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    Experimentally increased snow depth affects high Arctic microarthropods inconsistently over two consecutive winters

    Callaghan, T. V. et al. Multiple effects of changes in arctic snow cover. Ambio 40, 32–45 (2011).
    Google Scholar 
    Cooper, E. J. Warmer shorter winters disrupt arctic terrestrial ecosystems. Annu. Rev. Ecol. Evol. Syst. 45, 271 (2014).
    Google Scholar 
    IPCC. IPCC, 2013: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 1535 pp. https://doi.org/10.1017/CBO9781107415324. (Cambridge University Press, 2013).Seastedt, T. R. The role of microarthropods in decomposition and mineralization processes. Annu. Rev. Entomol. 29, 25–46 (1984).
    Google Scholar 
    Osler, G. H. & Sommerkorn, M. Toward a complete soil C and N cycle: Incorporating the soil fauna. Ecology 88, 1611–1621 (2007).PubMed 

    Google Scholar 
    Coulson, S. J. et al. The terrestrial and freshwater invertebrate biodiversity of the archipelagoes of the Barents Sea, Svalbard, Franz Josef Land and Novaya Zemlya. Soil Biol. Biochem. 68, 440–470 (2014).CAS 

    Google Scholar 
    Hodkinson, I. D. Terrestrial and freshwater invertebrates. In Arctic Biodiversity Assessment (ed. Barry, T.) 246–274 (Arctic Council, 2013).
    Google Scholar 
    Strathdee, A. T. & Bale, J. S. Life on the edge: Insect ecology in arctic environments. Annu. Rev. Entomol. 43, 85–106 (1998).CAS 
    PubMed 

    Google Scholar 
    Templer, P. H. et al. Impact of a reduced winter snowpack on litter arthropod abundance and diversity in a northern hardwood forest ecosystem. Biol. Fertil. Soils 48, 413–424 (2012).
    Google Scholar 
    Bokhorst, S., Metcalfe, D. B. & Wardle, D. A. Reduction in snow depth negatively affects decomposers but impact on decomposition rates is substrate dependent. Soil Biol. Biochem. 62, 157–164 (2013).CAS 

    Google Scholar 
    Slatyer, R. A., Nash, M. A. & Hoffmann, A. A. Measuring the effects of reduced snow cover on Australia’s alpine arthropods. Austral Ecol. 42, 844–857 (2017).
    Google Scholar 
    Bokhorst, S. et al. Extreme winter warming events more negatively impact small rather than large soil fauna: Shift in community composition explained by traits not taxa. Glob. Change Biol. 18, 1152–1162 (2012).ADS 

    Google Scholar 
    Sulkava, P. & Huhta, V. Effects of hard frost and freeze-thaw cycles on decomposer communities and N mineralisation in boreal forest soil. Appl. Soil Ecol. 22, 225–239 (2003).
    Google Scholar 
    Konestabo, H. S., Michelsen, A. & Holmstrup, M. Responses of springtail and mite populations to prolonged periods of soil freeze-thaw cycles in a sub-arctic ecosystem. Appl. Soil Ecol. 36, 136–146 (2007).
    Google Scholar 
    Coulson, S. J., Leinaas, H. P., Ims, R. A. & Søvik, G. Experimental manipulation of the winter surface ice layer: The effects on a high arctic soil microarthropod community. Ecography 23, 299–306 (2000).
    Google Scholar 
    Dollery, R., Hodkinson, I. D. & Jonsdottir, I. S. Impact of warming and timing of snow melt on soil microarthropod assemblages associated with Dryas-dominated plant communities on Svalbard. Ecography 29, 111–119 (2006).
    Google Scholar 
    Ávila-Jimenez, M. L., Coulson, S. J., Solhoy, T. & Sjoblom, A. Overwintering of terrestrial Arctic arthropods: The fauna of Svalbard now and in the future. Polar Res. 29, 127–137 (2010).
    Google Scholar 
    Makkonen, M. et al. Traits explain the responses of a sub-arctic Collembola community to climate manipulation. Soil Biol. Biochem. 43, 377–384 (2011).CAS 

    Google Scholar 
    Lindo, Z. Warming favours small-bodied organisms through enhanced reproduction and compositional shifts in belowground systems. Soil Biol. Biochem. 91, 271–278 (2015).CAS 

    Google Scholar 
    Hågvar, S. A review of Fennoscandian arthropods living on and in snow. Eur. J. Entomol. 107, 281–298 (2010).
    Google Scholar 
    Hao, C., Chen, T.-W., Wu, Y., Chang, L. & Wu, D. Snow microhabitats provide food resources for winter-active Collembola. Soil Biol. Biochem. 143, 107731 (2020).CAS 

    Google Scholar 
    Christenson, L. et al. Winter climate change influences on soil faunal distribution and abundance: Implications for decomposition in the Northern Forest. Northeast. Nat. 24, B209–B234 (2017).
    Google Scholar 
    Convey, P. et al. Survival of rapidly fluctuating natural low winter temperatures by High Arctic soil invertebrates. J. Therm. Biol. 54, 111–117 (2015).PubMed 

    Google Scholar 
    Krab, E. J., Monteux, S., Weedon, J. T. & Dorrepaal, E. Plant expansion drives bacteria and collembola communities under winter climate change in frost-affected tundra. Soil Biol. Biochem. 138, 107569 (2019).CAS 

    Google Scholar 
    Sörensen, J. G. & Holmstrup, M. Cryoprotective dehydration is widespread in Arctic springtails. J. Insect Physiol. 57, 1147–1153 (2011).PubMed 

    Google Scholar 
    Convey, P., Coulson, S. J., Worland, M. R. & Sjöblom, A. The importance of understanding annual and shorter-term temperature patterns and variation in the surface levels of polar soils for terrestrial biota. Polar Biol. 41, 1587–1605 (2018).
    Google Scholar 
    Birkemoe, T. & Leinaas, H. P. Reproductive biology of the arctic collembolan Hypogastrura tullbergi. Ecography 22, 31–39 (1999).
    Google Scholar 
    Birkemoe, T. & Leinaas, H. P. Effects of temperature on the development of an arctic Collembola (Hypogastrura tullbergi). Funct. Ecol. 14, 693–700 (2001).
    Google Scholar 
    Kankaanpää, T. et al. Spatiotemporal snowmelt patterns within a high Arctic landscape, with implications for flora and fauna. Arct. Antarct. Alp. Res. 50, e1415624 (2018).
    Google Scholar 
    Cooper, E. J., Dullinger, S. & Semenchuk, P. Late snowmelt delays plant development and results in lower reproductive success in the high arctic. Plant Sci. 180, 157–167 (2011).CAS 
    PubMed 

    Google Scholar 
    Krab, E. J. et al. Winter warming effects on tundra shrub performance are species-specific and dependent on spring conditions. J. Ecol. 106, 599–612 (2018).CAS 

    Google Scholar 
    Wheeler, H. C., Hoye, T. T., Schmidt, N. M., Svenning, J.-C. & Forchhammer, M. C. Phenological mismatch with abiotic conditions-implications for flowering in Arctic plants. Ecology 96, 775–787 (2015).PubMed 

    Google Scholar 
    Wheeler, J. A. et al. The snow and the willows: Earlier spring snowmelt reduces performance in the low-lying alpine shrub Salix herbacea. J. Ecol. 104, 1041–1050 (2016).CAS 

    Google Scholar 
    Pollierer, M. M., Langel, R., Körner, C., Maraun, M. & Scheu, S. The underestimated importance of belowground carbon input for forest soil animal food webs. Ecol. Lett. 10, 729–736 (2007).PubMed 

    Google Scholar 
    Coulson, S. J., Hodkinson, I. D. & Webb, N. R. Microscale distribution patterns in high Arctic soil microarthropod communities: The influence of plant species within the vegetation mosaic. Ecography 26, 801–809 (2003).
    Google Scholar 
    Hodkinson, I. D. et al. Global change and Arctic ecosystems: Conclusions and predictions from experiments with terrestrial invertebrates on Spitsbergen. Arct. Alp. Res. 30, 306–313 (1998).
    Google Scholar 
    Førland, E. J., Benestad, R., Hanssen-Bauer, I., Haugen, J. E. & Skaugen, T. E. Temperature and precipitation development at Svalbard 1900–2100. Adv. Meteorol. 2011, 893790 (2011).
    Google Scholar 
    Alatalo, J. M., Jagerbrand, A. K. & Cuchta, P. Collembola at three alpine subarctic sites resistant to twenty years of experimental warming. Sci. Rep. 5, 18161 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coulson, S. J. et al. Effects of experimental temperature elevation on high-arctic soil microarthropod populations. Polar Biol. 16, 147–153 (1996).
    Google Scholar 
    Decker, K. L. M., Wang, D., Waite, C. & Scherbatskoy, T. Snow removal and ambient air temperature effects on forest soil temperatures in Northern Vermont. Soil Sci. Soc. Am. J. 67, 1234–1242 (2003).ADS 
    CAS 

    Google Scholar 
    van Pelt, W. J. J. et al. Multidecadal climate and seasonal snow conditions in Svalbard. J. Geophys. Res. Earth Surf. 121, 2100–2117 (2016).ADS 

    Google Scholar 
    Semenchuk, P. R. et al. Deeper snow alters soil nutrient availability and leaf nutrient status in high Arctic tundra. Biogeochemistry 124, 81–94 (2015).
    Google Scholar 
    Sjursen, H., Michelsen, A. & Jonasson, S. Effects of long-term soil warming and fertilisation on microarthropod abundances in three sub-arctic ecosystems. Appl. Soil Ecol. 30, 148–161 (2005).
    Google Scholar 
    Meehan, M. L. et al. Response of soil fauna to simulated global change factors depends on ambient climate conditions. Pedobiologia 83, 150672 (2020).
    Google Scholar 
    Harte, J., Rawa, A. & Price, V. Effects of manipulated soil microclimate on mesofaunal biomass and diversity. Soil Biol. Biochem. 28, 313–322 (1996).CAS 

    Google Scholar 
    Siepel, H. Life history tactics of soil microarthropods. Biol. Fertil. Soils 18, 263–278 (1994).
    Google Scholar 
    Chernova, N. M., Potapov, M. B., Savenkova, Y. Y. & Bokova, A. I. Ecological significance of parthenogenesis in Collembola. Zool. Zhurnal 88, 1455–1470 (2009).
    Google Scholar 
    Birkemoe, T. & Somme, L. Population dynamics of two collembolan species in an Arctic tundra. Pedobiologia 42, 131–145 (1998).
    Google Scholar 
    Bokhorst, S. et al. Contrasting responses of springtails and mites to elevation and vegetation type in the sub-Arctic. Pedobiologia 67, 57–64 (2018).
    Google Scholar 
    Widenfalk, L. A., Malmstrom, A., Berg, M. P. & Bengtsson, J. Small-scale Collembola community composition in a pine forest soil—Overdispersion in functional traits indicates the importance of species interactions. Soil Biol. Biochem. 103, 52–62 (2016).CAS 

    Google Scholar 
    Morgner, E. The importance of winter in annual ecosystem respiration in the High Arctic: Effects of snow depth in two vegetation types. Polar Res. 29, 474–474 (2010).
    Google Scholar 
    Green, K. & Slatyer, R. Arthropod community composition along snowmelt gradients in snowbeds in the Snowy Mountains of south-eastern Australia. Austral Ecol. 45, 144–157 (2020).
    Google Scholar 
    Ayres, E. et al. Experimentally increased snow accumulation alters soil moisture and animal community structure in a polar desert. Polar Biol. 33, 897–907 (2010).
    Google Scholar 
    Semenchuk, P. R., Elberling, B. & Cooper, E. J. Snow cover and extreme winter warming events control flower abundance of some, but not all species in high arctic Svalbard. Ecol. Evol. 3, 2586–2599 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Morsdorf, M. A. et al. Deepened winter snow significantly influences the availability and forms of nitrogen taken up by plants in High Arctic tundra. Soil Biol. Biochem. 135, 222–234 (2019).CAS 

    Google Scholar 
    Cooper, E. J., Little, C. J., Pilsbacher, A. K. & Morsdorf, M. A. Disappearing green: Shrubs decline and bryophytes increase with nine years of increased snow accumulation in the High Arctic. J. Veg. Sci. 30, 857–867 (2019).
    Google Scholar 
    Mundra, S. et al. Ectomycorrhizal and saprotrophic fungi respond differently to long-term experimentally increased snow depth in the High Arctic. Microbiologyopen 5, 856–869 (2016).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Schneider, K. & Maraun, M. Feeding preferences among dark pigmented fungal taxa (“Dematiacea”) indicate limited trophic niche differentiation of oribatid mites (Oribatida, Acari). Pedobiologia 49, 61–67 (2005).
    Google Scholar 
    Krab, E. J., Berg, M. P., Aerts, R., van Logtestijn, R. S. P. & Cornelissen, J. H. C. Vascular plant litter input in subarctic peat bogs changes Collembola diets and decomposition patterns. Soil Biol. Biochem. 63, 106–115 (2013).CAS 

    Google Scholar 
    Jucevica, E. & Melecis, V. Global warming affect Collembola community: A long-term study. Pedobiologia 50, 177–184 (2006).
    Google Scholar 
    Krab, E. J., Oorsprong, H., Berg, M. P. & Cornelissen, J. H. C. Turning northern peatlands upside down: Disentangling microclimate and substrate quality effects on vertical distribution of Collembola. Funct. Ecol. 24, 1362–1369 (2010).
    Google Scholar 
    Zettel, J. Alpine Collembola—Adaptations and strategies for survival in harsh environments. Zool. Anal. Complex Syst. 102, 73–89 (2000).
    Google Scholar 
    Block, W. Terrestrial arthropods and low-temperature. Cryobiology 18, 436–444 (1981).CAS 
    PubMed 

    Google Scholar 
    Semenchuk, P. R., Christiansen, C. T., Grogan, P., Elberling, B. & Cooper, E. J. Long-term experimentally deepened snow decreases growing-season respiration in a low- and high-arctic tundra ecosystem. J. Geophys. Res. Biogeosci. 121, 1236–1248 (2016).
    Google Scholar 
    Semenchuk, P. R. et al. Soil organic carbon depletion and degradation in surface soil after long-term non-growing season warming in High Arctic Svalbard. Sci. Total Environ. 646, 158–167 (2019).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gillespie, M. A. K. et al. Status and trends of terrestrial arthropod abundance and diversity in the North Atlantic region of the Arctic. Ambio 49, 718–731 (2020).PubMed 

    Google Scholar 
    Andriuzzi, W. S., Adams, B. J., Barrett, J. E., Virginia, R. A. & Wall, D. H. Observed trends of soil fauna in the Antarctic Dry Valleys: Early signs of shifts predicted under climate change. Ecology 99, 312–321 (2018).CAS 
    PubMed 

    Google Scholar 
    Staub, B. & Delaloye, R. Using near-surface ground temperature data to derive snow insulation and melt indices for mountain permafrost applications. Permafr. Periglac. Process. 28, 237–248 (2017).
    Google Scholar 
    Rendos, M. et al. Organic carbon content and temperature as substantial factors affecting diversity and vertical distribution of Collembola on forested scree slopes. Eur. J. Soil Biol. 75, 180–187 (2016).
    Google Scholar 
    Fjellberg, A. The Collembola of the Norwegian Arctic Islands (Norsk Polarinstitutt, 1994).
    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/. (R Foundation for Statistical Computing, 2020). Accessed 06 June 2020. More

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    Abiotic conditions shape spatial and temporal morphological variation in North American birds

    Dehling, D. M., Jordano, P., Schaefer, H. M., Böhning-Gaese, K. & Schleuning, M. Morphology predicts species’ functional roles and their degree of specialization in plant–frugivore interactions. Proc. R. Soc. B 283, 20152444 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Grant, P. R. Inheritance of size and shape in a population of Darwin’s finches, Geospiza conirostris. Proc. R. Soc. Lond. B 220, 219–236 (1983).
    Google Scholar 
    Des Roches, S. et al. The ecological importance of intraspecific variation. Nat. Ecol. Evol. 2, 57–64 (2018).PubMed 

    Google Scholar 
    Bergmann, C. Über die verhältnisse der wärmeökonomie der thiere zu ihrer grösse. Gött. Stud. 3, 595–708 (1847).
    Google Scholar 
    Allen, J. A. The influence of physical conditions in the genesis of species. Radic. Rev. 1, 108–140 (1877).
    Google Scholar 
    Altshuler, D. L. & Dudley, R. The physiology and biomechanics of avian flight at high altitude. Integr. Comp. Biol. 46, 62–71 (2006).PubMed 

    Google Scholar 
    Teplitsky, C. & Millien, V. Climate warming and Bergmann’s rule through time: is there any evidence? Evol. Appl. 7, 156–168 (2014).PubMed 

    Google Scholar 
    Gardner, J. L., Peters, A., Kearney, M. R., Joseph, L. & Heinsohn, R. Declining body size: a third universal response to warming? Trends Ecol. Evol. 26, 285–291 (2011).PubMed 

    Google Scholar 
    Yom-Tov, Y., Yom-Tov, S., Wright, J., Thorne, C. J. R. & Du Feu, R. Recent changes in body weight and wing length among some British passerine birds. Oikos 112, 91–101 (2006).
    Google Scholar 
    Van Buskirk, J., Mulvihill, R. S. & Leberman, R. C. Declining body sizes in North American birds associated with climate change. Oikos 119, 1047–1055 (2010).
    Google Scholar 
    Weeks, B. C. et al. Shared morphological consequences of global warming in North American migratory birds. Ecol. Lett. 23, 316–325 (2020).PubMed 

    Google Scholar 
    Rosenberg, K. V. et al. Decline of the North American avifauna. Science 366, 120–124 (2019).CAS 
    PubMed 

    Google Scholar 
    DeSante, D. F., Saracco, J. F., O’Grady, D. R., Burton, K. M. & Walker, B. L. Methodological considerations of the Monitoring Avian Productivity and Survivorship (MAPS) program. Stud. Avian Biol. 29, 28–45 (2004).West, G. B., Brown, J. H. & Enquist, B. J. A general model for the origin of allometric scaling laws in biology. Science 276, 122–126 (1997).CAS 
    PubMed 

