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    Multiple roles of bamboo as a regulator of cyanobacterial bloom in aquatic systems

    1.Merel, S. et al. State of knowledge and concerns on cyanobacterial blooms and cyanotoxins. Environ. Int. 59, 303–327 (2013).CAS 
    PubMed 

    Google Scholar 
    2.Huisman, J. et al. Cyanobacterial blooms. Nat. Rev. Microbiol. 16, 471–483 (2018).CAS 
    PubMed 

    Google Scholar 
    3.Paerl, H. W. & Otten, T. G. Harmful cyanobacterial blooms: Causes, consequences, and controls. Microb. Ecol. 65, 995–1010 (2013).CAS 
    PubMed 

    Google Scholar 
    4.Ibelings, B. W. & Chorus, I. Accumulation of cyanobacterial toxins in freshwater “seafood” and its consequences for public health: A review. Environ. Pollut. 150, 177–192 (2007).CAS 
    PubMed 

    Google Scholar 
    5.Cheung, M. Y., Liang, S. & Lee, J. Toxin-producing cyanobacteria in freshwater: A review of the problems, impact on drinking water safety, and efforts for protecting public health. J. Microbiol. 51, 1–10 (2013).CAS 
    PubMed 

    Google Scholar 
    6.Rousso, B. Z., Bertone, E., Stewart, R. & Hamilton, D. P. A systematic literature review of forecasting and predictive models for cyanobacteria blooms in freshwater lakes. Water Res. 182, 115959 (2020).7.Vadeboncoeur, Y. et al. From Greenland to green lakes: Cultural eutrophication and the loss of benthic pathways in lakes. Limnol. Oceanogr. 48, 1408–1418 (2003).ADS 

    Google Scholar 
    8.Han, Z. & Cui, B. Performance of macrophyte indicators to eutrophication pressure in ponds. Ecol. Eng. 96, 8–19 (2016).
    Google Scholar 
    9.Dorgham, M. Effects of Eutrophication. In Eutrophication: Causes, Consequences and Control (eds. Ansari, A. & Gill, S.). vol. 2, 29–44. (Springer, 2014).10.Glibert, P. M. Eutrophication, harmful algae and biodiversity—Challenging paradigms in a world of complex nutrient changes. Mar. Pollut. Bull. 124, 591–606 (2017).CAS 
    PubMed 

    Google Scholar 
    11.Lürling, M. & Mucci, M. Mitigating eutrophication nuisance: In-lake measures are becoming inevitable in eutrophic waters in the Netherlands. Hydrobiologia 847, 4447–4467 (2020).
    Google Scholar 
    12.Hall, R. O., Likens, G. E. & Malcom, H. M. Trophic basis of invertebrate production in 2 streams at the Hubbard Brook Experimental Forest. J. N. Am. Benthol. Soc. 20, 432–447 (2001).
    Google Scholar 
    13.Tanentzap, A. J. et al. Forests fuel fish growth in freshwater deltas. Nat. Commun. 5, 4077 (2014).ADS 
    CAS 
    PubMed 

    Google Scholar 
    14.Fey, S. B., Mertens, A. N. & Cottingham, K. L. Autumn leaf subsidies influence spring dynamics of freshwater plankton communities. Oecologia 178, 875–885 (2015).ADS 
    PubMed 

    Google Scholar 
    15.Wondzell, S. M. & Bisson, P. A. Influence of wood on aquatic biodiversity. Am. Fish. Soc. Symp. 37, 249–263 (2003).
    Google Scholar 
    16.Czarnecka, M. Coarse woody debris in temperate littoral zones: Implications for biodiversity, food webs and lake management. Hydrobiologia 767, 13–25 (2016).
    Google Scholar 
    17.Graham, M. D. & Vinebrooke, R. D. Coupling of boreal forests and lakes: Effects of conifer pollen on littoral communities. Limnol. Oceanogr. 51, 1524–1529 (2006).ADS 

    Google Scholar 
    18.Kelly, P. T. et al. Experimental whole-lake increase of dissolved organic carbon concentration produces unexpected increase in crustacean zooplankton density. Glob. Change Biol. 22, 2766–2775 (2016).ADS 

    Google Scholar 
    19.Shao, J., Li, R., Lepo, J. E. & Gu, J. D. Potential for control of harmful cyanobacterial blooms using biologically derived substances: Problems and prospects. J. Environ. Manag. 125, 149–155 (2013).
    Google Scholar 
    20.Tan, K. et al. A review of allelopathy on microalgae. Microbiology 165, 587–592 (2019).CAS 
    PubMed 

    Google Scholar 
    21.Tsuchiya, R., Kihei, M., Sakagami, Y. & Araki, T. Assessment of inhibition effect on growth of Microcystis aeruginosa by autoclaved water extracts from leaves of 104 woody plant species. J. Jpn. Limnol. 79, 41–48 (2018) (in Japanese with English abstract).22.Neilen, A. D., Hawker, D. W., O’Brien, K. R. & Burford, M. A. Phytotoxic effects of terrestrial dissolved organic matter on a freshwater cyanobacteria and green algae species is affected by plant source and DOM chemical composition. Chemosphere 184, 969–980 (2017).ADS 
    CAS 
    PubMed 

    Google Scholar 
    23.Chen, J., Zhang, H., Han, Z., Ye, J. & Liu, Z. The influence of aquatic macrophytes on Microcystis aeruginosa growth. Ecol. Eng. 42, 130–133 (2012).
    Google Scholar 
    24.Zhou, B., Fu, M., Xie, J., Yang, X. & Li, Z. Ecological functions of bamboo forest: Research and application. J. For. Res. 16, 143–147 (2005).
    Google Scholar 
    25.Xu, Q. F. et al. Rapid bamboo invasion (expansion) and its effects on biodiversity and soil processes +. Glob. Change Biol. 21, e00787 (2020).26.Shinohara, Y., Misumi, Y., Kubota, T. & Nanko, K. Characteristics of soil erosion in a moso-bamboo forest of western Japan: Comparison with a broadleaved forest and a coniferous forest. CATENA 172, 451–460 (2019).
    Google Scholar 
    27.Suzuki, S. & Nakagoshi, N. Expansion of bamboo forests caused by reduced bamboo-shoot harvest under different natural and artificial conditions. Ecol. Res. 23, 641–647 (2008).
    Google Scholar 
    28.Buziquia, S. T., Lopes, P. V. F., Almeida, A. K. & de Almeida, I. K. Impacts of bamboo spreading: A review. Biodivers. Conserv. 28, 3695–3711 (2019).
    Google Scholar 
    29.Kudo, G., Amagai, Y., Hoshino, B. & Kaneko, M. Invasion of dwarf bamboo into alpine snow-meadows in Northern Japan: Pattern of expansion and impact on species diversity. Ecol. Evol. 1, 85–96 (2011).PubMed 
    PubMed Central 

    Google Scholar 
    30.Wei, Q. et al. The diversity of soil mesofauna decline after bamboo invasion in subtropical China. Sci. Total Environ. 789, 147982 (2021).31.Fujii, Y. & Kobayashi, Y. Allelopathic activities of leaf leachates of Bamboo and Sasa; sandwich method of 80 species. Weed Biol. Manag. 39, 94–95 (1994).
    Google Scholar 
    32.Ogita, S. & Sasamoto, H. In vitro bioassay of allelopathy in four bamboo species; Bambusa multiplex, Phyllostachys bambusoides, P. nigra, Sasa kurilensis, using sandwich method and protoplast co-culture method with digital image analysis. Am. J. Plant Sci. 8, 1699 (2017).33.Chuyen, N. V., Kurata, T., Kato, H. & Fujimaki, M. Antimicrobial activity of Kumazasa (Sasa albo-marginata). Agr. Biol. Chem. 46, 971–978 (1982).
    Google Scholar 
    34.Chongtham, N., Bisht, M. S. & Haorongbam, S. Nutritional properties of bamboo shoots: potential and prospects for utilization as a health food. Compr. Rev. Food Sci. Food Saf. 10, 153–168 (2011).CAS 

    Google Scholar 
    35.Singhal, P., Satya, S. & Sudhakar, P. Antioxidant and pharmaceutical potential of bamboo leaves. Bamboo Sci. Cult. 24, 19–28 (2011).
    Google Scholar 
    36.Jin, L. et al. Bamboo nutrients and microbiome affect gut microbiome of giant panda. Symbiosis 80, 293–304 (2020).CAS 

    Google Scholar 
    37.Lin, Y. T. et al. Changes in the soil bacterial communities in a cedar plantation invaded by moso bamboo. Microb. Ecol. 67, 421–429 (2014).PubMed 

    Google Scholar 
    38.Li, Y. et al. Bamboo invasion of broadleaf forests altered soil fungal community closely linked to changes in soil organic C chemical composition and mineral N production. Plant Soil 418, 507–521 (2017).CAS 

    Google Scholar 
    39.Liu, X. et al. Moso bamboo (Phyllostachys edulis) invasion effects on litter, soil and microbial PLFA characteristics depend on sites and invaded forests. Plant Soil 438, 85–99 (2019).CAS 

    Google Scholar 
    40.O’connor, P. J., Covich, A. P., Scatena, F. N. & Loope, L. L. Non-indigenous bamboo along headwater streams of the Luquillo Mountains, Puerto Rico: Leaf fall, aquatic leaf decay and patterns of invasion. J. Trop. Ecol. 16, 499–516 (2000).
    Google Scholar 
    41.Cai, L., Zhang, K., McKenzie, E. H. & Hyde, K. D. Freshwater fungi from bamboo and wood submerged in the Liput River in the Philippines. Fungal Divers. 13, 1–12 (2003).
    Google Scholar 
    42.Suto, S. Mariculture of seaweeds and its problems in Japan. NOAA Tech. Rep. NMFS Circ 388, 7–16 (1974).
    Google Scholar 
    43.Milstein, A., Azim, M. E., Wahab, M. A. & Verdegem, M. C. J. The effects of periphyton, fish and fertilizer dose on biological processes affecting water quality in earthen fish ponds. Environ. Biol. Fishes 68, 247–260 (2003).
    Google Scholar 
    44.Azim, M. E. et al. The effect of periphyton substrate density on production in freshwater polyculture ponds. Aquaculture 232, 441–453 (2004).
    Google Scholar 
    45.Khatoon, H., Yusoff, F., Banerjee, S., Shariff, M. & Bujang, J. S. Formation of periphyton biofilm and subsequent biofouling on different substrates in nutrient enriched brackishwater shrimp ponds. Aquaculture 273, 470–477 (2007).
    Google Scholar 
    46.Ma, J. F. & Takahashi, E. Soil, Fertilizer, and Plant Silicon Research in Japan. (Elsevier Science, 2002).47.Akagi, T. et al. Dissolved ion analyses of stream water from bamboo forests: Implication for enhancement of chemical weathering by bamboo. Geochem. J. 46, 505–515 (2012).ADS 
    CAS 

    Google Scholar 
    48.Umemura, M. & Takenaka, C. Biological cycle of silicon in moso bamboo (Phyllostachys pubescens) forests in central Japan. Ecol. Res. 29, 501–510 (2014).CAS 

    Google Scholar 
    49.Lürling, M. & Roessink, I. On the way to cyanobacterial blooms: impact of the herbicide metribuzin on the competition between a green alga (Scenedesmus) and a cyanobacterium (Microcystis). Chemosphere 65, 618–626 (2006).ADS 
    PubMed 

    Google Scholar 
    50.Ji, X., Verspagen, J. M., Stomp, M. & Huisman, J. Competition between cyanobacteria and green algae at low versus elevated CO2: Who will win, and why?. J. Exp. Bot. 68, 3815–3828 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    51.Kang, C. et al. Effects of macrophyte Vallisneria asiatica biomasses on the algae community. Int. J. Environ. Eng. 7, 1161–1166 (2013).
    Google Scholar 
    52.Hao, A., Haraguchi, T., Kuba, T., Kai, H., Lin, Y. & Iseri, Y. Effect of the microorganism-adherent carrier for Nitzschia palea to control the cyanobacterial blooms. Ecol. Eng. 159, 106127 (2021).53.Wang, Z., Li, G., Li, G. & Li, D. The decline process and major pathways of Microcystis bloom in Taihu Lake, China. Chin. J. Oceanol. Limnol. 30, 37–46 (2012).ADS 
    CAS 

    Google Scholar 
    54.Xiao, M., Li, M. & Reynolds, C. S. Colony formation in the cyanobacterium. Microcystis Biol. Rev. 93, 1399–1420 (2018).PubMed 

    Google Scholar 
    55.Wu, Y. et al. Allelopathic control of cyanobacterial blooms by periphyton biofilms. Environ. Microb. 13, 604–615 (2011).CAS 

    Google Scholar 
    56.Ko, S. R. et al. Bioremediation of eutrophic water and control of cyanobacterial bloom by attached periphyton. Int. J. Environ. Sci. Technol. 16, 4173–4180 (2019).CAS 

    Google Scholar 
    57.Mühlbauer, L. K., Schulze, M., Harpole, W. S. & Clark, A. T. gauseR: Simple methods for fitting Lotka-Volterra models describing Gause’s “Struggle for Existence”. Ecol. Evol. 10, 13275–13283 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    58.Li, J. et al. Growth inhibition and oxidative damage of Microcystis aeruginosa induced by crude extract of Sagittaria trifolia tubers. J. Environ. Sci. 43, 40–47 (2016).
    Google Scholar 
    59.Ma, J. et al. Environmental factors controlling colony formation in blooms of the cyanobacteria Microcystis spp. in Lake Taihu, China. Harmful Algae 31, 136–142 (2014).60.Hua, Q. et al. Allelopathic effect of the rice straw aqueous extract on the growth of Microcystis aeruginosa. Ecotoxicol. Environ. Saf. 148, 953–959 (2018).CAS 

    Google Scholar 
    61.Zhao, W., Zheng, Z., Zhang, J., Roger, S. F. & Luo, X. Allelopathically inhibitory effects of eucalyptus extracts on the growth of Microcystis aeruginosa. Chemosphere 225, 424–433 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    62.Ball, A. S., Williams, M., Vincent, D. & Robinson, J. Algal growth control by a barley straw extract. Bioresour. Technol. 77, 177–181 (2001).CAS 
    PubMed 

