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    Value wild animals’ carbon services to fill the biodiversity financing gap

    Pettorelli, N. et al. J. Appl. Ecol. 58, 2384–2393 (2021).Article 

    Google Scholar 
    CBD High-Level Panel Resourcing the Aichi Biodiversity Targets: An Assessment of Benefits, Investments and Resource Needs for Implementing the Strategic Plan for Biodiversity 2011–2020 (Secretariat of the Convention on Biological Diversity, 2014).Schmitz, O. J. et al. Science 362, eaar3213 (2018).Article 

    Google Scholar 
    Krause, T. & Nielsen, M. R. Forests 10, 344 (2019).Article 

    Google Scholar 
    Jørgensen, D. BioScience 63, 719–720 (2013).Article 

    Google Scholar 
    Berzaghi, F., Chami, R., Cosimano, T. & Fullenkamp, C. Proc. Natl Acad. Sci. USA 119, e2120426119 (2022).Article 

    Google Scholar 
    van Duuren, E., Plantinga, A. & Scholtens, B. J. Bus. Ethics 138, 525–533 (2016).Article 

    Google Scholar 
    Broadstock, D. C., Chan, K., Cheng, L. T. W. & Wang, X. Finance Res. Lett. 38, 101716 (2021).Article 

    Google Scholar 
    Joos, F., Meyer, R., Bruno, M. & Leuenberger, M. Geophys. Res. Lett. 26, 1437–1440 (1999).CAS 
    Article 

    Google Scholar 
    Wang, F. et al. Biol. Conserv. 253, 108913 (2021).Article 

    Google Scholar 
    Sullivan, S. Antipode 45, 198–217 (2013).Article 

    Google Scholar 
    Kamilaris, A., Cole, I. R. & Prenafeta-Boldú, F. X., in Food Technology Disruptions (ed. Galanakis, C. M.) 247–284 (Academic Press, 2021).O’Donnell, E. & Talbot-Jones, J. Ecol. Soc. 23, 7 (2018).Article 

    Google Scholar 
    Anderson, K. & Peters, G. Science 354, 182–183 (2016).CAS 
    Article 

    Google Scholar 
    Berzaghi, F. et al. Nat. Geosci. 12, 725–729 (2019).CAS 
    Article 

    Google Scholar 
    Mariani, G. et al. Sci. Adv. 6, eabb4848 (2020).CAS 
    Article 

    Google Scholar 
    Martin, A. H., Pearson, H. C., Saba, G. K. & Olsen, E. M. One Earth 4, 680–693 (2021).Article 

    Google Scholar 
    Durfort, A., Mariani, G., Troussellier, M., Tulloch, V. & Mouillot, D. Preprint at Research Square https://doi.org/10.21203/rs.3.rs-92037/v1 (2021).Norris, K., Terry, A., Hansford, J. P. & Turvey, S. T. Trends Ecol. Evol. 35, 919–926 (2020).Article 

    Google Scholar 
    Berzaghi, F. et al. Ecography 41, 1934–1954 (2018).Article 

    Google Scholar  More

  • in

    Biodiversity mediates ecosystem sensitivity to climate variability

    Scheffers, B. R. et al. The broad footprint of climate change from genes to biomes to people. Science 354, aaf7671 (2016).PubMed 

    Google Scholar 
    IPBES. Global Assessment Report on Biodiversity and Ecosystem Service. Debating Nature’s Value (IPBES, 2019).Harrison, S. Plant community diversity will decline more than increase under climatic warming. Philos. Trans. R. Soc. B Biol. Sci. 375, 20190106 (2020).
    Google Scholar 
    Díaz, S. et al. Pervasive human-driven decline of life on Earth points to the need for transformative change. Science (80-.). 1327, eaax3100 (2019).Chapin, F. S. et al. Consequences of changing biodiversity. Nature 405, 234–242 (2000).CAS 
    PubMed 

    Google Scholar 
    Isbell, F. et al. Linking the influence and dependence of people on biodiversity across scales. Nature 546, 65–72 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Craven, D. et al. Multiple facets of biodiversity drive the diversity–stability relationship. Nat. Ecol. Evol. 2, 1579–1587 (2018).PubMed 

    Google Scholar 
    Hautier, Y. et al. Anthropogenic environmental changes affect ecosystem stability via biodiversity. Science (80-.). 348, 336–340 (2015).CAS 

    Google Scholar 
    Díaz, S., Fargione, J., Chapin, F. S. & Tilman, D. Biodiversity loss threatens human well-being. PLoS Biol. 4, e277 (2006).PubMed 
    PubMed Central 

    Google Scholar 
    Pennekamp, F. et al. Biodiversity increases and decreases ecosystem stability. Nature 563, 109–112 (2018).CAS 
    PubMed 

    Google Scholar 
    Valencia, E. et al. Synchrony matters more than species richness in plant community stability at a global scale. Proc. Natl Acad. Sci. USA 117, 24345–24351 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wang, Y. et al. Global evidence of positive biodiversity effects on spatial ecosystem stability in natural grasslands. Nat. Commun. 10, 1–9 (2019).
    Google Scholar 
    Poorter, L. et al. Diversity enhances carbon storage in tropical forests. Glob. Ecol. Biogeogr. 24, 1314–1328 (2015).
    Google Scholar 
    Schnabel, F. et al. Drivers of productivity and its temporal stability in a tropical tree diversity experiment. Glob. Chang. Biol. 25, 4257–4272 (2019).PubMed 

    Google Scholar 
    Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J. & Baldocchi, D. D. Linking plant and ecosystem functional biogeography. Proc. Natl Acad. Sci. USA 111, 13697–13702 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mori, A. S. Advancing nature-based approaches to address the biodiversity and climate emergency. Ecol. Lett. 23, 1729–1732 (2020).PubMed 

    Google Scholar 
    Mazzochini, G. G. et al. Plant phylogenetic diversity stabilizes large-scale ecosystem productivity. Glob. Ecol. Biogeogr. 28, 1430–1439 (2019).
    Google Scholar 
    Manhães, A. P., Mazzochini, G. G., Oliveira-Filho, A. T., Ganade, G. & Carvalho, A. R. Spatial associations of ecosystem services and biodiversity as a baseline for systematic conservation planning. Divers. Distrib. 22, 932–943 (2016).
    Google Scholar 
    García-Palacios, P., Gross, N., Gaitán, J. & Maestre, F. T. Climate mediates the biodiversity–ecosystem stability relationship globally. Proc. Natl Acad. Sci. USA 115, 8400–8405 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    De Keersmaecker, W. et al. A model quantifying global vegetation resistance and resilience to short-term climate anomalies and their relationship with vegetation cover. Glob. Ecol. Biogeogr. 24, 539–548 (2015).
    Google Scholar 
    Seddon, A. W. R., Macias-Fauria, M., Long, P. R., Benz, D. & Willis, K. J. Sensitivity of global terrestrial ecosystems to climate variability. Nature 531, 229–232 (2016).CAS 
    PubMed 

    Google Scholar 
    Linscheid, N. et al. Towards a global understanding of vegetation-climate dynamics at multiple timescales. Biogeosciences 17, 945–962 (2020).
    Google Scholar 
    Nemani, R. R. et al. Climate-driven increases in global terrestrial net primary production from 1982 to 1999. Science (80-.). 300, 1560–1563 (2003).CAS 

    Google Scholar 
    Quetin, G. R. & Swann, A. L. S. Empirically derived sensitivity of vegetation to climate across global gradients of temperature and precipitation. J. Clim. 30, 5835–5849 (2017).
    Google Scholar 
    Cavender-bares, J. et al. The role of diversification in community assembly of the oaks (Quercus L.) across the continental U. S. Am. J. Bot. 105, 565–586 (2018).PubMed 

    Google Scholar 
    Woodward, F. I., Lomas, M. R. & Kelly, C. K. Global climate and the distribution of plant biomes. Philos. Trans. R. Soc. Lond. Ser. B Biol. Sci. 359, 1465–1476 (2004).CAS 

    Google Scholar 
    Maurer, G. E., Hallmark, A. J., Brown, R. F., Sala, O. E. & Collins, S. L. Sensitivity of primary production to precipitation across the United States. Ecol. Lett. 23, 527–536 (2020).PubMed 

    Google Scholar 
    Cavender-Bares, J., Ackerly, D. D., Hobbie, S. E. & Townsend, P. A. Evolutionary legacy effects on ecosystems: biogeographic origins, plant traits, and implications for management in the era of global change. Annu. Rev. Ecol. Evol. Syst. 47, 433–462 (2016).
    Google Scholar 
    Harrison, S., Spasojevic, M. J. & Li, D. Climate and plant community diversity in space and time. Proc. Natl Acad. Sci. USA 117, 4464–4470 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Šímová, I. et al. Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species. J. Biogeogr. 45, 895–916 (2018).
    Google Scholar 
    Lamanna, C. et al. Functional trait space and the latitudinal diversity gradient. Proc. Natl Acad. Sci. USA 111, 13745–13750 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Craven, D. et al. A cross-scale assessment of productivity–diversity relationships. Glob. Ecol. Biogeogr. 29, 1940–1955 (2020).
    Google Scholar 
    White, H. J. et al. Ecosystem stability at the landscape scale is primarily associated with climatic history. Funct. Ecol. 1–13 https://doi.org/10.1111/1365-2435.13957 (2021).Enquist, B. J. et al. Scaling from Traits to Ecosystems: Developing a General Trait Driver Theory via Integrating Trait-Based and Metabolic Scaling Theories. Advances in Ecological Research. Vol. 52 (Elsevier Ltd., 2015).Gonzalez, A. et al. Scaling-up biodiversity-ecosystem functioning research. Ecol. Lett. 23, 757–776 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Barry, K. E. et al. A graphical null model for scaling biodiversity–ecosystem functioning relationships. J. Ecol. 109, 1549–1560 (2021).
    Google Scholar 
    Mori, A. S., Furukawa, T. & Sasaki, T. Response diversity determines the resilience of ecosystems to environmental change. Biol. Rev. 88, 349–364 (2013).PubMed 

