More stories

  • 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

  • in

    Thermal acclimation and metabolic scaling of a groundwater asellid in the climate change scenario

    Li, J. & Thompson, D. W. Widespread changes in surface temperature persistence under climate change. Nature 599(7885), 425–430. https://doi.org/10.1038/s41586-021-03943-z (2021).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Raftery, A. E., Zimmer, A., Frierson, D. M., Startz, R. & Liu, P. Less than 2 °C warming by 2100 unlikely. Nat. Clim. Change 7, 637–641 (2017).ADS 
    CAS 

    Google Scholar 
    Olabi, A. G. et al. Assessment of the pre-combustion carbon capture contribution into sustainable development goals SDGs using novel indicators. Renew. Sustain. Energy Rev. 153, 111710. https://doi.org/10.1016/j.rser.2021.111710 (2022).CAS 

    Google Scholar 
    Badino, G. Cave temperatures and global climatic change. Int. J. Speleol. 33(1), 103–114 (2004).
    Google Scholar 
    Wang, J. et al. Recent global decline in endorheic basin water storages. Nat. Geosci. 11(12), 926–932 (2018).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Figura, S., Livingstone, D. M., Hoehn, E. & Kipfer, R. Regime shift in groundwater temperature triggered by the Arctic Oscillation. Geophys. Res. Lett. 38(23), 401–405 (2011).
    Google Scholar 
    Mueller, M. H., Huggenberger, P. & Epting, J. Combining monitoring and modelling tools as a basis for city-scale concepts for a sustainable thermal management of urban groundwater resources. Sci. Total Environ. 627, 1121–1136 (2018).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Taylor, C. A. & Stefan, H. G. Shallow groundwater temperature response to climate change and urbanization. J. Hydrol. 375, 601–612 (2009).ADS 
    CAS 

    Google Scholar 
    Dehghani, R., Poudeh, H. T. & Izadi, Z. The effect of climate change on groundwater level and its prediction using modern meta-heuristic model. Ground. Sustain. Dev. 16, 100702. https://doi.org/10.1016/j.gsd.2021.100702 (2022).
    Google Scholar 
    Lenton, T. M. et al. Climate tipping points—Too risky to bet against. Nature 57, 592–595 (2019).ADS 

    Google Scholar 
    Albert, J. S. et al. Scientists’ warning to humanity on the freshwater biodiversity crisis. Ambio 50(1), 85–94 (2021).PubMed 

    Google Scholar 
    Stein, H. et al. Stygoregions—A promising approach to a bioregional classification of groundwater systems. Sci. Rep. 2, 673. https://doi.org/10.1038/srep00673 (2012).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Baković, N., Matoničkin Kepčija, R. & Siemensma, F. J. Transitional and small aquatic cave habitats diversification based on protist assemblages in the Veternica cave (Medvednica Mt., Croatia). Subterr. Biol. 42, 43–60 (2022).
    Google Scholar 
    Magnabosco, C. et al. The biomass and biodiversity of the continental subsurface. Nat. Geosci. 11(10), 707–717 (2018).ADS 
    CAS 

    Google Scholar 
    Chen, Z. et al. The World Karst Aquifer Mapping project: Concept, mapping procedure and map of Europe. Hydrogeol. J. 25, 771–785 (2017).ADS 

    Google Scholar 
    Eme, D. et al. Do cryptic species matter in macroecology? Sequencing European groundwater crustaceans yields smaller ranges but does not challenge biodiversity determinants. Ecography 41(2), 424–436 (2018).
    Google Scholar 
    Manenti, R. et al. The stenoendemic cave-dwelling planarians (Platyhelminthes, Tricladida) of the Italian Alps and Apennines: conservation issues. J. Nat. Conserv. 45, 90–97 (2018).
    Google Scholar 
    Zagmajster, M., Malard, F., Eme, D. & Culver, D. C. Subterranean biodiversity patterns from global to regional scales. In Cave Ecology, Ecological Studies—Analysis and Synthesis (eds Moldovan, O. et al.) 19–227 (Springer, 2018).
    Google Scholar 
    Hose, G. C. et al. Invertebrate traits, diversity and the vulnerability of groundwater ecosystems. Funct. Ecol. 36, 2200. https://doi.org/10.1111/1365-2435.14125 (2022).CAS 

    Google Scholar 
    Angilletta, M. J. Jr. & Angilletta, M. J. Thermal Adaptation: A Theoretical and Empirical Synthesis (Oxford University Press, 2009).
    Google Scholar 
    Pallarées, S. et al. Loss of heat acclimation capacity could leave subterranean specialists highly sensitive to climate change. Anim. Conserv. 24(3), 482–490 (2020).
    Google Scholar 
    Vasseur, D. A. et al. Increased temperature variation poses a greater risk to species than climate warming. Proc. R. Soc. B 281, 20132612. https://doi.org/10.1098/rspb.2013.2612 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Castaño-Sánchez, A., Hose, G. C. & Reboleira, A. S. P. Ecotoxicological effects of anthropogenic stressors in subterranean organisms: A review. Chemosphere 244, 125422. https://doi.org/10.1016/j.chemosphere.2019.125422 (2020).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Castaño-Sánchez, A., Hose, G. C. & Reboleira, A. S. P. Salinity and temperature increase impact groundwater crustaceans. Sci. Rep. 10(1), 1–9 (2020).
    Google Scholar 
    Issartel, J., Hervant, F., Voituron, Y., Renault, D. & Vernon, P. Behavioural, ventilatory and respiratory responses of epigean and hypogean crustaceans to different temperatures. Comp. Biochem. Physiol. Mol. Amp Integr. Physiol. 141, 1–7 (2005).
    Google Scholar 
    Issartel, J., Voituron, Y. & Hervant, F. Impact of temperature on the survival, the activity and the metabolism of the cave-dwelling Niphargus virei, the ubiquitous stygobiotic N. rhenorhodanensis and the surface-dwelling Gammarus fossarum (Crustacea, Amphipoda). Subterr. Biol. 5, 9–14 (2007).
    Google Scholar 
    Mermillod-Blondin, F. et al. Thermal tolerance breadths among groundwater crustaceans living in a thermally constant environment. J. Exp. Biol. 216, 1683–1694 (2013).CAS 
    PubMed 

    Google Scholar 
    Di Lorenzo, T. et al. Metabolic rates of a hypogean and an epigean species of copepod in an alluvial aquifer. Freshw. Biol. 60, 426–435 (2015).
    Google Scholar 
    Di Lorenzo, T. & Galassi, D. M. P. Effect of temperature rising on the stygobitic crustacean species Diacyclops belgicus: Does global warming affect groundwater populations? Water 9, 951. https://doi.org/10.3390/w9120951 (2017).ADS 
    CAS 

    Google Scholar 
    Mammola, S. et al. Climate change going deep: The effects of global climatic alterations on cave ecosystems. Anthr. Rev. 6(1–2), 98–116 (2019).
    Google Scholar 
    Jones, K. et al. The critical thermal maximum of diving beetles (Coleoptera: Dytiscidae): A comparison of subterranean and surface-dwelling species. Curr. Opin. Insect. Sci. 1, 100019 (2021).
    Google Scholar 
    Pörtner, H. O. Physiological basis of temperature-dependent biogeography: Trade-offs in muscle design and performance in polar ectotherms. J. Exp. Biol. 205, 2217–2230 (2022).
    Google Scholar 
    Clarke, A. & Fraser, K. P. P. Why does metabolism scale with temperature? Funct. Ecol. 18, 243–251 (2004).
    Google Scholar 
    Dell, A. I., Pawar, S. & Savage, V. M. Systematic variation in the temperature dependence of physiological and ecological traits. Proc. Natl. Acad. Sci. 108, 10591–10596 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Willmer, P., Stone, G. & Johnston, I. Environmental Physiology of Animals (Wiley, 2009).
    Google Scholar 
    Gillooly, J. F., Brown, J. H., West, G. B., Savage, V. M. & Charnov, E. L. Effects of size and temperature on metabolic rate. Science 293, 2248–2251 (2001).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Gillooly, J. F., Charnov, E. L., West, G. B., Savage, V. M. & Brown, J. H. Effects of size and temperature on developmental time. Nature 417, 70–73 (2002).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Hervant, F., Mathieu, J., Barré, H., Simon, K. & Pinon, C. Comparative study on the behavioural, ventilatory, and respiratory responses of hypogean and epigean crustaceans to long-term starvation and subsequent feeding. Comp. Biochem. Physiol. B 118A, 1277–1283 (1997).CAS 

    Google Scholar 
    Wilhelm, F. M., Taylor, S. J. & Adams, G. L. Comparison of routine metabolic rates of the stygobite, Gammarus acherondytes (Amphipoda: Gammaridae) and the stygophile, Gammarus troglophilus. Freshwat. Biol. 51, 1162–1174 (2006).
    Google Scholar 
    Reboleira, A. S. P. S., Borges, P., Gonçalves, F., Serrano, A. R. M. & Oromí, P. The subterranean fauna of a biodiversity hotspot region—Portugal: An overview and its conservation. Int. J. Speleol. 40(1), 23–37 (2011).
    Google Scholar 
    Reboleira, A. S. P. S., Abrantes, N., Oromí, P. & Gonçalves, F. J. M. Acute toxicity of copper sulfate and potassium dichromate on stygobiont Proasellus: General aspects of groundwater ecotoxicology and future perspectives. Water Air Soil Pollut. 224, 1550. https://doi.org/10.1007/s11270-013-1550-0 (2013).ADS 
    CAS 