    Google Scholar 
    63.Park, M. H., Kim, B. H., Chung, I. M. & Hwang, S. J. Selective bactericidal potential of rice (Oryza sativa L. var. japonica) hull extract on Microcystis strains in comparison with green algae and zooplankton. Bull. Environ. Contam. Toxicol. 83, 97–101 (2009).64.Le Rouzic, B., Thiébaut, G. & Brient, L. Selective growth inhibition of cyanobacteria species (Planktothrix agardhii) by a riparian tree leaf extract. Ecol. Eng. 97, 74–78 (2016).
    Google Scholar 
    65.Eladel, H., Battah, M., Dawa, A., Abd-Elhay, R. & Anees, D. Effect of rice straw extracts on growth of two phytoplankton isolated from a fish pond. J. Appl. Phycol. 31, 3557–3563 (2019).
    Google Scholar 
    66.Yang, J. et al. High temperature and pH favor Microcystis aeruginosa to outcompete Scenedesmus obliquus. Environ. Sci. Pollut. Res. 25, 4794–4802 (2018).CAS 

    Google Scholar 
    67.Grover, J. P. Phosphorus-dependent growth kinetics of 11 species of freshwater algae. Limnol. Oceanogr. 34, 341–348 (1989).ADS 
    CAS 

    Google Scholar 
    68.Shia, L. et al. Community structure of bacteria associated with Microcystis colonies from cyanobacterial blooms. J. Freshwat. Ecol. 25, 193–203 (2010).
    Google Scholar 
    69.Smith, D. J. et al. Individual Microcystis colonies harbour distinct bacterial communities that differ by Microcystis oligotype and with time. Environ. Microbiol. 23, 3020–3036 (2021).CAS 
    PubMed 

    Google Scholar  More

  • in

    Fecal and soil microbiota composition of gardening and non-gardening families

    1.Turnbaugh, P. J. et al. The human microbiome project. Nature 449, 804–810 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    2.Sonnenburg, J. L. & Bäckhed, F. Diet-microbiota interactions as moderators of human metabolism. Nature 535, 56–64 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    3.Rook, G. A. Regulation of the immune system by biodiversity from the natural environment: An ecosystem service essential to health. Proc. Natl. Acad. Sci. U.S.A. 110, 18360–18367 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    4.Huang, Y. J. et al. The microbiome in allergic disease: Current understanding and future opportunities. J. Allergy Clin. Immunol. 139, 1099–1110 (2018).
    Google Scholar 
    5.Morgan, X. C. et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment. Genome Biol. 13, 2 (2012).
    Google Scholar 
    6.Schnabl, B. Linking intestinal homeostasis and liver disease. Curr. Opin. Gastroenterol. 29, 264–270 (2013).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    7.Scott, F. W., Pound, L. D., Patrick, C., Eberhard, C. E. & Crookshank, J. A. Where genes meet environment—integrating the role of gut luminal contents, immunity and pancreas in type 1 diabetes. Transl. Res. 179, 183–198 (2017).CAS 
    PubMed 

    Google Scholar 
    8.Rook, G. A. W. Hygiene hypothesis and autoimmune diseases. Clin. Rev. Allergy Immunol. 42, 5–15 (2012).CAS 
    PubMed 

    Google Scholar 
    9.Deehan, E. C. & Walter, J. The fiber gap and the disappearing gut microbiome: implications for human nutrition. Trends Endocrinol. Metab. 27, 239–242 (2016).CAS 
    PubMed 

    Google Scholar 
    10.Rothschild, D. et al. Environment dominates over host genetics in shaping human gut microbiota. Nature 555, 210–215 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    11.Schloss, P. D., Iverson, K. D., Petrosino, J. F. & Schloss, S. J. The dynamics of a family’s gut microbiota reveal variations on a theme. Microbiome 2, 1–13 (2014).
    Google Scholar 
    12.Song, S. J. et al. Cohabiting family members share microbiota with one another and with their dogs. ELife 2, 1–22 (2013).
    Google Scholar 
    13.Seedorf, H. et al. Bacteria from diverse habitats colonize and compete in the mouse gut. Cell 159, 253–266 (2014).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    14.Zhou, D. et al. Exposure to soil, house dust and decaying plants increases gut microbial diversity and decreases serum immunoglobulin E levels in BALB/c mice. Environ. Microbiol. 18, 1326–1337 (2016).CAS 
    PubMed 

    Google Scholar 
    15.Schnorr, S. L. et al. Gut microbiome of the Hadza hunter-gatherers. Nat. Commun. 5, 2 (2014).
    Google Scholar 
    16.Tasnim, N., Abulizi, N., Pither, J., Hart, M. M. & Gibson, D. L. Linking the gut microbial ecosystem with the environment: Does gut health depend on where we live?. Front. Microbiol. 8, 1–8 (2017).
    Google Scholar 
    17.Schnorr, S. L. The soil in our microbial DNA informs about environmental interfaces across host and subsistence modalities: Soil taxa in human gut microbiome. Philos. Trans. R. Soc. B Biol. Sci. 375, 2 (2020).
    Google Scholar 
    18.Rook, G. A. W. 99th Dahlem conference on infection, inflammation and chronic inflammatory disorders: Darwinian medicine and the “hygiene” or “old friends” hypothesis. Clin. Exp. Immunol. 160, 70–79 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    19.de Filippo, C. et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc. Natl. Acad. Sci. 107, 14691–14696 (2010).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    20.Martínez, I. et al. The gut microbiota of rural papua new guineans: Composition, diversity patterns, and ecological processes. Cell Rep. 11, 527–538 (2015).PubMed 

    Google Scholar 
    21.Senghor, B., Sokhna, C., Ruimy, R. & Lagier, J. C. Gut microbiota diversity according to dietary habits and geographical provenance. Hum. Microbiome J. 7–8, 1–9 (2018).
    Google Scholar 
    22.Holscher, H. D. Dietary fiber and prebiotics and the gastrointestinal microbiota. Gut Microbes 8, 172–184 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    23.McDonald, D. et al. American gut: an open platform for citizen-science microbiome research. mSystems 3, 1–28 (2018).
    Google Scholar 
    24.Mills, J. G. et al. Urban habitat restoration provides a human health benefit through microbiome rewilding: The Microbiome Rewilding Hypothesis. Restor. Ecol. 25, 866–872 (2017).
    Google Scholar 
    25.Shenhav, L. et al. FEAST: Fast expectation-maximization for microbial source tracking. Nat. Methods 16, 627–632 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    26.Dhillon, J., Li, Z. & Ortiz, R. M. Almond snacking for 8 wk increases alpha-diversity of the gastrointestinal microbiome and decreases bacteroides fragilis abundance compared with an isocaloric snack in college freshmen. Curr. Dev. Nutr. 3, 1–9 (2019).CAS 

    Google Scholar 
    27.Thompson, S. V. et al. Avocado consumption alters gastrointestinal bacteria abundance and microbial metabolite concentrations among adults with overweight or obesity: A randomized controlled trial. J. Nutr. 151, 753–762 (2021).PubMed 

    Google Scholar 
    28.Yu, D. et al. Long-term diet quality is associated with gut microbiome diversity and composition among urban Chinese adults. Am. J. Clin. Nutr. 113, 684–694 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    29.Koh, A., de Vadder, F., Kovatcheva-Datchary, P. & Bäckhed, F. From dietary fiber to host physiology: Short-chain fatty acids as key bacterial metabolites. Cell 165, 1332–1345 (2016).CAS 
    PubMed 

    Google Scholar 
    30.Chung, W. S. F. et al. Modulation of the human gut microbiota by dietary fibres occurs at the species level. BMC Biol. 14, 1–13 (2016).
    Google Scholar 
    31.Kaczmarek, J. L. et al. Broccoli consumption affects the human gastrointestinal microbiota. J. Nutr. Biochem. 63, 27–34 (2019).CAS 
    PubMed 

    Google Scholar 
    32.Rose, D. J., DeMeo, M. T. & Keshavarzian, A. Influence of dietary fiber on inflammatory bowel disease and colon cancer: Importance of fermentation pattern. Nutr. Rev. 65, 51–62 (2007).PubMed 

    Google Scholar 
    33.Keohane, D. M. et al. Microbiome and health implications for ethnic minorities after enforced lifestyle changes. Nat. Med. 26, 1089–1095 (2020).CAS 
    PubMed 

    Google Scholar 
    34.Fierer, N. Embracing the unknown: Disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 15, 579–590 (2017).CAS 
    PubMed 

    Google Scholar 
    35.Ottman, N. et al. Soil exposure modifies the gut microbiota and supports immune tolerance in a mouse model. J. Allergy Clin. Immunol. 143, 1198-1206.e12 (2019).CAS 
    PubMed 

    Google Scholar 
    36.Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).ADS 
    CAS 

    Google Scholar 
    37.Rook, G. A. W., Lowry, C. A. & Raison, C. L. Microbial, “Old Friends”, immunoregulation and stress resilience. Evol. Med. Public Heal. 2013, 46–64 (2013).
    Google Scholar 
    38.Brame, J. E., Liddicoat, C., Abbott, C. A. & Breed, M. F. The potential of outdoor environments to supply beneficial butyrate-producing bacteria to humans. Sci. Total Environ. 777, 2 (2021).
    Google Scholar 
    39.Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    40.Venable, E. B. et al. Effects of feeding management on the equine cecal microbiota. J. Equine Vet. Sci. 49, 113–121 (2017).
    Google Scholar 
    41.Bolyen, E. et al. Reproducible, interactive, scalable, and extensible microbiome data science using QIIME2. Nat. Biotechnol. 37, 852–857 (2019).CAS 
    PubMed 
    PubMed Central 

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

    Google Scholar 
    43.Yilmaz, P. et al. The SILVA and “all-species living tree project (LTP)” taxonomic frameworks. Nucleic Acids Res. 42, 643–648 (2014).
    Google Scholar 
    44.Subar, A. F. et al. The automated self-administered 24-hour dietary recall (ASA24): A resource for researchers, clinicians, and educators from the national cancer institute. J. Acad. Nutr. Diet 112, 1134–1137 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    45.Miller, P. E. et al. Development and evaluation of a method for calculating the Healthy Eating Index-2005 using the Nutrition Data System for Research. Public Health Nutr. 14, 306–313 (2011).PubMed 

    Google Scholar 
    46.Krebs-Smith, S. M. et al. Update of the healthy eating index: HEI-2015. J. Acad. Nutr. Diet 118, 1591–1602 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    47.Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B 57, 289–300 (1995).MathSciNet 
    MATH 

    Google Scholar 
    48.Segata, N. et al. Metagenomic biomarker discovery and explanation. Genome Biol 12, 2 (2011).
    Google Scholar  More

  • in

    Influence of state reopening policies in COVID-19 mortality

    1.

    2.Li, Q. et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382, 1199 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    3.Anderson, R. M., Heesterbeek, H., Klinkenberg, D. & Hollingsworth, T. D. How will country-based mitigation measures influence the course of the COVID-19 epidemic? Lancent 395, 931 (2020).CAS 

    Google Scholar 
    4.WHO. Coronavirus disease (COVID 2019) situation report-30.5.Linton, N. M. et al. Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: A statistical analysis of publicly available case data. J. Clin. Med. 9, 538 (2020).PubMed Central 

    Google Scholar 
    6.
    https://www.washingtonpost.com/graphics/2020/national/states-reopening-coronavirus-map/
    7.Kaufman, G. B. et al. Comparing associations of state reopening strategies with COVID-19 burden. J. Gen. Intern. Med. 35, 3627 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    8.Woolf, S. H. et al. Excess deaths from COVID-19 and other causes, March-July 2020. JAMA 324, 1562 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    9.Faust, J. S. et al. All-cause excess mortality and COVID-19-related mortality among US adults aged 25–44 years, March–July 2020. JAMA 325, 785 (2021).CAS 
    PubMed 

    Google Scholar 
    10.Huppert, A. & Katriel, G. Mathematical modelling and prediction in infectious disease epidemiology. Clin. Microbiol. Infect. 19, 999 (2003).
    Google Scholar 
    11.Kermack, W. O. & McKendrick, A. G. A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. 115, 700 (1927).ADS 
    MATH 

    Google Scholar 
    12.Crokidakis, C. Modeling the early evolution of the COVID-19 in Brazil: Results from a susceptible-infectious-quarantined-recovered (SIQR) model. Int. J. Mod. Phys. C 31, 2050135 (2020).ADS 
    MathSciNet 
    CAS 

    Google Scholar 
    13.Bin, M. et al. Post-lockdown abatement of COVID-19 by fast periodic switching. PLoS Comput. Biol. 17, e1008604 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    14.Pedersen, M. G., & Meneghini, M. Quantifying undetected COVID-19 cases and effects of containment measures in Italy: Predicting phase 2 dynamics. https://doi.org/10.13140/RG.2.2.11753.85600 (2020).15.Calafiore, G. C., Novara, C., & Possieri, C. A Modified SIR Model for the COVID-19 Contagion in Italy. arXiv:2003.14391 (2020).16.Bastos, S. B., & Cajueiro, D. O. Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil. arXiv:2003.14288 (2020).17.Gaeta, G. Chaos, social distancing versus early detection and contacts tracing in epidemic management. Solitons Fractals 140, 110074 (2020).MathSciNet 

    Google Scholar 
    18.Gaeta, G. Asymptomatic infectives and R0 for COVID. arXiv:2003.14098 (2020).19.te Vrugt, M., Bickmann, J., & Wittkowski, R. Effects of social distancing and isolation on epidemic spreading: a dynamical density functional theory model. arXiv:2003.13967 (2020).20.Schulz, R. A., Coimbra-Araújo, C. H., & Costiche, S. W. S. COVID-19: A model for studying the evolution of contamination in Brazil. arXiv:2003.13932 (2020).21.Zhang, Y., Yu, X., Sun, H., Tick, Geoffrey R., Wei, W., & Jin, B. COVID-19 infection and recovery in various countries: Modeling the dynamics and evaluating the non-pharmaceutical mitigation scenarios. arXiv:2003.13901 (2020).22.Dell’Anna, L. Solvable delay model for epidemic spreading: the case of Covid-19 in Italy. Sci. Rep. 10, 15763 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    23.Sonnino, G. & Nardone, P. Annals of clinical and medical case reports dynamics of the COVID-19 comparison between the theoretical predictions and the real data, and predictions about returning to normal life. Ann. Clin. Med. Case Rep. 4, 1 (2020).
    Google Scholar 
    24.Notari, A. Temperature dependence of COVID-19 transmission. arXiv:2003.12417 (2020).25.Amaro, J. E. The D model for deaths by COVID-19. arXiv:2003:13747 (2020).26.Simha, A., Prasad, R. V., & Narayana, S. A simple stochastic SIR model for COVID 19 infection dynamics for Karnataka: Learning from Europe. arXiv:2003.11920 (2020).27.Acioli, P. H. Diffusion as a first model of spread of viral infection. arXiv:2003.11449 (2020).28.Zullo, F. Some numerical observations about the COVID-19 epidemic in Italy. arXiv:2003.11363 (2020).29.Sameni, R. Mathematical modeling of epidemic diseases; a case study of the COVID-19 coronavirus. arXiv:2003.11371 (2020).30.Radulescu, A., & Cavanagh, K. Management strategies in a SEIR model of COVID 19 community spread. arXiv:2003.11150 (2020).31.Roques, L., Klein, E., Papaix, J. & Soubeyrand, S. Using early data to estimate the actual infection fatality ratio from COVID-19 in France. MDPI Biol. 9, 97 (2020).CAS 

