More stories

  • in

    Responses of alpine summit vegetation under climate change in the transition zone between subtropical and tropical humid environment

    Chen, I. C., Hill, J. K., Ohlemuller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026. https://doi.org/10.1126/science.1206432 (2011).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Gottfried, M. et al. Continent-wide response of mountain vegetation to climate change. Nat. Clim. Change 2, 111–115. https://doi.org/10.1038/nclimate1329 (2012).ADS 
    Article 

    Google Scholar 
    Rumpf, S. B. et al. Range dynamics of mountain plants decrease with elevation. Proc. Natl. Acad. Sci. 115, 201713936. https://doi.org/10.1073/pnas.1713936115 (2018).CAS 
    Article 

    Google Scholar 
    Gigauri, K., Akhalkatsi, M., Abdaladze, O. & Nakhutsrishvili, G. Alpine plant distribution and thermic vegetation indicator on GLORIA summits in the Central Greater Caucasus. Pak. J. Bot. 48, 1893–1902 (2016).
    Google Scholar 
    Gritsch, A., Dirnböck, T. & Dullinger, S. Recent changes in alpine vegetation differ among plant communities. J. Veg. Sci. 27, 1177–1186. https://doi.org/10.1111/jvs.12447 (2016).Article 

    Google Scholar 
    Speed, J. D. M., Austrheim, G., Hester, A. J. & Mysterud, A. Elevational advance of alpine plant communities is buffered by herbivory. J. Veg. Sci. 23, 617–625. https://doi.org/10.1111/j.1654-1103.2012.01391.x (2012).Article 

    Google Scholar 
    Grytnes, J. A. et al. Identifying the driving factors behind observed elevational range shifts on European mountains. Global Ecol. Biogeogr. 23, 876–884. https://doi.org/10.1111/geb.12170 (2014).Article 

    Google Scholar 
    Johnson, D. R., Ebert-May, D., Webber, P. J. & Tweedie, C. E. Forecasting alpine vegetation change using repeat sampling and a novel modeling approach. Ambio 40, 693. https://doi.org/10.1007/s13280-011-0175-z (2011).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Amagai, Y., Kudo, G. & Sato, K. Changes in alpine plant communities under climate change: Dynamics of snow-meadow vegetation in northern Japan over the last 40 years. Appl. Veg. Sci. 21, 561–571. https://doi.org/10.1111/avsc.12387 (2018).Article 

    Google Scholar 
    Crimmins, S. M., Dobrowski, S. Z., Greenberg, J. A., Abatzoglou, J. T. & Mynsberge, A. R. Changes in climatic water balance drive downhill shifts in plant species’ optimum elevations. Science 331, 324–327. https://doi.org/10.1126/science.1199040 (2011).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Engler, R. et al. 21st century climate change threatens mountain flora unequally across Europe. Global Change Biol. 17, 2330–2341. https://doi.org/10.1111/j.1365-2486.2010.02393.x (2011).ADS 
    Article 

    Google Scholar 
    Matteodo, M., Ammann, K., Verrecchia, E. P. & Vittoz, P. Snowbeds are more affected than other subalpine–alpine plant communities by climate change in the Swiss Alps. Ecol. Evol. 6, 6969–6982. https://doi.org/10.1002/ece3.2354 (2016).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Tingley, M. W., Monahan, W. B., Beissinger, S. R. & Moritz, C. Birds track their Grinnellian niche through a century of climate change. Proc. Natl. Acad. Sci. 106, 19637–19643. https://doi.org/10.1073/pnas.0901562106 (2009).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Cuesta, F. et al. Thermal niche traits of high alpine plant species and communities across the tropical Andes and their vulnerability to global warming. J. Biogeogr. 47, 408–420. https://doi.org/10.1111/jbi.13759 (2020).Article 

    Google Scholar 
    Hamid, M., Khuroo, A. A., Malik, A. H., Ahmad, R. & Singh, C. P. Assessment of alpine summit flora in Kashmir Himalaya and its implications for long-term monitoring of climate change impacts. J. Mt. Sci. 17, 1974–1988. https://doi.org/10.1007/s11629-019-5924-7 (2020).Article 

    Google Scholar 
    Steinbauer, K., Lamprecht, A., Semenchuk, P., Winkler, M. & Pauli, H. Dieback and expansions: Species-specific responses during 20 years of amplified warming in the high Alps. Alpine Bot. 130, 1–11. https://doi.org/10.1007/s00035-019-00230-6 (2019).Article 

    Google Scholar 
    Noroozi, J. et al. Hotspots within a global biodiversity hotspot-areas of endemism are associated with high mountain ranges. Sci. Rep. 8, 10345. https://doi.org/10.1038/s41598-018-28504-9 (2018).ADS 
    CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Testolin, R. et al. Global patterns and drivers of alpine plant species richness. Global Ecol. Biogeogr. 30, 12181–12231. https://doi.org/10.1111/geb.13297 (2021).Article 

    Google Scholar 
    Körner, C. in Alpine Plant Life Ch. 1. Plant ecology at high elevations, 1–22 (Springer, 2021).Smith, J. G., Sconiers, W., Spasojevic, M. J., Ashton, I. W. & Suding, K. N. Phenological changes in alpine plants in response to increased snowpack, temperature, and nitrogen. Arct. Antarct. Alp. Res. 44, 135–142. https://doi.org/10.1657/1938-4246-44.1.135 (2012).Article 

    Google Scholar 
    Körner, C. Alpine Plant Life. (Springer, 2021).Pauli, H. et al. The GLORIA field manual–standard Multi-Summit approach, supplementary methods and extra approaches. 5th edn, (GLORIA-Coordination, Austrian Academy of Sciences & University of Natural Resources and Life Sciences, 2015).Kuo, C.-C., Su, Y., Liu, H.-Y. & Lin, C.-T. Assessment of climate change effects on alpine summit vegetation in the transition of tropical to subtropical humid climate. Plant Ecol. 222, 933–951. https://doi.org/10.1007/s11258-021-01152-2 (2021).Article 

    Google Scholar 
    Suonan, J., Classen, A. T., Zhang, Z. & He, J. S. Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow. Funct. Ecol. 31, 2147–2156. https://doi.org/10.1111/1365-2435.12909 (2017).Article 

    Google Scholar 
    Lamprecht, A. et al. Changes in plant diversity in a water-limited and isolated high-mountain range (Sierra Nevada, Spain). Alpine Bot. 131, 27–39. https://doi.org/10.1007/s00035-021-00246-x (2021).Article 

    Google Scholar 
    Barthlott, W., Mutke, J., Rafiqpoor, D., Kier, G. & Kreft, H. Global centers of vascular plant diversity. Nova Acta Leopold. 92, 61–83 (2005).
    Google Scholar 
    Kier, G. et al. A global assessment of endemism and species richness across island and mainland regions. Proc. Natl. Acad. Sci. 106, 9322–9327. https://doi.org/10.1073/pnas.0810306106 (2009).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Huang, S.-F. Historical biogeography of the flora of Taiwan. J. Natl. Taiwan Museum 64, 33–63. https://doi.org/10.1111/j.1756-1051.1995.tb02123.x (2011).Article 

    Google Scholar 
    Beck, H. E. et al. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci. Data 5, 180214. https://doi.org/10.1038/sdata.2018.214 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    TCCIP. The past and future of climate in Taiwan. 1–31 (National Science and Technology Center for Disaster Reduction & Research Center for Environmental Change, Academia Sinica, New Taipei City, 2018).Central Weather Bureau. in The Typhoon Database (ed Central Weather Bureau;) (https://rdc28.cwb.gov.tw/TDB/, 2021).Henny, L., Thorncroft, C. D., Hsu, H.-H. & Bosart, L. F. Extreme rainfall in Taiwan: Seasonal statistics and trends. J. Climate https://doi.org/10.1175/jcli-d-20-0999.1 (2021).Article 

    Google Scholar 
    Tu, J.-Y. & Chou, C. Changes in precipitation frequency and intensity in the vicinity of Taiwan: Typhoon versus non-typhoon events. Environ. Res. Lett. 8, 014023. https://doi.org/10.1088/1748-9326/8/1/014023 (2013).ADS 
    Article 

    Google Scholar 
    Liang, A., Oey, L., Huang, S. & Chou, S. Long-term trends of typhoon-induced rainfall over Taiwan: In situ evidence of poleward shift of typhoons in western North Pacific in recent decades. J. Geophys. Res. Atmos. 122, 2750–2765. https://doi.org/10.1002/2017jd026446 (2017).ADS 
    Article 

    Google Scholar 
    Lee, Y.-C., Wang, C.-C., Weng, S.-P., Chen, C.-T. & Cheng, C.-T. Future projections of meteorological drought characteristics in Taiwan. Atmos. Sci. https://doi.org/10.3966/025400022019034701003 (2019).Article 

    Google Scholar 
    Kudo, G., Kawai, Y., Amagai, Y. & Winkler, D. E. Degradation and recovery of an alpine plant community: Experimental removal of an encroaching dwarf bamboo. Alpine Bot. 127, 75–83. https://doi.org/10.1007/s00035-016-0178-2 (2017).Article 

    Google Scholar 
    Richman, S. K., Levine, J. M., Stefan, L. & Johnson, C. A. Asynchronous range shifts drive alpine plant–pollinator interactions and reduce plant fitness. Global Change Biol. 26, 3052–3064. https://doi.org/10.1111/gcb.15041 (2020).ADS 
    Article 

    Google Scholar 
    Spasojevic, M. J., Bowman, W. D., Humphries, H. C., Seastedt, T. R. & Suding, K. N. Changes in alpine vegetation over 21 years: Are patterns across a heterogeneous landscape consistent with predictions? Ecosphere 4, 1–18. https://doi.org/10.1890/es13-00133.1 (2013).Article 

    Google Scholar 
    Rogora, M. et al. Assessment of climate change effects on mountain ecosystems through a cross-site analysis in the Alps and Apennines. Sci. Total Environ. 624, 1429–1442. https://doi.org/10.1016/j.scitotenv.2017.12.155 (2018).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Malanson, G. P., Resler, L. M., Butler, D. R. & Fagre, D. B. Mountain plant communities: Uncertain sentinels? Prog. Phys. Geogr. Earth Environ. 43, 521–543. https://doi.org/10.1177/0309133319843873 (2019).Article 

    Google Scholar 
    Berauer, B. J. et al. Low resistance of montane and alpine grasslands to abrupt changes in temperature and precipitation regimes. Arct Antarct. Alp. Res. 51, 215–231. https://doi.org/10.1080/15230430.2019.1618116 (2019).Article 

    Google Scholar 
    Körner, C. in Alpine Plant Life Ch. 9. Water relations, 333–383 (Springer, 2021).Cai, Y. et al. Photosynthetic response of an alpine plant, rhododendron delavayi Franch, to water stress and recovery: The role of Mesophyll conductance. Front. Plant Sci. 6, 1089. https://doi.org/10.3389/fpls.2015.01089 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Farooq, M., Wahid, A., Kobayashi, N., Fujita, D. & Basra, S. M. A. in Sustainable Agriculture (eds E. Lichtfouse et al.) 153–188 (Springer, 2009).Greenwood, S., Chen, J. C., Chen, C. T. & Jump, A. S. Temperature and sheltering determine patterns of seedling establishment in an advancing subtropical treeline. J. Veg. Sci. 26, 711–721. https://doi.org/10.1111/jvs.12269 (2015).Article 

    Google Scholar 
    Morley, P. J., Donoghue, D. N. M., Chen, J. C. & Jump, A. S. Montane forest expansion at high elevations drives rapid reduction in non-forest area, despite no change in mean forest elevation. J. Biogeogr. 47, 2405–2416. https://doi.org/10.1111/jbi.13951 (2020).Article 

    Google Scholar 
    Salick, J., Ghimire, S. K., Fang, Z., Dema, S. & Konchar, K. M. Himalayan alpine vegetation, climate change and mitigation. J. Ethnobiol. 34, 276–293. https://doi.org/10.2993/0278-0771-34.3.276 (2014).Article 

    Google Scholar 
    Winkler, M. et al. The rich sides of mountain summits–a pan-European view on aspect preferences of alpine plants. J. Biogeogr. 43, 2261–2273. https://doi.org/10.1111/jbi.12835 (2016).Article 

    Google Scholar 
    Verheyen, K. et al. Combining biodiversity resurveys across regions to advance global change research. Bioscience 67, 73–83. https://doi.org/10.1093/biosci/biw150 (2016).Article 
    PubMed 

    Google Scholar 
    Ganjurjav, H. et al. Complex responses of spring vegetation growth to climate in a moisture-limited alpine meadow. Sci. Rep. 6, 1–10. https://doi.org/10.1038/srep23356 (2016).CAS 
    Article 

    Google Scholar 
    Nagy, L., Kreyling, J., Gellesch, E., Beierkuhnlein, C. & Jentsch, A. Recurring weather extremes alter the flowering phenology of two common temperate shrubs. Int. J. Biometeorol. 57, 579–588. https://doi.org/10.1007/s00484-012-0585-z (2013).ADS 
    CAS 
    Article 
    PubMed 

    Google Scholar 
    Jump, A. S., Huang, T.-J. & Chou, C.-H. Rapid altitudinal migration of mountain plants in Taiwan and its implications for high altitude biodiversity. Ecography 35, 204–210. https://doi.org/10.1111/j.1600-0587.2011.06984.x (2012).Article 

    Google Scholar 
    Cowles, J., Boldgiv, B., Liancourt, P., Petraitis, P. S. & Casper, B. B. Effects of increased temperature on plant communities depend on landscape location and precipitation. Ecol. Evol. 8, 5267–5278. https://doi.org/10.1002/ece3.3995 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Oldfather, M. F. & Ackerly, D. D. Increases in thermophilus plants in an arid alpine community in response to experimental warming. Arct. Antarct. Alp. Res. 51, 201–214. https://doi.org/10.1080/15230430.2019.1618148 (2019).Article 

    Google Scholar 
    Shao, K.-T. Taiwan’s biodiversity research achievements over the past 10 years (2001–2011). Biodivers. Sci. https://doi.org/10.3724/sp.j.1003.2012.06123 (2012).Article 

