology 27, 239–248 (2017).CAS 
    Article 

    Google Scholar 
    Becker, C. et al. Effects of abiotic factors on HIPV-mediated interactions between plants and parasitoids. BioMed. Res. Int. 2015, 1–18 (2015).Article 
    CAS 

    Google Scholar 
    Brilli, F., Loreto, F. & Baccelli, I. Exploiting plant volatile organic compounds (VOCs) in agriculture to improve sustainable defense strategies and productivity of crops. Front. Plant. Sci. 10, 264 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Aoun, W. B., El Akkari, M., Flénet, F., Jacquet, F. & Gabrielle, B. Recommended fertilization practices improve the environmental performance of biodiesel from winter oilseed rape in France. J. Cleaner Prod. 139, 242–249 (2016).Article 
    CAS 

    Google Scholar 
    Micha, E., Roberts, W., O’ Sullivan, L., O’ Connell, K. & Daly, K. Examining the policy-practice gap: the divergence between regulation and reality in organic fertiliser allocation in pasture based systems. Agric. Syst. 179, 102708 (2020).Article 

    Google Scholar 
    Dudareva, N., Klempien, A., Muhlemann, J. K. & Kaplan, I. Biosynthesis, function and metabolic engineering of plant volatile organic compounds. New Phytol. 198, 16–32 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ormeño, E. & Fernandez, C. Effect of soil nutrient on production and diversity of volatile terpenoids from plants. Curr. Bioact. Compd. 8, 71–79 (2012).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Hu, B. et al. VOC emissions and carbon balance of two bioenergy plantations in response to nitrogen fertilization: A comparison of Miscanthus and Salix. Environ. Pollut. 237, 205–217 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Olson, D. M., Cortesero, A. M., Rains, G. C., Potter, T. & Lewis, W. J. Nitrogen and water affect direct and indirect plant systemic induced defense in cotton. Biol. Control. 49, 239–244 (2009).CAS 
    Article 

    Google Scholar 
    Rosatto, L., Lainé, P. & Ourry, A. Nitrogen storage and remobilization in Brassica napus L. during the growth cycle: Nitrogen fluxes within the plant and changes in soluble protein patterns. J Exp Bot 52, 1655–1663 (2001).Article 

    Google Scholar 
    Yoneyama, T., Ito, O. & Engelaar, W. M. H. G. Uptake, metabolism and distribution of nitrogen in crop plants traced by enriched and natural 15N: Progress over the last 30 years. Phytochem. Rev. 2, 121–132 (2003).CAS 
    Article 

    Google Scholar 
    Fahey, J. W., Zalcmann, A. T. & Talalay, P. The chemical diversity and distribution of glucosinolates and isothiocyanates among plants. Phytochemistry 56, 5–51 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mithen, R. F. Glucosinolates and their degradation products. Adv. Bot. Res. 35, 213–262 (2001).ADS 
    CAS 
    Article 

    Google Scholar 
    García-Coronado, H. et al. Analysis of a suppressive subtractive hybridization library of Alternaria alternata resistant to 2-propenyl isothiocyanate. Electron. J. Biotechnol. 18, 320–326 (2015).Article 

    Google Scholar 
    Renwick, J. A. A., Haribal, M., Gouinguené, S. & Städler, E. Isothiocyanates stimulating oviposition by the diamondback moth, Plutella xylostella. J. Chem. Ecol. 32, 755–766 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Awmack, C. S. & Leather, S. R. Host plant quality and fecundity in herbivorous insects. Annu. Rev. Entomol. 47, 817–844 (2002).CAS 
    PubMed 
    Article 

    Google Scholar 
    Behmer, S. T. Insect herbivore nutrient regulation. Annu. Rev. Entomol. 54, 165–187 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Butler, J., Garratt, M. P. D. & Leather, S. R. Fertilisers and insect herbivores: a meta-analysis. Ann. Appl. Biol. 161, 223–233 (2012).Article 

    Google Scholar 
    Soufbaf, M., Fathipour, Y., Zalucki, M. P. & Hui, C. Importance of primary metabolites in canola in mediating interactions between a specialist leaf-feeding insect and its specialist solitary endoparasitoid. Arthropod-Plant Interact. 6, 241–250 (2012).Article 

    Google Scholar 
    De Vries, S. C., van de Ven, G. W. J., van Ittersum, M. K. & Giller, K. E. Resource use efficiency and environmental performance of nine major biofuel crops, processed by first-generation conversion techniques. Biomass Bioenergy 34, 588–601 (2010).Article 
    CAS 

    Google Scholar 
    Hegewald, H., Koblenz, B., Wensch-Dorendorf, M. & Christen, O. Impacts of high intensity crop rotation and N management on oilseed rape productivity in Germany. Crop Pasture sci. 67, 439–449 (2016).CAS 
    Article 

    Google Scholar 
    Jankowski, K. J., Budzyński, W. S., Załuski, D., Hulanicki, P. S. & Dubis, B. Using a fractional factorial design to evaluate the effect of the intensity of agronomic practices on the yield of different winter oilseed rape morphotypes. Field. Crop. Res. 188, 50–61 (2016).Article 

    Google Scholar 
    Chakwizira, E. et al. Effects of nitrogen rate on nitrate-nitrogen accumulation in forage kale and rape crops. Grass. Forage Sci. 70, 268–282 (2015).CAS 
    Article 

    Google Scholar 
    Rathke, G. W., Behrens, T. & Diepenbrock, W. Integrated nitrogen management strategies to improve seed yield, oil content and nitrogen efficiency of winter oilseed rape (Brassica napus L.): A review. Agric. Ecosyst. Environ. 117, 80–108 (2006).CAS 
    Article 

    Google Scholar 
    Henke, J., Breustedt, G., Sieling, K. & Kage, H. Impact of uncertainty on the optimum nitrogen fertilization rate and agronomic, ecological and economic factors in an oilseed rape based crop rotation. J. Agric. Sci. 145, 455–468 (2007).CAS 
    Article 

    Google Scholar 
    Eurostat. Agriculture, Forestry and Fishery Statistics (Publications Office of the European Union, 2020). https://doi.org/10.2785/143455.Book 

    Google Scholar 
    Zapata, N., Vargas, M., Reyes, J. F. & Belmar, G. Quality of biodiesel and press cake obtained from Euphorbia lathyris, Brassica napus and Ricinus communis. Ind. Crops Prod. 38, 1–5 (2012).CAS 
    Article 

    Google Scholar 
    Alford, D. V., Nilsson, C. & Ulber, B. Insect pests of oilseed rape crops. In Biocontrol of Oilseed Rape Pests (ed. Alford, D. V.) 9–42 (Blackwell Science, 2003).Chapter 

    Google Scholar 
    Veromann, E., Luik, E., Metspalu, L. & Williams, I. Key pests and their parasitoids on spring and winter oilseed rape in Estonia. Entomol. Fennica 17, 4 (2006).Article 

    Google Scholar 
    Meier, U. (ed.) Growth Stages of Mono-and Dicotyledonous Plants: BBCH Monograph (Blackwell Wissenschaft, 1997).
    Google Scholar 
    Lancashire, P. D. et al. A uniform decimal code for growth stages of crops and weeds. Ann. Appl. Biol. 119, 561–601 (1991).Article 

    Google Scholar 
    Williams, I. H. The major insect pests of oilseed rape in Europe and their management: An overview. In Biocontrol-Based Integrated Management of Oilseed Rape Pests (ed. Williams, I. H.) 1–43 (Springer, 2010).Chapter 

    Google Scholar 
    Williams, I. H. & Free, J. B. The feeding and mating behaviour of pollen beetles (Meligethes aeneus Fab.) and seed weevils (Ceutorhynchus assimilis Payk.) on oil-seed rape (Brassica napus L.). J. Agric. Sci. 91, 453–459 (1978).Article 

    Google Scholar 
    Ekbom, B. & Borg, A. Pollen beetle (Meligethes aeneus) oviposition and feeding preference on different host plant species. Entomol. Exp. Appl. 78, 291–299 (1996).Article 

    Google Scholar 
    Kaasik, R. et al. Meligethes aeneus oviposition preferences, larval parasitism rate and species composition of parasitoids on Brassica nigra, Raphanus sativus and Eruca sativa compared with on Brassica napus. Biol. Control 69, 65–71 (2014).Article 

    Google Scholar 
    Thieme, T., Heimbach, U. & Müller, A. Chemical control of insect pests and insecticide resistance in oilseed rape. In Biocontrol-based integrated management of oilseed rape pests (ed. Williams, I. H.) 313–335 (Springer, 2010). https://doi.org/10.1007/978-90-481-3983-5_12.Chapter 

    Google Scholar 
    Slater, R. et al. Pyrethroid resistance monitoring in European populations of pollen beetle (Meligethes spp.): A coordinated approach through the Insecticide Resistance Action Committee (IRAC). Pest. Manag. Sci. 67, 633–638 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zimmer, C. T., Köhler, H. & Nauen, R. Baseline susceptibility and insecticide resistance monitoring in European populations of Meligethes aeneus and Ceutorhynchus assimilis collected in winter oilseed rape. Entomol Exp Appl 150, 279–288 (2014).CAS 
    Article 

    Google Scholar 
    Mota-Sanchez, D., Whalon, M. E., Hollingworth, R. M. & Xue, Q. 2008. Documentation of pesticide resistance in arthropods. In Global Pesticide Resistance in Arthropods (eds Whalon, M. E. et al.) 32–39 (Cromwell Press, Berlin, 2008).Chapter 

    Google Scholar 
    Willow, J., Silva, A., Veromann, E. & Smagghe, G. Acute effect of low-dose thiacloprid exposure synergised by tebuconazole in a parasitoid wasp. PLoS ONE 14, e0212456 (2019).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Osborne, P. Observations on the natural enemies of Meligethes aeneus (F.) and M. viridescens (F.) [Coleoptera: Nitidulidae]. Parasitology 50, 91–110 (1960).CAS 
    PubMed 
    Article 

    Google Scholar 
    Büchi, R. Mortality of pollen beetle (Meligethes spp.) larvae due to predators and parasitoids in rape fields and the effect of conservation strips. Agric. Ecosyst. Environ. 90, 255–263 (2002).Article 

    Google Scholar 
    Veromann, E., Saarniit, M., Kevväi, R. & Luik, A. Effect of crop management on the incidence of Meligethes aeneus Fab. and their larval parasitism rate in organic and conventional winter oilseed rape. Agronomy Res. 7, 548–554 (2009).
    Google Scholar 
    Veromann, E. et al. Effects of nitrogen fertilization on insect pests, their parasitoids, plant diseases and volatile organic compounds in Brassica napus. Crop Prot 43, 79–88 (2013).CAS 
    Article 

    Google Scholar 
    Kovács, G. et al. Effects of land use on infestation and parasitism rates of cabbage seed weevil in oilseed rape. Pest Manag Sci 75, 658–666 (2019).PubMed 
    Article 
    CAS 

    Google Scholar 
    Kaasik, R., Kovács, G., Toome, M., Metspalu, L. & Veromann, E. The relative attractiveness of Brassica napus, B. rapa, B. juncea and Sinapis alba to pollen beetles. Bio. Control. 59, 19–28 (2014).
    Google Scholar 
    Lucas-Barbosa, D. et al. Endure and call for help: strategies of black mustard plants to deal with a specialized caterpillar. Funct. Ecol. 31, 325–333 (2017).Article 

    Google Scholar 
    Toome, M. et al. Leaf rust induced volatile organic compounds signalling in willow during the infection. Planta 232, 235–243 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kännaste, A., Copolovici, L. & Niinemets, Ü. Gas chromatography–mass spectrometry method for determination of biogenic volatile organic compounds emitted by plants. Methods Mol. Biol. 1153, 161–169. https://doi.org/10.1007/978-1-4939-0606-2_11 (2014).CAS 
    Article 
    PubMed 

    Google Scholar 
    Kask, K., Kännaste, A., Talts, E., Copolovici, L. & Niinemets, Ü. How specialized volatiles respond to chronic and short-term physiological and shock heat stress in Brassica nigra. Plant Cell Environ. 39, 2027–2042 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Niinemets, Ü. et al. Estimations of isoprenoid emission capacity from enclosure studies: measurements, data processing, quality and standardized measurement protocols. Biogeosciences 8, 2209–2246 (2011).ADS 
    CAS 
    Article 

