Ecology

Lenoir, J. et al. Species better track climate warming in the oceans than on land. Nat. Ecol. Evol. 4(8), 1044–1059 (2020).Article 

Google Scholar 
Hobbs, R. J., Valentine, L. E., Standish, R. J. & Jackson, S. T. Movers and stayers: Novel assemblages in changing environments. Trends Ecol. Evol. 33, 116–128 (2017).Article 

Google Scholar 
Gilman, S. E., Urban, M. C., Tewksbury, J., Gilchrist, G. W. & Holt, R. D. A framework for community interactions under climate change. Trends Ecol. Evol. 25, 325–331 (2010).Article 

Google Scholar 
Ockendon, N. et al. Mechanisms underpinning climatic impacts on natural populations: Altered species interactions are more important than direct effects. Glob. Change Biol. 20, 2221–2229 (2014).Article 
ADS 

Google Scholar 
Gómez-Aparicio, L., García-Valdés, R., Ruíz-Benito, P. & Zavala, M. A. Disentangling the relative importance of climate, size and competition on tree growth in Iberian forests: Implications for forest management under global change. Glob. Change Biol. 17, 2400–2414 (2011).Article 
ADS 

Google Scholar 
Pecl, G. T. et al. Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being. Science https://doi.org/10.1126/science.aai9214 (2017).Article 

Google Scholar 
Scheffers, B. R. et al. The broad footprint of climate change from genes to biomes to people. Science 354, aaf7671. https://doi.org/10.1126/science.aaf7671 (2016).Article 
CAS 

Google Scholar 
Vergés, A. et al. The tropicalization of temperate marine ecosystems: Climate-mediated changes in herbivory and community phase shifts. Proc. R. Soc. B-Biol. Sci. 281, 20140846. https://doi.org/10.1098/rspb.2014.0846 (2014).Article 

Google Scholar 
Poore, A. G. B. et al. Global patterns in the impact of marine herbivores on benthic primary producers. Ecol. Lett. 15, 912–922. https://doi.org/10.1111/j.1461-0248.2012.01804.x (2012).Article 

Google Scholar 
Bennett, S., Wernberg, T., Harvey, E. S., Santana-Garcon, J. & Saunders, B. J. Tropical herbivores provide resilience to a climate-mediated phase shift on temperate reefs. Ecol. Lett. 18, 714–723 (2015).Article 

Google Scholar 
Vergés, A. et al. Long-term empirical evidence of ocean warming leading to tropicalization of fish communities, increased herbivory and loss of kelp. Proc. Natl. Acad. Sci. 113(48), 13791–13796 (2016).Article 
ADS 

Google Scholar 
Vergés, A. et al. Tropical rabbitfish and the deforestation of a warming temperate sea. J. Ecol. 102, 1518–1527. https://doi.org/10.1111/1365-2745.12324 (2014).Article 

Google Scholar 
Kumagai, N. H. et al. Ocean currents and herbivory drive macroalgae-to-coral community shift under climate warming. Proc. Natl. Acad. Sci. 115, 8990–8995 (2018).Article 
ADS 
CAS 

Google Scholar 
Demko, A. M. et al. Declines in plant palatability from polar to tropical latitudes depend on herbivore and plant identity. Ecology 98, 2312–2321. https://doi.org/10.1002/ecy.1918 (2017).Article 

Google Scholar 
Floeter, S. R., Behrens, M. D., Ferreira, C. E. L., Paddack, M. J. & Horn, M. H. Geographical gradients of marine herbivorous fishes: Patterns and processes. Mar Biol 147, 1435–1447 (2005).Article 

Google Scholar 
Longo, G. O., Hay, M. E., Ferreira, C. E. L. & Floeter, S. R. Trophic interactions across 61 degrees of latitude in the Western Atlantic. Glob. Ecol. Biogeogr. 28, 107–117. https://doi.org/10.1111/geb.12806 (2019).Article 

Google Scholar 
Bolser, R. & Hay, M. Are tropical plants better defended? Palatability and defenses of temperate versus tropical seaweeds. Ecology 77, 2269–2286 (1996).Article 

Google Scholar 
Borer, E. T. et al. Global biogeography of autotroph chemistry: is insolation a driving force?. Oikos 122, 1121–1130. https://doi.org/10.1111/j.1600-0706.2013.00465.x (2013).Article 
CAS 

Google Scholar 
Miranda, T. et al. Convictfish on the move: Variation in growth and trophic niche space along a latitudinal gradient. ICES J. Mar. Sci. https://doi.org/10.1093/icesjms/fsz098%JICESJournalofMarineScience (2019).Article 

Google Scholar 
Linton, S. M. The structure and function of cellulase (endo-β-1, 4-glucanase) and hemicellulase (β-1, 3-glucanase and endo-β-1, 4-mannase) enzymes in invertebrates that consume materials ranging from microbes, algae to leaf litter. Comp. Biochem. Physiol. B Biochem. Mol. Biol. 240, 110354 (2020).Article 
CAS 

Google Scholar 
Poloczanska, E. S. et al. Global imprint of climate change on marine life. Nat. Clim. Change 3, 919–925. https://doi.org/10.1038/nclimate1958 (2013).Article 
ADS 

Google Scholar 
Nakamura, Y., Feary, D. A., Kanda, M. & Yamaoka, K. Tropical fishes dominate temperate reef fish communities within western Japan. PLoS ONE 8, e81107 (2013).Article 
ADS 

Google Scholar 
Tanaka, K., Taino, S., Haraguchi, H., Prendergast, G. & Hiraoka, M. Warming off southwestern Japan linked to distributional shifts of subtidal canopy-forming seaweeds. Ecol. Evol. 2, 2854–2865. https://doi.org/10.1002/ece3.391 (2012).Article 

Google Scholar 
Pessarrodona, A. et al. Homogenization and miniaturization of habitat structure in temperate marine forests. Glob. Change Biol. 27, 5262–5275 (2021).Article 
CAS 

Google Scholar 
Yamano, H., Sugihara, K. & Nomura, K. Rapid poleward range expansion of tropical reef corals in response to rising sea surface temperatures. Geophys. Res. Lett. 38, L04601. https://doi.org/10.1029/2010gl046474 (2011).Article 
ADS 

Google Scholar 
Mezaki, T. & Kubota, S. Changes of hermatypic coral community in coastal sea area of Kochi, high-latitude Japan. Aquabiology 201, 332–337 (2012).
Google Scholar 
Serisawa, Y., Imoto, Z., Ishikawa, T. & Ohno, M. Decline of the Ecklonia cava population associated with increased seawater temperatures in Tosa Bay, southern Japan. Fish Sci 70, 189–191. https://doi.org/10.1111/j.0919-9268.2004.00788.x (2004).Article 
CAS 

Google Scholar 
Kiriyama, T., Mitsunaga, N., Yasumoto, S., Fujii, A. & Yotsui, T. Undergrown phenomenon of brown alga, Hizikia fusiformis, thought to be caused by grazing of herbivores at Tsutsuura, Tsushima Islands [Japan]. Bulletin of Nagasaki Prefectural Institute of Fisheries (Japan) (1999).Kiriyama, T., Fujii, A. & Fujita, Y. Feeding and characteristic bite marks on Sargassum fusiforme by several herbivorous fishes. Aquac. Sci. 53, 355–365 (2005).
Google Scholar 
Yatsuya, K., Kiriyama, T., Kiyomoto, S., Taneda, T. & Yoshimura, T. On the deterioration process of Ecklonia and Eisenia beds observed in 2013 at Gounoura, Iki Island, Nagasaki Prefecture, Japan.-Initiation of the bed degradation due to high water temperature in summer and subsequent cascading effect by the grazing of herbivorous fish in autumn. Algal Resour. 7, 79–94 (2014).
Google Scholar 
Noda, M., Ohara, H., Murase, N., Ikeda, I. & Yamamoto, K. The grazing of Eisenia bicyclis and several species of Sargassaceous and Cystoseiraceous seaweeds by Siganus fuscescens in relation to the differences of species composition of their seaweed beds. Nippon Suisan Gakkaishi 80, 201–213 (2014).Article 

Google Scholar 
Noda, M., Kinoshita, J., Tanada, N. & Murase, N. Characteristics of bite scars observed in kelp forests of Lessoniaceae denuded by short-term foraging damages of the herbivorous fish Siganus fuscecens. J. Natl. Fish. Univ. 66, 111–122 (2018).
Google Scholar 
Wernberg, T. et al. Seaweed communities in retreat from ocean warming. Curr. Biol. 21, 1828–1832. https://doi.org/10.1016/j.cub.2011.09.028 (2011).Article 
CAS 

Google Scholar 
Terazono, Y., Nakamura, Y., Imoto, Z. & Hiraoka, M. Fish response to expanding tropical Sargassum beds on the temperate coasts of Japan. Mar. Ecol. Prog. Ser. 464, 209–220. https://doi.org/10.3354/meps09873 (2012).Article 
ADS 

Google Scholar 
Duffy, J. E. & Hay, M. E. Seaweed adaptations to herbivory – chemical, structural, and morphological defenses are often adjusted to spatial or temporal patterns of attack. Bioscience 40, 368–375 (1990).Article 

Google Scholar 
Endo, H., Suehiro, K., Kinoshita, J. & Agatsuma, Y. Combined effects of temperature and nutrient enrichment on palatability of the brown alga Sargassum yezoense (Yamada) Yoshida & T. Konno. Am. J. Plant Sci. 6, 275 (2015).Article 
CAS 

Google Scholar 
Clements, K. D., German, D. P., Piché, J., Tribollet, A. & Choat, J. H. Integrating ecological roles and trophic diversification on coral reefs: Multiple lines of evidence identify parrotfishes as microphages. Biol. J. Linn. Soc. 120, 729–751. https://doi.org/10.1111/bij.12914 (2017).Article 

Google Scholar 
Wang, Y., Naumann, U., Wright, S. T. & Warton, D. I. mvabund–an R package for model-based analysis of multivariate abundance data. Methods Ecol. Evol. 3, 471–474 (2012).Article 

Google Scholar 
Wilson, S. K., Bellwood, D. R., Choat, J. H. & Furnas, M. J. Detritus in the epilithic algal matrix and its use by coral reef fishes. Oceanogr. Mar. Biol. Annu. Rev. 41, 279–309 (2003).
Google Scholar 
Helfman, G. S. in The Behaviour of Teleost Fishes 366–387 (Springer, 1986).Prince, J., LeBlanc, W. & Maciá, S. Design and analysis of multiple choice feeding preference data. Oecologia 138, 1–4 (2004).Article 
ADS 

Google Scholar 
Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. R package version 0.3 3 (2020).Ohno, M. & Ishikawa, M. Physiological ecology of brown alga, Ecklonia on coast of Tosa Bay, southern Japan. I. Seasonal variation of Ecklonia bed. Rep. USA Marine Biol. Inst. Kochi Univ. 4, 59–73 (1982).
Google Scholar 
Agostini, S. et al. Simplification, not “tropicalization”, of temperate marine ecosystems under ocean warming and acidification. Glob. Change Biol. 27, 4771–4784 (2021).Article 
CAS 

Google Scholar 
Clements, K. & Choat, J. Influence of season, ontogeny and tide on the diet of the temperate marine herbivorous fish Odax pullus (Odacidae). Mar. Biol. 117, 213–220 (1993).Article 

Google Scholar 
Mizuta, H., Hayasaki, J. & Yamamoto, H. Relationship between nitrogen content and sorus formation in the brown alga Laminaria japonica cultivated in southern Hokkaido, Japan. Fish. Sci. 64, 909–913 (1998).Article 
CAS 

Google Scholar 
Kumura, T., Yasui, H. & Mizuta, H. Nutrient requirement for zoospore formation in two alariaceous plants Undaria pinnatifida (Harvey) Suringar and Alaria crassifolia Kjellman (Phaeophyceae: Laminariales). Fish. Sci. 72, 860–869 (2006).Article 
CAS 