    Google Scholar 
    32.Teles, P. Predicting the evolution Of SARS-Covid-2 in Portugal using an adapted SIR Model previously used in South Korea for the MERS outbreak. arXiv:2003.10047 (2020).33.Piccolomini, E. L., & Zama, F. Preliminary analysis of COVID-19 spread in Italy with an adaptive SEIRD model. arXiv:2003.09909 (2020).34.Brugnano, L., & Iavernaro, F. A multi-region variant of the SIR model and its extensions. arXiv:2003.09875 (2020).35.Giordano, G. et al. Modelling the COVID-19 epidemic and implementation of population-wide interventions in Italy. the COVID19 IRCCS San Matteo Pavia Task Force. Nat. Med. 16, 855 (2020).
    Google Scholar 
    36.Zlatić, V., Barjašć, I., Kadović, A., Štefančić, H. & Gabrielli, A. Bi-stability of SUDR+ K model of epidemics and test kits applied to COVID-19. Nonlinear Dyn. 101, 1635 (2020).
    Google Scholar 
    37.Baker, R. Reactive Social distancing in a SIR model of epidemics such as COVID-19. arXiv:2003.08285 (2020).38.Biswas, K., Khaleque, A., & Sen, P. Covid-19 spread: Reproduction of data and prediction using a SIR model on Euclidean network. arXiv:2003.07063 (2020).39.Zhang, J., Wang, L., & Wang, J. SIR model-based prediction of infected population of coronavirus in Hubei Province. arXiv:2003.06419 (2020).40.Chen, Y.-C., Lu, P.-E., Chang, C.-S., & Liu, T.-H. A Time-dependent SIR model for COVID-19 with Undetectable Infected Persons. arXiv:2003.00122 (2020).41.Lloyd, A. L. Realistic distributions of infectious periods in epidemic models: Changing patterns of persistence and dynamics. Theor. Popul. Biol. 60, 59 (2001).CAS 
    PubMed 

    Google Scholar 
    42.Fokas, A. S., Dikaios, N. & Kastis, G. A. Mathematical models and deep learning for predicting the number of individuals reported to be infected with SARS-CoV-2. J. R. Soc. Interface 17, 20200494 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    43.Vadyala, S. R., Betgeri, S. N., Sherer, E. A., & Amritphale, A. Prediction of the number of COVID-19 confirmed cases based on K-means-LSTM. arXiv:2006.14752 (2020).44.Fokas, A. S., Cuevas-Maraver, J. & Kevrekidis, P. G. A quantitative framework for exploring exit strategies from the COVID-19 lockdown. Chaos Solitons Fractals 140, 11024 (2020).MathSciNet 

    Google Scholar 
    45.Coopera, I., Mondal, A. & Antonopoulos, C. G. A SIR model assumption for the spread of COVID-19 in different communities. Chaos Solitons Fractals 139, 110057 (2020).MathSciNet 

    Google Scholar 
    46.Bertozzi, A. L., Franco, E., Mohler, G., Short, M. B. & Sledge, D. The challenges of modeling and forecasting the spread of COVID-19. PNAS 117, 16732 (2020).MathSciNet 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    47.Prem, K. et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: A modelling study. The Lancet Public Health 5, e261 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    48.He, S., Peng, Y. & Sun, K. SEIR modeling of the COVID-19 and its dynamics. Nonlinear Dyn. 101, 1667 (2020).
    Google Scholar 
    49.Mwalili, S., Kimathi, M., Ojiambo, V., Gathungu, D. & Mbogo, R. SEIR model for COVID-19 dynamics incorporating the environment and social distancing. BMC Res. Notes 13, 352 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    50.Dehning, J. et al. Inferring change points in the spread of COVID-19 reveals the effectiveness of interventions. Science 369, 160 (2020).
    Google Scholar 
    51.Atkeson, A., Kopecky, K. A., & Zha, T. A. Estimating and forecasting disease scenarios for COVID-19 with an SIR Model. NBER Working Paper w27335 (2020).52.Wang, N., Fu, Y., Zhang, H. & Shi, H. An evaluation of mathematical models for the outbreak of COVID-19. Precis. Clin. Med. 3, 85 (2020).
    Google Scholar 
    53.Chang, S. et al. Mobility network models of COVID-19 explain inequities and inform reopening. Nature 589, 82 (2021).ADS 
    CAS 
    PubMed 

    Google Scholar 
    54.Alfano, V. & Ercolano, S. The efficacy of lockdown against COVID-19: A cross-country panel analysis. Appl. Health Econ. Health Policy 18, 509 (2020).PubMed 

    Google Scholar 
    55.Arshed, N., Meo, M. S. & Farooq, F. Empirical assessment of government policies and flattening of the COVID19 curve. J. Public Aff. 20, e2333 (2000).
    Google Scholar 
    56.Auger, K. A. et al. Association between statewide school closure and COVID-19 incidence and mortality in the US. JAMA 324, 859 (2020).CAS 
    PubMed 

    Google Scholar 
    57.Banerjee, T. & Nayak, A. Coping with being cooped up: Social distancing during COVID-19 among 60+ in the United States. Revista Panamericana de Salud Pública. 44, e81 (2020).
    Google Scholar 
    58.Castex, G., Dechter, E. & Lorca, M. COVID-19: The impact of social distancing policies, cross-country analysis. Econ. Disasters Clim. Change 5, 135 (2021).
    Google Scholar 
    59.Bennett, M. All things equal? Heterogeneity in policy effectiveness against COVID-19 spread in Chile. World Dev. 137, 105208 (2021).PubMed 

    Google Scholar 
    60.Castillo, R. C., Staguhn, E. D. & Weston-Farber, E. The effect of state-level stay-at-home orders on COVID-19 infection rates. Am. J. Infect. Control 48, 958 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    61.Cobb, J. S. & Seale, M. A. Examining the effect of social distancing on the compound growth rate of COVID-19 at the county level (United States) using statistical analyses and a random forest machine learning model. Public Health 185, 27 (2020).CAS 
    PubMed 

    Google Scholar 
    62.Courtemanche, C., Garuccio, J., Le, A., Pinkston, J. & Yelowitz, A. Strong social distancing measures in the United States reduced The COVID-19 growth rate. Health Aff. 39, 1237 (2020).
    Google Scholar 
    63.Dave, D., Friedson, A. I., Matsuzawa, K. & Sabia, J. J. When do shelter-in-place orders fight COVID-19 best? Policy heterogeneity across states and adoption time. Econ Inq. 59, 29 (2021).
    Google Scholar 
    64.Dave, D., Friedson, A., Matsuzawa, K., Sabia, J. J. & Safford, S. JUE insight: Were urban cowboys enough to control COVID-19? Local shelter-in-place orders and coronavirus case growth. J. Urban Econ. 2020, 103294 (2020).
    Google Scholar 
    65.Edelstein, M. et al. SARS-CoV-2 infection in London, England: Changes to community point prevalence around lockdown time, March–May 2020. J. Epidemiol. Commun. Health 75, 185 (2021).
    Google Scholar 
    66.Gallaway, M. S. et al. Trends in COVID-19 incidence after implementation of mitigation measures–Arizona, January 22–August 7, 2020. MMWR Morb. Mortal. Wkly. Rep. 69, 1460 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    67.Hsiang, S. et al. The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Nature 584, 262 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    68.Hyafil, A. & Moriña, D. Analysis of the impact of lockdown on the reproduction number of the SARS-Cov-2 in Spain. Gac. Sanit. 35, 453 (2021).PubMed 

    Google Scholar 
    69.Islam, N., Sharp, S. J. & Chowell, G. Physical distancing interventions and incidence of coronavirus disease 2019: Natural experiment in 149 countries. BMJ 2020, m2743 (2019).
    Google Scholar 
    70.Lyu, W. & Wehby, G. L. Comparison of estimated rates of coronavirus disease 2019 (COVID-19) in border counties in Iowa without a stay-at-home order and border counties in Illinois with a stay-at-home order. JAMA Netw. Open 3, e2011102 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    71.Lyu, W. & Wehby, G. L. Community use of face masks and COVID-19: Evidence from a natural experiment of state mandates in the US. Health Aff. 39, 1419 (2020).
    Google Scholar 
    72.Zhang, R., Li, Y., Zhang, A. L., Wang, Y. & Molina, M. J. Identifying airborne transmission as the dominant route for the spread of COVID-19. PNAS 117, 14857 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    73.Fokas, A. S., Athanassios, S., Jesus, C.-M. & Panayotis, G. K. A quantitative framework for exploring exit strategies from the COVID-19 lockdown. Chaos Solitons Fractals 140, 110244 (2020).MathSciNet 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    74.Olumoyin, K. D., Khaliq, A. Q. M., & Furati, F. M. A quantitative framework for exploring exit strategies from the COVID-19 lockdown. arXiv:2104.02603 (2021).75.Tam, K.-M., Walker, N. & Moreno, J. Effect of mitigation measures on the spreading of COVID-19 in hard-hit states in the U.S.. PLoS ONE 15, e0240877 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    76.Tam, K.-M., Walker, N., & Moreno, J. Projected Development of COVID-19 in Louisiana. arXiv:2004.02859 (2020).77.Marchant, R., Samia, N. I., Rosen, O., Tanner, M. A., & Cripps, S. Learning as we go: An examination of the statistical accuracy of COVID19 daily death count predictions. arXiv:2004.04734 (2020).78.Wu, Z. & McGoogan, J. M. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China. JAMA 323, 1239 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    79.Mizumoto, K., Kagaya, K., Zarebski, A. & Chowell, G. Estimating the asymptomatic proportion of coronavirus disease 2019 (COVID-19) cases on board the Diamond Princess cruise ship, Yokohama, Japan, 2020. Eurosurveill 25, 10 (2020).
    Google Scholar 
    80.
    https://github.com/nytimes/covid-19-data
    81.Holmdahl, I. & Buckee, C. Wrong but useful—What covid-19 epidemiologic models can and cannot tell us. N. Engl. J. Med. 383, 303 (2020).CAS 
    PubMed 

    Google Scholar 
    82.
    https://www.cdc.gov/coronavirus/2019-ncov/prevent-getting-sick/cloth-face-cover-guidance.html
    83.
    https://www.cdc.gov/mmwr/volumes/69/wr/mm695152a8.htm
    84.Abedi, V. et al. Racial, economic, and health inequality and COVID-19 infection in the United States. J. Racial Ethnic Health Disparities 8, 732 (2021).
    Google Scholar 
    85.Merow, C. & Urban, M. C. Seasonality and uncertainty in global COVID-19 growth rates. PNAS 117(44), 27456 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    86.Carlson, C. J., Gomez, A. C. R., Bansal, S. & Ryan, S. J. Misconceptions about weather and seasonality must not misguide COVID-19 response. Nat. Comm. 11, 412 (2020).
    Google Scholar 
    87.Burra, P. et al. Temperature and latitude correlate with SARS-CoV-2 epidemiological variables but not with genomic change worldwide. Evol. Bioinform. https://doi.org/10.1177/1176934321989695 (2021).Article 

    Google Scholar  More

  • in

    Competition between the tadpoles of Japanese toads versus frogs

    The average water temperature and pH in tanks was 19.29 ± 0.10 °C (SE, range: 17.0–22.5) and 8.59 ± 0.01 (SE, range 8.2–8.9) respectively. There was no significant difference among treatments (water temperature: F = 0.0086, df = 5, p = 1.0000, pH: F = 0.0063, df = 5, p = 1.0000).Intraspecific competition (density = 5, 15, 50 tadpoles per tank)The density of conspecifics did not have any significant effect on survival to metamorphosis of B. j. formosus (treatment: Wald chi-square = 3.468, df = 2, p = 0.1766; block: Wald chi-square = 7.770, df = 4, p = 0.1004; Fig. 1a). However, conspecific density had a significant effect on the combined responses of variables (larval period, metamorph SUL, metamorph mass) of B. j. formosus (MANOVA treatment: Wilks’ Lambda = 0.0181, F = 10.7224, df = 6, 10, p = 0.0007; block: Wilks’ Lambda = 0.2028, F = 0.9326, df = 12, 13.52, p = 0.5441). Higher densities of conspecifics increased the duration of the larval period (treatment: F = 6.678, df = 2, 9.30, p = 0.0159; block: F = 0.817, df = 4, 0.40, p = 0.7574; Fig. 1b), and decreased size at metamorphosis (SUL—treatment: F = 49.729, df = 2, 6.94, p  More

  • in

    Heterogeneity within and among co-occurring foundation species increases biodiversity

    1.Fernández, M. H. & Vrba, E. S. Rapoport effect and biomic specialization in African mammals: revisiting the climatic variability hypothesis. J. Biogeogr. 32, 903–918 (2005).
    Google Scholar 
    2.Tokeshi, M. & Arakaki, S. Habitat complexity in aquatic systems: fractals and beyond. Hydrobiologia 685, 27–47 (2012).
    Google Scholar 
    3.Connell, J. H. Diversity in tropical rain forests and coral reefs. Science 199, 1302–1310 (1978).ADS 
    CAS 
    PubMed 

    Google Scholar 
    4.Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc. Natl Acad. Sci. 96, 1463–1468 (1999).ADS 
    CAS 
    PubMed 
    PubMed Central 