    Google Scholar 
    Copolovici, L., Kännaste, A., Remmel, T., Vislap, V. & Niinemets, Ü. Volatile emissions from Alnus glutionosa induced by herbivory are quantitatively related to the extent of damage. J. Chem. Ecol. 37, 18–28 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Peck, J. E. In Multivariate Analysis for Ecologists: Step-by-Step 2nd edn (ed. Peck, J. E.) (MjM Software Design, 2016).
    Google Scholar 
    Narits, L. Effect of nitrogen rate and application time to yield and quality of winter oilseed rape (Brassica napus L. var. oleifera subvar. biennis). Agron. Res. 8, 671–686 (2010).ADS 

    Google Scholar 
    Naderi, R. & Ghadiri, H. Competition of wild mustard (Sinapis arvense L.) densities with rapeseed (Brassica napus L.) under different levels of nitrogen fertilizer. J. Agr. Sci. Technol. 13, 45–51 (2011).
    Google Scholar 
    Grzebisz, W., Łukowiak, R. & Kotnis, K. Evaluation of nitrogen fertilization systems based on the in-season variability in the nitrogenous growth factor and soil fertility factors—A case of winter oilseed rape (Brassica napus L.). Agronomy 10, 1701 (2020).CAS 
    Article 

    Google Scholar 
    He, H. et al. Genotypic variation in nitrogen utilization efficiency of oilseed rape (Brassica napus) under contrasting N supply in pot and field experiments. Front. Plant. Sci. 8, 1825 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pashalidou, F. G., Lucas-Barbosa, D., van Loon, J. J. A., Dicke, M. & Fatouros, N. E. Phenotypic plasticity of plant response to herbivore eggs: Effects on resistance to caterpillars and plant development. Ecology 94, 702–713 (2013).PubMed 
    Article 

    Google Scholar 
    Lucas-Barbosa, D., Loon van, J. J. A., Gols, R., Beek van, T. A. & Dicke, M. Reproductive escape: annual plant responds to butterfly eggs by accelerating seed production. Funct. Ecol. 27, 245–254 (2013).Article 

    Google Scholar 
    Milchunas, D. G. & Noy-Meir, I. Grazing refuges, external avoidance of herbivory and plant diversity. Oikos 99, 113–130 (2002).Article 

    Google Scholar 
    Williams, I. H. & Free, J. B. Compensation of oil-seed rape (Brassica napus L.) plants after damage to their buds and pods. J. Agric. Sci. 92, 53–59. https://doi.org/10.1017/S0021859600060494 (1979).Article 

    Google Scholar 
    Tatchell, G. Compensation in spring-sown oil-seed rape (Brassica napus L.) plants in response to injury to their flower buds and pods. J. Agric. Sci. 101, 565–573. https://doi.org/10.1017/S0021859600038594 (1983).Article 

    Google Scholar 
    Tiffin, P. Mechanisms of tolerance to herbivore damage: What do we know?. Evol. Ecol. 14, 523–536. https://doi.org/10.1023/A:1010881317261 (2000).Article 

    Google Scholar 
    Pinet, A., Mathieu, A. & Jullien, A. Floral bud damage compensation by branching and biomass allocation in genotypes of Brassica napus with different architecture and branching potential. Front. Plant Sci 6, 70. https://doi.org/10.3389/fpls.2015.00070 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Muzika, R. M. & Pregitzer, K. S. Effect of nitrogen fertilization on leaf phenolic production of grand fir seedlings. Trees 6, 241–244 (1992).Article 

    Google Scholar 
    Kesselmeier, J. Exchange of short-chain oxygenated volatile organic compounds (VOCs) between plants and the atmosphere: A compilation of field and laboratory studies. J. Atmos. Chem. 39, 219–233 (2001).CAS 
    Article 

    Google Scholar 
    Karl, T., Curtis, A. J., Rosenstiel, T. N., Monson, R. K. & Fall, R. Transient releases of acetaldehyde from tree leaves—Products of a pyruvate overflow mechanism?. Plant. Cell Environ. 25, 1121–1131 (2002).CAS 
    Article 

    Google Scholar 
    Szczepaniak, W., Grzebisz, W., Potarzycki, J., Łukowiak, R. & Przygocka-Cyna, K. Nutritional status of winter oilseed rape in cardinal stages of growth as the yield indicator. Plant Soil Environ. 61, 291–296 (2015).CAS 
    Article 

    Google Scholar 
    Anjum, N. A. et al. Improving growth and productivity of Oleiferous brassicas under changing environment: Significance of nitrogen and sulphur nutrition, and underlying mechanisms. Scientific World J. 2012, 657808 (2012).Article 
    CAS 

    Google Scholar 
    Okereke, C. N., Liu, B., Kaurilind, E. & Niinemets, Ü. Heat stress resistance drives coordination of emissions of suites of volatiles after severe heat stress and during recovery in five tropical crops. Environ. Exp. Bot. 184, 104375 (2021).CAS 
    Article 

    Google Scholar 
    Kanagendran, A., Pazouki, L. & Niinemets, Ü. Differential regulation of volatile emission from Eucalyptus globulus leaves upon single and combined ozone and wounding treatments through recovery and relationships with ozone uptake. Environ. Exp. Bot. 145, 21–38 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Robertson, G. W. et al. A comparison of the flower volatiles from hawthorn and four raspberry cultivars. Phytochemistry 33, 1047–1053 (1993).CAS 
    Article 

    Google Scholar 
    Robertson, G. W., Griffiths, D. W., Smith, W. M. & Butcher, R. D. The application of thermal desorption-gas chromatography-mass spectrometry to the analyses of flower volatiles from five varieties of oilseed rape (Brassica napus spp. oleifera). Phytochem. Anal. 4, 152–157 (1993).CAS 
    Article 

    Google Scholar 
    Kos, M. et al. Effects of glucosinolates on a generalist and specialist leaf-chewing herbivore and an associated parasitoid. Phytochemistry 77, 162–170 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Niinemets, Ü., Kännaste, A. & Copolovici, L. Quantitative patterns between plant volatile emissions induced by biotic stresses and the degree of damage. Front. Plant. Sci. 4, 262. https://doi.org/10.3389/fpls.2013.00262 (2013).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Shannon, R. W. R. et al. Something in the air? The impact of volatiles on mollusc attack of oilseed rape seedlings. Ann. Bot. 117, 1073–1082 (2016).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ruther, J., Reinecke, A. & Hilker, M. Plant volatiles in the sexual communication of Melolontha hippocastani: Response towards time-dependent bouquets and novel function of (Z)-3-hexen-1-ol as a sexual kairomone. Ecol. Entomol. 27, 76–83 (2002).Article 

    Google Scholar 
    Khan, Z. R., Pickett, J. A., Berg, J. V. D., Wadhams, L. J. & Woodcock, C. M. Exploiting chemical ecology and species diversity: Stem borer and striga control for maize and sorghum in Africa. Pest. Manag. Sci. 56, 957–962 (2000).CAS 
    Article 

    Google Scholar 
    Jayanthi, P. D. K. et al. Specific volatile compounds from mango elicit oviposition in gravid Bactrocera dorsalis females. J. Chem. Ecol. 40, 259–266 (2014).Article 
    CAS 

    Google Scholar 
    Hu, Z. et al. Aldehyde volatiles emitted in succession from mechanically damaged leaves of poplar cuttings. J. Plant. Biol. 51, 269–275 (2008).Article 

    Google Scholar 
    Giacomuzzi, V., Mattheis, J. P., Basoalto, E., Angeli, S. & Knight, A. L. Survey of conspecific herbivore-induced volatiles from apple as possible attractants for Pandemis pyrusana (Lepidoptera: Tortricidae). Pest. Manag. Sci. 73, 1837–1845 (2017).CAS 
    PubMed 
    Article 

    Google Scholar 
    Torrens-Spence, M. P. et al. Structural basis for independent origins of new catalytic machineries in plant AAAD proteins. BioRxiv 404970 (2018)Birkett, M. A. et al. The role of volatile semiochemicals in mediating host location and selection by nuisance and disease-transmitting cattle flies. Med. Vet. Entomol. 18, 313–322 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Brodmann, J. et al. Orchids mimic green-leaf volatiles to attract prey-hunting wasps for pollination. Curr. Biol. 18, 740–744 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hervé, M. R. et al. Oviposition behavior of the pollen beetle (Meligethes aeneus): A functional study. J. Insect. Behav. 28, 107–119 (2015).Article 

    Google Scholar 
    Hilker, M. & Meiners, T. Plants and insect eggs: How do they affect each other?. Phytochemistry 72, 1612–1623 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ibanez, S., Gallet, C. & Després, L. Plant insecticidal toxins in ecological networks. Toxins 4, 228–243 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar  More

  • in

    Co-application of proline or calcium and humic acid enhances productivity of salt stressed pomegranate by improving nutritional status and osmoregulation mechanisms

    Holland, D., Hatib, K. & Bar-Ya’akov, I. Pomegranate: Botany, horticulture and breeding. In Horticultural Reviews Vol. 35 (ed. Janick, J.) 127–191 (Wiley, 2009).Chapter 

    Google Scholar 
    Fayek, M. A., Mohamed, A. E. & Rashedy, A. A. Responses of five pomegranate (Punica granatum L.) cultivars to contrasting water availability: Leaf morphophysiological and anatomical adaptation. Appl. Ecol. Environ. Res. 20, 967–978 (2022).Article 

    Google Scholar 
    Naeini, M. R., Khoshgoftarmanesh, A. H., Lessani, H. & Fallahi, E. Effects of sodium chloride-induced salinity on mineral nutrients and soluble sugars in three commercial cultivars of pomegranate. J. Plant Nutr. 27(8), 1319–1326 (2005).Article 
    CAS 

    Google Scholar 
    Sun, Y., Niu, G., Masabni, J. G. & Ganjegunte, G. Relative salt tolerance of 22 pomegranate (Punica granatum) cultivars. HortScience 53(10), 1513–1519 (2018).Article 

    Google Scholar 
    Lansky, E. P. & Newman, R. A. Review: Punica granatum (pomegranate) and its potential for prevention and treatment of inflammation and cancer. J. Ethnopharmacol. 109(2), 177–206 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Khedr, E. H. Application of different coating treatments to enhance storability and fruit quality of pomegranate (Punica granatum L., cv. Wonderful) during prolonged storage. Rev. Braz. Fruitc. 44(2), 1–13 (2022).MathSciNet 

    Google Scholar 
    FAO (Food and Agriculture organization). Extent and causes of salt-affected soils in participating countries. Global network on integrated soil management for sustainable use of salt-affected soils. FAO-AGL website. Available in https://xueshu.baidu.com/usercenter/paper/show?paperid=9e5044cfc974c52d785834bbd8438017 (2000).Mehanna, H. T., Fayed, T. A. & Rashedy, A. A. Response of two grape rootstocks to some salt tolerance treatments under saline water conditions. J. Hortic. Sci. Ornam. Plants 2(2), 93–106 (2010).
    Google Scholar 
    Rady, M. M., Elrys, A. S., Abo El-Maati, M. F. & Desoky, E. M. Interplaying roles of silicon and proline effectively improve salt and cadmium stress tolerance in Phaseolus vulgaris plant. Plant Physiol. Biochem. 139, 558–568 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    El-Khawaga, A. S., Zaeneldeen, E. M. A. & Yossef, M. A. Response of three pomegranate cultivars (Punica granatum L.) to salinity stress. Middle East J. Agric. Res. 1(1), 64–75 (2013).
    Google Scholar 
    Khaled, H. & Fawy, H. A. Effect of different levels of humic acids on the nutrient content, plant growth, and soil properties under conditions of salinity. Soil Water Res. 6(1), 21–29 (2011).CAS 
    Article 

    Google Scholar 
    Jahromi, A. A. & Khankahdani, H. H. Effect of humic acid on some vegetative traits and ion concentrations of Mexican Lime (Citrus aurantifolia Swingle) seedlings under salt stress. Int. J. Hortic. Sci. Technol. 3(2), 255–264 (2016).CAS 

    Google Scholar 
    Hatami, E., Shokouhian, A. A., Ghanbari, A. R. & Naseri, L. A. Alleviating salt stress in almond rootstocks using of humic acid. Sci. Hortic. 237, 296–302 (2018).CAS 
    Article 

    Google Scholar 
    Shalaby, O. A. E. & El-Messairy, M. M. Humic acid and boron treatment to mitigate salt stress on the melon plant. Acta Agric. Slov. 111(2), 349–356 (2018).Article 
    CAS 