    Google Scholar 
    Jirinec, V. et al. Morphological consequences of climate change for resident birds in intact Amazonian rainforest. Sci. Adv. 7, eabk1743 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Dubiner, S. & Meiri, S. Widespread recent changes in morphology of Old World birds, global warming the immediate suspect. Glob. Ecol. Biogeogr. 31, 791–801 (2022).
    Google Scholar 
    Ballinger, M. A. & Nachman, M. W. The contribution of genetic and environmental effects to Bergmann’s rule and Allen’s rule in house mice. Am. Nat. https://doi.org/10.1086/719028 (2022).Andrew, S. C., Hurley, L. L., Mariette, M. M. & Griffith, S. C. Higher temperatures during development reduce body size in the zebra finch in the laboratory and in the wild. J. Evol. Biol. 30, 2156–2164 (2017).CAS 
    PubMed 

    Google Scholar 
    Siepielski, A. M. et al. No evidence that warmer temperatures are associated with selection for smaller body sizes. Proc. R. Soc. B 286, 20191332 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Salewski, V., Siebenrock, K.-H., Hochachka, W. M., Woog, F. & Fiedler, W. Morphological change to birds over 120 years is not explained by thermal adaptation to climate change. PLoS ONE 9, e101927 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Riddell, E. A., Iknayan, K. J., Wolf, B. O., Sinervo, B. & Beissinger, S. R. Cooling requirements fueled the collapse of a desert bird community from climate change. Proc. Natl Acad. Sci. USA 116, 21609–21615 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pecl, G. T. et al. Biodiversity redistribution under climate change: impacts on ecosystems and human well-being. Science 355, eaai9214 (2017).PubMed 

    Google Scholar 
    Futuyma, D. J. Evolutionary constraint and ecological consequences. Evolution 64, 1865–1884 (2010).PubMed 

    Google Scholar 
    Murren, C. J. et al. Constraints on the evolution of phenotypic plasticity: limits and costs of phenotype and plasticity. Heredity 115, 293–301 (2015).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Rollinson, C. R. et al. Working across space and time: nonstationarity in ecological research and application. Front. Ecol. Environ. 19, 66–72 (2021).
    Google Scholar 
    Riemer, K., Guralnick, R. P. & White, E. P. No general relationship between mass and temperature in endothermic species. eLife 7, e27166 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Ryding, S., Klaassen, M., Tattersall, G. J., Gardner, J. L. & Symonds, M. R. Shape-shifting: changing animal morphologies as a response to climatic warming. Trends Ecol. Evol. 36, 1036–1048 (2021).PubMed 

    Google Scholar 
    Baldwin, M. W., Winkler, H., Organ, C. L. & Helm, B. Wing pointedness associated with migratory distance in common-garden and comparative studies of stonechats (Saxicola torquata). J. Evol. Biol. 23, 1050–1063 (2010).CAS 
    PubMed 

    Google Scholar 
    Förschler, M. I. & Bairlein, F. Morphological shifts of the external flight apparatus across the range of a passerine (Northern Wheatear) with diverging migratory behaviour. PLoS ONE 6, e18732 (2011).PubMed 
    PubMed Central 

    Google Scholar 
    Macpherson, M. P., Jahn, A. E. & Mason, N. A. Morphology of migration: associations between wing shape, bill morphology and migration in kingbirds (Tyrannus). Biol. J. Linn. Soc. 135, 71–83 (2022).
    Google Scholar 
    Newton, I. The Migration Ecology of Birds (Elsevier, 2010).Clegg, S. M., Kelly, J. F., Kimura, M. & Smith, T. B. Combining genetic markers and stable isotopes to reveal population connectivity and migration patterns in a neotropical migrant, Wilson’s warbler (Wilsonia pusilla). Mol. Ecol. 12, 819–830 (2003).CAS 
    PubMed 

    Google Scholar 
    Bell, C. P. Leap-frog migration in the fox sparrow: minimizing the cost of spring migration. Condor 99, 470–477 (1997).
    Google Scholar 
    Billerman, S., Keeney, B., Rodewald, P. & Schulenberg, T. (eds) Birds of the World (Cornell Laboratory of Ornithology, 2020).Desrochers, A. Morphological response of songbirds to 100 years of landscape change in North America. Ecology 91, 1577–1582 (2010).CAS 
    PubMed 

    Google Scholar 
    Swaddle, J. P. & Lockwood, R. Morphological adaptations to predation risk in passerines. J. Avian Biol. 29, 172–176 (1998).
    Google Scholar 
    Chown, S. L. & Klok, C. J. Altitudinal body size clines: latitudinal effects associated with changing seasonality. Ecography 26, 445–455 (2003).
    Google Scholar 
    Hsiung, A. C., Boyle, W. A., Cooper, R. J. & Chandler, R. B. Altitudinal migration: ecological drivers, knowledge gaps, and conservation implications: animal altitudinal migration review. Biol. Rev. 93, 2049–2070 (2018).PubMed 

    Google Scholar 
    Barras, A. G., Liechti, F. & Arlettaz, R. Seasonal and daily movement patterns of an alpine passerine suggest high flexibility in relation to environmental conditions. J. Avian Biol. 52, jav.02860 (2021).
    Google Scholar 
    Spence, A. R. & Tingley, M. W. Body size and environment influence both intraspecific and interspecific variation in daily torpor use across hummingbirds. Funct. Ecol. 35, 870–883 (2021).CAS 

    Google Scholar 
    Moreau, R. E. Variation in the western Zosteropidae (Aves). Bull. Br. Mus. Nat. Hist. Zool. 4, 311–433 (1957).
    Google Scholar 
    Hamilton, T. H. The adaptive significances of intraspecific trends of variation in wing length and body size among bird species. Evolution 15, 180–194 (1961).
    Google Scholar 
    Hodkinson, I. D. Terrestrial insects along elevation gradients: species and community responses to altitude. Biol. Rev. 80, 489–513 (2005).PubMed 

    Google Scholar 
    Feinsinger, P., Colwell, R. K., Terborgh, J. & Chaplin, S. B. Elevation and the morphology, flight energetics, and foraging ecology of tropical hummingbirds. Am. Nat. 113, 481–497 (1979).
    Google Scholar 
    Aldrich, J. W. Ecogeographical Variation in Size and Proportions of Song Sparrows (Melospiza melodia) (American Ornithological Society, 1984).Sun, Y. et al. The role of climate factors in geographic variation in body mass and wing length in a passerine bird. Avian Res. 8, 1 (2017).Des Roches, S., Pendleton, L. H., Shapiro, B. & Palkovacs, E. P. Conserving intraspecific variation for nature’s contributions to people. Nat. Ecol. Evol. 5, 574–582 (2021).PubMed 

    Google Scholar 
    McKechnie, A. E. & Wolf, B. O. Climate change increases the likelihood of catastrophic avian mortality events during extreme heat waves. Biol. Lett. 6, 253–256 (2010).PubMed 

    Google Scholar 
    Conradie, S. R., Woodborne, S. M., Cunningham, S. J. & McKechnie, A. E. Chronic, sublethal effects of high temperatures will cause severe declines in southern African arid-zone birds during the 21st century. Proc. Natl Acad. Sci. USA 116, 14065–14070 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Radchuk, V. et al. Adaptive responses of animals to climate change are most likely insufficient. Nat. Commun. 10, 3109 (2019).PubMed 
    PubMed Central 

    Google Scholar 
    Riddell, E. A. et al. Exposure to climate change drives stability or collapse of desert mammal and bird communities. Science 371, 633–636 (2021).CAS 
    PubMed 

    Google Scholar 
    Tingley, M. W., Monahan, W. B., Beissinger, S. R. & Moritz, C. Birds track their Grinnellian niche through a century of climate change. Proc. Natl Acad. Sci. USA 106, 19637–19643 (2009).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Youngflesh, C. et al. Migratory strategy drives species-level variation in bird sensitivity to vegetation green-up. Nat. Ecol. Evol. 5, 987–994 (2021).PubMed 

    Google Scholar 
    Blueweiss, L. et al. Relationships between body size and some life history parameters. Oecologia 37, 257–272 (1978).CAS 
    PubMed 

    Google Scholar 
    Kleiber, M. Body size and metabolic rate. Physiol. Rev. 27, 511–541 (1947).CAS 
    PubMed 

    Google Scholar 
    Yodzis, P. & Innes, S. Body size and consumer-resource dynamics. Am. Nat. 139, 1151–1175 (1992).
    Google Scholar 
    Prum, R. O. Interspecific social dominance mimicry in birds: social mimicry in birds. Zool. J. Linn. Soc. 172, 910–941 (2014).
    Google Scholar 
    Pyle, P. Identification Guide to North American Birds: A Compendium of Information on Identifying, Ageing, and Sexing ‘Near-Passerines’ and Passerines in the Hand (Slate Creek Press, 1997).Leys, C., Ley, C., Klein, O., Bernard, P. & Licata, L. Detecting outliers: do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49, 764–766 (2013).
    Google Scholar 
    Danielson, J. J. & Gesch, D. B. Global Multi-Resolution Terrain Elevation Data 2010 (GMTED2010) (US Geological Survey, 2011).Thornton, M. M. et al. Daymet: Daily Surface Weather Data on a 1-km Grid for North America, Version 4 (ORNL Distributed Active Archive Center, 2020).Greenewalt, C. H. The flight of birds: the significant dimensions, their departure from the requirements for dimensional similarity, and the effect on flight aerodynamics of that departure. Trans. Am. Philos. Soc. 65, 1–67 (1975).
    Google Scholar 
    Longo, G. & Montévil, M. Perspectives on Organisms: Biological Time, Symmetries, and Singularities (Springer, 2014).Harvey, P. H. in Scaling in Biology (eds Brown, J. H. & West, G. B.) 253–265 (Oxford Univ. Press, 2000).Orme, D. et al. The caper package: comparative analysis of phylogenetics and evolution in R. R package version 5 (2013).R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2021).Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K. & Mooers, A. O. The global diversity of birds in space and time. Nature 491, 444–448 (2012).CAS 
    PubMed 

    Google Scholar 
    Nudds, R. L., Kaiser, G. W. & Dyke, G. J. Scaling of avian primary feather length. PLoS ONE 6, e15665 (2011).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nudds, R. Wing-bone length allometry in birds. J. Avian Biol. 38, 515–519 (2007).
    Google Scholar 
    Anderson, S. C., Branch, T. A., Cooper, A. B. & Dulvy, N. K. Black-swan events in animal populations. Proc. Natl Acad. Sci. USA 114, 3252–3257 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stan Modeling Language Users Guide and Reference Manual, Version 2.18.0 (Stan Development Team, 2018); http://mc-stan.orgCarpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017).Youngflesh, C. MCMCvis: tools to visualize, manipulate, and summarize MCMC output. J. Open Source Softw. 3, 640 (2018).
    Google Scholar 
    Wickham, H. et al. Welcome to the Tidyverse. J. Open Source Softw. 4, 1686 (2019).
    Google Scholar 
    Gabry, J., Simpson, D., Vehtari, A., Betancourt, M. & Gelman, A. Visualization in Bayesian workflow. J. R. Stat. Soc. A 182, 389–402 (2019).
    Google Scholar 
    McElreath, R. Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman and Hall/CRC, 2018).Data Zone (BirdLife International, 2019); http://datazone.birdlife.org/species/requestdisCramp, S. & Brooks, D. Handbook of the Birds of Europe, the Middle East and North Africa. The Birds of the Western Palearctic, Vol. VI. Warblers (Oxford Univ. Press, 1992).Che-Castaldo, J., Che-Castaldo, C. & Neel, M. C. Predictability of demographic rates based on phylogeny and biological similarity. Conserv. Biol. 32, 1290–1300 (2018).PubMed 

    Google Scholar 
    Villemereuil, P., de, Wells, J. A., Edwards, R. D. & Blomberg, S. P. Bayesian models for comparative analysis integrating phylogenetic uncertainty. BMC Evol. Biol. 12, 102 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Revell, L. J. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3, 217–223 (2012).
    Google Scholar 
    Pagel, M. Inferring the historical patterns of biological evolution. Nature 401, 877–884 (1999).CAS 
    PubMed 

    Google Scholar 
    Hendry, A. P. & Kinnison, M. T. Perspective: the pace of modern life: measuring rates of contemporary microevolution. Evolution 53, 1637–1653 (1999).PubMed 

    Google Scholar 
    Gingerich, P. Rates of evolution: effects of time and temporal scaling. Science 222, 159–162 (1983).CAS 
    PubMed 

    Google Scholar 
    Bird, J. P. et al. Generation lengths of the world’s birds and their implications for extinction risk. Conserv. Biol. 34, 1252–1261 (2020).Gingerich, P. D. Rates of evolution. Annu. Rev. Ecol. Evol. Syst. 40, 657–675 (2009).
    Google Scholar 
    Bürger, R. & Lynch, M. Evolution and extinction in a changing environment: a quantitative-genetic analysis. Evolution 49, 151–163 (1995).PubMed 

    Google Scholar 
    Hendry, A. P., Farrugia, T. J. & Kinnison, M. T. Human influences on rates of phenotypic change in wild animal populations. Mol. Ecol. 17, 20–29 (2008).PubMed 

    Google Scholar  More

  • in

    Recovery and genome reconstruction of novel magnetotactic Elusimicrobiota from bog soil

    Steen AD, Carini ACP, Lloyd KG, Thrash JC, Deangelis KM, Fierer N. High proportions of bacteria and archaea across most biomes remain uncultured. ISME J. 2019;13:3126–30.PubMed 
    PubMed Central 

    Google Scholar 
    Lloyd KG, Steen AD, Ladau J, Yin J. Phylogenetically novel uncultured microbial cells dominate earth microbiomes. mSystems. 2018;3:e00055–18.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Marcy Y, Ouverney C, Bik EM, Lo T, Ivanova N, Garcia H, et al. Dissecting biological “dark matter” with single-cell genetic analysis of rare and uncultivated TM7 microbes from the human mouth. Proc Natl Acad Sci USA. 2007;104:11889–94.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Pascoal F, Costa R, Magalhães C. The microbial rare biosphere: current concepts, methods and ecological principles. FEMS Microbiol Ecol. 2021;97:fiaa227.CAS 
    PubMed 

    Google Scholar 
    Sogin ML, Morrison HG, Huber JA, Welch DM, Huse SM, Neal PR, et al. Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proc Natl Acad Sci USA. 2006;103:12115–20.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gareev KG, Grouzdev DS, Kharitonskii PV, Kosterov A, Koziaeva VV, Sergienko ES, et al. Magnetotactic bacteria and magnetosomes: basic properties and applications. Magnetochemistry. 2021;7:86.CAS 

    Google Scholar 
    Lefevre CT, Bazylinski DA. Ecology, diversity, and evolution of magnetotactic bacteria. Microbiol Mol Biol Rev. 2013;77:497–526.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lin W, Pan Y, Bazylinsky DA. Diversity and ecology of and biomineralization by magnetotactic bacteria. Environ Microbiol Rep. 2017;9:345–56.CAS 
    PubMed 

    Google Scholar 
    Uebe R, Schüler D. Magnetosome biogenesis in magnetotactic bacteria. Nat Rev Microbiol. 2016;14:621–37.CAS 
    PubMed 

    Google Scholar 
    Lefèvre CT, Frankel RB, Bazylinski DA. Magnetotaxis in prokaryotes. eLS. 2011. https://onlinelibrary.wiley.com/action/showCitFormats?doi=10.1002%2F9780470015902.a0000397.pub2https://onlinelibrary.wiley.com/action/showCitFormats?doi=10.1002%2F9780470015902.a0000397.pub2.Goswami P, He K, Li J, Pan Y, Roberts AP, Lin W. Magnetotactic bacteria and magnetofossils: ecology, evolution and environmental implications. npj Biofilms Microbiomes. 2022;8:43.PubMed 
    PubMed Central 

    Google Scholar 
    Flies CB, Jonkers HM, De Beer D, Bosselmann K, Böttcher ME, Schüler D. Diversity and vertical distribution of magnetotactic bacteria along chemical gradients in freshwater microcosms. FEMS Microbiol Ecol. 2005;52:185–95.CAS 
    PubMed 

    Google Scholar 
    Wolfe RS, Thauer RK, Pfennig N. A’capillary racetrack’ method for isolation of magnetotactic bacteria. FEMS Microbiol Ecol. 1987;45:31–5.
    Google Scholar 
    Jogler C, Lin W, Meyerdierks A, Kube M, Katzmann E, Flies C, et al. Toward cloning of the magnetotactic metagenome: identification of magnetosome island gene clusters in uncultivated magnetotactic bacteria from different aquatic sediments. Appl Environ Microbiol. 2009;75:3972–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lin W, Zhang W, Paterson GA, Zhu Q, Zhao X. Expanding magnetic organelle biogenesis in the domain Bacteria. Microbiome. 2020;8:152.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Geissinger O, Herlemann DPR, Mo E, Maier UG, Brune A. The ultramicrobacterium “Elusimicrobium minutum” gen. nov., sp. nov., the first cultivated representative of the Termite Group 1 phylum. Appl Environ Microbiol. 2009;75:2831–40.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wakako I-O, Brune A. Cospeciation of termite gut flagellates and their bacterial endosymbionts: Trichonympha species and ‘Candidatus Endomicrobium trichonymphae’. Mol Ecol. 2009;18:332–42.
    Google Scholar 
    Zheng H, Dietrich C, Radek R, Brune A. Endomicrobium proavitum, the first isolate of Endomicrobia class. nov. (phylum Elusimicrobia) – an ultramicrobacterium with an unusual cell cycle that fixes nitrogen with a Group IV nitrogenase. Environ Ecol Stat. 2016;18:191–204.CAS 

    Google Scholar 
    Méheust R, Castelle CJ, Carnevali PBM, Chen L, Amano Y, Hug LA, et al. Groundwater Elusimicrobia are metabolically diverse compared to gut microbiome Elusimicrobia and some have a novel nitrogenase paralog. ISME J. 2020;14:2907–22.PubMed 
    PubMed Central 

    Google Scholar 
    Lin H, Ascher DB, Myung Y, Lamborg CH, Hallam SJ, Gionfriddo CM, et al. Mercury methylation by metabolically versatile and cosmopolitan marine bacteria. ISME J. 2021;15:1810–25.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks DH, Rinke C, Chuvochina M, Chaumeil PA, Woodcroft BJ, Evans PN, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol. 2017;2:1533–42.CAS 
    PubMed 

