Philippa Kaur

These authors contributed equally: György Kröel-Dulay, Andrea Mojzes.Institute of Ecology and Botany, Centre for Ecological Research, Vácrátót, HungaryGyörgy Kröel-Dulay & Andrea Mojzes‘Lendület’ Landscape and Conservation Ecology, Institute of Ecology and Botany, Centre for Ecological Research, Vácrátót, HungaryKatalin Szitár & Péter BatáryDepartment of Ecology, University of Innsbruck, Innsbruck, AustriaMichael BahnDepartment of Geosciences and Natural Resource Management, University of Copenhagen, Frederiksberg, DenmarkClaus Beier, Inger Kappel Schmidt & Klaus Steenberg LarsenNamibia University of Science and Technology, Windhoek, NamibiaMark BiltonPlants and Ecosystems (PLECO), Department of Biology, University of Antwerp, Wilrijk, BelgiumHans J. De Boeck & Sara ViccaDepartment of Forestry and Natural Resources, Purdue University, West Lafayette, IN, USAJeffrey S. DukesDepartment of Biological Sciences, Purdue University, West Lafayette, IN, USAJeffrey S. DukesCSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, SpainMarc Estiarte & Josep PeñuelasCREAF, Cerdanyola del Vallès, SpainMarc Estiarte & Josep PeñuelasGlobal Change Research Institute of the Czech Academy of Sciences, Brno, Czech RepublicPetr HolubDisturbance Ecology, Bayreuth Center of Ecology and Environmental Research, University of Bayreuth, Bayreuth, GermanyAnke JentschExperimental Plant Ecology, University of Greifswald, Greifswald, GermanyJuergen KreylingUK Centre for Ecology & Hydrology, Bangor, UKSabine ReinschSchool of Plant Sciences and Food Security, Faculty of Life Sciences, Tel Aviv University, Tel Aviv, IsraelMarcelo SternbergPlant Ecology Group, University of Tübingen, Tübingen, GermanyKatja TielbörgerInstitute for Biodiversity and Ecosystem Dynamics (IBED), Ecosystem and Landscape Dynamics (ELD), University of Amsterdam, Amsterdam, the NetherlandsAlbert Tietema More

Henrich, J. et al. Costly punishment across human societies. Science https://doi.org/10.1126/science.1127333 (2006).Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action (Cambridge University Press, 1990).Ostrom, E., Walker, J. & Gardner, R. Covenants with and without a sword: self-governance is possible. Am. Polit. Sci. Rev. 86, 404–417 (1992).Article 

Google Scholar 
Fehr, E. & Gächter, S. Cooperation and punishment in public goods experiments. Am. Econ. Rev. 90, 980–994 (2000).Article 

Google Scholar 
Dreber, A., Rand, D. G., Fudenberg, D. & Nowak, M. A. Winners don’t punish. Nature https://doi.org/10.1038/nature06723 (2008).Rand, D. G., Ohtsuki, H. & Nowak, M. A. Direct reciprocity with costly punishment: generous tit-for-tat prevails. J. Theor. Biol. https://doi.org/10.1016/j.jtbi.2008.09.015 (2009).Ohtsuki, H., Iwasa, Y. & Nowak, M. A. Indirect reciprocity provides only a narrow margin of efficiency for costly punishment. Nature https://doi.org/10.1038/nature07601 (2009).Sethi, R. & Somanathan, E. Understanding reciprocity. J. Econ. Behav. Organ. 50, 1–27 (2003).Article 

Google Scholar 
Bowles, S. & Gintis, H. A Cooperative Species (Princeton Univ. Press, 2011).Hauert, C., Traulsen, A., Brandt, H., Nowak, M. A. & Sigmund, K. Via freedom to coercion: the emergence of costly punishment. Science https://doi.org/10.1126/science.1141588 (2007).Brandt, H., Hauert, C. & Sigmund, K. Punishment and reputation in spatial public goods games. Proc. R. Soc. B https://doi.org/10.1098/rspb.2003.2336 (2003).Helbing, D., Szolnoki, A., Perc, M. & Szabó, G. Evolutionary establishment of moral and double moral standards through spatial interactions. PLoS Comput. Biol. https://doi.org/10.1371/journal.pcbi.1000758 (2010).Helbing, D., Szolnoki, A., Perc, M. & Szabó, G. Punish, but not too hard: how costly punishment spreads in the spatial public goods game. New J. Phys. https://doi.org/10.1088/1367-2630/12/8/083005 (2010).Perc, M. & Szolnoki, A. Self-organization of punishment in structured populations. New J. Phys. https://doi.org/10.1088/1367-2630/14/4/043013 (2012).Boyd, R., Gintis, H. & Bowles, S. Coordinated punishment of defectors sustains cooperation and can proliferate when rare. Science https://doi.org/10.1126/science.1183665 (2010).Sigmund, K., De Silva, H., Traulsen, A. & Hauert, C. Social learning promotes institutions for governing the commons. Nature 466, 861–863 (2010).CAS 
Article 

Google Scholar 
Hilbe, C., Traulsen, A., Röhl, T. & Milinski, M. Democratic decisions establish stable authorities that overcome the paradox of second-order punishment. Proc. Natl Acad. Sci. USA 111, 752–756 (2014).CAS 
Article 

Google Scholar 
Murphy, B. The Punisher’s Brain: The Evolution of Judge and Jury. By Hoffman, Morris B. Pp. xi, 359. Cambridge/NY, Cambridge University Press, 2014, £21.99/$30.00. Heythrop J. https://doi.org/10.1111/heyj.12249_81 (2015).Gruter, M. & Masters, R. D. Ostracism as a social and biological phenomenon: an introduction. Ethol. Sociobiolo. https://doi.org/10.1016/0162-3095(86)90043-9 (1986).Molleman, L., Kölle, F., Starmer, C. & Gächter, S. People prefer coordinated punishment in cooperative interactions. Nat. Hum. Behav. https://doi.org/10.1038/s41562-019-0707-2 (2019).Szolnoki, A., Szabó, G. & Perc, M. Phase diagrams for the spatial public goods game with pool punishment. Phys. Rev. E https://doi.org/10.1103/PhysRevE.83.036101 (2011).Ostrom, E. Collective action and the evolution of social norms. J. Econ. Perspect. 14, 137–158 (2000).Article 

Google Scholar 
Platteau, J.-P. Institutions, Social Norms, and Economic Development Vol. 1 (Psychology Press, 2000).van den Bergh, J. C. J. M., Ferrer-i-Carbonell, A. & Munda, G. Alternative models of individual behaviour and implications for environmental policy. Ecol. Econ. 32, 43–61 (2000).Article 

Google Scholar 
Traulsen, A., Nowak, M. A. & Pacheco, J. M. Stochastic dynamics of invasion and fixation. Phys. Rev. E 74, 11909 (2006).Article 

Google Scholar 
Dequech, D. Institutions, social norms, and decision-theoretic norms. J. Econ. Behav. Organ. 72, 70–78 (2009).Article 

Google Scholar 
Dunn, S. P. Bounded rationality is not fundamental uncertainty: a post Keynesian perspective. J. Post Keynes. Econ. 23, 567–587 (2001).Article 

Google Scholar 
Levin, S. The trouble of discounting tomorrow. Solutions 3, 20–24 (2012).
Google Scholar 
Alford, R. P. The proliferation of international courts and tribunals: international adjudication in ascendance. In Proc. Annual Meeting of the American Society of International Law Vol. 94, 160–165 (Cambridge University Press, 2000).Dunn, L. A. Containing Nuclear Proliferation (International Institute for Strategic Studies, 1991).Potoski, M. Green clubs in building block climate change regimes. Climatic Change 144, 53–63 (2017).Article 

Google Scholar 
Trzyna, T. C., Margold, E. & Osborn, J. K. World Directory of Environmental Organizations: A Handbook of National and International Organizations and Programs—Governmental and Non-governmental—Concerned with Protecting the Earth’s Resources Vol. 5 (Earthscan, 1996).Dixit, A. & Levin, S. in The Theory of Externalities and Public Goods: Essays in Memory of Richard C. Cornes (eds Buchholz, W. and Rübbelke, D.) 127–143 (Springer, 2017); https://doi.org/10.1007/978-3-319-49442-5_7Vasconcelos, V. V., Santos, F. C. & Pacheco, J. M. A bottom-up institutional approach to cooperative governance of risky commons. Nat. Clim. Change 3, 797–801 (2013).Article 

Google Scholar 
Vasconcelos, V. V., Santos, F. C. & Pacheco, J. M. Cooperation dynamics of polycentric climate governance. Math. Model. Methods Appl. Sci. 25, 2503–2517 (2015).Article 

Google Scholar 
Ostrom, E. Beyond markets and states: polycentric governance of complex economic systems. Am. Econ. Rev. 100, 641–672 (2010).Article 

Google Scholar 
Vasconcelos, V. V., Hannam, P. M., Levin, S. A. & Pacheco, J. M. Coalition-structured governance improves cooperation to provide public goods. Sci. Rep. 10, 9194 (2020).CAS 
Article 

Google Scholar 
Nyborg, K. et al. Social norms as solutions. Science 354, 42–43 (2016).CAS 
Article 

Google Scholar 
Hannam, P. M., Vasconcelos, V. V., Levin, S. A. & Pacheco, J. M. Incomplete cooperation and co-benefits: deepening climate cooperation with a proliferation of small agreements. Climatic Change 144, 65–79 (2017).Article 

Google Scholar 
Markussen, T., Putterman, L. & Tyran, J.-R. Self-organization for collective action: an experimental study of voting on sanction regimes. Rev. Econ. Stud. 81, 301–324 (2014).Article 

Google Scholar 
Gürerk, Ö., Irlenbusch, B. & Rockenbach, B. The competitive advantage of sanctioning institutions. Science 312, 108–111 (2006).Article 

Google Scholar 
Dannenberg, A. & Gallier, C. The choice of institutions to solve cooperation problems: a survey of experimental research. Exp. Econ. https://doi.org/10.1007/s10683-019-09629-8 (2019).Bühren, C. & Dannenberg, A. The demand for punishment to promote cooperation among like-minded people. Eur. Econ. Rev. 138, 103862 (2021).Radzvilavicius, A. L., Kessinger, T. A. & Plotkin, J. B. Adherence to public institutions that foster cooperation. Nat. Commun. 12, 3567 (2021).CAS 
Article 

Google Scholar  More

Darwin, C. The Effects of Cross and Self Fertilisation in the Vegetable Kingdom (D. Appleton and Company, 1877).
Google Scholar 
Charlesworth, D. Androdioecy and the evolution of dioecy. Biol. J. Linn Soc. 22, 333–348 (1984).Article 

Google Scholar 
Charlesworth, D., Morgan, M. T. & Charlesworth, B. Inbreeding depression, genetic load, and the evolution of outcrossing rates in a multilocus system with no linkage. Evolution 44, 1469–1489 (1990).CAS 
Article 

Google Scholar 
Lande, R. & Schemske, D. W. The evolution of self-fertilization and inbreeding depression in plants. I. Genetic models. Evolution 39, 24–40 (1985).
Google Scholar 
Weeks, S. C. When males and hermaphrodites coexist: a review of androdioecy in animals. Integr. Comp. Biol. 46, 449–464 (2006).Article 

Google Scholar 
Pannell, J. The maintenance of gynodioecy and androdioecy in a metapopulation. Evolution 51, 10–20 (1997).Article 

Google Scholar 
Wolf, D. E. & Takebayashi, N. Pollen limitation and the evolution of androdioecy from dioecy. Am. Nat. 163, 122–137 (2004).Article 

Google Scholar 
Charlesworth, D. Theories of the evolution of dioecy. In Gender and Sexual Dimorphism in Flowering Plants (eds Geber, M. A. et al.) 33–60 (Springer, Berlin, 1999). https://doi.org/10.1007/978-3-662-03908-3_2.Chapter 

Google Scholar 
Denver, D. R., Clark, K. A. & Raboin, M. J. Reproductive mode evolution in nematodes: insights from molecular phylogenies and recently discovered species. Mol. Phylogenetics Evol. 61, 584–592 (2011).CAS 
Article 