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

    Google Scholar 
    6.Willig, M. R., Kaufman, D. M. & Stevens, R. D. Latitudinal gradients of biodiversity: pattern, process, scale, and synthesis. Ann. Rev. Ecol. Evol. Syst. 34, 273–309 (2003).
    Google Scholar 
    7.Stein, A., Gerstner, K. & Kreft, H. Environmental heterogeneity as a universal driver of species richness across taxa, biomes and spatial scales. Ecol. Lett. 17, 866–880 (2014).PubMed 

    Google Scholar 
    8.Thomsen, M. S. et al. Secondary foundation species enhance biodiversity. Nat. Ecol. Evol. 2, 634–639 (2018).PubMed 

    Google Scholar 
    9.Mac Arthur, R. H. & Wilson, E. O. The theory of island biogeography. Vol. 1 (Princeton university press, 2001).10.Guégan, J.-F., Lek, S. & Oberdorff, T. Energy availability and habitat heterogeneity predict global riverine fish diversity. Nature 391, 382–384 (1998).ADS 

    Google Scholar 
    11.Heidrich, L. et al. Heterogeneity–diversity relationships differ between and within trophic levels in temperate forests. Nat. Ecol. Evol. 4, 1204–1212 (2020).PubMed 

    Google Scholar 
    12.Kerr, J. T. & Packer, L. Habitat heterogeneity as a determinant of mammal species richness in high-energy regions. Nature 385, 252–254 (1997).ADS 
    CAS 

    Google Scholar 
    13.Ranjard, L. et al. Turnover of soil bacterial diversity driven by wide-scale environmental heterogeneity. Nat. Commun. 4, 1–10 (2013).
    Google Scholar 
    14.Fahrig, L. et al. Functional landscape heterogeneity and animal biodiversity in agricultural landscapes. Ecol. Lett. 14, 101–112 (2011).PubMed 

    Google Scholar 
    15.Ben‐Hur, E. & Kadmon, R. Heterogeneity–diversity relationships in sessile organisms: a unified framework. Ecol. Lett. 23, 193–207 (2020).PubMed 

    Google Scholar 
    16.Tews, J. et al. Animal species diversity driven by habitat heterogeneity/diversity: the importance of keystone structures. J. Biogeogr. 31, 79–92 (2004).
    Google Scholar 
    17.Tuanmu, M. N. & Jetz, W. A global, remote sensing‐based characterization of terrestrial habitat heterogeneity for biodiversity and ecosystem modelling. Global Ecol. Biogeogr. 24, 1329–1339 (2015).
    Google Scholar 
    18.MacArthur, R. H. & MacArthur, J. W. On bird species diversity. Ecology 42, 594–598 (1961).
    Google Scholar 
    19.Allouche, O., Kalyuzhny, M., Moreno-Rueda, G., Pizarro, M. & Kadmon, R. Area–heterogeneity tradeoff and the diversity of ecological communities. Proc. Natl Acad. Sci. 109, 17495–17500 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    20.Fahrig, L. Rethinking patch size and isolation effects: the habitat amount hypothesis. J. Biogeogr. 40, 1649–1663 (2013).
    Google Scholar 
    21.Gómez, J., Valladares, F. & Puerta-Piñero, C. Differences between structural and functional environmental heterogeneity caused by seed dispersal. Funct. Ecol. 18, 787–792 (2004).
    Google Scholar 
    22.Azevedo, J. C., Jack, S. B., Coulson, R. N. & Wunneburger, D. F. Functional heterogeneity of forest landscapes and the distribution and abundance of the red-cockaded woodpecker. Forest Ecol. Manag. 127, 271–283 (2000).
    Google Scholar 
    23.Watson, D. M. & Herring, M. Mistletoe as a keystone resource: an experimental test. Proc. Royal Soc. B: Biol. Sci. 279, 3853–3860 (2012).
    Google Scholar 
    24.Ellison, A. M. et al. Loss of foundation species: consequences for the structure and dynamics of forested ecosystems. Front. Ecol. Environ. 3, 479–486 (2005).
    Google Scholar 
    25.Altieri, A. H., Silliman, B. R. & Bertness, M. D. Hierarchical organization via a facilitation cascade in intertidal cordgrass bed communities. Am. Natur. 169, 195–206 (2007).PubMed 

    Google Scholar 
    26.Angelini, C. et al. Foundation species’ overlap enhances biodiversity and multifunctionality from the patch to landscape scale in southeastern US salt marshes. Proc. Royal Soc. B: Biol. Sci. 282, 20150421 (2015).27.Angelini, C. & Silliman, B. R. Secondary foundation species as drivers of trophic and functional diversity: evidence from a tree-epiphyte system. Ecology 95, 185–196 (2014).PubMed 

    Google Scholar 
    28.Bishop, M. J., Byers, J. E., Marcek, B. J. & Gribben, P. E. Density-dependent facilitation cascades determine epifaunal community structure in temperate Australian mangroves. Ecology 93, 1388–1401 (2012).PubMed 

    Google Scholar 
    29.Bishop, M. J., Fraser, J. & Gribben, P. E. Morphological traits and density of foundation species modulate a facilitation cascade in Australian mangroves. Ecology 94, 1927–1936 (2013).PubMed 

    Google Scholar 
    30.Thomsen, M. S., Metcalfe, I., South, P. & Schiel, D. R. A host-specific habitat former controls biodiversity across ecological transitions in a rocky intertidal facilitation cascade. Marine Freshwater Res. 67, 144–152 (2016).
    Google Scholar 
    31.Gribben, P. E. et al. Positive and negative interactions control a facilitation cascade. Ecosphere 8, e02065 (2017).
    Google Scholar 
    32.Shurin, J. B. et al. A cross‐ecosystem comparison of the strength of trophic cascades. Ecol. Lett. 5, 785–791 (2002).
    Google Scholar 
    33.Thomsen, M. S. Experimental evidence for positive effects of invasive seaweed on native invertebrates via habitat-formation in a seagrass bed. Aquat. Invas. 5, 341–346 (2010).
    Google Scholar 
    34.Gribben, P. E. et al. Facilitation cascades in marine ecosystems: a synthesis and future directions. Oceanogr. Marine Biol. 57, 127–168 (2019).
    Google Scholar 
    35.Gotelli, N. J. & Colwell, R. K. Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness. Ecol. Lett. 4, 379–391 (2001).
    Google Scholar 
    36.Thomsen, M. S. et al. Habitat cascades: the conceptual context and global relevance of facilitation cascades via habitat formation and modification. Integrat. Comparat. Biol. 50, 158–175 (2010).
    Google Scholar 
    37.Thomsen, M. S. et al. Modified kelp seasonality and invertebrate diversity where an invasive kelp co-occurs with native mussels. Marine Biol. 165, 173 (2018).
    Google Scholar 
    38.Borst, A. C. et al. Food or furniture: separating trophic and non‐trophic effects of Spanish moss to explain its high invertebrate diversity. Ecosphere 10, e02846 (2019).
    Google Scholar 
    39.Bologna, P. A. & Heck, K. L. Jr. Macrofaunal associations with seagrass epiphytes: relative importance of trophic and structural characteristics. J. Exp. Marine Biol. Ecol. 242, 21–39 (1999).
    Google Scholar 
    40.Huston, M. A. & Huston, M. A. Biological diversity: the coexistence of species. (Cambridge University Press, 1994).41.Borer, E. T. et al. Finding generality in ecology: a model for globally distributed experiments. Methods Ecol. Evol. 5, 65–73 (2014).
    Google Scholar 
    42.Fraser, L. H. et al. Coordinated distributed experiments: an emerging tool for testing global hypotheses in ecology and environmental science. Front. Ecol. Environ. 11, 147–155 (2013).
    Google Scholar 
    43.Thompson, K., Askew, A., Grime, J., Dunnett, N. & Willis, A. Biodiversity, ecosystem function and plant traits in mature and immature plant communities. Funct. Ecol. 19, 355–358 (2005).
    Google Scholar 
    44.Duffy, J. E. et al. Biodiversity mediates top–down control in eelgrass ecosystems: a global comparative‐experimental approach. Ecol. Lett. 18, 696–705 (2015).PubMed 

    Google Scholar 
    45.Arft, A. et al. Responses of tundra plants to experimental warming: meta‐analysis of the international tundra experiment. Ecol. Monogr. 69, 491–511 (1999).
    Google Scholar 
    46.Thomas, M. A. & Klaper, R. Genomics for the ecological toolbox. Trends Ecol. Evol. 19, 439–445 (2004).PubMed 

    Google Scholar 
    47.Thomsen, M. S. et al. A sixth‐level habitat cascade increases biodiversity in an intertidal estuary. Ecol. Evol. 6, 8291–8303 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    48.Ricklefs, R. E. Environmental heterogeneity and plant species diversity: a hypothesis. Am. Natur. 111, 376–381 (1977).
    Google Scholar 
    49.Lundholm, J. T. Plant species diversity and environmental heterogeneity: spatial scale and competing hypotheses. J. Vegetation Sci. 20, 377–391 (2009).
    Google Scholar 
    50.Tamme, R., Hiiesalu, I., Laanisto, L., Szava‐Kovats, R. & Pärtel, M. Environmental heterogeneity, species diversity and co‐existence at different spatial scales. J. Vegetation Sci. 21, 796–801 (2010).
    Google Scholar 
    51.Hughes, A. R., Gribben, P. E., Kimbro, D. L. & Bishop, M. J. Additive and site-specific effects of two foundation species on invertebrate community structure. Mar. Ecol. Prog. Series 508, 129–138 (2014).ADS 

    Google Scholar 
    52.Yakovis, E. & Artemieva, A. Cockles, barnacles and ascidians compose a subtidal facilitation cascade with multiple hierarchical levels of foundation species. Sci. Rep. 7, 1–11 (2017).CAS 

    Google Scholar 
    53.Thomsen, M. S., Stæhr, P. A., Nejrup, L. & Schiel, D. R. Effects of the invasive macroalgae Gracilaria vermiculophylla on two co-occurring foundation species and associated invertebrates. Aquat. Invas. 8, 133–145 (2013).
    Google Scholar 
    54.Littler, M. M. Morphological form and photosynthetic performances of marine macroalgae: tests of a functional/form hypothesis. Botan. Marina 22, 161–165 (1980).
    Google Scholar 
    55.Padilla, D. K. & Allen, B. J. Paradigm lost: reconsidering functional form and group hypotheses in marine ecology. J. Exp. Mar. Biol. Ecol. 250, 207–221 (2000).CAS 
    PubMed 

    Google Scholar 
    56.Wainwright, P. C. Functional morphology as a tool in ecological research. Ecol. Morphol.: Int. Organismal Biol. 42, 59 (1994).
    Google Scholar 
    57.Angelini, C. & Briggs, K. Spillover of secondary foundation species transforms community structure and accelerates decomposition in oak savannas. Ecosystems, 18, 780–791 (2015).
    Google Scholar 
    58.Gutiérrez, J. L., Bagur, M. & Palomo, M. G. Algal epibionts as co-engineers in mussel beds: effects on abiotic conditions and mobile interstitial invertebrates. Diversity 11, 17 (2019).
    Google Scholar 
    59.He, Q., Bertness, M. D. & Altieri, A. H. Global shifts towards positive species interactions with increasing environmental stress. Ecol. Lett. 16, 695–706 (2013).PubMed 

    Google Scholar 
    60.Watson, D. M. Mistletoe—a keystone resource in forests and woodlands worldwide. Ann. Rev. Ecol. Syst. 32, 219–249 (2001).
    Google Scholar 
    61.Mújica, E., Raventós, J., González, E. & Bonet, A. Long-term hurricane effects on populations of two epiphytic orchid species from Guanahacabibes Peninsula. Cuba. Lankesteriana Int. J. Orchidol. 13, 47–55 (2013).
    Google Scholar 
    62.Lobelle, D., Kenyon, E. J., Cook, K. J. & Bull, J. C. Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics. PLoS ONE 8, e57072 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    63.Svirski, E., Beer, S. & Friedlander, M. Gracilaria conferta and its epiphytes: Interrelationship between the red seaweed and Ulva cf. lactuca. Hydrobiologia 260, 391–396 (1993).
    Google Scholar 
    64.Cummins, S., Roberts, D. & Zimmerman, K. Effects of the green macroalga Enteromorpha intestinalis on macrobenthic and seagrass assemblages in a shallow coastal estuary. Marine Ecol. Prog. Series 266, 77–87 (2004).ADS 

    Google Scholar 
    65.Holmquist, J. G. Disturbance and gap formation in a marine benthic mosaic: influence of shifting macroalgal patches on seagrass structure and mobile invertebrates. Marine Ecol. Prog. Series 158, 121–130 (1997).ADS 

    Google Scholar 
    66.Siciliano, A., Schiel, D. R. & Thomsen, M. S. Effects of local anthropogenic stressors on a habitat cascade in an estuarine seagrass system. Marine Freshwater Res. 70, 1129–1142 (2019).
    Google Scholar 
    67.Field, R. et al. Spatial species‐richness gradients across scales: a meta‐analysis. J. Biogeogr. 36, 132–147 (2009).
    Google Scholar 
    68.Šímová, I., Li, Y. M. & Storch, D. Relationship between species richness and productivity in plants: the role of sampling effect, heterogeneity and species pool. J. Ecol. 101, 161–170 (2013).
    Google Scholar 
    69.Crain, C. M., Kroeker, K. & Halpern, B. S. Interactive and cumulative effects of multiple human stressors in marine systems. Ecol. Lett. 11, 1304–1315 (2008).PubMed 

    Google Scholar 
    70.Berlow, E. L. Strong effects of weak interactions in ecological communities. Nature 398, 330–334 (1999).ADS 
    CAS 

    Google Scholar 
    71.Darling, E. S. & Côté, I. M. Quantifying the evidence for ecological synergies. Ecol. Lett. 11, 1278–1286 (2008).PubMed 

    Google Scholar 
    72.Paine, R. T., Tegner, M. J. & Johnson, E. A. Compounded perturbations yield ecological surprises. Ecosystems 1, 535–545 (1998).
    Google Scholar 
    73.Christensen, M. R. et al. Multiple anthropogenic stressors cause ecological surprises in boreal lakes. Glob. Change Biol. 12, 2316–2322 (2006).ADS 