    Google Scholar 
    Tilman, D., Reich, P. B. & Knops, J. M. H. Biodiversity and ecosystem stability in a decade-long grassland experiment. Nature 441, 629–632 (2006).CAS 
    PubMed 

    Google Scholar 
    Isbell, F. et al. Quantifying effects of biodiversity on ecosystem functioning across times and places. Ecol. Lett. 21, 763–778 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Bond, E. M. & Chase, J. M. Biodiversity and ecosystem functioning at local and regional spatial scales. Ecol. Lett. 5, 467–470 (2002).
    Google Scholar 
    Delsol, R., Loreau, M. & Haegeman, B. The relationship between the spatial scaling of biodiversity and ecosystem stability. Glob. Ecol. Biogeogr. 27, 439–449 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Price, G. R. The nature of selection. J. Theor. Biol. 175, 389-396 (1995).Fonseca, C. R. & Ganade, G. Species functional redundancy, random extinctions and the stability of ecosystems. J. Ecol. 89, 118–125 (2001).
    Google Scholar 
    Le Bagousse-Pinguet, Y. et al. Phylogenetic, functional, and taxonomic richness have both positive and negative effects on ecosystem multifunctionality. Proc. Natl Acad. Sci. USA 116, 8419–8424 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Cadotte, M., Dinnage, R. & Tilman, D. Phylogenetic diversity promotes ecosytem stability. Ecology 93, S223–S233 (2012).
    Google Scholar 
    Veron, S., Davies, T. J., Cadotte, M. W., Clergeau, P. & Pavoine, S. Predicting loss of evolutionary history: Where are we? Biol. Rev. 92, 271–291 (2017).PubMed 

    Google Scholar 
    Tucker, C. M., Davies, T. J., Cadotte, M. W. & Pearse, W. D. On the relationship between phylogenetic diversity and trait diversity. Ecology 99, 1473–1479 (2018).PubMed 

    Google Scholar 
    Faith, D. P. Systematics and conservation: on predicting the feature diversity of subsets of taxa. Cladistics 8, 361–373 (1992).PubMed 

    Google Scholar 
    Hisano, M., Searle, E. B. & Chen, H. Y. H. Biodiversity as a solution to mitigate climate change impacts on the functioning of forest ecosystems. Biol. Rev. 93, 439–456 (2018).PubMed 

    Google Scholar 
    Flynn, D. F. B., Mirotchnick, N., Jain, M., Palmer, M. I. & Naeem, S. Functional and phylogenetic diversity as predictors of biodiversity–ecosystem-function relationships. Ecology 92, 1573–1581 (2011).PubMed 

    Google Scholar 
    Cadotte, M. W., Cardinale, B. J. & Oakley, T. H. Evolutionary history and the effect of biodiversity on plant productivity. Proc. Natl Acad. Sci. USA 105, 17012–17017 (2008).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Venail, P. et al. Species richness, but not phylogenetic diversity, influences community biomass production and temporal stability in a re-examination of 16 grassland biodiversity studies. Funct. Ecol. 29, 615–626 (2015).
    Google Scholar 
    Enquist, B., Condit, R., Peet, R., Schildhauer, M. & Thiers, B. Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. PeerJ Prepr. 4, e2615v2 (2016).Maitner, B. S. et al. The bien R package: a tool to access the Botanical Information and Ecology Network (BIEN) database. Methods Ecol. Evol. 9, 373–379 (2018).
    Google Scholar 
    Mori, A. S. Resilience in the studies of biodiversity–ecosystem functioning. Trends Ecol. Evol. 31, 87–89 (2016).PubMed 

    Google Scholar 
    Holling, C. S. Resilience and stability of ecological systems. Annu. Rev. Ecol. Syst. 4, 1–23 (1973).
    Google Scholar 
    Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30, 673–684 (2015).PubMed 

    Google Scholar 
    Huete, A., Chris, J. & Leeuwen, W. Van. MODIS vegetation index (MOD 13). Algorithm theoretical basis document vol. 3 https://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf (1999).Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A. & Hegewisch, K. C. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci. Data 5, 170191 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    MacIas-Fauria, M., Forbes, B. C., Zetterberg, P. & Kumpula, T. Eurasian Arctic greening reveals teleconnections and the potential for structurally novel ecosystems. Nat. Clim. Chang. 2, 613–618 (2012).
    Google Scholar 
    Garcia, R. A., Cabeza, M., Rahbek, C. & Araújo, M. B. Multiple dimensions of climate change and their implications for biodiversity. Science (80-.). 344, 1247579 (2014).Zhang, Y. et al. Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production. Sci. Rep. 6, 39748 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Poulter, B. et al. Contribution of semi-arid ecosystems to interannual variability of the global carbon cycle. Nature 509, 600–603 (2014).CAS 
    PubMed 

    Google Scholar 
    Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on earth. Bioscience 51, 933 (2001).
    Google Scholar 
    Srivastava, D. S. et al. Phylogenetic diversity and the functioning of ecosystems. Ecol. Lett. 15, 637–648 (2012).PubMed 

    Google Scholar 
    Parker, I. M. et al. Phylogenetic structure and host abundance drive disease pressure in communities. Nature 520, 542–544 (2015).CAS 
    PubMed 

    Google Scholar 
    Díaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2015).PubMed 

    Google Scholar 
    Brun, P. et al. Plant community impact on productivity: Trait diversity or key(stone) species effects? Ecol. Lett. 25, 913–925 (2022).PubMed 

    Google Scholar 
    Aubin, I. et al. Traits to stay, traits to move: a review of functional traits to assess sensitivity and adaptive capacity of temperate and boreal trees to climate change. Environ. Rev. 24, 164–186 (2016).
    Google Scholar 
    Reichstein, M., Bahn, M., Mahecha, M. D., Kattge, J. & Baldocchi, D. D. Linking plant and ecosystem functional biogeography. Proc. Natl. Acad. Sci. USA https://doi.org/10.1073/pnas.1216065111 (2014).Díaz, S. & Cabido, M. Vive la différence: plant functional diversity matters to ecosystem processes. Trends Ecol. Evol. 16, 646–655 (2001).
    Google Scholar 
    Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530, 211–214 (2016).CAS 
    PubMed 

    Google Scholar 
    Ye, J. S., Pei, J. Y. & Fang, C. Under which climate and soil conditions the plant productivity–precipitation relationship is linear or nonlinear? Sci. Total Environ. 616–617, 1174–1180 (2018).PubMed 

    Google Scholar 
    Allan, E. et al. More diverse plant communities have higher functioning over time due to turnover in complementary dominant species. Proc. Natl Acad. Sci. U. S. A. 108, 17034–17039 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hurlbert, A. H. & Jetz, W. Species richness, hotspots, and the scale dependence of range maps in ecology and conservation. Proc. Natl Acad. Sci. 104, 13384–13389 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Mori, A. S. et al. Biodiversity–productivity relationships are key to nature-based climate solutions. Nat. Clim. Chang. 11, 543–550 (2021).
    Google Scholar 
    Kattge, J. et al. TRY plant trait database–enhanced coverage and open access. Glob. Chang. Biol. 26, 119–188 (2020).PubMed 

    Google Scholar 
    Feeley, K. J., Bravo-Avila, C., Fadrique, B., Perez, T. M. & Zuleta, D. Climate-driven changes in the composition of New World plant communities. Nat. Clim. Chang. 10, 965–970 (2020).CAS 

    Google Scholar 
    Li, D., Miller, J. E. D. & Harrison, S. Climate drives loss of phylogenetic diversity in a grassland community. Proc. Natl Acad. Sci. USA 116, 19989–19994 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Madani, N. et al. Future global productivity will be affected by plant trait response to climate. Sci. Rep. 8, 2870 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing Version 3.5.2. (R Core Team, 2018).Ammer, C. Diversity and forest productivity in a changing climate. N. Phytol. 221, 50–66 (2019).
    Google Scholar 
    Hooper, D. U. et al. A global synthesis reveals biodiversity loss as a major driver of ecosystem change. Nature 486, 105–108 (2012).CAS 
    PubMed 