    Google Scholar 
    Chen, J.-M., Lu, F.-C., Kuo, S.-L. & Shih, C.-F. Summer climate variability in Taiwan and associated large-scale processes. J. Meteorol. Soc. Japan 83, 499–516. https://doi.org/10.2151/jmsj.83.499 (2005).ADS 
    Article 

    Google Scholar 
    Chen, T.-C., Wang, S.-Y., Huang, W.-R. & Yen, M.-C. Variation of the East Asian summer monsoon rainfall. J. Climate 17, 744–762. https://doi.org/10.1175/1520-0442(2004)017%3c0744:voteas%3e2.0.co;2 (2004).ADS 
    Article 

    Google Scholar 
    Thornthwaite, C. W. An approach toward a rational classification of climate. Geogr. Rev. 38, 55. https://doi.org/10.2307/210739 (1948).Article 

    Google Scholar 
    Kambach, S. et al. Of niches and distributions: Range size increases with niche breadth both globally and regionally but regional estimates poorly relate to global estimates. Ecography 42, 467–477. https://doi.org/10.1111/ecog.03495 (2019).Article 

    Google Scholar 
    Luna, B. & Moreno, J. M. Range-size, local abundance and germination niche-breadth in Mediterranean plants of two life-forms. Plant Ecol. 210, 85–95. https://doi.org/10.1007/s11258-010-9740-y (2010).Article 

    Google Scholar 
    Newbold, T. Applications and limitations of museum data for conservation and ecology, with particular attention to species distribution models. Prog. Phys. Geog. 34, 3–22. https://doi.org/10.1177/0309133309355630 (2010).Article 

    Google Scholar 
    Karger, D. N., Wilson, A. M., Mahony, C., Zimmermann, N. E. & Jetz, W. Global daily 1 km land surface precipitation based on cloud cover-informed downscaling. Sci. Data 8, 307. https://doi.org/10.1038/s41597-021-01084-6 (2021).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Welham, S. J., Gezan, S. A., Clark, S. J. & Mead, A. Statistical Methods in Biology: Design and Analysis of Experiments and Regression. (Chapman and Hall/CRC, 2014).R: A Language and Environment for Statistical Computing v. 4.0.3 (2021).Beguería, S., Vicente-Serrano, S. M., Reig, F. & Latorre, B. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int. J. Climatol. 34, 3001–3023. https://doi.org/10.1002/joc.3887 (2014).Article 

    Google Scholar 
    rgbif: Interface to the Global Biodiversity Information Facility API v. 3.7.1 (2022). More

  • in

    Linking personality traits and reproductive success in common marmoset (Callithrix jacchus)

    Réale, D., Reader, S. M., Sol, D., McDougall, P. T. & Dingemanse, N. J. Integrating animal temperament within ecology and evolution. Biol. Rev. 82, 291–318 (2007).PubMed 
    Article 

    Google Scholar 
    Smith, B. R. & Blumstein, D. T. Fitness consequences of personality: A meta-analysis. Behav. Ecol. 19, 448–455 (2008).Article 

    Google Scholar 
    Gasparini, C., Speechley, E. M. & Polverino, G. The bold and the sperm: Positive association between boldness and sperm number in the guppy. R. Soc. Open Sci. 6, 190474 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Jokela, M., Alvergne, A., Pollet, T. V. & Lummaa, V. Reproductive behavior and personality traits of the five factor model. Eur. J. Pers. 25, 487–500 (2011).Article 

    Google Scholar 
    Schuett, W., Dall, S. R. X. & Royle, N. J. Pairs of zebra finches with similar ‘personalities’ make better parents. Anim. Behav. 81, 609–618 (2011).Article 

    Google Scholar 
    Vetter, S. G. et al. Shy is sometimes better: Personality and juvenile body mass affect adult reproductive success in wild boars, Sus scrofa. Anim. Behav. 115, 193–205 (2016).Article 

    Google Scholar 
    Weiss, A. Personality traits: A view from the animal kingdom. J. Pers. 86, 12–22 (2018).PubMed 
    Article 

    Google Scholar 
    Bergmüller, R. & Taborsky, M. Animal personality due to social niche specialisation. Trends Ecol. Evol. 25, 504–511 (2010).PubMed 
    Article 

    Google Scholar 
    Montiglio, P. O., Wey, T. W., Chang, A. T., Fogarty, S. & Sih, A. Correlational selection on personality and social plasticity: Morphology and social context determine behavioural effects on mating success. J. Anim. Ecol. 86, 213–226 (2017).PubMed 
    Article 

    Google Scholar 
    Wolf, M. & McNamara, J. M. On the evolution of personalities via frequency-dependent selection. Am. Nat. 179, 679–692 (2012).PubMed 
    Article 

    Google Scholar 
    Munson, A. A., Jones, C., Schraft, H. & Sih, A. You’re just my type: Mate choice and behavioral types. Trends Ecol. Evol. 35, 823–833 (2020).PubMed 
    Article 

    Google Scholar 
    Muller, H. & Chittka, L. Animal personalities: The advantage of diversity. Curr. Biol. 18, 961–963 (2008).Article 
    CAS 

    Google Scholar 
    Biro, P. A. & Stamps, J. A. Are animal personality traits linked to life-history productivity?. Trends Ecol. Evol. 23, 361–368 (2008).PubMed 
    Article 

    Google Scholar 
    Dingemanse, N. J., Both, C., Drent, P. J. & Tinbergen, J. M. Fitness consequences of avian personalities in a fluctuating environment. Proc. R. Soc. B 271, 847–852 (2004).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Boon, A. K., Réale, D. & Boutin, S. The interaction between personality, offspring fitness and food abundance in North American red squirrels. Ecol. Lett. 10, 1094–1104 (2007).PubMed 
    Article 

    Google Scholar 
    Nicolaus, M., Tinbergen, J. M., Ubels, R., Both, C. & Dingemanse, N. J. Density fluctuations represent a key process maintaining personality variation in a wild passerine bird. Ecol. Lett. 19, 478–486 (2016).PubMed 
    Article 

    Google Scholar 
    Altschul, D. M. et al. Personality links with lifespan in chimpanzees. eLife 7, e33781 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Réale, D., Martin, J., Coltman, D. W., Poissant, J. & Festa-Bianchet, M. Male personality, life-history strategies and reproductive success in a promiscuous mammal. J. Evol. Biol. 22, 1599–1607 (2009).PubMed 
    Article 

    Google Scholar 
    Brent, L. J. N. et al. Personality traits in rhesus macaques (Macaca mulatta) are heritable but do not predict reproductive output. Int. J. Primatol. 35, 188–209 (2014).PubMed 
    Article 

    Google Scholar 
    Rangassamy, M., Dalmas, M., Féron, C., Gouat, P. & Rödel, H. G. Similarity of personalities speeds up reproduction in pairs of a monogamous rodent. Anim. Behav. 103, 7–15 (2015).Article 

    Google Scholar 
    Schuett, W., Tregenza, T. & Dall, S. R. X. Sexual selection and animal personality. Biol. Rev. 85, 217–246 (2010).PubMed 
    Article 

    Google Scholar 
    Carlstead, K., Fraser, J., Bennett, C. & Kleiman, D. G. Black rhinoceros (Diceros bicornis) in US zoos: II. Behavior, breeding success, and mortality in relation to housing facilities. Zoo Biol. 18, 35–52 (1999).Article 

    Google Scholar 
    Martin-Wintle, M. S. et al. Do opposites attract? Effects of personality matching in breeding pairs of captive giant pandas on reproductive success. Biol. Conserv. 207, 27–37 (2017).Article 

    Google Scholar 
    Fox, R. A. & Millam, J. R. Personality traits of pair members predict pair compatibility and reproductive success in a socially monogamous parrot breeding in captivity. Zoo Biol. 33, 166–172 (2014).PubMed 
    Article 

    Google Scholar 
    Choi, S., Grocutt, E., Erlandsson, R. & Angerbjörn, A. Parent personality is linked to juvenile mortality and stress behavior in the arctic fox (Vulpes lagopus). Behav. Ecol. Sociobiol. 73, 162 (2019).Article 

    Google Scholar 
    Kappeler, P. M. & van Schaik, C. P. Evolution of primate social systems. Int. J. Primatol. 23, 707–740 (2002).Article 

    Google Scholar 
    Tardif, S. D. et al. Reproduction in captive common marmosets (Callithrix jacchus). Comp. Med. 53, 364–368 (2003).CAS 
    PubMed 

    Google Scholar 
    Marini, R., Wachtman, L., Tardif, S., Mansfield, K. & Fox, J. The Common Marmoset in Captivity and Biomedical Research (Academic Press, 2019). https://doi.org/10.1016/C2016-0-00861-6.Book 

    Google Scholar 
    Arruda, M. D. F., Yamamoto, M. E., Pessoa, D. M. A. & Araujo, A. Taxonomy and Natural History. In The Common Marmoset in Captivity and Biomedical Research (eds Marini, R. et al.) 3–15 (Academic Press, 2019). https://doi.org/10.1016/B978-0-12-811829-0.00001-7.Chapter 

    Google Scholar 
    Buchanan-Smith, H. M. Marmosets and tamarins. In The UFAW Handbook on the Care and Management of Laboratory and Other Research Animals (eds Hubrecht, R. & Kirkwood, J.) (Wiley-Blackwell, 2010). https://doi.org/10.1002/9781444318777.ch36.Chapter 

    Google Scholar 
    Smucny, D. A. et al. Reproductive output, maternal age, and survivorship in captive common marmoset females (Callithrix jacchus). Am. J. Primatol. 64, 107–121 (2004).PubMed 
    Article 

    Google Scholar 
    Ash, H. & Buchanan-Smith, H. M. Long-term data on reproductive output and longevity in captive female common marmosets (Callithrix jacchus). Am. J. Primatol. 76, 1062–1073 (2014).PubMed 
    Article 

    Google Scholar 
    Frye, B. M. et al. After short interbirth intervals, captive callitrichine monkeys have higher infant mortality. iScience 25, 103724 (2022).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McCoy, D. E. et al. A comparative study of litter size and sex composition in a large dataset of callitrichine monkeys. Am. J. Primatol. 81, e23038 (2019).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Jaquish, C. E., Tardif, S. D. & Cheverud, J. M. Interactions between infant growth and survival: Evidence for selection on age-specific body weight in captive common marmosets (Callithrix jacchus). Am. J. Primatol. 42, 269–280 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tardif, S. D. & Jaquish, C. E. Number of ovulations in the marmoset monkey (Callithrix jacchus): Relation to body weight, age and repeatability. Am. J. Primatol. 42, 323–329 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Poole, T. B. & Evans, R. G. Reproduction, infant survival and productivity of a colony of common marmosets (Callithrix jacchus jacchus). Lab. Anim. 16, 88–97 (1982).CAS 
    PubMed 
    Article 

    Google Scholar 
    Tardif, S. D., Richter, C. B. & Carson, R. L. Effects of sibling-rearing experience on future reproductive success in two species of callitrichidae. Am. J. Primatol. 6, 377–380 (1984).PubMed 
    Article 

    Google Scholar 
    Rothe, H., Koenig, A. & Darms, K. Infant survival and number of helpers in captive groups of common marmosets (Callithrix jacchus). Am. J. Primatol. 30, 131–137 (1993).CAS 
    PubMed 
    Article 

    Google Scholar 
    Koski, S. E., Buchanan-Smith, H. M., Burkart, J. M., Bugnyar, T. & Weiss, A. Common marmoset (Callithrix jacchus) personality. J. Comp. Psychol. 131, 326–336 (2017).PubMed 
    Article 

    Google Scholar 
    Šlipogor, V., Burkart, J. M., Martin, J. S., Bugnyar, T. & Koski, S. E. Personality method validation in common marmosets (Callithrix jacchus): Getting the best of both worlds. J. Comp. Psychol. 134, 52–70 (2020).PubMed 
    Article 

    Google Scholar 
    Weiss, A., Yokoyama, C., Hayashi, T. & Inoue-Murayama, M. Personality, subjective well-being, and the serotonin 1a receptor gene in common marmosets (Callithrix jacchus). PLoS ONE 16, e0238663 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Freeman, H., Gosling, S. D. & Schapiro, S. J. Comparison of methods for assessing personality in nonhuman primates. In Personality and Temperament in Nonhuman Primates (eds Weiss, A. et al.) 17–40 (Springer, 2011).Chapter 

    Google Scholar 
    Finkenwirth, C. & Burkart, J. M. Why help? Relationship quality, not strategic grooming predicts infant-care in group-living marmosets. Physiol. Behav. 193, 108–116 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Haines, J. A. et al. Sex- and context-specific associations between personality and a measure of fitness but no link with life history traits. Anim. Behav. 167, 23–39 (2020).Article 

    Google Scholar 
    Carlstead, K., Mellen, J. & Kleiman, D. G. Black rhinoceros (Diceros bicornis) in US zoos: I. Individual behavior profiles and their relationship to breeding success. Zoo Biol. 18, 17–34 (1999).Article 

    Google Scholar 
    Berg, V., Lummaa, V., Lahdenperä, M., Rotkirch, A. & Jokela, M. Personality and long-term reproductive success measured by the number of grandchildren. Evol. Hum. Behav. 35, 533–539 (2014).Article 

    Google Scholar 
    Silva, H. P. A. & Sousa, M. B. C. The pair-bond formation and its role in the stimulation of reproductive function in female common marmosets (Callithrix jacchus). Int. J. Primatol. 18, 387–400 (1997).Article 

    Google Scholar 
    Cavanaugh, J., Mustoe, A. C., Taylor, J. H. & French, J. A. Oxytocin facilitates fidelity in well-established marmoset pairs by reducing sociosexual behavior toward opposite-sex strangers. Psychoneuroendocrinology 49, 1–10 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Andersen, I. L., Nævdal, E. & Bøe, K. E. Maternal investment, sibling competition, and offspring survival with increasing litter size and parity in pigs (Sus scrofa). Behav. Ecol. Sociobiol. 65, 1159–1167 (2011).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Johnstone-Yellin, T. L., Shipley, L. A., Myers, W. L. & Robinson, H. S. To twin or not to twin? Trade-offs in litter size and fawn survival in mule deer. J. Mammal. 90, 453–460 (2009).Article 