Google Scholar 
Qiu, Z. et al. Future climate change is predicted to affect the microbiome and condition of habitat-forming kelp. Proc. R. Soc. B 286, 20181887 (2019).Article 

Google Scholar 
Hoey, A. S. & Bellwood, D. R. Limited functional redundancy in a high diversity system: Single species dominates key ecological process on coral reefs. Ecosystems 12, 1316–1328. https://doi.org/10.1007/s10021-009-9291-z (2009).Article 

Google Scholar 
Streit, R. P., Hoey, A. S. & Bellwood, D. R. Feeding characteristics reveal functional distinctions among browsing herbivorous fishes on coral reefs. Coral Reefs 34, 1037–1047 (2015).Article 
ADS 

Google Scholar 
Van Alstyne, K. L. & Paul, V. J. The biogeography of polyphenolic compounds in marine macroalgae – Temperate brown algal defenses deter feeding by tropical herbivorous fishes. Oecologia 84, 158–163 (1990).Article 
ADS 

Google Scholar 
Targett, N. M., Boettcher, A. A., Targett, T. E. & Vrolijk, N. H. Tropical marine herbivore assimilation of phenolic-rich plants. Oecologia 103, 170–179 (1995).Article 
ADS 

Google Scholar 
Prado, P. & Heck, K. L. Seagrass selection by omnivorous and herbivorous consumers: Determining factors. Mar. Ecol. Prog. Ser. 429, 45–55. https://doi.org/10.3354/meps09076 (2011).Article 
ADS 

Google Scholar 
Montgomery, W. L. & Gerking, S. D. Marine macroalgae as foods for fishes: an evaluation of potential food quality. Environ. Biol. Fish. 5, 143–153 (1980).Article 

Google Scholar 
Duffy, J. & Paul & V.J.,. Prey nutritional quality and the effectiveness of chemical defenses against tropical reef fishes. Oecologia 90, 333–339 (1992).Article 
ADS 
CAS 

Google Scholar 
Michael, P. J., Hyndes, G. A., Vanderklift, M. A. & Vergés, A. Identity and behaviour of herbivorous fish influence large-scale spatial patterns of macroalgal herbivory in a coral reef. Mar. Ecol. Prog. Ser. 482, 227–240 (2013).Article 
ADS 

Google Scholar 
Bennett, S. & Bellwood, D. R. Latitudinal variation in macroalgal consumption by fishes on the Great Barrier Reef. Mar. Ecol. Prog. Ser. 426, 241–252 (2011).Article 
ADS 

Google Scholar 
Zarco-Perello, S., Wernberg, T., Langlois, T. J. & Vanderklift, M. A. Tropicalization strengthens consumer pressure on habitat-forming seaweeds. Sci. Rep. 7, 820. https://doi.org/10.1038/s41598-017-00991-2 (2017).Article 
ADS 
CAS 

Google Scholar 
Smith, S. M. et al. Tropicalisation and kelp loss shift trophic composition and lead to more winners than losers in fish communities. Glob. Change Biol. 27(11), 2537–2548 (2021).Article 
ADS 
CAS 

Google Scholar 
Zarco-Perello, S. et al. Range-extending tropical herbivores increase diversity, intensity and extent of herbivory functions in temperate marine ecosystems. Funct. Ecol. 34, 2411–2421. https://doi.org/10.1111/1365-2435.13662 (2020).Article 

Google Scholar  More

Narayan, S. et al. The effectiveness, costs and coastal protection benefits of natural and nature-based defences. PLoS ONE 11, e0154735 (2016).Article 

Google Scholar 
Schürch, M., Rapaglia, J., Liebetrau, V., Vafeidis, A. T. & Reise, K. Salt marsh accretion and storm tide variation: An example from a barrier island in the North Sea. ESCO 35, 486–500 (2012).
Google Scholar 
de Groot, A. V., Veeneklaas, R. M., Kuijper, D. P. & Bakker, J. P. Spatial patterns in accretion on barrier-island salt marshes. Geomorphology 134, 280–296 (2011).Article 
ADS 

Google Scholar 
Temmerman, S. et al. Ecosystem-based coastal defence in the face of global change. Nature 504, 79–83 (2013).Article 
ADS 
CAS 

Google Scholar 
Barbier, E. B. et al. Coastal ecosystem: Based management with nonlinear ecologial functions and values. Science 319, 321–323 (2008).Article 
ADS 
CAS 

Google Scholar 
Schoonees, T. et al. Hard structures for coastal protection, towards greener designs. Estuaries Coasts 21, 755 (2019).
Google Scholar 
IPCC. Summary for Policymakers. in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (2021).Lenssen, G. M., Lamers, J., Stroetenga, M. & Rozema, J. CO2 and biosphere 379–390 (Kluwer Academic Publishers, 1993).Book 

Google Scholar 
Cherry, J. A., McKee, K. L. & Grace, J. B. Elevated CO2 enhances biological contributions to elevation change in coastal wetlands by offsetting stressors associated with sea-level rise. J. Ecol. 97, 67–77 (2009).Article 

Google Scholar 
Arp, W. J., Drake, B. G., Pockman, W. T., Curtis, P. S. & Whigham, D. F. CO2 and Biosphere 133–143 (Kluwer Academic Publishers, 1993).Book 

Google Scholar 
Cao, H. et al. Wave effects on seedling establishment of three pioneer marsh species: survival, morphology and biomechanics. Ann. Bot. 125, 345–352 (2020).Article 

Google Scholar 
Puijalon, S. et al. Plant resistance to mechanical stress: Evidence of an avoidance-tolerance trade-off. New Phytol. 191, 1141–1149 (2011).Article 
CAS 

Google Scholar 
Niklas, K. Plant Biomechanics: An Engineering Approach to Plant Form and Function (University of Chicago Press, 1992).
Google Scholar 
Silinski, A. et al. Effects of wind waves versus ship waves on tidal marsh plants: A flume study on different life stages of Scirpus maritimus. PLoS ONE 10, e0118687 (2015).Article 

Google Scholar 
Rupprecht, F., Möller, I., Evans, B. R., Spencer, T. & Jensen, K. Biophysical properties of salt marsh canopies: Quantifying plant stem flexibility and above ground biomass. Coast. Eng. 100, 48–57 (2015).Article 

Google Scholar 
Paul, M. & de los Santos, C. B. Variation in flexural, morphological, and biochemical leaf properties of eelgrass (Zostera marina) along the European Atlantic climate regions. Mar. Biol. 166, 2187 (2019).Article 

Google Scholar 
Carus, J., Paul, M. & Schröder, B. Vegetation as self-adaptive coastal protection: Reduction of current velocity and morphologic plasticity of a brackish marsh pioneer. Ecol. Evol. 6, 1579–1589 (2016).Article 

Google Scholar 
Callaghan, F. M. et al. A submersible device for measuring drag forces on aquatic plants and other organisms. NZ J. Mar. Freshw. Res. 41, 119–127 (2007).Article 

Google Scholar 
Paul, M., Bouma, T. J. & Amos, C. L. Wave attenuation by submerged vegetation: combining the effect of organism traits and tidal current. Mar. Ecol. Prog. Ser. 444, 31–41 (2012).Article 
ADS 

Google Scholar 
Taphorn, M., Villanueva, R., Paul, M., Visscher, J. H. & Schlurmann, T. Flow field and wake structure characteristics imposed by single seagrass blade surrogates. J. Ecohydraul. 1, 1–13 (2021).
Google Scholar 
Lightbody, A. F. & Nepf, H. M. Prediction of velocity profiles and longitudinal dispersion in emergent salt marsh vegetation. Limnol. Oceangr 51, 218–228 (2006).Article 
ADS 

Google Scholar 
Kobayashi, N., Raichle, A. W. & Asano, T. Wave attenuation by vegetation. J. Waterway Port Coastal Ocean Eng. 119, 30–48 (1993).Article 

Google Scholar 
Villanueva, R., Thom, M., Visscher, J. H., Paul, M. & Schlurmann, T. Wake length of an artificial seagrass meadow: A study of shelter and its feasibility for restoration. J. Ecohydraul. 1, 1–15 (2021).
Google Scholar 
Paul, M. & Amos, C. L. Spatial and seasonal variation in wave attenuation over Zostera noltii. J. Geophys. Res. 116, C08019 (2011).ADS 

Google Scholar 
Marjoribanks, T. I. & Paul, M. Modelling flow-induced reconfiguration of variable rigidity aquatic vegetation. J. Hydraul. Res. 1, 1–16 (2021).
Google Scholar 
Schulze, D., Rupprecht, F., Nolte, S. & Jensen, K. Seasonal and spatial within-marsh differences of biophysical plant properties: Implications for wave attenuation capacity of salt marshes. Aquat. Sci. 81, 82 (2019).Article 

Google Scholar 
Gillis, L. G. et al. Living on the edge: How traits of ecosystem engineers drive bio-physical interactions at coastal wetland edges. Adv. Water Resour. 166, 104257 (2022).Article 

Google Scholar 
Zhao, H. & Chen, Q. Modeling attenuation of storm surge over deformable vegetation: methodology and verification. J. Eng. Mech. 140, 4014090 (2014).
Google Scholar 
Möller, I. et al. Wave attenuation over coastal salt marshes under storm surge conditions. Nat. Geosci 7, 727–731 (2014).Article 
ADS 

Google Scholar 
Maza, M. et al. Large-scale 3-D experiments of wave and current interaction with real vegetation. Part 2. Experimental analysis. Coast. Eng. 106, 73–86 (2015).Article 

Google Scholar 
Gray, A. J. & Mogg, R. J. Climate impacts on pioneer saltmarsh plants. Clim. Res. 18, 105–112 (2001).Article 

Google Scholar 
Novaes, E., Kirst, M., Chiang, V., Winter-Sederoff, H. & Sederoff, R. Lignin and biomass: A negative correlation for wood formation and lignin content in trees. Plant Physiol. 154, 555–561 (2010).Article 
CAS 

Google Scholar 
Redfield, A. C. Development of a New England salt marsh. Ecol. Monogr. 42, 201–237 (1972).Article 

Google Scholar 
Kirwan, M. L. et al. Limits on the adaptability of coastal marshes to rising sea level. Geophys. Res. Lett. 37, 1–10 (2010).Article 

Google Scholar 
Idier, D., Dumas, F. & Muller, H. Tide-surge interaction in the English Channel. Nat. Hazards Earth Syst. Sci. 12, 3709–3718 (2012).Article 
ADS 

Google Scholar 
Weisse, R., von Storch, H., Niemeyer, H. D. & Knaack, H. Changing North Sea storm surge climate: An increasing hazard?. Ocean Coast. Manag. 68, 58–68 (2012).Article 

Google Scholar 
Idier, D., Paris, F., Le Cozannet, G., Boulahya, F. & Dumas, F. Sea-level rise impacts on the tides of the European Shelf. Cont. Shelf Res. 137, 56–71 (2017).Article 
ADS 

Google Scholar 
Marcos, M., Calafat, F. M., Berihuete, Á. & Dangendorf, S. Long-term variations in global sea level extremes. J. Geophys. Res. Oceans 120, 8115–8134 (2015).Article 
ADS 

Google Scholar 
Dangendorf, S., Mudersbach, C., Jensen, J., Anette, G. & Heinrich, H. Seasonal to decadal forcing of high water level percentiles in the German Bight throughout the last century. Ocean Dyn. 46, 277 (2013).
Google Scholar 
de Winter, R. C., Sterl, A. & Ruessink, B. G. Wind extremes in the North Sea Basin under climate change: An ensemble study of 12 CMIP5 GCMs. J. Geophys. Res. Atmos. 118, 1601–1612 (2013).Article 
ADS 

Google Scholar 
Arns, A. et al. Sea-level rise induced amplification of coastal protection design heights. Sci. Rep. 7, 40171 (2017).Article 
ADS 
CAS 