Google Scholar 
Pires-daSilva, A. Evolution of the control of sexual identity in nematodes. Semin. Cell Dev. Biol. 18, 362–370 (2007).Article 

Google Scholar 
Kanzaki, N. et al. Description of two three-gendered nematode species in the new genus Auanema (Rhabditina) that are models for reproductive mode evolution. Sci. Rep. 7, 11135 (2017).ADS 
Article 

Google Scholar 
Tandonnet, S. et al. Sex- and gamete-specific patterns of X chromosome segregation in a trioecious nematode. Curr. Biol. 28, 93-99.e3 (2018).CAS 
Article 

Google Scholar 
Chaudhuri, J. et al. Mating dynamics in a nematode with three sexes and its evolutionary implications. Sci. Rep. 5, 17676 (2015).ADS 
CAS 
Article 

Google Scholar 
Félix, M.-A. Alternative morphs and plasticity of vulval development in a rhabditid nematode species. Dev. Genes Evol. 214, 55–63 (2004).Article 

Google Scholar 
Shakes, D. C., Neva, B. J., Huynh, H., Chaudhuri, J. & Pires-daSilva, A. Asymmetric spermatocyte division as a mechanism for controlling sex ratios. Nat. Commun. 2, 157 (2011).ADS 
Article 

Google Scholar 
Winter, E. S. et al. Cytoskeletal variations in an asymmetric cell division support diversity in nematode sperm size and sex ratios. Development 144, 3253–3263 (2017).CAS 

Google Scholar 
Robles, P. et al. Parental energy-sensing pathways control intergenerational offspring sex determination in the nematode Auanema freiburgensis. BMC Biol. 19, 102 (2021).CAS 
Article 

Google Scholar 
Zuco, G. et al. Sensory neurons control heritable adaptation to stress through germline reprogramming. bioRxiv 406033 (2018) https://doi.org/10.1101/406033.Colegrave, N., Kaltz, O. & Bell, G. The ecology and genetics of fitness in chlamydomonas. VIII. The dynamics of adaptation to novel environments after a single episode of sex. Evolution 56, 14–21 (2002).Article 

Google Scholar 
Goddard, M. R., Godfray, H. C. J. & Burt, A. Sex increases the efficacy of natural selection in experimental yeast populations. Nature 434, 636–640 (2005).ADS 
CAS 
Article 

Google Scholar 
Gray, J. C. & Goddard, M. R. Sex enhances adaptation by unlinking beneficial from detrimental mutations in experimental yeast populations. BMC Evol. Biol. 12, 43 (2012).Article 

Google Scholar 
Poon, A. & Chao, L. Drift increases the advantage of sex in RNA bacteriophage ⌽6. Genetics 166, 19 (2004).Article 

Google Scholar 
Stewart, A. D. & Phillips, P. C. Selection and maintenance of androdioecy in Caenorhabditis elegans. Genetics 160, 975–982 (2002).Article 

Google Scholar 
Stiernagle, T. Maintenance of C. elegans. WormBook: The Online Review of C. elegans Biology (WormBook, 2006).Avery, L. The genetics of feeding in Caenorhabditis elegans. Genetics 133, 897–917 (1993).CAS 
Article 

Google Scholar 
Bargmann, C. I. & Horvitz, H. R. Control of larval development by chemosensory neurons in Caenorhabditis elegans. Science 251, 1243–1246 (1991).ADS 
CAS 
Article 

Google Scholar 
Lenth, R. V. Emmeans: estimated marginal means, aka least-squares means (2021).Lipton, J., Kleemann, G., Ghosh, R., Lints, R. & Emmons, S. W. Mate searching in Caenorhabditis elegans: a genetic model for sex drive in a simple invertebrate. J. Neurosci. 24, 7427–7434 (2004).CAS 
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 
Pino, E. C., Webster, C. M., Carr, C. E. & Soukas, A. A. Biochemical and high throughput microscopic assessment of fat mass in Caenorhabditis elegans. J. Vis. Exp. https://doi.org/10.3791/50180 (2013).Article 

Google Scholar 
Hakim, A. et al. WorMachine: machine learning-based phenotypic analysis tool for worms. BMC Biol. 16, 8 (2018).Article 

Google Scholar 
Motola, D. L. et al. Identification of ligands for DAF-12 that govern dauer formation and reproduction in C. elegans. Cell 124, 1209–1223 (2006).CAS 
Article 

Google Scholar 
Ogawa, A., Streit, A., Antebi, A. & Sommer, R. J. A conserved endocrine mechanism controls the formation of dauer and infective larvae in nematodes. Curr. Biol. 19, 67–71 (2009).CAS 
Article 

Google Scholar 
Wang, Z. et al. Identification of the nuclear receptor DAF-12 as a therapeutic target in parasitic nematodes. Proc. Natl. Acad. Sci. 106, 9138–9143 (2009).ADS 
CAS 
Article 

Google Scholar 
Hu, P. Dauer. WormBook: The C. elegans Research Community (2007).Chaudhuri, J., Kache, V. & Pires-daSilva, A. Regulation of sexual plasticity in a nematode that produces males, females, and hermaphrodites. Curr. Biol. 21, 1548–1551 (2011).CAS 
Article 

Google Scholar 
Luciani, G. M. et al. Dafadine inhibits DAF-9 to promote dauer formation and longevity of Caenorhabditis elegans. Nat. Chem. Biol. 7, 891–893 (2011).CAS 
Article 

Google Scholar 
Adams, S., Pathak, P., Shao, H., Lok, J. B. & Pires-daSilva, A. Liposome-based transfection enhances RNAi and CRISPR-mediated mutagenesis in non-model nematode systems. Sci. Rep. 9, 483 (2019).ADS 
Article 

Google Scholar 
Andrews, S. FastQC: A Quality Control Tool for High Throughput Sequence Data [Online]. http://www.bioinformatics.babraham.ac.uk/projects/fastqc/ (2010).Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).CAS 
Article 

Google Scholar 
Grabherr, M. G. et al. Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nat. Biotechnol. 29, 644–652 (2011).CAS 
Article 

Google Scholar 
Haas, B. J. et al. De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity. Nat. Protoc. 8, 1494 (2013).CAS 
Article 

Google Scholar 
Schmieder, R. & Edwards, R. Fast identification and removal of sequence contamination from genomic and metagenomic datasets. PLoS ONE 6, e17288 (2011).ADS 
CAS 
Article 

Google Scholar 
Huang, Y., Niu, B., Gao, Y., Fu, L. & Li, W. CD-HIT Suite: a web server for clustering and comparing biological sequences. Bioinformatics 26, 680–682 (2010).CAS 
Article 

Google Scholar 
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).CAS 
Article 

Google Scholar 
Bendtsen, J. D., Nielsen, H., von Heijne, G. & Brunak, S. Improved prediction of signal peptides: SignalP 3.0. J. Mol. Biol. 340, 783–795 (2004).Article 

Google Scholar 
Bryant, D. M. et al. A tissue-mapped axolotl de novo transcriptome enables identification of limb regeneration factors. Cell Rep. 18, 762–776 (2017).CAS 
Article 

Google Scholar 
Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucl. Acids Res. 39, W29–W37 (2011).CAS 
Article 

Google Scholar 
Andersen, C. L., Jensen, J. L. & Ørntoft, T. F. Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 64, 5245–5250 (2004).CAS 
Article 

Google Scholar 
McGhee, J. D. The C. elegans intestine. WormBook: The Online Review of C. elegans Biology [Internet] (WormBook, 2007).Mullaney, B. C. & Ashrafi, K. C. elegans fat storage and metabolic regulation. Biochim. Biophys. Acta (BBA) Mol. Cell Biol. Lipids 1791, 474–478 (2009).CAS 

Google Scholar 
O’Rourke, E. J., Soukas, A. A., Carr, C. E. & Ruvkun, G. C. elegans major fats are stored in vesicles distinct from lysosome-related organelles. Cell Metab. 10, 430–435 (2009).Article 

Google Scholar 
Mak, H. Y. Lipid droplets as fat storage organelles in Caenorhabditis elegans. J. Lipid Res. 53, 28–33 (2012).CAS 
Article 

Google Scholar 
Kroetz, S. M., Srinivasan, J., Yaghoobian, J., Sternberg, P. W. & Hong, R. L. The cGMP signaling pathway affects feeding behavior in the necromenic nematode Pristionchus pacificus. BMC Proc. 6, P27 (2012).Article 

Google Scholar 
Edgar, L. G. & McGhee, J. D. Embryonic expression of a gut-specific esterase in Caenorhabditis elegans. Dev. Biol. 114, 109–118 (1986).CAS 
Article 

Google Scholar 
Barr, M. M. & Sternberg, P. W. A polycystic kidney-disease gene homologue required for male mating behaviour in C. elegans. Nature 401, 386 (1999).ADS 
CAS 

Google Scholar 
Bendesky, A., Tsunozaki, M., Rockman, M. V., Kruglyak, L. & Bargmann, C. I. Catecholamine receptor polymorphisms affect decision-making in C. elegans. Nature 472, 313–318 (2011).ADS 
CAS 
Article 

Google Scholar 
Garrison, J. L. et al. Oxytocin/vasopressin-related peptides have an ancient role in reproductive behavior. Science 338, 540–543 (2012).ADS 
CAS 
Article 

Google Scholar 
Joo, H.-J. et al. Contribution of the peroxisomal acox gene to the dynamic balance of daumone production in Caenorhabditis elegans. J. Biol. Chem. 285, 29319–29325 (2010).CAS 
Article 

Google Scholar 
Yassin, L. et al. Characterization of the DEG-3/DES-2 receptor: a nicotinic acetylcholine receptor that mutates to cause neuronal degeneration. Mol. Cell. Neurosci. 17, 589–599 (2001).CAS 
Article 

Google Scholar 
Zhang, X., Wang, Y., Perez, D. H., Lipinski, R. A. J. & Butcher, R. A. Acyl-CoA oxidases fine-tune the production of ascaroside pheromones with specific side chain lengths. ACS Chem. Biol. https://doi.org/10.1021/acschembio.7b01021 (2018).Article 

Google Scholar 
Borne, F., Kasimatis, K. R. & Phillips, P. C. Quantifying male and female pheromone-based mate choice in Caenorhabditis nematodes using a novel microfluidic technique. PLoS ONE 87, 511 (2017).
Google Scholar 
Choe, A. et al. Sex-specific mating pheromones in the nematode Panagrellus redivivus. Proc. Natl. Acad. Sci. 109, 20949–20954 (2012).ADS 
CAS 
Article 

Google Scholar 
Duggal, C. L. Sex attraction in the free-living nematode panagrellus redivivus. Nematologica 24, 213–221 (1978).Article 

Google Scholar 
Andersson, M. Sexual Selection Vol. 72 (Princeton University Press, 1994).Book 

Google Scholar 
Bateman, A. J. Intra-sexual selection in Drosophila. Heredity 2, 349–368 (1948).CAS 
Article 

Google Scholar 
Kvarnemo, C. & Simmons, L. W. Polyandry as a mediator of sexual selection before and after mating. Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20120042 (2013).Article 

Google Scholar 
Parker, G. A. & Birkhead, T. R. Polyandry: the history of a revolution. Philos. Trans. R. Soc. Lond. B Biol. Sci. 368, 20120335 (2013).Article 

Google Scholar 
Rhainds, M. Female mating failures in insects. Entomol. Exp. Appl. 136, 211–226 (2010).Article 

Google Scholar 
Hammond, K. A. Adaptation of the maternal intestine during lactation. J. Mammary Gland Biol. Neoplasia 2, 243–252 (1997).CAS 
Article 

Google Scholar 
Speakman, J. R. The physiological costs of reproduction in small mammals. Philos. Trans. R. Soc. B Biol. Sci. 363, 375–398 (2008).Article 

Google Scholar 
Reiff, T. et al. Endocrine remodelling of the adult intestine sustains reproduction in Drosophila. Elife 4, e06930 (2015).Article 

Google Scholar 
Kaliszewicz, A. Interference of asexual and sexual reproduction in the green hydra. Ecol. Res. 26, 147–152 (2011).Article 

