More stories

  • in

    Stable isotopes unveil one millennium of domestic cat paleoecology in Europe

    Turner, D. & Bateson, P. (eds) The Domestic Cat: The Biology of Its Behaviour (Cambridge Univ. Press, 2000).
    Google Scholar 
    Bradshaw, J. W. S., Goodwin, D., Legrand-Defrétin, V. & Nott, H. M. R. Food selection by the domestic cat, an obligate carnivore. Comp. Biochem. Physiol. A Physiol. 114, 205–209 (1996).CAS 
    PubMed 
    Article 

    Google Scholar 
    Trouwborst, A., McCormack, P. C. & Martínez Camacho, E. Domestic cats and their impacts on biodiversity: A blind spot in the application of nature conservation law. People Nat. 2, 235–250 (2020).Article 

    Google Scholar 
    Crowley, S. L., Cecchetti, M. & McDonald, R. A. Our wild companions: Domestic cats in the anthropocene. Trends Ecol. Evol. 35, 477–483 (2020).PubMed 
    Article 

    Google Scholar 
    Driscoll, C. A. et al. The Near Eastern origin of cat domestication. Science 317, 519–523 (2007).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Van Neer, W., Linseele, V., Friedman, R. & De Cupere, B. More evidence for cat taming at the Predynastic elite cemetery of Hierakonpolis (Upper Egypt). J. Archaeol. Sci. 45, 103–111 (2014).Article 

    Google Scholar 
    Ottoni, C. et al. The palaeogenetics of cat dispersal in the ancient world. Nat. Ecol. Evol. 1, 0139 (2017).Article 

    Google Scholar 
    Baca, M. et al. Human-mediated dispersal of cats in the Neolithic Central Europe. Heredity 121, 557–563 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Vigne, J. The beginning of cat domestication in East and West Asia. Doc. Archaeobiol. 15, 343–354 (2019).
    Google Scholar 
    Krajcarz, M. et al. Ancestors of domestic cats in Neolithic Central Europe: Isotopic evidence of a synanthropic diet. Proc. Natl. Acad. Sci. USA 117, 17710–17719 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Piontek, A. M. et al. Analysis of cat diet across an urbanisation gradient. Urban Ecosyst. 24, 59–69 (2021).Article 

    Google Scholar 
    Medina, F. M. et al. A global review of the impacts of invasive cats on island endangered vertebrates. Glob. Chang. Biol. 17, 3503–3510 (2011).ADS 
    Article 

    Google Scholar 
    Moseby, K. E., Peacock, D. E. & Read, J. L. Catastrophic cat predation: A call for predator profiling in wildlife protection programs. Biol. Conserv. 191, 331–340 (2015).Article 

    Google Scholar 
    Loss, S. R., Will, T. & Marra, P. P. The impact of free-ranging domestic cats on wildlife of the United States. Nat. Commun. 4, 1396 (2013).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Beaumont, M. et al. Genetic diversity and introgression in the Scottish wildcat. Mol. Ecol. 10, 319–336 (2001).CAS 
    PubMed 
    Article 

    Google Scholar 
    Beugin, M. P. et al. Hybridization between Felis silvestris silvestris and Felis silvestris catus in two contrasted environments in France. Ecol. Evol. 10, 263–276 (2020).PubMed 
    Article 

    Google Scholar 
    Biró, Z., Lanszki, J., Szemethy, L., Heltai, M. & Randi, E. Feeding habits of feral domestic cats (Felis catus), wild cats (Felis silvestris) and their hybrids: Trophic niche overlap among cat groups in Hungary. J. Zool. 266, 187–196 (2005).Article 

    Google Scholar 
    Széles, G. L., Purger, J. J., Molnár, T. & Lanszki, J. Comparative analysis of the diet of feral and house cats and wildcat in Europe. Mammal. Res. 63, 43–53 (2018).Article 

    Google Scholar 
    Ottoni, C. & Van Neer, W. The dispersal of the domestic cat paleogenetic and zooarcheological evidence. Near East. Archaeol. 83, 38–45 (2020).Article 

    Google Scholar 
    Bitz-Thorsen, J. & Gotfredsen, A. B. Domestic cats (Felis catus) in Denmark have increased significantly in size since the Viking Age. Danish J. Archaeol. 7, 241–254 (2018).Article 