Google Scholar 
Pansch, A., Winde, V., Asmus, R. & Asmus, H. Tidal benthic mesocosms simulating future climate change scenarios in the field of marine ecology. Limnol. Oceanogr. Methods 14, 257–267 (2016).Article 

Google Scholar 
Meehl, G. A. et al. Climate Change 2007: The Physical Science Basis: Summary for Policymakers. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2007).
Google Scholar 
Miler, O., Albayrak, I., Nikora, V. I. & O’Hare, M. T. Biomechanical properties of aquatic plants and their effects on plant–flow interactions in streams and rivers. Aquat. Sci. 74, 31–44 (2012).Article 

Google Scholar  More

Chemotaxonomic characteristicsThe predominant respiratory quinone for all novel strains was ubiquinone 8 (Q-8), consistent with other Ramlibacter species. C16:0 and summed feature 3 (consisting of C16:1 ω7c and/or C16:1 ω6c) were identified as the common major fatty acids ( > 10%) of the novel strains USB13T, AW1T, GTP1T, and HM2T. Other than the aforementioned fatty acids, strain USB13T had C10:0 3-OH additionally as its major fatty acid, whereas strains AW1T and HM2T shared C17:0 cyclo and summed feature 8 (consisting of C18:1 ω7c and/or C18: 1 ω6c) as its additional fatty acids. Detailed comparisons of the fatty acid profiles of the novel strains and their reference strains are summarized in Table S1.Strains USB13T, AW1T, GTP1T, and HM2T shared major polar lipids diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), and phosphatidylethanolamine (PE), which was consistent with the major polar lipids of the reference strains. Additionally, the polar lipid profile of USB13T consisted of one unidentified phosphoaminolipid, two unidentified phosphoglycoaminolipids, and six unidentified polar lipids while the polar lipid profile of AW1T had one unidentified lipid, one unidentified phosphoglycolipid, and three unidentified glycolipids in addition. The polar lipid profile of strain GTP1T additionally consisted of two unidentified phosphoaminolipids, and that of strain HM2T additionally had one unidentified phosphoaminolipid, one unidentified phosphoglycolipid, one unidentified phosphoglycoaminolipid, and two unidentified phospholipids. Polar lipid profiles of the novel strains USB13T, AW1T, GTP1T, and HM2T are shown in Figure S1.Physiological, morphological characteristics, and screening of cellulose-degrading strainsWhen grown on R2A agar, strain USB13T produced reddish white and flat colonies while strain AW1T produced orange, convex colonies, strain GTP1T produced white, convex colonies, and strain HM2T produced cream-colored, flat, transparent colonies. Under TEM, monotrichous flagella were observed only in strain HM2T, and when tested for motility, strain USB13T and AW1T showed gliding motility, whereas strain GTP1T was non-motile. Strains USB13T and HM2T showed positive results for both catalase and oxidase activities; strain AW1T showed positive results for catalase and negative results for oxidase activity, and strain GTP1T showed negative results for catalase and positive results for oxidase activity. All strains were identified to be strictly aerobic, while showing negative results for urea, gelatin, starch, chitin, and DNA hydrolysis and positive results for hydrolysis of Tween 80. In addition, strain USB13T was the only strain to produce iron-chelating siderophores. When tested for NaCl tolerance, growth of strain USB13T was observed in NaCl concentrations of 0–7% (w/v), possibly due to the fact the strain was isolated from a marine environment. A detailed comparison of physiological and morphological characteristics between the novel species and its closely related Ramlibacter strains is presented in Table 1, while TEM images of the novel strains are shown in Figure S2. Results of the reference strains in Table 1 coincided with the data from the original literature1,3,4,5,7,8.Table 1 Characteristics differentiating strains USB13T, AW1T, GTP1T, and HM2T from closely related strains of the genus Ramlibacter.Full size tableStrains: 1, USB13T; 2, AW1T; 3, GTP1T; 4, HM2T; R. monticola KACC 19175T; 6, R. alkalitolerans KACC 19305T; 7, R. ginsenosidimutans KACC 17527T; 8, R. humi KCTC 52922T; 9, R. henchirensis KACC 11925T; 10, R. tataouinensis KACC 11924T; 11, R. rhizophilus KCTC 52083T. All strains are positive for esterase lipase (C8), while all strains are negative for chitin hydrolysis. All data were obtained from this study unless indicated otherwise. + , Positive; w + , weakly positive; -, negative.R2A agar plates supplemented with 1% (w/v) CMC were stained with Congo red dye after 7 days of incubation. Clear zones only formed around colonies of strain USB13T, indicating that strain USB13T solely possessed CMC-hydrolyzing activity among the four novel strains. When inoculated in basal salt medium, filter paper from the USB13T sample underwent degradation, whereas samples containing strains AW1T, GTP1T, and HM2T did not show any signs of degradation.Phylogenetic and genomic analysesEzBioCloud search results and BLASTn searches revealed that the novel strains belonged to the family Comamonadaceae and genus Ramlibacter. Using BLASTn, 16S rRNA gene sequence similarities were determined where strain USB13T was closest to strain GTP1T (98.5%), followed by strain HM2T (98.1%) and strain AW1T (97.1%). Strain AW1T shared the highest similarity with strain GTP1T (97.3%), followed by strain HM2T (97.1%), while strain GTP1T shared a similarity of 98.2% with strain HM2T. Phylogenetic analysis based on the MP method (Fig. 1) showed the clustering of the novel strains USB13T, AW1T, GTP1T, and HM2T with strains such as R. monticola G-3-2T, R. ginsenosidimutans BXN5-27T, R. alkalitolerans CJ661T, and R. rhizophilus YS3.2.7T. Similar topologies were observed in trees reconstructed by ML (Figure S3) and MP methods. The UBCG phylogenomic tree (Fig. 2), which was reconstructed using whole genome sequences, also showed close clustering of the selected reference strains and novel strains.Figure 1Maximum-parsimony (MP) tree reconstructed based on 16S rRNA gene sequences, showing the relationship between strains USB13T, AW1T, GTP1T, and HM2T and other closely related type strains. Bootstrap values based on 1000 replications are listed as percentages at branching points. Only bootstrap values exceeding 50% are shown. Bar, 50 substitutions per nucleotide position.Full size imageFigure 2Phylogenomic tree of strains USB13T, AW1T, GTP1T, and HM2T and their closely related taxa was reconstructed based on core genomes using UBCG version 3.0 pipeline42. NCBI GenBank accession numbers are shown in parentheses. Bootstrap analysis was carried out using 1000 replications. Percentage bootstrap values ( > 50%) are given at branching points. Bar, 0.050 substitution per position.Full size imageDraft genome sequences of the novel strains USB13T, AW1T, GTP1T, and HM2T were deposited in the GenBank database under the accession numbers JACORT000000000, JAEQNA000000000, JACORU000000000, and JADDIV000000000, respectively. In addition, the draft genome sequences of R. monticola KACC 19175T, R. alkalitolerans KACC 19305T, and R. ginsenosidimutans KACC 17527T were also deposited in GenBenk under the accession numbers JAEQNE000000000, JAEQND000000000, and JAEPWM000000000, respectively. The assembled genome size of the novel strains USB13T, AW1T, GTP1T, and HM2T was 5.53 Mbp, 5.11 Mbp, 6.15 Mbp, 4.31 Mbp, respectively. G + C content ranged from 67.9% to 69.9%, which was similar to those of the reference strains. The genomic features of the novel strains and their closely related Ramlibacter strains are presented in Table S2. CheckM analysis showed the following estimations for each strain: USB13T, had a 99.84% completeness and 0.68% contamination; AWIT, had a 99.84% completeness and 0.86% contamination; GTP1T, had a 99.38% completeness and 1.32% contamination; HM2T, had a 97.51% completeness and 0.16% contamination. These results indicated that the draft genome results for all strains were reliable. ANI values between the novel strains and reference strains ranged from 76.5–83.4% while dDDH values ranged from 20.7–26.7%, and AAI values ranged from 65.7–80.4%. All values were below the threshold for delineation of a new species54. ANI values between the novel strains and their reference strains are presented in Fig. 3, while a detailed comparison of GGDC and AAI values are shown in Table 2.Figure 3Heatmap of strains USB13T, AW1T, GTP1T, and HM2T and other closely related strains within the genus Ramlibacter, generated with OrthoANI values calculated using OAT software45. Bacterial strains and accession numbers are indentical to those of Fig. 2.Full size imageTable 2 Average amino acid identity (AAI) and digital DNA-DNA hybridization (dDDH) value comparisons between the closely related Ramlibacter type species and the novel strains, USB13T, AW1T, GTP1T, and HM2T. AAI values were calculated by two-way AAI, while dDDH values were calculated based on formula 246.Full size tableBased on NCBI PGAP annotation and CAZyme prediction results, strain USB13T, which was the only strain to show cellulolytic activity, possessed a total of four protein CDs encoding CAZymes, namely, two GH15 proteins, one glycosyl hydrolase protein, and one GH99-like domain-containing protein. Despite not showing any cellulolytic activity, strain AW1T possessed eight CAZyme CDs; the most amount among the novel strains. The enzymes include, two GH2 proteins, one GH5 protein, three GH15 proteins, one glycoside hydrolase protein, and one cellulase family glycosyl hydrolase. Strain GTP1T possessed two CDs encoding one GH15 protein and one GH16 protein; strain HM2T possessed three CDs encoding one GH2, one GH15, and one GH18 protein. All strains possessed GH15, which is known for its glucoamylase activity in fungi55. A detailed summary of the novel strains CAZymes are presented in Table S3 and a comparison of CAZyme numbers between strains USB13T, AW1T, GTP1T, and HM2T is summarized in Table S4. The presence of these genes may suggest the cellulolytic activity of strain USB13T, while it is uncertain why GH families responsible for endoglucanase (GH 5–8, 12, 16, 44, 45, 48, 51, 64, 71, 74, 81, 87, 124, and 128), exoglucanase (GH 5–7, and 48), and β-glucosidase (GH 1, 3, 4, 17, 30, and 116) were not present in the genome11.COG predictions (Fig. 4) revealed that the majority of the core genes of the four novel strains accounted for genes belonging to the functional categories C (energy production and conversion), E (amino acid transport and metabolism), I (lipid transport and metabolism), T (signal transduction mechanisms), and K (transcription). Meanwhile, the number of core genes belonging in category G, carbohydrate transport and metabolism, was the highest for strain USB13T (258), followed by GTP1T (230), HM2T (212), and AW1T (181). The high number of genes in strain USB13T may be a contributing factor in the strain’s cellulolytic activity. A comparison of COG gene count distribution of the novel strains is presented in Table S5.Figure 4Comparison of total number of matched genes of strains USB13T, AW1T, GTP1T, and HM2T according to functional classes based on Cluster of Orthologous Groups of proteins (COG) predictions48.Full size imageAntiSMASH analysis results showed four gene clusters within the genome of strain USB13T: ribosomally synthesized and post-translationally modified peptides (RIPP)-like cluster (989,516–1,000,916 nt; JACORT010000001), terpene synthesis (8,622–30,347 nt; JACORT010000003), RIPP precursor peptide recognition element (RRE)-containing cluster (311,469–333,619 nt; JACORT010000004), and redox-cofactor (281,860–303,948 nt; JACORT010000007). Among the clusters, the RRE-containing cluster showed 11% similarity to streptobactin, a tricatechol-type siderophore isolated from Streptomyces sp. YM5-79956. Strain AW1T had a total of eight gene clusters which encoded for: arylpolyene (165,946–207,130 nt), terpene (618,322–640,854 nt), RIPP-like proteins (804,411–819,137 nt), non-ribosomal peptide synthetase cluster (NRPS)-like (61,798–104,764 nt), betalactone (323,399–348,739 nt), N-acetylglutaminylglutamine amide (NAGGN; 106,834–121,648 nt), type I polyketide synthase (T1PKS; 56,584–107,578 nt), and heterocyst glycolipid synthase-like polyketide synthase (hglE-KS; 75,419–113,566 nt). Strain GTP1T possessed four gene clusters that encoded for RRE-containing cluster (175,155–199,102 nt), homoserine lactone (110,293–130,892 nt), a signaling molecule known for its involvement in bacterial quorum sensing, the RIPP-like cluster (38,002–48,856 nt), and terpene synthesis (47,942–69,701 nt). Strain HM2T had two gene clusters that encoded for resorcinol (403,967–445,901 nt), an organic compound known for its antiseptic properties, and terpene (697,660–721,242 nt), which showed 100% similarity for carotenoid synthesis. BRIG analysis results showed that a majority of the regions within the four analyzed genomes were conserved with at least 70% similarity (Figure S4).Cellulolytic potential and FE-SEM analysis of strain USB13T