    Google Scholar 
    Larue, E. A., Hardiman, B. S., Elliott, J. M. & Fei, S. Structural diversity as a predictor of ecosystem function. Environ. Res. Lett. 14, 114011 (2019).Phillips, S. J. & Dudìk, M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography (Cop.). 31, 161–175 (2008).
    Google Scholar 
    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978 (2005).
    Google Scholar 
    Diniz-Filho, J. A. F. & Bini, L. M. Modelling geographical patterns in species richness using eigenvector-based spatial filters. Glob. Ecol. Biogeogr. 14, 177–185 (2005).
    Google Scholar 
    Merow, C., Smith, M. J. & Silander, J. a. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography (Cop.). 36, 1058–1069 (2013).
    Google Scholar 
    Merow, C. BIEN range methods description. http://bien.nceas.ucsb.edu/bien/wp-content/uploads/2017/06/BIEN3RangeMethodsSummary.pdf (2017).Schrodt, F. et al. BHPMF-a hierarchical Bayesian approach to gap-filling and trait prediction for macroecology and functional biogeography. Glob. Ecol. Biogeogr. 24, 1510–1521 (2015).
    Google Scholar 
    Bruelheide, H. et al. Global trait–environment relationships of plant communities. Nat. Ecol. Evol. 2, 1906–1917 (2018).PubMed 

    Google Scholar 
    Guo, W. Y. et al. Half of the world’s tree biodiversity is unprotected and is increasingly threatened by human activities. Preprint at bioRxiv https://doi.org/10.1101/2020.04.21.052464 (2020).Guo, W., Serra-diaz, J. M., Schrodt, F. & Eiserhardt, W. L. Paleoclimate and current climate collectively shape the phylogenetic and functional diversity of trees worldwide. Preprint at bioRxiv https://doi.org/10.1101/2020.06.02.128975 (2020).Diniz-Filho, J. A. F. et al. On the selection of phylogenetic eigenvectors for ecological analyses. Ecography (Cop.). 35, 239–249 (2012).
    Google Scholar 
    Penone, C. et al. Imputation of missing data in life-history trait datasets: which approach performs the best? Methods Ecol. Evol. 5, 961–970 (2014).
    Google Scholar 
    Santos, T. PVR: Phylogenetic eigenvectors regression and phylogentic signal-representation curve. R package version 0.3. Available at: http://CRAN.R-project.org/package=PVR (2018).Brum, F. T. et al. Global priorities for conservation across multiple dimensions of mammalian diversity. Proc. Natl Acad. Sci. USA 114, 7641–7646 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gerhold, P., Cahill, J. F., Winter, M., Bartish, I. V. & Prinzing, A. Phylogenetic patterns are not proxies of community assembly mechanisms (they are far better). Funct. Ecol. 29, 600–614 (2015).
    Google Scholar 
    Kendall, M. & Stuart, A. The Advanced Theory of Statistics (Macmillan, 1983).Pavoine, S. & Bonsall, M. B. Measuring biodiversity to explain community assembly: a unified approach. Biol. Rev. Camb. Philos. Soc. 86, 792–812 (2011).CAS 
    PubMed 

    Google Scholar 
    Tucker, C. M. et al. A guide to phylogenetic metrics for conservation, community ecology and macroecology. Biol. Rev. 92, 698–715 (2017).PubMed 

    Google Scholar 
    Schliep, K. P. phangorn: phylogenetic analysis in R. Bioinformatics 27, 592–593 (2011).CAS 
    PubMed 

    Google Scholar 
    Cornwell, W. K., Schwilk, L. D. W. & Ackerly, D. D. A trait-based test for habitat filtering: convex hull volume. Ecology 87, 1465–1471 (2006).PubMed 

    Google Scholar 
    Villéger, S., Maire, E. & Leprieur, F. On the risks of using dendrograms to measure functional diversity and multidimensional spaces to measure phylogenetic diversity: a comment on Sobral et al. (2016). Ecol. Lett. 20, 554–557 (2017).PubMed 

    Google Scholar 
    Laliberté, E., Legendre, P. & Shipley, B. FD: measuring functional diversity from multiple traits, an other tools for functional ecology. R package version 1.0-12 (Comprehensive R Archive Network, Vienna, Austria, 2015).Podani, J. & Schmera, D. On dendrogram-based measures of functional diversity. Oikos 115, 179–185 (2006).
    Google Scholar 
    Poos, M. S., Walker, S. C. & Jackson, D. A. Functional-diversity indices can be driven by methodological choices and species richness. Ecology 90, 341–347 (2009).PubMed 

    Google Scholar 
    Gotelli, N. J. & Graves, G. R. Null Models in Ecology (Smithsonian Institution Press, 1996).Swenson, N. G. Functional and Phylogenetic Ecology in R. (Springer, 2014).Dormann, C. F. et al. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography (Cop.). 30, 609–628 (2007).
    Google Scholar 
    Kissling, W. D. & Carl, G. Spatial autocorrelation and the selection of simultaneous autoregressive models. Glob. Ecol. Biogeogr. 17, 59–71 (2008).
    Google Scholar 
    Bivand, R. spatialreg: Spatial Regression Analysis (R package version 1.1-5, 2019). More

  • in

    Archiving the genomic and genetic resources of glaciers

    Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.This is a summary of: Liu, Y. et al. A genome and gene catalog of glacier microbiomes. Nat. Biotechnol. https://doi.org/10.1038/s41587-022-01367-2 (2022). More

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    Meta-analysis shows that plant mixtures increase soil phosphorus availability and plant productivity in diverse ecosystems

    Vitousek, P. M., Porder, S., Houlton, B. Z. & Chadwick, O. A. Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen–phosphorus interactions. Ecol. Appl. 20, 5–15 (2010).PubMed 
    Article 

    Google Scholar 
    Hou, E. Q. et al. Global meta-analysis shows pervasive phosphorus limitation of aboveground plant production in natural terrestrial ecosystems. Nat. Commun. 11, 637 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Cordell, D., Drangert, J.-O. & White, S. The story of phosphorus: global food security and food for thought. Glob. Environ. Change 19, 292–305 (2009).Article 

    Google Scholar 
    Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, X. L., Chen, H. Y. H., Searle, E. B., Chen, C. & Reich, P. B. Negative to positive shifts in diversity effects on soil nitrogen over time. Nat. Sustain. 4, 225–234 (2021).Article 

    Google Scholar 
    Oelmann, Y. et al. Plant diversity effects on aboveground and belowground N pools in temperate grassland ecosystems: development in the first 5 years after establishment. Glob. Biogeochem. Cy. 25, GB2014 (2011).Article 
    CAS 

    Google Scholar 
    Fornara, D. A. et al. Plant effects on soil N mineralization are mediated by the composition of multiple soil organic fractions. Ecol. Res. 26, 201–208 (2011).CAS 
    Article 

    Google Scholar 
    Wright, A. J., Wardle, D. A., Callaway, R. & Gaxiola, A. The overlooked role of facilitation in biodiversity experiments. Trends Ecol. Evol. 32, 383–390 (2017).PubMed 
    Article 

    Google Scholar 
    Oelmann, Y. et al. Above- and belowground biodiversity jointly tighten the P cycle in agricultural grasslands. Nat. Commun. 12, 4431 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li, L. et al. Diversity enhances agricultural productivity via rhizosphere phosphorus facilitation on phosphorus-deficient soils. Proc. Natl Acad. Sci. USA 104, 11192–11196 (2007).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Li, L., Tilman, D., Lambers, H. & Zhang, F. S. Plant diversity and overyielding: insights from belowground facilitation of intercropping in agriculture. New Phytol. 203, 63–69 (2014).PubMed 
    Article 
    CAS 

    Google Scholar 
    Hacker, N. et al. Plant diversity shapes microbe–rhizosphere effects on P mobilisation from organic matter in soil. Ecol. Lett. 18, 1356–1365 (2015).PubMed 
    Article 

    Google Scholar 
    Vance, C. P., Uhde-Stone, C. & Allan, D. L. Phosphorus acquisition and use: critical adaptations by plants for securing a nonrenewable resource. New Phytol. 157, 423–447 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    Chen, J. et al. Long-term nitrogen loading alleviates phosphorus limitation in terrestrial ecosystems. Glob. Change Biol. 26, 5077–5086 (2020).Article 

    Google Scholar 
    Hinsinger, P. et al. P for two, sharing a scarce resource: soil phosphorus acquisition in the rhizosphere of intercropped species. Plant Physiol. 156, 1078–1086 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Liu, X. J. et al. Plant diversity and species turnover co-regulate soil nitrogen and phosphorus availability in Dinghushan forests, southern China. Plant Soil 464, 257–272 (2021).CAS 
    Article 

    Google Scholar 
    Hooper, D. U. & Vitousek, P. M. Effects of plant composition and diversity on nutrient cycling. Ecol. Monogr. 68, 121–149 (1998).Article 

    Google Scholar 
    Alberti, G. et al. Tree functional diversity influences belowground ecosystem functioning. Appl. Soil Ecol. 120, 160–168 (2017).Article 

    Google Scholar 
    Maddhesiya, P. K., Singh, K. & Singh, R. P. Effects of perennial aromatic grass species richness and microbial consortium on soil properties of marginal lands and on biomass production. Land Degrad. Dev. 32, 1008–1021 (2021).Article 

    Google Scholar 
    Zhang, C. B. et al. Effects of plant diversity on nutrient retention and enzyme activities in a full-scale constructed wetland. Bioresour. Technol. 101, 1686–1692 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Štursová, M. & Baldrian, P. Effects of soil properties and management on the activity of soil organic matter transforming enzymes and the quantification of soil-bound and free activity. Plant Soil 338, 99–110 (2011).Article 
    CAS 