Google Scholar 
Oyarzún, P. A., Nuñez, J. J., Toro, J. E. & Gardner, J. P. A. Trioecy in the Marine Mussel Semimytilus algosus (Mollusca, Bivalvia): stable sex ratios across 22 degrees of a latitudinal gradient. Front. Mar. Sci. 7, 348 (2020).Article 

Google Scholar 
Armoza-Zvuloni, R., Kramarsky-Winter, E., Loya, Y., Schlesinger, A. & Rosenfeld, H. Trioecy, a unique breeding strategy in the sea anemone aiptasia diaphana and its association with sex steroids. Biol. Reprod. 90, 122 (2014).Article 

Google Scholar 
Greene, J. S. et al. Balancing selection shapes density-dependent foraging behaviour. Nature. 539(7628), 254–258. https://doi.org/10.1038/nature19848 (2016).ADS 
CAS 
Article 

Google Scholar 
Kieninger, M. R. et al. The Nuclear Hormone Receptor NHR-40 Acts Downstream of the Sulfatase EUD-1 as Part of a Developmental Plasticity Switch in Pristionchus.Curr Biol 26(16), 2174–2179. https://doi.org/10.1016/j.cub.2016.06.018 (2016).Therrien, M., Rouleau, G. A., Dion, P. A., Parker, J. A. & Dupuy, D. Deletion of C9ORF72 Results in Motor Neuron Degeneration and Stress Sensitivity in C. elegans. PLoS ONE 8(12), e83450. https://doi.org/10.1371/journal.pone.0083450 (2013).Lee, B. H., Liu, J., Wong, D., Srinivasan, S., Ashrafi, K. & Kim, S. K. Hyperactive Neuroendocrine Secretion Causes Size Feeding and Metabolic Defects of C. elegans Bardet-Biedl Syndrome Mutants. PLoS Biol 9(12), e1001219. https://doi.org/10.1371/journal.pbio.1001219 (2011).CAS 
Article 

Google Scholar 
Li, C. & Kim, K. Family of FLP Peptides in Caenorhabditis elegans and Related Nematodes. Front Endocrinol. https://doi.org/10.3389/fendo.2014.00150 (2014). Buntschuh, I. et al. FLP-1 neuropeptides modulate sensory and motor circuits in the nematode Caenorhabditis elegans. PLoS ONE 13(1), e0189320. https://doi.org/10.1371/journal.pone.0189320 (2018).Topalidou, I. et al. The EARP Complex and Its Interactor EIPR-1 Are Required for Cargo Sorting to Dense-Core Vesicles. PLOS Genet 12(5), e1006074. https://doi.org/10.1371/journal.pgen.1006074 (2016).Maman, M. et al. A Neuronal GPCR is Critical for the Induction of the Heat Shock Response in the Nematode C. elegans. J Neurosci 33(14), 6102–6111. https://doi.org/10.1523/JNEUROSCI.4023-12.2013 (2013). More

High-severity fire results in a multi-decadal recovery of the soil microbiome, with concomitant differences in aboveground vegetation and soil chemistryMicrobial community composition was significantly different among all post-fire stages (PerMANOVA – prokaryotes: p  More

Aune, J. B. & Lal, R. Agricultural productivity in the tropics and critical limits of properties of Oxisols, Ultisols, Alfisols. Trop. Agric. (Trinidad and Tobago) 74, 96–103 (1997).
Google Scholar 
Bauer, A. & Black, A. L. Quantification of the effect of soil organic matter content on soil productivity. Soil Sci. Soc. Am. J. 58, 185–193 (1994).ADS 
Article 

Google Scholar 
Hamamoto, T., Chirwa, M., Nyambe, I. & Uchida, Y. Small-scale variability in the soil microbial community structure in a semideveloped farm in Zambia. Appl. Environ. Soil Sci. 2018, 1–6 (2018).Article 

Google Scholar 
Mapanda, F., Wuta, M., Nyamangara, J. & Rees, R. M. Effects of organic and mineral fertilizer nitrogen on greenhouse gas emissions and plant-captured carbon under maize cropping in Zimbabwe. Plant Soil 343, 67–81 (2011).CAS 
Article 

Google Scholar 
Lal, R. Soil carbon sequestration impacts on global climate change and food security. Science 304, 1623–1627 (2004).ADS 
CAS 
Article 

Google Scholar 
Swanepoel, C. M., van der Laan, M., Weepener, H. L., du Preez, C. C. & Annandale, J. G. Review and meta-analysis of organic matter in cultivated soils in southern Africa. Nutr. Cycl. Agroecosyst. 104, 107–123 (2016).CAS 
Article 

Google Scholar 
Zingore, S., Manyame, C., Nyamugafata, P. & Giller, K. E. Long-term changes in organic matter of woodland soils cleared for arable cropping in Zimbabwe. Eur. J. Soil Sci. 56, 727–736 (2005).CAS 

Google Scholar 
Sakala, W. D., Cadisch, G. & Giller, K. E. Interactions between residues of maize and pigeonpea and mineral N fertilizers during decomposition and N mineralization. Soil Biol. Biochem. 32, 679–688 (2000).CAS 
Article 

Google Scholar 
Lal, R. & Stewart, B. A. (eds) Food security and soil quality (CRC Press, 2010).
Google Scholar 
Aparna, K., Pasha, M. A., Rao, D. L. N. & Krishnaraj, P. U. Organic amendments as ecosystem engineers: microbial, biochemical and genomic evidence of soil health improvement in a tropical arid zone field site. Ecol. Eng. 71, 268–277 (2014).Article 

Google Scholar 
Dhull, S., Goyal, S., Kapoor, K. & Mundra, M. Microbial biomass carbon and microbial activities of soils receiving chemical fertilizers and organic amendments. Arch. Agron. Soil Sci. 50, 641–647 (2004).CAS 
Article 

Google Scholar 
Zhong, W. et al. The effects of mineral fertilizer and organic manure on soil microbial community and diversity. Plant Soil 326, 511–522 (2010).CAS 
Article 

Google Scholar 
Janssen, B. H. Simple models and concepts as tools for the study of sustained soil productivity in long-term experiments. I. New soil organic matter and residual effect of P from fertilizers and farmyard manure in Kabete, Kenya. Plant Soil 339, 3–16 (2011).CAS 
Article 

Google Scholar 
Ge, G. et al. Soil biological activity and their seasonal variations in response to long-term application of organic and inorganic fertilizers. Plant Soil 326, 31 (2010).CAS 
Article 

Google Scholar 
Crowther, T. W. et al. The global soil community and its influence on biogeochemistry. Science 365, 6455 (2019).Article 

Google Scholar 
Grunwald, D., Kaiser, M. & Ludwig, B. Effect of biochar and organic fertilizers on C mineralization and macro-aggregate dynamics under different incubation temperatures. Soil Tillage Res. 164, 11–17 (2016).Article 

Google Scholar 
Schleuss, P.-M. et al. Stoichiometric controls of soil carbon and nitrogen cycling after long-term nitrogen and phosphorus addition in a mesic grassland in South Africa. Soil Biol. Biochem. 135, 294–303 (2019).CAS 
Article 

Google Scholar 
de Vries, F. T., Hoffland, E., van Eekeren, N., Brussaard, L. & Bloem, J. Fungal/bacterial ratios in grasslands with contrasting nitrogen management. Soil Biol. Biochem. 38, 2092–2103 (2006).Article 

Google Scholar 
Francioli, D. et al. Mineral vs. organic amendments: microbial community structure, activity and abundance of agriculturally relevant microbes are driven by long-term fertilization strategies. Front. Microbiol. 7, (2016).Fan, F. et al. Probing potential microbial coupling of carbon and nitrogen cycling during decomposition of maize residue by 13C-DNA-SIP. Soil Biol. Biochem. 70, 12–21 (2014).CAS 
Article 

Google Scholar 
Guo, Z., Han, J., Li, J., Xu, Y. & Wang, X. Effects of long-term fertilization on soil organic carbon mineralization and microbial community structure. PLoS ONE 14, e0211163 (2019).CAS 
Article 

Google Scholar 
Kihara, J. et al. Soil aggregation and total diversity of bacteria and fungi in various tillage systems of sub-humid and semi-arid Kenya. Appl. Soil Ecol. 58, 12–20 (2012).Article 

Google Scholar 
Sugihara, S., Funakawa, S., Kilasara, M. & Kosaki, T. Effects of land management on CO2 flux and soil C stock in two Tanzanian croplands with contrasting soil texture. Soil Biol. Biochem. 46, 1–9 (2012).CAS 
Article 

Google Scholar 
Ouédraogo, E., Brussaard, L. & Stroosnijder, L. Soil fauna and organic amendment interactions affect soil carbon and crop performance in semi-arid West Africa. Biol Fertil Soils 44, 343–351 (2007).Article 

Google Scholar 
Ouédraogo, E., Mando, A. & Brussaard, L. Soil macrofaunal-mediated organic resource disappearance in semi-arid West Africa. Appl. Soil Ecol. 27, 259–267 (2004).Article 

Google Scholar 
Powlson, D. S., Hirsch, P. R. & Brookes, P. C. The role of soil microorganisms in soil organic matter conservation in the tropics. Nutr. Cycl. Agroecosyst. 61, 41–51 (2001).Article 

Google Scholar 
Gentile, R., Vanlauwe, B., Kavoo, A., Chivenge, P. & Six, J. Residue quality and N fertilizer do not influence aggregate stabilization of C and N in two tropical soils with contrasting texture. Nutr. Cycl. Agroecosyst. 88, 121–131 (2010).CAS 
Article 

Google Scholar 
Amato, M. & Ladd, J. N. Decomposition of 14C-labelled glucose and legume material in soils: Properties influencing the accumulation of organic residue C and microbial biomass C. Soil Biol. Biochem. 24, 455–464 (1992).CAS 
Article 

Google Scholar 
Spain, A. V. Influence of environmental conditions and some soil chemical properties on the carbon and nitrogen contents of some tropical Australian rainforest soils. Soil Res. 28, 825–839 (1990).CAS 
Article 

Google Scholar 
Schimel, D. S., Coleman, D. C. & Horton, K. A. Soil organic matter dynamics in paired rangeland and cropland toposequences in North Dakota. Geoderma 36, 201–214 (1985).ADS 
Article 

Google Scholar 
Schimel, D., Stillwell, M. A. & Woodmansee, R. G. Biogeochemistry of C, N, and P in a soil catena of the shortgrass steppe. Ecology 66, 276–282 (1985).CAS 
Article 

Google Scholar 
Macharia, J. M. et al. Soil greenhouse gas fluxes from maize production under different soil fertility management practices in East Africa. J. Geophys. Res. Biogeosci. 125, e2019JG005427 (2020).Ortiz-Gonzalo, D. et al. Multi-scale measurements show limited soil greenhouse gas emissions in Kenyan smallholder coffee-dairy systems. Sci. Total Environ. 626, 328–339 (2018).ADS 
CAS 
Article 

Google Scholar 
De la Cruz-Barrón, M. et al. The bacterial community structure and dynamics of carbon and nitrogen when maize (Zea mays L.) and its neutral detergent fibre were added to soil from zimbabwe with contrasting management practices. Microb. Ecol. 73, 135–152 (2017).Article 

Google Scholar 
Wood, S. A. et al. Agricultural intensification and the functional capacity of soil microbes on smallholder African farms. J. Appl. Ecol. 52, 744–752 (2015).CAS 
Article 

Google Scholar 
Bardgett, R. D. & van der Putten, W. H. Belowground biodiversity and ecosystem functioning. Nature 515, 505–511 (2014).ADS 
CAS 
Article 

Google Scholar 
Wagg, C., Dudenhöffer, J.-H., Widmer, F. & van der Heijden, M. G. A. Linking diversity, synchrony and stability in soil microbial communities. Funct. Ecol. 32, 1280–1292 (2018).Article 

Google Scholar 
Nannipieri, P. et al. Microbial diversity and soil functions. Eur. J. Soil Sci. 54, 655–670 (2003).Article 

Google Scholar 
Liu, B. et al. Microbial metabolic efficiency and community stability in high and low fertility soils following wheat residue addition. Appl. Soil Ecol. 159, 103848 (2021).Article 