A USB13T-inoculated basal salt medium sample containing degraded filter paper was examined under FE-SEM to observe the morphological interactions between cellulose fibers and USB13T cells. Images in Fig. 5 show individual rod cells of strain USB13T surrounding filter paper fibers, indicating bacterial adherence.Figure 5Field emission-scanning electron microscopy (FE-SEM) images of adhesion of strain USB13T to degraded filter paper fibers. Arrows indicate filter paper fibers. (A) low magnification (5000(times)) and (B), high magnification (20,000(times)) images of strain USB13T surrounding filter paper fibers.Full size imageThe enzymatic assay results showed endoglucanase, exoglucanase, β-glucosidase, and filter paper cellulase (FPCase) activities of strain USB13T, wherein activities for endoglucanase was the highest and β-glucosidase was the lowest in all experiments. As seen in Fig. 6A, enzyme activity for all cellulolytic enzymes increased along with its cultivation time. In addition, enzyme activities showed the highest results when tested on buffer solutions of pH 6.0 (Fig. 6B), indicating the enzymes’ resistance to moderately acidic conditions. The pH of the buffer solution seemed to be an important factor in enzyme activity, as activity of endoglucanase, exoglucanase, and FPCase drastically decreased when the pH was altered from pH 6.0 to pH 7.0. Meanwhile, β-glucosidase activity was relatively resistant to pH change as its activity decreased less than 50%. On day 7, enzyme activities were measured as 1.91 IU/mL for endoglucanase, 1.77 IU/mL for exoglucanase, 0.76 IU/mL for β-glucosidase, and 1.12 IU/mL for FPCase at pH 6.0. When measured at pH 8.0, where enzyme activity was the lowest, enzyme activities were measured as 0.51 IU/mL for endoglucanase, 0.25 IU/mL for exoglucanase, 0.45 IU/mL for β-glucosidase, and 0.23 IU/mL for FPCase; all values were less than half of the measured activity at pH 6.0. The results of strain USB13T are comparable to FPCase results of other species such as Mucilaginibacter polytrichastri RG4-7T (0.98 U/mL) isolated from the moss Polytrichastrum formosum14, Paenibacillus lautus BHU3 (2.9 U/mL) isolated from a landfill site57, and Serratia rubidaea DBT4 (0.5 U/mL) isolated from the gastrointestinal tract of a black Bengal goat58.Figure 6Cellulolytic enzyme activity of strain USB13T. Enzyme activity was defined in international units (IU); one unit of enzymatic activity was defined as the amount of enzyme that releases 1 μmol of glucose per mL per 1 min of reaction. (A) cellulase activity results under different cultivation time; (B) cellulase activity under different buffer solution pH. Values in the figure are mean values of triplicate data with standard deviation.Full size imageDespite the absence of the main three cellulolytic enzymes, endoglucanase, exoglucanase, and β-glucosidase, the cellulolytic activity of strain USB13T was confirmed through SEM images, CMC agar screening, and enzymatic assay results. However, because PGAP annotation results showed that other non-cellulolytic strains also possessed CAZymes, in some cases more than strain USB13T, further research is necessary to understand the mechanics of how CAZymes and other cellulases interact to degrade cellulose, and how these genes are expressed under certain conditions. Furthermore, the cellulolytic activity of strain USB13T can be further optimized for commercial use by adjusting growth conditions such as pH, temperature, and growth media.While cellulolytic bacteria are known to inhabit animal intestinal tracts, the rumen, and soil, they can be found almost everywhere, such as ocean floors, municipal landfills, and even extreme environments such as hot springs59. In these habitats, cellulolytic bacteria utilize cellulose while cohabiting with non-cellulolytic bacteria. There have been many studies suggesting the synergistic role non-cellulolytic bacteria play in cellulose degradation, where non-cellulolytic bacteria aid cellulose degradation by neutralizing pH or removing harmful metabolites60,61,62.Bacterial cellulases have shown immense value in various industries such as animal feed processing, food and brewery production, and agriculture, not to mention biofuel synthesis through biomass utilization11. Due to the versatile uses of bacterial cellulases, the cellulolytic strain USB13T has the potential to become an invaluable resource. However, further research of the novel strain’s cellulose-degradation mechanisms is necessary to develop and commercially make use of its bacterial cellulases in the future. In addition, research regarding co-culturing non-cellulolytic bacteria and strain USB13T may also help in developing effective methods to use an otherwise underutilized bioresource.Taxonomy of novel Ramlibacter speciesWhile phylogenetic analyses indicated that the novel strains USB13T, AW1T, GTP1T, and HM2T should be assigned to the genus Ramlibacter, differences in fatty acid compositions, polar lipid profiles, and physiological characteristics suggested that the four novel strains are noticeably distinct from other validly published species of the genus. Additionally, genomic characteristics such as ANI, dDDH, and AAI values further supported the novel strains’ position as a distinct species within the genus Ramlibacter. Therefore, we propose that the strains USB13T, AW1T, GTP1T, and HM2T represent novel species within the genus Ramlibacter.Description of the novel Ramlibacter speciesThe descriptions of the novel species are given according to the standards of the Judicial Commission of the International Committee on Systematic Bacteriology63.Description of Ramlibacter cellulosilyticus sp. nov
Ramlibacter cellulosilyticus (cel.lu.lo.si.ly’ti.cus. N.L. n. cellulosum, cellulose; N.L. adj. lyticus from Gr. lytikos, dissolving; N.L. masc. adj. cellulosilyticus, cellulose-dissolving).Cells of strain USB13T are Gram-negative, rod-shaped, non-flagellated and motile by gliding. The strain is positive for both oxidase and catalase activity, while cells have a width of 0.3–0.5 μm and length of 2.0–2.4 μm. When observed on R2A agar, colonies are reddish white, flat with entire margins, and have a diameter of 1–2 mm. Growth of strain USB13T is observed at 7–50 °C (optimum, 28–30 °C), at pH 5.0–10.0 (optimum, pH 6.0), and at NaCl concentrations of 0–7% (optimum, 0–3%). The strain is unable to grow in anaerobic conditions. Produces siderophores and hydrolyzes Tween 20, Tween 80, CMC, and esculin. According to the API ZYM results, the strain showed positive results for alkaline phosphatase, esterase lipase (C8), leucine arylamidase, acid phosphatase, β-galactosidase, α-glucosidase, and β-glucosidase. In the API 20NE assay, strain USB13T showed positive results only for β-galactosidase. The predominant respiratory quinone is ubiquinone 8 (Q-8). The major fatty acids are C16:0, C10:0 3-OH, and summed feature 3 (consisting of C16:1 ω7c and/or C16:1 ω6c). The polar lipid profile consists of diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), one unidentified phosphoaminolipid, two unidentified phosphoglycoaminolipids, and six unidentified polar lipids. The G + C content is 69.7%. The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequence and the assembled genome sequence of strain USB13T are MN603953 and JACORT000000000, respectively.The type strain USB13T (= KACC 21656T = NBRC 114839T) was isolated from shallow coastal water at Haeundae Beach, Busan, Republic of Korea.Description of Ramlibacter aurantiacus sp. nov
Ramlibacter aurantiacus (au.ran.ti’a.cus. L. masc. adj. aurantiacus, orange-colored, referring to the orange colonies of the strain).Cells of strain AW1T are Gram-negative, coccoid to short rod-shaped, non-flagellated, and motile by gliding. The strain is negative for oxidase activity, and positive for catalase activity. When observed on R2A agar, colonies are orange, convex, with entire margins, and 0.5–1.0 mm in diameter. Under TEM cells have and approximate width of 0.3–0.5 μm and length of 0.6–0.8 μm. Growth of strain AW1T can be observed at 7–45 °C (optimum, 30 °C), at pH 7.0–10.0 (optimum, 7.0–8.0), and at NaCl concentrations of 0–3% (optimum, 0–1%). The strain does not grow under anaerobic conditions but is able to hydrolyze Tween 80. In addition, AW1T is not able to produce siderophores. In the API ZYM assay, positive for alkaline phosphatase, esterase (C4), esterase lipase (C8), leucine arylamidase, and β-glucosidase. In the API 20NE assay, positive for esculin hydrolysis. The predominant respiratory quinone is ubiquinone 8 (Q-8). The major fatty acids are C16:0, C17:0 cyclo, summed feature 3 (consisting of C16:1 ω7c and/or C16:1 ω6c), and summed feature 8 (consisting of C18:1 ω7c and/or C18:1 ω6c). The polar lipid profile consists of diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), one unidentified phosphoglycolipid, one unidentified lipid, and three unidentified glycolipids. The G + C content is 68.6%. The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequence and the assembled genome sequence of strain AW1T are MN498045 and JAEQNA000000000, respectively.The type strain AW1T (= KACC 21544T = NBRC 114862T) was isolated from soil at Aewol, Jeju Island, Republic of Korea.Description of Ramlibacter albus sp. nov
Ramlibacter albus (al’bus. L. masc. adj. albus, white, referring to the white colonies of the strain).Strain GTP1T is non-motile, Gram-negative, strictly aerobic, positive for oxidase activity, and negative for catalase activity. When observed on R2A, colonies are white, convex, with entire margins, and 1–2 mm in diameter. Under TEM, cells lack flagella, are rod-shaped, and have a width of 0.7–0.8 μm and length of 1.6–1.9 μm. Growth of strain GTP1T can be observed at 10–45 °C (optimum, 30 °C), at pH 5.0–8.0 (optimum, pH 7.0), and at NaCl concentrations of 0–2% (optimum, 0%). The strain shows positive results for Tween 20 and Tween 80 hydrolysis. GTP1T does not produce siderophores when tested on CAS-blue agar. According to API ZYM results, strain GTP1T is positive for alkaline phosphatase, esterase (C4), esterase lipase (C8), and leucine arylamidase, while the API 20NE assay results show negative results for all substrates. The predominant respiratory quinone is ubiquinone 8 (Q-8). The major fatty acids are C16:0 and summed feature 3 (consisting of C16:1 ω7c and/or C16:1 ω6c). The polar lipid profile consists of diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), and two unidentified phosphoaminolipids. The predominant respiratory quinone is ubiquinone 8 (Q-8). The major fatty acids are C16:0, C17:0 cyclo, summed feature 3 (consisting of C16:1 ω7c and/or C16:1 ω6c), and summed feature 8 (consisting of C18:1 ω7c and/or C18:1 ω6c). The polar lipid profile consists of diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), one unidentified phosphoaminolipid, one unidentified phosphoglycolipid, one unidentified phosphoglycoaminolipid, and two unidentified polar lipids. The G + C content is 67.9%. The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequence and the assembled genome sequence of strain GTP1T are MN498046 and JACORU000000000, respectively.The type strain GTP1T (= KACC 21702T = NBRC 114488T) was isolated from soil at Seogwipo, Jeju Island, Republic of Korea.Description of Ramlibacter pallidus sp. nov
Ramlibacter pallidus (pal’li.dus. L. masc. adj. pallidus, pale, referring to the color of the colonies).Cells of strain HM2T are Gram-negative, and positive for both oxidase and catalase activities. When observed on R2A agar, colonies are cream-colored, transparent, 1.0–2.5 mm in diameter, and flat with entire margins. Under TEM, monotrichous flagella are observed, and cells are rod-shaped with a width of 0.4–0.78 μm and length of 1.7–1.8 μm. The strain shows the fastest growth at a temperature range of 25–35 °C and at pH values between 8.0 and 9.0. When NaCl is present, growth is observed at concentrations of 0–3% (w/v), with optimal growth was observed at concentrations of 0–1% (w/v). The strain is not able to tolerate anaerobic conditions. Strain HM2T hydrolyzes Tween 80 and weakly hydrolyzes casein. However, siderophore production cannot be observed when tested on CAS-blue agar. According to API ZYM tests, strain HM2T shows positive results for alkaline phosphatase, esterase (C4), esterase lipase (C8), leucine arylamidase, valine arylamidase, acid phosphatase, and naphthol-AS-BI-phosphohydrolase. In addition, API 20NE tests show positive results for nitrate (NO3) to nitrite (NO2-) reduction and esculin hydrolysis. The G + C content is 69.9%. The GenBank/EMBL/DDBJ accession numbers for the 16S rRNA gene sequence and the assembled genome sequence of strain HM2T are MN498047 and JADDIV000000000, respectively.The type strain HM2T (= KCTC 82557T = NBRC 114489T) was isolated from soil at Seopjikoji, Jeju Island, Republic of Korea. More