    Google Scholar 
    Zhang L, Gong X, Wang L, Guo K, Cao S, Zhou Y. Science of the total environment metagenomic insights into the effect of thermal hydrolysis pre-treatment on microbial community of an anaerobic digestion system. Sci Total Environ. 2021;791:148096.CAS 
    PubMed 

    Google Scholar 
    Woodcroft BJ, Singleton CM, Boyd JA, Evans PN, Emerson JB, Zayed AAF, et al. Genome-centric view of carbon processing in thawing permafrost. Nature. 2018;560:49–54.CAS 
    PubMed 

    Google Scholar 
    Uzun M, Alekseeva L, Krutkina M, Koziaeva V, Grouzdev D. Unravelling the diversity of magnetotactic bacteria through analysis of open genomic databases. Sci Data. 2020;7:252.PubMed 
    PubMed Central 

    Google Scholar 
    Tully BJ, Wheat CG, Glazer BT, Huber JA. A dynamic microbial community with high functional redundancy inhabits the cold, oxic subseafloor aquifer. ISME J. 2018;12:1–16.CAS 
    PubMed 

    Google Scholar 
    Kirillova NP, Sileva TM, Ul’yanova TY, Rozov SY, Il’yashenko MA, Makarov MI. Digital soil map of Chashnikovo training and experimental soil ecological center, Moscow State University. Mosc Univ Soil Sci Bull. 2015;70:58–65.
    Google Scholar 
    Koziaeva VV, Alekseeva LM, Uzun MM, Leão P, Sukhacheva MV, Patutina EO, et al. Biodiversity of magnetotactic bacteria in the freshwater lake Beloe Bordukovskoe, Russia. Microbiology. 2020;89:348–58.CAS 

    Google Scholar 
    Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26:2460–1.CAS 
    PubMed 

    Google Scholar 
    Edgar RC, Flyvbjerg H. Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics. 2015;31:3476–82.CAS 
    PubMed 

    Google Scholar 
    Edgar RC. UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv 2016. https://doi.org/10.1101/081257.Pruesse E, Peplies J, Glöckner FO. SINA: Accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics. 2012;28:1823–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fierer N, Jackson JA, Vilgalys R, Jackson RB. Assessment of soil microbial community structure by use of taxon-specific quantitative PCR assays. Appl Environ Microbiol. 2005;71:4117–20.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. MetaSPAdes: a new versatile metagenomic assembler. Genome Res. 2017;27:824–34.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Wu YW, Simmons BA, Singer SW. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 2016;32:605–7.CAS 
    PubMed 

    Google Scholar 
    Kang DD, Li F, Kirton E, Thomas A, Egan R, An H, et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 2019;7:e7359.PubMed 
    PubMed Central 

    Google Scholar 
    Lin HH, Liao YC. Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes. Sci Rep. 2016;6:12–9.
    Google Scholar 
    Sieber CMK, Probst AJ, Sharrar A, Thomas BC, Hess M, Tringe SG, et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat Microbiol. 2018;3:836–43.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29:1072–5.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Chaumeil P, Mussig AJ, Parks DH, Hugenholtz P. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics. 2019;36:1925–7.PubMed Central 

    Google Scholar 
    Tatusova T, Dicuccio M, Badretdin A, Chetvernin V, Nawrocki EP, Zaslavsky L, et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res. 2016;44:6614–24.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ji R, Zhang W, Pan Y, Lin W. MagCluster: a tool for identification, annotation, and visualization of magnetosome gene clusters. Microbiol Resour Announc. 2022;11:e01031–21.CAS 
    PubMed Central 

    Google Scholar 
    Wu S, Zhu Z, Fu L, Niu B, Li W. WebMGA: a customizable web server for fast metagenomic sequence analysis. BMC Genomics. 2011;12:444.PubMed 
    PubMed Central 

    Google Scholar 
    Kanehisa M, Sato Y. KEGG Mapper for inferring cellular functions from protein sequences. Protein Sci. 2020;29:28–35.CAS 
    PubMed 

    Google Scholar 
    Shaffer M, Borton MA, McGivern BB, Zayed AA, La Rosa SL. 0003 3527 8101, Solden LM, et al. DRAM for distilling microbial metabolism to automate the curation of microbiome function. Nucleic Acids Res. 2020;48:8883–900.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9:5114.PubMed 
    PubMed Central 

    Google Scholar 
    Nguyen LT, Schmidt HA, Von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74.CAS 
    PubMed 

    Google Scholar 
    Kalyaanamoorthy S, Minh BQ, Wong TKF, Haeseler AVon, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods. 2017;14:587–9.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hoang DT, Chernomor O, Von Haeseler A, Minh BQ, Vinh LS. UFBoot2: improving the ultrafast bootstrap approximation. Mol Biol Evol. 2018;35:518–22.CAS 
    PubMed 

    Google Scholar 
    Letunic I, Bork P. Interactive tree of life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 2021;49:W293–6.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Coleman GA, Davín AA, Mahendrarajah TA, Szánthó LL, Spang A, Hugenholtz P, et al. A rooted phylogeny resolves early bacterial evolution. Science. 2021;372:eabe0511.CAS 
    PubMed 

    Google Scholar 
    Parks DH. https://github.com/dparks1134/CompareM.Dombrowski N, Lee JH, Williams TA, Offre P, Spang A. Genomic diversity, lifestyles and evolutionary origins of DPANN archaea. FEMS Microbiol Lett. 2019;366:fnz008.CAS 
    PubMed Central 

    Google Scholar 
    Lin W, Zhang W, Zhao X, Roberts AP, Paterson GA, Bazylinski DA, et al. Genomic expansion of magnetotactic bacteria reveals an early common origin of magnetotaxis with lineage-specific evolution. ISME J. 2018;12:1508–19.CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Urakawa H, Garcia JC, Nielsen JL, Le VQ, Kozlowski JA, Stein LY, et al. Nitrosospira lacus sp. nov., a psychrotolerant, ammonia-oxidizing bacterium from sandy lake sediment. Int J Syst Evol Microbiol. 2015;65:242–50.CAS 
    PubMed 

    Google Scholar 
    Kalyuzhnaya MG, De Marco P, Bowerman S, Pacheco CC, Lara JC, Lidstrom ME, et al. Methyloversatilis universalis gen. nov., sp. nov., a novel taxon within the Betaproteobacteria represented by three methylotrophic isolates. Int J Syst Evol Microbiol. 2006;56:2517–22.CAS 
    PubMed 

    Google Scholar 
    Bazylinski DA, Frankel RB, Konhauser KO. Modes of biomineralization of magnetite by microbes. Geomicrobiol J. 2007;24:465–75.CAS 

    Google Scholar 
    Uzun M, Koziaeva V, Dziuba M, Leão P, Krutkina M, Grouzdev D. Detection of interphylum transfers of the magnetosome gene cluster in magnetotactic bacteria. Front Microbiol. 2022;13:945734.PubMed 
    PubMed Central 

    Google Scholar 
    Parks DH, Chuvochina M, Waite DW, Rinke C, Skarshewski A, Chaumeil PA, et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol. 2018;36:996.CAS 
    PubMed 

    Google Scholar 
    Murphy CL, Biggerstaff J, Eichhorn A, Ewing E, Shahan R, Soriano D, et al. Genomic characterization of three novel Desulfobacterota classes expand the metabolic and phylogenetic diversity of the phylum. Environ Microbiol. 2021;23:4326–43.CAS 
    PubMed 

    Google Scholar 
    Konstantinidis KT, Rosselló-Móra R, Amann R. Uncultivated microbes in need of their own taxonomy. ISME J. 2017;11:2399–406.PubMed 
    PubMed Central 

    Google Scholar 
    Denise R, Abby SS, Rocha EPC. Diversification of the type IV filament superfamily into machines for adhesion, protein secretion, DNA uptake, and motility. PLoS Biol. 2019;17:e3000390.PubMed 
    PubMed Central 

    Google Scholar 
    Hennell James R, Deme JC, Kjӕr A, Alcock F, Silale A, Lauber F, et al. Structure and mechanism of the proton-driven motor that powers type 9 secretion and gliding motility. Nat Microbiol. 2021;6:221–33.CAS 
    PubMed 

    Google Scholar 
    Nolan LM, Whitchurch CB, Barquist L, Katrib M, Boinett CJ, Mayho M, et al. A global genomic approach uncovers novel components for twitching motility-mediated biofilm expansion in Pseudomonas aeruginosa. Micro Genomics. 2018;4:e000229.
    Google Scholar 
    Uzun M, Koziaeva V, Dziuba M, Alekseeva L, Grouzdev D. Mam protein trees. 2022. https://doi.org/10.6084/m9.figshare.c.6045158.v1.Arnoux P, Siponen MI, Lefèvre CT, Ginet N, Pignol D. Structure and evolution of the magnetochrome domains: no longer alone. Front Microbiol. 2014;5:117.PubMed 
    PubMed Central 

    Google Scholar 
    Katzmann E, Scheffel A, Gruska M, Plitzko JM, Schüler D. Loss of the actin-like protein MamK has pleiotropic effects on magnetosome formation and chain assembly in Magnetospirillum gryphiswaldense. Mol Microbiol. 2010;77:208–24.CAS 
    PubMed 

    Google Scholar 
    Wagner-Döbler I, Bennasar A, Vancanneyt M, Strömpl C, Brümmer I, Eichner C, et al. Microcosm enrichment of biphenyl-degrading microbial communities from soils and sediments. Appl Environ Microbiol. 1998;64:3014–22.PubMed 
    PubMed Central 

    Google Scholar 
    Ibekwe AM, Papiernik SK, Gan J, Yates SR, Crowley DE, Yang CH. Microcosm enrichment of 1,3-dichloropropene-degrading soil microbial communities in a compost-amended soil. J Appl Microbiol. 2001;91:668–76.CAS 
    PubMed 

    Google Scholar 
    Yakimov MM, Denaro R, Genovese M, Cappello S, D’Auria G, Chernikova TN, et al. Natural microbial diversity in superficial sediments of Milazzo Harbor (Sicily) and community successions during microcosm enrichment with various hydrocarbons. Environ Microbiol. 2005;7:1426–41.CAS 
    PubMed 

    Google Scholar 
    Tringe SG, Von Mering C, Kobayashi A, Salamov AA, Chen K, Chang HW, et al. Comparative metagenomics of microbial communities. Science. 2005;308:554–7.CAS 
    PubMed 

    Google Scholar 
    Lefèvre CT, Trubitsyn D, Abreu F, Kolinko S, Jogler C, de Almeida LGP, et al. Comparative genomic analysis of magnetotactic bacteria from the Deltaproteobacteria provides new insights into magnetite and greigite magnetosome genes required for magnetotaxis. Environ Microbiol. 2013;15:2712–35.PubMed 

    Google Scholar 
    Wadhwa N, Berg HC. Bacterial motility: machinery and mechanisms. Nat Rev Microbiol. 2022;20:161–73.CAS 
    PubMed 

    Google Scholar 
    Zhu K, Pan H, Li J, Yu-Zhang K, Zhang SD, Zhang WY, et al. Isolation and characterization of a marine magnetotactic spirillum axenic culture QH-2 from an intertidal zone of the China Sea. Res Microbiol. 2010;161:276–83.CAS 
    PubMed 

    Google Scholar 
    Kaimer C, Zusman DR. Regulation of cell reversal frequency in Myxococcus xanthus requires the balanced activity of CheY-like domains in FrzE and FrzZ. Mol Microbiol. 2016;100:379–95.CAS 
    PubMed 

    Google Scholar 
    Kühn MJ, Talà L, Inclan YF, Patino R, Pierrat X, Vos I, et al. Mechanotaxis directs Pseudomonas aeruginosa twitching motility. Proc Natl Acad Sci USA. 2021;118:e2101759118.PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Temporal change in plant communities and its relationship to soil salinity and microtopography on the Caspian Sea coast

    Shomurodov, K. F. & Adilov, B. A. Current state of the flora of Vozrozhdeniya Island (Uzbekistan). Arid Ecosyst. 9, 97–103 (2019).
    Google Scholar 
    Adilov, B. et al. Transformation of vegetative cover on the Ustyurt Plateau of Central Asia as a consequence of the Aral Sea shrinkage. J. Arid Land 13, 71–87 (2020).
    Google Scholar 
    Kuz’mina, Z. V. & Treshkin, S. E. Soil salinization and dynamics of Tugai vegetation in the southeastern Caspian Sea region and in the Aral Sea coastal region. Eurasian Soil Sci. 30, 642–649 (1997).
    Google Scholar 
    Kuz’mina, Z. V., Shinkarenko, S. S. & Solodovnikov, D. A. Main tendencies in the dynamics of floodplain ecosystems and landscapes of the lower reaches of the Syr Darya river under modern changing conditions. Arid Ecosyst. 9, 226–236 (2019).
    Google Scholar 
    Dimeyeva, L. A. Phytogeography of the northeastern coast of the Caspian Sea: Native flora and recent colonizations. J. Arid Land 5, 439–451 (2013).
    Google Scholar 
    Goryaev, I. A. & Korablev, A. P. Halophytic vegetation in the west caspian lowland. Contemp. Probl. Ecol. 13, 514–521 (2020).
    Google Scholar 
    Novikova, N. M., Volkova, N. A., Ulanova, S. S. & Chemidov, M. M. Change in vegetation on meliorated solonetcic soils of the Peri-Yergenian plain over 10 years (Republic of Kalmykia). Arid Ecosyst. 10, 194–202 (2020).
    Google Scholar 
    Ravanbakhsh, M., Amini, T. & Hosseini, S. M. N. Plant species diversity among ecological species groups in the Caspian Sea coastal sand dune; Case study: Guilan Province, North of Iran. Biodiversitas 16, 16–21 (2015).
    Google Scholar 
    Yan, S., Mu, G., Xu, Y. & Zhao, Z. Quarternary environmental evolution of the Lop Nur region, China. Dili Xuebao/Acta Geogr. Sin. 53, 332–340 (1998).
    Google Scholar 
    Hao, H., Ferguson, D. K., Chang, H. & Li, C. S. Vegetation and climate of the Lop Nur area, China, during the past 7 million years. Clim. Change 113, 323–338 (2012).ADS 

    Google Scholar 
    Li, C. et al. Growth and sustainability of Suaeda salsa in the Lop Nur, China. J. Arid Land 10, 429–440 (2018).
    Google Scholar 
    Barrett, G. Vegetation communities on the shores of a salt lake in semi-arid Western Australia. J. Arid Environ. 67, 77–89 (2006).ADS 

    Google Scholar 
    Neffar, S., Chenchouni, H. & Si Bachir, A. Floristic composition and analysis of spontaneous vegetation of Sabkha Djendli in north-east Algeria. Plant Biosyst. 150, 396–403 (2016).
    Google Scholar 
    Yanina, T. A. The Ponto-Caspian region: Environmental consequences of climate change during the Late Pleistocene. Quat. Int. 345, 88–99 (2014).
    Google Scholar 
    Rychagov, G. I. Pleistocene History of the Caspian Sea (Moscow State University, 1977).
    Google Scholar 
    Rychagov, G. I. The level mode of the Caspian Sea during the last 10000. Vestn. Mosk. Univ. Seriya 5 Geogr. 2, 38–49 (1993).
    Google Scholar 
    Kroonenberg, S. B. et al. Solar-forced 2600 BP and Little Ice Age highstands of the Caspian Sea. Quat. Int. 173–174, 137–143 (2007).
    Google Scholar 
    Kasimov, N. S., Lychagin, M. Y. & Kroonenberg, S. B. Geochemical indication of cyclic fluctuations of the caspian sea level. Vestn. Mosk. Univ. Seriya Geogr. 2, 72–77 (2011).
    Google Scholar 
    Kroonenberg, S. B., Badyukova, E. N., Storms, J. E. A., Ignatov, E. I. & Kasimov, N. S. A full sea-level cycle in 65 years: Barrier dynamics along Caspian shores. Sediment. Geol. 134, 257–274 (2000).ADS 

    Google Scholar 
    Bolikhovskaya, N. & Kasimov, N. The evolution of climate and landscapes of the Lower Volga region during the Holocene. Geogr. Environ. Sustain. 3, 78–97 (2010).
    Google Scholar 
    Magomedov, M.M.-R. & Gasanov, S. M. Features of soil changes under crowns of the shrubberies tamarisk (Tamarix meyeri boiss, T. ramosissima zedeb). South Russ. Ecol. Dev. 6, 12–21 (2014).
    Google Scholar 
    Du, N. et al. Facilitation or competition? The effects of the shrub species tamarix chinensis on herbaceous communities are dependent on the successional stage in an impacted coastal wetland of North China. Wetlands 37, 899–911 (2017).
    Google Scholar 
    Jiang, L., Jiapaer, G., Bao, A., Guo, H. & Ndayisaba, F. Vegetation dynamics and responses to climate change and human activities in Central Asia. Sci. Total Environ. 599–600, 967–980 (2017).ADS 
    PubMed 

    Google Scholar 
    Burke, I. C. et al. Plant–soil interactions in temperate grasslands. In Plant-Induced Soil Changes: Processes and Feedbacks (ed. van Breemen, N.) 121–143 (Springer, 1998). https://doi.org/10.1007/978-94-017-2691-7_7.Chapter 

    Google Scholar 
    Webb, C. O., Ackerly, D. D., McPeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu. Rev. Ecol. Syst. 33, 475–505 (2002).
    Google Scholar 
    Abaturov, B. D. Microdepression microrelief of Caspian Lowland and mechanisms of its formation. Arid. Ecosistemy 16, 31–45 (2010).
    Google Scholar 
    Sapanov, M. K. The results of soil water investigations in Djanybek stationary. Dokuchaev Soil Bull. 83, 22–40 (2016).
    Google Scholar 
    Bolshakov, A. F. & Bazykina, G. S. Natural biogeocenoses and the conditions of their existence. In Biogeocenotic Basis of the Reclamation of Semidesert in the Northern Caspain Lowland (ed. Rode, A. A.) 6–34 (Nauka, 1974).
    Google Scholar 
    Konyushkova, M. V., Nukhimovskaya, Y. D., Gasanova, Z. U. & Stepanova, N. Y. The temporal change in variability of soil salinity and phytodiversity at the coastal plain of the Caspian Sea. Arid Ecosyst. 10, 312–321 (2020).
    Google Scholar 
    Semenkov, I., Konyushkova, M., Heidari, A., Nukhimovskaya, Y. & Klink, G. Data on the soilscape and vegetation properties at the key site in the NW Caspian Sea coast, Russia. Data Br. 31, 105972 (2020).
    Google Scholar 
    Konyushkova, M. V. et al. Spatial and seasonal salt translocation in the young soils at the coastal plains of the Caspian Sea. Quat. Int. 590, 15–25 (2021).
    Google Scholar 
    Semenkov, I., Konyushkova, M., Heidari, A. & Nikolaev, E. Chemical differentiation of recent fine-textured soils on the Caspian Sea coast: A case study in Golestan (Iran) and Dagestan (Russia). Quat. Int. 590, 48–55 (2021).
    Google Scholar 
    Haghani, S. et al. An early ‘Little Ice Age’ brackish water invasion along the south coast of the Caspian Sea (sediment of Langarud wetland) and its wider impacts on environment and people. Holocene 26, 3–16 (2016).ADS 