    Google Scholar 
    Morvan, C. et al. Timetree of Aselloidea reveals species diversification dynamics in groundwater. Syst. Biol. 62(4), 512–522 (2013).CAS 
    PubMed 

    Google Scholar 
    Castaño-Sánchez, A., Malard, F., Kalčikova, G. & Reboleira, A. S. P. S. Novel protocol for acute in situ ecotoxicity test using native crustaceans applied to groundwater ecosystems. Water 13(8), 1132. https://doi.org/10.3390/w13081132 (2021).CAS 

    Google Scholar 
    Di Lorenzo, T. et al. Recommendations for ecotoxicity testing with stygobiotic species in the framework of groundwater environmental risk assessment. Sci. Total Environ. 681(1), 292–304 (2019).ADS 
    MathSciNet 
    PubMed 

    Google Scholar 
    Rezende, E. L., Tejedo, M. & Santos, M. Estimating the adaptative potential of critical thermal limits: Methodological problems and evolutionary implications. Funct. Ecol. 25, 111–121 (2011).
    Google Scholar 
    Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9(7), 671–675 (2012).CAS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
    Google Scholar 
    Harvey, P. H. & Pagel, M. D. The Comparative Method in Evolutionary Biology (Oxford University Press, 1991).
    Google Scholar 
    Dodds, P. S., Rothman, D. H. & Weitz, J. S. Re-examination of the “3/4” law of metabolism. J. Theor. Biol. 209, 9–27 (2001).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Manly, B. F. J. Randomization, Bootstrap and Monte Carlo Methods in Biology (Chapman & Hall/CRC Press, 2006).MATH 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. https://www.R-project.org/ (R Foundation for Statistical Computing, Vienna, Austria, 2018).Simčič, T. & Sket, B. Comparison of some epigean and troglobiotic animals regarding their metabolism intensity. Examination of a classical assertion. Int. J. Speleol. 48, 133–144 (2019).
    Google Scholar 
    Hazell, S. P., Pedersen, B. P., Worland, M. R., Blackburn, T. M. & Bale, J. S. A method for the rapid measurement of thermal tolerance traits in studies of small insects. Physiol. Entomol. 33(4), 389–394 (2008).
    Google Scholar 
    Cohen, J. M., Lajeunesse, M. J. & Rohr, J. R. A global synthesis of animal phenological responses to climate change. Nat. Clim. Change 8, 224. https://doi.org/10.1038/s41558-018-0067-3 (2018).ADS 

    Google Scholar 
    Ficetola, G. F., Lunghi, E. & Manenti, R. Microhabitat analyses support relationships between niche breadth and range size when spatial autocorrelation is strong. Ecography 43(5), 724–734 (2020).
    Google Scholar 
    Sánchez-Fernández, D., Rizzo, V. & Bourdeau, C. The deep subterranean environment as a model system in ecological, biogeographical and evolutionary research. Subterr. Biol. 25, 1–7 (2018).
    Google Scholar 
    Pallarés, S. et al. Loss of heat acclimation capacity could leave subterranean specialists highly sensitive to climate change. Anim. Conserv. 24(3), 482–490 (2021).MathSciNet 

    Google Scholar 
    Griebler, C. & Avramov, M. Groundwater ecosystem services: A review. Freshw. Sci. 34(1), 355–367 (2015).
    Google Scholar 
    Saccò, M. et al. Stygofaunal diversity and ecological sustainability of coastal groundwater ecosystems in a changing climate: The Australian paradigm. Freshw. Biol. https://doi.org/10.1111/fwb.13987 (2022).
    Google Scholar 
    Ikeda, T., Kanno, Y., Ozaki, K. & Shinada, A. Metabolic rates of epipelagic marine copepods as a function of body mass and temperature. Mar. Biol. 139, 587–596 (2001).
    Google Scholar 
    Mezek, T., Simčič, T., Arts, M. T. & Brancelj, A. Effect of fasting on hypogean (Niphargus stygius) and epigean (Gammarus fossarum) amphipods: A laboratory study. Aquat. Ecol. 44(2), 397–408 (2010).CAS 

    Google Scholar 
    Hüppop, K. The role of metabolism in the evolution of cave animals. NSS Bulletin 47, 136–146 (1985).
    Google Scholar 
    Humphreys, W. F. Hydrogeology and groundwater ecology: Does each inform the other? Hydrogeol. J. 17(1), 5–21 (2009).ADS 
    CAS 

    Google Scholar 
    Glazier, D. S. The 3/4-power law is not universal: Evolution of isometric, ontogenetic metabolic scaling in pelagic animals. Bioscience 56(4), 325–332 (2006).
    Google Scholar 
    Sánchez-Fernández, D., Galassi, D. M. P., Wynne, J. J., Cardoso, P. & Mammola, S. Don’t forget subterranean ecosystems in climate change agendas. Nat. Clim. Change 11, 458–459 (2021).ADS 

    Google Scholar 
    Reboleira, A. S. P. S. et al. Nutrient-limited subarctic caves harbour more diverse and complex bacterial communities than their surface soil. Environ. Microbiome 17, 41 (2022).PubMed 
    PubMed Central 

    Google Scholar  More

  • in

    Dark plumes of glacial meltwater affect vertical distribution of zooplankton in the Arctic

    Meredith, M. et al. Polar regions. in IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (Pörtner, H.‐O. et al. Eds.). 203–320 (2019).Nummelin, A., Ilicak, M., Li, C. & Smedsrud, L. H. Consequences of future increased Arctic runoff on Arctic Ocean stratification, circulation, and sea ice cover. J. Geophys. Res. Oceans 121, 617–637 (2016).ADS 

    Google Scholar 
    Smedsrud, L. H., Sorteberg, A. & Kloster, K. Recent and future changes of the Arctic sea-ice cover. Geophys. Res. Lett. 35, L20503 (2008).ADS 

    Google Scholar 
    Ardyna, M. & Arrigo, K. R. Phytoplankton dynamics in a changing Arctic Ocean. Nat. Clim. Change 10, 892–903. https://doi.org/10.1038/s41558-020-0905-y (2020).Article 
    ADS 
    CAS 

    Google Scholar 
    Tripathy, S. C. et al. Summer variability in bio-optical properties and phytoplankton pigment signatures in two adjacent high Arctic fjords, Svalbard. Int. J. Environ. Sci. Technol. https://doi.org/10.1007/s13762-021-03767-4 (2021).Article 

    Google Scholar 
    Sagan, S. & Darecki, M. Inherent optical properties and particulate matter distribution in summer season in waters of Hornsund and Kongsfjordenen, Spitsbergen. Oceanologia 60, 65–75 (2018).
    Google Scholar 
    Mouginot, J. et al. Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018. in Proceedings of the National Academy of Sciences of the United States of America. Vol. 116. 9239–9244. Preprint at https://doi.org/10.1073/pnas.1904242116 (2019).Rignot, E., Jacobs, S., Mouginot, J. & Scheuchl, B. Ice-shelf melting around antarctica. Science 1979(341), 266–270 (2013).ADS 

    Google Scholar 
    Konik, M., Darecki, M., Pavlov, A. K., Sagan, S. & Kowalczuk, P. Darkening of the Svalbard Fjords waters observed with satellite ocean color imagery in 1997–2019. Front. Mar. Sci. 8, 27 (2021).
    Google Scholar 
    IPCC. Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. (2022).Szeligowska, M. et al. The interplay between plankton and particles in the Isfjorden waters influenced by marine- and land-terminating glaciers. Sci. Total Environ. 780, 146491 (2021).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Trudnowska, E., Dąbrowska, A. M., Boehnke, R., Zajączkowski, M. & Blachowiak-Samolyk, K. Particles, protists, and zooplankton in glacier-influenced coastal svalbard waters. Estuar. Coast Shelf Sci. 242, 106842 (2020).
    Google Scholar 
    Maekakuchi, M., Matsuno, K., Yamamoto, J., Abe, Y. & Yamaguchi, A. Abundance, horizontal and vertical distribution of epipelagic ctenophores and scyphomedusae in the northern Bering Sea in summer 2017 and 2018: Quantification by underwater video imaging analysis. Deep Sea Res. 2 Top. Stud. Oceanogr. 181–182, 104818 (2020).
    Google Scholar 
    Norrbin, F., Eilertsen, H. C. & Degerlund, M. Vertical distribution of primary producers and zooplankton grazers during different phases of the Arctic spring bloom. Deep Sea Res. 2 Top. Stud. Oceanogr. 56, 1945–1958 (2009).
    Google Scholar 
    Stemmann, L. et al. Vertical distribution (0–1000 m) of macrozooplankton, estimated using the Underwater Video Profiler, in different hydrographic regimes along the northern portion of the Mid-Atlantic Ridge. Deep Sea Res. 2 Top. Stud. Oceanogr. 55, 94–105 (2008).
    Google Scholar 
    Arendt, K. E. et al. Effects of suspended sediments on copepods feeding in a glacial influenced sub-Arctic fjord. J. Plankton Res. 33, 1526–1537 (2011).CAS 