Indonesia’s bleeding toad (Leptophryne cruentata) is critically endangered.Credit: Pepew Fegley/Shutterstock

One-quarter of all plant and animal species are threatened with extinction owing to factors such as climate change and pollution. Starting this week, negotiators and ministers from more than 190 countries are meeting at a United Nations biodiversity summit called COP15 in Montreal, Canada, to address the emergency.
10 startling images of nature in crisis — and the struggle to save it
From 7 to 19 December, they will be trying to seal a new deal to save Earth’s biodiversity. The treaty, known as the post-2020 Global Biodiversity Framework, is intended to establish precise targets for countries to protect and restore nature, including conserving 30% of the planet by 2030 and cutting nutrient pollution, such as reducing nitrogen fertilizer loss from farmland.Time is running out. “We’re driving species to extinction at a rate about 1,000 times faster than they are created through evolution,” says Stuart Pimm, an ecologist at Duke University in Durham, North Carolina, and head of Saving Nature, a non-profit conservation organization.As COP15 kicks off, researchers and policy experts are concerned that countries still disagree on too many issues to secure a deal that will protect species and ecosystems effectively. Here, Nature looks at the extent of the crisis, and what scientists say countries must do to succeed.Which species are most at risk, and what’s threatening them?Among the most at-risk groups are amphibians and reef-forming corals. A global assessment shows that more than 40% of amphibians are threatened with extinction1, including the critically endangered bleeding toad (Leptophryne cruentata), which lives in Mount Gede Pangrango National Park in Java, Indonesia.These toads were thought to be extinct until the year 2000, when some were spotted by a team led by Mirza Kusrini, a herpetologist at Bogor Agricultural University in Indonesia. But the researchers found that the amphibians were infected with chytrid (Chytridiomycota sp.), a fungus that has devastated global amphibian populations. Kusrini says that climate change is probably making life hard for the tiny toad, which got its common name from the crimson, splatter-like spots covering its body. Warm weather can stimulate fungal outbreaks and shift the timing of behaviours, such as the toads’ breeding season, making the amphibians vulnerable.

Source: Red List Index/IUCN

Global warming, which has been raising sea temperatures, is also responsible for harming coral reefs around the globe (see ‘Threat assessment’). Over a period of 9 years, up to 2018, 14% of the world’s coral died out — a massive problem, because today, coral reefs support one-quarter of all marine species.Research shows that climate change is quickly becoming a large threat to biodiversity2. But still, the most-destructive forces are the conversion of land and seas for agricultural uses and people exploiting natural resources through fishing, logging, hunting and the wildlife trade. About 75% of land and 66% of ocean areas have been significantly altered, usually for producing food.What might happen if species disappear?It’s difficult to predict, because doing so requires knowledge of which species are present in a particular ecosystem, such as a rainforest, and what functions they have, says Shahid Naeem, an ecologist at Columbia University in New York City. Much of that information is often unknown. However, scientists have shown3 that ecosystems with less biodiversity are not as good at capturing and converting resources into biomass, such as happens when plants capture nutrients or sunlight used for growth.
Why deforestation and extinctions make pandemics more likely
Neither are less-diverse ecosystems as good at decomposing and recycling biological materials and nutrients. For example, studies show that dead organisms are broken down, and their nutrients recycled, more quickly when a high variety of plant litter covers the forest floor4. Ecosystems with low biodiversity also have low resilience — they are not as able to bounce back after a perturbation or shock, such as a fire, as more-diverse systems are, Naeem says.“If we lose parts of our system, it simply won’t function very efficiently, and it won’t be very robust,” he adds. “The science behind that is rock solid.”Ecosystems also provide clean water and can sometimes prevent diseases from spreading to humans. When species are lost, these services deteriorate, Kusrini says. For example, most amphibians eat insects, many of which are considered pests, such as cockroaches, termites and mosquitoes. Studies have shown a rise in cases of malaria — spread by mosquitoes — in areas in Central America where amphibian populations have collapsed5. “You know when they disappear”, Kusrini says, because insect numbers rise and people start using more pesticides to kill them.What solutions do researchers say are needed to protect biodiversity?Protecting and conserving habitats is central to saving species. This idea is captured in the framework being negotiated at COP15. The draft includes the goal of conserving at least 30% of the world’s land and sea by 2030. But for protections to be most effective, they must include regions that are rich in biodiversity, such as tropical forests, Pimm says. Despite an increase in protected areas worldwide over the past ten years, species numbers have still declined, because these safeguards were not in the right places, studies show6.

Delegates at COP15 in Montreal show their support for a new agreement among nations to protect Earth’s biodiversity.Credit: UN Convention on Biological Diversity (CC BY 2.0)

“What we’re going to be looking for at COP15 is more quality, not just more quantity,” Pimm says.Eradicating invasive species is another important conservation strategy, and the framework’s draft currently calls for cutting the introduction of such species in half. Some estimates suggest that invasive predators, such as cats and rats, are responsible for more than half of all extinctions of birds, mammals and reptiles7.It’s important that nations agree on a framework with at least some quantifiable targets, so that progress can be measured, and so that countries can be held accountable if they fail to meet their targets, researchers say. “I’m afraid what will happen is, they will produce a long list of ‘waffle’,” Pimm says. “We need quantification.”Will nations manage to agree on a new deal to protect nature?As COP15 begins, the outlook is not good. The text of the draft is still littered with unresolved issues. At a press conference on 6 December, Elizabeth Mrema, executive secretary of the Convention on Biological Diversity — the global treaty that underpins the new biodiversity deal — said that national negotiators had made insufficient progress in a final round of discussions before the start of the summit. She urged countries to compromise, otherwise they will fail to reach a deal. “The state of the planet is in crisis,” Mrema said. “This is our last chance to act.”
Troubled biodiversity plan gets billion-dollar funding boost
One key contentious issue is how to finance biodiversity conservation, particularly in low- and middle-income countries, which are home to much of the world’s biodiversity. These nations, including Brazil and Gabon, would like a new fund to be established with US$100 billion added per year in aid. So far, that proposal has not gained traction with wealthier countries. “They really need to have the financial commitments, because things don’t get done without the money,” Naeem says.Despite the pessimism, Naeem is certain that scientists and advocates will keep pushing for a deal. “There would be real change” if countries were able to achieve a universal decrease in biodiversity loss, he says. More

Field parameters and major ionsThe results of the hydrochemistry and environmental isotopes for the 40 lakes are presented spatially in Figs. S1–S11 and are located in Tables S1 and S2.The lake waters are oxic (8.6–12.6 mg l−1) and range from slightly acidic (pH 6.0) to slightly alkaline (pH 9.2). Lake water temperatures are generally highest for lakes along the west coast (greater than 10 °C, Table S2). Phosphate concentrations are below detection level (0.1 mg l−1) for all lakes and nitrate was low ranging from below detection limit ( More

Tölgyesi, C., Buisson, E., Helm, A., Temperton, V. M. & Török, P. Urgent need for updating a slogan of global climate actions from ‘tree planting’ to ‘restore native vegetation’. Restor. Ecol. 30, e13594. https://doi.org/10.1111/rec.13594 (2021).Article 

Google Scholar 
Dengler, J., Janišová, M., Török, P. & Wellstein, C. Biodiversity of Palaearctic grasslands: A synthesis. Agric. Ecosyst. Environ. 182, 1–14 (2014).Article 

Google Scholar 
Dass, P., Houlton, B. Z., Wang, Y. & Warlind, D. Grasslands may be more reliable carbon sinks than forests in California. Environ. Res. Lett. 13, 074027. https://doi.org/10.1088/1748-9326/aacb39 (2018).Article 
ADS 

Google Scholar 
Terrer, C. et al. A trade-off between plant and soil carbon storage under elevated CO2. Nature 591, 599–603 (2021).Article 
ADS 
CAS 

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).Article 
ADS 
CAS 

Google Scholar 
Stevens, C. J. Recent advances in understanding grasslands. F1000 Res. https://doi.org/10.12688/f1000research.15050.1 (2018).Article 

Google Scholar 
Klaus, V. H. et al. Do biodiversity-ecosystem functioning experiments inform stakeholders how to simultaneously conserve biodiversity and increase ecosystem service provisioning in grasslands?. Biol. Conserv. 245, 108552. https://doi.org/10.1016/j.biocon.2020.108552 (2020).Article 

Google Scholar 
Dudley, N. et al. Grasslands and savannahs in the UN decade on ecosystem restoration. Restor. Ecol. 28, 1313–1317 (2020).Article 

Google Scholar 
Bardgett, R. D. et al. Combatting global grassland degradation. Nat. Rev. Earth Environ. 2, 720–735 (2021).Article 
ADS 

Google Scholar 
Lengyel, S. et al. Restoration for variability: Emergence of the habitat diversity paradigm in terrestrial ecosystem restoration. Restor. Ecol. 28, 1087–1099 (2020).Article 

Google Scholar 
Waldén, E. & Lindborg, R. Long term positive effect of grassland restoration on plant diversity: Success or not?. PLoS ONE 11, e0155836. https://doi.org/10.1371/journal.pone.0155836 (2016).Article 
CAS 

Google Scholar 
Lengyel, S. et al. Grassland restoration to conserve landscape-level biodiversity: A synthesis of early results from a large-scale project. Appl. Veg. Sci. 15, 264–276 (2012).Article 

Google Scholar 
Sojneková, M. & Chytrý, M. From arable land to species-rich semi-natural grasslands: Succession in abandoned fields in a dry region of central Europe. Ecol. Eng. 77, 373–381 (2015).Article 

Google Scholar 
Ellis, E. C. et al. Used planet: A global history. Proc. Natl. Acad. Sci. USA 110, 7978–7985 (2013).Article 
ADS 
CAS 

Google Scholar 
Levers, C., Schneider, M., Prishchepov, A. V., Estel, S. & Kuemmerle, T. Spatial variation in determinants of agricultural land abandonment in Europe. Sci. Total Environ. 644, 95–111 (2018).Article 
ADS 
CAS 

Google Scholar 
Winkler, K., Fuchs, R., Rounsevell, M. & Herold, M. Global land use changes are four times greater than previously estimated. Nat. Commun. 12, 2501. https://doi.org/10.1038/s41467-021-22702-2 (2021).Article 
ADS 
CAS 

Google Scholar 
Perpiña Castillo, C. et al. Agricultural Land Abandonment in the EU within 2015–2030 (No: JRC113718) (Joint Research Centre (Seville site), 2018).Müller, D., Leitão, P. J. & Sikor, T. Comparing the determinants of cropland abandonment in Albania and Romania using boosted regression trees. Agric. Syst. 117, 66–77 (2013).Article 