    Google Scholar 
    Panin, G. N., Mamedov, R. M. & Mitrofanov, I. V. Present State of the Caspian Sea (Nauka, 2005).
    Google Scholar 
    Konyushkova, M. V. et al. The spatial differentiation of soil salinity at the young saline coastal plain of the Caspian region. Dokuchaev Soil Bull. 95, 41–57 (2018).
    Google Scholar 
    Cherepanov, S. K. Vascular Plants of Russia and Adjacent States (Within the Former USSR) (Cambridge University Press, 1995).
    Google Scholar 
    Takhtajan, A. Flowering Plants (Springer Science+Business Media B.V, 2009). https://doi.org/10.1007/978-1-4020-9609-9.Book 

    Google Scholar 
    Govaerts, R., Nic Lughadha, E., Black, N., Turner, R. & Paton, A. The World Checklist of Vascular Plants, a continuously updated resource for exploring global plant diversity. Sci. Data 8, 215 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    POWO. Plants of the World Online. Facilitated by the Royal Botanic Gardens, Kew (Board of Trustees of the Royal Botanic Gardens, 2022).Chase, M. W. et al. An update of the Angiosperm Phylogeny Group classification for the orders and families of flowering plants: APG IV. Bot. J. Linn. Soc. 181, 1–20 (2016).
    Google Scholar 
    Qian, H. & Jin, Y. An updated megaphylogeny of plants, a tool for generating plant phylogenies and an analysis of phylogenetic community structure. J. Plant Ecol. 9, 233–239 (2016).
    Google Scholar 
    Clarke, K. R. & Warwick, R. M. A taxonomic distinctness index and its statistical properties. J. Appl. Ecol. 35, 523–531 (1998).
    Google Scholar 
    Semenkov, I. N. et al. The variability of soils and vegetation of hydrothermal fields in the Valley of Geysers at Kamchatka Peninsula. Sci. Rep. 11, 11077 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2020).Wickham, H. & Henry, L. tidyr: Tidy Messy Data. R Packag. version 1.0.0 (2019).Goryaev, I. A. Regularities of distribution of halophytic vegetation on the Caspian Lowland. Bot. Zhurnal 104, 1072–1089 (2019).
    Google Scholar 
    Soltanmuradova, Z. I. & Teimurov, A. A. Taxonomic structure of the flora of the Primorskaya Lowland of the Republic of Dagestan. South Russ. Ecol. Dev. 3, 38 (2010).
    Google Scholar 
    Zörb, C., Sümer, A., Sungur, A., Flowers, T. J. & Özcan, H. Ranking of 11 coastal halophytes from salt marshes in northwest Turkey according their salt tolerance. Turk. J. Botany 37, 1125–1133 (2013).
    Google Scholar 
    Zhao, Y., Yu, H., Zhang, T. & Guo, J. Mycorrhizal colonization of chenopods and its influencing factors in different saline habitats, China. J. Arid Land 9, 143–152 (2017).
    Google Scholar 
    Podar, D. et al. Morphological, physiological and biochemical aspects of salt tolerance of halophyte Petrosimonia triandra grown in natural habitat. Physiol. Mol. Biol. Plants 25, 1335–1347 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nayyar, H. & Gupta, D. Differential sensitivity of C3 and C4 plants to water deficit stress: Association with oxidative stress and antioxidants. Environ. Exp. Bot. 58, 106–113 (2006).CAS 

    Google Scholar 
    Way, D. A., Katul, G. G., Manzoni, S. & Vico, G. Increasing water use efficiency along the C3 to C4 evolutionary pathway: A stomatal optimization perspective. J. Exp. Bot. 65, 3683–3693 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Atia, A. et al. Ecophysiological aspects in 105 plants species of saline and arid environments in Tunisia. J. Arid Land 6, 762–770 (2014).
    Google Scholar 
    Pickett, S. T. A. Space-for-time substitution as an alternative to long-term studies. In Long-Term Studies in Ecology 110–135 (1989) https://doi.org/10.1007/978-1-4615-7358-6_5.Walker, L. R., Wardle, D. A., Bardgett, R. D. & Clarkson, B. D. The use of chronosequences in studies of ecological succession and soil development. J. Ecol. 98, 725–736 (2010).
    Google Scholar 
    Dimeeva, L. A. Dynamics of vegetation in deserts of Aral and Caspian regions. (2011).Yu, K. et al. Late quaternary environments in the Gobi Desert of Mongolia: Vegetation, hydrological, and palaeoclimate evolution. Palaeogeogr. Palaeoclimatol. Palaeoecol. 514, 77–91 (2019).
    Google Scholar 
    Cao, X., Tian, F., Dallmeyer, A. & Herzschuh, U. Northern Hemisphere biome changes ( >30°N) since 40 cal ka BP and their driving factors inferred from model-data comparisons. Quat. Sci. Rev. 220, 291–309 (2019).ADS 

    Google Scholar 
    Zhang, D. et al. Response of vegetation to Holocene evolution of westerlies in the Asian Central Arid Zone. Quat. Sci. Rev. 229, 106138 (2020).
    Google Scholar 
    Lu, K. Q. et al. A new approach to interpret vegetation and ecosystem changes through time by establishing a correlation between surface pollen and vegetation types in the eastern central Asian desert. Palaeogeogr. Palaeoclimatol. Palaeoecol. 551, 109762 (2020).
    Google Scholar 
    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 
    Ziffer-Berger, J., Weisberg, P. J., Cablk, M. E. & Osem, Y. Spatial patterns provide support for the stress-gradient hypothesis over a range-wide aridity gradient. J. Arid Environ. 102, 27–33 (2014).ADS 

    Google Scholar 
    Vinogradov, B. V. Plant Indicators and Their Use in the Study of Natural Resources (Visshaya shkola, 1964).
    Google Scholar 
    Luo, C. et al. Characteristics of the modern pollen distribution and their relationship to vegetation in the Xinjiang region, northwestern China. Rev. Palaeobot. Palynol. 153, 282–295 (2009).
    Google Scholar 
    Zhao, Y. & Herzschuh, U. Modern pollen representation of source vegetation in the Qaidam Basin and surrounding mountains, north-eastern Tibetan Plateau. Veg. Hist. Archaeobot. 18, 245–260 (2009).
    Google Scholar  More

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    Morphological diversity and molecular phylogeny of five Paramecium bursaria (Alveolata, Ciliophora, Oligohymenophorea) syngens and the identification of their green algal endosymbionts

    Molecular Phylogeny of Paramecium bursaria and Identification of its EndosymbiontsThe SSU and ITS rDNA of the nuclear ribosomal operon were sequenced to infer the genetic variability of the investigated strains. The SSU and ITS rDNA sequences were aligned according to their secondary structure (examples are presented for the strain SAG 27.96; Fig. 1 and Supplementary Fig. 1). Additional sequences acquired from GenBank were incorporated into a dataset, which included all syngens also from references known for P. bursaria. The phylogenetic analyses revealed five highly supported lineages among the P. bursaria strains, which corresponded to their syngen assignment. As demonstrated in Fig. 2, all investigated strains belonging to the syngens R1, R2 and R5 originated from Europe, whereas the others of the syngens R3-R4 showed a worldwide distribution. The three known green algal endosymbionts, i.e., Chlorella variabilis (Cvar), Chlorella vulgaris (Cvul) and Micractinium conductrix (Mcon) showed no or only little affiliation to specific syngens.Figure 1ITS‐1 (A) and ITS-2 (B) secondary structures of Paramecium protobursaria, SAG 27.96 (syngen R1).Full size imageFigure 2Molecular phylogeny of the Paramecium bursaria species complex based on SSU and ITS rDNA sequence comparisons. The phylogenetic tree shown was inferred using the maximum likelihood method based on the datasets (2197 aligned positions of 19 taxa) using the computer program PAUP 4.0a169. For the analyses, the best model was calculated by PAUP 4.0a169. The setting of the best model was given as follows: TVM + I (base frequencies: A 0.2983, C 0.1840, G 0.2271, T 0.2906; rate matrix A–C 2.6501, A–G 8.6851, A–U 5.3270, C–G 0.91732, C–U 8.6851, G–U 1.0000) with the proportion of invariable sites (I = 0.9544). The branches in bold are highly supported in all bootstrap analyses (bootstrap values  > 50% calculated with PAUP using the maximum likelihood, neighbour—joining, and maximum parsimony). The clades are named after the syngens (color‐coded) proposed by Greczek‐Stachura et al.10 and Bomford9 in brackets. The accession numbers are given after the strain numbers. The endosymbiotic green algae identified are highlighted (Mcon—Micractinium conductrix, Cvar—Chlorella variabilis and Cvul—Chlorella vulgaris) after the origin of the P. bursaria strains. The reference strain of each syngen is marked with an asterisk. The strains used for morphological comparisons are marked with a green dot next to the strain number.Full size imageSynapomorphies of the Paramecium bursaria SyngensAs demonstrated in Fig. 2, the subdivision of the P. bursaria strains into syngens is supported by the phylogenetic analyses of the SSU and ITS rDNA sequences. To figure out if these splits were also supported by characteristic molecular signatures, we studied the secondary structures of both SSU and ITS of all available sequences. We discovered 30, respectively 23 variable positions among the SSU and ITS sequences (numbers of these positions in the respective alignments are given in Fig. 3). All syngens showed characteristic patterns among the SSU and ITS. Only the syngens R1 and R2 could not be distinguished using the SSU only, however, in combination with the ITS, each syngen is characterized by unique synapomorphies as highlighted in yellow (Fig. 3). In addition, few variable base positions within syngens (marked in blue in Fig. 3) have been recognized in the ITS regions. For comparison with literature data, we also analyzed all available sequences of the mitochondrial COI gene to find synapomorphies for the five syngens. Within this gene, only 18 variable positions at the amino acid level could be discovered of which 13 are diagnostic for the five syngens (Fig. 3).Figure 3Variable base positions among the SSU, ITS rRNA, and COI sequences of the five syngens among the Paramecium bursaria species complex. The unique synapomorphies are highlighted in yellow, variable positions marked in blue.Full size imageThe synapomorphies discovered above were used to get insights into the geographical distribution of each P. bursaria syngen. Despite the complete SSU and ITS rDNA sequences included in the phylogeny presented in Fig. 2, records of the partial SSU or ITS rDNA sequences are available in GenBank (BLASTn search; 100% identity;13). Considering the metadata of our investigated strains and of the entries in GenBank (Supplementary Table 1), we constructed three haplotype networks using the Templeton-Crandall-Sing (TCS) approach. The SSU haplotype network (Fig. 4) containing 84 records showed that the syngens R1, R2 and R5 were only found in Europe, whereas the other three syngens have been discovered around the world. A similar distribution pattern occurred when using the ITS (101 entries in GenBank). Records of syngens R1 and R5 have only been found in Europe, whereas all other syngens were distributed around the world. The 132 COI records found in GenBank by the BLASTn search were used for the haplotype network, which also showed the similar pattern (Fig. 4).Figure 4TCS haplotype networks of the five syngens inferred from SSU, ITS rRNA, and COI sequences of the Paramecium bursaria species complex. This network was inferred using the algorithm described by Clement et al.40,41. Sequence nodes corresponding to samples collected from different geographical regions.Full size imageCiliate TaxonomyConsidering all our findings, P. bursaria is morphologically highly variable, and obviously represents a cryptic species complex (Figs. 5, 6; Supplementary Table 2). The known five syngens most likely represent biological species according to Mayr14 and can be attributed to the cryptic species described by Greczek-Stachura et al.11. As mentioned above, the assignments of these cryptic species by Greczek-Stachura et al.11 have not been validly described according to the ICZN. In addition, the naming using a mixture of Latin prefix and Greek suffix is also not appropriate (the epithet bursa derived from the Greek word byrsa). Therefore, we describe the five syngens as new species as follows. The general morphological features of these species are summarized in Table 1.Figure 5Ventral views of Paramecium bursaria morphotypes in vivo: P. protobursaria (syngen R1), i.e., strains SAG 2645 (A) and PB-25 (B); P. deuterobursaria (syngen R2), i.e., strains CCAP 1660/36 (C) and CCAP 1660/34 (D); P. tritobursaria (syngen R3), i.e., strains CCAP 1660/28 (E), CCAP 1660/26 (F) and CCAP 1660/31 (G); P. tetratobursaria (syngen R4), i.e., strains CCAP 1660/25 (H) and CCAP 1660/33 (I); P. pentobursaria (syngen R5), i.e., strain CCAP 1660/30 (J). Scale bar 20 µm.Full size imageFigure 6Morphological details of the Paramecium bursaria species complex from specimens of strains PB-25 (A), CCAP 1660/30 (B), SAG 2645 (C, F, G, I, L–N), CCAP 1660/36 (D), CCAP 1660/26 (E, H), CCAP 1660/30 (J, O), CCAP 1660/16 (K) in vivo (A–F, H–O) and after silver nitrate staining (G). Adoral membranelles (A, B), endosymbiotic algae Micractinium conductrix (C), caudal and somatic cilia (D), arrows denote excretory pores of the contractile vacuoles: extruded extrusomes are shown and caudal cilia (E), ventral views showing the preoral suture and the oral opening (F), the ciliary pattern (G), arrows denote excretory pores of the contractile vacuoles (H), trichocysts and symbiotic algae underneath the pellicula (I, J), cell size variations (K), radial collecting channels (white arrows) and excretory pores (black arrows) of contractile vacuoles (L), macro- and micronucleus (M), cytopyge and characteristic rectangular pellicular pattern (N), pattern of the pellicula (O). AS anterior suture, CC caudal cilia, CP cytopyge (cell after), CV contractile vacuole, EP excretory pore of a contractile vacuole, EX extrusomes, M1–M3 membranelles 1–3, MA macronucleus, MI micronucleus, OO oral opening, S symbiotic algae, SC somatic cilia, SK somatic kineties, UM undulating membrane. Scale bars 10 µm (A, I), 20 µm (B, D–H, J, L–O), 50 µm (K).Full size imageTable 1 Main morphometric and morphological characteristics of the Paramecium bursaria syngens (min and max values).Full size table
    Paramecium protobursaria sp. nov.Synonym: Paramecium primabursaria nom. inval.Description: The strains SAG 27.96 and PB-25 belong to syngen R1 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (MT231333). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 70–164 × 44–65 µm; the single macronucleus is located around mid-cell and measures 25–38 × 11–22 µm; the adjacent single compact micronucleus measures 11–20 × 5–8 µm; the usually two (rarely one) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 14–22; the length of the caudal cilia is 9–19 µm; the numerous trichocysts located in the cell cortex are 4–6 µm in length. The symbiotic algae belong to M. conductrix; the larger algae measure 4–7 × 4–7 µm; the smaller algal cells measure 2–5 × 2–5 µm.Geographic distribution: The investigated strains of syngen R1 were found in Europe: Göttingen, Germany; Lake Mondsee, Austria. In addition, this species has been reported from different places in Europe, Asia and North America (see details in Supplementary Table 1).Reference material: Strain SAG 27.96 and the clonal strain SAG 2645 derived from SAG 27.96 are available at the Culture Collection of Algae (SAG), University of Göttingen, Germany.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the clonal culture SAG 2645, which derived from the reference material SAG 27.96, isolated from the pond of the Old Botanical Garden of the University of Göttingen (Germany), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: AFD967ED-BC2A-43FD-847E-5DF588BB025C.
    Paramecium deuterobursaria sp. nov.Synonym: Paramecium bibursaria nom. inval.Description: The strains CCAP 1660/34 and CCAP 1660/36 belong to syngen R2 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (OK318487). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 81–167 × 35–83 µm; the single macronucleus is located around mid-cell and measures 24–46 × 10–32 µm; the adjacent single compact micronucleus measures 10–18 × 5–9 µm, no micronucleus seen in live cells of strain CCAP 1660/34; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 13–22; the length of the caudal cilia is 11–20 µm; the numerous trichocysts located in the cell cortex are 4–6 µm in length. The symbiotic algae belong to M. conductrix; the larger algae measure 5–7 × 4–7 µm; the smaller algal cells measure 3–5 × 2–5 µm.Geographic distribution: The investigated strains of syngen R2 were found in Europe: Zurich, Switzerland; Lake Piburg, Austria. In addition, this species has been reported from different places in Europe, Asia and Australia (see details in Supplementary Table 1).Reference material: Strain CCAP 1660/36 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/36, isolated from Lake Piburg (Tyrol, Austria), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: D1C20BE6-9A15-4A3D-A7E5-DFC31FF04679.
    Paramecium tritobursaria sp. nov.Synonym: Paramecium tribursaria nom. inval.Description: The strains CCAP 1660/26, CCAP 1660/28 and CCAP 1660/31 belong to syngen R3 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (MT231339). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 80–153 × 49–73 µm; the single macronucleus is located around mid-cell and measures 21–53 × 12–31 µm; the adjacent single compact micronucleus measures 9–17 × 3–6 µm; no micronucleus seen in live cells of strain CCAP 1660/28; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 12–20; the length of the caudal cilia is 8–19 µm; the numerous trichocysts located in the cell cortex are 4–6 µm in length. The symbiotic algae belong to C. variabilis; the larger algae measure 4–7 × 3–6 µm; the smaller algal cells measure 3–5 × 2–4 µm.Geographic distribution: The investigated strains of syngen R3 were found in Europe and Asia: Lake Piburg, Austria; Tokyo, Japan; Khabarovsk region, Amur River, Russia. In addition, this species has been reported from different places in Europe, Asia, North and South America as well as in Australia (see details in Supplementary Table 1).Reference material: Strain CCAP 1660/26 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/26, isolated from Japan, have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: CC0FBA7E-9E3A-4C37-B424-C9BFF2018EC0.
    Paramecium tetratobursaria sp. nov.Synonym: Paramecium tetrabursaria nom. inval.Description: The strains CCAP 1660/25 and CCAP 1660/33 belong to syngen R4 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (MT231347). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 65–179 × 37–79 µm; the single macronucleus is located around mid-cell and measures 18–53 × 10–29 µm; the adjacent single compact micronucleus measures 8–18 × 4–10 µm; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 14–19; the length of the caudal cilia is 12–20 µm; the numerous trichocysts located in the cell cortex are 4–7 µm in length. The symbiotic algae belong to C. variabilis (CCAP 1660/25) and M. conductrix (CCAP 1660/33); the larger algae measure 3–6 × 3–6 µm; the smaller algal cells measure 2–5 × 1–4 µm.Geographic distribution: The investigated strains of syngen R4 are found in North- and South America: Burlington, North Carolina, USA; San Pedro de la Paz, Laguna Grande, Chile. In addition, this species has been reported from Europe (see details in Supplementary Table 1).Reference material: Strain CCAP 1660/25 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/25, isolated from a pond in Burlington (North Carolina, USA), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: 78BA9923-07A9-4918-AD7C-9E5E15CC9CDB.
    Paramecium pentobursaria sp. nov.Synonym: Paramecium pentabursaria nom. inval.Description: The strain CCAP 1660/30 belongs to syngen R5 according to Greczek-Stachura et al.10,11 and differs from other syngens by their SSU and ITS rDNA sequences (MT231348). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 161–194 × 76–99 µm; the single macronucleus is located around mid-cell and measures 24–47 × 19–31 µm; the adjacent single compact micronucleus measures 13–20 × 4–9 µm; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–4 excretory pores each; the number of ciliary rows/20 µm is 13–19; the length of the caudal cilia is 14–25 µm; the numerous trichocysts located in the cell cortex are 5–7 µm in length. The symbiotic algae belong to C. variabilis; the larger algae measure 5–6 × 5–6 µm; the smaller algal cells measure 4–5 × 3–4 µm.Geographic distribution: The investigated strain of Syngen R5 was found in Europe: Astrakhan Nature Reserve, Russia.Reference material: Strain CCAP 1660/30 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/30, isolated from Astrakhan Nature Reserve (Russia), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: 6629FA71-E00F-48C6-83AB-61C0CA4823B6.Syngen Affiliation related to Ciliate Morphology, Endosymbionts and Geographic DistributionPearson-correlations of morphometric, syngen-specific and endosymbiont datasets of the P. bursaria strains revealed four significant positive correlations (p  r  > 0.75) between ciliate cell length (BLEN) and width (BWID), BWID and macronucleus width (MACWID), as well as length and width of large symbiotic algae (LSALEN and LSAWID; Fig. 7).Figure 7Pearson-correlations of morphometric, symbiont and syngen data of Paramecium strains under study. Colored dots indicate the strength of correlation, and the size of dots represent p-values. Bold squares highlight significant correlations, with − 0.75  > r  > 0.75 and p  1, accounting for 73.1% variation in total (Supplementary Table 3). Principal component axis 1 (PC1) appears to be most negatively weighted by syngen (SYN) and width of the macronucleus (MACWID), separating CCAP 1660/30 and CCAP 1660/33 from the other strains. Principal component axis 2 (PC2) is primarily positively influenced by symbiotic algae characteristics (LSALEN, LSAWID, small symbiotic algal length (SSALEN) and width (SSAWID)) and, ciliate cell length (BLEN) and width (BWID; Supplementary Table 4), partitioning strain PB-25, CCAP 1660/26 and CCAP 1660/36 from CCAP 1660/31 and SAG 27.96 (Fig. 8).Figure 8PCA of morphometric data of Paramecium bursaria strains. Only the top eight contributing variables are shown.Full size imageThe redundancy analysis (RDA; Fig. 9) revealed a large difference between morphometric features and the tested set of explanatory variables (i.e., algal species (ALSPEC), LSAWID, SSALEN, SYN and GEO) as only 26.9% of the total variation could be explained.Figure 9Ordination diagram for redundancy analysis (RDA) of morphometric data and shown syngen (SYN), geographic region (GEO), and algal features (ALSPEC, LSAWID and SSALEN) as explanatory features.Full size image More