    Google Scholar 
    Arimitsu, M., Piatt, J. & Mueter, F. Influence of glacier runoff on ecosystem structure in Gulf of Alaska fjords. Mar. Ecol. Prog. Ser. 560, 19–40 (2016).ADS 

    Google Scholar 
    Renner, M., Arimitsu, M. L. & Piatt, J. F. Structure of marine predator and prey communities along environmental gradients in a glaciated fjord. Can. J. Fish. Aquat. Sci. 69, 2029–2045 (2012).
    Google Scholar 
    Lydersen, C. et al. The importance of tidewater glaciers for marine mammals and seabirds in Svalbard, Norway. J. Mar. Syst. 129, 452–471. https://doi.org/10.1016/j.jmarsys.2013.09.006 (2014).Article 

    Google Scholar 
    Falk-Petersen, S., Pavlov, V., Timofeev, S. & Sargent, J. R. Climate variability and possible effects on arctic food chains: The role of Calanus. in Arctic Alpine Ecosystems and People in a Changing Environment. 147–166. https://doi.org/10.1007/978-3-540-48514-8_9 (Springer, 2007).Stempniewicz, L. et al. Visual prey availability and distribution of foraging little auks (Alle alle) in the shelf waters of West Spitsbergen. Polar Biol. 36, 949–955 (2013).
    Google Scholar 
    CAFF. Arctic Coastal Biodiversity Monitoring Plan (CAFF Monitoring Series Report No. 29). (2019).Arendt, K. E., Nielsen, T. G., Rysgaard, S. & Tönnesson, K. Differences in plankton community structure along the Godthåbsfjord, from the Greenland Ice Sheet to offshore waters. Mar. Ecol. Prog. Ser. 401, 49–62 (2010).ADS 
    CAS 

    Google Scholar 
    Blachowiak-Samolyk, K. et al. Arctic zooplankton do not perform diel vertical migration (DVM) during periods of midnight sun. Mar. Ecol. Prog. Ser. 308, 101–116 (2006).ADS 

    Google Scholar 
    Cottier, F. R., Tarling, G. A., Wold, A. & Falk-Petersen, S. Unsynchronized and synchronized vertical migration of zooplankton in a high arctic fjord. Limnol. Oceanogr. 51, 2586–2599 (2006).ADS 

    Google Scholar 
    Hobbs, L. et al. A marine zooplankton community vertically structured by light across diel to interannual timescales. Biol Lett 17, 20200810 (2021).PubMed 
    PubMed Central 

    Google Scholar 
    Wallace, M. I. et al. Comparison of zooplankton vertical migration in an ice-free and a seasonally ice-covered Arctic fjord: An insight into the influence of sea ice cover on zooplankton behavior. Limnol. Oceanogr. 55, 831–845 (2010).ADS 

    Google Scholar 
    Bandara, K. et al. Seasonal vertical strategies in a high-Arctic coastal zooplankton community. Mar. Ecol. Prog. Ser. 555, 49–64 (2016).ADS 

    Google Scholar 
    Rabindranath, A. et al. Seasonal and diel vertical migration of zooplankton in the High Arctic during the autumn midnight sun of 2008. Mar. Biodivers. 41, 365–382 (2011).
    Google Scholar 
    Piwosz, K. et al. Comparison of productivity and phytoplankton in a warm (Kongsfjorden) and a cold (Hornsund) Spitsbergen fjord in mid-summer 2002. Polar Biol. 32, 549–559 (2009).
    Google Scholar 
    Frank, T. M. & Widder, E. A. Effects of a decrease in downwelling irradiance on the daytime vertical distribution patterns of zooplankton and micronekton. Mar. Biol. 140, 1181–1193 (2002).
    Google Scholar 
    Ortega, J. C. G., Figueiredo, B. R. S., da Graça, W. J., Agostinho, A. A. & Bini, L. M. Negative effect of turbidity on prey capture for both visual and non-visual aquatic predators. J. Anim. Ecol. 89, 2427–2439. https://doi.org/10.1111/1365-2656.13329 (2020).Article 
    PubMed 

    Google Scholar 
    Aksnes, D. et al. Coastal water darkening and implications for mesopelagic regime shifts in Norwegian fjords. Mar. Ecol. Prog. Ser. 387, 39–49 (2009).ADS 
    CAS 

    Google Scholar 
    Urbanski, J. A. et al. Subglacial discharges create fluctuating foraging hotspots for sea birds in tidewater glacier bays. Sci. Rep. 7, 1–12 (2017).
    Google Scholar 
    Weslawski, J. M., Pedersen, G., Petersen, S. F. & Porazinski, K. Entrapment of macroplankton in an Arctic fjord basin, Kongsfjorden, Svalbard. Oceanologia 42, 1 (2000).
    Google Scholar 
    Berge, J. et al. Arctic complexity: A case study on diel vertical migration of zooplankton. J. Plankton Res. 36, 1279–1297 (2014).PubMed 
    PubMed Central 

    Google Scholar 
    Darnis, G. et al. From polar night to midnight sun: Diel vertical migration, metabolism and biogeochemical role of zooplankton in a high Arctic fjord (Kongsfjorden, Svalbard). Limnol. Oceanogr. 62, 1586–1605 (2017).ADS 
    CAS 

    Google Scholar 
    Descamps, S. et al. Climate change impacts on wildlife in a High Arctic archipelago – Svalbard, Norway. Glob. Chang Biol. 23, 490–502 (2017).ADS 
    PubMed 

    Google Scholar 
    Cottier, F. R. et al. Arctic fjords: A review of the oceanographic environment and dominant physical processes. Geol. Soc. Spec. Publ. 344, 35–50 (2010).ADS 

    Google Scholar 
    Inall, M. E., Nilsen, F., Cottier, F. R. & Daae, R. Shelf/fjord exchange driven by coastal-trapped waves in the Arctic. J. Geophys. Res. Oceans 120, 8283–8303 (2015).ADS 

    Google Scholar 
    Promińska, A., Cisek, M. & Walczowski, W. Kongsfjorden and Hornsund hydrography—Comparative study based on a multiyear survey in fjords of west Spitsbergen. Oceanologia 59, 397–412 (2017).
    Google Scholar 
    Agrawal, Y. C. & Pottsmith, H. C. Instruments for particle size and settling velocity observations in sediment transport. Mar. Geol. 168, 89–114 (2000).ADS 

    Google Scholar 
    Basedow, S. L., Tande, K. S. & Zhou, M. Biovolume spectrum theories applied: Spatial patterns of trophic levels within a mesozooplankton community at the polar front. J. Plankton Res. 32, 1105–1119 (2010).PubMed 

    Google Scholar 
    Trudnowska, E., Basedow, S. L. & Blachowiak-Samolyk, K. Mid-summer mesozooplankton biomass, its size distribution, and estimated production within a glacial Arctic fjord (Hornsund, Svalbard). J. Mar. Syst. 137, 55–66 (2014).
    Google Scholar 
    Jakubas, D. et al. Foraging closer to the colony leads to faster growth in little auks. Mar. Ecol. Prog. Ser. 489, 263–278 (2013).ADS 

    Google Scholar 
    Basedow, S. L., Tande, K. S., Norrbin, M. F. & Kristiansen, S. A. Capturing quantitative zooplankton information in the sea: Performance test of laser optical plankton counter and video plankton recorder in a Calanus finmarchicus dominated summer situation. Prog. Oceanogr. 108, 72–80 (2013).ADS 

    Google Scholar 
    Woźniak, S. B., Darecki, M., Zabłocka, M., Burska, D. & Dera, J. New simple statistical formulas for estimating surface concentrations of suspended particulate matter (SPM) and particulate organic carbon (POC) from remote-sensing reflectance in the southern Baltic Sea. Oceanologia 58, 161–175 (2016).
    Google Scholar 
    Marker, A. The measurement of photosynthetic pigments in freshwaters and standardization of methods : Conclusions and recommendations. Arch. Hydrobiol. Beih 14, 91–106 (1980).CAS 

    Google Scholar 
    Stramska, M. Bio-optical relationships and ocean color algorithms for the north polar region of the Atlantic. J. Geophys. Res. 108, 3143 (2003).ADS 

    Google Scholar 
    Picheral, M. et al. The Underwater Vision Profiler 5: An advanced instrument for high spatial resolution studies of particle size spectra and zooplankton. Limnol. Oceanogr. Methods 8, 462–473 (2010).
    Google Scholar 
    Gabrielsen, T. M. et al. Potential misidentifications of two climate indicator species of the marine arctic ecosystem: Calanus glacialis and C. finmarchicus. Polar Biol. 35, 1621–1628 (2012).
    Google Scholar 
    Trudnowska, E. et al. In a comfort zone and beyond—Ecological plasticity of key marine mediators. Ecol. Evol. 10, 14067–14081 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Jakobsson, M. et al. The International Bathymetric Chart of the Arctic Ocean version 4.0. Sci Data 7, 1–14 (2020).
    Google Scholar 
    van Rossum, G. & Drake, F. L. Python 3 Reference Manual. Preprint (2009).Caswell, T. A. et al. matplotlib/matplotlib: REL: v3.1.1. https://doi.org/10.5281/ZENODO.3264781 (2019).Hunter, J. D. Matplotlib: A 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).
    Google Scholar 
    Mckinney, W. Data Structures for Statistical Computing in Python. (2010).Reback, J. et al. pandas-dev/pandas: Pandas 1.0.5. https://doi.org/10.5281/ZENODO.3898987 (2020).Pond, S. & Pickard, G. L. Introductory dynamical oceanography. 2nd Ed. (1983).Mojica, K. D. A. et al. Phytoplankton community structure in relation to vertical stratification along a north-south gradient in the Northeast Atlantic Ocean. Limnol. Oceanogr. 60, 1498–1521 (2015).ADS 