Google Scholar 
Prishchepov, A. V., Müller, D., Dubinin, M., Baumann, M. & Radeloff, V. C. Determinants of agricultural land abandonment in post-Soviet European Russia. Land Use Policy 30, 873–884 (2013).Article 

Google Scholar 
Prishchepov, A. V., Schierhorn, F. & Löw, F. Unraveling the diversity of trajectories and drivers of global agricultural land abandonment. Land 10, 97 (2021).Article 

Google Scholar 
Bossuyt, B. & Honnay, O. Can the seed bank be used for ecological restoration? An overview of seed bank characteristics in European communities. J. Veg. Sci. 19, 875–884 (2008).Article 

Google Scholar 
Humphries, T., Florentine, S., Dowling, K., Turville, C. & Sinclair, S. Weed management for landscape scale restoration of global temperate grasslands. Land Degrad. Dev. 32, 1090–1102 (2021).Article 

Google Scholar 
Valkó, O. et al. Dynamics in vegetation and seed bank composition highlight the importance of post-restoration management in sown grasslands. Restor. Ecol. 29, e13192. https://doi.org/10.1111/rec.13192 (2021).Article 

Google Scholar 
Valkó, O. et al. High-diversity sowing in establishment gaps: A promising new tool for enhancing grassland biodiversity. Tuexenia 36, 359–378 (2016).
Google Scholar 
Kövendi-Jakó, A. et al. Three years of vegetation development worth 30 years of secondary succession in urban-industrial grassland restoration. Appl. Veg. Sci. 22, 138–149 (2019).Article 

Google Scholar 
Kiss, R. et al. Establishment gaps in species-poor grasslands: Artificial biodiversity hotspots to support the colonization of target species. Restor. Ecol. 29, e13135. https://doi.org/10.1111/rec.13135 (2021).Article 

Google Scholar 
Török, P., Vida, E., Deák, B., Lengyel, S. & Tóthmérész, B. Grassland restoration on former croplands in Europe: An assessment of applicability of techniques and costs. Biodivers. Conserv. 20, 2311–2332 (2011).Article 

Google Scholar 
Critchley, C. N. R., Fowbert, J. A., Sherwood, A. J. & Pywell, R. F. Vegetation development of sown grass margins in arable fields under a countrywide agri-environment scheme. Biol. Conserv. 132, 1–11 (2006).Article 

Google Scholar 
Wagner, M., Walker, K. J. & Pywell, R. F. Seed bank dynamics in restored grassland following the sowing of high-and low-diversity seed mixtures. Restor. Ecol. 26, S189–S199 (2018).Article 

Google Scholar 
Lepš, J. et al. Long-term effectiveness of sowing high and low diversity seed mixtures to enhance plant community development on ex-arable fields. Appl. Veg. Sci. 10, 97–110 (2007).
Google Scholar 
Török, P. et al. Restoring grassland biodiversity: Sowing low diversity seed mixtures can lead to rapid favourable changes. Biol. Conserv. 148, 806–812 (2010).Article 

Google Scholar 
Schaub, S. et al. The costs of diversity: Higher prices for more diverse grassland seed mixtures. Environ. Res. Lett. 16, 094011. https://doi.org/10.1088/1748-9326/ac1a9c (2021).Article 
ADS 
CAS 

Google Scholar 
Werner, C. M., Vaughn, K. J., Stuble, K. L., Wolf, K. & Young, T. P. Persistent asymmetrical priority effects in a California grassland restoration experiment. Ecol. Appl. 26, 1624–1632 (2016).Article 

Google Scholar 
Williams, D. W., Jackson, L. L. & Smith, D. D. Effects of frequent mowing on survival and persistence of forbs seeded into a species-poor grassland. Restor. Ecol. 15, 24–33 (2007).Article 

Google Scholar 
Klaus, V. H. et al. Enriching plant diversity in grasslands by large-scale experimental sward disturbance and seed addition along gradients of land-use intensity. J. Plant Ecol. 10, 581–591 (2017).
Google Scholar 
Kiss, R. et al. Zoochory on and off: A field experiment for trait-based analysis of establishment success of grassland species. J. Veg. Sci. 32, e13051. https://doi.org/10.1111/jvs.13051 (2021).Article 

Google Scholar 
Weidlich, E. W. A. et al. Priority effects and ecological restoration. Restor. Ecol. 29, e13317. https://doi.org/10.1111/rec.13317 (2021).Article 

Google Scholar 
Wilsey, B. Restoration in the face of changing climate: Importance of persistence, priority effects, and species diversity. Restor. Ecol. 29, e13132. https://doi.org/10.1111/rec.13132 (2021).Article 

Google Scholar 
von Gillhaussen, P. et al. Priority effects of time of arrival of plant functional groups override sowing interval or density effects: A grassland experiment. PLoS ONE 9, e86906. https://doi.org/10.1371/journal.pone.0086906 (2014).Article 
ADS 
CAS 

Google Scholar 
Eddy, K. C. & Van Auken, O. W. Priority effects allow Coreopsis tinctoria to avoid interspecific competition with a C4 grass. Am. Midl. Nat. 181, 104–114 (2019).Article 

Google Scholar 
Delory, B. M., Weidlich, E. W., von Gillhaussen, P. & Temperton, V. M. When history matters: The overlooked role of priority effects in grassland overyielding. Funct. Ecol. 33, 2369–2380 (2019).Article 

Google Scholar 
Fenner, M. The effects of the parent environment on seed germinability. Seed Sci. Res. 1, 75–84 (1991).Article 

Google Scholar 
Ruprecht, E., Donath, T. W., Otte, A. & Eckstein, R. L. Chemical effects of a dominant grass on seed germination of four familial pairs of dry grassland species. Seed Sci. Res. 18, 239–248 (2008).Article 

Google Scholar 
Partzsch, M., Faulhaber, M. & Meier, T. The effect of the dominant grass Festuca rupicola on the establishment of rare forbs in semi-dry grasslands. Folia Geobot. 53, 103–113 (2018).Article 

Google Scholar 
Fenesi, A., Kelemen, K., Sándor, D. & Ruprecht, E. Influential neighbours: Seeds of dominant species affect the germination of common grassland species. J. Veg. Sci. 31, 1028–1038 (2020).Article 

Google Scholar 
Garbowski, M. et al. Getting to the root of restoration: Considering root traits for improved restoration outcomes under drought and competition. Restor. Ecol. 28, 1384–1395 (2020).Article 

Google Scholar 
Rehling, F., Sandner, T. M. & Matthies, D. Biomass partitioning in response to intraspecific competition depends on nutrients and species characteristics: A study of 43 plant species. J. Ecol. 109, 2219–2233 (2021).Article 

Google Scholar 
Gross, K. L. & Mittelbach, G. G. Negative effects of fertilization on grassland species richness are stronger when tall clonal species are present. Folia Geobot. 52, 401–409 (2017).Article 

Google Scholar 
Bakker, J. P. & Berendse, F. Constraints in the restoration of ecological diversity in grassland and heathland communities. Trends Ecol. Evol. 14, 63–68 (1999).Article 
CAS 

Google Scholar 
Kiss, R., Valkó, O., Tóthmérész, B. & Török, P. Seed bank research in Central-European grasslands: An overview. In Seed Banks: Types Roles and Research (ed. Murphy, J.) 1–34 (Nova Science Publishers, 2016).
Google Scholar 
Prach, K., Jongepierová, I. & Řehounková, K. Large-scale restoration of dry grasslands on ex-arable land using a regional seed mixture: Establishment of target species. Restor. Ecol. 21, 33–39 (2013).Article 

Google Scholar 
Adler, P. B. et al. Competition and coexistence in plant communities: intraspecific competition is stronger than interspecific competition. Ecol. Lett. 21, 1319–1329 (2018).Article 

Google Scholar 
Baskin, C. C. & Baskin, J. M. Seeds: Ecology, Biogeography, And Evolution of Dormancy and Germination (Academic Press, 1998).
Google Scholar 
Kövendi-Jakó, A. et al. Effect of seed storing duration and sowing year on the seedling establishment of grassland species in xeric environments. Restor. Ecol. 29, e13209. https://doi.org/10.1111/rec.13209 (2020).Article 

Google Scholar 
Cevallos, D., Szitár, K., Halassy, M., Kövendi-Jakó, A. & Török, K. Larger seed mass predicts higher germination and emergence rates in sand grassland species with non-dormant seeds. Acta Bot. Hung. 64, 237–258 (2022).Article 

Google Scholar 
Leishman, M. R., Wright, I. J., Moles, A. T. & Westoby, M. The evolutionary ecology of seed size. In Seeds: The Ecology of Regeneration in Plant Communities (ed. Fenner, M.) 31–57 (CAB International, 2000).Chapter 

Google Scholar 
Westoby, M., Falster, D. S., Moles, A. T., Vesk, P. A. & Wright, I. J. Plant ecological strategies: Some leading dimensions of variation between species. Annu. Rev. Ecol. Evol. Syst. 33, 125–215 (2002).Article 

Google Scholar 
Moles, A. T. & Westoby, M. Seed size and plant strategy across the whole life cycle. Oikos 113, 91–105 (2006).Article 

Google Scholar 
Scotton, M. Seed production in grassland species: Morpho-biological determinants in a species-rich semi-natural grassland. Grass Forage Sci. 73, 764–776 (2018).Article 

Google Scholar 
Thompson, K., Bakker, J. P. & Bekker, R. M. The Soil Seed Banks of North West Europe: Methodology, Density and Longevity (Cambridge University Press, 1997).
Google Scholar 
Fick, S. E. & Hijmans, R. J. Worldclim 2: New 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).Article 

Google Scholar 
ENSCONET (European Native Seed Conservation Network). ENSCONET Seed Collecting Manual for Wild Species. ENSCONET, Royal Botanic Gardens, Kew and Universidad Politécnica de Madrid (2009). http://www.kew.org/sites/default/files/ENSCONET_Collecting_protocol_English.pdf. Accessed 15 April 2014).Borhidi, A. Social behaviour types, the naturalness and relative indicator values of the higher plants in the Hungarian flora. Acta Bot. Hung. 39, 97–181 (1995).
Google Scholar 
Király, G. (ed). Új magyar füvészkönyv. Magyarország hatásos növényei (New Hungarian Herbal. The Vascular Plants of Hungary. Identification Key) [in Hungarian]. (Aggtelek National Park Directorate, 2009).R Core Team. R: A Language and Environment for Statistical Computing (4.0.5). Computer Software. R Foundation for Statistical Computing. https://www.R-project.org (2021).Brooks, M. E. et al. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. R. J. 9, 378–400 (2017).Article 

Google Scholar 
Lenth, R. emmeans: Estimated Marginal Means, aka Least-Squares Means (Version 1.3.4) [R]. https://CRAN.R-project.org/package=emmeans (2019). More

Piao, S., Friedlingstein, P., Ciais, P., Viovy, N. & Demarty, J. Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades. Glob. Biogeochem. Cycles 21, GB3018 (2007).Article 

Google Scholar 
Richardson, A. D. et al. Climate change, phenology, and phenological control of vegetation feedbacks to the climate system. Agric. For. Meteorol. 169, 156–173 (2013).Article 

Google Scholar 
Xia, J., Niu, S., Ciais, P. & Janssens, I. A. Joint control of terrestrial gross primary productivity by plant phenology and physiology. Proc. Natl Acad. Sci. USA 112, 2788–2793 (2015).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Yang, J. et al. Divergent shifts in peak photosynthesis timing of temperate and alpine grasslands in China. Remote Sens. Environ. 233, 111395 (2019).Article 

Google Scholar 
Huang, K., Xia, J., Wang, Y. & Ahlstrom, A. Enhanced peak growth of global vegetation and its key mechanisms. Nat. Ecol. Evol. 2, 1897–1905 (2018).Article 
PubMed 