    Google Scholar 
    Faure, E. & Kitchener, A. C. An archaeological and historical review of the relationships between felids and people. Anthrozoos 22, 221–238 (2009).Article 

    Google Scholar 
    von den Driesch, A. Kulturgeschichte der Hauskatze. In Krankheiten der Katze, Bd. 1 (eds Schmidt, V. & Horzinek, M. C.) 17–40 (Fischer, 1992).
    Google Scholar 
    Głażewska, I. & Kijewski, T. A new view on the European feline population from mtDNA analysis in Polish domestic cats. Forensic Sci. Int. Genet. 27, 116–122 (2017).PubMed 
    Article 
    CAS 

    Google Scholar 
    Cucchi, T. et al. Tracking the Near Eastern origins and European dispersal of the western house mouse. Sci. Rep. 10, 8276 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Van Klinken, G. J., Richards, M. P. & Hedges, B. E. M. An overview of causes for stable isotopic variations in past European human populations: environmental, ecophysiological, and cultural effects. In Biogeochemical Approaches to Paleodietary Analysis (eds Ambrose, S. & Katzenberg, M.) 39–63 (Kluwer Academic Publishers, 2002). https://doi.org/10.1007/0-306-47194-9_3.Chapter 

    Google Scholar 
    Drucker, D. G., Bridault, A., Hobson, K. A., Szuma, E. & Bocherens, H. Can carbon-13 in large herbivores reflect the canopy effect in temperate and boreal ecosystems? Evidence from modern and ancient ungulates. Palaeogeogr. Palaeoclimatol. Palaeoecol. 266, 69–82 (2008).Article 

    Google Scholar 
    Koch, P. L. Isotopic study of the biology of modern and fossil vertebrates. In Stable Isotopes in Ecology and Environmental Science (eds Michener, R. & Lajtha, K.) 99–154 (Blackwell Publishing Ltd, 2007). https://doi.org/10.1002/9780470691854.ch5.Chapter 

    Google Scholar 
    Hofman-Kamińska, E. et al. Foraging habitats and niche partitioning of European large herbivores during the holocene—Insights from 3D dental microwear texture analysis. Palaeogeogr. Palaeoclimatol. Palaeoecol. 506, 183–195 (2018).Article 

    Google Scholar 
    Bocherens, H., Hofman-Kamińska, E., Drucker, D. G., Schmölcke, U. & Kowalczyk, R. European bison as a refugee species? Evidence from isotopic data on Early Holocene bison and other large herbivores in northern Europe. PLoS ONE 10, 1–19 (2015).Article 
    CAS 

    Google Scholar 
    Hu, Y. et al. Earliest evidence for commensal processes of cat domestication. Proc. Natl. Acad. Sci. USA. 111, 116–120 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Haruda, A. F. et al. The earliest domestic cat on the Silk Road. Sci. Rep. 10, 11241 (2020).CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Meckstroth, A. M., Miles, A. K. & Chandra, S. Diets of introduced predators using stable isotopes and stomach contents. J. Wildl. Manag. 71, 2387–2392 (2007).Article 

    Google Scholar 
    McDonald, B. W. et al. High variability within pet foods prevents the identification of native species in pet cats’ diets using isotopic evaluation. PeerJ 8, e8337 (2020).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Maeda, T., Nakashita, R., Shionosaki, K., Yamada, F. & Watari, Y. Predation on endangered species by human-subsidized domestic cats on Tokunoshima Island. Sci. Rep. 9, 16200 (2019).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Stewart, G. R., Aidar, M. P. M., Joly, C. A. & Schmidt, S. Impact of point source pollution on nitrogen isotope signatures (δ15N) of vegetation in SE Brazil. Oecologia 131, 468–472 (2002).ADS 
    PubMed 
    Article 

    Google Scholar 
    Graven, H., Keeling, R. F. & Rogelj, J. Changes to carbon isotopes in atmospheric CO2 over the industrial era and into the future. Glob. Biogeochem. Cycles 34, 1–21 (2020).Article 
    CAS 

    Google Scholar 
    DeNiro, M. J. Postmortem preservation and alteration of in vivo bone collagen isotope ratios in relation to palaeodietary reconstruction. Nature 317, 806–809 (1985).ADS 
    CAS 
    Article 