    Google Scholar 
    74.Strain, E. M. et al. A global analysis of complexity–biodiversity relationships on marine artificial structures. Glob. Ecol. Biogeogr. 30, 140–153 (2021).
    Google Scholar 
    75.Richardson, J. T. Eta squared and partial eta squared as measures of effect size in educational research. Educ. Res. Rev. 6, 135–147 (2011).
    Google Scholar 
    76.Clarke, K. R., Gorley, R., Somerfield, P. J. & Warwick, R. Change in marine communities: an approach to statistical analysis and interpretation. (Primer-E Ltd, 2014).77.Gartner, A., Tuya, F., Lavery, P. S. & McMahon, K. Habitat preferences of macroinvertebrate fauna among seagrasses with varying structural forms. J. Exp. Marine Biol. Ecol. 439, 143–151 (2013).
    Google Scholar 
    78.Green, D. S. & Crowe, T. P. Context-and density-dependent effects of introduced oysters on biodiversity. Biol. Invasions 16, 1145–1163 (2014).
    Google Scholar 
    79.Lawton, J. H. Are there general laws in ecology? Oikos 84, 177–192 (1999).
    Google Scholar 
    80.Borer, E. et al. What determines the strength of a trophic cascade? Ecology 86, 528–537 (2005).
    Google Scholar 
    81.Vellend, M. Conceptual synthesis in community ecology. Quart. Rev. Biol. 85, 183–206 (2010).PubMed 

    Google Scholar 
    82.Chase, J. M. & Leibold, M. A. Ecological niches: linking classical and contemporary approaches. (University of Chicago Press, 2003).83.Anderson, M. J. et al. Navigating the multiple meanings of β diversity: a roadmap for the practicing ecologist. Ecol. Lett. 14, 19–28 (2011).ADS 
    PubMed 

    Google Scholar 
    84.Anderson, M. J. A new method for non‐parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
    Google Scholar 
    85.Veech, J. A. & Crist, T. O. Habitat and climate heterogeneity maintain beta‐diversity of birds among landscapes within ecoregions. Glob. Ecol. Biogeogr. 16, 650–656 (2007).
    Google Scholar 
    86.Turner, M. G. Landscape ecology: the effect of pattern on process. Ann. Rev. Ecol. Syst. 20, 171–197 (1989).
    Google Scholar 
    87.Wilson, M. V. & Shmida, A. Measuring beta diversity with presence-absence data. J. Ecol. 72, 1055–1064 (1984).
    Google Scholar 
    88.Jost, L. Partitioning diversity into independent alpha and beta components. Ecology 88, 2427–2439 (2007).PubMed 

    Google Scholar 
    89.Socolar, J. B., Gilroy, J. J., Kunin, W. E. & Edwards, D. P. How should beta-diversity inform biodiversity conservation? Trends Ecol. Evol. 31, 67–80 (2016).PubMed 

    Google Scholar 
    90.McAfee, D., Cole, V. J. & Bishop, M. J. Latitudinal gradients in ecosystem engineering by oysters vary across habitats. Ecology 97, 929–939 (2016).PubMed 

    Google Scholar 
    91.Altieri, A. H. & Irving, A. D. Species coexistence and the superior ability of an invasive species to exploit a facilitation cascade habitat. PeerJ 5, e2848 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    92.Lindenmayer, D., Franklin, J. & Fischer, J. General management principles and a checklist of strategies to guide forest biodiversity conservation. Biol. Conser. 131, 433–445 (2006).
    Google Scholar 
    93.Le Roux, D. S., Ikin, K., Lindenmayer, D. B., Manning, A. D. & Gibbons, P. Single large or several small? Applying biogeographic principles to tree-level conservation and biodiversity offsets. Biol. Conser. 191, 558–566 (2015).
    Google Scholar 
    94.Wernberg, T. et al. Genetic diversity and kelp forest vulnerability to climatic stress. Sci. Rep. 8, 1–8 (2018).
    Google Scholar 
    95.Macintosh, D. J. & Ashton, E. C. A review of mangrove biodiversity conservation and management. Centre for tropical ecosystems research. (University of Aarhus, 2002).96.Grabowski, J. H. et al. Economic valuation of ecosystem services provided by oyster reefs. Bioscience 62, 900–909 (2012).
    Google Scholar 
    97.Renzi, J. J., He, Q. & Silliman, B. R. Harnessing positive species interactions to enhance coastal wetland restoration. Front. Ecol. Evol. 7, 131 (2019).
    Google Scholar 
    98.Silliman, B. R. et al. Facilitation shifts paradigms and can amplify coastal restoration efforts. Proc. Natl Acad. Sci. 112, 14295–14300 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    99.Bulleri, F. et al. Harnessing positive species interactions as a tool against climate-driven loss of coastal biodiversity. PLoS Biol. 16, e2006852 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    100.Brancalion, P. H. et al. Global restoration opportunities in tropical rainforest landscapes. Sci. Adv. 5, eaav3223 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    101.Burns, K. Meta-community structure of vascular epiphytes in a temperate rainforest. Botany 86, 1252–1259 (2008).
    Google Scholar 
    102.Chapman, M. & Blockley, D. Engineering novel habitats on urban infrastructure to increase intertidal biodiversity. Oecologia 161, 625–635 (2009).ADS 
    CAS 
    PubMed 

    Google Scholar 
    103.Schneider-Mayerson, M. Some islands will rise: Singapore in the Anthropocene. Resilience: J. Environ. Human. 4, 166–184 (2017).
    Google Scholar 
    104.Wangpraseurt, D. et al. Bionic 3D printed corals. Nat. Commun. 11, 1–8 (2020).
    Google Scholar 
    105.de Alvarenga, R. A. F., Galindro, B. M., de Fátima Helpa, C. & Soares, S. R. The recycling of oyster shells: an environmental analysis using Life Cycle Assessment. J. Environ. Manag. 106, 102–109 (2012).CAS 

    Google Scholar 
    106.Morris, J. P., Backeljau, T. & Chapelle, G. Shells from aquaculture: a valuable biomaterial, not a nuisance waste product. Rev. Aqua. 11, 42–57 (2019).
    Google Scholar 
    107.Hylander, K. & Nemomissa, S. Home garden coffee as a repository of epiphyte biodiversity in Ethiopia. Front. Ecol. Environ. 6, 524–528 (2008).
    Google Scholar 
    108.Franken, R. J. et al. Effects of interstitial refugia and current velocity on growth of the amphipod Gammarus pulex Linnaeus. J. North Am. Bentholog. Soc. 25, 656–663 (2006).
    Google Scholar 
    109.Bishop, M. et al. Facilitation of molluscan assemblages in mangroves by the fucalean alga Hormosira banksii. Marine Ecol. Prog. Series 392, 111–122 (2009).ADS 

    Google Scholar 
    110.Macreadie, P. I., Kimbro, D. L., Fourgerit, V., Leto, J. & Hughes, A. R. Effects of Pinna clams on benthic macrofauna and the possible implications of their removal from seagrass ecosystems. J. Molluscan Studies 80, 102–106 (2014).
    Google Scholar 
    111.Thomsen, M. S. et al. Earthquake-driven destruction of an intertidal habitat cascade. Aquat. Botany 164, 103217 (2020).
    Google Scholar 
    112.Enochs, I. C., Toth, L. T., Brandtneris, V. W., Afflerbach, J. C. & Manzello, D. P. Environmental determinants of motile cryptofauna on an eastern Pacific coral reef. Marine Ecol. Prog. Series 438, 105–118 (2011).ADS 

    Google Scholar  More

  • in

    Fungal fruit body assemblages are tougher in harsh microclimates

    1.McGill, B. J., Enquist, B. J., Weiher, E. & Westoby, M. Rebuilding community ecology from functional traits. Trends Ecol. Evol. 21, 178–185 (2006).PubMed 

    Google Scholar 
    2.Urban, M. C. et al. Improving the forecast for biodiversity under climate change. Science 353, 6304 (2016).
    Google Scholar 
    3.Sheridan, J. A. & Bickford, D. Shrinking body size as an ecological response to climate change. Nat. Clim. Chang. 1, 401–406 (2011).ADS 

    Google Scholar 
    4.Zeuss, D., Brandl, R., Brändle, M., Rahbek, C. & Brunzel, S. Global warming favours light-coloured insects in Europe. Nat. Commun. 5, 1–10 (2014).
    Google Scholar 
    5.Senf, C., Sebald, J. & Seidl, R. Increasing canopy mortality affects the future demographic structure of Europe’s forests. One Earth 4, 749–755 (2021).
    Google Scholar 
    6.Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    7.Scharenbroch, B. C. & Bockheim, J. G. Impacts of forest gaps on soil properties and processes in old growth northern hardwood-hemlock forests. Plant Soil 294, 219–233 (2007).CAS 

    Google Scholar 
    8.de Frenne, P. et al. Global buffering of temperatures under forest canopies. Nat. Ecol. Evol. 3, 744–749 (2019).PubMed 

    Google Scholar 
    9.Kermavnar, J. et al. Effects of various cutting treatments and topographic factors on microclimatic conditions in Dinaric fir-beech forests. Agric. For. Meteorol. 295, 108186 (2020).ADS 

    Google Scholar 
    10.Brown, M. J., Parker, G. G. & Posner, N. E. A survey of ultraviolet-B radiation in forests. J. Ecol. 82, 843 (1994).
    Google Scholar 
    11.Thom, D. et al. Effects of disturbance patterns and deadwood on the microclimate in European beech forests. Agric. For. Meteorol. 291, 108066 (2020).ADS 

    Google Scholar 
    12.Frank, A. et al. Risk of genetic maladaptation due to climate change in three major European tree species. Glob. Change Biol. 23, 5358–5371 (2017).ADS 

    Google Scholar 
    13.Maxime, C. & Hendrik, D. Effects of climate on diameter growth of co-occurring Fagus sylvatica and Abies alba along an altitudinal gradient. Trees 25, 265–276 (2011).
    Google Scholar 
    14.Vitasse, Y. et al. Contrasting resistance and resilience to extreme drought and late spring frost in five major European tree species. Glob. Change Biol. 25, 3781–3792 (2019).ADS 

    Google Scholar 
    15.Seidl, R. et al. Forest disturbances under climate change. Nat. Clim. Chang. 7, 395–402 (2017).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    16.Penone, C. et al. Specialisation and diversity of multiple trophic groups are promoted by different forest features. Ecol. Lett. 22, 170–180 (2019).PubMed 

    Google Scholar 
    17.Müller, J. et al. Primary determinants of communities in deadwood vary among taxa but are regionally consistent. Oikos 129, 1579–1588 (2020).
    Google Scholar 
    18.Krah, F.-S. et al. Independent effects of host and environment on the diversity of wood-inhabiting fungi. J. Ecol. 106, 1428–1442 (2018).
    Google Scholar 
    19.Nagy, L. G. et al. Six key traits of fungi: Their evolutionary origins and genetic bases. Microbiol. Spect. 5, 4 (2017).
    Google Scholar 
    20.Baldrian, P. Forest microbiome: Diversity, complexity and dynamics. FEMS Microbiol. Rev. 41, 109–130 (2017).CAS 
    PubMed 

    Google Scholar 
    21.Raudaskoski, M. & Salonen, M. Interrelationships between vegetative development and basidiocarp initiation. in The Ecology and Physiology of the Fungal Mycelium: Symposium of the British Mycological Society, vol. 8, p. 291 (Cambridge University Press, 1984).22.Kües, U. & Liu, Y. Fruiting body production in Basidiomycetes. Appl. Microbiol. Biotechnol. 54, 141–152 (2000).PubMed 

    Google Scholar 
    23.Sakamoto, Y. Influences of environmental factors on fruiting body induction, development and maturation in mushroom-forming fungi. Fungal Biol. Rev. 32, 236–248 (2018).
    Google Scholar 
    24.Luo, L., Zhang, S., Wu, J., Sun, X. & Ma, A. Heat stress in macrofungi: Effects and response mechanisms. Appl. Microbiol. Biotechnol. 1, 1–10 (2021).
    Google Scholar 
    25.Krah, F., Hess, J., Hennicke, F., Kar, R. & Bässler, C. Transcriptional response of mushrooms to artificial sun exposure. Ecol. Evol. 11, 10538–10546 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    26.Krah, F.-S. et al. European mushroom assemblages are darker in cold climates. Nat. Commun. 10, 2890 (2019).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    27.Bässler, C. et al. Global analysis reveals an environmentally driven latitudinal pattern in mushroom size across fungal species. Ecol. Lett. https://doi.org/10.1111/ele.13678 (2021).Article 
    PubMed 

    Google Scholar 
    28.Bässler, C. et al. Mean reproductive traits of fungal assemblages are correlated with resource availability. Ecol. Evol. 6, 582–592 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    29.Abrego, N., Norberg, A. & Ovaskainen, O. Measuring and predicting the influence of traits on the assembly processes of wood-inhabiting fungi. J. Ecol. 105, 1070–1081 (2016).
    Google Scholar 
    30.Sánchez-García, M. et al. Fruiting body form, not nutritional mode, is the major driver of diversification in mushroom-forming fungi. Proc. Natl. Acad. Sci. 117, 32528–32534 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    31.Hibbett, D. S. & Binder, M. Evolution of complex fruiting–body morphologies in homobasidiomycetes. Proc. R. Soc. Lond. B 269, 1963–1969 (2002).CAS 

    Google Scholar 
    32.Hibbett, D. S., Pine, E. M., Langer, E., Langer, G. & Donoghue, M. J. Evolution of gilled mushrooms and puffballs inferred from ribosomal DNA sequences. Proc. Natl. Acad. Sci. 94, 12002–12006 (1997).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    33.Halbwachs, H., Simmel, J. & Bässler, C. Tales and mysteries of fungal fruiting: How morphological and physiological traits affect a pileate lifestyle. Fungal Biol. Rev. 30, 36–61 (2016).
    Google Scholar 
    34.Wilson, A. W., Binder, M. & Hibbett, D. S. Effects of gasteroid fruiting body morphology on diversification rates in three independent clades of fungi estimated using binary state speciation and extinction analysis. Evol. Int. J. Org. Evol. 65, 1305–1322 (2011).
    Google Scholar 
    35.Cordero, R. J. B. & Casadevall, A. Functions of fungal melanin beyond virulence. Fungal Biol. Rev. 31, 99–112 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    36.Zamora-Camacho, F. J., Reguera, S. & Moreno-Rueda, G. Bergmann’s Rule rules body size in an ectotherm: Heat conservation in a lizard along a 2200-metre elevational gradient. J. Evol. Biol. 27, 2820–2828 (2014).CAS 
    PubMed 