Google Scholar 
Park, T., Chen, C. & Macias-Fauria, M. Changes in timing of seasonal peak photosynthetic activity in northern ecosystems. Glob. Change Biol. 25, 2382–2395 (2019).Article 

Google Scholar 
Medlyn, B. E. Physiological basis of the light use efficiency model. Tree Physiol. 18, 167 (1998).Article 
PubMed 

Google Scholar 
Turner, D. P., Urbanski, S., Bremer, D., Wofsy, S. C. & Gregory, M. A cross-biome comparison of daily light use efficiency for gross primary production. Glob. Change Biol. 9, 383–395 (2003).Article 

Google Scholar 
Monteith, J. L. Solar radiation and productivity in tropical ecosystems. Appl. Ecol. 9, 747–766 (1972).Article 

Google Scholar 
Wang, H. et al. Towards a universal model for carbon dioxide uptake by plants. Nat. Plants 3, 734–741 (2017).Article 
PubMed 
CAS 

Google Scholar 
Zhang, Y., Joiner, J., Alemohammad, S. H., Zhou, S. & Gentine, P. A global spatially contiguous solar-induced fluorescence (CSIF) dataset using neural networks. Biogeosciences 15, 5779–5800 (2018).Article 
CAS 

Google Scholar 
Frankenberg, C. et al. New global observations of the terrestrial carbon cycle from GOSAT: patterns of plant fluorescence with gross primary productivity. Geophys. Res. Lett. 38, L17706 (2011).Article 

Google Scholar 
Yuan, H., Dai, Y., Xiao, Z., Ji, D. & Shangguan, W. Reprocessing the MODIS Leaf Area Index products for land surface and climate modelling. Remote Sens. Environ. 115, 1171–1187 (2011).Article 

Google Scholar 
Elith, J., Leathwick, J. R. & Hastie, T. A working guide to boosted regression trees. J. Anim. Ecol. 77, 802–813 (2008).Article 
PubMed 
CAS 

Google Scholar 
Wang, X. et al. Globally consistent patterns of asynchrony in vegetation phenology derived from optical, microwave, and fluorescence satellite data. J. Geophys. Res. Biogeosci. 125, e2020JG005732 (2020).Article 

Google Scholar 
Poorter, H. et al. Biomass allocation to leaves, stems and roots: meta-analyses of interspecific variation and environmental control. New Phytol. 193, 30–50 (2012).Article 
PubMed 
CAS 

Google Scholar 
Zhang, Y., Commane, R., Zhou, S., Williams, A. P. & Gentine, P. Light limitation regulates the response of autumn terrestrial carbon uptake to warming. Nat. Clim. Change 10, 739–743 (2020).Article 
CAS 

Google Scholar 
Yuan, W. et al. Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database. Agric. For. Meteorol. 192-193, 108–120 (2014).Article 

Google Scholar 
Reich, P. B. et al. Temperature drives global patterns in forest biomass distribution in leaves, stems, and roots. Proc. Natl Acad. Sci. USA 111, 13721–13726 (2014).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Wright, I. J., Reich, P. B. & Westoby, M. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).Article 
PubMed 
CAS 

Google Scholar 
Reich, P. B., Oleksyn, J. & Wright, I. J. Leaf phosphorus influences the photosynthesis–nitrogen relation: a cross-biome analysis of 314 species. Oecologia 160, 207–212 (2009).Article 
PubMed 

Google Scholar 
Chen, Y., Han, W., Tang, L., Tang, Z. & Fang, J. Leaf nitrogen and phosphorus concentrations of woody plants differ in responses to climate, soil and plant growth form. Ecography 36, 178–184 (2013).Article 

Google Scholar 
Jiang, M., Caldararu, S., Zaehle, S., Ellsworth, D. S. & Medlyn, B. E. Towards a more physiological representation of vegetation phosphorus processes in land surface models. New Phytol. 222, 1223–1229 (2019).Article 
PubMed 

Google Scholar 
Kergoat, L., Lafont, S., Arneth, A., Le Dantec, V. & Saugier, B. Nitrogen controls plant canopy light-use efficiency in temperate and boreal ecosystems. J. Geophys. Res. Biogeosci. 113, G04017 (2008).Article 

Google Scholar 
Du, E. et al. Global patterns of terrestrial nitrogen and phosphorus limitation. Nat. Geosci. 13, 221–226 (2020).Article 
CAS 

Google Scholar 
Cleveland, C. C. et al. Patterns of new versus recycled primary production in the terrestrial biosphere. Proc. Natl Acad. Sci. USA 110, 12733–12737 (2013).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Veneklaas, E. J. et al. Opportunities for improving phosphorus-use efficiency in crop plants. New Phytol. 195, 306–320 (2012).Article 
PubMed 
CAS 

Google Scholar 
Janssens, I. A. & Luyssaert, S. Nitrogen’s carbon bonus. Nat. Geosci. 2, 318–319 (2009).Article 
CAS 

Google Scholar 
Luo, X. et al. Global variation in the fraction of leaf nitrogen allocated to photosynthesis. Nat. Commun. 12, 4866 (2021).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Lambers, H., Iii, F. & Pons, T. L. Plant Physiological Ecology (Springer, 2008).Vose, J. M. et al. Factors influencing the amount and distribution of leaf area of pine stands. Ecol. Bull. 43, 102−114 (1994).Carter, S. K., Saenz, D. & Rudolf, V. H. W. Shifts in phenological distributions reshape interaction potential in natural communities. Ecol. Lett. 21, 1143–1151 (2018).Article 
PubMed 

Google Scholar 
Sitch, S. et al. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12, 653–679 (2015).Article 

Google Scholar 
Farquhar, G. D., von Caemmerer, S. & Berry, J. A. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149, 78–90 (1980).Article 
PubMed 
CAS 

Google Scholar 
Krinner, G. et al. A dynamic global vegetation model for studies of the coupled atmosphere–biosphere system. Glob. Biogeochem. Cycles 19, GB1015 (2005).Article 

Google Scholar 
Murray-Tortarolo, G. et al. Evaluation of land surface models in reproducing satellite-derived LAI over the high-latitude Northern Hemisphere. Part I: Uncoupled DGVMs. Remote Sens. 5, 4819–4838 (2013).Article 

Google Scholar 
Lawrence, D. M. et al. The community land model version 5: description of new features, benchmarking, and impact of forcing uncertainty. J. Adv. Model. Earth Syst. 11, 4245–4287 (2019).Article 

Google Scholar 
Goll, D. S., Winkler, A. J. & Raddatz, T. Carbon–nitrogen interactions in idealized simulations with JSBACH (version 3.10). Geosci. Model Dev. 10, 2009–2030 (2017).Article 
CAS 

Google Scholar 
Goll, D. S., Vuichard, N. & Maignan, F. A representation of the phosphorus cycle for ORCHIDEE (revision 4520). Geosci. Model Dev. 10, 3745–3770 (2017).Article 
CAS 

Google Scholar 
Sun, Y., Goll, D. S. & Chang, J. Global evaluation of the nutrient-enabled version of the land surface model ORCHIDEE-CNP v1.2 (r5986). Geosci. Model Dev. 14, 1987–2010 (2021).Article 
CAS 

Google Scholar 
Clark, D. B., Mercado, L. M. & Sitch, S. The Joint UK Land Environment Simulator (JULES), model description—Part 2: Carbon fluxes and vegetation dynamics. Geosci. Model Dev. 4, 701–722 (2011).Article 

Google Scholar 
Terrer, C. et al. Nitrogen and phosphorus constrain the CO2 fertilization of global plant biomass. Nat. Clim. Change 9, 684–689 (2019).Article 
CAS 

Google Scholar 
Reyes-Fox, M. et al. Elevated CO2 further lengthens growing season under warming conditions. Nature 510, 259–262 (2014).Article 
PubMed 
CAS 

Google Scholar 
Guanter, L. et al. Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proc. Natl Acad. Sci. USA 111, E1327–E1333 (2014).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Sun, Y. et al. OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence. Science 358, eaam5747 (2017).Article 
PubMed 

Google Scholar 
Joiner, J. et al. The seasonal cycle of satellite chlorophyll fluorescence observations and its relationship to vegetation phenology and ecosystem atmosphere carbon exchange. Remote Sens. Environ. 152, 375–391 (2014).Article 

Google Scholar 
Chu, D. et al. Long time-series NDVI reconstruction in cloud-prone regions via spatio-temporal tensor completion. Remote Sens. Environ. 264, 112632 (2021).Joiner, J. et al. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2. Atmos. Meas. Tech. 6, 2803–2823 (2013).Article 

Google Scholar 
Zhang, Y., Joiner, J., Gentine, P. & Zhou, S. Reduced solar-induced chlorophyll fluorescence from GOME-2 during Amazon drought caused by dataset artifacts. Glob. Change Biol. 24, 2229–2230 (2018).Article 

Google Scholar 
Rodell, M., Houser, P. R. & Jambor, U. The Global Land Data Assimilation System. Bull. Am. Meteorol. Soc. 85, 381–394 (2004).Article 

Google Scholar 
Pastorello, G. et al. The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data. Sci. Data 7, 225 (2020).Article 
PubMed 
PubMed Central 

Google Scholar 
Reichstein, M. et al. On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm. Glob. Change Biol. 11, 1424–1439 (2005).Article 

Google Scholar 
LASSLOP, G. et al. Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: critical issues and global evaluation. Glob. Change Biol. 16, 187–208 (2010).Article 

Google Scholar 
Vautard, R., Yiou, P. & Ghil, M. Singular-spectrum analysis: a toolkit for short, noisy chaotic signals. Phys. D. 58, 95–126 (1992).Article 

Google Scholar 
Zhou, S. et al. Dominant role of plant physiology in trend and variability of gross primary productivity in North America. Sci. Rep. 7, 41366 (2017).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Butler, E. E., Datta, A. & Flores-Moreno Mapping local and global variability in plant trait distributions. Proc. Natl Acad. Sci. USA 114, E10937–E10946 (2017).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Simard, M., Pinto, N., Fisher, J. B. & Baccini, A. Mapping forest canopy height globally with spaceborne lidar. J. Geophys. Res. Biogeosci. 116, G04021 (2011).Article 

Google Scholar 
Ellis, E. C., Antill, E. C. & Kreft, H. All is not loss: plant biodiversity in the anthropocene. PLoS ONE 7, e30535 (2012).Article 
PubMed 
PubMed Central 
CAS 

Google Scholar 
Kier, G., Mutke, J., Dinerstein, E., Ricketts, T. H. & Barthlott, W. Global patterns of plant diversity and floristic knowledge. J. Biogeogr. 32, 1107–1116 (2005).Article 

Google Scholar 
Boles, S. H. et al. Land cover characterization of temperate East Asia using multi-temporal VEGETATION sensor data. Remote Sens. Environ. 90, 477–489 (2004).Article 

Google Scholar  More

Daszak, P. Emerging infectious diseases of wildlife-threats to biodiversity and human health. Science 287, 443–449 (2000).Article 
ADS 
CAS 

Google Scholar 
Jones, K. E. et al. Global trends in emerging infectious diseases. Nature 451, 990–993 (2008).Article 
ADS 
CAS 

Google Scholar 
Altizer, S., Ostfeld, R. S., Johnson, P. T. J., Kutz, S. & Harvell, C. D. Climate change and infectious diseases: From evidence to a predictive framework. Science 1979(341), 514–519 (2013).Article 
ADS 

Google Scholar 
Kilpatrick, A. M., Briggs, C. J. & Daszak, P. The ecology and impact of chytridiomycosis: An emerging disease of amphibians. Trends Ecol. Evol. 25, 109–118 (2010).Article 

Google Scholar 
Blehert, D. S. et al. Bat white-nose syndrome: An emerging fungal pathogen?. Science 1979(323), 227–227 (2009).Article 