    Google Scholar 
    Ariyomo, T. O. & Watt, P. J. The effect of variation in boldness and aggressiveness on the reproductive success of zebrafish. Anim. Behav. 83, 41–46 (2012).Article 

    Google Scholar 
    Patterson, L. D. & Schulte-Hostedde, A. I. Behavioural correlates of parasitism and reproductive success in male eastern chipmunks, Tamias striatus. Anim. Behav. 81, 1129–1137 (2011).Article 

    Google Scholar 
    Mutzel, A., Dingemanse, N. J., Araya-Ajoy, Y. G. & Kempenaers, B. Parental provisioning behaviour plays a key role in linking personality with reproductive success. Proc. R. Soc. B 280, 20131019 (2013).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Costa, T. S. O. et al. Individual behavioral differences and health of golden-headed lion tamarins (Leontopithecus chrysomelas). Am. J. Primatol. 82, e23118 (2020).PubMed 
    Article 

    Google Scholar 
    Harrison, P. M. et al. Personality-dependent spatial ecology occurs independently from dispersal in wild burbot (Lota lota). Behav. Ecol. 26, 483–492 (2015).Article 

    Google Scholar 
    Tardif, S. D., Power, M., Oftedal, O. T., Power, R. A. & Layne, D. G. Lactation, maternal behavior and infant growth in common marmoset monkeys (Callithrix jacchus): Effects of maternal size and litter size. Behav. Ecol. Sociobiol. 51, 17–25 (2001).Article 

    Google Scholar 
    Mills, D. A., Windle, C. P., Baker, H. F. & Ridley, R. M. Analysis of infant carrying in large, well-established family groups of captive marmosets (Callithrix jacchus). Primates 45, 259–265 (2004).PubMed 
    Article 

    Google Scholar 
    Leutenegger, W. Maternal-fetal weight relationships in primates. Folia Primatol. 20, 280–293 (1973).CAS 
    Article 

    Google Scholar 
    Schultz-Darken, N., Ace, L. & Ash, H. Behavior and behavioral management. In The Common Marmoset in Captivity and Biomedical Research (eds Marini, R. et al.) 109–117 (Academic Press, 2019). https://doi.org/10.1016/b978-0-12-811829-0.00007-8.Chapter 

    Google Scholar 
    Bardi, M. & Petto, A. J. Parental failure in captive common marmosets (Callithrix jacchus): A comparison with tamarins. Folia Primatol. 73, 46–48 (2002).Article 

    Google Scholar 
    Barbosa, M. N. & da Silva Mota, M. T. Alloparental responsiveness to newborns by nonreproductive, adult male, common marmosets (Callithrix jacchus). Am. J. Primatol. 75, 145–152 (2013).PubMed 
    Article 

    Google Scholar 
    Rutherford, J. N. et al. Womb to womb: Maternal litter size and birth weight but not adult characteristics predict early neonatal death of offspring in the common marmoset monkey. PLoS ONE 16, e0252093 (2021).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Finkenwirth, C., Martins, E., Deschner, T. & Burkart, J. M. Oxytocin is associated with infant-care behavior and motivation in cooperatively breeding marmoset monkeys. Horm. Behav. 80, 10–18 (2016).CAS 
    PubMed 
    Article 

    Google Scholar 
    Edwards, H. A., Dugdale, H. L., Richardson, D. S., Komdeur, J. & Burke, T. Extra-pair parentage and personality in a cooperatively breeding bird. Behav. Ecol. Sociobiol. 72, 37 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Schürch, R. & Heg, D. Variation in helper type affects group stability and reproductive decisions in a cooperative breeder. Ethology 116, 257–269 (2010).Article 

    Google Scholar 
    Class, B. & Dingemanse, N. J. A variance partitioning perspective of assortative mating: Proximate mechanisms and evolutionary implications. J. Evol. Biol. 35, 483–490 (2022).PubMed 
    Article 

    Google Scholar 
    Scherer, U., Godin, J. G. J. & Schuett, W. Do female rainbow kribs choose males on the basis of their apparent aggression and boldness? A non-correlational mate choice study. Behav. Ecol. Sociobiol. 74, 34 (2020).Article 

    Google Scholar 
    Schuett, W., Godin, J.-G.J. & Dall, S. R. X. Do female zebra finches, Taeniopygia guttata, choose their mates based on their ‘personality’?. Ethology 117, 908–917 (2011).Article 

    Google Scholar 
    Ophir, A. G., Crino, O. L., Wilkerson, Q. C., Wolff, J. O. & Phelps, S. M. Female-directed aggression predicts paternal behavior, but female prairie voles prefer affiliative males to paternal males. Brain. Behav. Evol. 71, 32–40 (2008).PubMed 
    Article 

    Google Scholar 
    Lazaro-Perea, C. Intergroup interactions in wild common marmosets, Callithrix jacchus: Territorial defence and assessment of neighbours. Anim. Behav. 62, 11–21 (2001).Article 

    Google Scholar 
    Koski, S. E. & Burkart, J. M. Common marmosets show social plasticity and group-level similarity in personality. Sci. Rep. 5, 8878 (2015).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Norman, M., Rowden, L. J. & Cowlishaw, G. Potential applications of personality assessments to the management of non-human primates: A review of 10 years of study. PeerJ 9, e12044 (2021).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Gorsuch, R. L. Factor Analysis 2nd edn. (Lawrence Erlbaum Associates, 1983).MATH 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2020).Bates, D., Mächler, M., Bolker, B. M. & Walker, S. C. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).Article 
    CAS 

    Google Scholar 
    Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A. & Smith, G. M. Mixed Effects Models and Extensions in Ecology with R (Springer, 2009). https://doi.org/10.1007/978-0-387-87458-6.Book 
    MATH 

    Google Scholar 
    Christensen, R. H. B. Ordinal—Regression Models for Ordinal Data. R package version 2019.4-25. (2019).Burnham, K. P. & Anderson, D. R. Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (Springer-Verlag, 2002). https://doi.org/10.1007/b97636.Book 
    MATH 

    Google Scholar 
    Bartoń, K. Mu-MIn: Multi-model inference. R package version 2019 1.43.6. (2019).Grueber, C. E., Nakagawa, S., Laws, R. J. & Jamieson, I. G. Multimodel inference in ecology and evolution: Challenges and solutions. J. Evol. Biol. 24, 699–711 (2011).CAS 
    PubMed 
    Article 

    Google Scholar 
    Richards, S. A. Dealing with overdispersed count data in applied ecology. J. Appl. Ecol. 45, 218–227 (2008).Article 

    Google Scholar 
    Hartig, F. DHARMa: Residual Diagnostics for Hierarchical (Multi-Level/Mixed) Regression Models. R package version 0.2.7 (2020).Lüdecke, D. sjPlot: Data Visualization for Statistics in Social Science. R package version 2.8.2 (2020)du Sert, N. P. et al. Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0. PLoS Biol. 18, e3000411 (2020).Article 
    CAS 

    Google Scholar  More

  • in

    Soil carbon stocks in forest-tundra ecotones along a 500 km latitudinal gradient in northern Norway

    Pan, Y. et al. A large and persistent carbon sink in the world’s forests. Science 333, 988–993 (2011).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Tarnocai, C. et al. Soil organic carbon pools in the northern circumpolar permafrost region. Glob. Biogeochem. Cycles 23, 1–11 (2009).Article 
    CAS 

    Google Scholar 
    Davidson, E. A. & Janssens, I. A. Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440, 165–173 (2006).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Wardle, D. A., Nilsson, M. C., Zackrisson, O. & Gallet, C. Determinants of litter mixing effects in a Swedish boreal forest. Soil Biol. Biochem. 35, 827–835 (2003).CAS 
    Article 

    Google Scholar 
    Moen, J., Cairns, D. M. & Lafon, C. W. Factors structuring the treeline ecotone in Fennoscandia. Plant Ecol. Divers. 1, 77–87 (2008).Article 

    Google Scholar 
    Sjögersten, S. & Wookey, P. A. Climatic and resource quality controls on soil respiration across a forest-tundra ecotone in Swedish Lapland. Soil Biol. Biochem. 34, 1633–1646 (2002).Article 

    Google Scholar 
    Sjögersten, S., Turner, B. L., Mahieu, N., Condron, L. M. & Wookey, P. A. Soil organic matter biochemistry and potential susceptibility to climatic change across the forest-tundra ecotone in the Fennoscandian mountains. Glob. Change Biol. 9, 759–772 (2003).ADS 
    Article 

    Google Scholar 
    IPCC. IPCC report global warming of 1.5 °C. Ipcc Sr15. 2, 17–20 (2018).
    Google Scholar 
    Hobbie, S. E., Nadelhoffer, K. J. & Högberg, P. A synthesis: The role of nutrients as constraints on carbon balances in boreal and arctic regions. Plant Soil 242, 163–170 (2002).CAS 
    Article 

    Google Scholar 
    DeLuca, T. H. & Boisvenue, C. Boreal forest soil carbon: Distribution, function and modelling. Forestry 85, 161–184 (2012).Article 

    Google Scholar 
    Hansson, A., Dargusch, P. & Shulmeister, J. A review of modern treeline migration, the factors controlling it and the implications for carbon storage. J. Mt. Sci. 18, 291–306 (2021).Article 

    Google Scholar 
    Sjögersten, S. & Wookey, P. A. The impact of climate change on ecosystem carbon dynamics at the Scandinavian mountain birch forest-tundra heath ecotone. Ambio 38, 2–10 (2009).PubMed 
    Article 

    Google Scholar 
    Rustad, L. E. et al. A meta-analysis of the response of soil respiration, net nitrogen mineralization, and aboveground plant growth to experimental ecosystem warming. Oecologia 126, 543–562 (2001).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Kullman, L. Rapid recent range-margin rise of tree and shrub species in the Swedish Scandes. J. Ecol. 90, 68–77 (2002).Article 

    Google Scholar 
    Lloyd, A. H. & Fastie, C. L. Recent changes in treeline forest distribution and structure in interior Alaska. Ecoscience 10, 176–185 (2003).Article 

    Google Scholar 
    Truong, C., Palmé, A. E. & Felber, F. Recent invasion of the mountain birch Betula pubescens ssp. tortuosa above the treeline due to climate change: Genetic and ecological study in northern Sweden. J. Evol. Biol. 20, 369–380 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Danby, R. K. & Hik, D. S. Variability, contingency and rapid change in recent subarctic alpine tree line dynamics. J. Ecol. 95, 352–363 (2007).Article 

    Google Scholar 
    Harsch, M. A., Hulme, P. E., McGlone, M. S. & Duncan, R. P. Are treelines advancing? A global meta-analysis of treeline response to climate warming. Ecol. Lett. 12, 1040–1049 (2009).PubMed 
    Article 

    Google Scholar 
    Tingstad, L., Olsen, S. L., Klanderud, K., Vandvik, V. & Ohlson, M. Temperature, precipitation and biotic interactions as determinants of tree seedling recruitment across the tree line ecotone. Oecologia 179, 599–608 (2015).ADS 
    PubMed 
    Article 

    Google Scholar 
    Hofgaard, A. Inter-Relationships between treeline position, species diversity, land use and climate change in the Central Scandes Mountains of Norway. Annika Hofgaard Source Glob. Ecol. Biogeogr. Lett. 6(6), 419–429 (1997).Article 

    Google Scholar 
    Olsson, E. G. A., Austrheim, G. & Grenne, S. N. Landscape change patterns in mountains, land use and environmental diversity, Mid-Norway 1960–1993. Landsc. Ecol. 15, 155–170 (2000).Article 

    Google Scholar 
    Weintraub, M. N. & Schimel, J. P. Interactions between carbon and nitrogen mineralization and soil organic matter chemistry in arctic tundra soils. Ecosystems 6, 129–143 (2003).CAS 
    Article 

    Google Scholar 
    Melillo, J. M. et al. Soil warming and carbon-cycle feedbacks to the climate system. Science 298, 2173–2176 (2002).Kammer, A. et al. Treeline shifts in the Ural mountains affect soil organic matter dynamics. Glob. Change Biol. 15, 1570–1583 (2009).ADS 
    Article 

    Google Scholar 
    Parker, T. C., Subke, J. A. & Wookey, P. A. Rapid carbon turnover beneath shrub and tree vegetation is associated with low soil carbon stocks at a subarctic treeline. Glob. Change Biol. 21, 2070–2081 (2015).ADS 
    Article 

    Google Scholar 
    Speed, J. D. M. et al. Continuous and discontinuous variation in ecosystem carbon stocks with elevation across a treeline ecotone. Biogeosciences 12, 1615–1627 (2015).ADS 
    Article 

    Google Scholar 
    Hartley, I. P. et al. A potential loss of carbon associated with greater plant growth in the European Arctic. Nat. Clim. Chang. 2, 875–879 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Yoo, K., Amundson, R., Heimsath, A. M. & Dietrich, W. E. Spatial patterns of soil organic carbon on hillslopes: Integrating geomorphic processes and the biological C cycle. Geoderma 130, 47–65 (2006).ADS 
    CAS 
    Article 

    Google Scholar 
    Zhu, M. et al. Soil organic carbon as functions of slope aspects and soil depths in a semiarid alpine region of Northwest China. CATENA 152, 94–102 (2017).CAS 
    Article 

    Google Scholar 
    Hilli, S., Stark, S. & Derome, J. Litter decomposition rates in relation to litter stocks in boreal coniferous forests along climatic and soil fertility gradients. Appl. Soil Ecol. 46, 200–208 (2010).Article 

    Google Scholar 
    Parker, T. C. et al. Exploring drivers of litter decomposition in a greening Arctic: Results from a transplant experiment across a treeline. Ecology 99, 2284–2294 (2018).PubMed 
    Article 