    Google Scholar 
    Anderson, M. J., Gorley, R. N. & Clarke, K. R. PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods. http://www.primer-e.com (2008).Clarke, K. R. & Gorley, R. N. Getting Started with PRIMER v7 Plymouth Routines in Multivariate Ecological Research. www.primer-e.com (2015).Virtanen, P. et al. SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261–272 (2020).Terpilowski, M. scikit-posthocs: Pairwise multiple comparison tests in Python. J. Open Source Softw. 4, 1169 (2019).ADS 

    Google Scholar 
    Alcaraz, M. et al. The role of arctic zooplankton in biogeochemical cycles: Respiration and excretion of ammonia and phosphate during summer. Polar Biol. 33, 1719–1731 (2010).
    Google Scholar 
    Soviadan, Y. D. et al. Patterns of mesozooplankton community composition and vertical fluxes in the global ocean. Prog. Oceanogr. 200, 102717 (2022).
    Google Scholar 
    Falk-Petersen, S. et al. Vertical migration in high Arctic waters during autumn 2004. Deep Sea Res. 2 Top. Stud. Oceanogr. 55, 2275–2284 (2008).
    Google Scholar 
    Lane, P. V. Z., Llinás, L., Smith, S. L. & Pilz, D. Zooplankton distribution in the western Arctic during summer 2002: Hydrographic habitats and implications for food chain dynamics. J. Mar. Syst. 70, 97–133 (2008).
    Google Scholar 
    Kulk, G., Poll, W. H. & Buma, A. G. J. Photophysiology of nitrate limited phytoplankton communities in Kongsfjorden, Spitsbergen. Limnol. Oceanogr. 63, 2606–2617 (2018).ADS 
    CAS 

    Google Scholar 
    Moskalik, M. et al. Spatiotemporal changes in the concentration and composition of suspended particulate matter in front of Hansbreen, a tidewater glacier in Svalbard. Oceanologia 60, 446–463 (2018).
    Google Scholar 
    Svendsen, H. et al. The physical environment of Kongsfjorden-Krossfjorden, an Arctic fjord system in Svalbard. Polar Res. 21, 133–166 (2002).
    Google Scholar 
    Chiswell, S. M., Calil, P. H. R. & Boyd, P. W. Spring blooms and annual cycles of phytoplankton: A unified perspective. J. Plankton Res. 37, 500–508 (2015).
    Google Scholar 
    Kaartvedt, S., Melle, W., Knutsen, T. & Skjoldal, H. Vertical distribution of fish and krill beneath water of varying optical properties. Mar. Ecol. Prog. Ser. 136, 51–58 (1996).ADS 

    Google Scholar 
    Schmid, M. S., Maps, F. & Fortier, L. Lipid load triggers migration to diapause in Arctic Calanus copepods—Insights from underwater imaging. J. Plankton Res. 40, 311–325 (2018).CAS 

    Google Scholar 
    Campbell, R. G. et al. Mesozooplankton prey preference and grazing impact in the western Arctic Ocean. Deep Sea Res. 2 Top. Stud. Oceanogr. 56, 1274–1289 (2009).
    Google Scholar 
    Hirche, H. J. Diapause in the marine copepod, calanus finmarchicus—A review. Ophelia 44, 129–143 (1996).
    Google Scholar 
    Pedersen, S. A. & Smidt, E. L. B. Zooplankton Investigations Off West Greenland, 1956–1984. (ICES, 1995).Reiner Vonnahme, T. et al. Early spring subglacial discharge plumes fuel under-ice primary production at a Svalbard tidewater glacier. Cryosphere 15, 2083–2107 (2021).ADS 

    Google Scholar 
    Majaneva, S. et al. Aggregations of predators and prey affect predation impact of the Arctic ctenophore Mertensia ovum. Mar. Ecol. Prog. Ser. 476, 87–100 (2013).ADS 

    Google Scholar 
    Purcell, J. E., Hopcroft, R. R., Kosobokova, K. N. & Whitledge, T. E. Distribution, abundance, and predation effects of epipelagic ctenophores and jellyfish in the western Arctic Ocean. Deep Sea Res. 2 Top Stud Oceanogr 57, 127–135 (2010).
    Google Scholar 
    Condon, R. H. et al. Questioning the rise of gelatinous zooplankton in the world’s oceans. Bioscience 62, 160–169 (2012).
    Google Scholar 
    Balazy, K., Trudnowska, E. & Błachowiak-Samołyk, K. Dynamics of Calanus copepodite structure during little Auks’ breeding seasons in two different Svalbard locations. Water (Basel) 11, 1405 (2019).CAS 

    Google Scholar 
    Karnovsky, N. J. & Hunt, G. L. Estimation of carbon flux to dovekies (Alle alle) in the North Water. Deep Sea Res. 2 Top. Stud. Oceanogr. 49, 5117–5130 (2002).CAS 

    Google Scholar 
    Renaud, P. E. et al. Is the poleward expansion by Atlantic cod and haddock threatening native polar cod, Boreogadus saida?. Polar Biol. 35, 401–412. https://doi.org/10.1007/s00300-011-1085-z (2012).Article 

    Google Scholar 
    Szeligowska, M. et al. Spatial patterns of particles and plankton in the warming Arctic Fjord (Isfjorden, West Spitsbergen) in seven consecutive mid-summers (2013–2019). Front. Mar. Sci. 7, 584 (2020).
    Google Scholar  More

  • in

    From the archive: a plague in frogs, and oxygen consumption after running

    Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
    the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
    Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
    and JavaScript. More

  • in

    Flexible embryonic shell allies large offspring size and anti-predatory protection in viviparous snails