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    Climate change and species facilitation affect the recruitment of macroalgal marine forests

    Intergovernmental Panel on Climate Change (IPCC). The Ocean and Cryosphere in a Changing Climate: Special Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2022). https://doi.org/10.1017/9781009157964.Doney, S. C. et al. Climate change impacts on marine ecosystems. Annu. Rev. Mar. Sci. 4, 11–37 (2012).ADS 

    Google Scholar 
    Gattuso, J.-P. et al. Contrasting futures for ocean and society from different anthropogenic CO2 emissions scenarios. Science 349, aac4722 (2015).PubMed 

    Google Scholar 
    Hall-Spencer, J. M. & Harvey, B. P. Ocean acidification impacts on coastal ecosystem services due to habitat degradation. Emerg. Top. Life Sci. 3, 197–206 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Straub, S. C. et al. Resistance, extinction, and everything in between—The diverse responses of seaweeds to marine heatwaves. Front. Mar. Sci. 6, 763 (2019).
    Google Scholar 
    Connell, S. D., Kroeker, K. J., Fabricius, K. E., Kline, D. I. & Russell, B. D. The other ocean acidification problem: CO2 as a resource among competitors for ecosystem dominance. Philos. Trans. R. Soc. B Biol. Sci. 368, 20120442 (2013).
    Google Scholar 
    Kroeker, K. J., Micheli, F., Gambi, M. C. & Martz, T. R. Divergent ecosystem responses within a benthic marine community to ocean acidification. Proc. Natl. Acad. Sci. 108, 14515–14520 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Harvey, B. P., Kon, K., Agostini, S., Wada, S. & Hall-Spencer, J. M. Ocean acidification locks algal communities in a species-poor early successional stage. Glob. Change Biol. 27, 2174–2187 (2021).ADS 
    CAS 

    Google Scholar 
    Sunday, J. M. et al. Ocean acidification can mediate biodiversity shifts by changing biogenic habitat. Nat. Clim. Change 7, 81–85 (2017).ADS 
    CAS 

    Google Scholar 
    Wernberg, T. et al. Climate-driven regime shift of a temperate marine ecosystem. Science 353, 169–172 (2016).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Steneck, R. S. et al. Kelp forest ecosystems: Biodiversity, stability, resilience and future. Environ. Conserv. 29, 436–459 (2002).
    Google Scholar 
    Schiel, D. R. & Foster, M. S. The population biology of large brown seaweeds: Ecological consequences of multiphase life histories in dynamic coastal environments. Annu. Rev. Ecol. Evol. Syst. 37, 343–372 (2006).
    Google Scholar 
    Wernberg, T. & Filbee-Dexter, K. Missing the marine forest for the trees. Mar. Ecol. Prog. Ser. 612, 209–215 (2019).ADS 

    Google Scholar 
    Cheminée, A. et al. Nursery value of Cystoseira forests for Mediterranean rocky reef fishes. J. Exp. Mar. Biol. Ecol. 442, 70–79 (2013).
    Google Scholar 
    Smale, D. A., Burrows, M. T., Moore, P., O’Connor, N. & Hawkins, S. J. Threats and knowledge gaps for ecosystem services provided by kelp forests: A northeast Atlantic perspective. Ecol. Evol. 3, 4016–4038 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Carbajal, P., Gamarra Salazar, A., Moore, P. J. & Pérez-Matus, A. Different kelp species support unique macroinvertebrate assemblages, suggesting the potential community-wide impacts of kelp harvesting along the Humboldt Current System. Aquat. Conserv. Mar. Freshw. Ecosyst. 32, 14–27 (2022).
    Google Scholar 
    Filbee-Dexter, K. & Wernberg, T. Rise of turfs: A new battlefront for globally declining kelp forests. Bioscience 68, 64–76 (2018).
    Google Scholar 
    Pessarrodona, A. et al. Homogenization and miniaturization of habitat structure in temperate marine forests. Glob. Change Biol. 27, 5262–5275 (2021).CAS 

    Google Scholar 
    Orfanidis, S. et al. Effects of natural and anthropogenic stressors on Fucalean brown seaweeds across different spatial scales in the Mediterranean Sea. Front. Mar. Sci. 8, 1330 (2021).
    Google Scholar 
    Krumhansl, K. A. et al. Global patterns of kelp forest change over the past half-century. Proc. Natl. Acad. Sci. 113, 13785–13790 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Capdevila, P. et al. Warming impacts on early life stages increase the vulnerability and delay the population recovery of a long-lived habitat-forming macroalga. J. Ecol. 107, 1129–1140 (2019).
    Google Scholar 
    Irving, A. D., Balata, D., Colosio, F., Ferrando, G. A. & Airoldi, L. Light, sediment, temperature, and the early life-history of the habitat-forming alga Cystoseira barbata. Mar. Biol. 156, 1223–1231 (2009).
    Google Scholar 
    Smith, K. E., Moore, P. J., King, N. G. & Smale, D. A. Examining the influence of regional-scale variability in temperature and light availability on the depth distribution of subtidal kelp forests. Limnol. Oceanogr. 67, 314–328 (2022).ADS 

    Google Scholar 
    Smale, D. A. et al. Climate-driven substitution of foundation species causes breakdown of a facilitation cascade with potential implications for higher trophic levels. J. Ecol. 00, 1–13 (2022).
    Google Scholar 
    Hollarsmith, J. A., Buschmann, A. H., Camus, C. & Grosholz, E. D. Varying reproductive success under ocean warming and acidification across giant kelp (Macrocystis pyrifera) populations. J. Exp. Mar. Biol. Ecol. 522, 151247 (2020).
    Google Scholar 
    Verdura, J. et al. Local-scale climatic refugia offer sanctuary for a habitat-forming species during a marine heatwaves. J. Ecol. 109, 1758–1773 (2021).
    Google Scholar 
    Mariani, S. et al. Past and present of Fucales from shallow and sheltered shores in Catalonia. Reg. Stud. Mar. Sci. 32, 100824 (2019).
    Google Scholar 
    Smale, D. A. Impacts of ocean warming on kelp forest ecosystems. New Phytol. 225, 1447–1454 (2020).PubMed 

    Google Scholar 
    Coelho, S. M., Rijstenbil, J. W. & Brown, M. T. Impacts of anthropogenic stresses on the early development stages of seaweeds. J. Aquat. Ecosyst. Stress Recov. 7, 317–333 (2000).CAS 

    Google Scholar 
    de Caralt, S., Verdura, J., Vergés, A., Ballesteros, E. & Cebrian, E. Differential effects of pollution on adult and recruits of a canopy-forming alga: Implications for population viability under low pollutant levels. Sci. Rep. 10, 17825 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Capdevila, P. et al. Recruitment patterns in the Mediterranean deep-water alga Cystoseira zosteroides. Mar. Biol. 162, 1165–1174 (2015).CAS 

    Google Scholar 
    Vadas, R. L., Johnson, S. & Norton, T. A. Recruitment and mortality of early post-settlement stages of benthic algae. Br. Phycol. J. 27, 331–351 (1992).
    Google Scholar 
    Koch, M., Bowes, G., Ross, C. & Zhang, X.-H. Climate change and ocean acidification effects on seagrasses and marine macroalgae. Glob. Change Biol. 19, 103–132 (2013).ADS 

    Google Scholar 
    Shih, P. M. et al. Biochemical characterization of predicted Precambrian RuBisCO. Nat. Commun. 7, 10382 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cornwall, C. E. et al. Inorganic carbon physiology underpins macroalgal responses to elevated CO2. Sci. Rep. 7, 46297 (2017).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Hepburn, C. D. et al. Diversity of carbon use strategies in a kelp forest community: Implications for a high CO2 ocean. Glob. Change Biol. 17, 2488–2497 (2011).ADS 

    Google Scholar 
    Porzio, L., Buia, M. C. & Hall-Spencer, J. M. Effects of ocean acidification on macroalgal communities. J. Exp. Mar. Biol. Ecol. 400, 278–287 (2011).CAS 

    Google Scholar 
    Kroeker, K. J. et al. Impacts of ocean acidification on marine organisms: Quantifying sensitivities and interaction with warming. Glob. Change Biol. 19, 1884–1896 (2013).ADS 

    Google Scholar 
    Kroeker, K. J., Kordas, R. L., Crim, R. N. & Singh, G. G. Meta-analysis reveals negative yet variable effects of ocean acidification on marine organisms: Biological responses to ocean acidification. Ecol. Lett. 13, 1419–1434 (2010).PubMed 

    Google Scholar 
    Rindi, F. et al. Coralline algae in a changing Mediterranean Sea: How can we predict their future, if we do not know their present?. Front. Mar. Sci. 6, 723 (2019).
    Google Scholar 
    James, R. K., Hepburn, C. D., Cornwall, C. E., McGraw, C. M. & Hurd, C. L. Growth response of an early successional assemblage of coralline algae and benthic diatoms to ocean acidification. Mar. Biol. 161, 1687–1696 (2014).CAS 

    Google Scholar 
    Comeau, S. & Cornwall, C. E. Contrasting effects of ocean acidification on coral reef “animal forests” versus seaweed “kelp forests.” In Marine Animal Forests: The Ecology of Benthic Biodiversity Hotspots (eds Rossi, S. et al.) 1–25 (Springer International Publishing, 2016) https://doi.org/10.1007/978-3-319-17001-5_29-1.Chapter 

    Google Scholar 
    Airoldi, L. Effects of disturbance, life histories, and overgrowth on coexistence of algal crusts and turfs. Ecology 81, 798–814 (2000).
    Google Scholar 
    Asnaghi, V. et al. Colonisation processes and the role of coralline algae in rocky shore community dynamics. J. Sea Res. 95, 132–138 (2015).ADS 

    Google Scholar 
    Bulleri, F., Bertocci, I. & Micheli, F. Interplay of encrusting coralline algae and sea urchins in maintaining alternative habitats. Mar. Ecol. Prog. Ser. 243, 101–109 (2002).ADS 

    Google Scholar 
    Villas Bôas, A. B. & Figueiredo, M. A. D. O. Are anti-fouling effects in coralline algae species specific?. Braz. J. Oceanogr. 52, 11–18 (2004).
    Google Scholar 
    Bulleri, F., Benedetti-Cecchi, L., Acunto, S., Cinelli, F. & Hawkins, S. J. The influence of canopy algae on vertical patterns of distribution of low-shore assemblages on rocky coasts in the northwest Mediterranean. J. Exp. Mar. Biol. Ecol. 267, 89–106 (2002).
    Google Scholar 
    Maggi, E., Bertocci, I., Vaselli, S. & Benedetti-Cecchi, L. Connell and Slatyer’s models of succession in the biodiversity era. Ecology 92, 1399–1406 (2011).CAS 
    PubMed 

    Google Scholar 
    Irving, A. D., Connell, S. D., Johnston, E. L., Pile, A. J. & Gillanders, B. M. The response of encrusting coralline algae to canopy loss: An independent test of predictions on an Antarctic coast. Mar. Biol. 147, 1075–1083 (2005).
    Google Scholar 
    Irving, A. D., Connell, S. D. & Elsdon, T. S. Effects of kelp canopies on bleaching and photosynthetic activity of encrusting coralline algae. J. Exp. Mar. Biol. Ecol. 310, 1–12 (2004).
    Google Scholar 
    Melville, A. J. & Connell, S. D. Experimental effects of kelp canopies on subtidal coralline algae. Austral. Ecol. 26, 102–108 (2001).
    Google Scholar 
    Breitburg, D. L. Residual effects of grazing: Inhibition of competitor recruitment by encrusting coralline algae. Ecology 65, 1136–1143 (1984).
    Google Scholar 
    Bulleri, F., Bruno, J. F., Silliman, B. R. & Stachowicz, J. J. Facilitation and the niche: Implications for coexistence, range shifts and ecosystem functioning. Funct. Ecol. 30, 70–78 (2016).
    Google Scholar 
    van der Heide, T., Angelini, C., de Fouw, J. & Eklöf, J. S. Facultative mutualisms: A double-edged sword for foundation species in the face of anthropogenic global change. Ecol. Evol. 11, 29–44 (2021).PubMed 

    Google Scholar 
    Molinari-Novoa, E. A. & Guiry, E. Reinstatement of the genera Gongolaria Boehmer and Ericaria Stackhouse (Sargassaceae, Phaeophyceae). Notulae Algarum 1–10 (2020).Celis-Plá, P. S. M., Martinez, B., Korbee, N., Hall-Spencer, J. M. & Figueroa, F. L. Ecophysiological responses to elevated CO2 and temperature in Cystoseira tamariscifolia (Phaeophyceae). Clim. Change 142, 67–81 (2017).ADS 

    Google Scholar 
    Falace, A. et al. Is the South-Mediterranean canopy-forming Ericaria giacconei (= Cystoseira hyblaea) a loser from ocean warming?. Front. Mar. Sci. 8, 1758 (2021).
    Google Scholar 
    Hernández, C. A., Sangil, C., Fanai, A. & Hernández, J. C. Macroalgal response to a warmer ocean with higher CO2 concentration. Mar. Environ. Res. 136, 99–105 (2018).PubMed 

    Google Scholar 
    Falace, A., Kaleb, S., Fuente, G. D. L., Asnaghi, V. & Chiantore, M. Ex situ cultivation protocol for Cystoseira amentacea var. stricta (Fucales, Phaeophyceae) from a restoration perspective. PLoS ONE 13, e0193011 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Bevilacqua, S. et al. Climatic anomalies may create a long-lasting ecological phase shift by altering the reproduction of a foundation species. Ecology 100, 1–4 (2019).
    Google Scholar 
    Savonitto, G. et al. Addressing reproductive stochasticity and grazing impacts in the restoration of a canopy-forming brown alga by implementing mitigation solutions. Aquat. Conserv. Mar. Freshw. Ecosyst. 31, 1611–1623 (2021).
    Google Scholar 
    Mangialajo, L. et al. Zonation patterns and interspecific relationships of fucoids in microtidal environments. J. Exp. Mar. Biol. Ecol. 412, 72–80 (2012).
    Google Scholar 
    Verlaque, M., Boudouresque, C.-F. & Perret-Boudouresque, M. Mediterranean seaweeds listed as threatened under the Barcelona Convention: A critical analysis. Sci. Rep. Port-Cros Natl. Park. 33, 179–214 (2019).
    Google Scholar 
    Benedetti-Cecchi, L. & Cinelli, F. Effects of canopy cover, herbivores and substratum type on patterns of Cystoseira spp. settlement and recruitment in littoral rockpools. Mar. Ecol. Prog. Ser. 90, 183–191 (1992).ADS 