    Google Scholar 
    Strand, L. T., Callesen, I., Dalsgaard, L. & de Wit, H. A. Carbon and nitrogen stocks in Norwegian forest soils—The importance of soil formation, climate, and vegetation type for organic matter accumulation. Can. J. For. Res. 46, 1459–1473 (2016).CAS 
    Article 

    Google Scholar 
    Thieme, N., Bollandsås, O. M., Gobakken, T. & Næsset, E. Detection of small single trees in the forest-tundra ecotone using height values from airborne laser scanning. Can. J. Remote Sens. 37, 264–274 (2011).ADS 
    Article 

    Google Scholar 
    Mienna, I. M., Klanderud, K., Ørka, H. O., Bryn, A. & Bollandsås, O. M. Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral- and three-dimensional information from UAV -based aerial imagery. Remote Sens. Ecol. Conserv. https://doi.org/10.1002/rse2.260 (2022).Article 

    Google Scholar 
    Tveito, O. E., Bjørdal, I., Skjelvåg, A. O. & Aune, B. A GIS-based agro-ecological decision system based on gridded climatology. Meteorol. Appl. 12, 57–68 (2005).ADS 
    Article 

    Google Scholar 
    Carter, T. R. Changes in the thermal growing season in Nordic countries during the past century and prospects for the future. Agric. Food Sci. Finl. 7, 161–179 (1998).Article 

    Google Scholar 
    Abdi, H. Partial least square regression PLS-regression. Encyclopedia Res. Methods Social Sci. 792.295 (2003).Wold, S., Sjöström, M. & Eriksson, L. PLS-regression: A basic tool of chemometrics. Chemom. Intell. Lab. Syst. 58, 109–130 (2001).CAS 
    Article 

    Google Scholar 
    Liland, K. H., Mevik, B.-H., Wehrens, R. & Hiemstra, P. Package ‘ pls ’. (2021).Mevik, B.-H. & Wehrens, R. Introduction to the pls Package. Help Sect. ‘pls’ Packag. RStudio Softw. 1–23 (2015).Huang, X. et al. Soil moisture dynamics within soil profiles and associated environmental controls. CATENA 136, 189–196 (2016).Article 

    Google Scholar 
    Trap, J., Hättenschwiler, S., Gattin, I. & Aubert, M. Forest ageing: An unexpected driver of beech leaf litter quality variability in European forests with strong consequences on soil processes. For. Ecol. Manage. 302, 338–345 (2013).Article 

    Google Scholar 
    Sørensen, M. V. et al. Draining the pool? Carbon storage and fluxes in three alpine plant communities. Ecosystems 21, 316–330 (2018).Article 
    CAS 

    Google Scholar 
    Qian, H., Joseph, R. & Zeng, N. Enhanced terrestrial carbon uptake in the Northern High Latitudes in the 21st century from the Coupled Carbon Cycle Climate Model Intercomparison Project model projections. Glob. Chang. Biol. 16, 641–656 (2010).ADS 
    Article 

    Google Scholar 
    Sturm, M. et al. Snow—Shrub interactions in Arctic Tundra : A hypothesis with climatic implications. J. Clim. 14, 336–344 (2001).ADS 
    Article 

    Google Scholar 
    Grogan, P. & Jonasse, S. Ecosystem CO2 production during winter in a Swedish subarctic region: The relative importance of climate and vegetation type. Glob. Change Biol. 12, 1479–1495 (2006).ADS 
    Article 

    Google Scholar 
    Sistla, S. A. et al. Long-term warming restructures Arctic tundra without changing net soil carbon storage. Nature 497, 615–617 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Wiesmeier, M. et al. Soil organic carbon storage as a key function of soils—A review of drivers and indicators at various scales. Geoderma 333, 149–162 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Brooks, P. D. & Williams, M. W. Snowpack controls on nitrogen cycling and export in seasonally snow-covered catchments. Hydrological processes 13, 2177–2190 (1999).Broll, G. et al. Landscape mosaic in the treeline ecotone on Mt. Rodjanoaivi, Subarctic Finland. Fenn. J. Geogr. 185, 89–105 (2007).
    Google Scholar 
    Turetsky, M. R. The role of bryophytes in carbon and nitrogen cycling. Bryologist 106, 395–409 (2003).Article 

    Google Scholar  More

  • in

    Modeling geographical invasions of Solenopsis invicta influenced by land-use patterns

    This study used comprehensive surveillance data to profile RIFA invasions in time and space on an isolated island. By using this surveillance data, which were collected regularly together with information on land-use in different years, distinctions of RIFA severity can be compared, and RIFA SIRH were therefore identified. Our statistical model decomposed the spatial invasion risk into four geographic and anthropogenic factors: land-use characteristics, distances from RIFA sampling location to the nearest road, and spatial factors. For land use from 2014 to 2017, agricultural land, transportation usage, and land-use change had significantly higher odds of RIFA SIRH than natural land cover. Regarding the distance from the nearest road, RIFA invasions were most likely ( > 60%) to occur within 350 m from the nearest road on the transportation usage land. Meanwhile, it was likely ( > 60%) to have RIFA invasions within 150 m from the nearest road in areas where land-use change had occurred between 2014 and 2016. Finally, the highest risks of RIFA SIRH were identified around the pier area and the area of the earliest RIFA invasions on Kinmen. Our study provided an example showing how RIFA gradually expanded to the entire isolated island.Highest risks for agricultural land, transportation usage, and land-use changeAgricultural landThe vulnerability of agricultural lands to RIFA invasions has been reported in many studies. For example, a review by Apperson and Adams showed that RIFA often infested soybean fields in the United States28. Way and Khoo reviewed the RIFA infestation of crop plants, including sugar cane and cotton29, and indicated that crop invasion by RIFAs was a common occurrence. The study conducted by Stuhler et al. demonstrated that in unthinned patches, RIFA mounds were likely to occur in agricultural lands compared to woodlands in South Carolina30. Thus, the results of our study align with the literature in finding that agricultural land tends to be highly assailable by RIFAs.The large majority of agricultural lands on Kinmen Island include sorghum farms, peanut farms, and other food crop farms31. These farms need to be plowed or cultivated at least twice per year. Therefore, soil disturbances by humans could be the reason for the defenselessness against RIFA invasions. The potential mechanism is that soil disturbances destroy habitats for all living organisms, including RIFA. However, RIFAs reestablished their colonies faster than others30,32. Thus, RIFAs became one of the dominant species in highly disturbed areas. Higher soil disturbances associated with higher RIFA abundances were evidenced by the study by Stuhler et al.30 in which the authors compared the thinned areas to unthinned areas, identifying more RIFA mounds in thinned plots. King and Tschinkel also conducted a field experiment on different levels of soil disturbances. They demonstrated that higher numbers of RIFAs persisted at higher levels of disturbance (i.e., plowing) than at lower levels (i.e., mowing)32.Land for transportation usageThe land-use type for transportation purposes, including roads and ports (i.e., seaports and airports), was also identified as a risk factor for RIFA SIRH in this study (Table 2). Among the 1814 sampling tubes in the transportation area, there were 1768 sampling tubes for roads and 46 for ports. As most of the sampling tubes were set along roads in the present study, it could be deduced that roadsides or road cuts were at risk of being infested by RIFA. This result was in compliance with previous studies in the U.S., showing that areas beside roads such as roadsides and road margins provided suitable habitats for RIFA development11,33,34,35,36,37.Roadsides or road cuts had significant risks of RIFA SIRH in Kinmen, which could be due to frequent disturbances from vehicles. In Kinmen, most roads have only one lane or two narrow lanes. When two vehicles traveling in opposite directions pass each other, they will sometimes take turns or pull over onto the side, resulting in frequent soil disturbance. Roadsides or areas near roads are generally considered highly disturbed10,11,34,38, and narrow and disturbed areas suitable for RIFA establishment were demonstrated by Stiles and Jones12.In addition to disturbances along roads, some vehicles may also transport RIFAs in potted plants and soil. Newly-mated queens may potentially attach to the surface of vehicles and fall during transportation, further facilitating invasions near roadsides. This traffic-related dispersal process has been documented in many plant species39,40,41.Road maintenance could also be a reason for the high risks near roadsides. Road maintenance involves moving soil from one place and adding soil to construction sites. If the transported soil is contaminated by RIFAs, the maintenance areas will likely be occupied by RIFA. A case report by King et al. revealed how RIFA spread to roadsides by road maintenance32.Ports, in addition to roads, are another land type for transportation usages. Our finding was in line with previous studies showing that airports or seaports were common areas of RIFA invasion in Taiwan and neighboring countries. For example, Taoyuan International Airport was considered one of the earliest RIFA infestation locations in Taiwan42,43. RIFAs were also detected in container yards in Taiwan’s Kaohsiung commercial port in 201844. In other Asia–Pacific countries, such as China, South Korea, Japan, and Australia, RIFAs have also been reported at ports in the last decade44,45.Ports in this study consist of one seaport and one airport (Fig. 1). Based on the predicted risk of RIFA SIRH (Fig. 8a), one of the highest risk areas was around Shuitou Pier in Jincheng township (Fig. 1). The Pier area had high risks could be because it is one of the cargo container entrances on Kinmen Island. Shipping cargo containers have been suggested to facilitate the movement of RIFAs from abroad or between domestic ports42,43,44. Container yards can become infested when RIFA-contaminated cargo containers are unloaded44,46. In addition to possible contributions from cargos, the pier area had high risks of invasions, which could be due to environmental conditions. This can be supported by the risk of spatial factors, showing that the Pier area had high risks (Fig. 8c). One of the possible environmental factors could be that floating rubbish tends to accumulate in the Pier area47. Studies have shown that nonnative species, including ants, can travel with marine litter to new locations32,48,49,50,51.The Kinmen Shangyi Airport is the other cargo entrance in Kinmen (Fig. 1). Intuitionally, because of cargo containers, the airport area was expected to have risks similar to those in the pier area; however, the risks of RIFA invasions in the airport area were considerably lower (Fig. 8a). The differences in risks could be due to their cargo carrying capacities. In 2018, the airport had 6778 tons of cargo, but the pier had one million tons of cargo52,53. Differences in the types of cargo between the two locations may also play a role in invasion risks. From 2001 to 2018, the majority of goods arriving at the Pier included building stones and block stones from China53. These products have higher risks of being contaminated by RIFAs than goods such as ferrous articles and eggs arriving from the airport of Taiwan53,54.Land-use changeThe land-use change category was identified as a risk factor for RIFA SIRH in the current study. Among land-use change areas, 61.6% were natural land cover in 2014 but were converted to agricultural land, transportation areas, and artificial structures in 2017, which we designated development-related areas (Fig. 6).As previously mentioned, the reasons why the land-use change category had a high risk of RIFA invasion could be due to anthropogenic disturbances. Taking development-related areas as an example, when natural land cover such as forests are changed to other land usages, the first step may be to remove vegetation by clearcutting or plowing. These activities involve soil or habitat disturbances and could aid in the establishment of RIFA populations55. Then, if lands are changed to build houses or schools (i.e., artificial structures), soil disturbances could also occur during construction activities56. For lands that are changed to transportation usages, moving and adding RIFA-contaminated soil could occur during road construction.Effects of roads on RIFA SIRHDistances to the nearest roads were important for understanding invasion where undergoing land-use change, as well in places used as transportation lands (Fig. 7). These land-use categories share a common feature: roads. Meanwhile, agriculture lands had the greatest level of RIFA SIRH, but did not show interaction with distance to roads (Table 2). This could be because agriculture lands were far from roads as compared to land-use change and transportation lands. The median distances to roads from these three land-use categories supported this speculation. Therefore, from this study, it can be deduced that the roads could play a role to transport RIFAs to areas closer to road (i.e., land-use change and transportation). However, the effects of roads on RIFA SIRH did not appear when the areas away from roads (i.e., agricultural lands).Lowest risk in natural land coverIn the present study, natural land cover were identified as the lowest risk category of RIFA SIRH among the five land-use categories (Fig. 8d). This finding was in line with the study conducted by Brown et al., showing that a high percentage of canopy cover was associated with a low mean number of RIFAs in Texas between 2008 and 201057. In addition, Tschinkel and King investigated longleaf pine forests in Florida in 2012 and found that RIFA had difficulty establishing long-term colonies in the forest35. However, in another longleaf pine forest in Georgia, the ant survey conducted by Stuble et al. revealed that RIFAs were the predominant species in the ant community from 2006 to 200758. Wetlands also had high numbers of RIFAs. In northern Florida, Tschinkel observed that RIFA mounds clustered near pond margins11.Natural land cover in Kinmen had the lowest risk of RIFA invasions, which could be because most areas ( > 75%, data not shown) are forests. The forests are preserved and protected by the Forestry Bureau of Taiwan. Because of protection, forests can avoid most anthropogenic disturbances, such as soil excavation, which are known as one of the factors facilitating RIFA relocation32,59,60. Additionally, the forest environment is cool, humid, and shaded, which are unfavorable environmental conditions for RIFAs1,12,30,34,61,62.Implications of study findings for RIFA management in KinmenPublic communicationsTo date, the Kinmen County Animal and Plant Disease Control Center (KAPCDC) has launched a program aimed at raising public awareness of RIFAs on the island through newspapers, social media, and posters. In addition, for RIFA control, the KAPCDC has listed certified pesticides such as pyriproxyfen and lambda-cyhalothrin for the use of controlling RIFAs on agricultural lands. Nevertheless, our study documented that a greater risk of RIFA invasions still occurred on agricultural lands and lands used for transportation, suggesting communications should target owners of agricultural lands as well as the general public in future campaigns. Many individuals of the general public may not be able to identify ant species, so communications should therefore emphasize the importance of reporting any ant mounds, especially along roads. As different sociodemographic groups react to source information differently, communications have to be tailored to ages and educational levels7. For example, for students in primary school, the study by Madeira et al. showed that by teaching activities including insect specimens and short-film presentations, students increased their awareness of the importance of pest control63. For owners of agricultural lands and workers at ports, educational activities on basic RIFA knowledge and pesticide treatments with suitable communication methods may be needed. Those methods included regular face-to-face discussions on RIFA elimination strategies in the meetings of farmers’ associations or a system sharing updated materials likely to be contaminated with RIFAs64,65.RIFA control personnelTo prioritize resources, according to the findings from this study, we suggest that government staff focus on the controls within 350 m from the nearest road on transportation usage land and within 150 m from the nearest road on the areas where land-use change occurred between 2014 and 2016. The authorities could consider integrated pest management approaches, which include chemical and biological controls, to preserve the local ecosystem66.For agricultural lands, RIFA management mainly relies on awareness and reports from owners, as control personnel cannot perform inspections and intervention on private agricultural lands without the owners’ permissions, Although control personnel cannot directly perform interventions on private land, plant quarantine officers in seaports, which were a high-risk area in this study, can prevent RIFA importation by checking cargos to ensure that RIFAs are not stowaways on materials such as plants, rocks, and soil. More