    Google Scholar 
    Wu, H. et al. Linkage between tree species richness and soil microbial diversity improves phosphorus bioavailability. Funct. Ecol. 33, 1549–1560 (2019).Article 

    Google Scholar 
    Steinauer, K. et al. Plant diversity effects on soil microbial functions and enzymes are stronger than warming in a grassland experiment. Ecology 96, 99–112 (2015).PubMed 
    Article 

    Google Scholar 
    Zhang, D. S. et al. Increased soil phosphorus availability induced by faba bean root exudation stimulates root growth and phosphorus uptake in neighbouring maize. New Phytol. 209, 823–831 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Berendse, F., van Ruijven, J., Jongejans, E. & Keesstra, S. Loss of plant species diversity reduces soil erosion resistance. Ecosystems 18, 881–888 (2015).CAS 
    Article 

    Google Scholar 
    Forrester, D. I. & Bauhus, J. A review of processes behind diversity–productivity relationships in forests. Curr. Rep. 2, 45–61 (2016).Article 
    CAS 

    Google Scholar 
    Batterman, S. A. et al. Phosphatase activity and nitrogen fixation reflect species differences, not nutrient trading or nutrient balance, across tropical rainforest trees. Ecol. Lett. 21, 1486–1495 (2018).PubMed 
    Article 

    Google Scholar 
    Chen, C., Chen, H. Y. H., Chen, X. & Huang, Z. Meta-analysis shows positive effects of plant diversity on microbial biomass and respiration. Nat. Commun. 10, 1332 (2019).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hisano, M., Chen, H. Y. H., Searle, E. B. & Reich, P. B. Species-rich boreal forests grew more and suffered less mortality than species-poor forests under the environmental change of the past half-century. Ecol. Lett. 22, 999–1008 (2019).PubMed 
    Article 

    Google Scholar 
    Chen, X. & Chen, H. Y. H. Plant diversity loss reduces soil respiration across terrestrial ecosystems. Glob. Change Biol. 25, 1482–1492 (2019).Article 

    Google Scholar 
    Chen, X. & Chen, H. Y. H. Plant mixture balances terrestrial ecosystem C:N:P stoichiometry. Nat. Commun. 12, 4562 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Reich, P. B. et al. Species and functional group diversity independently influence biomass accumulation and its response to CO2 and N. Proc. Natl Acad. Sci. USA 101, 10101–10106 (2004).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Chen, X. et al. Effects of plant diversity on soil carbon in diverse ecosystems: a global meta-analysis. Biol. Rev. 95, 167–183 (2020).Article 

    Google Scholar 
    Zhang, Y., Chen, H. Y. H. & Reich, P. B. Forest productivity increases with evenness, species richness and trait variation: a global meta-analysis. J. Ecol. 100, 742–749 (2012).Article 

    Google Scholar 
    Alewell, C. et al. Global phosphorus shortage will be aggravated by soil erosion. Nat. Commun. 11, 4546 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Mueller, K. E., Tilman, D., Fornara, D. A. & Hobbie, S. E. Root depth distribution and the diversity–productivity relationship in a long-term grassland experiment. Ecology 94, 787–793 (2013).Article 

    Google Scholar 
    Tang, X. Y. et al. Intercropping legumes and cereals increases phosphorus use efficiency; a meta-analysis. Plant Soil 460, 89–104 (2021).CAS 
    Article 

    Google Scholar 
    Karanika, E. D., Alifragis, D. A., Mamolos, A. P. & Veresoglou, D. S. Differentiation between responses of primary productivity and phosphorus exploitation to species richness. Plant Soil 297, 69–81 (2007).CAS 
    Article 

    Google Scholar 
    Bünemann, E. K., Prusisz, B. & Ehlers, K. in Phosphorus in Action: Biological Processes in Soil Phosphorus Cycling (eds Bünemann, E. et al.) 37–57 (Springer, 2011).Ma, Z. L. & Chen, H. Y. H. Effects of species diversity on fine root productivity in diverse ecosystems: a global meta-analysis. Glob. Ecol. Biogeogr. 25, 1387–1396 (2016).Article 

    Google Scholar 
    Mellado-Vazquez, P. G. et al. Plant diversity generates enhanced soil microbial access to recently photosynthesized carbon in the rhizosphere. Soil Biol. Biochem. 94, 122–132 (2016).CAS 
    Article 

    Google Scholar 
    Qin, Y. et al. Arbuscular mycorrhizal fungus differentially regulates P mobilizing bacterial community and abundance in rhizosphere and hyphosphere. Appl. Soil Ecol. 170, 104294 (2022).Article 

    Google Scholar 
    Rojo, M. J., Carcedo, S. G. & Mateos, M. P. Distribution and characterization of phosphatase and organic phosphorus in soil fractions. Soil Biol. Biochem. 22, 169–174 (1990).CAS 
    Article 

    Google Scholar 
    Barrow, N. The effects of pH on phosphate uptake from the soil. Plant Soil 410, 401–410 (2017).CAS 
    Article 

    Google Scholar 
    Button, K. S. et al. Power failure: why small sample size undermines the reliability of neuroscience. Nat. Rev. Neurosci. 14, 365–376 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Yu, R. P., Li, X. X., Xiao, Z. H., Lambers, H. & Li, L. Phosphorus facilitation and covariation of root traits in steppe species. New Phytol. 226, 1285–1298 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G. & PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Medicine 6, e1000097 (2009).Jenkins, D. G. & Quintana-Ascencio, P. F. A solution to minimum sample size for regressions. PLoS ONE 15, e0229345 (2020)..Rohatgi, A. WebPlotDigitizer v.4.5 (Automeris, 2021); https://automeris.io/WebPlotDigitizerJobbagy, E. G. & Jackson, R. B. The distribution of soil nutrients with depth:global patterns and the imprint of plants. Biogeochemistry 53, 51–77 (2001).CAS 
    Article 

    Google Scholar 
    Trabucco, A. & Zomer, R. Global Aridity Index (Global-Aridity) and Global Potential Evapo-Transpiration (Global-PET) Geospatial Database (CGIAR, 2009); http://www.cgiar-csi.org/data/global-aridity-and-pet-databaseBridgham, S. D., Pastor, J., Mcclaugherty, C. A. & Richardson, C. J. Nutrient-use efficiency: a litterfall index, a model, and a test along a nutrient-availability gradient in North Carolina peatlands. Am. Nat. 145, 1–21 (1995).Article 

    Google Scholar 
    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 
    Loreau, M. & Hector, A. Partitioning selection and complementarity in biodiversity experiments. Nature 412, 72–76 (2001).CAS 
    PubMed 
    Article 

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

    Google Scholar 
    Bates, D. et al. lme4: Linear mixed-effects models using Eigen and S4. R package version 1.1-10 https://cran.r-project.org/web/packages/lme4/index.html (2017).Zuur, A. F., Ieno, E. N. & Elphick, C. S. A protocol for data exploration to avoid common statistical problems. Methods Ecol. Evol. 1, 3–14 (2010).Article 

    Google Scholar 
    Johnson, J. B. & Omland, K. S. Model selection in ecology and evolution. Trends Ecol. Evol. 19, 101–108 (2004).PubMed 
    Article 

    Google Scholar 
    MuMIn: Multi-model inference. R package version 1.42.1 (2018).Zuur, A. F., Ieno, E. N., Walker, N., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009).Koricheva, J., Gurevitch, J. & Mengersen, K. Handbook of Meta-analysis in Ecology and Evolution (Princeton Univ. Press, 2013).Graham, M. H. Confronting multicollinearity in ecological multiple regression. Ecology 84, 2809–2815 (2003).Article 

    Google Scholar 
    Lefcheck, J. S. piecewiseSEM: piecewise structural equation modelling in R for ecology, evolution, and systematics. Methods Ecol. Evol. 7, 573–579 (2016).Article 

    Google Scholar 
    Long, J. A. Interactions: comprehensive, user-friendly toolkit for probing interactions. R package version 1.1.5 https://cran.r-project.org/package=interactions (2021).Adams, D. C., Gurevitch, J. & Rosenberg, M. S. Resampling tests for meta-analysis of ecological data. Ecology 78, 1277–1283 (1997).Article 

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

  • in

    Accounting for ecosystem service values in climate policy

    IPCC Climate Change 2007: Synthesis Report (eds Pachauri, R. K. & Reisinger, A.) (IPCC, 2007).Boyd, J. & Banzhaf, S. Ecol. Econ. 63, 616–626 (2007).Article 

    Google Scholar 
    Ruhl, J. B. et al. Front. Ecol. Environ. 19, 519–525 (2021).Article 

    Google Scholar 
    Carleton, T. & Greenstone, M. Updating the United States Government’s Social Cost of Carbon Working Paper 2021-04 (Univ. Chicago, Becker Friedman Institute for Economics, 2021).Mandle, L. et al. Nat. Sustain. 4, 161–169 (2021).Article 

    Google Scholar 
    Druckenmiller, H. Estimating an Economic and Social Value of Forests: Evidence from Tree Mortality in the American West (Univ. California Berkeley, 2021).Burkett, V. R. et al. Ecol. Complexity 2, 357–394 (2005).Article 

    Google Scholar 
    Hanley, N. & Czajkowski, M. Rev. Environ. Econ. Policy 13, 248–266 (2019).Article 