Google Scholar 
Hamamoto, T., Uchida, Y., von Rein, I. & Mukumbuta, I. Effects of short-term freezing on nitrous oxide emissions and enzyme activities in a grazed pasture soil after bovine-urine application. Sci. Total Environ. 740, 140006 (2020).ADS 
CAS 
Article 

Google Scholar 
Thomsen, I. K., Schjønning, P., Jensen, B., Kristensen, K. & Christensen, B. T. Turnover of organic matter in differently textured soils: II. Microbial activity as influenced by soil water regimes. Geoderma 89, 199–218 (1999).ADS 
Article 

Google Scholar 
Rughöft, S. et al. Community composition and abundance of bacterial, archaeal and nitrifying populations in savanna soils on contrasting bedrock material in Kruger National Park, South Africa. Front. Microbiol. 7, 1638 (2016).
Google Scholar 
Xue, L. et al. Long term effects of management practice intensification on soil microbial community structure and co-occurrence network in a non-timber plantation. For. Ecol. Manag. 459, 117805 (2020).Article 

Google Scholar 
Naether, A. et al. Environmental factors affect acidobacterial communities below the subgroup level in grassland and forest Soils. Appl. Environ. Microbiol. 78, 7398–7406 (2012).ADS 
CAS 
Article 

Google Scholar 
Fierer, N. et al. Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science 342, 621–624 (2013).ADS 
CAS 
Article 

Google Scholar 
Fierer, N., Allen, A. S., Schimel, J. P. & Holden, P. A. Controls on microbial CO2 production: a comparison of surface and subsurface soil horizons. Glob. Change Biol. 9, 1322–1332 (2003).ADS 
Article 

Google Scholar 
Bergmann, G. T. et al. The under-recognized dominance of Verrucomicrobia in soil bacterial communities. Soil Biol. Biochem. 43, 1450–1455 (2011).CAS 
Article 

Google Scholar 
Moreno-Espíndola, I. P. et al. The bacterial community structure and microbial activity in a traditional organic milpa farming system under different soil moisture conditions. Front. Microbiol. 9, 2737 (2018).Article 

Google Scholar 
Steven, B. et al. Resistance, resilience, and recovery of dryland soil bacterial communities across multiple disturbances. Front. Microbiol. 12, (2021).Elliott, E. T., Anderson, R. V., Coleman, D. C. & Cole, C. V. Habitable pore space and microbial trophic interactions. Oikos 35, 327–335 (1980).Article 

Google Scholar 
Bushby, H. V. A. & Marshall, K. C. Water status of rhizobia in relation to their susceptibility to desiccation and to their protection by montmorillonite. Microbiology 99, 19–27 (1977).
Google Scholar 
Bitton, G., Henis, Y. & Lahav, N. Influence of clay minerals, humic acid and bacterial capsular polysaccharide on the survival of Klebsiella aerogenes exposed to drying and heating in soils. Plant Soil 45, 65–74 (1976).Article 

Google Scholar 
Bastida, F. et al. Soil microbial diversity–biomass relationships are driven by soil carbon content across global biomes. ISME J. 15, 1–11 (2021).Article 

Google Scholar 
Hernandez, D. J., David, A. S., Menges, E. S., Searcy, C. A. & Afkhami, M. E. Environmental stress destabilizes microbial networks. ISME J. 15, 1–13 (2021).Article 

Google Scholar 
Jones, A. et al. (eds) Soil Atlas of Africa (European Commission. Publication Office of the European Union, 2013).
Google Scholar 
Mehlich, A. Mehlich 3 soil test extractant: a modification of Mehlich 2 extractant. Commun. Soil Sci. Plant Anal. 15, 1409–1416 (1984).CAS 
Article 

Google Scholar 
Hadas, A., Kautsky, L., Goek, M. & Erman Kara, E. Rates of decomposition of plant residues and available nitrogen in soil, related to residue composition through simulation of carbon and nitrogen turnover. Soil Biol. Biochem. 36, 255–266 (2004).CAS 
Article 

Google Scholar 
Sagova-Mareckova, M. et al. Innovative methods for soil DNA purification tested in soils with widely differing characteristics. Appl. Environ. Microbiol. 74, 2902–2907 (2008).ADS 
CAS 
Article 

Google Scholar 
Miller, D. N., Bryant, J. E., Madsen, E. L. & Ghiorse, W. C. Evaluation and optimization of DNA extraction and purification procedures for soil and sediment samples. Appl. Environ. Microbiol. 65, 4715–4724 (1999).ADS 
CAS 
Article 

Google Scholar 
Schroeder, J., Kammann, L., Helfrich, M., Tebbe, C. C. & Poeplau, C. Impact of common sample pre-treatments on key soil microbial properties. Soil Biol. Biochem. 160, 108321 (2021).CAS 
Article 

Google Scholar 
Wang, F. et al. Air-drying and long time preservation of soil do not significantly impact microbial community composition and structure. Soil Biol. Biochem. 157, 108238 (2021).CAS 
Article 

Google Scholar 
Sirois, S. H. & Buckley, D. H. Factors governing extracellular DNA degradation dynamics in soil. Environ. Microbiol. Rep. 11, 173–184 (2019).CAS 
Article 

Google Scholar 
Carini, P. et al. Relic DNA is abundant in soil and obscures estimates of soil microbial diversity. Nat. Microbiol. 2, 1–6 (2016).
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 
Mickan, B. S. et al. Soil disturbance and water stress interact to influence arbuscular mycorrhizal fungi, rhizosphere bacteria and potential for N and C cycling in an agricultural soil. Biol. Fertil. Soils 55, 53–66 (2019).CAS 
Article 

Google Scholar 
Lehman, C. L. & Tilman, D. Biodiversity, stability, and productivity in competitive communities. Am. Nat. 156, 534–552 (2000).Article 

Google Scholar  More

Caldeira, K. & Wickett, M. E. Oceanography: Anthropogenic carbon and ocean pH. Nature 425, 365–365 (2003).ADS 
CAS 
Article 

Google Scholar 
Sabine, C. L. et al. The oceanic sink for anthropogenic CO2. Science 305, 367–371 (2004).ADS 
CAS 
Article 

Google Scholar 
IPCC. In IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (eds. Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., Weyer, N. M.) (2019).Kroeker, K. J. et al. Impacts of ocean acidification on marine organisms: Quantifying sensitivities and interaction with warming. Glob. Change Biol. 19, 1884–1896 (2013).ADS 
Article 

Google Scholar 
Ries, J. B., Cohen, A. L. & McCorkle, D. C. Marine calcifiers exhibit mixed responses to CO2-induced ocean acidification. Geology 37, 1131–1134 (2014).ADS 
Article 

Google Scholar 
Ramajo, L. et al. Food supply confers calcifiers resistance to ocean acidification. Sci. Rep. 6, 19374 (2016).ADS 
CAS 
Article 

Google Scholar 
Vargas, C. A. et al. Species-specific responses to ocean acidification should account for local adaptation and adaptive plasticity. Nat. Ecol. Evol. 1, 0084 (2017).Article 

Google Scholar 
Kleypas, J. A. & Yates, K. K. Coral reefs and ocean acidification. Oceanography 22, 108–117 (2009).Article 

Google Scholar 
Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737–1742 (2007).ADS 
CAS 
Article 

Google Scholar 
Pandolfi, J. M., Connolly, S. R., Marshall, D. J. & Cohen, A. L. Projecting coral reef futures under global warming and ocean acidification. Science 333, 418–422 (2011).ADS 
CAS 
Article 

Google Scholar 
Cornwall, C. E. et al. Global declines in coral reef calcium carbonate production under ocean acidification and warming. Proc. Natl. Acad. Sci. 118, e2015265118 (2021).CAS 
Article 

Google Scholar 
Langer, M. R., Silk, M. T. & Lipps, J. H. Global ocean carbonate and carbon dioxide production: The role of reef foraminifera. J. Foraminifer. Res. 27, 271–277 (1997).Article 

Google Scholar 
Langer, M. R. Assessing the contribution of foraminiferan protists to global ocean carbonate production. J. Eukaryot. Microbiol. 55, 163–169 (2008).Article 

Google Scholar 
Hallock, P. Symbiont-bearing Foraminifera. In Modern Foraminifera (ed. Sen Gupta, B. K.) 123–139 (Springer Netherlands, 2003). https://doi.org/10.1007/0-306-48104-9_8.BouDagher-Fadel, M. K. Biology and evolutionary history of larger benthic foraminifera. In Evolution and Geological Significance of Larger Benthic Foraminifera 1–44 (UCL Press, 2018).Köhler-Rink, S. & Kühl, M. Microsensor studies of photosynthesis and respiration in larger symbiotic foraminifera. I The physico-chemical microenvironment of Marginopora vertebralis, Amphistegina lobifera and Amphisorus hemprichii. Mar. Biol. 137, 473–486 (2000).Article 

Google Scholar 
Glas, M. S., Fabricius, K. E., de Beer, D. & Uthicke, S. The O2, pH and Ca2+ microenvironment of benthic foraminifera in a high CO2 world. PLoS One 7, e50010 (2012).ADS 
CAS 
Article 

Google Scholar 
De Nooijer, L. J., Toyofuku, T. & Kitazato, H. Foraminifera promote calcification by elevating their intracellular pH. Proc. Natl. Acad. Sci. U. S. A. 106, 15374–15378 (2009).ADS 
Article 

Google Scholar 
Glas, M., Langer, G. & Keul, N. Calcification acidifies the microenvironment of a benthic foraminifer (Ammonia sp.). J. Exp. Mar. Biol. Ecol. 424–425, 53–58 (2012).Article 

Google Scholar 
Toyofuku, T. et al. Proton pumping accompanies calcification in foraminifera. Nat. Commun. 8, 14145 (2017).ADS 
CAS 
Article 

Google Scholar 
Hallock, P., Lidz, B. H., Cockey-Burkhard, E. M. & Donnelly, K. B. Foraminifera as bioindicators in coral reef assessment and monitoring: The FORAM Index. Environ. Monit. Assess. 81, 221–238 (2003).Article 

Google Scholar 
Uthicke, S., Thompson, A. & Schaffelke, B. Effectiveness of benthic foraminiferal and coral assemblages as water quality indicators on inshore reefs of the Great Barrier Reef, Australia. Coral Reefs 29, 209–225 (2010).ADS 
Article 

Google Scholar 
Prazeres, M., Martínez-Colón, M. & Hallock, P. Foraminifera as bioindicators of water quality: The FoRAM Index revisited. Environ. Pollut. 257, 113612 (2020).CAS 
Article 

Google Scholar 
Sen Gupta, B. K. Modern Foraminifera. (Springer Science & Business Media, 2003).Morse, J. W., Andersson, A. J. & Mackenzie, F. T. Initial responses of carbonate-rich shelf sediments to rising atmospheric pCO2 and “ocean acidification”: Role of high Mg-calcites. Geochim. Cosmochim. Acta 70, 5814–5830 (2006).ADS 
CAS 
Article 

Google Scholar 
Andersson, A. J., Mackenzie, F. T. & Bates, N. R. Life on the margin: Implications of ocean acidification on Mg-calcite, high latitude and cold-water marine calcifiers. Mar. Ecol. Prog. Ser. 373, 265–273 (2008).ADS 
CAS 
Article 

Google Scholar 
Van Dijk, I., De Nooijer, L. J. & Reichart, G.-J. Trends in element incorporation in hyaline and porcelaneous foraminifera as a function of pCO2. Biogeosciences 14, 497–510 (2017).ADS 
Article 

Google Scholar 
Not, C., Thibodeau, B. & Yokoyama, Y. Incorporation of Mg, Sr, Ba, U, and B in high-Mg calcite benthic foraminifers cultured under controlled pCO2. Geochem. Geophys. Geosyst. 19, 83–98 (2018).ADS 
CAS 
Article 

Google Scholar 
Levi, A., Müller, W. & Erez, J. Intrashell variability of trace elements in benthic foraminifera grown under high CO2 levels. Front. Earth Sci. 7, 247 (2019).ADS 
Article 