    Google Scholar 
    Fuente, G. D. L., Chiantore, M., Asnaghi, V., Kaleb, S. & Falace, A. First ex situ outplanting of the habitat-forming seaweed Cystoseira amentacea var. stricta from a restoration perspective. PeerJ 7, e7290 (2019).
    Google Scholar 
    Orlando-Bonaca, M. et al. First restoration experiment for Gongolaria barbata in Slovenian coastal waters. What can go wrong?. Plants 10, 239 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Christie, H. et al. Shifts between sugar kelp and turf algae in Norway: Regime shifts or fluctuations between different opportunistic seaweed species?. Front. Mar. Sci. 6, 72 (2019).
    Google Scholar 
    Orlando-Bonaca, M., Pitacco, V. & Lipej, L. Loss of canopy-forming algal richness and coverage in the northern Adriatic Sea. Ecol. Indic. 125, 107501 (2021).
    Google Scholar 
    Thibaut, T., Blanfune, A., Boudouresque, C.-F. & Verlaque, M. Decline and local extinction of Fucales in French Riviera: The harbinger of future extinctions?. Mediterr. Mar. Sci. 16, 206–224 (2015).
    Google Scholar 
    Thibaut, T., Pinedo, S., Torras, X. & Ballesteros, E. Long-term decline of the populations of Fucales (Cystoseira spp. and Sargassum spp.) in the Albères coast (France, North-western Mediterranean). Mar. Pollut. Bull. 50, 1472–1489 (2005).CAS 
    PubMed 

    Google Scholar 
    Leal, P. P. et al. Copper pollution exacerbates the effects of ocean acidification and warming on kelp microscopic early life stages. Sci. Rep. 8, 14763 (2018).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Fernández, P. A., Navarro, J. M., Camus, C., Torres, R. & Buschmann, A. H. Effect of environmental history on the habitat-forming kelp Macrocystis pyrifera responses to ocean acidification and warming: A physiological and molecular approach. Sci. Rep. 11, 2510 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Lind, A. C. & Konar, B. Effects of abiotic stressors on kelp early life-history stages. Algae 32, 223–233 (2017).CAS 

    Google Scholar 
    Fernández, P. A. et al. Nitrogen sufficiency enhances thermal tolerance in habitat-forming kelp: Implications for acclimation under thermal stress. Sci. Rep. 10, 3186 (2020).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Celis-Plá, P. S. M. et al. Macroalgal responses to ocean acidification depend on nutrient and light levels. Front. Mar. Sci. 2, 26 (2015).
    Google Scholar 
    Mancuso, F. P. et al. Influence of ambient temperature on the photosynthetic activity and phenolic content of the intertidal Cystoseira compressa along the Italian coastline. J. Appl. Phycol. 31, 3069–3076 (2019).CAS 

    Google Scholar 
    Vergés, A. et al. The tropicalization of temperate marine ecosystems: Climate-mediated changes in herbivory and community phase shifts. Proc. R. Soc. B Biol. Sci. 281, 20140846 (2014).
    Google Scholar 
    Vergés, A. et al. Tropical rabbitfish and the deforestation of a warming temperate sea. J. Ecol. 102, 1518–1527 (2014).
    Google Scholar 
    Gaitán-Espitia, J. D. et al. Interactive effects of elevated temperature and pCO2 on early-life-history stages of the giant kelp Macrocystis pyrifera. J. Exp. Mar. Biol. Ecol. 457, 51–58 (2014).
    Google Scholar 
    Leal, P. P., Hurd, C. L., Fernández, P. A. & Roleda, M. Y. Ocean acidification and kelp development: Reduced pH has no negative effects on meiospore germination and gametophyte development of Macrocystis pyrifera and Undaria pinnatifida. J. Phycol. 53, 557–566 (2017).CAS 
    PubMed 

    Google Scholar 
    Roleda, M. Y., Morris, J. N., McGraw, C. M. & Hurd, C. L. Ocean acidification and seaweed reproduction: Increased CO2 ameliorates the negative effect of lowered pH on meiospore germination in the giant kelp Macrocystis pyrifera (Laminariales, Phaeophyceae). Glob. Change Biol. 18, 854–864 (2011).ADS 

    Google Scholar 
    Zhang, X. et al. Elevated CO2 concentrations promote growth and photosynthesis of the brown alga Saccharina japonica. J. Appl. Phycol. https://doi.org/10.1007/s10811-020-02108-1 (2020).Article 

    Google Scholar 
    Falkenberg, L. J., Russell, B. D. & Connell, S. D. Contrasting resource limitations of marine primary producers: Implications for competitive interactions under enriched CO2 and nutrient regimes. Oecologia 172, 575–583 (2013).ADS 
    PubMed 

    Google Scholar 
    Nagelkerken, I., Russell, B. D., Gillanders, B. M. & Connell, S. D. Ocean acidification alters fish populations indirectly through habitat modification. Nat. Clim. Change 6, 89–93 (2016).ADS 
    CAS 

    Google Scholar 
    Connell, S. D. & Russell, B. D. The direct effects of increasing CO2 and temperature on non-calcifying organisms: increasing the potential for phase shifts in kelp forests. Proc. R. Soc. B Biol. Sci. 277, 1409–1415 (2010).
    Google Scholar 
    Cornwall, C. E., Comeau, S. & McCulloch, M. T. Coralline algae elevate pH at the site of calcification under ocean acidification. Glob. Change Biol. 23, 4245–4256 (2017).ADS 

    Google Scholar 
    Martin, S. & Gattuso, J.-P. Response of Mediterranean coralline algae to ocean acidification and elevated temperature. Glob. Change Biol. 15, 2089–2100 (2009).ADS 

    Google Scholar 
    Cornwall, C. E. et al. Diffusion boundary layers ameliorate the negative effects of ocean acidification on the temperate coralline macroalga Arthrocardia corymbosa. PLoS ONE 9, e97235 (2014).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Gefen-Treves, S. et al. The microbiome associated with the reef builder Neogoniolithon sp. in the eastern Mediterranean. Microorganisms 9, 1374 (2021).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Johnson, C. R. & Mann, K. H. The crustose coralline alga, Phymatolithon Foslie, inhibits the overgrowth of seaweeds without relying on herbivores. J. Exp. Mar. Biol. Ecol. 96, 127–146 (1986).
    Google Scholar 
    Keats, D. W., Knight, M. A. & Pueschel, C. M. Antifouling effects of epithallial shedding in three crustose coralline algae (Rhodophyta, Coralinales) on a coral reef. J. Exp. Mar. Biol. Ecol. 213, 281–293 (1997).
    Google Scholar 
    Mancuso, F., D’Hondt, S., Willems, A., Airoldi, L. & Clerck, O. Diversity and temporal dynamics of the epiphytic bacterial communities associated with the canopy-forming seaweed Cystoseira compressa (Esper) Gerloff and Nizamuddin. Front. Microbiol. 7, 476 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Blanfuné, A., Boudouresque, C. F., Verlaque, M. & Thibaut, T. The ups and downs of a canopy-forming seaweed over a span of more than one century. Sci. Rep. 9, 1–10 (2019).
    Google Scholar 
    Cebrian, E. et al. A roadmap for the restoration of Mediterranean macroalgal forests. Front. Mar. Sci. 8, 1456 (2021).
    Google Scholar 
    Gianni, F. et al. Conservation and restoration of marine forests in the Mediterranean Sea and the potential role of Marine Protected Areas. Adv. Oceanogr. Limnol. 4, 83–101 (2013).
    Google Scholar 
    Gorman, D. & Connell, S. D. Recovering subtidal forests in human-dominated landscapes. J. Appl. Ecol. 46, 1258–1265 (2009).
    Google Scholar 
    Riquet, F. et al. Highly restricted dispersal in habitat-forming seaweed may impede natural recovery of disturbed populations. Sci. Rep. 11, 16792 (2021).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Halpern, B. S., McLeod, K. L., Rosenberg, A. A. & Crowder, L. B. Managing for cumulative impacts in ecosystem-based management through ocean zoning. Ocean Coast. Manag. 51, 203–211 (2008).
    Google Scholar 
    Verdura, J., Sales, M., Ballesteros, E., Cefalì, M. E. & Cebrian, E. Restoration of a canopy-forming alga based on recruitment enhancement: Methods and long-term success assessment. Front. Plant Sci. 9, 1832 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Kwiatkowski, L. et al. Twenty-first century ocean warming, acidification, deoxygenation, and upper-ocean nutrient and primary production decline from CMIP6 model projections. Biogeosciences 17, 3439–3470 (2020).ADS 
    CAS 

    Google Scholar 
    Dickson, A. G., Sabine, C. L. & Christian, J. R. Guide to Best Practices for Ocean CO2 Measurements. https://repository.oceanbestpractices.org/handle/11329/249 (2007).Spencer Davies, P. Short-term growth measurements of corals using an accurate buoyant weighing technique. Mar. Biol. 101, 389–395. https://doi.org/10.1007/BF00428135 (1989).Article 

    Google Scholar 
    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting Linear Mixed-Effects Models Using lme4. ArXiv14065823 Stat (2015).R: The R Project for Statistical Computing. https://www.r-project.org/.Fox, J. & Weisberg, S. An R Companion to Applied Regression (SAGE Publications, 2018).
    Google Scholar 
    Lenth, R. V. et al. emmeans: Estimated Marginal Means, aka Least-Squares Means (2022). More

  • in

    Characterizing phenotypic diversity in marine populations of the threespine stickleback

    Bell, M. A. & Foster, S. A. The Evolutionary Biology of the Threespine Stickleback (Oxford University Press, 1994).
    Google Scholar 
    Seebacher, F., Webster, M. M., James, R. S., Tallis, J. & Ward, A. J. W. Morphological differences between habitats are associated with physiological and behavioural trade-offs in stickleback (Gasterosteus aculeatus). R. Soc. Open Sci. 3, 160316 (2016).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Bolnick, D. I. et al. Phenotype-dependent native habitat preference facilitates divergence between parapatric lake and stream stickleback. Evolution 63, 2004–2016 (2009).PubMed 

    Google Scholar 
    Svanbäck, R. & Schluter, D. Niche specialization influences adaptive phenotypic plasticity in the threespine stickleback. Am. Nat. 180, 50–59 (2012).PubMed 

    Google Scholar 
    Caldecutt, W. J. & Adams, D. C. Morphometrics of trophic osteology in the threespine stickleback, Gasterosteus aculeatus. Copeia 1998, 827–838 (1998).
    Google Scholar 
    Yershov, P. & Sukhotin, A. Age and growth of marine three-spined stickleback in the White Sea 50 years after a population collapse. Polar Biol. 38, 1813–1823 (2015).
    Google Scholar 
    Dorgham, A. S. et al. Morphological variation of threespine stickleback (Gasterosteus aculeatus) on different stages of spawning period. Proc. KarRC RAS 59–73 (2018). https://doi.org/10.17076/them819.DeFaveri, J. & Merilä, J. Evidence for adaptive phenotypic differentiation in Baltic Sea sticklebacks. J. Evol. Biol. 26, 1700–1715 (2013).CAS 
    PubMed 

    Google Scholar 
    Shaw, K. A., Scotti, M. L. & Foster, S. A. Ancestral plasticity and the evolutionary diversification of courtship behaviour in threespine sticklebacks. Anim. Behav. 73, 415–422 (2007).
    Google Scholar 
    McGee, M. D., Schluter, D. & Wainwright, P. C. Functional basis of ecological divergence in sympatric stickleback. BMC Evol. Biol. 13, 277 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Berner, D., Grandchamp, A.-C. & Hendry, A. P. Variable progress toward ecological speciation in parapatry: Stickleback across eight lake-stream transitions. Evolution 63, 1740–1753 (2009).PubMed 

    Google Scholar 
    Walker, J. A. Ecological morphology of lacustrine threespine stickleback Gasterosteus aculeatus L. (Gasterosteidae) body shape. Biol. J. Linn. Soc. 61, 3–50 (1997).
    Google Scholar 
    Hagen, D. W. & Gilbertson, L. G. Geographic variation and environmental selection in Gasterosteus aculeatus L. in the Pacific Northwest America. Evolution 26, 32–51 (1972).CAS 
    PubMed 

    Google Scholar 
    Smith, C., Zięba, G., Spence, R., Klepaker, T. & Przybylski, M. Three-spined stickleback armour predicted by body size, minimum winter temperature and pH. J. Zool. 311, 13–22 (2020).
    Google Scholar 
    Aguirre, W. E. & Bell, M. A. Twenty years of body shape evolution in a threespine stickleback population adapting to a lake environment: Stickleback body shape evolution. Biol. J. Linn. Soc. 105, 817–831 (2012).
    Google Scholar 
    Lavin, P. A. & McPhail, J. D. The evolution of freshwater diversity in the threespine stickleback (Gasterosteus aculeatus): Site-specific differentiation of trophic morphology. Can. J. Zool. 63, 2632–2638 (1985).
    Google Scholar 
    Matthews, B., Marchinko, K. B., Bolnick, D. I. & Mazumder, A. Specialization of trophic position and habitat use by sticklebacks in an adaptive radiation. Ecology 91, 1025–1034 (2010).PubMed 

    Google Scholar 
    Lefébure, R., Larsson, S. & Byström, P. A temperature-dependent growth model for the three-spined stickleback Gasterosteus aculeatus. J. Fish Biol. 79, 1815–1827 (2011).PubMed 

    Google Scholar 
    Foster, S. A. Inference of evolutionary pattern: Diversionary displays of three-spined sticklebacks. Behav. Ecol. 5, 114–121 (1992).
    Google Scholar 
    Taylor, E. B. & McPhail, J. D. Evolutionary history of an adaptive radiation in species pairs of threespine sticklebacks (Gasterosteus): Insights from mitochondrial DNA. Biol. J. Linn. Soc. 66, 271–291 (1999).
    Google Scholar 
    Hohenlohe, P. A., Bassham, S., Currey, M. & Cresko, W. A. Extensive linkage disequilibrium and parallel adaptive divergence across threespine stickleback genomes. Phil. Trans. R. Soc. B 367, 395–408 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Walker, J. A. & Bell, M. A. Net evolutionary trajectories of body shape evolution within a microgeographic radiation of threespine sticklebacks (Gasterosteus aculeatus). J. Zool. 252, 293–302 (2000).
    Google Scholar 
    Kristjánsson, B. K., Skúlason, S. & Noakes, D. L. G. Rapid divergence in a recently isolated population of threespine stickleback (Gasterosteus aculeatus L.). Evol. Ecol. Res. 4, 659–672 (2002).
    Google Scholar 
    Wund, M. A., Baker, J. A., Clancy, B., Golub, J. L. & Foster, S. A. A test of the “flexible stem” model of evolution: Ancestral plasticity, genetic accommodation, and morphological divergence in the threespine stickleback radiation. Am. Nat. 172, 449–462 (2008).PubMed 

    Google Scholar 
    Arif, S., Aguirre, W. E. & Bell, M. A. Evolutionary diversification of opercle shape in Cook Inlet threespine stickleback. Biol. J. Linn. Soc. 97, 832–844 (2009).
    Google Scholar 
    Terekhanova, N. V. et al. Fast evolution from precast bricks: Genomics of young freshwater populations of threespine stickleback Gasterosteus aculeatus. PLoS Genet. 10, e1004696 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Miller, S. E., Roesti, M. & Schluter, D. A single interacting species leads to widespread parallel evolution of the stickleback genome. Curr. Biol. 29, 530–537 (2019).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ab Ghani, N. I., Herczeg, G. & Merilä, J. Effects of perceived predation risk and social environment on the development of three-spined stickleback (Gasterosteus aculeatus) morphology. Biol. J. Linn. Soc. 118, 520–535 (2016).
    Google Scholar 
    DeFaveri, J. & Merilä, J. Local adaptation to salinity in the three-spined stickleback?. J. Evol. Biol. 27, 290–302 (2014).CAS 
    PubMed 

    Google Scholar 
    Jakubavičiūtė, E., De Blick, Y., Dainys, J., Ložys, L. & Olsson, J. Morphological divergence of three-spined stickleback in the Baltic Sea—Implications for stock identification. Fish. Res. 204, 305–315 (2018).
    Google Scholar 
    Yanos, C. L. et al. Predator biomass and vegetation influence the coastal distribution of threespine stickleback morphotypes. Ecol. Evol. 00, 1–12 (2021).
    Google Scholar 
    Fang, B., Merilä, J., Ribeiro, F., Alexandre, C. M. & Momigliano, P. Worldwide phylogeny of three-spined sticklebacks. Mol. Phylogenet. Evol. 127, 613–625 (2018).PubMed 

    Google Scholar 
    Ortí, G., Bell, M. A., Reimchen, T. E. & Meyer, A. Global survey of mitochondrial DNA sequences in the threespine sticklebacks: Evidence for recent migrations. Evolution 48, 608–622 (1994).PubMed 

    Google Scholar 
    Mäkinen, H. S. & Merilä, J. Mitochondrial DNA phylogeography of the three-spined stickleback (Gasterosteus aculeatus) in Europe: Evidence for multiple glacial refugia. Mol. Phylogenet. Evol. 46, 167–182 (2008).PubMed 

    Google Scholar 
    Thomson, R. E. Oceanography of the British Columbia Coast (Department of Fisheries and Oceans, 1981).
    Google Scholar 
    Emmett, R. et al. Geographic signatures of North American west coast estuaries. Estuaries 23, 765 (2000).CAS 

    Google Scholar 
    Dallimore, A. & Jmieff, D. Canadian west coast fjords and inlets. Geol. Soc. Spec. Pub. 344, 143–162 (2010).
    Google Scholar 
    Schoch, G. C., Albert, D. M. & Shanley, C. S. An estuarine habitat classification for a complex fjordal island archipelago. Estuaries Coasts 37, 160–176 (2014).
    Google Scholar 
    Rudnick, D. L. & Ferrari, R. Compensation of horizontal temperature and salinity gradients in the ocean mixed layer. Science 283, 526–529 (1999).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Barrett, R. D. H., Rogers, S. M. & Schluter, D. Environment specific pleiotropy facilitates divergence at the Ectodysplasin locus in threespine stickleback. Evolution 63, 2831–2837 (2009).PubMed 