    Google Scholar 
    Kavi Kishor, P. B. et al. Regulation of proline biosynthesis, degradation, uptake and transport in higher plants: Its implications in plant growth and abiotic stress tolerance. Curr. Sci. 88(3), 424–438 (2005).
    Google Scholar 
    Mahmoudi, M. & Aryaee, P. Study the effects of fulvic acid on physiological traits of citrus unshu under salt stress. Int. J. Chem. Environ. Biol. Sci. 3(3), 198–200 (2015).
    Google Scholar 
    Kaya, C., AKram, N. A., Ashraf, M. & Sonmez, O. Exogenous application of humic acid mitigates salinity stress in maize (Zea mays L.) plants by improving some key physico-biochemical attributes. Curr. Sci. 46, 67–78 (2018).CAS 

    Google Scholar 
    Hayat, S. et al. Role of proline under changing environments. Plant Signal. Behav. 7(11), 1456–1466 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Meena, M. et al. Regulation of L-proline biosynthesis, signal transduction, transport, accumulation and its vital role in plants during variable environmental conditions. Heliyon 5, e02952 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Semida, W. M., Abdelkhalik, A., Rady, M. O. A., Marey, R. A. & Abd El-Mageed, T. A. Exogenously applied proline enhances growth and productivity of drought stressed onion by improving photosynthetic efficiency, water use efficiency and up-regulating osmoprotectants. Sci. Hortic. 272, 109580 (2020).CAS 
    Article 

    Google Scholar 
    Abo-ogiala, A. Crop production of pomegranate cv. wonderful via foliar application of ascorbic acid, proline and glycinbetaine under environmental stresses. Int. J. Environ. 7(3), 95–103 (2018).
    Google Scholar 
    El Moukhtari, A., Cabassa-Hourton, C., Farissi, M. & Savoure, A. How does proline treatment promote salt stress tolerance during crop plant development?. Front. Plant Sci. 11, 1127 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Orlov, S. N., Aksentsev, S. L. & Kotelevtsev, S. V. Extracellular calcium is required for the maintenance of plasma membrane integrity in nucleated cells. Cell Calcium 38(1), 53–57 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wu, G. Q. & Wang, S. M. Calcium regulates K+/Na+ homeostasis in rice (Oryza sativa L.) under saline conditions. Plant Soil Environ. 58(3), 121–127 (2012).CAS 
    Article 

    Google Scholar 
    Cheng, X., Zhang, X., Yu, L. & Xu, H. Calcium signaling in membrane repair. Semin. Cell Dev. Biol. 45, 24–31 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wang, P. et al. J. Na+/Ca2+ exchanger-like protein (AtNCL) involved in salt stress in Arabidopsis. J. Biol. Chem. 287, 44062–44070 (2012).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li, P. H., Zhang, G. Y., Gonzales, N., Guo, Y. Q., Hu, H. H., Park, S. & Zhao, J.  Ca2+-regulated and diurnal rhythm-regulated Na+/Ca2+ exchanger AtNCL affects flowering time and auxin signalling in Arabidopsis. Plant Cell Environ. 39, 377–392 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Paiva, E. A. S. Are calcium oxalate crystals a dynamic calcium store in plants?. New Phytol. 223, 1707–1711 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Bates, L. S., Waldren, R. P. & Teare, I. Rapid determination of free proline for water-stress studies. Plant Soil 39, 205–207 (1973).CAS 
    Article 

    Google Scholar 
    Herbert, D., Phipps, P. J. & Strange, R. E. Chemical analysis of microbial cells. J. Microbiol. Methods 5, 209–344 (1971).Article 

    Google Scholar 
    Smith, G. S., Johnston, C. M. & Cornforth, I. S. Comparison of nutrient solutions for growth of plants in sand culture. New Phytol. 94(4), 537–548 (1983).CAS 
    Article 

    Google Scholar 
    Mastrogiannidou, E., Chatzissavvidis, C., Antonopoulou, C., Tsabardoukas, V., Giannakoula, A. & Therios, I. Response of pomegranate cv. wonderful plants to salinity. J. Soil Sci. Plant Nutr. 16(3), 621–636 (2016).CAS 

    Google Scholar 
    Temminghoff, E. E. J. M. & Houba, V. J. G. Plant Analysis Procedures. Second Edition Analysis 94–96 (Kluwer Academic Publishers, 2004). https://doi.org/10.1007/978-1-4020-2976-9.Book 

    Google Scholar 
    Jones, J. B. Jr. Kjeldahl Method for Nitrogen Determination (Micro-Macro Publishing, 1991).
    Google Scholar 
    Association of Official Analytical Chemists—A. O. A. C. Official Methods of Analysis of the Association of the Analytical Chemists 17th edn, 2200 (AOAC International, 2000).
    Google Scholar 
    Snedecor, W. & Cochran, W. G. Statistical Methods 8th edn, 503 (Iowa State University Press, 1989).MATH 

    Google Scholar 
    Ennab, H. A. Effect of humic acid on growth and productivity of egyptian lime trees (Citrus aurantifolia swingle) under salt stress conditions. J. Agric. Res. (Kafr El-Shaikh Univ.) 42(4), 494–505 (2016).
    Google Scholar 
    Genaidy, E. A. E., Merwad, M. A. & Haggag, L. F. Effect of algae, humic acid and waste organic material in culture media on growth performance of “Picual” olive seedlings. Int. J. Chemtech Res. 8(11), 43–50 (2015).
    Google Scholar 
    Fekry, W. M. E., Rashad, M. A. & Alalaf, A. H. Attempts to improve the growth and fruiting of barhi date palms under salinity stress. Asian J. Plant Sci. 19, 146–151 (2020).CAS 
    Article 

    Google Scholar 
    Abdelhamid, M. T., Rady, M. M., Osman, A. S. H. & Abdalla, M. A. Exogenous application of proline alleviates saltinduced oxidative stress in Phaseolus vulgaris L. plants. J. Hortic. Sci. Biotechnol. 88(4), 439–446 (2013).CAS 
    Article 

    Google Scholar 
    Wani, A. S., Ahmad, A., Hayat, S. & Tahir, I. Epibrassinolide and proline alleviate the photosynthetic and yield inhibition under salt stress by acting on antioxidant system in mustard. Plant Physiol. Biochem. 135, 385–394 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ben Mahmoud, O. M. et al. Auxin and proline producing rhizobacteria mitigate salt-induced growth inhibition of barley plants by enhancing water and nutrient status. S. Afr. J. Bot. 128, 209–217 (2020).Article 
    CAS 

    Google Scholar 
    Nakhaie, A., Habibi, G. & Vaziri, A. Exogenous proline enhances salt tolerance in acclimated Aloe vera by modulating photosystem II efficiency and antioxidant defense. S. Afr. J. Bot. 147, 1–10 (2020).
    Google Scholar 
    Hasanuzzaman, M. et al. Exogenous proline and glycine betaine mediated upregulation of antioxidant defense and glyoxalase systems provides better protection against salt-induced oxidative stress in two rice (Oryza sativa L.) varieties. BioMed Res. Int. 2014, 1–17 (2014).
    Google Scholar 
    Shahid, M. A. et al. Exogenous proline and proline-enriched Lolium perenne leaf extract protects against phytotoxic effects of nickel and salinity in Pisum sativum by altering polyamine metabolism in leaves. Turk. J. Bot. 38, 914–926 (2014).CAS 
    Article 

    Google Scholar 
    Lima-Costa, M.E., Ferreira, S., Duarte, A. & Ferreira, A. L. Alleviation of salt stress using exogenous proline on a citrus cell line. Acta Hortic. 868, 109–112 (2010).CAS 
    Article 

    Google Scholar 
    Alotaibi, S., Ali, E., Darwesh, H., Ahmed, A. & Al-Thubaiti, E. Effect of proline on growth and nutrient uptake of Simmondsia chinensis (link) schneider under salinity stress. Pak. J. Biol. Sci. 22(9), 412–418 (2019).CAS 
    PubMed 
    Article 

    Google Scholar 
    AlKahtani, M. D. F. et al. Evaluation of silicon and proline application on the oxidative machinery in drought-stressed sugar beet. Antioxidants 10(3), 398 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ahmad, P. et al. Exogenous application of calcium to 24-epibrassinosteroid pretreated tomato seedlings mitigates NaCl toxicity by modifying ascorbate–glutathione cycle and secondary metabolites. Sci. Rep. 8, 13515 (2018).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Jasim, A. M., Abbas, M. F. & Shareef, H. J. Calcium application mitigates salt stress in Date Palm (Phoenix dactylifera L.) offshoots cultivars of Berhi and Sayer. Acta Agric. Slov. 107(1), 103–112 (2016).Article 

    Google Scholar 
    Zhou, L., Lan, W., Jiang, Y., Fang, W. & Luan, S. Calcium-dependent protein kinase interacts with and activates a calcium channel to regulate pollen tube growth. Mol. Plant 7(2), 369–376 (2014).CAS 
    PubMed 
    Article 

    Google Scholar 
    Zou, J. J. et al. Arabidopsis calcium-dependent protein kinse8 and catalase3 function in abscisic acid-mediated signaling and H2O2 homeostasis in stomatal guard cells under drought stress. Plant Cell 27(5), 1445–1460 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    El-Beltagi, H. S. & Mohamed, H. I. Alleviation of cadmium toxicity in Pisum sativum L. seedlings by calcium chloride. Not. Bot. Horti. Agrobot. Cluj Napoca 41, 157–168 (2013).CAS 
    Article 

    Google Scholar 
    White, P. J. Calcium channels in higher plants. Biochim. Biophys. Acta (BBA) Biomembr. 1465(1–2), 171–189 (2000).CAS 
    Article 

    Google Scholar 
    Salahshoor, F. & Kazemi, F. Effect of calcium on reducing salt stress in seed germination and early growth stage of Festuca ovina. Plant Soil Environ. 62, 460–467 (2016).CAS 
    Article 

    Google Scholar 
    Tzortzakis, N. G. Potassium and calcium enrichment alleviate salinity-induced stress in hydroponically grown endives. Sci. Rep. 8, 13515 (2010).
    Google Scholar 
    Cha-um, S., Singh, H. P., Samphumphuang, T. & Kirdmanee, C. Calcium-alleviated salt tolerance in indica rice (Oryza sativa L. spp. indica): Physiological and morphological changes. Aust. J. Crop Sci. 6(1), 176–182 (2012).CAS 

    Google Scholar 
    Murillo-Amador, B. et al. Influence of calcium silicate on growth, physiological parameters and mineral nutrition in two legume species under salt stress. J. Agron. Crop Sci. 193(6), 413–421 (2007).CAS 
    Article 

    Google Scholar 
    Zaman, B., Niazi, B.H., Athar, M. & Ahmad, M. Response of wheat plants to sodium and calcium ion interaction under saline environment. Int. J. Environ. Sci. Technol. 2, 7–12 (2005).CAS 
    Article 

    Google Scholar 
    Akladious, S. A. & Mohamed, H. I. Ameliorative effects of calcium nitrate and humic acid on the growth, yield component and biochemical attribute of pepper (Capsicum annuum) plants grown under salt stress. Sci. Hortic. 236, 244–250 (2018).CAS 
    Article 

    Google Scholar 
    Wójcik, P., Filipczak, J. & Wójcik, M. Effects of prebloom sprays of tryptophan and zinc on calcium nutrition, yielding and fruit quality of ‘Elstar’ apple trees. Sci. Hortic. 246, 212–216 (2019).Article 
    CAS 

    Google Scholar 
    Hagagg, L. F., Abd-Alhamid, N. & Maklad, M. F. Effect of kaolin and calcium carbonate on vegetative growth, leaf pigments and mineral content of kalamata and manzanillo olive trees. Middle East J. Agric. Res. 8(1), 298–310 (2019).
    Google Scholar 
    El-Hoseiny, H. M., Helaly, M. N., Elsheery, N. I. & Alam-Eldein, S. M. Quality of mango trees humic acid and boron to minimize the incidence of alternate bearing and improve the productivity and fruit quality of mango trees. HortScience 55, 1026–1037 (2020).CAS 
    Article 

    Google Scholar 
    Masoud, A. A. B., Khodair, O. A. & Gouda, F. E. M. Effect of gibberellic acid, naphthalenacetic acid, calcium and zinc spraying on fruiting of manfalouty pomegranate trees. Assiut J. Agric. Sci. 50(2), 219–228 (2019).
    Google Scholar 
    Russo, R. O. & Berlyn, G. P. The use of organic biostimulants to help low input sustainable agriculture. J. Sustain. Agric. 1(2), 19–42 (1990).Article 