Google Scholar 
Doo, S. S., Fujita, K., Byrne, M. & Uthicke, S. Fate of calcifying tropical symbiont-bearing large benthic foraminifera: Living sands in a changing ocean. Biol. Bull. 226, 169–186 (2014).CAS 
Article 

Google Scholar 
Fujita, K. et al. Effects of ocean acidification on calcification of symbiont-bearing reef foraminifers. Biogeosciences 8, 2089–2098 (2011).ADS 
Article 

Google Scholar 
Hikami, M. et al. Contrasting calcification responses to ocean acidification between two reef foraminifers harboring different algal symbionts. Geophys. Res. Lett. 38, L19601 (2011).ADS 
Article 

Google Scholar 
Vogel, N. & Uthicke, S. Calcification and photobiology in symbiont-bearing benthic foraminifera and responses to a high CO2 environment. J. Exp. Mar. Biol. Ecol. 424–425, 15–24 (2012).Article 

Google Scholar 
McIntyre-Wressnig, A., Bernhard, J. M., McCorkle, D. C. & Hallock, P. Non-lethal effects of ocean acidification on the symbiont-bearing benthic foraminifer Amphistegina gibbosa. Mar. Ecol. Prog. Ser. 472, 45–60 (2013).ADS 
CAS 
Article 

Google Scholar 
Kuroyanagi, A., Kawahata, H., Suzuki, A., Fujita, K. & Irie, T. Impacts of ocean acidification on large benthic foraminifers: Results from laboratory experiments. Mar. Micropaleontol. 73, 190–195 (2009).ADS 
Article 

Google Scholar 
Knorr, P. O., Robbins, L. L., Harries, P. J., Hallock, P. & Wynn, J. Response of the Miliolid Archaias angulatus to simulated ocean acidification. J. Foraminifer. Res. 45, 109–127 (2015).Article 

Google Scholar 
Prazeres, M., Uthicke, S. & Pandolfi, J. M. Ocean acidification induces biochemical and morphological changes in the calcification process of large benthic foraminifera. Proc. R. Soc. B Biol. Sci. 282, 20142782 (2015).Article 

Google Scholar 
Reymond, C., Lloyd, A., Kline, D., Dove, S. & Pandolfi, J. Decline in growth of foraminifer Marginopora rossi under eutrophication and ocean acidification scenarios. Glob. Change Biol. 19, 291–302 (2013).ADS 
Article 

Google Scholar 
Sinutok, S., Hill, R., Doblin, M. A., Wuhrer, R. & Ralph, P. J. Warmer more acidic conditions cause decreased productivity and calcification in subtropical coral reef sediment-dwelling calcifiers. Limnol. Oceanogr. 56, 1200–1212 (2011).ADS 
CAS 
Article 

Google Scholar 
Sinutok, S., Hill, R., Kühl, M., Doblin, M. A. & Ralph, P. J. Ocean acidification and warming alter photosynthesis and calcification of the symbiont-bearing foraminifera Marginopora vertebralis. Mar. Biol. 161, 2143–2154 (2014).CAS 
Article 

Google Scholar 
Schmidt, C., Kucera, M. & Uthicke, S. Combined effects of warming and ocean acidification on coral reef Foraminifera Marginopora vertebralis and Heterostegina depressa. Coral Reefs 33, 805–818 (2014).ADS 
Article 

Google Scholar 
Engel, B., Hallock, P., Price, R. & Pichler, T. Shell dissolution in larger benthic foraminifers exposed to pH and temperature extremes: Results from an in situ experiment. J. Foraminifer. Res. 45, 190–203 (2015).Article 

Google Scholar 
Marques, J. A., de Barros Marangoni, L. F. & Bianchini, A. Combined effects of sea water acidification and copper exposure on the symbiont-bearing foraminifer Amphistegina gibbosa. Coral Reefs 36, 489–501 (2017).ADS 
Article 

Google Scholar 
Uthicke, S. & Fabricius, K. E. Productivity gains do not compensate for reduced calcification under near-future ocean acidification in the photosynthetic benthic foraminifer species Marginopora vertebralis. Glob. Change Biol. 18, 2781–2791 (2012).ADS 
Article 

Google Scholar 
Uthicke, S., Momigliano, P. & Fabricius, K. E. High risk of extinction of benthic foraminifera in this century due to ocean acidification. Sci. Rep. 3, 1–5 (2013).Article 

Google Scholar 
Pettit, L. R., Smart, C. W., Hart, M. B., Milazzo, M. & Hall-Spencer, J. M. Seaweed fails to prevent ocean acidification impact on foraminifera along a shallow-water CO2 gradient. Ecol. Evol. 5, 1784–1793 (2015).Article 

Google Scholar 
Martinez, A., Hernández-Terrones, L., Rebolledo-Vieyra, M. & Paytan, A. Impact of carbonate saturation on large Caribbean benthic foraminifera assemblages. Biogeosciences 15, 6819–6832 (2018).ADS 
CAS 
Article 

Google Scholar 
Pettit, L. R. et al. Benthic foraminifera show some resilience to ocean acidification in the northern Gulf of California, Mexico. Mar. Pollut. Bull. 73, 452–462 (2013).CAS 
Article 

Google Scholar 
Charrieau, L. M. et al. The effects of multiple stressors on the distribution of coastal benthic foraminifera: A case study from the Skagerrak-Baltic Sea region. Mar. Micropaleontol. 139, 42–56 (2018).ADS 
Article 

Google Scholar 
Narayan, G. R. et al. Response of large benthic foraminifera to climate and local changes: Implications for future carbonate production. Sedimentology https://doi.org/10.1111/sed.12858 (2021).Article 

Google Scholar 
Le Cadre, V., Debenay, J.-P. & Lesourd, M. Low pH effect on Ammonia beccarii test deformation: Implications for using test deformations as a pollution indicator. J. Foraminifer. Res. 33, 1–9 (2003).Article 

Google Scholar 
Kurtarkar, S. R., Nigam, R., Saraswat, R. & Linshy, V. N. Regeneration and abnormality in benthic foraminifer Rosalina leei: Implications in reconstructing past salinity changes. Riv. Ital. Paleontol. E Stratigr. 117(1), 189–196 (2011).
Google Scholar 
Haynert, K., Schönfeld, J., Polovodova-Asteman, I. & Thomsen, J. The benthic foraminiferal community in a naturally CO2-rich coastal habitat of the southwestern Baltic Sea. Biogeosciences 9, 4421–4440 (2012).ADS 
CAS 
Article 

Google Scholar 
Lee, J. J. ‘Living Sands’—Larger foraminifera and their endosymbiotic algae. Symbiosis 25, 71–100 (1997).CAS 

Google Scholar 
Parker, J. Ultrastructure of the test wall in modern porcelaneous foraminifera: Implications for the classification of the Miliolida. J. Foraminifer. Res. 47, 136–174 (2017).ADS 
Article 

Google Scholar 
Erez, J. The source of ions for biomineralization in foraminifera and their implications for paleoceanographic proxies. Rev. Mineral. Geochem. 54, 115–149 (2003).CAS 
Article 

Google Scholar 
Dissard, D., Nehrke, G., Reichart, G. J. & Bijma, J. Impact of seawater pCO2 on calcification and Mg/Ca and Sr/Ca ratios in benthic foraminifera calcite: results from culturing experiments with Ammonia tepida. Biogeosciences 7, 81–93 (2010).ADS 
CAS 
Article 

Google Scholar 
McIntyre-Wressnig, A., Bernhard, J. M., Wit, J. C. & Mccorkle, D. C. Ocean acidification not likely to affect the survival and fitness of two temperate benthic foraminiferal species: Results from culture experiments. J. Foraminifer. Res. 44, 341–351 (2014).Article 

Google Scholar 
Charrieau, L. M. et al. Decalcification and survival of benthic foraminifera under the combined impacts of varying pH and salinity. Mar. Environ. Res. 138, 36–45 (2018).CAS 
Article 

Google Scholar 
Saraswat, R. et al. Effect of salinity induced pH/alkalinity changes on benthic foraminifera: A laboratory culture experiment. Estuar. Coast. Shelf Sci. 153, 96–107 (2015).ADS 
CAS 
Article 

Google Scholar 
Buzas-Stephens, P. & Buzas, M. A. Population dynamics and dissolution of foraminifera in Nueces Bay, Texas. J. Foraminifer. Res. 35, 248–258 (2005).Article 

Google Scholar 
Cesbron, F. et al. Vertical distribution and respiration rates of benthic foraminifera: Contribution to aerobic remineralization in intertidal mudflats covered by Zostera noltei meadows. Estuar. Coast. Shelf Sci. 179, 23–38 (2016).CAS 
Article 

Google Scholar 
Lee, J. J. et al. Nutritional and related experiments on laboratory maintenance of three species of symbiont-bearing, large foraminifera. Mar. Biol. 109, 417–425 (1991).Article 

Google Scholar 
Yanko, V., Arnold, A. J. & Parker, W. C. Effects of marine pollution on benthic Foraminifera. In Modern Foraminifera 217–235 (Springer Netherlands, 1999). https://doi.org/10.1007/0-306-48104-9_13.Polovodova Asteman, I. & Schönfeld, J. Foraminiferal test abnormalities in the western Baltic Sea. J. Foraminifer. Res. 38, 318–336 (2008).Article 

Google Scholar 
Boltovskoy, E. & Wright, R. The test. In Recent Foraminifera (eds. Boltovskoy, E. & Wright, R.) 51–93 (Springer Netherlands, 1976). https://doi.org/10.1007/978-94-017-2860-7_3.Kaczmarek, K. et al. Boron incorporation in the foraminifer Amphistegina lessonii under a decoupled carbonate chemistry. Biogeosciences 12, 1753–1763 (2015).ADS 
Article 

Google Scholar 
Allen, K. et al. Controls on boron incorporation in cultured tests of the planktic foraminifer Orbulina universa. Earth Planet. Sci. Lett. 309, 291–301 (2011).ADS 
CAS 
Article 

Google Scholar 
Allen, K., Hönisch, B., Eggins, S. & Rosenthal, Y. Environmental controls on B/Ca in calcite tests of the tropical planktic foraminifer species Globigerinoides ruber and Globigerinoides sacculifer. Earth Planet. Sci. Lett. s351–352, 270–280 (2012).ADS 
Article 

Google Scholar 
Howes, E. L. et al. Decoupled carbonate chemistry controls on the incorporation of boron into Orbulina universa. Biogeosciences 14, 415–430 (2017).ADS 
CAS 
Article 

Google Scholar 
Lea, D. W. Trace elements in foraminiferal calcite. In Modern Foraminifera 259–277 (Springer Netherlands, 2003).Quigg, A. Micronutrients. In The Physiology of Microalgae (eds. Borowitzka, M. A., Beardall, J. & Raven, J. A.) 211–231 (Springer International Publishing, 2016). https://doi.org/10.1007/978-3-319-24945-2_10.Jennings, D. Culturing Benthic Foraminifera to Understand the Effects of Changing Seawater Chemistry and Temperature on Foraminiferal Shell Chemistry. (2015).Van Dijk, I., De Nooijer, L. J., Barras, C. & Reichart, G.-J. Mn Incorporation in large benthic foraminifera: Differences between species and the impact of pCO2. Front. Earth Sci. https://doi.org/10.3389/feart.2020.567701 (2020).Article 

Google Scholar 
Raitzsch, M., Dueñas-Bohórquez, A., Reichart, G.-J., de Nooijer, L. J. & Bickert, T. Incorporation of Mg and Sr in calcite of cultured benthic foraminifera: Impact of calcium concentration and associated calcite saturation state. Biogeosciences 7, 869–881 (2010).ADS 
CAS 
Article 

Google Scholar 
Holzmann, M., Hohenegger, J., Hallock, P., Piller, W. E. & Pawlowski, J. Molecular phylogeny of large miliolid foraminifera (Soritacea Ehrenberg 1839). Mar. Micropaleontol. 43, 57–74 (2001).ADS 
Article 

Google Scholar 
Hottinger, L., Halicz, E. & Reiss, Z. Recent Foraminiferida from the Gulf of Aqaba, Red Sea. vol. 33 (Slovenska Akademija Znanosti in Umetnosti, Dela Opera, Classis IV: Historia Naturalis, 1993).Langer, M., Makled, W., Pietsch, S. & Weinmann, A. Asynchronous calcification in juvenile megalospheres: An ontogenetic window into the life cycle and polymorphism of Peneroplis. J. Foraminifer. Res. 39, 8–14 (2009).Article 