    Google Scholar 
    McCairns, R. J. S. & Bernatchez, L. Plasticity and heritability of morphological variation within and between parapatric stickleback demes. J. Evol. Biol. 25, 1097–1112 (2012).CAS 
    PubMed 

    Google Scholar 
    Webster, M. M., Atton, N., Hart, P. J. B. & Ward, A. J. W. Habitat-specific morphological variation among threespine sticklebacks (Gasterosteus aculeatus) within a drainage basin. PLoS ONE 6, e21060 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Spoljaric, M. A. & Reimchen, T. E. 10 000 years later: evolution of body shape in Haida Gwaii three-spined stickleback. J. Fish. Biol. 70, 1484–1503 (2007).
    Google Scholar 
    Spoljaric, M. A. & Reimchen, T. E. Habitat-dependent reduction of sexual dimorphism in geometric body shape of Haida Gwaii threespine stickleback. Biol. J. Linn. Soc. 95, 505–516 (2008).
    Google Scholar 
    Spoljaric, M. A. & Reimchen, T. E. Habitat-specific trends in ontogeny of body shape in stickleback from coastal archipelago: Potential for rapid shifts in colonizing populations. J. Morphol. 272, 590–597 (2011).CAS 
    PubMed 

    Google Scholar 
    Morris, M. R. J. et al. Gene expression plasticity evolves in response to colonization of freshwater lakes in threespine stickleback. Mol. Ecol. 23, 3226–3240 (2014).PubMed 

    Google Scholar 
    Ramler, D., Mitteroecker, P., Shama, L. N. S., Wegner, K. M. & Ahnelt, H. Nonlinear effects of temperature on body form and developmental canalization in the threespine stickleback. J. Evol. Biol. 27, 497–507 (2014).CAS 
    PubMed 

    Google Scholar 
    Mazzarella, A. B., Voje, K. L., Hansson, T. H., Taugbøl, A. & Fischer, B. Strong and parallel salinity-induced phenotypic plasticity in one generation of threespine stickleback. J. Evol. Biol. 28, 667–677 (2015).CAS 
    PubMed 

    Google Scholar 
    Leinonen, T., Cano, J. M., Mäkinen, H. & Merilä, J. Contrasting patterns of body shape and neutral genetic divergence in marine and lake populations of threespine sticklebacks. J. Evol. Biol. 19, 1803–1812 (2006).CAS 
    PubMed 

    Google Scholar 
    Schluter, D., Marchinko, K. B., Barrett, R. D. H. & Rogers, S. M. Natural selection and the genetics of adaptation in threespine stickleback. Phil. Trans. R. Soc. B 365, 2479–2486 (2010).PubMed 
    PubMed Central 

    Google Scholar 
    Rogers, S. M. et al. Genetic signature of adaptive peak shift in threespine stickleback. Evolution 66, 2439–2450 (2012).PubMed 
    PubMed Central 

    Google Scholar 
    Jamniczky, H. A., Barry, T. N. & Rogers, S. M. Eco-evo-devo in the study of adaptive divergence: Examples from threespine stickleback (Gasterosteus aculeatus). Integr. Comp. Biol. 55, 166–178 (2015).PubMed 

    Google Scholar 
    Gow, J. L., Rogers, S. M., Jackson, M. & Schluter, D. Ecological predictions lead to the discovery of a benthic–limnetic sympatric species pair of threespine stickleback in Little Quarry Lake, British Columbia. Can. J. Zool. 86, 564–571 (2008).
    Google Scholar 
    McPhail, J. D. Genetic evidence for a species pair in Enos Lake, British Columbia. Can. J. Zool. 62, 1402–1408 (1984).
    Google Scholar 
    McPhail, J. D. Ecology and evolution of sympatric sticklebacks (Gasterosteus): Origin of the species pairs. Can. J. Zool. 71, 515–523 (1993).
    Google Scholar 
    Kimmel, C. B., Aguirre, W., Ullmann, B., Currey, M. & Cresko, W. Allometric change accompanies opercular shape evolution in Alaskan threespine sticklebacks. Behaviour 145, 669–691 (2008).
    Google Scholar 
    Wootton, R. J. A Functional Biology of Sticklebacks (Croom Helm, 1984).
    Google Scholar 
    Kitano, J., Mori, S. & Peichel, C. L. Sexual dimorphism in the external morphology of the threespine stickleback (Gasterosteus aculeatus). Copeia 2, 336–349 (2007).
    Google Scholar 
    Aguirre, W. E., Ellis, K. E., Kusenda, M. & Bell, M. A. Phenotypic variation and sexual dimorphism in anadromous threespine stickleback: Implications for postglacial adaptive radiation. Biol. J. Linn. Soc. 95, 465–478 (2008).
    Google Scholar 
    Davenne, E. & Masson, D. Water properties in the Straits of Georgia and Juan de Fuca. 41 http://www.pac.dfo-mpo.gc.ca/sci/osap/projects/straitofgeorgia/JdFG_e.pdf (2001).Irvine, J. R. & Crawford, W. R. State of the Ocean Report for the Pacific North Coast Integrated Management Area (PNCIMA). 51 (2011).DFO. Data from British Columbia (BC) Lighthouses. Department of Fisheries and Oceans https://www.dfo-mpo.gc.ca/science/data-donnees/lightstations-phares/index-eng.html (2020).Palumbi, S. R. Genetic divergence, reproductive isolation, and marine speciation. Annu. Rev. Ecol. Evol. Syst. 25, 547–572 (1994).
    Google Scholar 
    Griffin, D. A. & LeBlond, P. H. Estuary/ocean exchange controlled by spring-neap tidal mixing. Estuar. Coast Shelf. Sci. 30, 275–297 (1990).ADS 

    Google Scholar 
    Vaz, N., Dias, J. M., Leitão, P. & Martins, I. Horizontal patterns of water temperature and salinity in an estuarine tidal channel: Ria de Aveiro. Ocean Dyn. 55, 416–429 (2005).ADS 

    Google Scholar 
    Rybkina, E. V., Ivanova, T. S., Ivanov, M. V., Kucheryavyy, A. V. & Lajus, D. L. Habitat preference of three-spined stickleback juveniles in experimental conditions and in wild eelgrass. J. Mar. Biol. Ass. UK 97, 1437–1445 (2017).
    Google Scholar 
    Flynn, S., Cadrin, C. & Filatow, D. Estuaries in British Columbia. 6 (2006).Kelly, J. R., Proctor, H. & Volpe, J. P. Intertidal community structure differs significantly between substrates dominated by native eelgrass (Zostera marina L.) and adjacent to the introduced oyster Crassostrea gigas (Thunberg) in British Columbia, Canada. Hydrobiologia 596, 57–66 (2008).
    Google Scholar 
    Fagherazzi, S. et al. Ecogeomorphology of Salt Marshes. In The Ecogeomorphology of Tidal Marshes (eds Blum, L. K. & Marani, M.) 182–200 (American Geophysical Union, 2004).
    Google Scholar 
    Campbell, A. Vegetation-environment relationships and plant community classification and ordination in British Columbia coastal salt marshes. Master’s Thesis. (University of British Columbia, 1986).Kjerfve, B. Comparative oceanography of coastal lagoons. in Estuarine Variability (ed. Wolfe, D. A.) 63–81 (Academic Press, 1986). https://doi.org/10.1016/B978-0-12-761890-6.50009-5.Barnes, R. S. K. & de Villiers, C. J. Animal abundance and food availability in coastal lagoons and intertidal marine sediments. J. Mar. Biol. Ass. UK 80, 193–202 (2000).
    Google Scholar 
    Saimoto, R. K. Life history of marine stickleback in Oyster Lagoon, British Columbia. Master’s Thesis. (University of British Columbia, 1993).King, R. W. The threespine stickleback adaptive radiation: Salinity, plasticity, and the important of ancestry. Doctoral Dissertation. (Clark University, 2016).Ahnelt, H. Imprecise naming: the anadromous and the sea spawning threespine stickleback should be discriminated by names. Biologia 73, 389–392 (2018).
    Google Scholar 
    Morris, M. R. J., Bowles, E., Allen, B. E., Jamniczky, H. A. & Rogers, S. M. Contemporary ancestor? Adaptive divergence from standing genetic variation in Pacific marine threespine stickleback. BMC Evol. Biol. 18, 113 (2018).PubMed 
    PubMed Central 

    Google Scholar 
    Kim, S.-Y., Costa, M. M., Esteve-Codina, A. & Velando, A. Transcriptional mechanisms underlying life-history responses to climate change in the three-spined stickleback. Evol. Appl. 10, 718–730 (2017).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Sambrook, R. J. Interactions between threespine stickleback (Gasterosteus aculeatus linnæus) and juvenile Chinook salmon (Oncorhynchus tshawytscha Walbaum) in an estuarine marsh. Master’s Thesis. (University of British Columbia, 1990). https://doi.org/10.14288/1.0098704.Jakubavičiūtė, E., Bergström, U., Eklöf, J. S., Haenel, Q. & Bourlat, S. J. DNA metabarcoding reveals diverse diet of the three-spined stickleback in a coastal ecosystem. PLoS ONE 12, e0186929 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Kennedy, G. J. A. & Strange, C. D. The distribution of salmonids in upland streams in relation to depth and gradient. J. Fish Biol. 20, 579–591 (1982).
    Google Scholar 
    Macdonald, J. S., Birtwell, I. K. & Kruzynski, G. M. Food and habitat utilization by juvenile salmonids in the Campbell River estuary. Can. J. Fish. Aquat. Sci. 44, 1233–1246 (1987).
    Google Scholar 
    Everest, F. H. & Chapman, D. W. Habitat selection and spatial interaction by juvenile chinook salmon and steelhead trout in two Idaho streams. J. Fish. Res. Bd. Can. 29, 91–100 (2011).
    Google Scholar 
    McPhail, J. D. Speciation and the evolution of reproductive isolation in the sticklebacks (Gasterosteus) of south-western British Columbia. In The Evolutionary Biology of the Threespine Stickleback (eds Bell, M. A. & Foster, S. A.) 399–471 (Oxford University Press, 1994).
    Google Scholar 
    Kimmel, C. B. et al. Independent axes of genetic variation and parallel evolutionary divergence of opercle bone shape in threespine stickleback. Evolution 66, 419–434 (2012).PubMed 

    Google Scholar 
    Østbye, K. et al. The temporal window of ecological adaptation in postglacial lakes: A comparison of head morphology, trophic position and habitat use in Norwegian threespine stickleback populations. BMC Evol. Biol. 16, 102 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Aguirre, W. E. & Akinpelu, O. Sexual dimorphism of head morphology in three-spined stickleback Gasterosteus aculeatus. J. Fish Biol. 77, 802–821 (2010).CAS 
    PubMed 

    Google Scholar 
    Reimchen, T. E. & Nosil, P. Variable predation regimes predict the evolution of sexual dimorphism in a population of threespine stickleback. Evolution 58, 1274 (2004).CAS 
    PubMed 

    Google Scholar 
    Pistore, A. Ontogeny of population-specific phenotypic variation in the threespine stickleback. Master’s Thesis. (University of Calgary, 2018).Yurtseva, A. O. et al. Aging three-spined sticklebacks Gasterosteus aculeatus: Comparison of estimates from three structures. J. Fish Biol. 95, 802–811 (2019).PubMed 

    Google Scholar 
    Picard, P. Jr., Dodson, J. J. & FitzGerald, G. J. Habitat segregation among the age groups of Gasterosteus aculeatus (Pisces: Gasterosteidae) in the middle St. Lawrence estuary, Canada. Can. J. Zool. 68, 1202–1208 (1990).
    Google Scholar 
    Reimchen, T. E., Bergström, C. A. & Nosil, P. Natural selection and the adaptive radiation of Haida Gwaii stickleback. Evol. Ecol. Res. 15, 241–269 (2013).
    Google Scholar 
    Raeymaekers, J. A. M., Delaire, L. & Hendry, A. P. Genetically based differences in nest characteristics between lake, inlet, and hybrid threespine stickleback from the Misty system, British Columbia, Cananda. Evol. Ecol. Res. 11, 905–919 (2009).
    Google Scholar 
    Di Poi, C., Lacasse, J., Rogers, S. M. & Aubin-Horth, N. Evolution of stress reactivity in stickleback. Evol. Ecol. Res. 17, 395–405 (2016).
    Google Scholar 
    Weber, J. N., Bradburd, G. S., Stuart, Y. E., Stutz, W. E. & Bolnick, D. I. Partitioning the effects of isolation by distance, environment, and physical barriers on genomic divergence between parapatric threespine stickleback. Evolution 71, 342–356 (2017).PubMed 

    Google Scholar 
    Rohlf, F. J. Package: tpsUtil, tps file utility program. Version 1. 61. Department of Ecology and Evolution, State University of New York at Stony Brook, Stony Brook, NY. (2015).Rohlf, F. J. Package: tpsDig, digitize landmarks and outlines. Version 2. 05. Department of Ecology and Evolution, State University of New York at Stony Brook, Stony Brook, NY. (2005).Adams, D. C., Collyer, M. L. & Kaliontzopoupou, A. Geomorph: Software for geometric morphometric analysis (2020).Zelditch, M. L., Swiderski, D. L. & Sheets, H. D. Geometric Morphometrics for Biologists: A Primer (Elsevier Academic Press, 2012).MATH 

    Google Scholar 
    Galipaud, M., Gillingham, M. A. F., David, M. & Dechaume-Moncharmont, F.-X. Ecologists overestimate the importance of predictor variables in model averaging: A plea for cautious interpretations. Methods Ecol. Evol. 5, 983–991 (2014).
    Google Scholar 
    Scheipl, F., Greven, H. & Kuechenhoff, H. Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models. Comput. Stat. Data Anal. 52, 3283–3299 (2008).MathSciNet 
    MATH 

    Google Scholar 
    Robinson, J. James Robinson’s functions. Version 0. 0. 0. 1. Retrieved from https://rdrr.io/github/jpwrobinson/funk/. (2019).Bartoń, K. R Package: MuMIn: Multi-model inference. Version 1. 43. 17. Retrieved from https://CRAN.R-project.org/package=MuMIn. (2020).Frank, A. Diagnosing collinearity in mixed models from lme4 R package, vif.mer function [R script]. Retrieved from https://raw.githubusercontent.com/aufrank/R-hacks/master/mer-utils.R. GitHub https://raw.githubusercontent.com/aufrank/R-hacks/master/mer-utils.R. (2011).Lakens, D. Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Front. Psychol. https://doi.org/10.3389/fpsyg.2013.00863 (2013).PubMed 
    PubMed Central 

    Google Scholar 
    Kilkenny, C., Browne, W. J., Cuthill, I. C., Emerson, M. & Altman, D. G. Improving bioscience research reporting: The ARRIVE guidelines for reporting animal research. PLoS Biol. 8, e1000412 (2010).PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Foundation plant species provide resilience and microclimatic heterogeneity in drylands

    Hantson, S., Huxman, T. E., Kimball, S., Randerson, J. T. & Goulden, M. L. Warming as a driver of vegetation loss in the Sonoran Desert of California. J. Geophys. Res. Biogeosci. 126, e2020JG005942. https://doi.org/10.1029/2020JG005942 (2021).Article 
    ADS 

    Google Scholar 
    Lortie, C. J., Filazzola, A., Kelsey, R., Hart, A. K. & Butterfield, H. S. Better late than never: A synthesis of strategic land retirement and restoration in California. Ecosphere 9, e02367. https://doi.org/10.1002/ecs2.2367 (2018).Article 

    Google Scholar 
    Ye, J.-S., Reynolds, J. F., Sun, G.-J. & Li, F.-M. Impacts of increased variability in precipitation and air temperature on net primary productivity of the Tibetan Plateau: A modeling analysis. Clim. Change 119, 321–332. https://doi.org/10.1007/s10584-013-0719-2 (2013).Article 
    ADS 

    Google Scholar 
    Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C. & Sanderson, B. M. Precipitation variability increases in a warmer climate. Sci. Rep. 7, 17966. https://doi.org/10.1038/s41598-017-17966-y (2017).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Zhang, W. et al. Increasing precipitation variability on daily-to-multiyear time scales in a warmer world. Sci. Adv. 7, eabf8021. https://doi.org/10.1126/sciadv.abf8021 (2021).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Stahle David, W. Anthropogenic megadrought. Science 368, 238–239. https://doi.org/10.1126/science.abb6902 (2020).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Williams, A. P. et al. Large contribution from anthropogenic warming to an emerging North American megadrought. Science 368, 314–318. https://doi.org/10.1126/science.aaz9600 (2020).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Bryant, B. P. et al. Shaping land use change and ecosystem restoration in a water-stressed agricultural landscape to achieve multiple benefits. Front. Sustain. Food Syst. 4, 138 (2020).Article 

    Google Scholar 
    Ross, C. W. et al. Woody-biomass projections and drivers of change in sub-Saharan Africa. Nat. Clim. Chang. 11, 449–455. https://doi.org/10.1038/s41558-021-01034-5 (2021).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Scanlon, B. R., Reedy, R. C., Stonestrom, D. A., Prudic, D. E. & Dennehy, K. F. Impact of land use and land cover change on groundwater recharge and quality in the southwestern US. Glob. Change Biol. 11, 1577–1593. https://doi.org/10.1111/j.1365-2486.2005.01026.x (2005).Article 
    ADS 

    Google Scholar 
    Scanlon, B. R. et al. Global synthesis of groundwater recharge in semiarid and arid regions. Hydrol. Process. 20, 3335–3370. https://doi.org/10.1002/hyp.6335 (2006).Article 
    ADS 
    CAS 

    Google Scholar 
    Kelsey, R., Hart, A., Butterfield, H. S. & Vink, D. Groundwater sustainability in the San Joaquin Valley: Multiple benefits if agricultural lands are retired and restored strategically. Calif. Agric. 2, 151–154 (2018).Article 

    Google Scholar 
    Capdevila, P. et al. Reconciling resilience across ecological systems, species and subdisciplines. J. Ecol. 109, 3102–3113. https://doi.org/10.1111/1365-2745.13775 (2021).Article 