    Google Scholar 
    37.Kalmus, H. Physiology and ecology of cuticle colour in insects. Nature 148, 693 (1941).ADS 

    Google Scholar 
    38.Law, S. J. et al. Darker ants dominate the canopy: Testing macroecological hypotheses for patterns in colour along a microclimatic gradient. J. Anim. Ecol. 89, 347–359 (2020).PubMed 

    Google Scholar 
    39.Bogert, C. M. Thermoregulation in reptiles, a factor in evolution. Evolution 3, 195–211 (1949).CAS 
    PubMed 

    Google Scholar 
    40.R Core Team. R: A Language and Environment for Statistical Computing. (R Core Team, 2015).41.Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2016).MATH 

    Google Scholar 
    42.Olou, B. A., Yorou, N. S., Striegel, M., Bässler, C. & Krah, F.-S. Effects of macroclimate and resource on the diversity of tropical wood-inhabiting fungi. For. Ecol. Manage. 436, 79–87 (2019).
    Google Scholar 
    43.Moser, M. Fungal growth and fructification under stress conditions. Ukrainian Bot. J. 50, 5–11 (1993).
    Google Scholar 
    44.Walter, H. et al. Vegetation of the Earth in Relation to Climate and the Eco-Physiological Conditions (English Universities Press, 1973).
    Google Scholar 
    45.Botti, D. A phytoclimatic map of Europe. Cybergeo Eur. J. Geogr. https://doi.org/10.4000/cybergeo.29495 (2018).Article 

    Google Scholar 
    46.Sofo, A., Manfreda, S., Fiorentino, M., Dichio, B. & Xiloyannis, C. The olive tree: A paradigm for drought tolerance in Mediterranean climates. Hydrol. Earth Syst. Sci. 12, 293–301 (2008).ADS 

    Google Scholar 
    47.Poorter, H., Niinemets, Ü., Poorter, L., Wright, I. J. & Villar, R. Causes and consequences of variation in leaf mass per area (LMA): A meta-analysis. New Phytol. 182, 565–588 (2009).PubMed 

    Google Scholar 
    48.Ellenberg, H. H. Spring areas and adjacent swamps. in Vegetation ecology of central Europe 313–313 (Cambridge University Press, 1988).49.Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L. & Heinsohn, R. Declining body size: A third universal response to warming?. New Phytol. 26, 285–291 (2011).
    Google Scholar 
    50.Stamets, P. Growing Gourmet and Medicinal Mushrooms (Ten Speed Press, 2011).
    Google Scholar 
    51.Cordero, R. J. B. et al. Impact of yeast pigmentation on heat capture and latitudinal distribution. Curr. Biol. 28, 2657-2664.e3 (2018).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    52.Graham, J. H. et al. Species richness, equitability, and abundance of ants in disturbed landscapes. Ecol. Ind. 9, 866–877 (2009).
    Google Scholar 
    53.Palladini, J. D., Jones, M. G., Sanders, N. J. & Jules, E. S. The recovery of ant communities in regenerating temperate conifer forests. For. Ecol. Manage. 242, 619–624 (2007).
    Google Scholar 
    54.Punttila, P., Haila, Y., Niemelä, J. & Pajunen, T. Ant communities in fragments of old-growth taiga and managed surroundings. Ann. Zool. Fenn. 31, 131–144 (1994).
    Google Scholar 
    55.Entling, W., Schmidt-Entling, M. H., Bacher, S., Brandl, R. & Nentwig, W. Body size–climate relationships of European spiders. J. Biogeogr. 37, 477–485 (2010).
    Google Scholar 
    56.Gotelli, N. J. Null model analysis of species co-occurrence patterns. Ecology 81, 2606–2621 (2000).
    Google Scholar 
    57.Tucker, C. M., Shoemaker, L. G., Davies, K. F., Nemergut, D. R. & Melbourne, B. A. Differentiating between niche and neutral assembly in metacommunities using null models of beta-diversity. Oikos 125, 778–789 (2015).
    Google Scholar 
    58.Shipley, B. et al. Reinforcing loose foundation stones in trait-based plant ecology. Oecologia 180, 923–931 (2016).ADS 
    PubMed 

    Google Scholar 
    59.Krah, F.-S. & Bässler, C. What can intraspecific trait variability tell us about fungal communities and adaptations?. Mycol. Prog. 20, 905–910 (2021).
    Google Scholar 
    60.Norros, V. & Halme, P. Growth sites of polypores from quantitative expert evaluation: Late-stage decayers and saprotrophs fruit closer to ground. Fungal Ecol. 28, 53–65 (2017).
    Google Scholar 
    61.Senf, C. et al. Canopy mortality has doubled in Europe’s temperate forests over the last three decades. Nat. Commun. 9, 4978 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    62.Bässler, C., Seifert, L. & Müller, J. The BIOKLIM project in the National Park Bavarian Forest: Lessons from a biodiversity survey. Silva Gabreta 21, 81–93 (2015).
    Google Scholar 
    63.Halme, P. & Kotiaho, J. S. The importance of timing and number of surveys in fungal biodiversity research. Biodivers. Conserv. 21, 205–219 (2012).
    Google Scholar 
    64.Crous, P. W. et al. MycoBank: An online initiative to launch mycology into the 21st century. Stud. Mycol. 50, 19–22 (2004).
    Google Scholar 
    65.van den Broek, E. L. & van Rikxoort, E. M. Evaluation of color representation for texture analysis. in Paper presented at 16th Belgium-Dutch Conference on Artificial Intelligence, BNAIC 2004, Groningen, Netherlands 35–42 (2004).66.Bernicchia, A. Fungi Europaei, Volume 10. Polyporaceae sl. (Alassio, Italia: Edizioni Candusso, 2005).67.Kembel, S. Community Phylogenetic Analysis with Picante Installing Picante 1–18 (Springer, 2009).
    Google Scholar 
    68.Gotelli, N. J. & Graves, G. R. Null Models in Ecology (Springer, 1996).
    Google Scholar 
    69.Hochberg, Y. & Tamhane, A. C. Multiple Comparison Procedures (Wiley, 1987).MATH 

    Google Scholar 
    70.Dormann, C. G., Elith, J., Bacher, S., Buchmann, C. & Lautenback, S. Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography 35, 001–020 (2012).
    Google Scholar 
    71.Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models using lme4. J. Stat. Softw. 67, 1–48 (2015).
    Google Scholar 
    72.Purhonen, J. et al. Morphological traits predict host-tree specialization in wood-inhabiting fungal communities. Fungal Ecol. 46, 100863 (2020).
    Google Scholar 
    73.Heilmann-Clausen, J. & Christensen, M. Does size matter?: On the importance of various dead wood fractions for fungal diversity in Danish beech forests. For. Ecol. Manage. 201, 105–117 (2004).
    Google Scholar 
    74.Lenth, R. V. Least-squares means: The R package lsmeans. J. Stat. Softw. 69, 1–33 (2016).
    Google Scholar  More

  • in

    Effects of reduced salinity caused by reclamation on population and physiological characteristics of the sesarmid crab Chiromantes dehaani

    1.Chen, L. et al. Spatiotemporal dynamics of coastal wetlands and reclamation in the Yangtze estuary during past 50 years (1960s–2015). Chin. Geogr. Sci. 28(3), 386–399 (2018).
    Google Scholar 
    2.Lv, W. et al. Effect of freshwater inflow on self-restoration of macrobenthic diversity in seaward intertidal wetlands influenced by reclamation projects in the Yangtze estuary, China. Mar. Pollut. Bull. 138, 177–186 (2019).CAS 
    PubMed 

    Google Scholar 
    3.Lv, W. et al. Loss and selfrestoration of macrobenthic diversity in reclamation habitats of estuarine islands in Yangtze Estuary, China. Mar. Pollut. Bull. 103, 128–136 (2016).CAS 
    PubMed 

    Google Scholar 
    4.Matsuda, O. & Kokubu, H. Recent coastal environmental management based on new concept of Satoumi which promotes land-ocean interaction: A case study in Japan. Estuar. Coast. Shelf S 183, 179–186 (2016).ADS 

    Google Scholar 
    5.Wang, J. et al. Exotic Spartina alterniflora provides compatible habitats for native estuarine crab Sesarma dehaani in the Yangtze River estuary. Ecol. Eng. 34, 57–64 (2008).CAS 

    Google Scholar 
    6.Lee, S. Y. & Khim, J. S. Hard science is essential to restoring soft-sediment intertidal habitats in burgeoning East Asia. Chemosphere 168, 765–776 (1998).ADS 

    Google Scholar 
    7.Wang, L. The complete larval development of Sesarma dehaani. J. Shanghai Fisheries Univ. 10(3), 199–206 (2001).CAS 

    Google Scholar 
    8.Liu, Z. et al. Different effects of reclamation methods on macrobenthos community structure in the Yangtze Estuary, China. Mar. Pollut. Bull. 127, 429–436 (2018).CAS 
    PubMed 

    Google Scholar 
    9.Henry, R. P., Lucu, C., Onken, H. & Weihrauch, D. Multiple functions of the crustacean gill: Osmotic/ionic regulation, acid-base balance, ammonia excretion, and bioaccumulation of toxic metals. Front. Physiol. 3, 431 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    10.McNamara, J. C. & Faria, S. C. Evolution of osmoregulatory patterns and gill ion transport mechanisms in the decapod Crustacea: A review. J. Comp. Physiol. B. 182(8), 997–1014 (2012).CAS 
    PubMed 

    Google Scholar 
    11.Thabet, R., Ayadi, H., Koken, M. & Leignel, V. Homeostatic responses of crustaceans to salinity changes. Hydrobiologia 799(1), 1–20 (2017).CAS 

    Google Scholar 
    12.Boonsanit, P. & Pairohakul, S. Effects of salinity on haemolymph osmolality, gill Na+/K+ ATPase and antioxidant enzyme activities in the male mud crab Scylla olivacea (Herbst, 1796). Mar. Biol. Res. 17(1), 86–97 (2021).
    Google Scholar 
    13.Wang, R. et al. Osmotic and ionic regulation and Na+/K+-ATPase, carbonic anhydrase activities in mature Chinese mitten crab, Eriocheir sinensis H. Milne Edwards, 1853 (Decapoda, Brachyura) exposed to different salinities. Crustaceana 85(12–13), 1431–1447 (2012).
    Google Scholar 
    14.Garçon, D. P. et al. Na+, K+-ATPase activity in the posterior gills of the blue crab, Callinectes ornatus (Decapoda, Brachyura): Modulation of ATP hydrolysis by the biogenic amines spermidine and spermine. J. Membr. Biol. 244, 9–20 (2011).PubMed 

    Google Scholar 
    15.Jiang, S. & Xu, Q. Influence of salinity stress on the activity of gill Na+/K+-ATPase in swimming crab(Portunus trituberculatus). J. Fish. China 35(10), 1475–1480 (2011).CAS 

    Google Scholar 
    16.Mo, J. L., Devos, P. & Trausch, G. Active absorption of Cl– and Na+ in posterior gills of Chinese crab, Eriocheir sinensis: modulation by dopamine and cAMP. J. Crust. Biol. 23, 505–512 (2003).
    Google Scholar 
    17.Charmantier, G. Ontogeny of osmoregulation in crustaceans: A review. Invertebr. Reprod. Dev. 33(2–3), 177–190 (1998).CAS 

    Google Scholar 
    18.Vargas-Chacoff, L. et al. Effects on the metabolism, growth, digestive capacity and osmoregulation of juvenile of sub-Antarctic Notothenioid fish Eleginops maclovinus acclimated at different salinities. Fish Physiol. Biochem. 41, 1369–1381 (2015).CAS 
    PubMed 

    Google Scholar 
    19.Wang, R. et al. The response of digestive enzyme activity in the mature Chinese mitten crab, Eriocheir sinensis (Decapoda: Brachyura), to gradual increase of salinity. Sci. Mar. 77(2), 323–329 (2013).
    Google Scholar 
    20.Li, E. et al. Comparison of digestive and antioxidant enzymes activities, haemolymph oxyhemocyanin contents and hepatopancreas histology of white shrimp, Litopenaeus vannamei, at various salinities. Aquaculture 274, 80–86 (2008).CAS 

    Google Scholar 
    21.Asaro, A., del Valle, J. C. & López Mañanes, A. A. Amylase, maltase and sucrase activities in hepatopancreas of the euryhaline crab Neohelice granulata (Decapoda: Brachyura: Varunidae): Partial characterization and response to low environmental salinity. Sci. Mar. 75, 517–524 (2011).CAS 

    Google Scholar 
    22.Sǒderhǎll, I. et al. Hemocyte production andmaturation in an invertebrate animal; proliferation and gene expression in hematopoietic stem cells of Pacifastacus leniusculus. Dev. Comp. Immunol. 97(8), 661–672 (2004).
    Google Scholar 
    23.Liu, S., Jiang, X., Mou, H., Wang, H. & Guan, H. Effects of immunopoiysaccharide on LSZ, ALP, ACP and POD activities of Penaeus chinensis serum. Oceanol. Limnol. Sin. 30(3), 278–283 (1999).CAS 

    Google Scholar 
    24.Ma, Z., Zhang, F. & Jing, A. Overview and graph theory of the immune system of crustacean. Aquacul. Sci. Technol. 11(8), 19–23 (2010).CAS 

    Google Scholar 
    25.Gu, Q. & He, L. Analysis of hemolymph osmotic pressure in crab (Eriocheir sinensis H. Milne Edwards) during oogenesis. Acta Zool. Sin. 36(2), 165–171 (1990).
    Google Scholar 
    26.Esser, L. J. & Cumberlidge, N. Evidence that salt water may not be a barrier to the dispersal of Asian freshwater crabs (Decapoda: Brachyura: Gecarcinucidae and potamidae). Raffles B. Zool. 59(2), 259–268 (2011).
    Google Scholar 
    27.Novo, M. S., Miranda, R. B. & Bianchini, A. Sexual and seasonal variations in osmoregulation and ionoregulation in the estuarine crab Chasmagnathus granulatus (Crustacea, Decapoda). J. Exp. Mar. Biol. Ecol. 323(2), 118–137 (2005).CAS 

    Google Scholar 
    28.Huong, D. T. T., Yang, W., Okuno, A. & Wilder, M. N. Changes in free amino acids in the hemolymph of giant freshwater prawn Macrobrachium rosenbergii exposed to varying salinities: Relationship to osmoregulatory ability. Comp. Biochem. Phys. A 128(2), 317–326 (2001).CAS 