Google Scholar 
Dissard, D., Nehrke, G., Reichart, G.-J. & Bijma, J. The impact of salinity on the Mg/Ca and Sr/Ca ratio in the benthic foraminifera Ammonia tepida: Results from culture experiments. Geochim. Chosmocimica Acta 74, 928–940 (2010).ADS 
CAS 
Article 

Google Scholar 
Schiebel, R. & Hemleben, C. Planktic Foraminifers in the Modern Ocean. (Springer, 2017).Culberson, C. H., Pytkowicz, R. M. & Hawley, J. E. Seawater alkalinity determination by the pH method. J. Mar. Res. 28, 15–21 (1970).CAS 

Google Scholar 
Dickson, A. G. & Goyet, C. DOE. Handbook of Methods for the Analysis of the Various Parameters of the Carbon Dioxide System in Sea Water, Version 2. (eds., ORNL/CDIAC-74., 1994).Suga, H., Sakai, S., Toyofuku, T. & Ohkouchi, N. A simplified method for determination of total alkalinity in seawater based on the small sample one-point titration method. JAMSTEC Rep. Res. Dev. 17, 23–33 (2013).Article 

Google Scholar 
Robbins, L. L., Hansen, M. E., Kleypas, J. A. & Meylan, S. C. CO2calc: A User-Friendly Seawater Carbon Calculator for Windows, Mac OS X, and iOS (iPhone): U.S. Geological Survey Open-File Report 2010–1280. 17 (2010).Lueker, T. J., Dickson, A. G. & Keeling, C. D. Ocean pCO2 calculated from dissolved inorganic carbon, alkalinity, and equations for K1 and K2: Validation based on laboratory measurements of CO2 in gas and seawater at equilibrium. Mar. Chem. 70, 105–119 (2000).CAS 
Article 

Google Scholar 
Uppström, L. R. The boron/chlorinity ratio of deep-sea water from the Pacific Ocean. Deep Sea Res. Oceanogr. Abstr. 21, 161–162 (1974).ADS 
Article 

Google Scholar 
Orr, J. C., Epitalon, J.-M. & Gattuso, J.-P. Comparison of ten packages that compute ocean carbonate chemistry. Biogeosciences 12, 1483–1510 (2015).ADS 
Article 

Google Scholar 
Fontanier, C. et al. Living (stained) deep-sea foraminifera from the Sea of Marmara: A preliminary study. Deep Sea Res. Part II Top. Stud. Oceanogr. 153, 61 (2018).ADS 
CAS 
Article 

Google Scholar 
Gaffey, S. & Bronnimann, C. Effects of bleaching on organic and mineral phases in biogenic carbonates. J. Sediment. Res. 63, 752–754 (1993).ADS 
Article 

Google Scholar 
Jochum, K. P. et al. Determination of reference values for NIST SRM 610–617 glasses following ISO guidelines. Geostand. Geoanal. Res. 35, 397–429 (2011).CAS 
Article 

Google Scholar  More

Franklin, J. F., Shugart, H. H. & Harmon, M. E. Tree death as an ecological process. Bioscience 37, 550–556 (1987).Article 

Google Scholar 
Harmon, M. E. et al. Ecology of coarse woody debris in temperate ecosystems. In Advances in Ecological Research (eds MacFadyen, A. & Ford, E. D.) 133–302 (Academic Press, 1986).Chapter 

Google Scholar 
Harmon, M. E. & Bell, D. M. Mortality in forested ecosystems: suggested conceptual advances. Forests 11, 572 (2020).Article 

Google Scholar 
van Mantgem, P. J. et al. Widespread increase of tree mortality rates in the Western United States. Science 323, 521–524 (2009).ADS 
Article 

Google Scholar 
Kinnucan, H. W. Timber price dynamics after a natural disaster: Hurricane Hugo revisited. J. For. Econ. 25, 115–129 (2016).
Google Scholar 
Marsinko, A. P., Straka, T. J. & Haight, R. G. The effect of a large-scale natural disaster on regional timber supply. J. World For. Resour. Manag. 8, 75–85 (1997).
Google Scholar 
Lugo, A. E. Visible and invisible effects of hurricanes on forest ecosystems: an international review. Austral Ecol. 33, 368–398 (2008).Article 

Google Scholar 
Shifley, S. R., Brookshire, B. L., Larsen, D. R. & Herbeck, L. A. Snags and down wood in missouri old-growth and mature second-growth forests. North. J. Appl. For. 14, 165–172 (1997).Article 

Google Scholar 
Bobiec, A. Living stands and dead wood in the Białowieża forest: suggestions for restoration management. For. Ecol. Manag. 165, 125–140 (2002).Article 

Google Scholar 
Spetich, M. A., Shifley, S. R. & Parker, G. R. Regional distribution and dynamics of coarse woody debris in midwestern old-growth forests. For. Sci. 45, 302–313 (1999).
Google Scholar 
Rimle, A., Heiri, C. & Bugmann, H. Deadwood in Norway spruce dominated mountain forest reserves is characterized by large dimensions and advanced decomposition stages. For. Ecol. Manag. 404, 174–183 (2017).Article 

Google Scholar 
Ruokolainen, A., Shorohova, E., Penttilä, R., Kotkova, V. & Kushnevskaya, H. A continuum of dead wood with various habitat elements maintains the diversity of wood-inhabiting fungi in an old-growth boreal forest. Eur. J. For. Res. 137, 707–718 (2018).Article 

Google Scholar 
Ranius, T. & Kindvall, O. Modelling the amount of coarse woody debris produced by the new biodiversity-oriented silvicultural practices in Sweden. Biol. Conserv. 119, 51–59 (2004).Article 

Google Scholar 
Bouget, C. & Duelli, P. The effects of windthrow on forest insect communities: a literature review. Biol. Conserv. 118, 281–299 (2004).Article 

Google Scholar 
Svensson, M. et al. The relative importance of stand and dead wood types for wood-dependent lichens in managed boreal forests. Fungal Ecol. 20, 166–174 (2016).Article 

Google Scholar 
Bahuguna, D., Mitchell, S. J. & Nishio, G. R. Post-harvest windthrow and recruitment of large woody debris in riparian buffers on Vancouver Island. Eur. J. For. Res. 131, 249–260 (2012).Article 

Google Scholar 
Fortin, M. & DeBlois, J. Modeling tree recruitment with zero-inflated models: the example of hardwood stands in southern Quebec Canada. For. Sci. 53, 529–539 (2007).
Google Scholar 
Herrero, C., Pando, V. & Bravo, F. Modelling coarse woody debris in Pinus spp. Plantations. A case study in Northern Spain. Ann. For. Sci. 67, 708–708 (2010).Article 

Google Scholar 
Arekhi, S. Modeling spatial pattern of deforestation using GIS and logistic regression: a case study of northern Ilam forests, Ilam province Iran. Afr. J. Biotechnol. 10, 16236–16249 (2011).
Google Scholar 
Kumar, R., Nandy, S., Agarwal, R. & Kushwaha, S. P. S. Forest cover dynamics analysis and prediction modeling using logistic regression model. Ecol. Indic. 45, 444–455 (2014).Article 

Google Scholar 
Podur, J. J., Martell, D. L. & Stanford, D. A compound poisson model for the annual area burned by forest fires in the province of Ontario. Environmetrics 21, 457–469 (2010).MathSciNet 

Google Scholar 
Tobler, W. R. A computer movie simulating urban growth in the Detroit Region. Econ. Geogr. 46, 234–240 (1970).Article 

Google Scholar 
Griffith, D. & Chun, Y. Spatial autocorrelation and spatial filtering. In Handbook of regional science 1477–1507 (eds Fischer, M. M. & Nijkamp, P.) (Springer, 2014). https://doi.org/10.1007/978-3-642-23430-9_72.Chapter 

Google Scholar 
Li, T. & Meng, Q. Forest dynamics in relation to meteorology and soil in the Gulf Coast of Mexico. Sci. Total Environ. 702, 134913 (2019).ADS 
Article 

Google Scholar 
Brunsdon, C., Fotheringham, A. S. & Charlton, M. E. Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr. Anal. 28, 281–298 (1996).Article 

Google Scholar 
Fotheringham, A. S., Charlton, M. E. & Brunsdon, C. Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environ. Plan. A 30, 1905–1927 (1998).Article 

Google Scholar 
Yang, C., Fu, M., Feng, D., Sun, Y. & Zhai, G. Spatiotemporal changes in vegetation cover and its influencing factors in the loess Plateau of China based on the geographically weighted regression model. Forests 12, 673 (2021).Article 

Google Scholar 
Monjarás-Vega, N. et al. Predicting forest fire kernel density at multiple scales with geographically weighted regression in Mexico. Sci. Total Environ. 718, 137313 (2020).ADS 
Article 

Google Scholar 
Peng, X., Wu, H. & Ma, L. A study on geographically weighted spatial autoregression models with spatial autoregressive disturbances. Commun. Stat. Theor. Methods 49, 5235–5251 (2020).MathSciNet 
Article 

Google Scholar 
Harris, P. & Brunsdon, C. Exploring spatial variation and spatial relationships in a freshwater acidification critical load data set for Great Britain using geographically weighted summary statistics. Comput. Geosci. 36, 54–70 (2010).ADS 
Article 

Google Scholar 
Li, J., Jin, M. & Li, H. Exploring spatial influence of remotely sensed PM2.5 concentration using a developed deep convolutional neural network model. Int. J. Environ. Res. Public Health 16, 454 (2019).Article 

Google Scholar 
Peng, C., Wang, M. & Chen, W. Spatial analysis of PAHs in soils along an urban-suburban-rural gradient: scale effect, distribution patterns, diffusion and influencing factors. Sci. Rep. 6, 37185 (2016).ADS 
CAS 
Article 

Google Scholar 
Wu, S. et al. Geographically and temporally neural network weighted regression for modeling spatiotemporal non-stationary relationships. Int. J. Geogr. Inf. Sci. 35, 582–608 (2021).Article 

Google Scholar 
Wu, S. et al. Modeling spatially anisotropic nonstationary processes in coastal environments based on a directional geographically neural network weighted regression. Sci. Total Environ. 709, 136097 (2020).ADS 
CAS 
Article 

Google Scholar 
Du, Z., Wang, Z., Wu, S., Zhang, F. & Liu, R. Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity. Int. J. Geogr. Inf. Sci. 34, 1353–1377 (2020).Article 

Google Scholar 
Sun, Y., Ao, Z., Jia, W., Chen, Y. & Xu, K. A geographically weighted deep neural network model for research on the spatial distribution of the down dead wood volume in liangshui national nature reserve (China). IForest 14, 353–361 (2021).Article 

Google Scholar 
Wilkinson, L. Tests of significance in stepwise regression. Psychol. Bull. 86, 168–174 (1979).Article 

Google Scholar 
Henderson, D. A. & Denison, D. R. Stepwise regression in social and psychological research. Psychol. Rep. 64, 251–257 (1989).Article 

Google Scholar 
Carl, G. & Kühn, I. Analyzing spatial autocorrelation in species distributions using Gaussian and logit models. Ecol. Model. 207, 159–170 (2007).Article 

Google Scholar 
Wu, W. & Zhang, L. Comparison of spatial and non-spatial logistic regression models for modeling the occurrence of cloud cover in north-eastern Puerto Rico. Appl. Geogr. 37, 52–62 (2013).Article 

Google Scholar 
Ozdemir, A. Using a binary logistic regression method and GIS for evaluating and mapping the groundwater spring potential in the Sultan Mountains (Aksehir, Turkey). J. Hydrol. 405, 123–136 (2011).ADS 
Article 

Google Scholar 
Pineda Jaimes, N. B., Bosque Sendra, J., Gómez Delgado, M. & Franco, Plata R. Exploring the driving forces behind deforestation in the state of Mexico (Mexico) using geographically weighted regression. Appl. Geogr. 30, 576–591 (2010).Article 