    Google Scholar 
    Chen, Y. & Aviad, T. Effects of humic substances on plant growth. In Humic Substances in Soil and Crop Science: Selected Readings (ed. Maccarthy, P.) 161–186 (CSSA and ASA, 1990).
    Google Scholar 
    El Sayed, O. M., El Gammal, O. H. M. & Salama, A. S. M. Effect of proline and tryptophan amino acids on yield and fruit quality of Manfalouty pomegranate variety. Sci. Hortic. 69, 1–5 (2014).Article 
    CAS 

    Google Scholar 
    Mattioli, R., Palombi, N., Funck, D. & Trovato, M. Proline accumulation in pollen grains as potential target for improved yield stability under salt stress. Front. Plant Sci. 11, 582877 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Badran, M. A. Benefits of calcium carbonate sprays on yield and fruit quality of samany and zaghloul date palm under new reclaimed soils. Assiut J. Agric. Sci. 46(5), 48–57 (2015).
    Google Scholar  More

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    Abiotic and biotic factors controlling the dynamics of soil respiration in a coastal dune ecosystem in western Japan

    Site descriptionThe study site (about 1 ha) is within a coastal dune ecosystem (35° 32′ 26.0″ N, 134° 12′ 27.5″ E) located at the Arid Land Research Center of Tottori University, Tottori, Japan. The mean annual temperature is 15.2 °C, and the mean total precipitation is 1931 mm, based on records collected from 1991 to 2020 at the Tottori observation station of the Japan Meteorological Agency. Dominant plant species around the measurement plot were Vitex rotundifolia and Artemisia capillaris. Carex kobomugi and Ischaemum anthephoroides were also scattered around the coastal side of the study site, and planted Pinus thunbergii trees cover the inland side.Experimental designIn May 2020, we established four measurement plots at the study site (Fig. 9). Plot 1 was a gap area surrounded by V. rotundifolia seedlings. Plot 2 consisted of clusters of V. rotundifolia seedlings and was adjacent to plot 1. Within plots 1 and 2, C. kobomugi and I. anthephoroides were also scattered. Plot 3 was in a mixed area of V. rotundifolia and A. capillaris; this plot was in the center of the study site. Plot 4 was located in front of P. thunbergii trees and was in the most inland area of the study site. On 10 June 2020, we set an environmental measurement system at the center of the study site adjacent to plot 3, and we then obtained continuous data for soil temperature and soil moisture. In each plot (main plot), we set 10 plastic (polypropylene) collars (n = 10) before the start of the Rs measurement. We measured Rs every 2 weeks from 15 June to 2 December 2020 in the main plots. Vitex rotundifolia and C. kobomugi invaded a part of plot 1 in late June and early July, after the first Rs measurement on 15 June. Therefore, we set new measurement points for plot 1 in early July (Fig. 9), and flux calculations for plot 1 were conducted after removing data from the invaded area measured on June 15.Figure 9Diagram and photos of measurement plots in the focal coastal dune ecosystem. Vitex rotundifolia and C. kobomugi invaded a part of plot 1 in late June to early July, after the first Rs measurement on 15 June. Therefore, we set new measurement points for plot 1 in early July.Full size imageEnvironmental measurement systemThe environmental measurement system was composed of a data logger (CR1000, Campbell Scientific Inc., Logan, UT, USA), battery (SC dry battery, Kind Techno Structure Co. Ltd, Saitama, Japan), solar panel (RNG-50D-SS, RENOGY International Inc., Ontario, CA, USA), charge controller (Solar Amp mini, CSA-MN05-8, DENRYO, Tokyo, Japan), thermocouples (E type), and soil moisture sensors (CS616, Campbell Scientific Inc.). The data logger, battery, and charge controller were kept in a plastic box to avoid exposure to rainfall and sand. Each end of the thermocouple was inserted into a copper tube (4-mm inner diameter, 5-cm length) and affixed with glue. To measure the reference soil temperature at different depths, copper tubes enclosing E-type thermocouples were buried horizontally in the sand at depths of 5, 10, 30, and 50 cm (n = 1 for each depth) at the center of plot 3 as reference soil temperature (the data was recorded every 30 min). In addition, we set stand-alone soil temperature sensors (Thermochron SL type, KN Laboratories, Inc. Osaka, Japan) at the center of plots 1 and 4 at depths of 5, 10, and 30 cm (n = 1 for each plot, each depth), and they recorded soil temperature data every 30 min. Reference soil temperature at the depth of 5, 10, and 30 cm was used for gap-filling for soil temperature measured by stand-alone sensors at each depth and plot. Soil moisture sensors were buried horizontally in the sand at a depth of 30 cm in the center of plots 1, 3, and 4 (n = 1 for each plot) and recorded data every 30 min. Raw values of soil moisture sensors were converted to volumetric soil moisture (%) using a calibration line from 0 to 15% measured in the laboratory using dune sand and three sensors (CS616) referring to the procedure of Bongiovanni et al.53. Data for precipitation at the local meteorological observatory in Tottori was downloaded from the home page of the Japan Meteorological Agency (https://www.data.jma.go.jp/gmd/risk/obsdl/index.php).
    R
    s measurement in the main plotsPolypropylene collars (30-cm inner diameter, 5-cm depth, n = 10) were set in each measurement plot in late May 2020. The first Rs measurement was conducted on 15 June 2020. However, V. rotundifolia and C. kobomugi then invaded about half of the gap area of plot 1, so on 1 July we set 5 new polypropylene collars for plot 1 to replace the 5 invaded measurement points (Fig. 9). The second Rs measurement was conducted on 2 July, and all polypropylene collars then remained in the same position until the end of the measurement period.Rs was measured using an automated closed dynamic chamber system54 composed of two cylindrical aluminum chambers (30 cm diameter, 30 cm height) equipped with thermistor temperature sensors (44006, Omega Engineering, Stanford, CA, USA) for measuring air temperature inside the chamber during Rs measurement. Those chambers were connected to a control box equipped with a pump, data logger (CR1000, Campbell Scientific Inc.), CO2 analyzer (Gascard NG infrared gas sensor, Edinburgh Sensors, Lancashire, UK), and thermometer (MHP, Omega Engineering). The composition of the control box is basically the same as used in previous studies54,55. The measurement period for each point was 3 min, and the CO2 concentration and air temperature inside the chamber were recorded every 5 s. During the measurement, another chamber was set on the next polypropylene collar with the lid opened, and the next measurement was started at that moment of finishing the previous measurement by automatically closing the chamber lid on the next polypropylene collar in the same plot. Soil temperature at a depth of 0–5 cm was recorded simultaneously by inserting the rod of the thermometer vertically into the soil surface near the polypropylene collar (about 1–2 m from the collar).Rs was calculated by using the following equation:$$R_{{text{s}}} = frac{{PV}}{{RS(T_{{{text{air}}}} + 273.15)}}frac{{partial C}}{{partial t}},$$
    (1)
    where P is the air pressure (Pa), V is the effective chamber volume (m3), R is the ideal gas constant (8.314 Pa m3 K−1 mol−1), S is the soil surface area (m2), Tair is the air temperature inside the chamber (°C). ∂C/∂t is the rate of change of the CO2 mole fraction (μmol mol−1 s−1), which was calculated using least-squares regression of the CO2 changes inside the chamber12. For the flux calculation, we removed data for the first 35 s (dead band) of each measurement as an outlier.Trench treatment and soil CO2 efflux (F
    c) measurement in subplotsIn November 2020, we conducted root-cut treatment (trench treatment) in subplots using polyvinyl chloride (PVC) tubes to estimate the contribution of Ra to Rs in the soil layer above 50 cm in each plot (Ra_50/Rs). Small PVC collars (10.7 cm inner diameter, 5 cm depth, n = 10 for each plot), with the upper ends about 1–2 cm above the soil surface, were set in subplots adjacent to the main plots on 23 October 2020. Rs was measured in subplots using two cylindrical mini PVC chambers (11.8 cm inner diameter at the bottom, 30 cm height, equipped with the same thermistors as cylindrical aluminum chambers for air temperature measurement) connected to the same control box as used for Rs measurement in the main plots. The measurement period was 3 min, and the measurement procedure and the flux calculation were the same as the main plot. Rs was first measured in subplots on 3 November to examine the spatial variation of Rs before trench treatment. Using the data, we selected subplots to conduct trench treatment and control plots for comparison, while aiming to achieve a minimal difference in the average Rs between control and pre-trenched plots. On 4 November, we inserted PVC tubes (10.7 cm inner diameter, 50 cm length) into about half (n = 3–5) of the subplots (the same position as PVC collars were set on 23 October) by using a hammer and aluminum lid until the upper end of each PVC tube was 1–2 cm above the soil surface to exclude roots to a depth of about 50 cm. On 19 November, after 15 days of trench treatment, respiration was measured in the same subplots.The Ra_50/Rs was calculated as follows:$$R_{{{text{a}}_{5}0}} /R_{{text{s}}} = (F_{{{text{c}}_{text{control}}}} -F_{{{text{c}}_{text{trenched}}}}) /F_{{{text{c}}_{text{control}}}} ,$$
    (2)
    where Fc_trenched and Fc_control (= Rs) are the Fc values in trenched and control plots on 19 November, respectively.In late December 2020, all the belowground plant biomass (BPB) in subplots (control and trenched plots) to a depth of 50 cm was collected for biomass analysis, about 2 months after trench treatment. In the laboratory, all the collected plant materials were washed and oven-dried for 72 h at 70 °C, and then the dry weight of the BPB samples was measured.Biomass measurementWe conducted BPB analysis from 18 May to 8 June 2021 in each plot (n = 1). At that time, 100 cm × 100 cm sampling plots near the CO2 measurement plots (100 cm × 100 cm for plots 2–4 and 50 cm × 50 cm in plot 1 because of the narrow gap area) were dug to a depth of 100–220 cm, according to the root distribution in each plot, and all plant materials were collected by passing the soil through 5- to 7-mm sieves. Once we reached a depth where no roots were visible, no more digging was conducted. In plots 2 and 3, stolons of V. rotundifolia were difficult to distinguish from roots if underground. Therefore, we defined plant material as BPB if it was underground. In the laboratory, all of the collected plant materials were washed and air-dried at room temperature for 0–6 days depending on the biomass. After that, samples were oven-dried for 15–25 h at 70–80 °C, and the dry weight of those samples was then measured.Soil organic carbon and nitrogenOn 21 October 2020, soil pits were dug to a depth of 50 cm near each plot (n = 3), and soil core samples were collected. Cylindrical stainless core samplers (5 cm diameter, 5 cm height, 100 cc) were horizontally inserted into the soil pit at depths of 0–5, 5–10, 10–20, and 20–30 cm. In the laboratory, soil core samples were weighed and oven-dried at 105 °C for 48 h, and the dry weight was measured. Oven-dried soil samples were sieved with a 2-mm-pore stainless wire mesh screen, and visible fungal mycelia in soil samples from plot 4 were removed as well as possible. Sieved samples were ground with an agate mortar. Samples (fine powder) were oven-dried for 24 h at 105 °C and weighed before SOC and nitrogen analysis. About 1.5 g of powdered samples were used for the analysis. Organic carbon content (combustion at 400 °C) and total nitrogen in samples were analyzed using a Soli TOC cube (Elementar Analysensysteme GmbH, Langenselbold, Germany) by the combustion method.Microbial abundanceOn 21 October 2020, soil samples for microbial analysis were collected at the same time as soil core sampling for SOC and nitrogen analysis. Soil samples were collected at depths of 0–10, 10–20, and 20–30 cm using a stainless spatula and placed individually in a polyethylene bag. The bags were kept in a cooler box with ice in the field and then placed in a freezer (− 30 °C) in the laboratory soon after sampling.DNA was extracted from 0.5 g of the fresh soils using NucleoSpin Soil (Takara Bio, Inc., Shiga, Japan) according to the manufacturer’s instructions (SL1 buffer), and the extracts were stored at − 20 °C until further analysis. Bacterial and archaeal 16S rRNA and fungal internal transcribed spacer (ITS) gene were targeted to investigate the microbial abundance. Bacterial and archaeal 16S rRNA (V4 region) and fungal ITS were determined using the universal primer sets 515F/806R and ITS1F_KYO2/ITS2_KYO2, respectively56,57.For qPCR, samples were prepared with 10 μL of the KAPA SYBR Fast qPCR kit (Kapa Biosystems, Wilmington, MA, USA), 0.8 μL of forward primer, 0.8 μL of reverse primer, and 3 μL of 1–50 × diluted soil DNA. Nuclease-free water was added to make up to a final volume of 20 μL. Cycling conditions of 16S rRNA were 95 °C for 30 s, followed by 40 cycles at 95 °C for 30 s, 58 °C for 30 s, and 72 °C for 1 min. Cycling conditions of ITS were 95 °C for 30 s, followed by 40 cycles at 95 °C for 30 s, 55 °C for 1 min, and 72 °C for 1 min. A melting curve analysis was performed in a final cycle of 95 °C for 15 s, 60 °C for 1 min, and 95 °C for 15 s. High amplification efficiencies of 99% for bacterial and archaeal 16S rRNA genes and 101% for the fungal ITS were obtained based on the standard curves.Data analysisTo examine the environmental response (soil temperature and soil moisture) of Rs, nonlinear and quadratic regression models were applied. We conducted F-tests by comparing the regression model to a constant model whose value is the mean of the observations (significance set at p  More