Google Scholar 
Wilfert, L. et al. Deformed wing virus is a recent global epidemic in honeybees driven by Varroa mites. Science 1979(351), 594–597 (2016).Article 
ADS 

Google Scholar 
Garamszegi, L. Z. Climate change increases the risk of malaria in birds. Glob. Change Biol. 17, 1751–1759 (2011).Article 
ADS 

Google Scholar 
Zamora-Vilchis, I., Williams, S. E. & Johnson, C. N. Environmental temperature affects prevalence of blood parasites of birds on an elevation gradient: Implications for disease in a warming climate. PLoS ONE 7, e39208 (2012).Article 
ADS 
CAS 

Google Scholar 
Harvell, D., Altizer, S., Cattadori, I. M., Harrington, L. & Weil, E. Climate change and wildlife diseases: When does the host matter the most?. Ecology 90, 912–920 (2009).Article 

Google Scholar 
Burge, C. A. et al. Climate change influences on marine infectious diseases: Implications for management and society. Ann. Rev. Mar. Sci. 6, 249–277 (2014).Article 

Google Scholar 
Tracy, A. M., Pielmeier, M. L., Yoshioka, R. M., Heron, S. F. & Harvell, C. D. Increases and decreases in marine disease reports in an era of global change. Proc. R. Soc. B Biol. Sci. 286, 20191718 (2019).Article 

Google Scholar 
Lejeusne, C., Chevaldonné, P., Pergent-Martini, C., Boudouresque, C. F. & Pérez, T. Climate change effects on a miniature ocean: The highly diverse, highly impacted Mediterranean Sea. Trends Ecol. Evol. 25, 250–260 (2010).Article 

Google Scholar 
Basso, L. et al. The Pen Shell, Pinna nobilis: A review of population status and recommended research priorities in the Mediterranean Sea. Adv. Mar. Biol. 71, 109–160 (2015).Article 

Google Scholar 
Catanese, G. et al. Haplosporidium pinnae sp. nov., a haplosporidan parasite associated with mass mortalities of the fan mussel, Pinna nobilis, in the Western Mediterranean Sea. J. Invertebr. Pathol. 157, 9–24 (2018).Article 
CAS 

Google Scholar 
Vázquez-Luis, M. et al. S.O.S. Pinna nobilis: A mass mortality event in western Mediterranean sea. Front. Mar. Sci. 4, 220 (2017).Article 

Google Scholar 
García-March, J. R. et al. Can we save a marine species affected by a highly infective, highly lethal, waterborne disease from extinction?. Biol. Conserv. 243, 108498 (2020).Article 

Google Scholar 
Prado, P. et al. Pinna nobilis in suboptimal environments are more tolerant to disease but more vulnerable to severe weather phenomena. Mar. Environ. Res. 163, 105220 (2021).Article 
CAS 

Google Scholar 
Cabanellas-Reboredo, M. et al. Tracking a mass mortality outbreak of pen shell Pinna nobilis populations: A collaborative effort of scientists and citizens. Sci. Rep. 9, 13355 (2019).Article 
ADS 

Google Scholar 
Kersting, D. K. et al. Recruitment disruption and the role of unaffected populations for potential recovery after the Pinna nobilis mass mortality event. Front. Mar. Sci. 7, 1–11 (2020).Article 
ADS 

Google Scholar 
Box, A. et al. Reduced antioxidant response of the fan mussel Pinna nobilis related to the presence of haplosporidium pinnae. Pathogens 9, 1–14 (2020).Article 

Google Scholar 
Peyran, C., Morage, T., Nebot-Colomer, E., Iwankow, G. & Planes, S. Unexpected residual habitats raise hope for the survival of the fan mussel Pinna nobilis along the Occitan coast (Northwest Mediterranean Sea). Endanger Species Res. 48, 123–137 (2022).Article 

Google Scholar 
Rosa, R. D. et al. A hemocyte gene expression signature correlated with predictive capacity of oysters to survive Vibrio infections. BMC Genomics 13, 1–12 (2012).Article 

Google Scholar 
van de Vijver, M. J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002).Article 

Google Scholar 
Seppey, M., Manni, M. & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness. In Methods in Molecular Biology 227–245 https://doi.org/10.1007/978-1-4939-9173-0_14 (2019).Smith-Unna, R., Boursnell, C., Patro, R., Hibberd, J. M. & Kelly, S. TransRate: Reference-free quality assessment of de novo transcriptome assemblies. Genome Res. 26, 1134–1144 (2016).Article 
CAS 

Google Scholar 
Guo, X. & Ford, S. E. Infectious diseases of marine mollusks and host responses as revealed by genomic tools. Philos. Trans. R. Soc. B Biol. Sci. https://doi.org/10.1098/rstb.2015.0206 (2016).Article 

Google Scholar 
Pauletto, M. et al. Deep transcriptome sequencing of Pecten maximus hemocytes: A genomic resource for bivalve immunology. Fish Shellfish Immunol. 37, 154–165 (2014).Article 
CAS 

Google Scholar 
Caurcel, C. et al. MolluscDB: A genome and transcriptome database for molluscs. Philos. Trans. R. Soc. Lond. B Biol. Sci. 376, 20200157 (2021).Article 
CAS 

Google Scholar 
de Oliveira, A. L. et al. Comparative transcriptomics enlarges the toolkit of known developmental genes in mollusks. BMC Genomics 17, 1–23 (2016).Article 

Google Scholar 
Richardson, M. F. & De Sherman, C. D. H. De novo assembly and characterization of the invasive Northern Pacific Seastar transcriptome. PLoS ONE 10, e0142003 (2015).Article 

Google Scholar 
Zhang, D., Wang, F., Dong, S. & Lu, Y. D. De novo assembly and transcriptome analysis of osmoregulation in Litopenaeus vannamei under three cultivated conditions with different salinities. Gene 578, 185–193 (2016).Article 
CAS 

Google Scholar 
Werner, G. D. A., Gemmell, P., Grosser, S., Hamer, R. & Shimeld, S. M. Analysis of a deep transcriptome from the mantle tissue of Patella vulgata Linnaeus (Mollusca: Gastropoda: Patellidae) reveals candidate biomineralising genes. Mar. Biotechnol. 15, 230–243 (2013).Article 
CAS 

Google Scholar 
Ding, J. et al. Transcriptome sequencing and characterization of Japanese scallop Patinopecten yessoensis from different shell color lines. PLoS ONE 10, e0116406 (2015).Article 

Google Scholar 
Harney, E. et al. De novo assembly and annotation of the European abalone Haliotis tuberculata transcriptome. Mar Genomics 28, 11–16 (2016).Article 

Google Scholar 
Khalturin, K., Hemmrich, G., Fraune, S., Augustin, R. & Bosch, T. C. G. More than just orphans: Are taxonomically-restricted genes important in evolution?. Trends Genet. 25, 404–413. https://doi.org/10.1016/j.tig.2009.07.006 (2009).Article 
CAS 

Google Scholar 
Gibson, A. K., Smith, Z., Fuqua, C., Clay, K. & Colbourne, J. K. Why so many unknown genes? Partitioning orphans from a representative transcriptome of the lone star tick Amblyomma americanum. BMC Genomics 14, 135 (2013).Article 
CAS 

Google Scholar 
Albertin, C. B. et al. The octopus genome and the evolution of cephalopod neural and morphological novelties. Nature 524, 220–224 (2015).Article 
ADS 
CAS 

Google Scholar 
Vogeler, S., Galloway, T. S., Lyons, B. P. & Bean, T. P. The nuclear receptor gene family in the Pacific oyster, Crassostrea gigas, contains a novel subfamily group. BMC Genomics 15, 369 (2014).Article 

Google Scholar 
Allam, B. & Raftos, D. Immune responses to infectious diseases in bivalves. J. Invertebr. Pathol. 131, 121–136. https://doi.org/10.1016/j.jip.2015.05.005 (2015).Article 
CAS 

Google Scholar 
Allam, B. & Pales Espinosa, E. Bivalve immunity and response to infections: Are we looking at the right place?. Fish Shellfish Immunol. 53, 4–12. https://doi.org/10.1016/j.fsi.2016.03.037 (2016).Article 
CAS 

Google Scholar 
Qiu, L., Song, L., Xu, W., Ni, D. & Yu, Y. Molecular cloning and expression of a Toll receptor gene homologue from Zhikong Scallop, Chlamys farreri. Fish Shellfish Immunol. 22, 451–466 (2007).Article 
CAS 

Google Scholar 
Zhang, L., Li, L., Zhu, Y., Zhang, G. & Guo, X. Transcriptome analysis reveals a rich gene set related to innate immunity in the eastern oyster (Crassostrea virginica). Mar. Biotechnol. 16, 17–33 (2014).Article 

Google Scholar 
Moreira, R. et al. Transcriptomics of in vitro immune-stimulated hemocytes from the Manila clam Ruditapes philippinarum using high-throughput sequencing. PLoS ONE 7, e35009 (2012).Article 
ADS 
CAS 

Google Scholar 
Toubiana, M. et al. Toll-like receptors and MyD88 adaptors in Mytilus: Complete cds and gene expression levels. Dev. Comp. Immunol. 40, 158–166 (2013).Article 
CAS 

Google Scholar 
He, Y. et al. Transcriptome analysis reveals strong and complex antiviral response in a mollusc. Fish Shellfish Immunol. 46, 131–144 (2015).Article 
CAS 

Google Scholar 
Zhang, L. et al. Massive expansion and functional divergence of innate immune genes in a protostome. Sci. Rep. 5, 8693 (2015).Article 
CAS 

Google Scholar 
Casadevall, A. & Pirofski, L. A. Host–pathogen interactions: The attributes of virulence. J. Infect. Dis. 184, 337–344. https://doi.org/10.1086/322044 (2001).Article 
CAS 

Google Scholar 
Jones, B., Pascopella, L. & Falkow, S. Entry of microbes into the host: Using M cells to break the mucosal barrier. Curr. Opin. Immunol. 7, 474–478 (1995).Article 
CAS 

Google Scholar 
Liévin-Le Moal, V. & Servin, A. L. The front line of enteric host defense against unwelcome intrusion of harmful microorganisms: Mucins, antimicrobial peptides, and microbiota. Clin. Microbiol. Rev. 19, 315–337. https://doi.org/10.1128/CMR.19.2.315-337.2006 (2006).Article 
CAS 

Google Scholar 
Trigos, S., Vicente, N., Prado, P. & Espinós, F. J. Adult spawning and early larval development of the endangered bivalve Pinna nobilis. Aquaculture 483, 102–110 (2018).Article 

Google Scholar 
Vázquez-Luis, M., Nebot-Colomer, E., Deudero, S., Planes, S. & Boissin, E. Natural hybridization between pen shell species: Pinna rudis and the critically endangered Pinna nobilis may explain parasite resistance in P. nobilis. Mol. Biol. Rep. https://doi.org/10.1007/s11033-020-06063-5 (2021).Article 

Google Scholar 
Katsares, V., Tsiora, A., Galinou-Mitsoudi, S. & Imsiridou, A. Genetic structure of the endangered species Pinna nobilis (Mollusca: Bivalvia) inferred from mtDNA sequences. Biologia 63, 412–417 (2008).Article 
CAS 

Google Scholar 
Gonzalez-Wanguemert, M. et al. Highly polymorphic microsatellite markers for the Mediterranean endemic fan mussel Pinna nobilis. Mediterr. Mar. Sci. 16, 31 (2014).Article 

Google Scholar 
Peyran, C., Planes, S., Tolou, N., Iwankow, G. & Boissin, E. Development of 26 highly polymorphic microsatellite markers for the highly endangered fan mussel Pinna nobilis and cross-species amplification. Mol. Biol. Rep. 47, 2551–2559 (2020).Article 
CAS 

Google Scholar 
Peakall, R. & Smouse, P. E. GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—an update. Bioinformatics 28, 2537–2539 (2012).Article 
CAS 

Google Scholar  More