  • in

    Comparison of multi-class and fusion of multiple single-class SegNet model for mapping karst wetland vegetation using UAV images

    Hu, S., Niu, Z., Chen, Y., Li, L. & Zhang, H. Global wetlands: Potential distribution, wetland loss, and status. Sci. Total Environ. 586, 319–327 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Guo, M., Li, J., Sheng, C., Xu, J. & Wu, L. A review of wetland remote sensing. Sensors 17, 777 (2017).ADS 
    PubMed Central 
    Article 

    Google Scholar 
    Mingwu, Z., Haijiang, J., Desuo, C. & Chunbo, J. The comparative study on the ecological sensitivity analysis in Huixian karst wetland, China. Procedia Environ. Sci. 2, 386–398 (2010).Article 

    Google Scholar 
    Li, Z., Jin, Z. & Li, Q. Changes in Land Use and their Effectson Soil Properties in Huixian KarstWetland System. Pol. J. Environ. Stud. 26, 699–707 (2017).Article 

    Google Scholar 
    Jiang, X., Xiong, Z., Liu, H., Liu, G. & Liu, W. Distribution, source identification, and ecological risk assessment of heavy metals in wetland soils of a river–reservoir system. Environ. Sci. Pollut. Res. 24, 436–444 (2016).Article 
    CAS 

    Google Scholar 
    Fu, B. et al. Comparison of optimized object-based RF-DT algorithm and SegNet algorithm for classifying Karst wetland vegetation communities using ultra-high spatial resolution UAV data. Int. J. Appl. Earth Obs. Geoinf. 104, 102553 (2021).
    Google Scholar 
    Xu, D. et al. Distribution, speciation, environmental risk, and source identification of heavy metals in surface sediments from the karst aquatic environment of the Lijiang River, Southwest China. Environ. Sci. Pollut. Res. 23, 9122–9133 (2016).CAS 
    Article 

    Google Scholar 
    Gao, P. et al. Spatial and temporal changes of P and Ca distribution and fractionation in soil and sediment in a karst farmland-wetland system. Chemosphere 220, 644–650 (2019).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Gil-Márquez, J. M., Barberá, J. A., Andreo, B. & Mudarra, M. Hydrological and geochemical processes constraining groundwater salinity in wetland areas related to evaporitic (karst) systems. A case study from Southern Spain. J. Hydrol. 544, 538–554 (2017).Chamberlin, C. A. et al. Mass balance implies Holocene development of a low-relief karst patterned landscape. Chem. Geol. 527, 118782 (2019).ADS 
    CAS 
    Article 

    Google Scholar 
    Watts, A. C. et al. Evidence of biogeomorphic patterning in a low-relief karst landscape. Earth Surf. Proc. Land. 39, 2027–2037 (2014).ADS 
    Article 

    Google Scholar 
    Fan, Z., Li, J., Yue, T., Zhou, X. & Lan, A. Scenarios of land cover in Karst area of Southwestern China. Environ. Earth Sci. 74, 6407–6420 (2015).Article 

    Google Scholar 
    Wang, S., Zhang, L., Zhang, H., Han, X. & Zhang, L. Spatial-temporal wetland landcover changes of poyang lake derived from landsat and HJ-1A/B data in the dry season from 1973–2019. Remote Sens. 12, 1595 (2020).ADS 
    Article 

    Google Scholar 
    Szabó, L., Deák, B., Bíró, T., Dyke, G. J. & Szabó, S. NDVI as a proxy for estimating sedimentation and vegetation spread in artificial lakes—monitoring of spatial and temporal changes by using satellite images overarching three decades. Remote Sens. 12, 1468 (2020).ADS 
    Article 

    Google Scholar 
    Malekmohammadi, B. & Rahimi Blouchi, L. Ecological risk assessment of wetland ecosystems using multi criteria decision making and geographic information system. Ecol. Indic. 41, 133–144 (2014).Article 

    Google Scholar 
    Tian, Y. et al. Monitoring invasion process of spartina alterniflora by seasonal sentinel-2 imagery and an object-based random forest classification. Remote Sens. 12, 1383 (2020).ADS 
    Article 

    Google Scholar 
    Lane, C. et al. Improved wetland classification using eight-band high resolution satellite imagery and a hybrid approach. Remote Sens. 6, 12187–12216 (2014).ADS 
    Article 

    Google Scholar 
    Betbeder, J., Rapinel, S., Corgne, S., Pottier, E. & Hubert-Moy, L. TerraSAR-X dual-pol time-series for mapping of wetland vegetation. ISPRS J. Photogramm. Remote. Sens. 107, 90–98 (2015).ADS 
    Article 

    Google Scholar 
    Franklin, S. E., Skeries, E. M., Stefanuk, M. A. & Ahmed, O. S. Wetland classification using Radarsat-2 SAR quad-polarization and Landsat-8 OLI spectral response data: A case study in the Hudson Bay Lowlands Ecoregion. Int. J. Remote Sens. 39, 1615–1627 (2017).Article 

    Google Scholar 
    Cao, J. et al. Object-based mangrove species classification using unmanned aerial vehicle hyperspectral images and digital surface models. Remote Sens. 10, 89 (2018).ADS 
    Article 

    Google Scholar 
    Liu, T. & Abd-Elrahman, A. Multi-view object-based classification of wetland land covers using unmanned aircraft system images. Remote Sens. Environ. 216, 122–138 (2018).ADS 
    Article 

    Google Scholar 
    Churches, C. E., Wampler, P. J., Sun, W. & Smith, A. J. Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data. Int. J. Appl. Earth Obs. Geoinf. 30, 203–216 (2014).ADS 

    Google Scholar 
    Gerke, M. & Xiao, J. Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification. ISPRS J. Photogramm. Remote. Sens. 87, 78–92 (2014).ADS 
    Article 

    Google Scholar 
    Maulik, U. & Chakraborty, D. Learning with transductive SVM for semisupervised pixel classification of remote sensing imagery. ISPRS J. Photogramm. Remote. Sens. 77, 66–78 (2013).ADS 
    Article 

    Google Scholar 
    Crasto, N. et al. A LiDAR-based decision-tree classification of open water surfaces in an Arctic delta. Remote Sens. Environ. 164, 90–102 (2015).ADS 
    Article 

    Google Scholar 
    O’Neil, G. L., Goodall, J. L. & Watson, L. T. Evaluating the potential for site-specific modification of LiDAR DEM derivatives to improve environmental planning-scale wetland identification using Random Forest classification. J. Hydrol. 559, 192–208 (2018).ADS 
    Article 

    Google Scholar 
    Howard, A. G. Some improvements on deep convolutional neural network based image classification. arXiv.org https://doi.org/10.48550/arXiv.1805.07836 (2013).Yao, X. et al. Land use classification of the deep convolutional neural network method reducing the loss of spatial features. Sensors 19, 2792 (2019).ADS 
    PubMed Central 
    Article 

    Google Scholar 
    Chen, Y., Fan, R., Yang, X., Wang, J. & Latif, A. Extraction of urban water bodies from high-resolution remote-sensing imagery using deep learning. Water 10, 585 (2018).Article 

    Google Scholar 
    Gu, J. et al. Recent advances in convolutional neural networks. Pattern Recogn. 77, 354–377 (2018).ADS 
    Article 

    Google Scholar 
    Srinivas, S., Subramanya, A. & Babu, R. V. Training Sparse Neural Networks. in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (IEEE, 2017).Liang, S., Lan, Y., Jiang, S., Li, Y. & Lu, Z. The activities of microbial communities in Huixian Wetland sediments under the interactive toxicity of Cu(II) and pentachloronitrobenzene. Acta Ecol. Sin. 37, 379–391 (2017).Article 

    Google Scholar 
    Feng, W. Fish diversity in huixian wetland in guangxi. Wetland Science 44, (2017).Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).MATH 
    Article 

    Google Scholar 
    Mutanga, O., Adam, E. & Cho, M. A. High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm. Int. J. Appl. Earth Obs. Geoinf. 18, 399–406 (2012).ADS 

    Google Scholar 
    van Beijma, S., Comber, A. & Lamb, A. Random forest classification of salt marsh vegetation habitats using quad-polarimetric airborne SAR, elevation and optical RS data. Remote Sens. Environ. 149, 118–129 (2014).ADS 
    Article 

    Google Scholar 
    Badrinarayanan, V., Kendall, A. & Cipolla, R. SegNet: A deep convolutional encoder-decoder architecture for image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 39, 2481–2495 (2017).PubMed 
    Article 

    Google Scholar 
    Ioffe, S. & Szegedy, C. Batch normalization: Accelerating deep network training by reducing internal covariate shift. Int. Conf. Mach. Learn. 37, 448–456 (2015).
    Google Scholar 
    Long, J., Shelhamer, E. & Darrell, T. Fully convolutional networks for semantic segmentation. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 3431–3440 (IEEE, 2015).Chen, L.-C., Barron, J. T., Papandreou, G., Murphy, K. & Yuille, A. L. semantic image segmentation with task-specific edge detection using CNNs and a discriminatively trained domain transform. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 4545–4546 (IEEE, 2016).Eigen, D. & Fergus, R. Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture. in 2015 IEEE International Conference on Computer Vision (ICCV) (IEEE, 2015).Hu, Y. et al. Deep learning classification of coastal wetland hyperspectral image combined spectra and texture features: A case study of Huanghe (Yellow) River Estuary wetland. Acta Oceanol. Sin. 38, 142–150 (2019).Article 

    Google Scholar 
    Liu, F. & Fang, M. Semantic segmentation of underwater images based on improved Deeplab. J. Marine Sci. Eng. 8, 188 (2020).Article 

    Google Scholar 
    Dronova, I. Object-based image analysis in wetland research: A review. Remote Sens. 7, 6380–6413 (2015).ADS 
    Article 

    Google Scholar 
    Zhang, Z. & Sabuncu, M. R. Generalized cross entropy loss for training deep neural networks with noisy labels. arXiv.org https://arxiv.org/abs/1805.07836 (2018).Ruder, S. An overview of gradient descent optimization algorithms. arXiv.org https://arxiv.org/abs/1609.04747 (2016).Song, S. et al. Intelligent object recognition of urban water bodies based on deep learning for multi-source and multi-temporal high spatial resolution remote sensing imagery. Sensors 20, 397 (2020).ADS 
    CAS 
    PubMed Central 
    Article 

    Google Scholar 
    Sun, G. et al. Fusion of multiscale convolutional neural networks for building extraction in very high-resolution images. Remote Sens. 11, 227 (2019).ADS 
    Article 

    Google Scholar 
    Al-Najjar, H. A. H. et al. Land cover classification from fused DSM and UAV images using convolutional neural networks. Remote Sens. 11, 1461 (2019).ADS 
    Article 

    Google Scholar 
    Villoslada, M. et al. Fine scale plant community assessment in coastal meadows using UAV based multispectral data. Ecol. Ind. 111, 105979 (2020).Article 

    Google Scholar 
    Zhao, H. & Liu, H. Multiple classifiers fusion and CNN feature extraction for handwritten digits recognition. Granul. Comput. 5, 411–418 (2019).Article 

    Google Scholar 
    Hu, K., Zhang, S. & Zhao, X. Context-based conditional random fields as recurrent neural networks for image labeling. Multimedia Tools Appl. 79, 17135–17145 (2019).Article 

    Google Scholar 
    Wang, M. et al. Assessing texture features to classify coastal wetland vegetation from high spatial resolution imagery using completed local binary patterns (CLBP). Remote Sens. 10, 778 (2018).ADS 
    Article 

    Google Scholar 
    Szantoi, Z., Escobedo, F., Abd-Elrahman, A., Smith, S. & Pearlstine, L. Analyzing fine-scale wetland composition using high resolution imagery and texture features. Int. J. Appl. Earth Obs. Geoinf. 23, 204–212 (2013).ADS 

    Google Scholar 
    Bhatnagar, S., Gill, L., Regan, S., Waldren, S. & Ghosh, B. A nested drone-satellite approach to monitoring the ecological conditions of wetlands. ISPRS J. Photogramm. Remote. Sens. 174, 151–165 (2021).ADS 
    Article 

    Google Scholar  More

  • in

    Fossoriality in desert-adapted tenebrionid (Coleoptera) larvae

    Matthews, E. G., Lawrence, J. F., Bouchard, P., Steiner, W. E. Jr. & Ślipiński, S. A. Tenebrionidae Latreille, 1802. In Handbook of Zoology. A Natural History of the Phyla of the Animal Kingdom. Vol. IV—Arthropoda: Insecta. Part 38 Coleoptera, Beetles. Vol. 2: Systematics (Part 2) (eds Leschen, R. A. B. et al.) 574–659 (Walter de Gruyter GmbH & Co, 2010).
    Google Scholar 
    Kergoat, G. J. et al. Higher-level molecular phylogeny of darkling beetles (Coleoptera: Tenebrionidae). Syst. Entomol. 39, 486–499. https://doi.org/10.1111/syen.12065 (2014).Article 

    Google Scholar 
    Bouchard, P. et al. Review of genus-group names in the family Tenebrionidae (Insecta, Coleoptera). Zookeys 26, 1–633. https://doi.org/10.3897/zookeys.1050.64217 (2021).Article 