    Google Scholar 
    Mendelsohn, R. Rev. Environ. Econ. Policy 13, 267–282 (2019).Article 

    Google Scholar 
    Fenichel, E. P. et al. Proc. Natl Acad. Sci. USA 113, 2382–2387 (2016).CAS 
    Article 

    Google Scholar 
    Martin-Ortega, J. et al. Ecosyst. Serv. 50, 101327 (2021).Article 

    Google Scholar 
    Borrelli, P. et al. Proc. Natl Acad. Sci. USA 117, 21994–22001 (2020).CAS 
    Article 

    Google Scholar 
    Tropek, R. et al. Science 344, 981–981 (2014).CAS 
    Article 

    Google Scholar 
    Vardon, M., Burnett, P. & Dovers, S. Ecol. Econ. 124, 145–152 (2016).Article 

    Google Scholar 
    Bastien-Olvera, B. A. & Moore, F. C. Nat. Sustain. 4, 101–108 (2021).Article 

    Google Scholar 
    Beland, M. et al. For. Ecol. Manage. 450, 117484 (2019).Article 

    Google Scholar 
    Vargas, L., Willemen, L. & Hein, L. Environ. Manage. 63, 1–15 (2019).Article 

    Google Scholar 
    Hallgren, W. et al. Environ. Model. Softw. 76, 182–186 (2016).Article 

    Google Scholar 
    Rolf, E. et al. Nat. Commun. 12, 4392 (2021).CAS 
    Article 

    Google Scholar 
    Chernozhukov, V. et al. NBER Working Paper 24678 (National Bureau of Economic Research, 2018). More

  • in

    Manure amendment can reduce rice yield loss under extreme temperatures

    Zhu, C. et al. Carbon dioxide (CO2) levels this century will alter the protein, micronutrients, and vitamin content of rice grains with potential health consequences for the poorest rice-dependent countries. Sci. Adv. 4, eaaq1012 (2018).
    Google Scholar 
    Alexandratos, N. & Bruinsma, J. World Agriculture Towards 2030/2050: The 2012 Revision (FAO Agricultural Development Economics Division, 2012).Arunrat, N., Pumijumnong, N., Sereenonchai, S., Chareonwong, U. & Wang, C. Assessment of climate change impact on rice yield and water footprint of large-scale and individual farming in Thailand. Sci. Total Environ. 726, 137864 (2020).CAS 

    Google Scholar 
    Lafferty, D. C. et al. Statistically bias-corrected and downscaled climate models underestimate the adverse effects of extreme heat on U.S. maize yields. Commun. Earth Environ. 2, 196 (2021).
    Google Scholar 
    Davis, K. F., Downs, S. & Gephart, J. A. Towards food supply chain resilience to environmental shocks. Nat. Food. 2, 54–65 (2021).
    Google Scholar 
    Wang, X. et al. Emergent constraint on crop yield response to warmer temperature from field experiments. Nat. Sustain. 3, 908–916 (2020).
    Google Scholar 
    Sun, T. et al. Current rice models underestimate yield losses from short-term heat stresses. Glob. Chang. Biol. 27, 402–416 (2020).
    Google Scholar 
    Challinor, A. J. et al. A meta-analysis of crop yield under climate change and adaptation. Nat. Clim. Chang. 4, 287–291 (2014).
    Google Scholar 
    Iizumi, T. & Ramankutty, N. Changes in yield variability of major crops for 1981–2010 explained by climate change. Environ. Res. Lett. 11, 034003 (2016).
    Google Scholar 
    Ray, D. K., Ramankutty, N., Mueller, N. D., West, P. C. & Foley, J. A. Recent patterns of crop yield growth and stagnation. Nat. Commun. 3, 1293 (2012).
    Google Scholar 
    Amelung, W. et al. Towards a global-scale soil climate mitigation strategy. Nat. Commun. 11, 1–10 (2020).
    Google Scholar 
    Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 494, 390 (2013).CAS 

    Google Scholar 
    Chen, X. et al. Producing more grain with lower environmental costs. Nature 514, 486–489 (2014).CAS 

    Google Scholar 
    Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).CAS 

    Google Scholar 
    Guo, J. et al. Significant acidification in major Chinese croplands. Science 327, 1008–1010 (2010).CAS 

    Google Scholar 
    Galloway, J. et al. Transformation of the nitrogen cycle: Recent trends, questions, and potential solutions. Science 320, 889–892 (2008).CAS 

    Google Scholar 
    Xia, L., Lam, S. K., Yan, X. & Chen, D. How does recycling of livestock manure in agroecosystems affect crop productivity, reactive nitrogen losses, and soil carbon balance? Environ. Sci. Technol. 51, 7450–7457 (2017).CAS 

    Google Scholar 
    Zhang, T. et al. Replacing synthetic fertilizer by manure requires adjusted technology and incentives: A farm survey across China. Resour. Conserv. Recycl. 168, 105301 (2021).
    Google Scholar 
    Bi, L. et al. Long-term effects of organic amendments on the rice yields for double rice cropping systems in subtropical China. Agric. Ecosyst. Environ. 129, 534–541 (2009).
    Google Scholar 
    Du, Y. et al. Effects of manure fertilizer on crop yield and soil properties in China: A meta-analysis. Catena 193, 104617 (2020).CAS 

    Google Scholar 
    Wang, K., Zhang, X. & Ervin, E. Antioxidative responses in roots and shoots of creeping bentgrass under high temperature: Effects of nitrogen and cytokinin. J. Plant Physiol. 169, 492–500 (2012).CAS 

    Google Scholar 
    Jespersen, D. & Huang, B. Proteins associated with heat‐induced leaf senescence in creeping bentgrass as affected by foliar application of nitrogen, cytokinins, and an ethylene inhibitor. Proteomics. 15, 798–812 (2015).CAS 

    Google Scholar 
    Xi, Y. et al. Exogenous phosphite application alleviates the adverse effects of heat stress and improves thermotolerance of potato (Solanum tuberosum L.) seedlings. Ecotoxicol. Environ. Saf. 190, 110048 (2020).CAS 

    Google Scholar 
    Waraich, E. A., Ahmad, R., Halim, A. & Aziz, T. Alleviation of temperature stress by nutrient management in crop plants: a review. J. Soil Sci. Plant Nut. 12, 221–244 (2012).
    Google Scholar 
    Yamori, W., Noguchi, K., Hikosaka, K. & Terashima, I. Phenotypic plasticity in photosynthetic temperature acclimation among crop species with different cold tolerances. Plant Physiol. 152, 388–399 (2010).CAS 

    Google Scholar 
    Mittler, R. Oxidative stress, antioxidants and stress tolerance. Trends. Plant Sci. 7, 405–410 (2002).CAS 

    Google Scholar 
    Wang, Q., Chen, J., He, N. & Guo, F. Metabolic reprogramming in chloroplasts under heat stress in plants. Int. J. Mol. Sci. 19, 849 (2018).
    Google Scholar 
    Cheng, Q. et al. An alternatively spliced heat shock transcription factor, OsHSFA2dI, functions in the heat stress-induced unfolded protein response in rice. Plant Biol. 17, 419–429 (2015).CAS 

    Google Scholar 
    Miura, K. et al. SIZ1-mediated sumoylation of ICE1 controls CBF3/DREB1A expression and freezing tolerance in Arabidopsis. Plant Cell 19, 1403–1414 (2007).CAS 

    Google Scholar 
    Xie, G., Kato, H., Sasaki, K. & Imai, R. A cold-induced thioredoxin h of rice, OsTrx23, negatively regulates kinase activities of OsMPK3 and OsMPK6 in vitro. FEBS Lett. 583, 2734–2738 (2009).CAS 

    Google Scholar 
    Hasanuzzaman, M., Hossain, M. A. & Fujita, M. Nitric oxide modulates antioxidant defense and the methylglyoxal detoxification system and reduces salinity-induced damage of wheat seedlings. Plant Biotechnol. Rep. 5, 353 (2011).
    Google Scholar 
    Uchida, A., Jagendorf, A. T., Hibino, T., Takabe, T. & Takabe, T. Effects of hydrogen peroxide and nitric oxide on both salt and heat stress tolerance in rice. Plant Sci. 163, 515–523 (2002).CAS 

    Google Scholar 
    Khan, S. et al. Plants mechanisms and adaptation strategies to improve heat tolerance in rice. A review. Plants 8, 508 (2019).CAS 

    Google Scholar 
    Li, Y., Gao, Y., Xu, X., Shen, Q. & Guo, S. Light-saturated photosynthetic rate in high-nitrogen rice (Oryza sativa L.) leaves is related to chloroplastic CO2 concentration. J. Exp. Bot. 60, 2351–2360 (2009).CAS 

    Google Scholar 
    Xiong, D. et al. Rapid responses of mesophyll conductance to changes of CO2 concentration, temperature, and irradiance are affected by N supplements in rice. Plant. Cell Environ. 38, 2541–2550 (2015).CAS 

    Google Scholar 
    Waraich, E. A., Ahmad, R., Ashraf, M. Y., Saifullah & Ahmad, M. Improving agricultural water use effciency by nutrient management in crop plants. Acta Agric. Scand. Sect.-B Soil. Plant Sci. 61, 291–304 (2011).CAS 