    Google Scholar 
    29.Malmsten, M. & Larsson, A. Immobilization of trypsin on porous glycidyl methacrylate beads: Effects of polymer hydrophilization. Colloid. Surf. B 18, 277–284 (2000).CAS 

    Google Scholar 
    30.Hosoi, M. et al. Effect of salinity change on free amino acid content in Pacific oyster. Fish. Sci. 69(2), 395–400 (2003).CAS 

    Google Scholar 
    31.Wang, G. D., Xu, K. F., Tian, X. L., Dong, S. L. & Fang, Z. H. Changes in plasma osmolality, cortisol and amino acid levels of tongue sole (Cynoglossus semilaevis) at different salinities. J. Ocean Univ. China 14(5), 881–887 (2015).ADS 
    CAS 

    Google Scholar 
    32.Johnston, D. & Freeman, J. Dietary preference and digestive enzyme activities as indicators of trophic resource utilization by six species of crab. Biol. Bull. 208, 36–46 (2005).CAS 
    PubMed 

    Google Scholar 
    33.Zhang, Y. & Tong, C. Stomach content characteristics and feeding preference of Chiromantes dehaani in the salt marsh of Yangtze estuary. Chinese J. Ecol. 37(7), 2059–2066 (2018).
    Google Scholar 
    34.Ye, Y. et al. Comparative study on some traits of male and female Eriocheir sinensis raised in pond. Contemp. Aquacult. 38(4), 7–8 (2000).
    Google Scholar 
    35.Han, S. & Guan, W. Growth and maturity of Chiromantes dehaani in Dazhi River Estuary. Trans. Oceanol. Limnol. 15(1), 51–65 (2012).
    Google Scholar 
    36.Li, W., Guan, Y. & Yu, Z. Effects of salinity variation on outbreak of white spot syndrome and immunocompetence in Penaeus japonicas. Mar. Environ. Sci. 21(4), 6–9 (2002).
    Google Scholar 
    37.Pan, L. & Jiang, L. The effect of sudden changes in salinity and pH on immune activity of two species of shrimps. J. Ocean Univ. Qingdao 32(6), 903–910 (2002).CAS 

    Google Scholar 
    38.Gamperl, A. K., Vijayan, M. M. & Boutilier, R. G. Experimental control of stress hormone levels in fishes: Techniques and applications. Rev. Fish Biol. Fish. 4(2), 215–255 (1994).
    Google Scholar 
    39.Weerd, J. H. V. & Komen, J. The effects of chronic stress on growth in fish: A critical appraisal. Comp. Biochem. Phys. A 120(1), 107–112 (1998).
    Google Scholar 
    40.Barton, B. A., Schreck, C. B. & Barton, L. D. Effects of chronic cortisol administration and daily acute stress on growth, physiological conditions, and stress responses in juvenile rainbow trout. Dis. Aquat. Organ. 2(3), 173–185 (1987).CAS 

    Google Scholar 
    41.Zhao, Q., Qin, F., Li, C. & Jin, S. Preliminary study on the activities of enzymes in haemolymph of three species of marine crabs. J. Ningbo Univ. 22(1), 33–38 (2009).CAS 

    Google Scholar 
    42.Lv, W. et al. Macrobenthic diversity in protected, disturbed, and newly formed intertidal wetlands of a subtropical estuary in China. Mar. Pollut. Bull. 89, 259–266 (2014).CAS 
    PubMed 

    Google Scholar 
    43.Ma, Z., Jing, K., Tang, S. & Chen, J. Shorebirds in the eastern intertidal areas of Chongming island during the 2001 northern migration. Stilt 41, 6–10 (2002).
    Google Scholar 
    44.Sui, L., Wille, M., Cheng, Y., Wu, X. & Sorgeloos, P. Larviculture techniques of Chinese mitten crab Eriocheir sinensis. Aquaculture 315(1–2), 16–19 (2011).
    Google Scholar 
    45.Luo, M. et al. Community characteristics of macrobenthos in waters around the nature reserve of the Chinese sturgeon Acipenser sinensis and the adjacent waters in Yangtze River estuary. J. Appl. Ichthyol. 27, 425–432 (2011).
    Google Scholar 
    46.Yang, Z., Zhu, L., Zhao, X. & Cheng, Y. Effects of salinity stress on osmotic pressure, free amino acids, and immune-associated parameters of the juvenile Chinese mitten crab, Eriocheir sinensis. Aquaculture 549, 737776 (2022).
    Google Scholar 
    47.Tian, L., Tan, P., Yang, L., Zhu, W. & Xu, D. Effects of salinity on the growth, plasma ion concentrations, osmoregulation, non-specific immunity, and intestinal microbiota of the yellow drum (Nibea albiflora). Aquaculture 528, 735470 (2020).CAS 

    Google Scholar  More

  • in

    Fire-prone Rhamnaceae with South African affinities in Cretaceous Myanmar amber

    1.Lloyd, G. T. et al. Dinosaurs and the Cretaceous terrestrial revolution. Proc. R. Soc. B 275, 2483–2490 (2008).PubMed 
    PubMed Central 

    Google Scholar 
    2.Bininda-Emonds, O. R. P. et al. The delayed rise of present-day mammals. Nature 446, 507–512 (2007).CAS 
    PubMed 

    Google Scholar 
    3.Herrera-Flores, J. A., Stubbs, T. L. & Benton, M. J. Ecomorphological diversification of squamates in the Cretaceous. R. Soc. Open Sci. 8, 201961 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    4.Benton, M. J. The origins of modern biodiversity on land. Phil. Trans. R. Soc. B 365, 3667–3679 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    5.Roelants, K. et al. Global patterns of diversifcation in the history of modern amphibians. Proc. Natl Acad. Sci. USA 104, 887–892 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    6.Grosberg, R. K., Vermeij, G. J. & Wainwright, P. C. Biodiversity in water and on land. Curr. Biol. 22, 900–903 (2012).
    Google Scholar 
    7.Condamine, F. L., Silvestro, D., Koppelhus, E. B. & Antonelli, A. The rise of angiosperms pushed conifers to decline during global cooling. Proc. Natl Acad. Sci. USA 117, 28867–28875 (2020).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    8.Buggs, R. J. The deepening of Darwin’s abominable mystery. Nat. Ecol. Evol. 1, 0169 (2017).
    Google Scholar 
    9.Friis, E. M., Crane, P. R., Pedersen, K. R., Stampanoni, M. & Marone, F. Exceptional preservation of tiny embryos documents seed dormancy in early angiosperms. Nature 528, 551–554 (2015).PubMed 

    Google Scholar 
    10.Friis, E. M., Crane, P. R. & Pedersen, K. R. Early Flowers and Angiosperm Evolution (Cambridge Univ. Press, 2011).11.Friis, E. M., Pedersen, K. R. & Crane, P. R. Cretaceous angiosperm flowers: Innovation and evolution in plant reproduction. Palaeogeogr. Palaeoclimatol. Palaeoecol. 232, 251–293 (2006).
    Google Scholar 
    12.Soltis, P. S., Folk, R. A. & Soltis, D. E. Darwin review: angiosperm phylogeny and evolutionary radiations. Proc. R. Soc. B 286, 20190099 (2019).PubMed Central 

    Google Scholar 
    13.Bond, W. J. & Scott, A. C. Fire and the spread of flowering plants in the Cretaceous. New Phytol. 188, 1137–1150 (2010).PubMed 

    Google Scholar 
    14.Bond, W. J. & Midgley, J. J. Fire and the angiosperm revolutions. Int. J. Plant Sci. 173, 569–583 (2012).
    Google Scholar 
    15.Belcher, C. M. & Hudspith, V. A. Changes to Cretaceous surface fire behaviour influenced the spread of the early angiosperms. New Phytol. 213, 1521–1532 (2017).CAS 
    PubMed 

    Google Scholar 
    16.He, T., Lamont, B. B. & Pausas, J. G. Fire as a key driver of Earth’s biodiversity. Biol. Rev. 94, 1983–2010 (2019).PubMed 

    Google Scholar 
    17.Cruickshank, R. D. & Ko, K. Geology of an amber locality in the Hukawng Valley, Northern Myanmar. J. Asian Earth Sci. 21, 441–455 (2003).
    Google Scholar 
    18.Shi, G. H. et al. Age constraint on Burmese amber based on U–Pb dating of zircons. Cretac. Res. 37, 155–163 (2012).
    Google Scholar 
    19.Yu, T. et al. An ammonite trapped in Burmese amber. Proc. Natl Acad. Sci. USA 166, 11345–11350 (2019).
    Google Scholar 
    20.Xing, L. D. & Qiu, L. Zircon U–Pb age constraints on the Hkamti amber biota in northern Myanmar. Palaeogeogr. Palaeoclimatol. Palaeoecol. 558, 109960 (2020).
    Google Scholar 
    21.Xia, F. Y., Yang, G., Zhang, Q. & Shi, G. L. Amber Lives Through Time and Space (Beijing Science Press, 2015).22.Poinar, G. O. & Brown, A. E. A green algae (Chaetophorales: Chaetophoraceae) in Burmese amber. Hist. Biol. 33, 323–327 (2019).
    Google Scholar 
    23.Liu, Z. J., Huang, D., Cai, C. Y. & Wang, X. The core eudicot boom registered in Myanmar amber. Sci. Rep. 8, 16765 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    24.Poinar, G. O. & Chambers, K. L. Tropidogyne pentaptera sp. nov., a new mid-Cretaceous fossil angiosperm flower in Burmese amber. Palaeodiversity 10, 135–140 (2017).
    Google Scholar 
    25.Poinar, G. O. & Chambers, K. L. Palaeoanthella huangii gen. and sp. nov., an Early Cretaceous flower (Angiospermae) in Burmese amber. SIDA 21, 2087–2092 (2005).
    Google Scholar 
    26.Goldblatt, P. An analysis of the flora of Southern Africa: its characteristics, relationships, and orgins. Ann. Mo. Bot. Gard. 65, 369–436 (1978).
    Google Scholar 
    27.Verboom, G. A. et al. in Fynbos: Ecology, Evolution and Conservation of a Megadiverse Region (eds Allsopp, N. et al.) 93–118 (Oxford Univ. Press, 2014).28.Hauenschild, F., Favre, A., Michalak, I. & Muellner-Riehl, A. N. The influence of the Gondwanan breakup on the biogeographic history of the ziziphoids (Rhamnaceae). J. Biogeogr. 45, 2669–2677 (2018).
    Google Scholar 
    29.Onstein, R. E. & Linder, H. P. Beyond climate: convergence in fast evolving sclerophylls in Cape and Australian Rhamnaceae predates the mediterranean climate. J. Ecol. 104, 665–677 (2016).
    Google Scholar 
    30.Brown, S., Scott, A. C., Glasspool, I. J. & Collinson, M. E. Cretaceous wildfires and their impact on the Earth system. Cretac. Res. 36, 162–190 (2012).
    Google Scholar 
    31.Richardson, J. E. et al. Rapid and recent origin of species richness in the Cape flora of South Africa. Nature 412, 181–183 (2001).CAS 
    PubMed 

    Google Scholar 
    32.Pillans, N. S. The genus Phylica. J. S. Afr. Bot. 8, 1–164 (1942).
    Google Scholar 
    33.Rebelo, T. et al. in The vegetation of South Africa, Lesotho and Swaziland (eds Mucina, L. & Rutherford, M. C.) 52–219 (South African National Biodiversity Institute, 2006).34.Gimingham, C. H. & Cowling, R. The ecology of fynbos: nutrients, fire and diversity. J. Ecol. 81, 195–196 (1993).
    Google Scholar 
    35.Richardson, J. E., Fay, M. F., Cronk, Q. C. B. & Cronk, M. W. Species delimitation and the origin of populations in island representatives of Phylica (Rhamnaceae). Evolution 57, 816–827 (2003).PubMed 

    Google Scholar 
    36.Richardson, J. E. Molecular Systematics of the Genus Phylica L. With an Emphasis on the Island Species (Edinburgh Univ. Press, 1999).37.Schirarend, C. & Köhler, E. World Pollen and Spore Flora: Rhamnaceae Juss (Scandinavian Univ. Press, 1993).38.Medan, D. & Schirarend, C. in Flowering plants · Dicotyledons (ed. Kubitzki, K.) 320–338 (Springer, 2004).39.Gotelli, M. M., Galati, B. G. & Medan, D. Morphological and ultrastructural studies of floral nectaries in Rhamnaceae. J. Torrey Bot. Soc. 144, 63–73 (2017).
    Google Scholar 
    40.Friedrich, O., Norris, R. D. & Erbacher, J. Evolution of middle to Late Cretaceous oceans–a 55 m.y. record of Earth’s temperature and carbon cycle. Geology 40, 107–110 (2012).CAS 

    Google Scholar 
    41.Lenton, T. M., Daines, S. J. & Mills, B. J. W. COPSE reloaded: an improved model of biogeochemical cycling over Phanerozoic time. Earth Sci. Rev. 178, 1–28 (2018).CAS 

    Google Scholar 
    42.Huber, B. T., Hodell, D. A. & Hamilton, C. P. Middle-Late Cretaceous climate of the southern high latitudes: stable isotopic evidence for minimal equator-to-pole thermal gradients. Geol. Soc. Am. Bull. 107, 1164–1191 (1995).
    Google Scholar 
    43.Belcher, C. M., Yearsley, J. M., Hadden, R. M., Mcelwain, J. C. & Rein, G. Baseline intrinsic flammability of Earth’s ecosystems estimated from paleoatmospheric oxygen over the past 350 million years. Proc. Natl Acad. Sci. USA 107, 22448–22453 (2010).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    44.Berner, R. A., Beerling, D. J., Dudley, R., Robinson, J. M. & Wildman, R. A. Phanerozoic atmospheric oxygen. Annu. Rev. Earth Planet. Sci. 31, 105–134 (2003).CAS 

    Google Scholar 
    45.Glasspool, I. J. & Scott, A. C. Phanerozoic concentrations of atmospheric oxygen reconstructed from sedimentary charcoal. Nat. Geosci. 3, 627–630 (2010).CAS 

    Google Scholar 
    46.Poulsen, C. J., Tabor, C. & White, J. D. Long-term climate forcing by atmospheric oxygen concentrations. Science 348, 1238–1241 (2015).CAS 
    PubMed 