    Google Scholar 
    Matthews, E. G. & Bouchard, P. Tenebrionid Beetles of Australia 398 (Australian Biological Resources Study, 2008).
    Google Scholar 
    Thomas, D. B. J. R. Patterns in the abundance of some tenebrionid beetles in the Mojave Desert. Environ. Entomol. 8, 568–657 (1979).Article 

    Google Scholar 
    Seely, M. K. & Louw, G. N. First approximation of the effects of rainfall on the ecology and energetics of a Namib Desert dune ecosystem. J. Arid Environ. 3, 25–54 (1980).ADS 
    Article 

    Google Scholar 
    Crawford, C. S. The community ecology of macroarthropod detritivores. In The Ecology of Desert Communities (ed. Polis, G. A.) 89–112 (The University of Arizona Press, 1991).
    Google Scholar 
    Mordkovich, V. G. Species richness, population structure and functional significance of black-beetles (Coleoptera: Tenebrionidae) in steppes of Northern Asia. Russ. Entomol. J. 11, 57–68 (2002).
    Google Scholar 
    Bartholomew, A. & El Moghrabi, J. Seasonal preference of darkling beetles (Tenebrionidae) for shrub vegetation due to high temperatures, not predation or food availability. J. Arid Environ. 156, 34–40 (2018).ADS 
    Article 

    Google Scholar 
    Cheli, G. H., Bosco, T. & Flores, G. The role of Nyctelia dorsata Fairmaire, 1905 (Coleoptera: Tenebrionidae) on litter fragmentation processes and soil biogeochemical cycles in arid Patagonia. Ann. Zool. 72, 129–134. https://doi.org/10.3161/00034541ANZ2022.72.1.011 (2022).Article 

    Google Scholar 
    Nørgaard, T. & Dacke, M. Fog-basking behaviour and water collection efficiency in Namib Desert Darkling beetles. Front. Zool. 7, 23. https://doi.org/10.1186/1742-9994-7-23 (2010).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Comanns, P. Passive water collection with the integument: Mechanisms and their biomimetic potential. J. Exp. Biol. 221, jeb153130. https://doi.org/10.1242/jeb.153130 (2018).Article 
    PubMed 

    Google Scholar 
    Doyen, J. T. Familial and subfamilial classification of the Tenebrionoidea (Coleoptera) and a revised generic classification of the Coniontini (Tentyriidae). Quest. Entomol. 8, 357–376 (1972).
    Google Scholar 
    Schulze, L. The Tenebrionidae of Southern Africa. XLII. Description of the early stages of Carchares macer Pascoe and Herpiscus sommeri Solier with a discussion of some phylogenetic aspects arising from the incongruities of adult and larval systematics. Sci. Pap. Namib Desert Res. Stn. 53, 139–149 (1969).
    Google Scholar 
    Kamiński, M. J. et al. Reevaluation of Blapimorpha and Opatrinae: Addressing a major phylogeny-classification gap in darkling beetles (Coleoptera: Tenebrionidae: Blaptinae). Syst. Entomol. 46, 140–156. https://doi.org/10.1111/syen.12453 (2021).Article 

    Google Scholar 
    Skopin, N. G. [Larvae of the subfamily Pimeliinae (Coleoptera, Tenebrionidae)]. Lichinki podsemeystva Pimeliinae (Coleoptera, Tenebrionidae). Trudy Nauchno-Issledovatelskogo Instituta Zashchity Rastenii Kazakhstanskoy Akademii Selskokhozyastvennykh Nauk 7, 191–298 (1962).
    Google Scholar 
    Skopin, N. G. Die Larven der Tenebrioniden des Tribus Pycnocerini (Coleoptera, Heteromera). Ann. Museé R. l’Afrique Centrale 127, 1–35 (1964).
    Google Scholar 
    Iwan, D. & Bečvář, S. Description of the early stages of Anomalipus plebejus plebejulus (Coleoptera: Tenebrionidae) from Zimbabwe with notes on the classifcation of the Opatrinae. Eur. J. Entomol. 97, 403–412 (2000).Article 

    Google Scholar 
    Koch, C. Monograph of the Tenebrionidae of southern Africa Vol I (Tentyriinae, Molurini Trachynotina: Somaticus Hope). Transvaal Mus. Mem. 7, 242 (1955).
    Google Scholar 
    Kergoat, G. J. Cretaceous environmental changes led to high extinction rates in a hyperdiverse beetle family. BMC Evol. Biol. 14, 220. https://doi.org/10.1186/s12862-014-0220-1 (2014).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Smith, A. D., Dornburg, R. & Wheeler, Q. D. Larvae of the genus Eleodes (Coleoptera, Tenebrionidae): Matrix-based descriptions, cladistic analysis, and key to late instars. Zookeys 415, 217–268 (2014).Article 

    Google Scholar 
    Kamiński, M. J. et al. Immature stages of beetles representing the ‘Opatrinoid’ clade (Coleoptera: Tenebrionidae): An overview of current knowledge of the larval morphology and some resulting taxonomic notes on Blapstinina. Zoomorphology 138, 349–370. https://doi.org/10.1007/s00435-019-00443-7 (2019).Article 

    Google Scholar 
    Rasa, O. A. E. Bechavioural adaptations to moisture as an environmental constraint in a nocturnal burrow-linhabiting Kalahari detritivore Parastizopus amraticpes Peringuey (Coleoptera: Tenebrionidae). Koedoe 37(1), 57–66 (1994).Article 

    Google Scholar 
    Rasa, O. A. E. Ecological factors influencing burrow location, group size and mortality in a nocturnal fossorial Kalahari detritivore, Parastizopus armaticeps Peringuey (Coleoptera: Tenebrionidae). J. Arid Environ. 29, 353–365 (1995).ADS 
    Article 

    Google Scholar 
    Fabricius, J. C. Supplementum Entomologia Systematica. (Impensis CG Proft, 1978).Péringuey, L. Fourth contribution to the South African coleopterous fauna. Description of new Coleoptera in the South African Museum. Trans. S. Afr. Philos. Soc. 6, 95–136 (1892).Article 

    Google Scholar 
    Endrody-Younga, S. A revision of the subtribe Gonopina (Coleoptera: Tenebrionidae: Opatrinae: Platynotini). Ann. Transvaal Mus. 37, 1–54 (2000).
    Google Scholar 
    Kamiński, M. J. Notes on species diversity patterns in Stizopina (Coleoptera: Tenebrionidae), with description of a new genus from Nama Karoo. Ann. Zool. 65, 131–148. https://doi.org/10.3161/00034541ANZ2015.65.2.002 (2015).Article 

    Google Scholar 
    Schulze, L. The Tenebrionidae of Southern Africa. XXXVIII. On the morphology of the larvae of some Stizopina (Coleoptera: Opatrini). Sci. Pap. Namib Desert Res. Stn. 19, 1–23 (1963).
    Google Scholar 
    Schulze, L. A review of silk production and spinning activities in Arthropoda with special reference to spinning in Tenebrionid larvae (Coleoptera) and Brown, J. M. M.: A chromatographic analysis of Tenebrionid silk. Mem. Transvaal Mus. 51, 409–410 (1975).
    Google Scholar 
    Rasa, O. A. E. & Endrödy-Younga, S. Intergeneric associations of stizopinid tenebrionids relative to their geographical distribution (Coleoptera: Tenebrionidae: Opatrini: Stitzopina). Afr. Entomol. 5, 231–239 (1997).
    Google Scholar 
    Kamiński, M. J., Raś, M., Steiner, W. E. & Iwan, D. Immature stages of beetles representing the ‘Opatrinoid’ clade (Coleoptera: Tenebrionidae): An overview of current knowledge of the pupal morphology. Ann. Zool. 68, 825–836. https://doi.org/10.3161/00034541ANZ2018.68.4.006 (2018).Article 

    Google Scholar 
    Doyen, J. T. The skeletal anatomy of Tenebrio molitor (Coleoptera: Tenebrionidae). Ann. Entomol. Soc. Am. 5, 103–150 (1966).
    Google Scholar 
    Ohde, T., Yaginuma, T. & Niimi, T. Insect morphological diversification through the modification of wing serial homologs. Science 340, 495 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Zhu, J. Y., Yang, P., Zhang, Z., Wu, G. X. & Yang, B. Transcriptomic immune response of Tenebrio molitor pupae to parasitization by Scleroderma guani. PLoS ONE 8, e54411 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Raś, M., Iwan, D. & Kamiński, M. J. Tracheal system in post-embryonic development of holometabolous insects: A case study using mealworm beetle. J. Anat. 232, 997–1015. https://doi.org/10.1111/joa.12808 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Kwon, G. T. et al. Mealworm larvae (Tenebrio molitor L.) exuviae as a novel prebiotic material for BALB/c mouse gut microbiota. Food Sci. Biotechnol. 29(4), 531–537. https://doi.org/10.1007/s10068-019-00699-1 (2019).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Machona, O., Chidzwondo, F. & Mangoyi, R. Tenebrio molitor: Possible source of polystyrene-degrading bacteria. BMC Biotechnol. 22, 2. https://doi.org/10.1186/s12896-021-00733-3 (2022).CAS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Jösting, E. A. Die Innervierung des Skelettmuskelsystems des Mehlwurms (Tenebrio molitor L., Larve). Zool. Jb. Anat. 67, 381–460 (1942).
    Google Scholar 
    Burakowski, B., Mroczkowski, M. & Stefańska, J. Chrząszcze: Coleoptera. Cucujoidea, Część 3. Katalog Fauny Polski, XXIII, 14 (1987).Schulze, L. The Tenebrionidae of southern Africa. XXXIII. Description of the larvae of Gonopus tibialis Fabricius and Gonopus agrestis Fahraeus (Gonopina, sensu Koch 1956). Cimbebasia 5, 1–12 (1962).
    Google Scholar 
    Lawrence, J. F., Pollock, D. A. & Ślipiński, A. Tenebrionoidea. In Handbook of Zoology. A Natural History of the Phyla of the Animal kingdom, Vol. IV. Arthropoda: Insecta (eds Leschen, R. A. B. et al.) 487–659 (Walter de Gruyter, 2010).
    Google Scholar 
    Lawrence, J. F. et al. Phylogeny of the Coleoptera based on morphological characters of adults and larvae. Ann. Zool. 61(1), 1–217 (2011).Article 

    Google Scholar 
    Beutel, R. G. & Friedrich, F. Comparative study of larvae of Tenebrionoidea (Coleoptera: Cucujiformia). Eur. J. Entomol. 102, 241–264 (2005).Article 

    Google Scholar 
    Fredrich, F. & Beutel, R. G. The thorax of Zorotypus (Hexapoda, Zoraptera) and a new nomenclature for the musculature of Neoptera. Arthropod Struct. Dev. 37, 29–54 (2008).Article 

    Google Scholar 
    Beutel, R. G., Friedrich, F., Yang, X.-K. & Ge, S.-Q. Insect Morphology and Phylogeny: A Textbook for Students of Entomology 515 (Walter de Gruyter, 2014).
    Google Scholar 
    Aibekova, L. et al. The skeletomuscular system of the mesosoma of Formica rufa workers (Hymenoptera: Formicidae). Insect Syst. Divers. 6(2), 1–26. https://doi.org/10.1093/isd/ixac002 (2022).Article 

    Google Scholar 
    Raś, M. Digging adaptations in psammophilous beetle larvae. Harvard Dataverse https://doi.org/10.7910/DVN/NNAETE (2022).SkyScan. Method Notes, Skyscan 1172 Desktop Micro-CT (Skyscan, 2008).
    Google Scholar 
    R Core Team. 2020. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020) https://www.R-project.org/.Sokal, R. R. & Rohlf, F. J. Biometry 937 (W.H. Freeman, 2011).
    Google Scholar 
    Cloudsley-Thompson, J. L. Terrestrial animals in dry heat: Arthropods. In Handbook of Physiology. Section 4: Adaptation to the Environment 414–436 (American Physiological Society, 1964).
    Google Scholar 
    Cloudsley-Thompson, J. L. Adaptations of Arthropoda to arid environments. Annu. Rev. Entomol. 20, 261–283. https://doi.org/10.1146/annurev.en.20.010175.001401 (1975).CAS 
    Article 
    PubMed 

    Google Scholar 
    Draney, M. L. The subelytral cavity of desert tenebrionids. Fla. Entomol. 76, 539–549 (1993).Article 

    Google Scholar 
    Duncan, F. D. The role of the subelytral cavity in water loss in the flightless dung beetle, Circellium bacchus (Coleoptera: Scarabaeinae). Eur. J. Entomol. 99(2), 253–258. https://doi.org/10.14411/eje.2002.034 (2002).Article 

    Google Scholar 
    Endrödy-Younga, S. & Tschinkel, W. Estimation of population size and dispersal in Anomalipus mastodon Fåhraeus, 1870 (Coleoptera: Tenebrionidae: Platynotini). Ann. Transvaal Mus. 36(4), 21–30 (1993).
    Google Scholar 
    Iwan, D. Insecta Coleoptera Tenebrionidae Pedinini Platynotina. Vol. 93 of Faune de Madagascar 178 (Editions Quae, 2010).
    Google Scholar 
    Wallwork, J. A. Desert Soil Fauna 296 (Praeger Publication, 1982).
    Google Scholar 
    Iwan, D. Oviviparity in tenebrionid beetles of the melanocratoid Platynotina (Coleoptera: Tenebrionidae: Platynotini) from Madagascar with notes on the viviparous beetles. Ann. Zool. 50, 15–25 (2000).
    Google Scholar 
    Kaufmann, T. Observations on some factors which influence aggregated by Blaps sulcata in Israel. Ann. Entomol. Soc. Am. 59, 660–664 (1966).Article 

    Google Scholar 
    Kiihnelt, G. On the biology and temperature accommodation of Lepidochora argentogrisea Koch. Sci. Pap. Namib Desert Res. Stn. 51, 121–122 (1969).
    Google Scholar 
    Hamilton, W. J. Competition and thermoregulatory behaviour of the Namib desert tenebrionid beetle genus Cardiosis. Ecology 52, 810–822 (1971).Article 

    Google Scholar 
    Watt, J. A revised subfamily classifcation of Tenebrionidae (Coleoptera). N. Z. J. Zool. 11, 381–452 (1974).Article 