    The studied viviparous clausiliids developed four types of morphological adaptations that facilitate the delivery of embryos through the shell aperture: (1) reduction of the clausiliar apparatus, (2) decrease of embryonic shell width, (3) widening of the shell canal, and (4) development of a flexible embryonic shell.Reduction of the clausiliar apparatusMembers of the Reinia genus, arboreal species from Japan (Fig. 1), show the most advanced adaptations to live-bearing compared to hypothetical ancestral Phaedusinae. The shell shape in these species is more conical than fusiform, the number of whorls decreases, and the aperture widens. One of the species, R. variegata, features almost full reduction of the clausiliar apparatus that consists of only vestigial folds (Fig. 1F). This species also lacks the clausilium, so the entrance through the aperture is unprotected.Figure 1Different stages of reduction of apertural barriers in members of genus Reinia: R. ashizuriensis (A–C; upper row) and R. variegata (D–F; lower row). (A,D) Adult shells; (B,C,E,F) adult shells with body whorl cut open dorsally in microCT visualisation. cp clausilium plate, il inferior lamella, pr principal plica, sc subcolumellar lamella, sl superior lamella, sp spiral lamella, upp upper palatal plica.Full size imageDecrease of embryonic shell widthAnother adaptation concerns the shape of the embryonic shell (“protoconch”), which becomes very narrow in some viviparous species. This feature is conspicuous because embryonic whorls remain in the adult shell as apical whorls. For instance in S. addisoni (Fig. 2A–D), the apical part being much narrower than the first whorls of the teleoconch is a clear evidence that the growth trajectory has changed abruptly after birth. Other examples include E. cylindrella and E. steetzneri, in which both the protoconch and the teleoconch are very narrow, yet at the borderline between these parts, the shell axis is slightly bent (Fig. 2E–L). We suppose that this feature develops as a result of obstruction during birth.Figure 2Width difference between protoconch and teleoconch in Stereophaedusa addisoni (A–D, upper row), Euphaedusa cylindrella (E–H, middle row), Euphaedusa steetzneri (I–L, lower row). (A,C,E,G,I,K) Adult shells with very narrow apical whorls; (B,F,J) X-rayed adults; (F,J) with retained embryos inside; (D,H,L) X-rays of apical part of adult shell with schematic drawings of a neonate.Full size imageWidening of the shell canalThe third type of adaptation is the widening of the shell canal in the body whorl, allowing for easier passage of the embryo between the lamellae and plicae of the apertural barriers. In this case, the outline of the shell changes only slightly giving the body whorl a more convex appearance. A substantial difference to egg-laying species concerns the apertural barriers: the clausiliar includes a broad clausilium plate and a spirally ascending inferior lamella (Fig. 3A–D). These modifications result in a spacious shell canal in the body whorl, for example in S. addisoni and E. sheridani, that can accommodate the transfer of a large embryo. Table 1 presents neonatal size in these species (shell width ca. 1.2 mm), which is very similar to their clausilium width (ca. 1.1–1.2 mm).Figure 3Two types of clausiliar apparatus occurring in Phaedusinae in microCT visualisation: with spirally ascending inferior lamella and wide clausilium plate (upper row), and with straight ascending inferior lamella and narrow clausilium plate (lower row). (A) T. sheridani adult shell with the body whorl cut open dorsally; (B) clausilium of T. sheridani; (C) clausilium of S. addisoni; (D) clausilium of R. ashizuriensis; (E) Zaptyx ventriosa adult shell with body whorl cut open dorsally; (F) clausilium of Z. ventriosa; (G,H) clausilia of O. miranda. Note, that all depicted species are viviparous.Full size imageTable 1 Shell size of studied Phaedusinae species.Full size tableMost viviparid clausiliids develop one of these three types of modification; some adaptations co-occur within a single species, for example a wide clausilium accompanies a narrow apex. Interestingly, the Reinia genus includes taxa with a gradual escalation of viviparity-related adaptations: R. ashizurensis, with a stout shell shape and a low number of whorls, has fully developed apertural barriers with a broad clausilium plate (Fig. 1A–C), while its congener, R. variegata, has reduced apertural barriers (Fig. 1D–F).Development of a flexible embryonic shellThe fourth type of adaptation found in Phaedusinae concerns the structure of the embryonic shells. We report this adaptation in O. miranda and Z. ventriosa.Oospira miranda is a dextral, often decollated, ground-dwelling species from Vietnam (Fig. 4A). The species is viviparous: during microCT scanning of museum specimens, we found embryos within a parental shell (Fig. 4B); in laboratory culture, we observed neonates immediately after live birth (Fig. 4C,D). Morphological characters recognized in the adult shell, i.e., a wide apex (= wide embryonic shell), straightly ascending inferior lamella, and a narrow clausilium plate (Fig. 3G,H), seemed to exclude the possibility of live-bearing reproduction, as embryos are too large to pass through the shell canal at the narrowest point. The height and width of the neonatal shell (mean values: 5.19 mm, 3.59 mm) evidently exceeds the width of the clausilium plate in this species (1.97 mm) (Table 1). However, under closer examination, we found the shell to be thin and delicate, which we refer to as a ‘soft shell’. In direct examination, the neonatal shell of O. miranda resembles cellophane, which may keep a given shape for a long time but becomes distorted already under slight pressure.Figure 4Viviparous clausiliids and their ‘soft-shelled’ neonates born in laboratory culture. (A–D) O. miranda: adult shell, X-rayed shell with embryo visible inside, neonates; (E–H) Z. ventriosa: adult shell, X-rayed shell with eggs visible inside, neonates.Full size imageA similar adaptation exists in Z. ventriosa, a Taiwanese species with a very wide apex, never decollated, a straight ascending inferior lamella, and a narrow clausilium plate (Figs. 3E,F, 4E,F). This species produces neonates in laboratory culture (Fig. 4G–H). The dimensions of the neonates (mean values: height 3.37 mm, width 2.51 mm) exceed at last twofold the width of the clausilium plate (1.08 mm). The shells of such freshly delivered juveniles, when gently touched with laboratory tweezers, became dented, but not fractured. More intense and stronger pressing can break this dentation.These initial observations, that we made during the maintenance of the laboratory culture, suggested that the neonatal shells of O. miranda and Z. ventriosa have flexible walls. These ‘soft-shells’ seem to be highly malleable during the entire embryonic development period and delivery through apertural barriers, hardening shortly after birth. We further investigated the physical properties of the embryonic shell by means of microcomputed tomography and scanning electron microscopy.Microcomputed tomographyWe scanned ‘soft-shelled’ neonates of O. miranda and Z. ventriosa, together with ‘hard-shelled’ embryos and neonates of S. addisoni and T. sheridani, in order to compare the density and thickness of the shells (Fig. 5).Figure 5Comparison of embryonic shell thickness in clausiliids: ‘soft-shelled’ neonates of Z. ventriosa (A,B,G,H) and O. miranda (C,D,I,J); “hard-shelled” neonate of S. addisoni (E,K) and embryo of T. sheridani (F,L) scanned inside a parental shell. Upper row—microCT visualisation of shell surface; middle row—microCT sections of those specimens; (M–O) X-ray photographs of S. addisoni (embryo from dissected adult) and Z. ventriosa (neonate) enlarged in (N,O), respectively, showing the difference in shell density and thickness; (P) microCT based volume rendering of O. miranda (left) and S. addisoni (right) neonates, showing difference between relative density of their shells.Full size imagePreliminary observations using the two-dimensional X-ray photographs showed a difference in thickness and density between S. addisoni and Z. ventriosa (Fig. 5M, enlarged in N and O, respectively). The 3D visualization of O. miranda and S. addisoni (the same microCT scanning and reconstruction parameters) confirmed the difference between density and shell thickness of these two species (Fig. 5P).Due to variations in wall thickness within the neonatal shell (e.g., between the first and the second whorls), it is not possible to precisely determine the thickness of the shell wall. The accuracy of the measurement is also limited by the resolution of the microCT scans, especially in the case of the relatively large neonates of O. miranda and Z. ventriosa. When scanning the whole embryonic shell of Z. ventriosa (approximately 3.5 mm in height), the size of the voxel was approximately 1 µm. Thus, we cannot determine the shell thickness down to the nearest micron, but we can estimate it from a few to a dozen microns. A direct comparison between virtual microCT sections of specimens scanned under the same conditions shows a clear difference between the ‘soft-shelled’ and ‘hard-shelled’ taxa (Fig. 5G–L). The ’hard-shelled’ neonates have a shell wall of 30–40 µm thick. We examined the sequence of three ’soft-shelled’ O. miranda specimens that differed in size (the exact time of birth of each of the cultured neonates is unknown, ca. 1–2 days). The larger (older) the neonate was, the thicker the shell. The shell of the largest of the studied O. miranda was up to 20 µm thick. However, the shell wall of this relatively large juvenile (several millimeters in height) still did not reach the thickness of the small ’hard-shelled’ T. sheridani embryo, which was already about 30–40 µm thick, stiff and rigid during the retention in the genital tract. The neonates of O. miranda and Z. ventriosa were much larger than the embryos and neonates of S. addisoni and R. variegata (Table 1), however, the former taxa has much thinner shells.Scanning electron microscopyAfter the non-invasive microCT scan, we scanned embryos and neonates using SEM (Fig. 6). The different properties of the shells of Z. ventriosa and O. miranda vs. S. addisoni and R. variegata were already visible during the preparation of the analysis. Under vacuum conditions, the soft shells of Z. ventriosa and O. miranda shrank and crumpled, creating a cellophane-like surface (Fig. 6A). Embryos and neonates of S. addisoni and R. variegata did not require any special preparation and their shell shape remained unchanged under the vacuum conditions applied during the SEM examination (Fig. 6D,E). To reduce the shell deformations, we freeze-dried the next group of thin-shelled neonates prior to SEM analyses (Fig. 6B,C).Figure 6Neonates of O. miranda (A,B,F,I,L,M,O) and Z. ventriosa (C,G,J,P) in direct comparison with hard-shelled embryos and neonates of R. variegata (D,N,Q) and S. addisoni (E,H,K); SEM microphotographs. The vacuum conditions in SEM led to the shrinkage of the thin O. miranda shell (A); freeze-drying of ‘soft-shelled’ neonates prior to SEM imaging reduced the level of deformity (B,C). Contrastingly, R. variegata and S. addisoni shells do not require special preparation and retain their shape (D,E). (F) The dented surface of O. miranda neonate and SEM-close-up (I) on a cross-section of the shell just a few micrometers thick (arrow in F indicates the region enlarged in I). (G,J) Shell of Z. ventriosa in comparison with similarly ornamented fragment of S. addisoni (H,K); note several times thicker shell in the latter (arrows in G,H indicate the regions enlarged in J,K, respectively). (L,M) Inner surface of intact periostracum which still connects two fragments of broken aragonite shell of O. miranda (the arrow in M indicates the region enlarged in L); note the difference between shell thickness in O. miranda (L,M) and R. variegata (N). All observed specimens have similar crossed-lamellar microstructure (L–Q). However, just as shell thickness, also the number of lamellar layers of alternate orientation within the shell differs (L,M,O,P vs N,Q).Full size imageThe SEM studies allowed for complementary measurements of the shells. In the broken fragments of Z. ventriosa and O. miranda, the thickness of the shell wall ranged from 2–3 µm (Fig. 6F,G,I,J,L,M) to 18 µm in the largest neonate of O. miranda (Fig. 6O). The shells of S. addisoni (Fig. 6H,K) and R. variegata (Fig. 6N) are several times thicker.All analyzed samples have a thin ( More

  • in

    Predation impact on threatened spur-thighed tortoises by golden eagles when main prey is scarce

    Roff, D. A. The Evolution of Life Histories: Theory and Analysis (Chapman and Hall, 1992).
    Google Scholar 
    Sæther, B. E. & Bakke, O. Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81, 642–653 (2000).
    Google Scholar 
    Koons, D. N., Pavard, S., Baudisch, A. & Metcalf, J. E. C. Is life-history buffering or lability adaptive in stochastic environments?. Oikos 118, 972–980 (2009).
    Google Scholar 
    Boyce, M. S., Haridas, C. V. & Lee, C. T. Demography in an increasingly variable world. Trends Ecol. Evol. 21, 141–148 (2006).PubMed 

    Google Scholar 
    Morris, W. F. & Doak, D. F. Buffering of life histories against environmental stochasticity: Accounting for a spurious correlation between the variabilities of vital rates and their contributions to fitness. Am. Nat. 163, 579–590 (2004).PubMed 