    Google Scholar 
    Dias, A. S. & Lidon, F. C. Bread and durum wheat tolerance under heat stress: A synoptical overview. Emir. J. Food Agric. 22, 412–436 (2010).
    Google Scholar 
    Meshah, E. A. E. Effect of irrigation regimes and foliar spraying of potassium on yield, yield components and water use efficiency of wheat in sandy soils. World J. Agric. Sci. 5, 662–669 (2009).
    Google Scholar 
    Huang, G., Zhang, Q., Wei, X., Peng, S. & Li, Y. Nitrogen can alleviate the inhibition of photosynthesis caused by high temperature stress under both steady-state and flecked irradiance. Front. Plant Sci. 8, 945 (2017).
    Google Scholar 
    Zhou, Y. et al. High nitrogen input reduces yield loss from low temperature during the seedling stage in early-season rice. Field Crop. Res. 228, 68–75 (2018).
    Google Scholar 
    Hou, L. et al. Effects of different phosphate fertilizer application on permeability of membrane and antioxidative enzymes in rice under low temperature stress. Acta Agriculturae. Boreali-Sinica 27, 118–123 (2012).
    Google Scholar 
    Dong, W. et al. Effect of different fertilizer application on the soil fertility of paddy soils in red soil region of southern China. PLoS One 7, e44504 (2012).CAS 

    Google Scholar 
    Bertollo, A. M. et al. Precrops alleviate soil physical limitations for soybean root growth in an Oxisol from southern Brazil. Soil Till. Res. 206, 104820 (2021).
    Google Scholar 
    Ren, Y. et al. Functional compensation dominates plant rhizosphere microbiota assembly of plant rhizospheric bacterial community. Soil Biol. Biochem. 150, 107968 (2020).CAS 

    Google Scholar 
    Oka, Y. Mechanisms of nematode suppression by organic soil amendments—a review. Appl. Soil Ecol. 44, 101–115 (2010).
    Google Scholar 
    Rose, M. T. et al. A meta-analysis and review of plant-growth response to humic substances: Practical implications for agriculture. Adv. Agron 124, 37–89 (2014).CAS 

    Google Scholar 
    García, A. C. et al. Vermicompost humic acids modulate the accumulation and metabolism of ROS in rice plants. J. Plant Physiol. 192, 56–63 (2016).
    Google Scholar 
    Dieleman, W. I. et al. Simple additive effects are rare: A quantitative review of plant biomass and soil process responses to combined manipulations of CO2 and temperature. Glob. Chang. Biol. 18, 2681–2693 (2012).
    Google Scholar 
    Muhammad, Q. et al. Yield sustainability, soil organic carbon sequestration, and nutrients balance under long-term combined application of manure and inorganic fertilizers in acidic paddy soil. Soil Till. Res. 198, 104509 (2020).
    Google Scholar 
    Zhang, X. et al. Benefits and trade-offs of replacing synthetic fertilizers by animal manures in crop production in China: A meta‐analysis. Glob. Chang. Biol. 26, 888–900 (2020).
    Google Scholar 
    Zhang, X. et al. Significant residual effects of wheat fertilization on greenhouse gas emissions in succeeding soybean growing season. Soil Till. Res. 169, 7–15 (2017).
    Google Scholar 
    Latare, A. M., Kumar, O., Singh, S. K. & Gupta, A. Direct and residual effect of sewage sludge on yield, heavy metals content and soil fertility under rice–wheat system. Ecol. Eng. 69, 17–24 (2014).
    Google Scholar 
    Zhang, J. et al. Long-term straw incorporation increases rice yield stability under high fertilization level conditions in the rice–wheat system. Crop J. 9, 1191–1197 (2021).
    Google Scholar 
    Pachauri, R. K. et al. Climate change 2014: Synthesis Report. Contribution of Working Groups I, II, and III to the fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC, 2014).Choi, W. J., Lee, M. S., Choi, J. E., Yoon, S. & Kim, H. Y. How do weather extremes affect rice productivity in a changing climate? An answer to episodic lack of sunshine. Glob. Chang. Biol. 19, 1300–1310 (2013).
    Google Scholar 
    FAO. FAOSTAT Online Statistical Service. https://www.fao.org/faostat/en/#data/RFN, (FAO, 2016).Carlson, K. M. et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Chang. 7, 63–68 (2017).CAS 

    Google Scholar 
    Sheldrick, W., Syers, J. K. & Lingard, J. Contribution of livestock excreta to nutrient balances. Nutr. Cycling Agroecosyst. 66, 119–131 (2003).
    Google Scholar 
    Thangarajan, R., Bolan, N. S., Tian, G., Naidu, R. & Kunhikrishnan, A. Role of organic amendment application on greenhouse gas emission from soil. Sci. Total Environ. 465, 72–96 (2013).CAS 

    Google Scholar 
    Aryal, J. P. et al. Factors affecting farmers’ use of organic and inorganic fertilizers in South Asia. Environ. Sci. Pollut. Res. 28, 51480–51496 (2021).CAS 

    Google Scholar 
    Zhang, Q. et al. Targeting hotspots to achieve sustainable nitrogen management in China’s smallholder-dominated cereal production. Agronomy 11, 557 (2021).
    Google Scholar 
    Tyagi, V. K. et al. Anaerobic co-digestion of organic fraction of municipal solid waste (OFMSW): Progress and challenges. Renewable Sustain. Energy Rev. 93, 380–399 (2018).
    Google Scholar 
    Schlesinger, W. H. Carbon sequestration in soils: Some cautions amidst optimism. Agric. Ecosyst. Environ. 82, 121–127 (2000).CAS 

    Google Scholar 
    Potter, P., Ramankutty, N., Bennett, E. M. & Donner, S. D. Characterizing the spatial patterns of global fertilizer application and manure production. Earth Interact. 14, 1–22 (2010).
    Google Scholar 
    Zhao, F., Yang, L., Chen, L., Li, S. & Sun, L. Bioaccumulation of antibiotics in crops under long-term manure application: Occurrence, biomass response, and human exposure. Chemosphere 219, 882–895 (2019).CAS 

    Google Scholar 
    Chadwick, D. R. et al. Strategies to reduce nutrient pollution from manure management in China. Front. Agr. Sci. Eng. 7, 45–55 (2020).
    Google Scholar 
    Jin, S. et al. Decoupling livestock and crop production at the household level in China. Nat. Sustain 4, 48–55 (2021).
    Google Scholar 
    Chen, D., Yuan, L., Liu, Y., Ji, J. & Hou, H. Long-term application of manures plus chemical fertilizers sustained high rice yield and improved soil chemical and bacterial properties. Eur. J. Agron. 90, 34–42 (2017).
    Google Scholar 
    Siddik, M. A. et al. Responses of indica rice yield and quality to extreme high and low temperatures during the reproductive period. Eur. J. Agron. 106, 30–38 (2019).
    Google Scholar 
    Bates, L. S., Waldren, R. P. & Teare, I. D. Rapid determination of free proline for water stress studies. Plant Soil 39, 205–207 (1973).CAS 

    Google Scholar 
    Page, A. L., Miller, R. H. & Dennis, R. K. Methods of Soil Analysis. Part 2 Chemical Methods (ed Page, A. L.) (Soil Science Society of America, 1982).Black, C. A. Methods of Soil Analysis Part II. Chemical and Microbiological Properties (ed Norman, A. G.) (American Society of Agriculture, 1965).Murphy, J. & Riley, J. P. A modified single solution method for the determination of phosphate in natural waters. Anal. Chim. Acta 27, 31–36 (1962).CAS 

    Google Scholar 
    Knudsen, D., Peterson, G. A. & Pratt, P. F. Methods of Soil Analysis. Part 2. Chemical and Microbiological Properties (ed Page, A. L.) (American Society of Agriculture, 1982).Olsen, S. R. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate (United States Department of Agriculture Circular, 1954).Lewis, S. L., Brando, P. M., Phillips, O. L., Van Der Heijden, G. M. F. & Nepstad, D. The 2010 amazon drought. Science 331, 554–554 (2011).CAS 

    Google Scholar 
    Hedges, L. V., Gurevitch, J. & Curtis, P. S. The meta‐analysis of response ratios in experimental ecology. Ecology 80, 1150–1156 (1999).
    Google Scholar 
    van Groenigen, K. J., Van Kessel, C. & Hungate, B. A. Increased greenhouse-gas intensity of rice production under future atmospheric conditions. Nat. Clim. Chang. 3, 288–291 (2013).
    Google Scholar 
    Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biogeochem. Cycles 22, GB1022 (2008).
    Google Scholar 
    Laborte, A. G. et al. RiceAtlas, a spatial database of global rice calendars and production. Sci. Data 4, 170074 (2017).
    Google Scholar  More

  • in

    Regenerative living cities and the urban climate–biodiversity–wellbeing nexus

    CIAT Global Rural-Urban Mapping Project, v1 (GRUMPv1): Urban Extents Grid (NASA SEDAC, 2011).Global Status Report for Buildings and Construction: Towards a Zero-Emission, Efficient and Resilient Buildings and Construction Sector (UNEP, 2020).Harris, N. L. et al. Nat. Clim. Change 11, 234–240 (2021).Article 