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    Global systematic review with meta-analysis reveals yield advantage of legume-based rotations and its drivers

    Beillouin, D., Ben-Ari, T., Malezieux, E., Seufert, V. & Makowski, D. Positive but variable effects of crop diversification on biodiversity and ecosystem services. Glob. Change Biol. 27, 4697–4710 (2021).CAS 
    Article 

    Google Scholar 
    Ditzler, L. et al. Current research on the ecosystem service potential of legume inclusive cropping systems in Europe. A review. Agron. Sustain. Dev. 41, 26 (2021).Article 

    Google Scholar 
    Snapp, S. S., Blackie, M. J., Gilbert, R. A., Bezner-Kerr, R. & Kanyama-Phiri, G. Y. Biodiversity can support a greener revolution in Africa. Proc. Natl Acad. Sci. USA 107, 20840–20845 (2010).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Renard, D. & Tilman, D. National food production stabilized by crop diversity. Nature 571, 257–260 (2019).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Rodriguez, C., Mårtensson, L.-M. D., Jensen, E. S. & Carlsson, G. Combining crop diversification practices can benefit cereal production in temperate climates. Agron. Sustain. Dev. 41, 48 (2021).Article 

    Google Scholar 
    Zeng, Z. H. et al. in Crop Rotations: Farming Practices, Monitoring and Environmental Benefits (ed. Ma, B. L.) Ch. 1, 51–70 (Nova Science Publishers, 2016).Cusworth, G., Garnett, T. & Lorimer, J. Legume dreams: the contested futures of sustainable plant-based food systems in Europe. Glob. Environ. Change 69, 102321 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Reckling, M. et al. Grain legume yields are as stable as other spring crops in long-term experiments across northern Europe. Agron. Sustain. Dev. 38, 63 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Snapp, S. S., Cox, C. M. & Peter, B. G. Multipurpose legumes for smallholders in sub-Saharan Africa: identification of promising ‘scale out’ options. Glob. Food Secur-Agr. 23, 22–32 (2019).Article 

    Google Scholar 
    Hegewald, H., Wensch-Dorendorf, M., Sieling, K. & Christen, O. Impacts of break crops and crop rotations on oilseed rape productivity: a review. Eur. J. Agron. 101, 63–77 (2018).Article 

    Google Scholar 
    Angus, J. F. et al. Break crops and rotations for wheat. Crop . Sci. 66, 523–552 (2015).
    Google Scholar 
    Franke, A. C., van den Brand, G. J., Vanlauwe, B. & Giller, K. E. Sustainable intensification through rotations with grain legumes in Sub-Saharan Africa: a review. Agric. Ecosyst. Environ. 261, 172–185 (2018).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Preissel, S., Reckling, M., Schlaefke, N. & Zander, P. Magnitude and farm-economic value of grain legume pre-crop benefits in Europe: a review. Field Crops Res. 175, 64–79 (2015).Article 

    Google Scholar 
    Zhao, J. et al. Does crop rotation yield more in China? A meta-analysis. Field Crops Res. 245, 107659 (2020).Article 

    Google Scholar 
    Tamburini, G. et al. Agricultural diversification promotes multiple ecosystem services without compromising yield. Sci. Adv. 6, eaba1715 (2020).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cernay, C., Makowski, D. & Pelzer, E. Preceding cultivation of grain legumes increases cereal yields under low nitrogen input conditions. Environ. Chem. Lett. 16, 631–636 (2018).CAS 
    Article 

    Google Scholar 
    Peoples, M. B. et al. The contributions of nitrogen-fixing crop legumes to the productivity of agricultural systems. Symbiosis 48, 1–17 (2009).CAS 
    Article 

    Google Scholar 
    Watson, C. A. et al. Grain legume production and use in European agricultural systems. Adv. Agron. 144, 235–303 (2017).Article 

    Google Scholar 
    Bennett, A. J., Bending, G. D., Chandler, D., Hilton, S. & Mills, P. Meeting the demand for crop production:The challenge of yield decline in crops grown in short rotations. Biol. Rev. 87, 52–71 (2012).PubMed 
    Article 

    Google Scholar 
    Drinkwater, L. E., Wagoner, P. & Sarrantonio, M. Legume-based cropping systems have reduced carbon and nitrogen losses. Nature 396, 262–265 (1998).ADS 
    CAS 
    Article 

    Google Scholar 
    Smith, C. J. & Chalk, P. M. Grain legumes in crop rotations under low and variable rainfall: are observed short-term N benefits sustainable? Plant Soil 453, 271–279 (2020).CAS 
    Article 

    Google Scholar 
    Pullens, J. W. M., Sorensen, P., Melander, B. & Olesen, J. E. Legacy effects of soil fertility management on cereal dry matter and nitrogen grain yield of organic arable cropping systems. Eur. J. Agron. 122, 126169 (2021).CAS 
    Article 

    Google Scholar 
    Tognetti, P. M. et al. Negative effects of nitrogen override positive effects of phosphorus on grassland legumes worldwide. Proc. Natl Acad. Sci. USA 118, 28 (2021).Article 

    Google Scholar 
    Kirkegaard, J., Christen, O., Krupinsky, J. & Layzell, D. Break crop benefits in temperate wheat production. Field Crops Res. 107, 185–195 (2008).Article 

    Google Scholar 
    Brisson, N. et al. Why are wheat yields stagnating in Europe? A comprehensive data analysis for France. Field Crops Res. 119, 201–212 (2010).Article 

    Google Scholar 
    Anderson, R. L. Synergism: a rotation effect of improved growth efficiency. Adv. Agron. 112, 205–226 (2011).Article 

    Google Scholar 
    Bonilla-Cedrez, C., Chamberlin, J. & Hijmans, R. Fertilizer and grain prices constrain food production in sub-Saharan Africa. Nat. Food 2, 766–772 (2021).Article 

    Google Scholar 
    Seufert, V., Ramankutty, N. & Foley, J. A. Comparing the yields of organic and conventional agriculture. Nature 485, 229–232 (2012).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Barbieri, P., Pellerin, S., Seufert, V. & Nesme, T. Changes in crop rotations would impact food production in an organically farmed world. Nat. Sustain. 2, 378–385 (2019).Article 

    Google Scholar 
    Barbieri, P. et al. Global option space for organic agriculture is delimited by nitrogen availability. Nat. Food 2, 363–372 (2021).Article 

    Google Scholar 
    Muller, A. et al. Strategies for feeding the world more sustainably with organic agriculture. Nat. Commun. 8, 1290 (2017).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Nowak, B., Nesme, T., David, C. & Pellerin, S. Disentangling the drivers of fertilising material inflows in organic farming. Nutr. Cycl. Agroecosyst. 96, 79–91 (2013).Article 

    Google Scholar 
    Bender, S. F., Wagg, C. & van der Heijden, M. G. A. An underground revolution: biodiversity and soil ecological engineering for agricultural sustainability. Trends Ecol. Evol. 31, 440–452 (2016).PubMed 
    Article 

    Google Scholar 
    Mariotte, P. et al. Plant-soil feedback: Bridging natural and agricultural sciences. Trends Ecol. Evol. 33, 129–142 (2018).PubMed 
    Article 

    Google Scholar 
    Everwand, G., Cass, S., Dauber, J., Williams, M. & Stout, J. Legume crops and biodiversity. Legumes in Cropping Systems, 4, 55–69 (2017).Peoples, M. B., Giller, K. E., Jensen, E. S. & Herridge, D. F. Quantifying country-to-global scale nitrogen fixation for grain legumes: I. Reliance on nitrogen fixation of soybean, groundnut and pulses. Plant Soil 469, 1–14 (2021).CAS 
    Article 

    Google Scholar 
    Abalos, D., van Groenigen, J. W., Philippot, L., Lubbers, I. M. & De Deyn, G. B. Plant trait-based approaches to improve nitrogen cycling in agroecosystems. J. Appl. Ecol. 56, 2454–2466 (2019).Article 

    Google Scholar 
    Garland, G. et al. Crop cover is more important than rotational diversity for soil multifunctionality and cereal yields in European cropping systems. Nat. Food 2, 28–37 (2021).Article 

    Google Scholar 
    Pandey, A., Li, F., Askegaard, M., Rasmussen, I. A. & Olesen, J. E. Nitrogen balances in organic and conventional arable crop rotations and their relations to nitrogen yield and nitrate leaching losses. Agric. Ecosyst. Environ. 265, 350–362 (2018).CAS 
    Article 

    Google Scholar 
    Cook, R. J. Toward cropping systems that enhance productivity and sustainability. Proc. Natl Acad. Sci. USA 103, 18389–18394 (2006).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gan, Y. T. et al. Improving farming practices reduces the carbon footprint of spring wheat production. Nat. Commun. 5, 13 (2014).
    Google Scholar 
    Hufnagel, J., Reckling, M. & Ewert, F. Diverse approaches to crop diversification in agricultural research. A review. Agron. Sustain. Dev. 40, 14 (2020).Article 

    Google Scholar 
    Ma, B. L. & Wu, W. in Crop Rotations: Farming Practices, Monitoring and Environmental Benefits (ed Ma B. L.) Ch. 1, 1–35 (Nova Science Publishers, 2016).Seymour, M., Kirkegaard, J. A., Peoples, M. B., White, P. F. & French, R. J. Break-crop benefits to wheat in Western Australia – insights from over three decades of research. Crop. Sci. 63, 1–16 (2012).
    Google Scholar 
    Sileshi, G., Akinnifesi, F. K., Ajayi, O. C. & Place, F. Meta-analysis of maize yield response to woody and herbaceous legumes in sub-Saharan Africa. Plant Soil 307, 1–19 (2008).CAS 
    Article 

    Google Scholar 
    Bullock, D. G. Crop rotation. Crit. Rev. Plant Sci. 11, 309–326 (1992).Article 

    Google Scholar 
    Danga, B. O., Ouma, J. P., Wakindiki, I. I. C. & Bar-Tal, A. Legume-wheat ration effects on residual soil moisture, nitrogen and wheat yield in tropical regions. Adv. Agron. 101, 315–349 (2009).Article 

    Google Scholar 
    Ghosh, P. K. et al. Legume effect for enhancing productivity and nutrient use-efficiency in major cropping systems – An Indian perspective: a review. J. Sustain. Agric. 30, 59–86 (2007).Article 

    Google Scholar 
    Karlen, D. L., Varvel, G. E., Bullock, D. G. & Cruse, R. M. Crop rotation for the 21st century. Adv. Agron. 53, 1–45 (1994).Article 

    Google Scholar 
    Martin, G. et al. Role of ley pastures in tomorrow’s cropping systems. A review. Agron. Sustain. Dev. 40, 17 (2020).Article 

    Google Scholar 
    Ruisi, P. et al. Agro-ecological benefits of faba bean for rainfed Mediterranean cropping systems. Ital. J. Agron. 12, 233–245 (2017).
    Google Scholar 
    Ryan, J., Singh, M. & Pala, M. Long-term cereal-based rotation trials in the Mediterranean region: Implications for cropping sustainability. Adv. Agron. 97, 273–319 (2008).CAS 
    Article 

    Google Scholar 
    Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. & Grp, P. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. J. Clin. Epidemiol. 62, 1006–1012 (2009).PubMed 
    Article 

    Google Scholar 
    Pittelkow, C. M. et al. Productivity limits and potentials of the principles of conservation agriculture. Nature 517, 365–368 (2015).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