    Google Scholar 
    Burakowski, B. Laboratory methods for rearing soil beetles (Coleoptera). Memorab. Zool. 46, 1–66 (1993).
    Google Scholar 
    De Block, M. & Stoks, R. Fitness effects from egg to reproduction: Bridging the life history transition. Ecology 86, 185–197 (2005).Article 

    Google Scholar 
    Pechenik, J. A. Larval experience and latent effects: Metamorphosis is not a new beginning. Integr. Comp. Biol. 46, 323–333 (2006).PubMed 
    Article 

    Google Scholar 
    Doyen, J. T. Reconstitution of Coelometopini, Tenebrionini and related tribes of America north of Colombia (Coleoptera: Tenebrionidae). J. N. Y. Entomol. Soc. 97, 277–304 (1989).
    Google Scholar 
    St. George, R. A. Studies on the larvae on North American beetles of the subfamily Tenebrioninae with a description of the larva and pupa of Merinus laevis (Olivier). Proc. U.S. Natl. Mus. 65, 1–22. https://doi.org/10.5479/si.00963801.65-2514.1 (1924).Article 

    Google Scholar 
    Purchart, L. & Nabozhenko, M. V. First description of larva and pupa of the genus Deretus (Coleoptera: Tenebrionidae) with key to the larvae of the tribe Helopini. Acta Entomol. Musei Natl. Pragae 52, 295–302 (2012).
    Google Scholar 
    Steiner, W. Larvae and pupae of two North American darkling beetles (Coleoptera, Tenebrionidae, Stenochiinae), Glyptotus cribratus LeConte and Cibdelis blaschkei Mannerheim, with notes on ecological and behavioural similarities. ZooKeys 415, 311–327. https://doi.org/10.3897/zookeys.415.6891 (2014).Article 

    Google Scholar 
    Wagner, G. & Gosik, R. Comparative morphology of immature stages of two sympatric Tenebrionidae species, with comments on their biology. Zootaxa 4111, 201–222 (2017).Article 

    Google Scholar  More

  • in

    Iron mobilization during lactation reduces oxygen stores in a diving mammal

    Trivers, R. L. Parent-offspring conflict. Am. Zool. 14, 249–264 (1974).Article 

    Google Scholar 
    Gittleman, J. L. & Thompson, S. D. Energy allocation in mammalian reproduction. Am. Zool. 28, 863–875 (1988).Article 

    Google Scholar 
    Kerby, J. & Post, E. Capital and income breeding traits differentiate trophic match-mismatch dynamics in large herbivores. Philos. Trans. R. Soc. B Biol. Sci. 368, 20120484 (2013).Article 

    Google Scholar 
    Costa, D. P. Reproductive and foraging energetics of pinnipeds: Implications for life history patterns. In The Behaviour of Pinnipeds (ed. D. Renouf) 300–344 (Springer, Netherlands, 1991).Costa, D. P., Boeuf, B. J. L., Huntley, A. C. & Ortiz, C. L. The energetics of lactation in the Northern elephant seal, Mirounga angustirostris. J. Zool. 209, 21–33 (1986).Article 

    Google Scholar 
    Crocker, D. E., Williams, J. D., Costa, D. P. & Le Boeuf, B. J. Maternal traits and reproductive effort in northern elephant seals. Ecology 82, 3541–3555 (2001).Article 

    Google Scholar 
    Shero, M. R., Krotz, R. T., Costa, D. P., Avery, J. P. & Burns, J. M. How do overwinter changes in body condition and hormone profiles influence Weddell seal reproductive success? Funct. Ecol. 29, 1278–1291 (2015).Article 

    Google Scholar 
    Lönnerdal, B. Bioactive proteins in human milk—potential benefits for preterm infants. Clin. Perinatol. 44, 179–191 (2017).PubMed 
    Article 

    Google Scholar 
    Fields, D. A. et al. Associations between human breast milk hormones and adipocytokines and infant growth and body composition in the first 6 months of life. Pediatr. Obes. 12, 78–85 (2017).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Klein, L. D. et al. Concentrations of trace elements in human milk: comparisons among women in Argentina, Namibia, Poland, and the United States. PLoS ONE 12, e0183367 (2017).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Burns, J. M. & Hammill, M. O. Does iron availability limit oxygen store development in seal pups? In 4th CPB Meeting in Africa: Mara 2008. “Molecules to migration: The pressures of life” International Proceedings 417–428 (Medimond Publishing Co., 2008).Burns, J. M., Lestyk, K., Folkow, L. P., Hammill, M. O. & Blix, A. S. Size and distribution of oxygen stores in harp and hooded seals from birth to maturity. J. Comp. Physiol. B 177, 687–700 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kooyman, G. L. Diverse divers: Physiology and behavior. (Springer-Verlag, 1989).Butler, P. J. & Jones, D. R. Physiology of diving of birds and mammals. Physiol. Rev. 77, 837–899 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kanatous, S. B., DiMichele, L. V., Cowan, D. F. & Davis, R. W. High aerobic capacities in skeletal muscles of pinnipeds: adaptations to diving hypoxia. J. Appl. Physiol. 86, 1247–1256 (1999).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shero, M. R., Andrews, R. D., Lestyk, K. C. & Burns, J. M. Development of the aerobic dive limit and muscular efficiency in northern fur seals (Callorhinus ursinus). J. Comp. Physiol. B 182, 425–436 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shero, M. R., Costa, D. P. & Burns, J. M. Scaling matters: Incorporating body composition into Weddell seal seasonal oxygen store comparisons reveals maintenance of aerobic capacities. J. Comp. Physiol. B 185, 811–824 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shero, M. R., Reiser, P. J., Simonitis, L. & Burns, J. M. Links between muscle phenotype and life history: differentiation of myosin heavy chain composition and muscle biochemistry in precocial and altricial pinniped pups. J. Compar. Physiol. B, https://doi.org/10.1007/s00360-019-01240-w (2019).Burns, J. M., Lestyk, K., Freistroffer, D. & Hammill, M. O. Preparing muscles for diving: age-related changes in muscle metabolic profiles in Harp (Pagophilus groenlandicus) and hooded (Cystophora cristata) seals. Physiol. Biochem. Zool. 88, 167–182 (2015).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kooyman, G. L., Wahrenbrock, E. A., Castellini, M. A., Davis, R. W. & Sinnett, E. E. Aerobic and anaerobic metabolism during voluntary diving in Weddell seals: evidence of preferred pathways from blood chemistry and behavior. J. Comp. Physiol. 138, 335–346 (1980).CAS 
    Article 

    Google Scholar 
    Wallace, D. F. The regulation of iron absorption and homeostasis. Clin. biochemist. Rev. 37, 51–62 (2016).
    Google Scholar 
    Juan, S.-H. & Aust, S. D. Studies on the interaction between ferritin and ceruloplasmin. Arch. Biochem. Biophys. 355, 56–62 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hagler, L. et al. Influence of dietary iron deficiency on hemoglobin, myoglobin, their respective reductases, and skeletal muscle mitochondrial respiration. Am. J. Clin. Nutr. 34, 2169–2177 (1981).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kooyman, G. L. Weddell seal: Consummate Diver. (Cambridge University Press, 1981).Heerah, K. et al. Ecology of Weddell seals during winter: Influence of environmental parameters on their foraging behaviour. Deep Sea Res. Part II: Topical Stud. Oceanogr. 88–89, 23–33 (2013).ADS 
    Article 

    Google Scholar 
    Hindell, M. A., Harcourt, R., Waas, J. R. & Thompson, D. Fine-scale three-dimensional spatial use by diving, lactating female Weddell seals Leptonychotes weddellii. Mar. Ecol. Prog. Ser. 242, 275–284 (2002).ADS 
    Article 

    Google Scholar 
    Sato, K. et al. Deep foraging dives in relation to the energy depletion of Weddell seal (Leptonychotes weddellii) mothers during lactation. Polar Biol. 25, 696–702 (2002).Article 

    Google Scholar 
    Wheatley, K. E., Bradshaw, C. J., Davis, L. S., Harcourt, R. G. & Hindell, M. A. Influence of maternal mass and condition on energy transfer in Weddell seals. J. Anim. Ecol. 75, 724–733 (2006).PubMed 
    Article 

    Google Scholar 
    Walcott, S. M. Evaluating the dynamics of physiological, environmental and behavioral parameters to the cost of the annual pelage molt in a polar pinniped: the Weddell seal (Leptonychotes weddellii) MSc thesis, University of Alaska Anchorage, (2019).Beltran, R. S. et al. Seasonal resource pulses and the foraging depth of a Southern Ocean top predator. Proc. R. Soc. B: Biol. Sci. 288, 20202817 (2021).CAS 
    Article 

    Google Scholar 
    Shero, M. R., Goetz, K. T., Costa, D. P. & Burns, J. M. Temporal changes in Weddell seal dive behavior over winter: Are females increasing foraging effort to support gestation? Ecol. Evol. 8, 11857–11874 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Looker, A. C. & Johnson, C. L. Prevalence of elevated serum transferrin saturation in adults in the United States. Ann. Intern. Med. 129, 940–945 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    Eleftheriadis, T., Liakopoulos, V., Antoniadi, G. & Stefanidis, I. Which is the best way for estimating transferrin saturation. Ren. Fail. 32, 1022–1023 (2010).PubMed 
    Article 

    Google Scholar 
    McLaren, C. E. et al. Distribution of transferrin saturation in an Australian population: relevance to the early diagnosis of hemochromatosis. Gastroenterology 114, 543–549 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    Emmett, B. & Hochachka, P. W. Scaling of oxidative and glycolytic enzymes in mammals. Respir. Physiol. 45, 261–272 (1981).CAS 
    PubMed 
    Article 

    Google Scholar 
    Clark, C. A., Burns, J. M., Schreer, J. F. & Hammill, M. O. Erythropoietin concentration in developing harbor seals (Phoca vitulina). Gen. Comp. Endocrinol. 147, 262–267 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Richmond, J. P., Burns, J. M., Rea, L. D. & Mashburn, K. L. Postnatal ontogeny of erythropoietin and hematology in free-ranging Steller sea lions (Eumetopias jubatus). Gen. Comp. Endocrinol. 141, 240–247 (2005).CAS 
    PubMed 
    Article 

    Google Scholar 
    Hadley, G. L., Rotella, J. J. & Garrott, R. A. Influence of maternal characteristics and oceanographic conditions on survival and recruitment probabilities of Weddell seals. Oikos 116, 601–613 (2006).Article 

    Google Scholar 
    Hall, A. C., McConnell, B. J. & Barker, R. J. Factors affecting first-year survival in grey seals and their implications for life history strategies. J. Anim. Ecol. 70, 138–149 (2001).
    Google Scholar 
    Proffitt, K. M., Garrott, R. A. & Rotella, J. J. Long-term evaluation of body mass at weaning and postweaning survival rates of Weddell seals in Erebus Bay, Antarctica. Mar. Mamm. Sci. 24, 677–689 (2008).Article 

    Google Scholar 
    Burns, J. M. & Castellini, M. A. Physiological and behavioral determinants of the aerobic dive limit in Weddell seal (Leptonychotes weddellii) pups. J. Comp. Physiol. B 166, 473–483 (1996).Article 

    Google Scholar 
    Costa, D. P., Kuhn, C. E., Weise, M. J., Shaffer, S. A. & Arnould, J. P. Y. When does physiology limit the foraging behaviour of freely diving mammals? Int. Congr. Ser. 1275, 359–366 (2004).Article 

    Google Scholar 
    Hadley, G. L., Rotella, J. J. & Garrott, R. A. Evaluation of reproductive costs for Weddell seals in Erebus Bay, Antarctica. J. Anim. Ecol. 76, 448–458 (2007).PubMed 
    Article 

    Google Scholar 
    Young, S. P., Fahmy, M. & Golding, S. Ceruloplasmin, transferrin and apotransferrin facilitate iron release from human liver cells. FEBS Lett. 411, 93–96 (1997).CAS 
    PubMed 
    Article 

    Google Scholar 
    Mazzaro, L. M., Dunn, J. L., St. Aubin, D. J., Andrews, G. A. & Chavey, P. S. Serum indices of body stores of iron in northern fur seals (Callorhinus ursinus) and their relationship to hemochromatosis. Zoo. Biol. 23, 205–218 (2004).Article 

    Google Scholar 
    Yalçn, S. S., Baykan, A., Yurdakök, K., Yalçn, S. & Gücüs, A. I. The factors that affect milk-to-serum ratio for iron during early lactation. J. Pediatr. Hematol. Oncol. 31, 85–90 (2009).Article 

    Google Scholar 
    Geiseler, S. J., Blix, A. S., Burns, J. M. & Folkow, L. P. Rapid postnatal development of myoglobin from large liver iron stores in hooded seals. J. Exp. Biol. 216, 1793–1798 (2013).CAS 
    PubMed 

    Google Scholar 
    Samokyszyn, V. M., Miller, D. M., Reif, D. W. & Aust, S. D. Inhibition of superoxide and ferritin-dependent lipid peroxidation by ceruloplasmin. J. Biol. Chem. 264, 21–26 (1989).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kohgo, Y., Ikuta, K., Ohtake, T., Torimoto, Y. & Kato, J. Body iron metabolism and pathophysiology of iron overload. Int. J. Hematol. 88, 7–15 (2008).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Zhang, P. et al. The effect of serum iron concentration on iron secretion into mouse milk. J. Physiol. 522(Pt 3), 479–491 (2000).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Erdogan, S., Celik, S. & Erdogan, Z. Seasonal and locational effects on serum, milk, liver and kidney chromium, manganese, copper, zinc, and iron concentrations of dairy cows. Biol. Trace Elem. Res. 98, 51–61 (2004).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kaldor, I. & Morgan, E. H. Iron metabolism during lactation and suckling in a marsupial, the quokka (Setonix brachyurus). Comp. Biochem. Physiol. Part A: Physiol. 84, 691–694 (1986).CAS 
    Article 