    Google Scholar 
    Ripple, W. J. et al. Saving the world’s terrestrial megafauna. Bioscience 66(10), 807–812 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    He, F. et al. Disappearing giants: A review of threats to freshwater megafauna. WIREs Water 4, e1208 (2017).
    Google Scholar 
    Blackburn, T. M., Cassey, P., Duncan, R. P., Evans, K. L. & Gaston, K. J. Avian extinction and mammalian introductions on oceanic islands. Science 305(5692), 1955–1958 (2004).ADS 
    CAS 
    PubMed 

    Google Scholar 
    Courchamp, F., Langlais, M. & Sugihara, G. Rabbits killing birds: Modelling the hyperpredation process. J. Anim. Ecol. 69, 154–164 (2000).
    Google Scholar 
    Roemer, G. W., Coonan, T. J., Garcelon, D. K., Bascompte, J. & Laughrin, L. Feral pigs facilitate hyperpredation by golden eagles and indirectly cause the decline of the island fox. Anim. Conserv. 4, 307–318 (2001).
    Google Scholar 
    Kristan, W. B. & Boarman, W. I. Spatial patterns of risk of common raven predation on desert tortoises. Ecology 84, 2432–2443 (2003).
    Google Scholar 
    Whelan, C. J., Brown, J. S. & Maina, G. Search biases, frequency-dependent predation and species co-existence. Evol. Ecol. Res. 5, 329–343 (2003).
    Google Scholar 
    Moleón, M., Almaraz, P. & Sánchez-Zapata, J. A. An emerging infectious disease triggering large-scale hyperpredation. PLoS ONE 3, e2307 (2008).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Moleón, M., Almaraz, P. & Sánchez-Zapata, J. A. Inferring ecological mechanisms from hunting bag data in wildlife management: A reply to blanco-aguiar et al. 2012. Eur. J. Wildl. Res. 59, 599–608 (2013).
    Google Scholar 
    Bate, A. M. & Hilker, F. M. Rabbits protecting birds: Hypopredation and limitations of hyperpredation. J. Theor. Biol. 297, 103–115 (2012).ADS 
    MathSciNet 
    PubMed 
    MATH 

    Google Scholar 
    Turner, F. B., Medica, P. A. & Lyons, C. L. Reproduction and survival of the desert tortoise (Scaptochelys agassizii) in Ivanpah Valley California. Copeia 1984(4), 811–820 (1984).
    Google Scholar 
    Graciá, E. et al. Assessment of the key evolutionary traits that prevent extinctions in human altered habitats using a spatially explicit individual-based model. Ecol. Model. 415, 108823 (2020).
    Google Scholar 
    Segura, A., Jiménez, J. & Acevedo, P. Predation of young tortoises by rabbits: The effect of habitat structure on tortoise detectability and abundance. Sci. Rep. 10, 1–9 (2020).
    Google Scholar 
    Watson, J. The golden eagle (Bloomsbury Publishing, 2010).
    Google Scholar 
    Fischer, W., Zenker, D. & Baumgart, W. Ein beitrag zum bestand und zur ernährung des steinadlers Aquila chrysaetos af der balkanhalbinsel. Beiträge zur Vogelskunde 21, 275–287 (1975).
    Google Scholar 
    Delibes, M., Calderón, J. & Hiraldo, F. Selección de presa y alimentación en españa del águila real (Aquila chrysaetos). Ardeola 21, 285–303 (1975).
    Google Scholar 
    Handrinos, G. The Golden Eagle in Greece. Actes 1er Coll. Intern. Aigle Royal en Europe, Arvieux, 1986: 18–22 (1987).Bautista, J., Gil-Sánchez, J. M. & Moleón, M. Dieta del águila real en el sur de españa. Quercus 364, 17–23 (2016).
    Google Scholar 
    Bautista, J., Castillo, S., Paz, J. L., Llamas, J. & Ellis, D. H. Golden eagles (Aquila chrysaetos) as potential predators of barbary macaques (Macaca sylvanus) in northern Morocco: Evidences of predation. Go-South Bull. 15, 172–179 (2018).
    Google Scholar 
    Kouzmanov, G., Stoyanov, R. & Todorov, V. Sur la biologie et la Protection de l`Aigle royal Aquila chrysaetos en Bulgarie. In Eagle studies (eds Meyburg, B. & Chancellor, R.) 505–516 (World Working Group on Birds of Prey, 1996).
    Google Scholar 
    Capper, S. The predation of Testudo spp. By Golden Eagles Aquila chrysaetos in Dadia Forest Reserve, NE Greece. University of Reading (1998).Karyakin, I. V., Kovalenko, A. V., Levin, A. S. & Pazhenkov, A. S. Eagles of the Aral-Caspian region Kazakhstan. Raptors Conserv. 22, 92–152 (2011).
    Google Scholar 
    Papageorgiou, N., Vlachos, C., Bakaloudis, D. E., Kazaklis, A., Birtsas, P. Study on the biology and management of raptors in Dadia forest–Evros. Thessaloniki, GR (1995).Sidiropoulos, L. et al. Pronounced seasonal diet diversity expansion of golden eagles (Aquila chrysaetos) in Northern Greece during the non-breeding season: The role of tortoises. Diversity 14(2), 135 (2022).
    Google Scholar 
    IUCN. The IUCN red list of threatened species. Version 2020–3 (2020).Graciá, E. et al. Expansion after expansion: dissecting the phylogeography of the widely distributed spur-thighed tortoise, Testudo graeca (Testudines: Testudinidae). Biol. J. Linn. Soc. 121, 641–654 (2017).
    Google Scholar 
    Graciá, E. et al. Genetic patterns of a range expansion: The spur-thighed tortoise Testudo graeca graeca in southeastern Spain. Amphib. Reptil. 32, 49–61 (2011).
    Google Scholar 
    Graciá, E. et al. The uncertainty of late pleistocene range expansions in the western Mediterranean: A case study of the colonization of south-eastern Spain by the spur-thighed tortoise, Testudo graeca.. J. Biogeogr 40, 323–334 (2013).
    Google Scholar 
    Anadón, J. D., Giménez, A., Perez, I., Martinez, M. & Esteve-Selma, M. A. Habitat selection by the spur-thighed tortoise Testudo graeca in a multisuccessional landscape: implications for habitat management. Biodivers. Conserv. 15, 2287–2299 (2006).
    Google Scholar 
    Rodríguez-Caro, R. C. et al. Low tortoise abundances in pine forest plantations in forest-shrubland transition areas. PLoS ONE 12, e0173485 (2017).PubMed 
    PubMed Central 

    Google Scholar 
    Rodríguez-Caro, R. C. et al. The limits of demographic buffering in coping with environmental variation. Oikos 130(8), 1346–1358 (2021).
    Google Scholar 
    Rodríguez-Caro, R. C., Lima, M., Anadón, J. D., Graciá, E. & Giménez, A. Density dependence, climate and fires determine population fluctuations of the spur-thighed tortoise, Testudo graeca. J. Zool. 300, 265–273 (2016).
    Google Scholar 
    Rodríguez-Caro, R. C. et al. A low cost approach to estimate demographic rates using inverse modeling. Biol. Conserv. 237, 358–365 (2019).
    Google Scholar 
    Jiménez-Franco, M. V. et al. Sperm storage reduces the strength of the mate-finding allee effect. Ecol. Evol. 10(4), 1938–1948 (2020).PubMed 
    PubMed Central 

    Google Scholar 
    Graciá, E. et al. From troubles to solutions: Conservation of mediterranean tortoises under global change. Basic Appl. Herpetol. 34, 5–16 (2020).
    Google Scholar 
    Pérez, I. et al. Exurban sprawl increases the extinction probability of a threatened tortoise due to pet collections. Ecol. Model. 245, 19–30 (2012).
    Google Scholar 
    Del Moral, J. C. El águila real en España. Población reproductora en 2008 y método de censo. SEO/BirdLife. Madrid. pp. 30–50 (2009).Virgós, E., Cabezas-Díaz, S. & Lozano, J. Is the wild rabbit (Oryctolagus cuniculus) a threatened species in Spain? Sociological constraints in the conservation of species. Biodivers. Conserv. 16, 3489–3504 (2007).
    Google Scholar 
    Fernández, C. Effect of the viral haemorrhagic pneumonia of the wild rabbit on the diet and breeding success of the golden eagle Aquila chrysaetos (L.). Rev. Ecol. Terre et Vie 48, 323–329 (1993).
    Google Scholar 
    Villafuerte, R., Luco, D. F., Gortázar, C. & Blanco, J. C. Effect on red fox litter size and diet after rabbit haemorrhagic disease in northeastern Spain. J. Zool. 240, 764–767 (1996).
    Google Scholar 
    Martínez, J. A. & Zuberogoitia, I. The response of eagle owl (Bubo bubo) to an outbreak of the rabbit haemorrhagic disease. J. Ornithol. 142, 204–211 (2001).
    Google Scholar 
    Moleón, M. et al. Large-scale spatiotemporal shifts in the diet of a predator mediated by an emerging infectious disease of its main prey. J. Biogeogr. 36, 1502–1515 (2009).
    Google Scholar 
    Adamakopoulos, T., Gatzoyannis, S., Poirazidis, K. Study on the assessment, the enhancement of the legal infrastructure and the management of the protected area in the forest of Dadia. Specific Environmental Study, WWF-Greece, Athens (1995).Delibes, M., Hiraldo, F. The rabbit as prey in the Iberian Mediterranean ecosystem. In Proceedings of the World Lagomorph Conference. Guelph: University of Guelph. 1979: 614–622 (1979).Futuyma, D. J. & Moreno, G. The evolution of ecological specialization. Annu. Rev. Ecol. Syst. 19, 207–233 (1988).
    Google Scholar 
    Moleón, M. et al. Predator–prey relationships in a mediterranean vertebrate system: Bonelli’s eagles, rabbits and partridges. Oecologia 168, 679–689 (2012).ADS 
    PubMed 