    Google Scholar 
    Reid, W. V. et al. Ecosystems and Human Well-being: Biodiversity Synthesis (Millenium Ecosystem Assessment, World Resources Institute, 2005).Xu, C. et al. Resour. Conserv. Recycl. 151, 104478 (2019).Article 

    Google Scholar 
    Su, J., Friess, D. A. & Gasparatos, A. Nat. Commun. 12, 5050 (2021).CAS 
    Article 

    Google Scholar 
    van den Berg, M. et al. Urban For. Urban Green. 14, 806–816 (2015).Article 

    Google Scholar 
    Aerts, R., Honnay, O. & Van Nieuwenhuyse, A. Br. Med. Bull. 127, 5–22 (2018).Article 

    Google Scholar 
    Lindenmayer, D. et al. Ecol. Lett. 11, 78–91 (2008).
    Google Scholar 
    Knapp, S., Jaganmohan, M. & Schwarz, N. in Atlas of Ecosystem Services: Drivers, Risks, and Societal Responses (eds Schröter, M. et al.) 167–172 (Springer, 2019).Kim, H. Y. Geomat. Nat. Hazards Risk 12, 1181–1194 (2021).Article 

    Google Scholar 
    Vargas-Hernández, J. G., Pallagst, K. & Zdunek-Wielgołaska, J. in Handbook of Engaged Sustainability (ed. Marques, J.) 885–916 (Springer, 2018).Manso, M. et al. Renew. Sustain. Energy Rev. 135, 110111 (2021).Article 

    Google Scholar 
    Assimakopoulos, M.-N. et al. Sustainability 12, 3772 (2020).CAS 
    Article 

    Google Scholar 
    Mora-Melià, D. et al. Sustainability 10, 1130 (2018).Article 

    Google Scholar 
    IPBES. Curr. Opin. Environ. Sustain. 26, 7–16 (2017).
    Google Scholar 
    Schröpfer, T. & Menz, S. in Dense and Green Building Typologies: Research, Policy and Practice Perspectives (eds Schröpfer, T. & Menz, S.) 1–4 (Springer, 2019).Pedersen Zari, M. & Hecht, K. Biomimetics 5, 18 (2020).Article 

    Google Scholar  More

  • in

    Chaos is not rare in natural ecosystems

    May, R. M. Biological populations with nonoverlapping generations: stable points, stable cycles, and chaos. Science 186, 645–647 (1974).CAS 
    PubMed 
    Article 

    Google Scholar 
    Beddington, J. R., Free, C. A. & Lawton, J. H. Dynamic complexity in predator–prey models framed in difference equations. Nature 255, 58–60 (1975).Article 

    Google Scholar 
    Hastings, A., Hom, C. L., Ellner, S., Turchin, P. & Godfray, H. C. J. Chaos in ecology: is Mother Nature a strange attractor? Annu. Rev. Ecol. Syst. 24, 1–33 (1993).Article 

    Google Scholar 
    Cressie, N. & Wikle, C. K. Statistics for Spatio-Temporal Data (John Wiley & Sons, 2011).The State of World Fisheries and Aquaculture 2020 (FAO, 2020).Hastings, A. & Powell, T. Chaos in a three-species food chain. Ecology 72, 896–903 (1991).Article 

    Google Scholar 
    Huisman, J. & Weissing, F. J. Biodiversity of plankton by species oscillations and chaos. Nature 402, 407–410 (1999).Article 

    Google Scholar 
    Doebeli, M. & Ispolatov, I. Chaos and unpredictability in evolution. Evolution 68, 1365–1373 (2014).PubMed 
    Article 

    Google Scholar 
    Pearce, M. T., Agarwala, A. & Fisher, D. S. Stabilization of extensive fine-scale diversity by ecologically driven spatiotemporal chaos. Proc. Natl Acad. Sci. USA 117, 14572–14583 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Costantino, R. F., Desharnais, R. A., Cushing, J. M. & Dennis, B. Chaotic dynamics in an insect population. Science 275, 389–391 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Becks, L., Hilker, F. M., Malchow, H., Jürgens, K. & Arndt, H. Experimental demonstration of chaos in a microbial food web. Nature 435, 1226–1229 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Benincá, E. et al. Chaos in a long-term experiment with a plankton community. Nature 451, 822–825 (2008).PubMed 
    Article 
    CAS 

    Google Scholar 
    Tilman, D. & Wedin, D. Oscillations and chaos in the dynamics of a perennial grass. Nature 353, 653–655 (1991).Article 

    Google Scholar 
    Turchin, P. & Ellner, S. P. Living on the edge of chaos: population dynamics of fennoscandian voles. Ecology 81, 3099–3116 (2000).Article 

    Google Scholar 
    Ferrari, M. J. et al. The dynamics of measles in sub-Saharan Africa. Nature 451, 679–684 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Benincà, E., Ballantine, B., Ellner, S. P. & Huisman, J. Species fluctuations sustained by a cyclic succession at the edge of chaos. Proc. Natl Acad. Sci. USA 112, 6389–6394 (2015).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Hassell, M. P., Lawton, J. H. & May, R. M. Patterns of dynamical behaviour in single-species populations. J. Anim. Ecol. 45, 471–486 (1976).Article 

    Google Scholar 
    Sibly, R. M., Barker, D., Hone, J. & Pagel, M. On the stability of populations of mammals, birds, fish and insects. Ecol. Lett. 10, 970–976 (2007).PubMed 
    Article 

    Google Scholar 
    Shelton, A. O. & Mangel, M. Fluctuations of fish populations and the magnifying effects of fishing. Proc. Natl Acad. Sci USA. 108, 7075–7080 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Salvidio, S. Stability and annual return rates in amphibian populations. Amphib. Reptil. 32, 119–124 (2011).Article 

    Google Scholar 
    Snell, T. W. & Serra, M. Dynamics of natural rotifer populations. Hydrobiologia 368, 29–35 (1998).Article 

    Google Scholar 
    Gross, T., Ebenhöh, W. & Feudel, U. Long food chains are in general chaotic. Oikos 109, 135–144 (2005).Article 

    Google Scholar 
    Ispolatov, I., Madhok, V., Allende, S. & Doebeli, M. Chaos in high-dimensional dissipative dynamical systems. Sci. Rep. 5, 12506 (2015).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Clark, T. J. & Luis, A. D. Nonlinear population dynamics are ubiquitous in animals. Nat. Ecol. Evol. 4, 75–81 (2020).CAS 
    PubMed 
    Article 

    Google Scholar 
    Sivakumar, B., Berndtsson, R., Olsson, J. & Jinno, K. Evidence of chaos in the rainfall-runoff process. Hydrol. Sci. J. 46, 131–145 (2001).CAS 
    Article 

    Google Scholar 
    Hanski, I., Turchin, P., Korpimäki, E. & Henttonen, H. Population oscillations of boreal rodents: regulation by mustelid predators leads to chaos. Nature 364, 232–235 (1993).CAS 
    PubMed 
    Article 

    Google Scholar 
    Turchin, P. & Taylor, A. D. Complex dynamics in ecological time series. Ecology 73, 289–305 (1992).Article 

    Google Scholar 
    Munch, S. B., Brias, A., Sugihara, G. & Rogers, T. L. Frequently asked questions about nonlinear dynamics and empirical dynamic modelling. ICES J. Mar. Sci. 77, 1463–1479 (2020).Article 

    Google Scholar 
    Sugihara, G. & May, R. M. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature 344, 734–741 (1990).CAS 
    PubMed 
    Article 

    Google Scholar 
    Ellner, S. P. & Turchin, P. Chaos in a noisy world: new methods and evidence from time-series analysis. Am. Nat. 145, 343–375 (1995).Article 

    Google Scholar 
    Nychka, D., Ellner, S., Gallant, A. R. & McCaffrey, D. Finding chaos in noisy systems. J. R. Stat. Soc. B 54, 399–426 (1992).
    Google Scholar 
    Webber, C. L. & Zbilut, J. P. Dynamical assessment of physiological systems and states using recurrence plot strategies. J. Appl. Physiol. 76, 965–973 (1994).PubMed 
    Article 

    Google Scholar 
    Bandt, C. & Pompe, B. Permutation entropy: a natural complexity measure for time series. Phys. Rev. Lett. 88, 174102 (2002).PubMed 
    Article 
    CAS 

    Google Scholar 
    Luque, B., Lacasa, L., Ballesteros, F. & Luque, J. Horizontal visibility graphs: exact results for random time series. Phys. Rev. E 80, 46103 (2009).CAS 
    Article 

    Google Scholar 
    Toker, D., Sommer, F. T. & D’Esposito, M. A simple method for detecting chaos in nature. Commun. Biol. 3, 11 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pikovsky, A. & Politi, A. Lyapunov Exponents: A Tool to Explore Complex Dynamics (Cambridge Univ. Press, 2016).Rosenstein, M. T., Collins, J. J. & De Luca, C. J. A practical method for calculating largest Lyapunov exponents from small data sets. Physica D 65, 117–134 (1993).Article 

    Google Scholar 
    Dämmig, M. & Mitschke, F. Estimation of Lyapunov exponents from time series: the stochastic case. Phys. Lett. A 178, 385–394 (1993).Article 