    Google Scholar 
    Wieder, W. R., Boehnert, J., Bonan, G. B. & Langseth, M. Regridded Harmonized World Soil Database v1.2. ORNL DAAC. https://doi.org/10.3334/ORNLDAAC/1247 (2014).Soil Survey Staff. Soil taxonomy: a basic system of soil classification for making and interpreting soil surveys. 2nd edition. Natural Resources Conservation Service. U.S. Department of Agriculture Handbook 436. (1999).FAO. World Programme of the Census of Agriculture 2020. Vol. 1 (2015).Tiemann, L. K., Grandy, A. S., Atkinson, E. E., Marin-Spiotta, E. & McDaniel, M. D. Crop rotational diversity enhances belowground communities and functions in an agroecosystem. Ecol. Lett. 18, 761–771 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tilman, D. et al. The influence of functional diversity and composition on ecosystem processes. Science 277, 1300–1302 (1997).CAS 
    Article 

    Google Scholar 
    Yates, F. The analysis of experiments containing different crop rotations. Biometrics 10, 324–346 (1954).Article 

    Google Scholar 
    Zhao, J. et al. Dataset for evaluating global yield advantage and its drivers of legume-based rotations. Figshare, https://doi.org/10.6084/m9.figshare.20290923 (2022).Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta-analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).Article 

    Google Scholar 
    Adams, D. C., Gurevitch, J. & Rosenberg, M. S. Resampling tests for meta-analysis of ecological data. Ecology 78, 1277–1283 (1997).Article 

    Google Scholar 
    Van Lissa, C. MetaForest: Exploring Heterogeneity in Meta-analysis Using Random Forests. (2017).Terrer, C. et al. A trade-off between plant and soil carbon storage under elevated CO2. Nature 591, 599–CO603 (2021).ADS 
    CAS 
    PubMed 
    Article 

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

    Google Scholar 
    Kuhn, M. Building predictive models in R using the caret package. J. Stat. Softw. 28, 1–26 (2008).Article 

    Google Scholar 
    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 

    Google Scholar 
    Rosenberg, M. S. The file-drawer problem revisited: a general weighted method for calculating fail-safe numbers in meta-analysis. Evolution 59, 464–468 (2005).PubMed 
    Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing v.4.0.3 (R Foundation for Statistical Computing, Vienna, Austria, 2021). More

  • in

    Fine-scale movement of northern Gulf of Mexico red snapper and gray triggerfish estimated with three-dimensional acoustic telemetry

    Fodrie, F. J. et al. Measuring individuality in habitat use across complex landscapes: Approaches, constraints, and implications for assessing resource specialization. Oecologia 178, 75–87 (2015).ADS 
    PubMed 
    Article 

    Google Scholar 
    Bacheler, N. M., Michelot, T., Cheshire, R. T. & Shertzer, K. W. Fine-scale movement patterns and behavioral states of gray triggerfish Balistes capriscus determined from acoustic telemetry and hidden Markov models. Fish. Res. 215, 76–89 (2019).Article 

    Google Scholar 
    Furey, N. B., Dance, M. A. & Rooker, J. R. Fine-scale movements and habitat use of juvenile southern flounder Paralichthys lethostigma in an estuarine seascape. J. Fish Biol. 82, 1469–1483 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Froehlich, C. Y. M., Garcia, A. & Kline, R. J. Daily movement patterns of red snapper (Lutjanus campechanus) on a large artificial reef. Fish. Res. 209, 49–57 (2019).Article 

    Google Scholar 
    Williams-Grove, L. J. & Szedlmayer, S. T. Acoustic positioning and movement patterns of red snapper, Lutjanus campechanus, around artificial reefs in the northern Gulf of Mexico. Mar. Ecol. Prog. Ser. 553, 233–251 (2016).ADS 
    Article 

    Google Scholar 
    Secor, D. H., Zhang, F., O’Brien, M. H. P. & Li, M. Ocean destratification and fish evacuation caused by a Mid-Atlantic tropical storm. ICES J. Mar. Sci. 76, 573–584 (2019).Article 

    Google Scholar 
    Bacheler, N. M., Shertzer, K. W., Cheshire, R. T. & MacMahan, J. H. Tropical storms influence the movement behavior of a demersal oceanic fish species. Sci. Rep. 9, 1–13 (2019).CAS 
    Article 

    Google Scholar 
    Lowerre-Barbieri, S. K., Walters, S., Bickford, J., Cooper, W. & Muller, R. Site fidelity and reproductive timing at a spotted seatrout spawning aggregation site: Individual versus population scale behavior. Mar. Ecol. Prog. Ser. 481, 181–197 (2013).ADS 
    Article 

    Google Scholar 
    Espinoza, M., Farrugia, T. J., Webber, D. M., Smith, F. & Lowe, C. G. Testing a new acoustic telemetry technique to quantify long-term, fine-scale movements of aquatic animals. Fish. Res. 108, 364–371 (2011).Article 

    Google Scholar 
    Roy, R. et al. Testing the VEMCO positioning system: Spatial distribution of the probability of location and the positioning error in a reservoir. Anim. Biotelemetry 2, 1 (2014).CAS 
    Article 

    Google Scholar 
    Guzzo, M. M. et al. Field testing a novel high residence positioning system for monitoring the fine-scale movements of aquatic organisms. Methods Ecol. Evol. 9, 1478–1488 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Smedbol, S., Smith, F., Webber, D., Vallée, R. & King, T. Using underwater coded acoustic telemetry for fine scale positioning of aquatic animals. In 20th Symposium of the International Society on Biotelemetry Proceedings, 9–11 (2014).Dean, M. J., Hoffman, W. S., Zemeckis, D. R. & Armstrong, M. P. Fine-scale diel and gender-based patterns in behaviour of Atlantic cod (Gadus morhua) on a spawning ground in the western Gulf of Maine. ICES J. Mar. Sci. 71, 1474–1489 (2014).Article 

    Google Scholar 
    Tarnecki, J. H. & Patterson, W. F. A mini ROV-based method for recovering marine instruments at depth. PLoS One 15, 1–9 (2020).
    Google Scholar 
    Ellis, R. D. et al. Acoustic telemetry array evolution: From species- and project-specific designs to large-scale, multispecies, cooperative networks. Fish. Res. 209, 186–195 (2019).Article 

    Google Scholar 
    Friess, C. et al. Regional-scale variability in the movement ecology of marine fishes revealed by an integrative acoustic tracking network. Mar. Ecol. Prog. Ser. 663, 157–177 (2021).ADS 
    Article 

    Google Scholar 
    Walters, C. J. & Juanes, F. Recruitment limitation as a consequence of natural selection for use of restricted feeding habitats and predation risk taking by juvenile fishes. Can. J. Fish. Aquat. Sci. 50, 2058–2070 (1993).Article 

    Google Scholar 
    Ahrens, R. N. M., Walters, C. J. & Christensen, V. Foraging arena theory. Fish Fish. 13, 41–59 (2012).Article 

    Google Scholar 
    Schwartzkopf, B. D., Langland, T. A. & Cowan, J. H. Habitat selection important for red snapper feeding ecology in the northwestern Gulf of Mexico. Mar. Coast. Fish. 9, 373–387 (2017).Article 

    Google Scholar 
    Wells, R. J. D., Cowan, J. H. Jr. & Fry, B. Feeding ecology of red snapper Lutjanus campechanus in the northern Gulf of Mexico. Mar. Ecol. Prog. Ser. 361, 213–225 (2008).ADS 
    Article 

    Google Scholar 
    Goldman, S. F., Glasgow, D. M. & Falk, M. M. Feeding habits of 2 reef-associated fishes, red porgy (Pagrus pagrus) and gray triggerfish (Balistes capriscus), off the Southeastern United States. Fish. Bull. 114, 317–329 (2016).Article 

    Google Scholar 
    Villegas-Ríos, D., Réale, D., Freitas, C., Moland, E. & Olsen, E. M. Personalities influence spatial responses to environmental fluctuations in wild fish. J. Anim. Ecol. 87, 1309–1319 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rooker, J. R. et al. Seascape connectivity and the influence of predation risk on the movement of fishes inhabiting a back-reef ecosystem. Ecosphere 9, e02200 (2018).Article 

    Google Scholar 
    Forman, R. T. T. & Godron, M. Patches and structural components for a landscape ecology. Bioscience 31, 733–740 (1981).Article 

    Google Scholar 
    Dahl, K. A. & Patterson, W. F. Movement, home range, and depredation of invasive lionfish revealed by fine-scale acoustic telemetry in the northern Gulf of Mexico. Mar. Biol. 167, 1–22 (2020).Article 
    CAS 

    Google Scholar 
    Schoener, T. W. Resource partitioning in ecological communities. Science 185, 27–39 (1974).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Moulton, D. L. et al. Habitat partitioning and seasonal movement of red drum and spotted seatrout. Estuaries Coasts 40, 905–916 (2017).Article 

    Google Scholar 
    Hammerschlag, N., Luo, J., Irschick, D. J. & Ault, J. S. A Comparison of spatial and movement patterns between sympatric predators: bull sharks (Carcharhinus leucas) and Atlantic tarpon (Megalops atlanticus). PLoS ONE 7, e45958 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Novak, A. J. et al. Scale of biotelemetry data influences ecological interpretations of space and habitat use in yellowtail snapper. Mar. Coast. Fish. 12, 364–377 (2020).Article 

    Google Scholar 
    Lima, S. L. & Dill, L. M. Behavioral decisions made under the risk of predation: A review and prospectus. Can. J. Zool. 68, 619–640 (1990).Article 

    Google Scholar 
    Werner, E. E. & Gilliam, J. F. The ontogenetic niche and species interactions in size-structured populations. Annu. Rev. Ecol. Syst. 15, 393–425 (1984).Article 

    Google Scholar 
    Reale, D. et al. Personality and the emergence of the pace-of-life syndrome concept at the population level. Philos. Trans. R. Soc. B Biol. Sci. 365, 4051–4063 (2010).Article 

    Google Scholar 
    Sih, A., Bell, A. & Johnson, J. C. Behavioral syndromes: An ecological and evolutionary overview. Trends Ecol. Evol. 19, 372–378 (2004).PubMed 
    Article 

    Google Scholar 
    Huntingford, F. A. The relationship between anti-predator behavior and aggression among conspecifics in the three-spined stickleback, Gasterosteus aculeatus. Anim. Behav. 24, 245–260 (1976).Article 

    Google Scholar 
    Wilson, D. S., Clark, A. B., Coleman, K. & Dearstyne, T. Shyness and boldness in humans and other animals. Trends Ecol. Evol. 9, 442–446 (1994).Article 

    Google Scholar 
    Harrison, P. M. et al. Personality-dependent spatial ecology occurs independently from dispersal in wild burbot (Lota lota). Behav. Ecol. 26, 483–492 (2015).Article 

    Google Scholar 
    Gosling, S. D. From mice to men: What can we learn about personality from animal research?. Psychol. Bull. 127, 45–86 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hussey, N. E. et al. Aquatic animal telemetry: A panoramic window into the underwater world. Science 348, 1255642–1255642 (2015).PubMed 
    Article 
    CAS 

    Google Scholar 
    Lowerre-Barbieri, S. K., Kays, R., Thorson, J. T. & Wikelski, M. The ocean’s movescape: Fisheries management in the bio-logging decade (2018–2028). ICES J. Mar. Sci. 76, 477–488 (2019).Article 

    Google Scholar 
    National Marine Fisheries Service. Fisheries Economics of the United State 2016. NOAA Tech. Memo. NMFS-F/SPO-187a. https://www.fisheries.noaa.gov/resource/document/fisheries-economics-united-states-report-2016 (2018). Accessed 08 January 2018.Patterson, W. F. III, Tarnecki, J., Addis, D. T. & Barbieri, L. R. Reef fish community structure at natural versus artificial reefs in the northern Gulf of Mexico. In Proc. 66th Gulf Caribb. Fish. Inst. 4–8 (2014).Streich, M. K. et al. Effects of a new artificial reef complex on red snapper and the associated fish community: An evaluation using a before–after control–impact approach. Mar. Coast. Fish. 9, 404–418 (2017).Article 

    Google Scholar 
    Dance, M. A., Patterson, W. F. III. & Addis, D. T. Fish community and trophic structure at artificial reef sites in the northeastern Gulf of Mexico. Bull. Mar. Sci. 87, 301–324 (2011).Article 

    Google Scholar 
    Cowan, J. H. Red snapper in the Gulf of Mexico and the U.S. South Atlantic: data, doubt, and debate. Fisheries 36, 319–331 (2011).Article 

    Google Scholar 
    Addis, D. T., Patterson, W. F. III. & Dance, M. A. The potential for unreported artificial reefs to serve as refuges from fishing mortality for reef fishes. N. Am. J. Fish. Manag. 36, 131–139 (2016).Article 