    Google Scholar 
    Thebault, A., Mariotte, P., Lortie, C. & MacDougall, A. Land management trumps the effects of climate change and elevated CO2 on grassland functioning. J. Ecol. 102, 896–904. https://doi.org/10.1111/1365-2745.12236 (2014).Article 

    Google Scholar 
    Turney, C., Ausseil, A.-G. & Broadhurst, L. Urgent need for an integrated policy framework for biodiversity loss and climate change. Nature Ecol. Evol. 4, 996–996. https://doi.org/10.1038/s41559-020-1242-2 (2020).Article 

    Google Scholar 
    Strassburg, B. B. N. et al. Global priority areas for ecosystem restoration. Nature 586, 724–729. https://doi.org/10.1038/s41586-020-2784-9 (2020).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Ellison, A. M. Foundation species, non-trophic interactions, and the value of being common. iScience 13, 254–268. https://doi.org/10.1016/j.isci.2019.02.020 (2019).Article 
    ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    O’Brien, M. J., Carbonell, E. P., Losapio, G., Schlüter, P. M. & Schöb, C. Foundation species promote local adaptation and fine-scale distribution of herbaceous plants. J. Ecol. 109, 191–203. https://doi.org/10.1111/1365-2745.13461 (2021).Article 
    CAS 

    Google Scholar 
    Bagley, J. E. et al. The influence of land cover on surface energy partitioning and evaporative fraction regimes in the U.S. Southern Great Plains. J. Geophys. Res.: Atmos. 122, 5793–5807. https://doi.org/10.1002/2017JD026740 (2017).Article 
    ADS 

    Google Scholar 
    Norris, C., Hobson, P. & Ibisch, P. L. Microclimate and vegetation function as indicators of forest thermodynamic efficiency. J. Appl. Ecol. 49, 562–570. https://doi.org/10.1111/j.1365-2664.2011.02084.x (2012).Article 

    Google Scholar 
    Brooker, R. W. et al. Tiny niches and translocations: The challenge of identifying suitable recipient sites for small and immobile species. J. Appl. Ecol. 55, 621–630. https://doi.org/10.1111/1365-2664.13008 (2018).Article 

    Google Scholar 
    Forzieri, G. et al. Increased control of vegetation on global terrestrial energy fluxes. Nat. Clim. Chang. 10, 356–362. https://doi.org/10.1038/s41558-020-0717-0 (2020).Article 
    ADS 

    Google Scholar 
    Milling, C. R. et al. Habitat structure modifies microclimate: An approach for mapping fine-scale thermal refuge. Methods Ecol. Evol. 9, 1648–1657. https://doi.org/10.1111/2041-210X.13008 (2018).Article 

    Google Scholar 
    Ghazian, N., Zuliani, M. & Lortie, C. J. Micro-climatic amelioration in a california desert: Artificial shelter versus shrub canopy. J. Ecol. Eng. 21, 216–228. https://doi.org/10.12911/22998993/126875 (2020).Article 

    Google Scholar 
    Wright, A. J., Barry, K. E., Lortie, C. J. & Callaway, R. M. Biodiversity and ecosystem functioning: Have our experiments and indices been underestimating the role of facilitation?. J. Ecol. 109, 1962–1968. https://doi.org/10.1111/1365-2745.13665 (2021).Article 

    Google Scholar 
    Germano, D. J. et al. The San Joaquin Desert of California: Ecologically misunderstood and overlooked. Nat. Areas J. 31, 138–147. https://doi.org/10.3375/043.031.0206 (2011).Article 

    Google Scholar 
    Fairbairn, M., LaChance, J., De Master, K. T. & Ashwood, L. In vino veritas, in aqua lucrum: Farmland investment, environmental uncertainty, and groundwater access in California’s Cuyama Valley. Agric. Hum. Values 38, 285–299. https://doi.org/10.1007/s10460-020-10157-y (2021).Article 

    Google Scholar 
    Filazzola, A., Lortie, C. J., Westphal, M. F. & Michalet, R. Species-specificity challenges the predictability of facilitation along a regional desert gradient. J. Veg. Sci. 1, 1–12. https://doi.org/10.1111/jvs.12909 (2020).Article 

    Google Scholar 
    Cutlar, H. C. Monograph of the North American species of the genus Ephedra. Ann. Mo. Bot. Gard. 26, 373–428 (1939).Article 

    Google Scholar 
    Hollander, J. L., Wall, S. B. V. & Baguley, J. G. Evolution of seed dispersal in North American Ephedra. Evol. Ecol. 24, 333–345. https://doi.org/10.1007/s10682-009-9309-1 (2010).Article 

    Google Scholar 
    Filazzola, A., Brown, C., Westphal, M. & Lortie, C. J. Establishment of a desert foundation species is limited by exotic plants and light but not herbivory or water. Appl. Veg. Sci. 1, 1–12. https://doi.org/10.1111/avsc.12515 (2020).Article 

    Google Scholar 
    Lortie, C. J., Gruber, E., Filazzola, A., Noble, T. & Westphal, M. The Groot effect: Plant facilitation and desert shrub regrowth following extensive damage. Ecol. Evol. 8, 706–715. https://doi.org/10.1002/ece3.3671 (2018).Article 
    PubMed 

    Google Scholar 
    Lortie, C. J. et al. Telemetry of the lizard species Gambelia sila at Carrizo plain national monument. Figshare. Dataset. https://doi.org/10.6084/m9.figshare.8239667.v2 (2019).Article 

    Google Scholar 
    Braun, J., Westphal, M. & Lortie, C. J. The shrub Ephedra californica facilitates arthropod communities along a regional desert climatic gradient. Ecosphere 12, e03760. https://doi.org/10.1002/ecs2.3760 (2021).Article 

    Google Scholar 
    Terando, A., Youngsteadt, E., Meineke, E. & Prado, S. Accurate near surface air temperature measurements are necessary to gauge large-scale ecological responses to global climate change. Ecol. Evol. 8, 5233–5234. https://doi.org/10.1002/ece3.3972 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tielborger, K. & Kadmon, R. Indirect effects in a desert plant community: Is competition among annuals more intense under shrub canopies?. Plant Ecol. 150, 53–63 (2000).Article 

    Google Scholar 
    Holzapfel, C., Tielbörger, K., Parag, H. A., Kigel, J. & Sternberg, M. Annual plant–shrub interactions along an aridity gradient. Basic Appl. Ecol. 7, 268–279. https://doi.org/10.1016/j.baae.2005.08.003 (2006).Article 

    Google Scholar 
    Jankju, M. Role of nurse shrubs in restoration of an arid rangeland: Effects of microclimate on grass establishment. J. Arid Environ. 89, 103–109. https://doi.org/10.1016/j.jaridenv.2012.09.008 (2013).Article 
    ADS 

    Google Scholar 
    Baldelomar, M., Atala, C. & Molina-Montenegro, M. A. Top-down and Bottom-up effects deployed by a nurse shrub allow facilitating an endemic mediterranean orchid. Front. Ecol. Evol. 7, 466 (2019).Article 

    Google Scholar 
    Tielborger, K. & Kadmon, R. Temporal environmental variation tips the balance between facilitation and interference in desert plants. Ecology 81, 1544–1553. https://doi.org/10.1890/0012-9658(2000)081[1544:TEVTTB]2.0.CO;2 (2000).Article 

    Google Scholar 
    Walter, J. Effects of changes in soil moisture and precipitation patterns on plant-mediated biotic interactions in terrestrial ecosystems. Plant Ecol. https://doi.org/10.1007/s11258-018-0893-4 (2018).Article 

    Google Scholar 
    Schob, C., Armas, C. & Pugnaire, F. Direct and indirect interactions co-determine species composition in nurse plant systems. Oikos 122, 1371–1379. https://doi.org/10.1111/j.1600-0706.2013.00390.x (2013).Article 

    Google Scholar 
    Eldridge, D. J., Beecham, G. & Grace, J. B. Do shrubs reduce the adverse effects of grazing on soil properties?. Ecohydrology 8, 1503–1513. https://doi.org/10.1002/eco.1600 (2015).Article 

    Google Scholar 
    Nerlekar, A. N. & Veldman, J. W. High plant diversity and slow assembly of old-growth grasslands. Proc. Natl. Acad. Sci. 117, 18550. https://doi.org/10.1073/pnas.1922266117 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tielbörger, K. et al. Middle-Eastern plant communities tolerate 9 years of drought in a multi-site climate manipulation experiment. Nat. Commun. 5, 5102. https://doi.org/10.1038/ncomms6102 (2014).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Griffin, D. & Anchukaitis, K. J. How unusual is the 2012–2014 California drought?. Geophys. Res. Lett. 41, 9017–9023. https://doi.org/10.1002/2014GL062433 (2014).Article 
    ADS 

    Google Scholar 
    Data, U. C. In US Climate Data Product, New Cuyama, vol. 1. https://www.usclimatedata.com (2021).Gherardi, L. A. & Sala, O. E. Effect of interannual precipitation variability on dryland productivity: A global synthesis. Glob. Change Biol. 25, 269–276. https://doi.org/10.1111/gcb.14480 (2019).Article 
    ADS 

    Google Scholar 
    Ding, Y., Li, Z. & Peng, S. Global analysis of time-lag and -accumulation effects of climate on vegetation growth. Int. J. Appl. Earth Obs. Geoinf. 92, 102179. https://doi.org/10.1016/j.jag.2020.102179 (2020).Article 

    Google Scholar 
    Liu, H. et al. Analysis of the time-lag effects of climate factors on grassland productivity in Inner Mongolia. Glob. Ecol. Conserv. 30, e01751. https://doi.org/10.1016/j.gecco.2021.e01751 (2021).Article 

    Google Scholar 
    Liancourt, P., Song, X., Macek, M., Santrucek, J. & Dolezal, J. Plant’s-eye view of temperature governs elevational distributions. Glob. Change Biol. 26, 4094–4103. https://doi.org/10.1111/gcb.15129 (2020).Article 
    ADS 

    Google Scholar 
    Ryan, M. J. et al. Too dry for lizards: Short-term rainfall influence on lizard microhabitat use in an experimental rainfall manipulation within a pinon-juniper woodland. Funct. Ecol. https://doi.org/10.1111/1365-2435.12595 (2015).Article 

    Google Scholar 
    Moore, D., Stow, A. & Kearney, M. R. Under the weather?—The direct effects of climate warming on a threatened desert lizard are mediated by their activity phase and burrow system. J. Anim. Ecol. 87, 660–671. https://doi.org/10.1111/1365-2656.12812 (2018).Article 
    PubMed 

    Google Scholar 
    Gaudenti, N., Nix, E., Maier, P., Westphal, M. F. & Taylor, E. N. Habitat heterogeneity affects the thermal ecology of an endangered lizard. Ecol. Evol. 11, 14843–14856. https://doi.org/10.1002/ece3.8170 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Lortie, C. J., Filazzola, A. & Sotomayor, D. A. Functional assessment of animal interactions with shrub-facilitation complexes: A formal synthesis and conceptual framework. Funct. Ecol. 30, 41–51. https://doi.org/10.1111/1365-2435.12530 (2016).Article 

    Google Scholar 
    Lortie, C. J. et al. Shrub and vegetation cover predict resource selection use by an endangered species of desert lizard. Sci. Rep. 10, 4884. https://doi.org/10.1038/s41598-020-61880-9 (2020).Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    De Frenne, P. et al. Global buffering of temperatures under forest canopies. Nature Ecol. Evol. 3, 744–749. https://doi.org/10.1038/s41559-019-0842-1 (2019).Article 

    Google Scholar 
    Avolio, M. L. et al. Determinants of community compositional change are equally affected by global change. Ecol. Lett. 24, 1892–1904. https://doi.org/10.1111/ele.13824 (2021).Article 
    PubMed 

    Google Scholar 
    Cook-Patton, S. C. et al. Protect, manage and then restore lands for climate mitigation. Nat. Clim. Chang. 11, 1027–1034. https://doi.org/10.1038/s41558-021-01198-0 (2021).Article 
    ADS 

    Google Scholar 
    Hedden-Nicely, D. R. Climate change and the future of western US water governance. Nat. Clim. Chang. https://doi.org/10.1038/s41558-021-01141-3 (2021).Article 

    Google Scholar 
    Suggitt, A. J. et al. Extinction risk from climate change is reduced by microclimatic buffering. Nat. Clim. Chang. 8, 713–717. https://doi.org/10.1038/s41558-018-0231-9 (2018).Article 
    ADS 

    Google Scholar 
    Hanson, R. T., Flint, L. E., Faunt, C. C., Gibbs, D. R. & Schmid, W. Hydrologic models and analysis of water availability in Cuyama Valley, California. In U.S. Geological Survey Scientific Investigations Report, 2015 1–126 (2015).John, S. In Encyclopedia of World Climatology (ed John, E. O.) 89–94 (Springer Netherlands, 2005).James-Jeremy, J. et al. A systems approach to restoring degraded drylands. J. Appl. Ecol. 50, 730–739. https://doi.org/10.1111/1365-2664.12090 (2013).Article 

    Google Scholar 
    Upson, J. E. & Worts, G. F. In Ground water in the Cuyama Valley, California. Report No. 1110B 1–82 (1951).Hanson, M. T., Randall, T. & Sweetkind, D. Cuyama Valley, California hydrologic study—an assessment of water availability. In U.S. Geological Survey Scientific Investigations Report 2014 1–4. https://doi.org/10.3133/fs20143075 (2014).Greicius, T. NASA data show California’s San Joaquin Valley Still Sinking. JPL 28, 1–9 (2017).
    Google Scholar 
    Döll, P. et al. Impact of water withdrawals from groundwater and surface water on continental water storage variations. J. Geodyn. 59–60, 143–156. https://doi.org/10.1016/j.jog.2011.05.001 (2012).Article 

    Google Scholar 
    Lortie, C. J. & Filazzola, A. US climate data, New Cuyama, CA, 2016–2017. Figshare 1, 2016–2017. https://doi.org/10.6084/m9.figshare.17162600.v1 (2021).Article 

    Google Scholar 
    Lortie, C. J. & Filazzola, A. Vegetation surveys in Cuyama Valley, CA, USA in 2016 and 2017 at the peak of megadrought. Knowl. Netw. Biocompl. 1, 1–15. https://doi.org/10.5063/F1MG7MZH (2021).Article 

    Google Scholar 
    Hickman, J. C. The Jepson Manual (University of California Press, 1996).
    Google Scholar 
    Villanueva-Almanza, L. & Fonseca, R. M. In Taxonomic review and geographic distribution of Ephedra (Ephedraceae) in Mexico. ACTA BOTANICA MEXICANA 96 (2011).Alfieri, F. J. & Mottola, P. M. Seasonal changes in the phloem of Ephedra californica Wats. Bot. Gaz. 144, 240–246 (1983).Article 

    Google Scholar 
    Hoffman, O., de-Falco, N., Yizhaq, H. & Boeken, B. Annual plant diversity decreases across scales following widespread ecosystem engineer shrub mortality. J. Veg. Sci. https://doi.org/10.1111/jvs.12372 (2016).Article 

    Google Scholar 
    Ivey, K. N. et al. Thermal ecology of the federally endangered blunt-nosed leopard lizard (Gambelia sila). Conserv. Physiol. 2020, 8. https://doi.org/10.1093/conphys/coaa014 (2020).Article 

    Google Scholar 
    Grimes, A. J., Corrigan, G., Germano, D. J. & Smith, P. T. Mitochondrial phylogeography of the endangered blunt-nosed leopard lizard, Gambelia sila. Southwestern Natural. 59, 38–46. https://doi.org/10.1894/F06-GC-233.1 (2014).Article 

    Google Scholar 
    Stewart, J. A. E. et al. Habitat restoration opportunities, climatic niche contraction, and conservation biogeography in California’s San Joaquin Desert. PLoS ONE 14, e0210766. https://doi.org/10.1371/journal.pone.0210766 (2019).Article 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Germano, D. J., Rathbun, G. B. & Saslaw, L. R. Effects of grazing and invasive grasses on desert vertebrates in California. J. Wildl. Manag. 76, 670–682. https://doi.org/10.1002/jwmg.316 (2012).Article 

    Google Scholar 
    Moss, B. The water framework directive: Total environment or political compromise?. Sci. Total Environ. 400, 32–41. https://doi.org/10.1016/j.scitotenv.2008.04.029 (2008).Article 
    ADS 
    CAS 
    PubMed 

    Google Scholar 
    Denevan, W. M. The “Pristine Myth ” revisited. Geogr. Rev. 101, 576–591. https://doi.org/10.1111/j.1931-0846.2011.00118.x (2011).Article 

    Google Scholar 
    da Cunha, A. R. Evaluation of measurement errors of temperature and relative humidity from HOBO data logger under different conditions of exposure to solar radiation. Environ. Monit. Assess. 187, 236. https://doi.org/10.1007/s10661-015-4458-x (2015).Article 
    PubMed 

    Google Scholar 
    Terando, A. J., Youngsteadt, E., Meineke, E. K. & Prado, S. G. Ad hoc instrumentation methods in ecological studies produce highly biased temperature measurements. Ecol. Evol. 7, 9890–9904. https://doi.org/10.1002/ece3.3499 (2017).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Nature, I. I. U. f. C. o. The IUCN red list of threatened species. IUCN 2019-1 1–142 (2019).Lortie, C. J., Filazzola, A., Butterfield, H. S. & Westphal, M. Cuyama Micronet. Figshare 1, 1–6. https://doi.org/10.6084/m9.figshare.11888199.v2 (2020).Article 

    Google Scholar 
    Team, R. C. R: A Language and Environment for Statistical Computing. Vol. 4.2.1 (R foundation for Statistical Computing, 2022).Pinheiro, J., Bates, D., DebRoy, S. & Deepayan, S. nlme: Linear and nonlinear mixed effects models. CRAN 3, 1–153 (2021).
    Google Scholar 
    Pebesma, E. spacetime: Spatio-temporal data in R. J. Stat. Softw. 1(7), 2012. https://doi.org/10.18637/jss.v051.i07 (2012).Article 

    Google Scholar 
    Bates, D. et al. lme4: Linear mixed-effects models using “Eigen” and S4. CRAN 2020, 1–122 (2020).
    Google Scholar 
    Lenth, R. V. emmeans: Estimated marginal means. CRAN 1, 1–89 (2022).
    Google Scholar  More