    Google Scholar 
    47.Hudspith, V. A. & Belcher, C. M. Fire biases the production of charred flowers: implications for the Cretaceous fossil record. Geology 45, 727–730 (2017).
    Google Scholar 
    48.Scott, A. C. Charcoal recognition, taphonomy and uses in palaeoenvironmental analysis. Palaeogeogr. Palaeoclimatol. Palaeoecol. 291, 11–39 (2010).
    Google Scholar 
    49.Scott, A. C. The use of charcoal to interpret Cretaceous wildfires and volcanic activity. Glob. Geol. 22, 217–241 (2019).
    Google Scholar 
    50.Scott, A. C., Cripps, J. A., Nichols, G. J. & Collinson, M. E. The taphonomy of charcoal following a recent heathland fire and some implications for the interpretation of fossil charcoal deposits. Palaeogeogr. Palaeoclimatol. Palaeoecol. 164, 1–31 (2000).
    Google Scholar 
    51.Whtilock, C., Higuera, P. E., McWethy, D. B. & Briles, C. E. Paleoecological perspectives on fire ecology: revisiting the fire-regime concept. Open Ecol. J. 3, 6–23 (2010).
    Google Scholar 
    52.Bond, W. J. & Keeley, J. E. Fire as global ‘herbivore’: the ecology and evolution of flammable ecosystems. Trends Ecol. Evol. 20, 387–394 (2005).PubMed 

    Google Scholar 
    53.Bowman, D. M. J. S. et al. Fire in the Earth system. Science 324, 481–484 (2009).CAS 
    PubMed 

    Google Scholar 
    54.Crisp, M. D., Burrows, G. E., Cook, L. G., Thornhill, A. H. & Bowman, D. M. J. S. Flammable biomes dominated by eucalypts originated at the Cretaceous–Paleogene boundary. Nat. Commun. 2, 193 (2011).PubMed 

    Google Scholar 
    55.Pausas, J. G. & Keeley, J. E. A burning story: the role of fire in the history of life. Bioscience 59, 593–601 (2009).
    Google Scholar 
    56.Scott, A. C. Burning Planet. The Story of Fire Through Time (Oxford Univ. Press, 2018).57.Scott, A. C. Fire: A Very Short Introduction (Oxford Univ. Press, 2020).58.Scott, A. C., Bowman, D. J. M. S., Bond, W. J., Pyne, S. J. & Alexander M. Fire on Earth: An Introduction (J. Wiley & Sons Press, 2014).59.Keeley, J. E., Pausas, J. G., Rundel, P. W., Bond, W. J. & Bradstock, R. A. Fire as an evolutionary pressure shaping plant traits. Trends Plant Sci. 16, 406–411 (2011).CAS 
    PubMed 

    Google Scholar 
    60.Lenton,T. M. in Fire Phenomena and the Earth System: An Interdisciplinary Guide to Fire Science (ed. Belcher, C. M.) 289–308 (J. Wiley & Sons Press, 2013).61.Herendeen, P. S., Magallon-Puebla, S., Lupia, R., Crane, P. R. & Kobylinska, J. A preliminary conspectus of the Allon flora from the Late Cretaceous (Late Santonian) of the central Georgia, USA. Ann. Mo. Bot. Gard. 86, 407–471 (1999).
    Google Scholar 
    62.He, T., Pausas, J. G., Belcher, C. M., Schwilk, D. W. & Lamont, B. B. Fire-adapted traits of Pinus arose in the fiery Cretaceous. New Phytol. 194, 751–759 (2012).PubMed 

    Google Scholar 
    63.Cornwell, W. K. et al. Flammability across the gymnosperm phylogeny: the importance of litter particle size. New Phytol. 206, 672–681 (2015).PubMed 

    Google Scholar 
    64.Lamont, B. B. & He, T. Fire-adapted Gondwanan angiosperm floras evolved in the Cretaceous. BMC Evol. Biol. 12, 223 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    65.He, T., Lamont, B. B. & Manning, J. A. Cretaceous origin for fire adaptations in the Cape flora. Sci. Rep. 6, 34880 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    66.He, T., Lamont, B. B. & Downes, K. S. Banksia born to burn. New Phytol. 191, 184–196 (2011).PubMed 

    Google Scholar 
    67.Midgley, J. & Bond, W. Pushing back in time, the role of fire in plant evolution. New Phytol. 191, 5–7 (2011).PubMed 

    Google Scholar 
    68.Scott, A. C. The Pre-Quaternary history of fire. Palaeogeogr. Palaeoclimatol. Palaeoecol. 164, 281–329 (2000).
    Google Scholar 
    69.Midgley, J. J., Kruger, L. M. & Skelton, R. How do fires kill plants? The hydraulic death hypothesis and Cape Proteaceae “fire-resisters”. S. Afr. J. Bot. 77, 381–386 (2011).
    Google Scholar 
    70.Lamont, B. B., Groom, P. K., Williams, M. & He, T. LMA, density and thickness: recognizing different leaf shapes and correcting for their non-laminarity. New Phytol. 207, 942–947 (2015).PubMed 

    Google Scholar 
    71.Lamont, B. B., He, T. & Yan, Z. Evolutionary history of fire-stimulated resprouting, flowering, seed release and germination. Biol. Rev. 94, 903–928 (2019).PubMed 

    Google Scholar 
    72.Schwilk, D. W. & Kerr, B. Genetic niche-hiking: an alternative explanation for the evolution of flammability. Oikos 99, 431–442 (2002).
    Google Scholar 
    73.Kilian, D. & Cowling, R. M. Comparative seed biology and co-existence of two fynbos shrub species. J. Veg. Sci. 3, 637–646 (1992).
    Google Scholar 
    74.Hall, S. A., Newton, R. J., Holmes, P. M., Gaertner, M. & Esler, K. J. Heat and smoke pre‐treatment of seeds to improve restoration of an endangered Mediterranean climate vegetation type. Austral Ecol. 42, 354–366 (2017).
    Google Scholar 
    75.Ruprecht, E., Fenesi, A., Fodor, E. I., Kuhn, T. & Tklyi, J. Shape determines fire tolerance of seeds in temperate grasslands that are not prone to fire. Perspect. Plant Ecol. 17, 397–404 (2015).
    Google Scholar 
    76.Mohr, B. A. R. & Friis, E. M. Early angiosperms from the Lower Cretaceous Crato Formation (Brazil), a preliminary report. Int. J. Plant Sci. 161, 155–167 (2000).
    Google Scholar 
    77.Forest, F. et al. Preserving the evolutionary potential of floras in biodiversity hotspots. Nature 445, 757–760 (2007).CAS 
    PubMed 

    Google Scholar 
    78.Linder, H. P. Evolution of diversity: the Cape flora. Trends Plant Sci. 10, 536–541 (2005).CAS 
    PubMed 

    Google Scholar 
    79.Linder, H. P. The radiation of the Cape flora, southern Africa. Biol. Rev. 78, 597–638 (2003).CAS 
    PubMed 

    Google Scholar 
    80.Poinar, G. O. Burmese amber: evidence of Gondwanan origin and Cretaceous dispersion. Hist. Biol. 31, 1304–1309 (2019).
    Google Scholar 
    81.Oliveira, I. D. S. et al. Earliest onychophoran in amber reveals Gondwanan migration patterns. Curr. Biol. 26, 2594–2601 (2016).CAS 
    PubMed 

    Google Scholar 
    82.Poinar, G. O., Lambert, J. B. & Wu, Y. Araucarian source of fossiliferous Burmese amber: spectroscopic and anatomical evidence. J. Bot. Res. Inst. Tex. 1, 449–455 (2007).
    Google Scholar 
    83.Cai, C. Y. et al. Basal polyphagan beetles in mid-Cretaceous amber from Myanmar: biogeographic implications and long-term morphological stasis. Proc. R. Soc. B 286, 2175 (2019).
    Google Scholar 
    84.Zhang, W., Li, H., Shih, C., Zhang, A. & Ren, D. Phylogenetic analyses with four new Cretaceous bristletails reveal inter-relationships of Archaeognatha and Gondwana origin of Meinertellidae. Cladistics 34, 384–406 (2018).PubMed 

    Google Scholar 
    85.Westerweel, J. et al. Burma Terrane part of the Trans-Tethyan Arc during collision with India according to palaeomagnetic data. Nat. Geosci. 12, 5–6 (2019).
    Google Scholar 
    86.Metcalfe, I. in Biogeography and Geological Evolution of SE Asia (eds Hall, R. & Holloway, J. D.) 25–41 (Backhuys Publishers Press,1998).87.Li, J., Wu, Y., Peng, J. & Batten, D. J. Palynofloral evolution on the northern margin of the Indian Plate, southern Xizang, China during the Cretaceous period and its phytogeographic significance. Palaeogeogr. Palaeoclimatol. Palaeoecol. 515, 107–122 (2019).
    Google Scholar 
    88.Smith, A. G., Smith, D. G. & Funnell B. M. Atlas of Mesozoic and Cenozoic Coastlines (Cambridge Univ. Press, 2004).89.Klages, J. P. et al. Temperate rainforests near the South Pole during peak Cretaceous warmth. Nature 580, 81–86 (2020).CAS 
    PubMed 

    Google Scholar 
    90.Coetzee, J. A. & Muller, J. The phytogeographic significance of some extinct Gondwana pollen types from the Tertiary of the southwestern Cape (South Africa). Ann. Mo. Bot. Gard. 71, 1088–1099 (1984).
    Google Scholar 
    91.De Villiers, S. E. & Cadman, A. The palynology of Tertiary sediments from a palaeochannel in Namaqualand, South Africa. Palaeontol. Afr. 34, 69–99 (1997).
    Google Scholar 
    92.De Villiers, S. E. & Cadman, A. An analysis of the palynomorphs obtained from Tertiary sediments at Koingnaas, Namaqualand, South Africa. J. Afr. Earth Sci. 33, 17–47 (2001).
    Google Scholar 
    93.Sandersen, A., Scott, L., McLachlan, I. R. & Hancox, P. J. Cretaceous biozonation based on terrestrial palynomorphs from two wells in the offshore Orange Basin of South Africa. Palaeontol. Afr. 46, 21–41 (2011).
    Google Scholar 
    94.Hooghiemstra, H., Lézine, A. M., Leroy, S. A. G., Dupont, L. & Marret, F. Late Quaternary palynology in marine sediments: a synthesis of the understanding of pollen distribution patterns in the NW African setting. Quat. Int. 148, 29–44 (1988).
    Google Scholar 
    95.Scholtz, A. The palynology of the upper lacustrine sediments of the Arnot Pipe, Banke, Namaqualand. Ann. S. Afr. Mus. 95, 1–109 (1985).
    Google Scholar 
    96.Sciscio, L. et al. Fluctuations in Miocene climate and sea levels along the south-western South African coast: inferences from biogeochemistry, palynology and sedimentology. Palaeontol. Afr. 48, 2–18 (2013).
    Google Scholar 
    97.Roberts, D. L. et al. Miocene fluvial systems and palynofloras at the southwestern tip of Africa: implications for regional and global fluctuations in climate and ecosystems. Earth Sci. Rev. 124, 184–201 (2013).
    Google Scholar 
    98.Roberts, D. L. et al. Palaeoenvironments during a terminal Oligocene or early Miocene transgression in a fluvial system at the southwestern tip of Africa. Glob. Planet. Change 150, 1–23 (2017).
    Google Scholar 
    99.Grimaldi, D., Engel, M. S. & Nascimbene, P. Fossiliferous Cretaceous amber from Myanmar (Burma): its rediscovery, biotic diversity, and paleontological significance. Am. Mus. Novit. 3361, 1–72 (2002).
    Google Scholar 
    100.Mao, Y. et al. Various amberground marine animals on Burmese amber with discussions on its age. Palaeoentomology 1, 91–103 (2018).
    Google Scholar 
    101.Smith, R. D. & Ross, A. J. Amberground pholadid bivalve borings and inclusions in Burmese amber: implications for proximity of resin-producing forests to brackish waters, and the age of the amber. Earth Env. Sci. Trans. R. Soc. Edinb. 107, 239–247 (2018).
    Google Scholar 
    102.Schmidt, A. R. & Dilcher, D. L. Aquatic organisms as amber inclusions and examples from a modern swamp forest. Proc. Natl Acad. Sci. USA 104, 16581–16585 (2007).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    103.Cole, L. E., Bhagwat, S. A. & Willis, K. J. Fire in the swamp forest: palaeoecological insights into natural and human-induced burning in intact tropical peatlands. Front. For. Glob. Change 2, 48 (2019).
    Google Scholar 
    104.Labandeira, C. C. in Reading and Writing of the Fossil Record: Preservational Pathways to Exceptional Fossilization. The Paleontological Society Papers (eds Laflamme, M. et al.) 163–216 (Cambridge Univ. Press, 2014).105.Seyfullah, L. J. et al. Production and preservation of resins–past and present. Biol. Rev. 93, 1684–1714 (2018).PubMed 

    Google Scholar 
    106.Putz, M. K. & Taylor, E. L. Wound response in fossil trees assemblages from Antarctica and its potential as a palaeoenvironmental indicator. IAWA J. 17, 77–88 (1996).
    Google Scholar 
    107.McKellar, R. C. et al. Insect outbreaks produce distinctive carbon isotope signatures in defensive resins and fossiliferous ambers. Proc. R. Soc. B 278, 3219–3224 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    108.Pausas, J. G. Generalized fire response strategies in plants and animals. Oikos 128, 147–153 (2019).
    Google Scholar 
    109.Schmidt, A. R. et al. Arthropods in amber from the Triassic Period. Proc. Natl Acad. Sci. USA 109, 14796–14801 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    110.Silvestro, D. et al. Fossil data support a pre-Cretaceous origin of flowering plants. Nat. Ecol. Evol. 5, 449–457 (2021).PubMed 

    Google Scholar 
    111.Donoghue, P. Evolution: the flowering of land plant evolution. Curr. Biol. 29, 753–756 (2019).
    Google Scholar 
    112.Thulin, M. et al. Family relationships of the enigmatic rosid genera Barbeya and Dirachma from the Horn of Africa region. Plant Syst. Evol. 213, 103–119 (1998).
    Google Scholar 
    113.Wilf, P., Carvalho, M. R., Gandolfo, M. A. & Cúneo, N. R. Eocene lantern fruits from Gondwanan Patagonia and the early origins of Solanaceae. Science 355, 71–75 (2017).CAS 
    PubMed 

    Google Scholar  More