    Google Scholar 
    McCawley, J. R., Cowan, J. H. Jr. & Shipp, R. L. Feeding periodicity and prey habitat preference of red snapper, Lutjanus campechanus (Poey, 1860), on Alabama artificial reefs. Gulf Mex. Sci. 24, 14–27 (2006).
    Google Scholar 
    Glenn, H. D., Cowan, J. H. Jr. & Powers, J. E. A comparison of red snapper reproductive potential in the northwestern Gulf of Mexico: Natural versus artificial habitats. Mar. Coast. Fish. 9, 139–148 (2017).Article 

    Google Scholar 
    Kulaw, D. H., Cowan, J. H. Jr. & Jackson, M. W. Temporal and spatial comparisons of the reproductive biology of northern Gulf of Mexico (USA) red snapper (Lutjanus campechanus) collected a decade apart. PLoS One 12, e0172360 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Vose, F. E. & Nelson, W. G. Gray triggerfish (Balistes capriscus Gmelin) feeding from artificial and natural substrate in shallow Atlantic waters of Florida. Bull. Mar. Sci. 55, 1316–1323 (1994).
    Google Scholar 
    Herbig, J. L. & Szedlmayer, S. T. Movement patterns of gray triggerfish, Balistes capriscus, around artificial reefs in the northern Gulf of Mexico. Fish. Manag. Ecol. 23, 418–427 (2016).Article 

    Google Scholar 
    Szedlmayer, S. T. & Schroepfer, R. L. Long-term residence of red snapper on artificial reefs in the northeastern Gulf of Mexico. Trans. Am. Fish. Soc. 134, 315–325 (2005).Article 

    Google Scholar 
    Watterson, J. C. III., Patterson, W. F. I. I. I., Shipp, R. L. & Cowan, J. H. Jr. Movement of red snapper, Lutjanus campechanus, in the north central Gulf of Mexico: Potential effects of hurricanes. Gulf Mex. Sci. 16, 92–104 (1998).
    Google Scholar 
    Ingram, G. W. Jr. & Patterson, W. F. I. I. I. Movement patterns of red snapper (Lutjanus campechanus), greater amberjack (Seriola dumerili), and gray triggerfish (Balistes capriscus) in the Gulf of Mexico and the utility of marine reserves as management tools. Proc. Gulf Caribb. Fish. Inst. 52, 686–699 (2001).
    Google Scholar 
    Strelcheck, A. J., Cowan, J. H. Jr. & Patterson, W. F. III. Site fidelity, movement, and growth of red snapper Lutjanus campechanus: implications for artificial reef management. In Red Snapper Ecology and Fisheries in the U.S. Gulf of Mexico. American Fisheries Society Symposium 60 (eds. Patterson, W. F. III, Cowan, J. H. Jr., Nieland, D. A. & Fitzhugh, G. R.), 147–162 (2007).Addis, D. T., Patterson, W. F. I. I. I., Dance, M. A. & Ingram, G. W. Jr. Implications of reef fish movement from unreported artificial reef sites in the northern Gulf of Mexico. Fish. Res. 147, 349–358 (2013).Article 

    Google Scholar 
    Topping, D. T. & Szedlmayer, S. T. Site fidelity, residence time and movements of red snapper Lutjanus campechanus estimated with long-term acoustic monitoring. Mar. Ecol. Prog. Ser. 437, 183–200 (2011).ADS 
    Article 

    Google Scholar 
    Everett, A. G., Szedlmayer, S. T. & Gallaway, B. J. Movement patterns of red snapper Lutjanus campechanus based on acoustic telemetry around oil and gas platforms in the northern Gulf of Mexico. Mar. Ecol. Prog. Ser. 649, 155–173 (2020).Article 

    Google Scholar 
    Tarnecki, J. H. & Patterson, W. F. I. I. I. Changes in red snapper diet and trophic ecology following the Deepwater Horizon Oil Spill. Mar. Coast. Fish. 7, 135–147 (2015).Article 

    Google Scholar 
    McCawley, J. R. & Cowan, J. H. Jr. Seasonal and size specific diet and prey demand of Red Snapper on Alabama artificial reefs. In Red Snapper Ecology and Fisheries in the U.S. Gulf of Mexico. American Fisheries Society Symposium 60 (eds. Patterson, W. F. III., Cowan, J. H. Jr., Fitzhugh, G. R. & Nieland, D. L.), 77–104 (2007).Piraino, M. N. & Szedlmayer, S. T. Fine-scale movements and home ranges of red snapper around artificial reefs in the northern Gulf of Mexico. Trans. Am. Fish. Soc. 143, 988–998 (2014).Article 

    Google Scholar 
    Williams-Grove, L. J. & Szedlmayer, S. T. Depth preferences and three-dimensional movements of red snapper, Lutjanus campechanus, on an artificial reef in the northern Gulf of Mexico. Fish. Res. 190, 61–70 (2017).Article 

    Google Scholar 
    Topping, D. T. & Szedlmayer, S. T. Home range and movement patterns of red snapper (Lutjanus campechanus) on artificial reefs. Fish. Res. 112, 77–84 (2011).Article 

    Google Scholar 
    Baker, M. S. J. & Wilson, C. A. Use of bomb radiocarbon to validate otolith section ages of red snapper Lutjanus campechanus from the northern Gulf of Mexico. Limnol. Oceanogr. 46, 1819–1824 (2001).ADS 
    Article 

    Google Scholar 
    Allman, R. J., Fioramonti, C. L., Patterson, W. F. III. & Pacicco, A. E. Validation of annual growth-zone formation in gray triggerfish Balistes capriscus dorsal spines, fin rays, and vertebrae. Gulf Mex. Sci. 33, 68–76 (2016).
    Google Scholar 
    Frazer, T. K., Lindberg, W. J. & Stanton, G. R. Predation on sand dollars by gray triggerfish, Balistes capriscus, in the northeastern Gulf of Mexico. Bull. Mar. Sci. 48, 159–164 (1991).
    Google Scholar 
    Delorenzo, D. M., Bethea, D. M. & Carlson, J. K. An assessment of the diet and trophic level of Atlantic sharpnose shark Rhizoprionodon terraenovae. J. Fish Biol. 86, 385–391 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Aines, A. C., Carlson, J. K., Boustany, A., Mathers, A. & Kohler, N. E. Feeding habits of the tiger shark, Galeocerdo cuvier, in the northwest Atlantic Ocean and Gulf of Mexico. Environ. Biol. Fish. 101, 403–415 (2018).Article 

    Google Scholar 
    Castro, J. I. The Sharks of North America (Oxford University Press, 2011).
    Google Scholar 
    Springer, S. A collection of fishes from the stomachs of sharks taken off Salerno, Florida. Copeia 3, 174–175 (1946).Article 

    Google Scholar 
    Bohaboy, E. C., Guttridge, T. L., Hammerschlag, N., Van Zinnicq Bergmann, M. P. M. & Patterson, W. F. III. Application of three-dimensional acoustic telemetry to assess the effects of rapid recompression on reef fish discard mortality. ICES J. Mar. Sci. 77, 83–96 (2020).Article 

    Google Scholar 
    Drymon, J. M., Powers, S. P., Dindo, J., Dzwonkowski, B. & Henwood, T. Distributions of sharks across a continental shelf in the northern Gulf of Mexico. Mar. Coast. Fish. Dyn. Manag. Ecosyst. Sci. 2, 440–450 (2010).Article 

    Google Scholar 
    Ajemian, M. J. et al. Movement patterns and habitat use of tiger sharks (Galeocerdo cuvier) across ontogeny in the Gulf of Mexico. PLoS One 15, 1–24 (2020).
    Google Scholar 
    Ouzts, A. C. & Szedlmayer, S. T. Diel feeding patterns of Red Snapper on artificial reefs in the north-central Gulf of Mexico. Trans. Am. Fish. Soc. 132, 1186–1193 (2003).Article 

    Google Scholar 
    White, D. B. & Palmer, S. M. Age, growth, and reproduction of the red snapper, Lutjanus campechanus, from the Atlantic waters of the Southeastern US. Bull. Mar. Sci. 75, 335–360 (2004).
    Google Scholar 
    Fitzhugh, G. R., Lyon, H. M. & Barnett, B. K. Reproductive parameters of gray triggerfish (Balistes capriscus) from the Gulf of Mexico: Sex ratio, maturity and spawning fraction. SEDAR43-WP-03. (2015). http://sedarweb.org/sedar-82-rd14-sedar43-wp-03reproductive-parameters-gray-triggerfish-balistes-capriscus-gulf-mexico. Accessed 12 April 2021.Kelly-Stormer, A. et al. Gray Triggerfish reproductive biology, age, and growth off the Atlantic coast of the Southeastern USA. Trans. Am. Fish. Soc. 146, 523–538 (2017).Article 

    Google Scholar 
    Porch, C. E., Fitzhugh, G. R., Lang, E. T., Lyon, H. M. & Linton, B. C. Estimating the dependence of spawning frequency on size and age in Gulf of Mexico red snapper. Mar. Coast. Fish. 7, 233–245 (2015).Article 

    Google Scholar 
    Lang, E. T. & Fitzhugh, G. R. Oogenesis and fecundity type of gray triggerfish in the Gulf of Mexico. Mar. Coast. Fish. Dyn. Manag. Ecosyst. Sci. 7, 338–348 (2015).Article 

    Google Scholar 
    Woods, M. K. et al. Size and age at maturity of female red snapper Lutjanus campechanus in the Northern Gulf of Mexico. Proc. Gulf Caribb. Fish. Inst. 54, 526–537 (2003).
    Google Scholar 
    Simmons, C. M. & Szedlmayer, S. T. Territoriality, reproductive behavior, and parental care in gray triggerfish, Balistes capriscus, from the Northern Gulf of Mexico. Bull. Mar. Sci. 88, 197–209 (2012).Article 

    Google Scholar 
    Mackichan, C. A. & Szedlmayer, S. T. Reproductive behavior of the gray triggerfish, Balistes capriscus, in the northeastern Gulf of Mexico. Proc. Gulf Caribb. Fish. Inst. 59, 213–218 (2007).
    Google Scholar 
    Diamond, S. L. et al. Movers and stayers: Individual variability in site fidelity and movements of red snapper off Texas. In Red Snapper Ecology and Fisheries in the U.S. Gulf of Mexico. American Fisheries Society Symposium 60 (eds. Patterson, W. F. III, Cowan, J. H. Jr., Nieland, D. A. & Fitzhugh, G. R.), 163–187 (2007).Spiegel, O., Leu, S. T., Bull, C. M. & Sih, A. What’s your move? Movement as a link between personality and spatial dynamics in animal populations. Ecol. Lett. 20, 3–18 (2017).ADS 
    PubMed 
    Article 

    Google Scholar 
    Smith, F. Understanding HPE in the VEMCO Positioning System (VPS). (2013).US Department of Defense. Global Positioning System Standard Positioning Service Performance Standard. http://www.gps.gov/technical/ps/2008-SPS-performance-standard.pdf (2008). Accessed 08 July 2020.Heupel, M. R., Reiss, K. L., Yeiser, B. G. & Simpfendorfer, C. A. Effects of biofouling on performance of moored data logging acoustic receivers. Limnol. Oceanogr. Methods 6, 327–335 (2008).Article 

    Google Scholar 
    National Oceanic and Atmospheric Administration & National Weather Service. National Data Buoy Center: Station 42012—Orange Beach. http://www.ndbc.noaa.gov/station_page.php?station=42012 (2017). Accessed 07 November 2017.National Oceanic and Atmospheric Administration & National Weather Service. National Data Buoy Center: Station 42040- Luke Offshore Test Platform. https://www.ndbc.noaa.gov/station_page.php?station=42040 (2019). Accessed 07 January 2019.Lazaridis, E. R Package ‘lunar’: lunar phase & distance, seasons and other environmental factors. https://cran.r-project.org/web/packages/lunar/lunar.pdf (2015). Accessed 12 August 2019.Thieurmel, B. & Elmarhraoui, A. R Package ‘suncalc’: compute sun position, sunlight phases, moon position and lunar phase. https://cran.r-project.org/web/packages/suncalc/suncalc.pdf (2019). Accessed 22 June 2019.National Geophysical Data Center. U.S. Coastal Relief Model—Central Gulf of Mexico. https://doi.org/10.7289/V54Q7RW0 (2001).Cox, D. R. & Oakes, D. Analysis of Survival Data (Chapman and Hall, 1984).Benhamou, S. Dynamic approach to space and habitat use based on biased random bridges. PLoS One 6, e14592 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Horne, J. S., Garton, E. O., Krone, S. M. & Lewis, J. S. Analyzing animal movements using Brownian bridges. Ecology 88, 2354–2363 (2007).PubMed 
    Article 