    Google Scholar 
    Tedman, R. A. & Green, B. Water and sodium fluxes in suckling pups of Weddell seals (Leptonychotes weddelli). J. Zool. 212, 29–42 (1987).Article 

    Google Scholar 
    National Institutes of Health, Supplements, O. o. D. Iron Fact Sheet for Consumers, https://ods.od.nih.gov/factsheets/Iron-Consumer/ (2021).Saarinen, U. M., Siimes, M. A. & Dallman, P. R. Iron absorption in infants: high bioavailability ofbreast milk iron as indicated by the extrinsic tag method of iron absorption and by the concentration of serum ferritin. J. Pediatrics 91, 36–39 (1977).CAS 
    Article 

    Google Scholar 
    Loh, T.-T. Iron metabolism of the lactating mouse. Proc. Soc. Exp. Biol. Med. 137, 962–965 (1971).CAS 
    PubMed 
    Article 

    Google Scholar 
    Folkow, L. P., Nordoy, E. S. & Blix, A. S. Distribution and diving behavior of harp seals (Pagophilus groenlandica) from the Greenland Sea stock. Polar Biol. 27, 281–298 (2004).Article 

    Google Scholar 
    Beck, C. A., Bowen, W. D. & Iverson, S. J. Seasonal changes in buoyancy and diving behaviour of adult grey seals. J. Exp. Biol. 203, 2323–2330 (2000).CAS 
    PubMed 
    Article 

    Google Scholar 
    Gentry, R. L. & Kooyman, G. L. Fur seals: maternal strategies on land and at sea. (Princeton University Press, 1986).McDonald, B. I. & Ponganis, P. J. Insights from venous oxygen profiles: oxygen utilization and management in diving California sea lions. J. Exp. Biol. 216, 3332–3341 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Noren, S. R., Iverson, S. J. & Boness, D. J. Development of the blood and muscle oxygen stores in gray seals (Halichoerus grypus): Implications for juvenile diving capacity and the necessity of a terrestrial postweaning fast. Physiol. Biochem. Zool. 78, 482–490 (2005).PubMed 
    Article 

    Google Scholar 
    Weise, M. J. & Costa, D. P. Total body oxygen stores and physiological diving capacity of California sea lions as a function of sex and age. J. Exp. Biol. 210, 278–289 (2007).PubMed 
    Article 

    Google Scholar 
    Burns, J. M., Hindell, M. A., Bradshaw, C. J. A. & Costa, D. P. Fine-scale habitat selection by crabeater seals as determined by diving behavior. Deep Sea Res. II 55, 500–514 (2008).ADS 
    Article 

    Google Scholar 
    Burns, J. Crabeater seal oxygen stores. U.S. Antarctic Program (USAP) Data Center. https://doi.org/10.15784/601583 (2022).Nicol, S. et al. Southern Ocean iron fertilization by baleen whales and Antarctic krill. Fish. Fish. 11, 203–209 (2010).Article 

    Google Scholar 
    Williams, T. M. The cost of foraging by a marine predator, the Weddell seal Leptonychotes weddellii: pricing by the stroke. J. Exp. Biol. 207, 973–982 (2004).PubMed 
    Article 

    Google Scholar 
    Wheatley, K. E., Bradshaw, C. J. A., Harcourt, R. G. & Hindell, M. A. Feast or famine: evidence for mixed capital–income breeding strategies in Weddell seals. Oecologia 155, 11–20 (2008).ADS 
    PubMed 
    Article 

    Google Scholar 
    Honda, K., Sahrul, M., Hidaka, H. & Tatsukawa, R. Organ and tissue distribution of heavy metals, and their growth-related changes in Antarctic Fish, Pagothenia borchgrevinki. Agric. Biol. Chem. 47, 2521–2532 (1983).CAS 

    Google Scholar 
    Galbraith, E. D., Le Mézo, P., Solanes Hernandez, G., Bianchi, D. & Kroodsma, D. Growth limitation of marine fish by low iron availability in the open ocean. Front. Marine Sci. 6, https://doi.org/10.3389/fmars.2019.00509 (2019).Pollycove, M. & Mortimer, R. The quantitative determination of iron kinetics and hemoglobin synthesis in human subjects. J. Clin. Invest. 40, 753–782 (1961).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Åkeson, Å., Ehrenstein, G. V., Hevesy, G. & Theorell, H. Life span of myoglobin. Arch. Biochem. Biophys. 91, 310–318 (1960).PubMed 
    Article 

    Google Scholar 
    Tift, M. S. et al. Adaptive potential of the heme oxygenase/carbon monoxide pathway during hypoxia. Front. Physiol. 11, https://doi.org/10.3389/fphys.2020.00886 (2020).Tift, M. S., Ponganis, P. J. & Crocker, D. E. Elevated carboxyhemoglobin in a marine mammal, the northern elephant seal. J. Exp. Biol. 217, 1752–1757 (2014).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ma, Y.-J. et al. A modified carbon monoxide breath test for measuring erythrocyte lifespan in small animals. BioMed. Res. Int. 2016, 7173156 (2016).PubMed 
    PubMed Central 

    Google Scholar 
    Zhang, H.-D. et al. Human erythrocyte lifespan measured by Levitt’s CO breath test with newly developed automatic instrument. J. Breath. Res. 12, 036003 (2018).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Hochachka, P. W. & Somero, G. N. Biochemical adaptation. (Oxford University Press, 2002).De Miranda, M. A., Schlater, A. E., Green, T. L. & Kanatous, S. B. In the face of hypoxia: myoglobin increases in response to hypoxic conditions and lipid supplementation in cultured Weddell seal skeletal muscle cells. J. Exp. Biol. 215, 806–813 (2012).PubMed 
    Article 
    CAS 

    Google Scholar 
    Kanatous, S. B. & Mammen, P. P. Regulation of myoglobin expression. J. Exp. Biol. 213, 2741–2747 (2010).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Halvorsen, S. & Bechensteen, A. G. Physiology of erythropoietin during mammalian development. Acta Paediatr. Suppl. 438, 17–26 (2002).Article 

    Google Scholar 
    Hochachka, P. W. Mechanism and evolution of hypoxia-tolerance in humans. J. Exp. Biol. 201, 1243–1254 (1998).CAS 
    PubMed 
    Article 

    Google Scholar 
    Klopfleisch, R. & Olias, P. The pathology of comparative animal models of human haemochromatosis. J. Comp. Pathol. 147, 460–478 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Henriksson, J. & Reitman, J. S. Time course of changes in human skeletal muscle succinate dehydrogenase and cytochrome oxidase activities and maximal oxygen uptake with physical activity and inactivity. Acta Physiol. Scand. 99, 91–97 (1977).CAS 
    PubMed 
    Article 

    Google Scholar 
    Goetz, K. T. Movement, habitat, and foraging behavior of Weddell seals (Leptonychotes weddellii) in the western Ross Sea, Antarctica, University of California Santa Cruz, (2015).Cisewski, B., Strass, V. H., Rhein, M. & Krägefsky, S. Seasonal variation of diel vertical migration of zooplankton from ADCP backscatter time series data in the Lazarev Sea, Antarctica. Deep Sea Res. Part I: Oceanographic Res. Pap. 57, 78–94 (2010).ADS 
    CAS 
    Article 

    Google Scholar 
    Jones, R. M. & Smith, W. O. The influence of short-term events on the hydrographic and biological structure of the southwestern Ross Sea. J. Mar. Syst. 166, 184–195 (2017).Article 

    Google Scholar 
    Smith, W. O. & Nelson, D. M. Importance of ice edge phytoplankton production in the Southern Ocean. Bioscience 36, 251–257 (1986).CAS 
    Article 

    Google Scholar 
    Rivkin, R. B. Seasonal patterns of planktonic production in McMurdo Sound, Antarctica. Am. Zool. 31, 5–16 (2015).Article 

    Google Scholar 
    Proffitt, K. M., Rotella, J. J. & Garrott, R. A. Effects of pup age, maternal age, and birth date on pre-weaning survival rates of Weddell seals in Erebus Bay, Antarctica. Oikos 119, 1255–1264 (2010).Article 

    Google Scholar 
    Beltran, R. S., Kirkham, A. L., Breed, G. A., Testa, J. W. & Burns, J. M. Reproductive success delays moult phenology in a polar mammal. Sci. Rep. 9, 5221 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Mellish, J.-A. E., Tuomi, P. A., Hindle, A. G. & Horning, M. Chemical immobilization of Weddell seals (Leptonychotes weddellii) by ketamine/midazolam combination. Vet. Anaesth. Analg. 37, 123–131 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Shero, M. R., Pearson, L. E., Costa, D. P. & Burns, J. M. Improving the precision of our ecosystem calipers: a modified morphometric technique for estimating marine mammal mass and body composition. PLoS ONE 9, e91233 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Foldager, N. & Blomqvist, C. G. Repeated plasma volume determination with the Evans blue dye dilution technique: the method and the computer program. Comput. Biol. Med. 21, 35–41 (1991).CAS 
    PubMed 
    Article 

    Google Scholar 
    El-Sayed, H., Goodall, S. R. & Hainsworth, F. R. Re-evaluation of Evans blue dye dilution method of plasma volume measurement. Clin. Lab. Haem. 17, 189–194 (1995).CAS 

    Google Scholar 
    Reynafarje, B. Simplified method for the determination of myoglobin. J. Lab. Clin. Med. 61, 138–145 (1963).CAS 
    PubMed 

    Google Scholar 
    Prewitt, J. S., Freistroffer, D. V., Schreer, J. F., Hammill, M. O. & Burns, J. M. Postnatal development of muscle biochemistry in nursing harbor seal (Phoca vitulina) pups: Limitations to diving behavior? J. Comp. Physiol. B 180, 757–766 (2010).CAS 
    PubMed 
    Article 

    Google Scholar 
    Polasek, L., Dickson, K. A. & Davis, R. W. Metabolic indicators in the skeletal muscles of harbor seals (Phoca vitulina). Am. J. Physiol. Regul. Integr. Comp. Physiol. 290, R1720–R1727 (2006).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kooyman, G. L., Castellini, M. A., Davis, R. W. & Maue, R. A. Aerobic diving limits of immature Weddell seals. J. Comp. Physiol. 151, 171–174 (1983).Article 

    Google Scholar 
    Davis, R. W. & Kanatous, S. B. Convective oxygen transport and tissue oxygen consumption in Weddell seals during aerobic dives. J. Exp. Biol. 202, 1091–1113 (1999).CAS 
    PubMed 
    Article 

    Google Scholar 
    Lenfant, C., Johansen, K. & Torrance, J. D. Gas transport and oxygen storage capacity in some pinnipeds and the sea otter. Respir. Physiol. 9, 277–286 (1970).CAS 
    PubMed 
    Article 

    Google Scholar 
    Kleiber, M. The fire of life: an introduction to animal energetics. (R.E. Krieger Pub. Co., 1975).Sato, K., Mitani, Y., Cameron, M. F., Siniff, D. B. & Naito, Y. Factors affecting stroking patterns and body angle in diving Weddell seals under natural conditions. J. Exp. Biol. 206, 1461–1470 (2003).PubMed 
    Article 

    Google Scholar 
    Zuur, A. F., Hilbe, J. M. & Ieno, E. N. A Beginner’s Guide to GLM and GLMM with R: A Frequentist and Bayesian Perspective for Ecologists. (Highland Statistics Newburgh, 2013).Shero, M. Weddell seal iron dynamics and oxygen stores across lactation. U.S. Antarctic Program (USAP) Data Center. https://doi.org/10.15784/601575. (2022).Anderson, R. S. et al. Zinc, copper, iron and calcium concentrations in bitch milk. J. Nutr. 121, S81–S82 (1991).CAS 
    PubMed 
    Article 

    Google Scholar 
    Griffiths, M., Green, B., MC Leckie, R., Messer, M. & Newgrain, K. Constituents of platypus and echidna milk, with particular reference to the fatty acid complement of the triglycerides. Aust. J. Biol. Sci. 37, 323–330 (1984).CAS 
    Article 

    Google Scholar 
    Peddemors, V. M., de Muelenaere, H. J. H. & Devchand, K. Comparative milk composition of the bottlenosed dolphin (Tursiops truncatus), humpback dolphin (Sousa plumbea) and common dolphin (Delphinus delphis) from southern African waters. Comp. Biochem. Physiol. Part A Physiol. 94, 639–641 (1989).CAS 
    Article 

    Google Scholar 
    Ullrey, D. E. et al. Blue-green color and composition of Stejneger’s beaked whale (Mesoplodon stejnegeri) milk. Comp. Biochem. Physiol. B Comp. Biochem. 79, 349–352 (1984).CAS 
    Article 

    Google Scholar 
    Dosako, S. I. et al. Milk of Northern fur seal: composition, especially carbohydrate and protein. J. Dairy Sci. 66, 2076–2083 (1983).CAS 
    PubMed 
    Article 

    Google Scholar 
    Oftedal, O. T., Boness, D. J. & Tedman, R. The Behavior, Physiology, and Anatomy of Lactation in the Pinnipedia. (Genoyways, H. H. eds) (Current Mammalogy. Springer, Boston, MA, 1987).Habran, S., Pomeroy, P. P., Debier, C. & Das, K. Changes in trace elements during lactation in a marine top predator, the grey seal. Aquat. Toxicol. 126, 455–466 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Seal, U. S., Erickson, A. W., Siniff, D. B. & Cline, D. R. Blood chemistry and protein polymorphisms in three species of Antarctic seals (Lobodon carcinophagus, Leptonychootes weddellii, and Mirounga leonina) In Antarctic Pinnipedia 181–192 (1971).Green, B., Fogerty, A., Libke, J., Newgrain, K. & Shaughnessy, P. Aspects of lactation in the crab-eater seal (Lobodon-Carcinophagus). Aust. J. Zool. 41, 203–213 (1993).Article 

    Google Scholar 
    Casey, C. E., Smith, A. & Zhang, P. Microminerals in human and animal milks, In Handbook of milk composition 622–674 (ed. R. G. Jensen) (Academic Press, 1995). More

  • in

    Warmth signals male growth

    Share this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
    Provided by the Springer Nature SharedIt content-sharing initiative More