Google Scholar 
Tutmez, B., Kaymak, U., Erhan Tercan, A. & Lloyd, C. D. Evaluating geo-environmental variables using a clustering based areal model. Comput. Geosci. 43, 34–41 (2012).ADS 
Article 

Google Scholar 
Li, X., Wu, P., Guo, F.-T. & Hu, X. A geographically weighted regression approach to detect divergent changes in the vegetation activity along the elevation gradients over the last 20 years. For. Ecol. Manag. 490, 119089 (2021).Article 

Google Scholar 
Que, X., Ma, C., Ma, X. & Chen, Q. Parallel computing for fast spatiotemporal weighted regression. Comput. Geosci. 150, 104723 (2021).Article 

Google Scholar 
Wu, L. et al. Spatial analysis of severe fever with thrombocytopenia syndrome virus in China using a geographically weighted logistic regression model. Int. J. Environ. Res. Public Health 13, 1125 (2016).Article 

Google Scholar 
Liu, Y. et al. Geographical variations in maternal lifestyles during pregnancy associated with congenital heart defects among live births in Shaanxi province Northwestern China. Sci. Rep. 10, 12958 (2020).ADS 
CAS 
Article 

Google Scholar 
Saefuddin, A., Saepudin, D. & Kusumaningrum, D. Geographically weighted poisson regression (GWPR) for analyzing the malnutrition data in java-Indonesia (European Regional Science Association (ERSA), 2013).
Google Scholar 
Lecun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).ADS 
CAS 
Article 

Google Scholar 
Ketkar, N. Introduction to Keras. In Deep learning with python: a hands-on introduction (ed. Ketkar, N.) 97–111 (Apress, 2017). https://doi.org/10.1007/978-1-4842-2766-4_7.Chapter 

Google Scholar 
Tsomokos, D. I., Ashhab, S. & Nori, F. Fully connected network of superconducting qubits in a cavity. New J. Phys. 10, 113020 (2008).ADS 
Article 

Google Scholar 
Hu, T. et al. Study on the estimation of forest volume based on multi-source data. Sensors 21, 7796 (2021).ADS 
Article 

Google Scholar 
Chen, L., Ren, C., Zhang, B., Wang, Z. & Xi, Y. Estimation of forest above-ground biomass by geographically weighted regression and machine learning with sentinel imagery. Forests 9, 582 (2018).Article 

Google Scholar 
Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I. & Salakhutdinov, R. Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15, 1929–1958 (2014).MathSciNet 
MATH 

Google Scholar 
Mastromichalakis, S. ALReLU: A different approach on Leaky ReLU activation function to improve neural networks performance. arXiv:2012.07564 [Cs] arXiv:2012.07564 (2021).Chen, C., Li, Y., Yan, C., Dai, H. & Liu, G. A robust algorithm of multiquadric method based on an improved huber loss function for interpolating remote-sensing-derived elevation data sets. Remote Sens. 7, 3347–3371 (2015).ADS 
Article 

Google Scholar 
de Jong, P., Sprenger, C. & Veen, F. On extreme values of Moran’s I and Geary’s c ( spatial autocorrelation). Geogr. Anal. 16, 17–24 (1984).Article 

Google Scholar 
Fu, W. J., Jiang, P. K., Zhou, G. M. & Zhao, K. L. Using Moran’s i and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China. Biogeosciences 11, 2401–2409 (2014).ADS 
Article 

Google Scholar 
Parizi, E., Hosseini, S. M., Ataie-Ashtiani, B. & Simmons, C. T. Normalized difference vegetation index as the dominant predicting factor of groundwater recharge in phreatic aquifers: case studies across Iran. Sci. Rep. 10, 17473 (2020).ADS 
CAS 
Article 

Google Scholar 
Moore, J. R. Differences in maximum resistive bending moments of Pinus radiata trees grown on a range of soil types. For. Ecol. Manag. 135, 63–71 (2000).Article 

Google Scholar 
Lanquaye-Opoku, N. & Mitchell, S. J. Portability of stand-level empirical windthrow risk models. For. Ecol. Manag. 216, 134–148 (2005).Article 

Google Scholar 
Li, X. et al. Response of species and stand types to snow/wind damage in a temperate secondary forest Northeast China. J. For. Res. 29, 395–404 (2018).CAS 
Article 

Google Scholar 
Zhen, Z. et al. Geographically local modeling of occurrence, count, and volume of downwood in Northeast China. Appl. Geogr. 37, 114–126 (2013).Article 

Google Scholar 
Vozmishcheva, A. et al. Strong disturbance impact of tropical cyclone Lionrock (2016) on Korean pine-broadleaved forest in the Middle Sikhote-Alin Mountain range Russian Far East. Forests 10, 15 (2019).Article 

Google Scholar 
Bivand, R., Müller, W. G. & Reder, M. Power calculations for global and local Moran’s I. Comput. Stat. Data Anal. 53, 2859–2872 (2009).MathSciNet 
MATH 
Article 

Google Scholar 
Yuan, J. et al. Dynamics of coarse woody debris characteristics in the Qinling mountain forests in China. Forests 8, 403–403 (2017).MathSciNet 
Article 

Google Scholar 
Næsset, E. Estimating timber volume of forest stands using airborne laser scanner data. Remote Sens. Environ. 61, 246–253 (1997).ADS 
Article 

Google Scholar 
Næsset, E. Determination of mean tree height of forest stands by digital photogrammetry. Scand. J. For. Res. 17, 446–459 (2002).ADS 
Article 

Google Scholar 
Rich, R. L., Frelich, L. E. & Reich, P. B. Wind-throw mortality in the southern boreal forest: effects of species, diameter and stand age. J. Ecol. 95, 1261–1273 (2007).Article 

Google Scholar 
Odhiambo, B. O., Kenduiywo, B. K. & Were, K. Spatial prediction and mapping of soil pH across a tropical afro-montane landscape. Appl. Geogr. 114, 102129 (2020).Article 

Google Scholar  More

Rothstein, S. I. A model system for coevolution: Avian brood parasitism. Annu. Rev. Ecol. Syst. 21, 481–508 (1990).Article 

Google Scholar 
Feeney, W. E. et al. Brood parasitism and the evolution of cooperative breeding in birds. Science 342, 1506–1508 (2013).ADS 
CAS 
Article 

Google Scholar 
Brooke, M. de L. & Davies, N. B. Egg mimicry by cuckoos Cuculus canorus in relation to discrimination by hosts. Nature 335, 630–632 (1988).ADS 
Article 

Google Scholar 
Medina, I. & Langmore, N. E. The costs of avian brood parasitism explain variation in egg rejection behaviour in hosts. Biol. Let. 11, 20150296 (2015).Article 

Google Scholar 
Langmore, N. E., Hunt, S. & Kilner, R. M. Escalation of a coevolutionary arms race through host rejection of brood parasitic young. Nature 422, 157–160 (2003).ADS 
CAS 
Article 

Google Scholar 
Grim, T. Experimental evidence for chick discrimination without recognition in a brood parasite host. Proc. R. Soc. B: Biol. Sci. 274, 373–381 (2007).Article 

Google Scholar 
Sato, N. J., Tokue, K., Noske, R. A., Mikami, O. K. & Ueda, K. Evicting cuckoo nestlings from the nest: A new anti-parasitism behaviour. Biol. Let. 6, 67–69. https://doi.org/10.1098/rsbl.2009.0540 (2010).Article 

Google Scholar 
Davies, N. & Brooke, M. de L. Cuckoos versus reed warblers: Adaptations and counteradaptations. Anim. Behav. 36, 262–284 (1988).Article 

Google Scholar 
Langmore, N. E. et al. Visual mimicry of host nestlings by cuckoos. Proc. R. Soc. B: Biol. Sci. 278, 2455–2463 (2011).Article 

Google Scholar 
Noh, H.-J., Gloag, R. & Langmore, N. E. True recognition of nestlings by hosts selects for mimetic cuckoo chicks. Proc. R. Soc. B: Bio. Sci. 285, 20180726 (2018).Article 

Google Scholar 
Spottiswoode, C. N. & Stevens, M. Host-parasite arms races and rapid changes in bird egg appearance. Am. Nat. 179, 633–648. https://doi.org/10.1086/665031 (2012).Article 

Google Scholar 
Taylor, C. J. & Langmore, N. E. How do brood-parasitic cuckoos reconcile conflicting environmental and host selection pressures on egg size investment?. Anim. Behav. 168, 89–96. https://doi.org/10.1016/j.anbehav.2020.08.003 (2020).Article 

Google Scholar 
Langmore, N. E., Maurer, G., Adcock, G. J. & Kilner, R. M. Socially acquired host-specific mimicry and the evolution of host races in Horsfield’s bronze-cuckoo Chalcites basalis. Evolution 62, 1689–1699 (2008).Article 

Google Scholar 
Noh, H. J., Jacomb, F., Gloag, R. & Langmore, N. E. Frontline defences against cuckoo parasitism in the large-billed gerygones. Anim. Behav. 174, 51–61. https://doi.org/10.1016/j.anbehav.2021.01.021 (2021).Article 

Google Scholar 
Langmore, N. E. & Kilner, R. M. Why do Horsfield’s bronze-cuckoo Chalcites basalis eggs mimic those of their hosts?. Behav. Ecol. Sociobiol. 63, 1127–1131. https://doi.org/10.1007/s00265-009-0759-9 (2009).Article 

Google Scholar 
Spottiswoode, C. N. & Stevens, M. How to evade a coevolving brood parasite: Egg discrimination versus egg variability as host defences. Proc. R. Soc. B: Biol. Sci. 278, 3566–3573. https://doi.org/10.1098/rspb.2011.0401 (2011).Article 

Google Scholar 
Yang, C., Wang, L., Liang, W. & Møller, A. P. Egg recognition as antiparasitism defence in hosts does not select for laying of matching eggs in parasitic cuckoos. Anim. Behav. 122, 177–181. https://doi.org/10.1016/j.anbehav.2016.10.018 (2016).Article 

Google Scholar 
Stevens, M. Bird brood parasitism. Curr. Biol. 23, R909–R913. https://doi.org/10.1016/j.cub.2013.08.025 (2013).MathSciNet 
CAS 
Article 

Google Scholar 
Feeney, W. E., Troscianko, J., Langmore, N. E. & Spottiswoode, C. N. Evidence for aggressive mimicry in an adult brood parasitic bird, and generalized defences in its host. Proc. R. Soc. B: Biol. Sci. 282, 20150795 (2015).Article 

Google Scholar 
Davies, N. B. & Welbergen, J. A. Cuckoo–hawk mimicry? An experimental test. Proc. R. Soc. B: Biol. Sci. 275, 1817–1822 (2008).CAS 
Article 

Google Scholar 
Brooker, L. C. & Brooker, M. G. Why are cuckoos host specific?. Oikos 57, 301–309. https://doi.org/10.2307/3565958 (1990).Article 

Google Scholar 
Langmore, N. E., Stevens, M., Maurer, G. & Kilner, R. M. Are dark cuckoo eggs cryptic in host nests?. Anim. Behav. 78, 461–468 (2009).Article 

Google Scholar 
Lack, D. L. Ecological Adaptations for Breeding in Birds (Methuen & Co., Ltd., 1968).
Google Scholar 
Spaw, C. D. & Rohwer, S. A comparative study of eggshell thickness in cowbirds and other passerines. The Condor 89, 307–318. https://doi.org/10.2307/1368483 (1987).Article 

Google Scholar 
Igic, B. et al. Alternative mechanisms of increased eggshell hardness of avian brood parasites relative to host species. J. R. Soc. Interface 8, 1654–1664. https://doi.org/10.1098/rsif.2011.0207 (2011).Article 

Google Scholar 
Brooker, M. G. & Brooker, L. C. Eggshell strength in cuckoos and cowbirds. Ibis 133, 406–413. https://doi.org/10.1111/j.1474-919X.1991.tb04589.x (1991).Article 

Google Scholar 
Maurer, G. et al. First light for avian embryos: eggshell thickness and pigmentation mediate variation in development and UV exposure in wild bird eggs. Funct. Ecol. 29, 209–218 (2015).Article 