    Google Scholar 
    Tracey, J. A. et al. Movement-based estimation and visualization of space use in 3D for wildlife ecology and conservation. PLoS One 9, e101205 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Tracey, J. A. et al. R Package ‘mkde’: 2D and 3D movement-based kernel density estimates (MKDEs). https://CRAN.R-project.org/package=mkde (2014). Accessed 17 June 2019.Worton, B. J. Kernel methods for estimating the utilization distribution in home-range studies. Ecology 70, 164–168 (1989).Article 

    Google Scholar 
    Wood, S. N. Package ‘mgcv’: Mixed GAM computation vehicle with automatic smoothness estimation. https://doi.org/10.1201/9781315370279 (2019). More

  • in

    The gut microbiota affects the social network of honeybees

    Wilson, E. O. Sociobiology: The New Synthesis (Harvard Univ. Press, 1975).Diamond, J. M. & Ordunio, D. Guns, Germs, and Steel (Books on Tape, 1999).Couzin, I. D. et al. Self-organization and collective behavior in vertebrates. Adv. Study Behav. 32, 1–75 (2003).
    Google Scholar 
    Keller, L. Adaptation and the genetics of social behaviour. Philos. Trans. R. Soc. Lond. B 364, 3209–3216 (2009).
    Google Scholar 
    Kay, T., Keller, L. & Lehmann, L. The evolution of altruism and the serial rediscovery of the role of relatedness. Proc. Natl Acad. Sci. USA 117, 28894–28898 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cryan, J. F. & Dinan, T. G. Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat. Rev. Neurosci. 13, 701–712 (2012).CAS 
    PubMed 

    Google Scholar 
    Johnson, K. V. A. & Foster, K. R. Why does the microbiome affect behaviour? Nat. Rev. Microbiol. 16, 647–655 (2018).CAS 
    PubMed 

    Google Scholar 
    Sherwin, E., Bordenstein, S. R., Quinn, J. L., Dinan, T. G. & Cryan, J. F. Microbiota and the social brain. Science 366, eaar2016 (2019).CAS 
    PubMed 

    Google Scholar 
    Desbonnet, L., Clarke, G., Shanahan, F., Dinan, T. G. & Cryan, J. F. Microbiota is essential for social development in the mouse. Mol. Psychiatry 19, 146–148 (2014).CAS 
    PubMed 

    Google Scholar 
    Sharon, G. et al. Human gut microbiota from autism spectrum disorder promote behavioral symptoms in mice. Cell 177, 1600–1618 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhang, M. et al. A quasi-paired cohort strategy reveals the impaired detoxifying function of microbes in the gut of autistic children. Sci. Adv. 6, eaba3760 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wu, W.-L. et al. Microbiota regulate social behaviour via stress response neurons in the brain. Nature 595, 409–414 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Vuong, H. E., Yano, J. M., Fung, T. C. & Hsiao, E. Y. The microbiome and host behavior. Annu. Rev. Neurosci. 40, 21–49 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Douglas, A. E. Simple animal models for microbiome research. Nat. Rev. Microbiol. 17, 764–775 (2019).CAS 
    PubMed 

    Google Scholar 
    Schretter, C. E. Links between the gut microbiota, metabolism, and host behavior. Gut Microbes 11, 245–248 (2020).PubMed 

    Google Scholar 
    Liberti, J. & Engel, P. The gut microbiota–brain axis of insects. Curr. Opin. Insect Sci. 39, 6–13 (2020).PubMed 

    Google Scholar 
    O’Donnell, M. P., Fox, B. W., Chao, P.-H., Schroeder, F. C. & Sengupta, P. A neurotransmitter produced by gut bacteria modulates host sensory behaviour. Nature 583, 415–420 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Wilson, E. O. The Insect Societies (Harvard Univ. Press, 1971).Hölldobler, B. & Wilson, E. O. The Ants (Harvard Univ. Press, 1990).Teseo, S. et al. The scent of symbiosis: gut bacteria may affect social interactions in leaf-cutting ants. Anim. Behav. 150, 239–254 (2019).
    Google Scholar 
    Vernier, C. L. et al. The gut microbiome defines social group membership in honey bee colonies. Sci. Adv. 6, eabd3431 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Li, L. et al. Gut microbiome drives individual memory variation in bumblebees. Nat. Commun. 12, 6588 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Choi, S. H. et al. Individual variations lead to universal and cross-species patterns of social behavior. Proc. Natl Acad. Sci. USA 117, 31754–31759 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Geffre, A. C. et al. Honey bee virus causes context-dependent changes in host social behavior. Proc. Natl Acad. Sci. USA 117, 10406–10413 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kwong, W. K. & Moran, N. A. Gut microbial communities of social bees. Nat. Rev. Microbiol. 14, 374–384 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bonilla-Rosso, G. & Engel, P. Functional roles and metabolic niches in the honey bee gut microbiota. Curr. Opin. Microbiol. 43, 69–76 (2018).CAS 
    PubMed 

    Google Scholar 
    Raymann, K. & Moran, N. A. The role of the gut microbiome in health and disease of adult honey bee workers. Curr. Opin. Insect Sci. 26, 97–104 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Zheng, H., Powell, J. E., Steele, M. I., Dietrich, C. & Moran, N. A. Honeybee gut microbiota promotes host weight gain via bacterial metabolism and hormonal signaling. Proc. Natl Acad. Sci. USA 114, 4775–4780 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kešnerová, L. et al. Disentangling metabolic functions of bacteria in the honey bee gut. PLoS Biol. 15, e2003467 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Kešnerová, L. et al. Gut microbiota structure differs between honeybees in winter and summer. ISME J. 14, 801–814 (2020).PubMed 

    Google Scholar 
    Mersch, D. P., Crespi, A. & Keller, L. Tracking individuals shows spatial fidelity is a key regulator of ant social organization. Science 340, 1090–1093 (2013).CAS 
    PubMed 

    Google Scholar 
    Stroeymeyt, N. et al. Social network plasticity decreases disease transmission in a eusocial insect. Science 362, 941–945 (2018).CAS 
    PubMed 

    Google Scholar 
    Kao, A. B. & Couzin, I. D. Modular structure within groups causes information loss but can improve decision accuracy. Philos. Trans. R. Soc. Lond. B 374, 20180378 (2019).
    Google Scholar 
    de Groot, A. P. Protein and amino acid requirements of the honeybee (Apis mellifica L.). Physiol. Comp. Oecol. 3, 197–285 (1953).
    Google Scholar 
    Billard, J.-M. d-Amino acids in brain neurotransmission and synaptic plasticity. Amino Acids 43, 1851–1860 (2012).CAS 
    PubMed 

    Google Scholar 
    Marcaggi, P. & Attwell, D. Role of glial amino acid transporters in synaptic transmission and brain energetics. Glia 47, 217–225 (2004).PubMed 

    Google Scholar 
    Gage, S. L., Calle, S., Jacobson, N., Carroll, M. & DeGrandi-Hoffman, G. Pollen alters amino acid levels in the honey bee brain and this relationship changes with age and parasitic stress. Front. Neurosci. 14, 231 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Kawase, T. et al. Gut microbiota of mice putatively modifies amino acid metabolism in the host brain. Br. J. Nutr. 117, 775–783 (2017).CAS 
    PubMed 

    Google Scholar 
    Socha, E., Koba, M. & Koslinski, P. Amino acid profiling as a method of discovering biomarkers for diagnosis of neurodegenerative diseases. Amino Acids 51, 367–371 (2019).CAS 
    PubMed 

    Google Scholar 
    Tarlungeanu, D. C. et al. Impaired amino acid transport at the blood brain barrier is a cause of autism spectrum disorder. Cell 167, 1481–1494 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Maynard, T. M. & Manzini, M. C. Balancing act: maintaining amino acid levels in the autistic brain. Neuron 93, 476–479 (2017).CAS 
    PubMed 

    Google Scholar 
    Kurochkin, I. et al. Metabolome signature of autism in the human prefrontal cortex. Commun. Biol. 2, 234 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    van der Velpen, V. et al. Systemic and central nervous system metabolic alterations in Alzheimer’s disease. Alzheimer’s Res. Ther. 11, 93 (2019).
    Google Scholar 
    Aldana, B. I. et al. Glutamate–glutamine homeostasis is perturbed in neurons and astrocytes derived from patient iPSC models of frontotemporal dementia. Mol. Brain 13, 125 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Galizia, C. G., Eisenhardt, D. & Giurfa M. (eds) Honeybee Neurobiology and Behavior: A Tribute to Randolf Menzel (Springer Science & Business Media, 2011).Menzel, R. The honeybee as a model for understanding the basis of cognition. Nat. Rev. Neurosci. 13, 758–768 (2012).CAS 
    PubMed 

    Google Scholar 
    Ellegaard, K. M. & Engel, P. Genomic diversity landscape of the honey bee gut microbiota. Nat. Commun. 10, 446 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bruno, F., Angilica, A., Cosco, F., Luchi, M. L. & Muzzupappa, M. Mixed prototyping environment with different video tracking techniques. In IMProVe 2011 International Conference on Innovative Methods in Product Design (eds Concheri, G. et al.) 105–113 (Libreria Internazionale Cortina Padova, 2011).R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).Anderson, K. E., Rodrigues, P. A. P., Mott, B. M., Maes, P. & Corby-Harris, V. Ecological succession in the honey bee gut: shift in Lactobacillus strain dominance during early adult development. Microb. Ecol. 71, 1008–1019 (2016).CAS 
    PubMed 

    Google Scholar 
    Almasri, H., Liberti, J., Brunet, J. L., Engel, P. & Belzunces, L. P. Mild chronic exposure to pesticides alters physiological markers of honey bee health without perturbing the core gut microbiota. Sci. Rep. 12, 4281 (2022).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pfaffl, M. W. A new mathematical model for relative quantification in real-time RT-PCR. Nucleic Acids Res. 29, e45 (2001).Gallup, J. M. in PCR Troubleshooting and Optimization: The Essential Guide (eds Kennedy, S. & Oswald, N.) 23–65 (Caister Academic Press, 2011).Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10–12 (2011).
    Google Scholar 
    Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Davis, N. M., Proctor, D. M., Holmes, S. P., Relman, D. A. & Callahan, B. J. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6, 1–14 (2018).
    Google Scholar 
    Patassini, S. et al. Identification of elevated urea as a severe, ubiquitous metabolic defect in the brain of patients with Huntington’s disease. Biochem. Biophys. Res. Commun. 468, 161–166 (2015).CAS 
    PubMed 

    Google Scholar 
    Gonzalez-Riano, C., Garcia, A. & Barbas, C. Metabolomics studies in brain tissue: a review. J. Pharm. Biomed. Anal. 130, 141–168 (2016).CAS 
    PubMed 

    Google Scholar 
    Belle, J. E. L., Harris, N. G., Williams, S. R. & Bhakoo, K. K. A comparison of cell and tissue extraction techniques using high-resolution 1H-NMR spectroscopy. NMR Biomed. 15, 37–44 (2002).PubMed 

    Google Scholar 
    Wanichthanarak, K., Jeamsripong, S., Pornputtapong, N. & Khoomrung, S. Accounting for biological variation with linear mixed-effects modelling improves the quality of clinical metabolomics data. Comput. Struct. Biotechnol. J. 17, 611–618 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).CAS 
    PubMed 

    Google Scholar 
    Wallberg, A. et al. A hybrid de novo genome assembly of the honeybee, Apis mellifera, with chromosome-length scaffolds. BMC Genomics 20, 275 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).PubMed 
    PubMed Central 

    Google Scholar 
    Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).CAS 
    PubMed 

    Google Scholar 
    Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).PubMed 
    PubMed Central 

    Google Scholar 
    Durinck, S., Spellman, P. T., Birney, E. & Huber, W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt. Nat. Protoc. 4, 1184–1191 (2009).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Falcon, S. & Gentleman, R. Using GOstats to test gene lists for GO term association. Bioinformatics 23, 257–258 (2007).CAS 
    PubMed 

    Google Scholar 
    Reijnders, M. J. & Waterhouse, R. M. Summary visualisations of gene ontology terms with GO-Figure! Front. Bioinform. 1, 638255 (2021).
    Google Scholar  More