    Google Scholar 
    Prendergast, J., Bazeley-White, E., Smith, O., Lawton, J. & Inchausti, P. The Global Population Dynamics Database (KNB, 2010); https://doi.org/10.5063/F1BZ63Z8Thibaut, L. M. & Connolly, S. R. Hierarchical modeling strengthens evidence for density dependence in observational time series of population dynamics. Ecology 101, e02893 (2020).PubMed 
    Article 

    Google Scholar 
    Knape, J. & de Valpine, P. Are patterns of density dependence in the Global Population Dynamics Database driven by uncertainty about population abundance? Ecol. Lett. 15, 17–23 (2012).PubMed 
    Article 

    Google Scholar 
    Takens, F. in Dynamical Systems and Turbulence (eds Rand, D. A. & Young, L. S.) 366–381 (Springer, 1981).Sugihara, G. Nonlinear forecasting for the classification of natural time series. Philos. Trans. R. Soc. A 348, 477–495 (1994).
    Google Scholar 
    Loh, J. et al. The Living Planet Index: using species population time series to track trends in biodiversity. Philos. Trans. R. Soc. B 360, 289–295 (2005).Article 

    Google Scholar 
    Kendall, B. E. Cycles chaos, and noise in predator–prey dynamics. Chaos Solitons Fractals 12, 321–332 (2001).Article 

    Google Scholar 
    Anderson, C. N. K. et al. Why fishing magnifies fluctuations in fish abundance. Nature 452, 835–839 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Anderson, D. M. & Gillooly, J. F. Allometric scaling of Lyapunov exponents in chaotic populations. Popul. Ecol. 62, 364–369 (2020).Article 

    Google Scholar 
    Graham, D. W. et al. Experimental demonstration of chaotic instability in biological nitrification. ISME J. 1, 385–393 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Turchin, P. Nonlinear time-series modeling of vole population fluctuations. Res. Popul. Ecol. 38, 121–132 (1996).Article 

    Google Scholar 
    Becks, L. & Arndt, H. Different types of synchrony in chaotic and cyclic communities. Nat. Commun. 4, 1359 (2013).PubMed 
    Article 
    CAS 

    Google Scholar 
    Becks, L. & Arndt, H. Transitions from stable equilibria to chaos, and back, in an experimental food web. Ecology 89, 3222–3226 (2008).PubMed 
    Article 

    Google Scholar 
    Rezende, E. L., Albert, E. M., Fortuna, M. A. & Bascompte, J. Compartments in a marine food web associated with phylogeny, body mass, and habitat structure. Ecol. Lett. 12, 779–788 (2009).PubMed 
    Article 

    Google Scholar 
    Krause, A. E., Frank, K. A., Mason, D. M., Ulanowicz, R. E. & Taylor, W. W. Compartments revealed in food-web structure. Nature 426, 282–285 (2003).CAS 
    PubMed 
    Article 

    Google Scholar 
    The IUCN Red List of Threatened Species Version 2020-2 (IUCN, 2020); https://www.iucnredlist.orgFreckleton, R. P. & Watkinson, A. R. Are weed population dynamics chaotic? J. Appl. Ecol. 39, 699–707 (2002).Article 

    Google Scholar 
    May, R. M. Simple mathematical models with very complicated dynamics. Nature 261, 459–467 (1976).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mora, C., Tittensor, D. P., Adl, S., Simpson, A. G. B. & Worm, B. How many species are there on Earth and in the ocean? PLoS Biol. 9, e1001127 (2011).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Munch, S. B., Giron-Nava, A. & Sugihara, G. Nonlinear dynamics and noise in fisheries recruitment: a global meta-analysis. Fish Fish. 19, 964–973 (2018).Article 

    Google Scholar 
    Boettiger, C., Harte, T., Chamberlain, S. & Ram, K. rgpdd: R Interface to the Global Population Dynamics Database. https://docs.ropensci.org/rgpdd, https://github.com/ropensci/rgpdd (2019).Brook, B. W., Traill, L. W. & Bradshaw, C. J. A. Minimum viable population sizes and global extinction risk are unrelated. Ecol. Lett. 9, 375–382 (2006).PubMed 
    Article 

    Google Scholar 
    Baars, J. W. M. Autecological investigations of marine diatoms, 2. Generation times of 50 species. Hydrobiol. Bull. 15, 137–151 (1981).Article 

    Google Scholar 
    Lavigne, A. S., Sunesen, I. & Sar, E. A. Morphological, taxonomic and nomenclatural analysis of species of Odontella, Trieres and Zygoceros (Triceratiaceae, Bacillariophyta) from Anegada Bay (Province of Buenos Aires, Argentina). Diatom Res. 30, 307–331 (2015).Article 

    Google Scholar 
    Anderson, D. M. & Gillooly, J. F. Physiological constraints on long-term population cycles: a broad-scale view. Evol. Ecol. Res. 18, 693–707 (2017).
    Google Scholar 
    Janes, M. J. Oviposition studies on the chinch bug, Blissus leucopterus (Say). Ann. Entomol. Soc. Am. 28, 109–120 (1935).Article 

    Google Scholar 
    Cook, L. M. Food-plant specialization in the moth Panaxia dominula L. Evolution 15, 478–485 (1961).Article 

    Google Scholar 
    Casey, T. M. Flight energetics of sphinx moths: power input during hovering flight. J. Exp. Biol. 64, 529–543 (1976).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kobayashi, A., Tanaka, Y. & Shimada, M. Genetic variation of sex allocation in the parasitoid wasp Heterospilus prosopidis. Evolution 57, 2659–2664 (2003).PubMed 
    Article 

    Google Scholar 
    Hozumi, N. & Miyatake, T. Body-size dependent difference in death-feigning behavior of adult Callosobruchus chinensis. J. Insect Behav. 18, 557–566 (2005).Article 

    Google Scholar 
    Huntley, M. E. & Lopez, M. D. G. Temperature-dependent production of marine copepods: a global synthesis. Am. Nat. 140, 201–242 (1992).CAS 
    PubMed 
    Article 

    Google Scholar 
    Cohen, R. E. & Lough, R. G. Length–weight relationships for several copepods dominant in the Georges Bank–Gulf of Maine area. J. Northwest Atl. Fish. Sci. 2, 47–52 (1981).Article 

    Google Scholar 
    World Register of Marine Species (WoRMS, accessed 1 November 2020); https://doi.org/10.14284/170Nakamura, Y. Growth and grazing of a large heterotrophic dinoflagellate, Noctiluca scintillans, in laboratory cultures. J. Plankton Res. 20, 1711–1720 (1998).Article 

    Google Scholar 
    Boulding, E. G. & Platt, T. Variation in photosynthetic rates among individual cells of a marine dinoflagellate. Mar. Ecol. Prog. Ser. 29, 199–203 (1986).CAS 
    Article 

    Google Scholar 
    Rimet, F. et al. The Observatory on LAkes (OLA) database: sixty years of environmental data accessible to the public. J. Limnol. https://doi.org/10.4081/jlimnol.2020.1944 (2020).Rudstam, L. Zooplankton Survey of Oneida Lake, New York, 1964 to Present (KNB, 2020); https://knb.ecoinformatics.org/view/kgordon.17.99https://knb.ecoinformatics.org/knb/metacat/kgordon.17.67/defaultDumont, H. J., Van de Velde, I. & Dumont, S. The dry weight estimate of biomass in a selection of Cladocera, Copepoda and Rotifera from the plankton, periphyton and benthos of continental waters. Oecologia 19, 75–97 (1975).PubMed 
    Article 

    Google Scholar 
    Geller, W. & Müller, H. Seasonal variability in the relationship between body length and individual dry weight as related to food abundance and clutch size in two coexisting Daphnia species. J. Plankton Res. 7, 1–18 (1985).Article 

    Google Scholar 
    Branstrator, D. K. Contrasting life histories of the predatory cladocerans Leptodora kindtii and Bythotrephes longimanus. J. Plankton Res. 27, 569–585 (2005).Article 

    Google Scholar 
    Rosen, R. A. Length–dry weight relationships of some freshwater zooplankton. J. Freshw. Ecol. 1, 225–229 (1981).Article 

    Google Scholar 
    Peters, R. H. & Downing, J. A. Empirical analysis of zooplankton filtering and feeding rates. Limnol. Oceanogr. 29, 763–784 (1984).Article 

    Google Scholar 
    Eckmann, J. P., Kamphorst, S. O. & Ruelle, D. Recurrence plots of dynamical systems. Europhys. Lett. 4, 973–977 (1987).Article 

    Google Scholar 
    Luque, B., Lacasa, L., Ballesteros, F. J. & Robledo, A. Analytical properties of horizontal visibility graphs in the Feigenbaum scenario. Chaos 22, 013109 (2012).PubMed 
    Article 

    Google Scholar 
    McCaffrey, D. F., Ellner, S., Gallant, A. R. & Nychka, D. W. Estimating the Lyapunov exponent of a chaotic system with nonparametric regression. J. Am. Stat. Assoc. 87, 682–695 (1992).Article 

    Google Scholar 
    Brown, J. H., Gillooly, J. F., Allen, A. P., Savage, V. M. & West, G. B. Toward a metabolic theory of ecology. Ecology 85, 1771–1789 (2004).Article 

    Google Scholar 
    Ricker, W. E. Stock and recruitment. J. Fish. Board Can. 11, 559–623 (1954).Article 

    Google Scholar  More