Google Scholar 
Amos, A. & Rahn, H. Pores in avian eggshells: Gas conductance, gas exchange and embryonic growth rate. Respir. Physiol. 61, 1–20 (1985).Article 

Google Scholar 
Ar, A., Rahn, H. & Paganelli, C. V. The avian egg: Mass and strength. Condor 81, 331–337 (1979).Article 

Google Scholar 
Rahn, H. & Ar, A. Gas-exchange of the avian egg: Time, structure, and function. Am. Zool. 20, 477–484 (1980).Article 

Google Scholar 
Swynnerton, C. Rejections by birds of eggs unlike their own: With remarks on some of the cuckoo problems. Ibis 60, 127–154 (1918).Article 

Google Scholar 
López, A. V., Fiorini, V. D., Ellison, K. & Peer, B. D. Thick eggshells of brood parasitic cowbirds protect their eggs and damage host eggs during laying. Behav. Ecol. 29, 965–973 (2018).Article 

Google Scholar 
Wyllie, I. The Cuckoo (Batsford, 1981).
Google Scholar 
Yang, C. et al. Keeping eggs warm: Thermal and developmental advantages for parasitic cuckoos of laying unusually thick-shelled eggs. Sci. Nat. 105, 10 (2018).Article 

Google Scholar 
Davies, N. B. Cuckoos Cowbirds and other Cheats (T & A D Poyser, 2000).
Google Scholar 
Spottiswoode, C. N. The evolution of host-specific variation in cuckoo eggshell strength. J. Evol. Biol. 23, 1792–1799. https://doi.org/10.1111/j.1420-9101.2010.02010.x (2010).CAS 
Article 

Google Scholar 
Langmore, N. E. et al. The evolution of egg rejection by cuckoo hosts in Australia and Europe. Behav. Ecol. 16, 686–692. https://doi.org/10.1093/beheco/ari041 (2005).Article 

Google Scholar 
Rohwer, S., Spaw, C. D. & Røskaft, E. Costs to northern orioles of puncture-ejecting parasitic cowbird eggs from their nests. The Auk 106, 734–738 (1989).
Google Scholar 
Brooker, M. G., Brooker, L. C. & Rowley, I. Egg deposition by the bronze-cuckoos Chrysococcyx basalis and Chrysococcyx lucidus. Emu 88, 107–109. https://doi.org/10.1071/Mu9880107 (1988).Article 

Google Scholar 
McClelland, S. C. et al. Embryo movement is more frequent in avian brood parasites than birds with parental reproductive strategies. Proc. R. Soc B-Biol. Sci. https://doi.org/10.1098/rspb.2021.1137 (2021).Article 

Google Scholar 
Gosler, A. G. & Wilkin, T. A. Eggshell speckling in a passerine bird reveals chronic long-term decline in soil calcium. Bird Study 64, 195–204. https://doi.org/10.1080/00063657.2017.1314448 (2017).Article 

Google Scholar 
Lundholm, C. E. Inhibition of prostaglandin synthesis in eggshell gland mucosa as a mechanism for P, P’-DDE-induced eggshell thinning in birds: A comparison of ducks and domestic-fowls. Comp. Biochem. Phys. C 106, 389–394. https://doi.org/10.1016/0742-8413(93)90151-A (1993).Article 

Google Scholar 
Bitman, J., Cecil, H. C. & Fries, G. F. DDT-Induced inhibition of avian shell gland carbonic anhydrase: A mechanism for thin eggshells. Science 168, 594–596. https://doi.org/10.1126/science.168.3931.594 (1970).ADS 
CAS 
Article 

Google Scholar 
Ratcliffe, D. A. Changes attributable to pesticides in egg breakage frequency and eggshell thickness in some British birds. J. Appl. Ecol. 7, 67-+. https://doi.org/10.2307/2401613 (1970).Article 

Google Scholar 
Bouwman, H., Govender, D., Underhill, L. & Polder, A. Chlorinated, brominated and fluorinated organic pollutants in African Penguin eggs: 30 years since the previous assessment. Chemosphere 126, 1–10. https://doi.org/10.1016/j.chemosphere.2014.12.071 (2015).ADS 
CAS 
Article 

Google Scholar 
Bleu, J., Agostini, S., Angelier, F. & Biard, C. Experimental increase in temperature affects eggshell thickness, and not egg mass, eggshell spottiness or egg composition in the great tit (Parus major). Gen. Comp. Endocr. 275, 73–81. https://doi.org/10.1016/j.ygcen.2019.02.004 (2019).CAS 
Article 

Google Scholar 
Picman, J. & Pribil, S. Is greater eggshell density an alternative mechanism by which parasitic cuckoos increase the strength of their eggs?. J. Ornithol. 138, 531–541. https://doi.org/10.1007/bf01651384 (1997).Article 

Google Scholar 
Lopez, A. V. et al. How to build a puncture- and breakage-resistant eggshell? Mechanical and structural analyses of avian brood parasites and their hosts. J. Exp. Biol. 224, jeb243016. https://doi.org/10.1242/jeb.243016 (2021).Article 

Google Scholar 
Soler, M., Rodriguez-Navarro, A. B., Perez-Contreras, T., Garcia-Ruiz, J. M. & Soler, J. J. Great spotted cuckoo eggshell microstructure characteristics can make eggs stronger. J. Avian Biol. 50, e02252. https://doi.org/10.1111/jav.02252 (2019).Article 

Google Scholar 
D’Alba, L. et al. Evolution of eggshell structure in relation to nesting ecology in non-avian reptiles. J. Morphol. 282, 1066–1079. https://doi.org/10.1002/jmor.21347 (2021).CAS 
Article 

Google Scholar 
Legendre, L. J. & Clarke, J. A. Shifts in eggshell thickness are related to changes in locomotor ecology in dinosaurs. Evolution 75, 1415–1430. https://doi.org/10.1111/evo.14245 (2021).Article 

Google Scholar 
Le Roy, N., Stapane, L., Gautron, J. & Hincke, M. T. Evolution of the avian eggshell biomineralization protein toolkit: New insights from multi-omics. Front. Genet. 12, 672433. https://doi.org/10.3389/fgene.2021.672433 (2021).CAS 
Article 

Google Scholar 
Medina, I. & Langmore, N. E. Batten down the thatches: Front-line defences in an apparently defenceless cuckoo host. Anim. Behav. 112, 195–201. https://doi.org/10.1016/j.anbehav.2015.12.006 (2016).Article 

Google Scholar 
Starling, M., Heinsohn, R., Cockburn, A. & Langmore, N. E. Cryptic gentes revealed in pallid cuckoos Cuculus pallidus using reflectance spectrophotometry. Proc. R. Soc. Lond. B 273, 1929–1934 (2006).CAS 

Google Scholar 
Abernathy, V. E., Troscianko, J. & Langmore, N. E. Egg mimicry by the Pacific koel: Mimicry of one host facilitates exploitation of other hosts with similar egg types. J. Avian Biol. 48, 1414–1424. https://doi.org/10.1111/jav.01530 (2017).Article 

Google Scholar 
Green, R. E. An evaluation of three indices of eggshell thickness. Ibis 142, 676–679. https://doi.org/10.1111/j.1474-919X.2000.tb04468.x (2000).Article 

Google Scholar 
Green, R. E. Long-term decline in the thickness of eggshells of thrushes, Turdus spp., in Britain. Proc. R. Soc. London. Ser. B: Biol. Sci. 265, 679–684. https://doi.org/10.1098/rspb.1998.0347 (1998).Article 

Google Scholar 
Igic, B. et al. Comparison of micrometer-and scanning electron microscope-based measurements of avian eggshell thickness. J. Field Ornithol. 81, 402–410 (2010).Article 

Google Scholar 
Maurer, G., Portugal, S. J. & Cassey, P. A comparison of indices and measured values of eggshell thickness of different shell regions using museum eggs of 230 European bird species. Ibis 154, 714–724 (2012).Article 

Google Scholar 
Becking, J. The ultrastructure of the avian eggshell. Ibis 117, 143–151 (1975).Article 

Google Scholar 
Birkhead, T. et al. New insights from old eggs–the shape and thickness of Great Auk Pinguinus impennis eggs. Ibis 162(4), 1345–1354 (2020).Article 

Google Scholar 
Riley, A., Sturrock, C., Mooney, S. & Luck, M. Quantification of eggshell microstructure using X-ray micro computed tomography. Br. Poult. Sci. 55, 311–320 (2014).CAS 
Article 

Google Scholar 
Kibala, L., Rozempolska-Rucinska, I., Kasperek, K., Zieba, G. & Lukaszewicz, M. Ultrasonic eggshell thickness measurement for selection of layers. Poult. Sci. 94, 2360–2363. https://doi.org/10.3382/ps/pev254 (2015).Article 

Google Scholar 
Khaliduzzaman, A. et al. A nondestructive eggshell thickness measurement technique using terahertz waves. Sci. Rep. 10, 1–5 (2020).Article 

Google Scholar 
Santolo, G. M. A new nondestructive method for measuring eggshell thickness using a non-ferrous material thickness gauge. Wilson J. Ornithol. 130, 502–509. https://doi.org/10.1676/17-035.1 (2018).Article 

Google Scholar 
Marini, M. A. et al. The five million bird eggs in the world’s museum collections are an invaluable and underused resource. Auk 137, ukaa036. https://doi.org/10.1093/auk/ukaa036 (2020).Article 

Google Scholar 
Brooker, M. G. & Brooker, L. C. Cuckoo hosts in Australia. Aust. Zool. Rev. 2, 1–67 (1989).
Google Scholar 
Higgins, P. J. Vol. Volume 4: Parrots to Dollarbird (Oxford University Press, 1999).
Google Scholar 
Higgins, P. J. & Peter, J. M. Vol. 6: Pardalotes to Shrike-Thrushes (Oxford University Press, 2002).
Google Scholar 
Higgins, P. J., Peter, J. M. & Cowling, S. J. Vol. 4: Parrots to Dollarbird (Oxford University Press, 2006).
Google Scholar 
Higgins, P. J., Peter, J. M. & Steele, W. K. Vol. 5: Tyrant-flycatchers to Chats (Oxford University Press, 2001).
Google Scholar 
Landstrom, M., Heinsohn, R. & Langmore, N. E. Clutch variation and egg rejection in three hosts of the pallid cuckoo Cuculus pallidus. Behaviour 147, 19–36. https://doi.org/10.1163/000579509X12483520922043 (2010).Article 

Google Scholar 
Abernathy, V. E., Johnson, L. E. & Langmore, N. E. An experimental test of defenses against avian brood parasitism in a recent host. Front. Ecol. Evol. 9, 244. https://doi.org/10.3389/fevo.2021.651733 (2021).Article 

Google Scholar 
Landstrom, M. T., Heinsohn, R. & Langmore, N. E. Does clutch variability differ between populations of cuckoo hosts in relation to the rate of parasitism?. Anim. Behav. 81, 307–312 (2011).Article 

Google Scholar 
Peterson, S. H. et al. Avian eggshell thickness in relation to egg morphometrics, embryonic development, and mercury contamination. Ecol. Evol. 10, 8715–8740. https://doi.org/10.1002/ece3.6570 (2020).Article 

Google Scholar 
Attard, M., Medina, I., Langmore, N. E. & Sherratt, E. Egg shape mimicry in parasitic cuckoos. J. Evol. Biol. 30, 2079–2084 (2017).CAS 
Article 

Google Scholar 
Birchard, G. F. & Deeming, D. C. Avian eggshell thickness: Scaling and maximum body mass in birds. J. Zool. 279, 95–101. https://doi.org/10.1111/j.1469-7998.2009.00596.x (2009).Article 

Google Scholar 
Orme, D. et al. The caper package: Comparative analysis of phylogenetics and evolution in R. R Packag. Vers. 5, 549–593 (2013).
Google Scholar 
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448. https://doi.org/10.1038/nature11631 (2012).ADS 
CAS 
Article 

Google Scholar 
Schliep, K. P. Phangorn: Phylogenetic analysis in R. Bioinformatics 27, 592–593. https://doi.org/10.1093/bioinformatics/btq706 (2011).CAS 
Article 

Google Scholar 
R Core Team. R: A language and environment for statistical computing, (2013). More