    Google Scholar 
    Fedriani, J. M., Ferreras, P. & Delibes, M. Dietary response of the Eurasian badger, Meles meles, to a decline of its main prey in the Doñana national park. J. Zool. 245, 214–218 (1998).
    Google Scholar 
    Ferrer, M. & Negro, J. J. The near extinction of two large European predators: Super specialists pay a price. Conserv. Biol. 18, 344–349 (2004).
    Google Scholar 
    Lozano, J., Moleón, M. & Virgós, E. Biogeographical patterns in the diet of the wildcat, Felis silvestris Schreber, in Eurasia: Factors affecting the trophic diversity. J. Biogeogr. 33, 1076–1085 (2006).
    Google Scholar 
    Burgos, T. et al. Prey density determines the faecal-marking behaviour of a solitary predator, the Iberian lynx (Lynx pardinus). Ethol. Ecol. Evol. 31, 219–230 (2019).
    Google Scholar 
    Ontiveros, D. & Pleguezuelos, J. M. Influence of prey densities in the distribution and breeding success of Bonelli’s eagle (Hieraaetus fasciatus): Management implications. Biol. Conserv. 93, 19–25 (2000).
    Google Scholar 
    Araújo, M. S. & Gonzaga, M. O. Individual specialization in the hunting wasp Trypoxylon (Trypargilum) albonigrum (Hymenoptera, Crabronidae). Behav. Ecol. Sociobiol. 61, 1855–1863 (2007).
    Google Scholar 
    Stephens, D. W. & Krebs, J. R. Foraging Theory 1st edn. (Monographs in Behavior and Ecology. Princeton University Press, 1986).
    Google Scholar 
    Heath, J. A. et al. Golden Eagle dietary shifts following wildfire and shrub loss have negative consequences for nestling survivorship. Ornithol. Appl. 123(4), duabo34 (2021).
    Google Scholar 
    Anadón, J. D., Wiegand, T. & Giménez, A. Individual-based movement models reveal sex-biased effects of landscape fragmentation on animal movement. Ecosphere 3, 1–32 (2012).
    Google Scholar 
    Sanz-Aguilar, A., Anadón, J. D., Giménez, A., Ballestar, R. & Oro, D. Coexisting with fire: The case of the terrestrial tortoise Testudo graeca in mediterranean shrublands. Biol. Conserv. 144, 1040–1049 (2011).
    Google Scholar 
    Arroyo, B. Águila real – Aquila chrysaetos. In: Enciclopedia Virtual de los Vertebrados Españoles. Salvador, A., Morales, M. B. (Eds.). Museo Nacional de Ciencias Naturales, Madrid. http://www.vertebradosibericos.org/ (2017).Arroyo, B., Ferreiro, E., Garza, V. El águila real (Aquila chrysaetos) en España. Censo, distribución, reproducción y conservación. Serie Técnica, ICONA. Madrid (1990).Bautista, J., Gil-Sánchez, J. M., González Miras, E., Gómez, G. J. & Sánchez Balsera, J. L. Increase in the population of golden eagle in andalusian baetic system mountain ranges (southern of Spain): evidences of competition with the Bonelli’s eagle. Quercus 332, 16–22 (2013).
    Google Scholar 
    Rodríguez-Caro, R. C., Graciá, E., Anadón, J. D. & Giménez, A. Maintained effects of fire on individual growth and survival rates in a spur-thighed tortoise population. Eur. J. Wildl. Res. 59, 911–913 (2013).
    Google Scholar 
    Beissinger, S. R. & McCullough, D. R. Population viability analysis (University of Chicago Press, 2002).
    Google Scholar 
    Tylianakis, J. M., Didham, R. K., Bascompte, J. & Wardle, D. A. Global change and species interactions in terrestrial ecosystems. Ecol. Lett. 11, 1351–1363 (2008).PubMed 

    Google Scholar 
    Real, J. Biases in diet study methods in the Bonelli’s eagle. J. Wildl. Manag. 60(3), 632–638 (1996).
    Google Scholar 
    Moleón, M. et al. Laying the foundations for a human-predator conflict solution: Assessing the impact of Bonelli’s eagle on rabbits and partridges. PLoS ONE 6, e22851 (2011).ADS 
    PubMed 
    PubMed Central 

    Google Scholar 
    Esteve-Selma, M. A., et al. Effects of climate change on the potential distribution of Testudo graeca in southeastern Iberian Peninsula. In Graciá E, Rodríguez-Caro RC and Giménez A. Conservation of Mediterranean tortoises under global change. Madrid. Asociación Herpetológica Española. ISBN: 978-84-921999-6-9.Anadón, J. D., Giménez, A., Ballestar, R. & Pérez, I. Evaluation of local ecological knowledge as a method for collecting extensive data on animal abundance. Conserv. Biol. 23, 617–625 (2009).PubMed 

    Google Scholar 
    Abad, V. Variaciones del Índice corporal en una población de tortuga mora (Testudo graeca) del Sureste Ibérico. MSc thesis, Universidad Miguel Hernández de Elche, Spain (2007).Linden, H., Wikman, M. Goshawk predation on tetraonids: Availability of prey and diet of the predator in the breeding season. J. Anim. Ecol., 953–968 (1983).Fevold, H. R. & Craighead, J. J. Food requirements of the golden eagle. Auk 75, 312–317 (1958).
    Google Scholar 
    Collopy, M. W. Food consumption and growth energetics of nestling golden eagles. Wilson Bull. 445–458 (1986).Blanco, J. C., Villafuerte, R. Factores ecológicos que influyen sobre las poblaciones de conejos. Efectos de la enfermedad hemorrágico vírica. TRAGSA, Madrid Spain (1993). More

  • in

    Weather impacts on interactions between nesting birds, nest-dwelling ectoparasites and ants

    Study areaWe conducted the study in the best-preserved stands of the Białowieża Forest, strictly protected within the Białowieża National Park (hereafter BNP; coordinates of Białowieża village: 52°42′N, 23°52′E). The extensive Białowieża Forest (c. 1500 km2) straddles the Polish-Belarusian border, where the climate is subcontinental with annual mean temperatures during May–July of 13–18 °C, and mean annual precipitation of 426–940 mm66,67.The forest provides a unique opportunity to observe animals under conditions that likely prevailed across European lowlands before widespread deforestation and forest exploitation by humans66,68,69. The stands have retained a primeval character distinguished by a multi-layered structure, frequent fallen and standing dead trees, and a high species richness66,70. The stands are composed of about a dozen tree species of various ages, up to several hundred years old. The interspecific interactions and natural processes have been little affected by direct human activity.We conducted observations mostly within the three permanent study plots (MS, N, W), totalling c. 130 ha, and in other nearby fragments of primeval oak-lime-hornbeam Tilio-Carpinetum or mixed deciduous-coniferous Pino-Quercetum stands. However, a small number of observations from adjacent managed deciduous forest stands were also included. For details of the study area see71,72,73.Study speciesOur study system focused on ground-nesting Wood Warblers Phylloscopus sibilatrix, blowflies Protocalliphora azurea, and Myrmica or Lasius ants, which occurred in the birds’ nests.The Wood Warbler is a small (c. 10 g) insectivorous songbird that winters in equatorial Africa and breeds in temperate European forests, typically rearing one or two broods each year74. Wood Warblers build dome-shaped nests for each breeding attempt, composed of woven grass, leaves and moss, and lined with animal hair73. The nests are situated on the ground among moderately sparse vegetation, often under a tussock of vegetation or near a fallen tree-branch or log (see examples in Supplementary Fig. S2)53,75. The breeding season of Wood Warblers begins in late April–early May and ends in July–August, when nestlings from replacement clutches (after initial loss) or second broods leave the nest. The typical clutch size in BNP is 5–7 eggs, and the nestling stage lasts 12–13 days74,76.Wood Warbler nests are inhabited by various arthropods, including Myrmica ruginodis or M. rubra ants, and less often Lasius platythorax, L. niger or L. brunneus. The ants foraged and/or raised their own broods within the Wood Warbler nests52. The Myrmica and Lasius ant species are common in Europe77,78. Their colonies contain from tens to thousands of workers, and can be found on the forest floor, e.g. in soil, within or under fallen dead wood, in patches of moss, or among fallen tree-leaves53,77,78. All of the ant species found in the Wood Warbler nests are predators of other arthropods77,79,80.Blowflies, Protocalliphora spp., are obligatory blood-sucking (hematophagous) ectoparasites that reproduce within bird nests. The occurrence, abundance, and impact of blowflies on Wood Warbler offspring is largely unknown, similar to many other European songbirds that build dome-shaped nests. Adult blowflies emerge in late spring and summer to lay eggs on the birds’ nesting material or directly onto the skin of typically newly hatched nestlings14,26. The blowfly larvae hatch within two–three days, and develop in the structure of warm bird nests for another 6–15 days, during which they emerge intermittently to feed on host blood, before finally pupating within the nests14,25,26,27.Data collectionNest monitoring and measurements of nestlingsWe searched for Wood Warbler nests daily from late April until mid-July in 2018–2020, by following birds mainly during nest-building. Nests were assigned to a deciduous or mixed deciduous-coniferous habitat type, depending on the tree stand where they were found. We inspected nests systematically, according to the protocol described in Wesołowski and Maziarz76. The number of observer visits was kept to a minimum to reduce disruptions for birds or potential risks of nest predation.We aimed to establish the dates of hatching (day 0 ± 1 day), nestlings vacating the nest (fledging; ± 1 day) or nest failure (± 1–2 days). When nestlings hatched asynchronously, the hatching date corresponded to the earliest record of nestling hatching. The dates of fledging or nest failure were the mid-dates between the last visit when the nestlings were present in the nest, and the following visit, when the nest was found empty. Nest failure was primarily due to predation, which is the main cause of the Wood Warbler nest losses in BNP76,81 and elsewhere in Europe82,83.To assess fitness consequences for birds of variable weather conditions, blowfly abundance and/or ant presence, we measured nestling growth and determined brood reduction (i.e. the mortality of chicks in the nest) from hatching until fledging. To define brood reduction, we assessed the number of hatchlings (nestlings up to 4 days old) and the number of fledglings leaving the nests. To ensure accurate counting and avoid premature fledging of nestlings, we established the number of fledglings on the day of measurement, when all nestlings were temporarily extracted from the nest.We measured nestling growth on a single occasion when they were 6–9 days old (median 8 days), almost fully developed but too young to leave the nest. The measurements lasted for less than 10–15 min at each nest to minimise any potential risk of attracting predators. For each nestling we measured (using a ruler) the emerged length of the longest (3rd) primary feather vane (± 0.5 mm) on the left wing84,85, and body mass to the nearest 0.1 g using an electronic balance. The length of the feather vane is closely linked to feather growth86 and is one of the characteristics of nestling growth85,87. We treated the length of the primary feather vane and body mass as indices of nestling growth rate under varying conditions of weather, blood-sucking ectoparasites, or ant presence.Extraction of arthropods from bird nestsTo assess the number of blowflies and to establish the presence of ants, we checked the contents of 129 nests (including 11 nests from the managed forest stands) at which Wood Warbler nestlings had been measured. The sample included 86 successful breeding attempts (where a minimum of one nestling successfully left the nest), 27 failed (predated) nests (remnants of nestlings were found, but the nest structure remained intact), and 16 nests with an unknown fate (nestlings were large, so were capable of leaving the nest, but no family were located or other signs indicating fledging).Due to ethical reasons, we were unable to collect the Wood Warbler nests and extract the ectoparasites and ants from them while they were in use by the birds. Removing the nests and replacing them with dummy nests would cause unacceptable nest desertion by adults. Therefore, we assessed the occurrence and number of blowflies or ant presence after Wood Warbler nestlings fledged or the breeding attempts failed naturally. We retrospectively explored the changes in blowfly infestation14, including the effect of ant presence53 in the same nests.We collected nests from the field as soon as a breeding attempt ended, within approximately five days (median 1 day) following fledging or nest failure (nest structure remained intact). The delay of nest collection would not bias the ectoparasite infestation, as blowfly larvae pupate within bird nests and stay there after the hosts abandon their nests; puparia can be still found in nests collected in autumn or winter14. As the likelihood of finding ant broods (larvae or pupae associated with workers) was rather stable with the delay of nest collection53, the method seemed reliable also for assessing the presence of ant broods (35 of all 71 Wood Warbler nests containing ants). Only the number of nests with lone foraging ant workers could be underestimated, potentially inflating the uncertainty of tested relationships. However, as ants usually re-use rich food resources88, foraging Myrmica or Lasius ant workers might regularly exploit warbler nests, increasing the chances of finding the insects in the collected nests.Wood Warbler nests were collected in one piece, with each placed into a separate sealed and labelled plastic bag. We carefully inspected the leaf litter around the nests, and the soil surface under them, to make sure that all blowfly larvae or pupae were collected. We transported the collected nests to a laboratory, where we stored them in a fridge for up to 5–6 days before the arthropod extraction.To establish the number of blowflies and the presence of ants, in 2018, we carefully pulled apart the nesting material and searched for the arthropods amongst it 52. We gathered all blowfly pupae or larvae and a sample of ant specimens into separate tubes, labelled and filled with 70–80% alcohol, for later species identification. For nests collected in 2019–2020, we extracted the arthropods with a Berlese-Tullgren funnel. During the extraction, which usually lasted for 72 h, each nest was covered with fine metal mesh and placed c. 15 cm under the heat of a 40 W electric lamp. The arthropods were caught in 100 ml plastic bottles containing 30 ml of 70–80% ethanol, installed under each funnel. After the arthropod extraction, we carefully inspected the nesting material in the same way as in 2018, to collect any blowflies that remained within the nests. The quality of information collected on the number of ectoparasites and ant presence should be comparable each year.Weather dataWe obtained the mean daily temperatures and rainfall sums from a meteorological station, operated by the Meteorology and Water Management National Research Institute in the Białowieża village, 1–7 km from the study areas.Data analysesWeather conditions affecting blowfly ectoparasitesTo explore the impact of weather on blowfly ectoparasites, for each Wood Warbler nest we calculated average temperatures from daily means, and total sums of rainfall from daily sums, for the two time-windows in which we assumed the impact of weather would be of greatest importance:

    i.

    the early nestling stage, when Wood Warbler nestlings were 1–4 days old. During this stage, female blowflies require a minimum temperature of c. 16 °C to become active and oviposit in bird nests27. Thus, cool and wet weather in the early nestling stage should reduce the activity of ovipositing blowflies, leading to less frequent ectoparasite infestation of Wood Warbler nests.

    ii.

    The late nestling stage, when the warbler nestlings were aged between over four days old and until fledging or nest failure. During this stage, blowfly larvae grow and develop in bird nests after hatching a few days after oviposition14,25,26,27. As the temperature of bird nests strongly depends on ambient temperatures21, mortality of blowfly larvae should increase in cool weather, resulting in fewer ectoparasites in nests collected shortly after the fledging of birds29.

    Weather conditions affecting Wood Warbler nestling growthTo explore the impact of weather on nestling growth, for each nest we calculated the average temperatures and total sums of rainfall for the period when nestlings were over four days old and until their measurement, usually on day 8 from hatching (see above). During this stage, nestlings are no longer brooded by a parent74, so must balance their energetic expenditure between growth (feather length and body mass) or thermoregulation89. Thus, we expected that the gain in body mass and the growth of flight feathers would be reduced in nestlings during cool and wet weather, when maintaining a stable body temperature would be costly90.Statistical analysesAll statistical tests were two-tailed and performed in R version 4.1.091.The changes in blowfly infestation of the Wood Warbler nestsTo test the changes in blowfly infestation of warbler nests, we used zero-augmented negative binomial models (package pscl in R;92,93), which deal with the problem of overdispersion and excess of zeros92. In this study, hurdle and zero-inflated models fitted with the same covariates had an almost identical Akaike Information Criterion (AIC). Therefore, we presented only the results of hurdle models, which are easier to interpret than zero-inflated models. Hurdle models consisted of two parts: a left-truncated count with a negative binomial distribution representing the number of blowflies in infested nests, and a zero hurdle binomial estimating the probability of blowfly presence. We used models with a negative binomial distribution, which had a much lower AIC than with a Poisson distribution on a count part.We designed the most complex (global) model that contained a response variable of the number of blowflies in each of the 129 Wood Warbler nests. The covariates were: mean ambient temperature, total sum of rainfall, presence (or absence) of ants in the same nests, habitat type (deciduous vs mixed deciduous-coniferous forest), study year (2018–2020), the number of nestlings hatched (brood size), and nest phenology (the relative hatching date of Wood Warbler nestlings, as days from the median hatching date in a season: 23 May in 2018, 25 May in 2019 and 29 May in 2020). The initial global model also contained the two-way interaction terms that we suspected to be important: between temperature and rainfall, temperature and presence of ants, and rainfall and presence of ants.To explore all potentially meaningful subsets of models, we used the same covariates on both parts (count and binomial) of the global model. We performed automated model selection with the MuMIn package94, starting from the most complex (global) model and using all possible simpler models (i.e. all subsets)95. To attain the minimum sample size of c. 20 data points for each parameter96, we limited the maximum number of parameters to six in each part (count or binomial) of the candidate models.As some of the interaction terms appeared insignificant in the initial model selection, to minimise the risk of over-parametrisation, we included only the significant interaction term on a count part of the final global model. As described above, we performed model selection again. We tested linear relationships, as the quadratic effects of weather variables (presuming temperature or rainfall optima) appeared insignificant.To test whether blowfly infestation changed with weather in the early or late nestling stages, we twice repeated the procedure described above. The first global model included the mean ambient temperature and the total sum of rainfall for the early nestling stage, and the second global model contained weather variables for the late nestling stage. The remaining covariates were the same.A practice of including the same sets of covariates on count and binomial parts has been previously questioned97. However, our approach allowed us to comply with these objections97, as we presented only the most parsimonious models (with ΔAICc  More