    Google Scholar 
    Linderholm, A. & Kjellström, A. Stable isotope analysis of a medieval skeletal sample indicative of systemic disease from Sigtuna Sweden. J. Archaeol. Sci. 38, 925–933 (2011).Article 

    Google Scholar 
    Webb, E. C. et al. Compound-specific amino acid isotopic proxies for distinguishing between terrestrial and aquatic resource consumption. Archaeol. Anthropol. Sci. 10, 1–18 (2018).Article 

    Google Scholar 
    Müldner, G. & Richards, M. P. Stable isotope evidence for 1500 years of human diet at the city of York, UK. Am. J. Phys. Anthropol. 133, 682–697 (2007).PubMed 
    Article 

    Google Scholar 
    Müldner, G. & Richards, M. P. Fast or feast: Reconstructing diet in later medieval England by stable isotope analysis. J. Archaeol. Sci. 32, 39–48 (2005).Article 

    Google Scholar 
    van der Sluis, L. G., Hollund, H. I., Kars, H., Sandvik, P. U. & Denham, S. D. A palaeodietary investigation of a multi-period churchyard in Stavanger, Norway, using stable isotope analysis (C, N, H, S) on bone collagen. J. Archaeol. Sci. Rep. 9, 120–133 (2016).
    Google Scholar 
    Polet, C. & Katzenberg, M. A. Reconstruction of the diet in a mediaeval monastic community from the coast of Belgium. J. Archaeol. Sci. 30, 525–533 (2003).Article 

    Google Scholar 
    Kosiba, S. B., Tykot, R. H. & Carlsson, D. Stable isotopes as indicators of change in the food procurement and food preference of Viking Age and Early Christian populations on Gotland (Sweden). J. Anthropol. Archaeol. 26, 394–411 (2007).Article 

    Google Scholar 
    Olsen, K. C. et al. Isotopic anthropology of rural German medieval diet: Intra- and inter-population variability. Archaeol. Anthropol. Sci. 10, 1053–1065 (2018).Article 

    Google Scholar 
    Benevolo, L. The European City (Blackwell Publishers, 1993).
    Google Scholar 
    Barrett, J. et al. Detecting the medieval cod trade: A new method and first results. J. Archaeol. Sci. 35, 850–861 (2008).Article 

    Google Scholar 
    Barrett, J. H. et al. Interpreting the expansion of sea fishing in medieval Europe using stable isotope analysis of archaeological cod bones. J. Archaeol. Sci. 38, 1516–1524 (2011).Article 

    Google Scholar 
    Bogaard, A., Heaton, T. H. E., Poulton, P. & Merbach, I. The impact of manuring on nitrogen isotope ratios in cereals: Archaeological implications for reconstruction of diet and crop management practices. J. Archaeol. Sci. 34, 335–343 (2007).Article 

    Google Scholar 
    Heaton, T. H. E. Spatial, species, and temporal variations in the 13C/12C ratios of C3 plants: Implications for palaeodiet studies. J. Archaeol. Sci. 26, 637–649 (1999).Article 

    Google Scholar 
    Bogaard, A. et al. Crop manuring and intensive land management by Europe’s first farmers. Proc. Natl. Acad. Sci. USA. 110, 12589–12594 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Styring, A. K. et al. Refining human palaeodietary reconstruction using amino acid δ15N values of plants, animals and humans. J. Archaeol. Sci. 53, 504–515 (2015).CAS 
    Article 

    Google Scholar 
    Guiry, E. Complexities of stable carbon and nitrogen isotope biogeochemistry in ancient freshwater ecosystems: Implications for the study of past subsistence and environmental change. Front. Ecol. Evol. 7, 313 (2019).Article 

    Google Scholar 
    Fuller, B. T., Müldner, G., Van Neer, W., Ervynck, A. & Richards, M. P. Carbon and nitrogen stable isotope ratio analysis of freshwater, brackish and marine fish from Belgian archaeological sites (1st and 2nd millennium AD). J. Anal. At. Spectrom. 27, 807–820 (2012).CAS 
    Article 

    Google Scholar 
    Robson, H. K. et al. Carbon and nitrogen stable isotope values in freshwater, brackish and marine fish bone collagen from Mesolithic and Neolithic sites in central and northern Europe. Environ. Archaeol. 21, 105–118 (2016).Article 

    Google Scholar 
    Hobson, K. A., Piatt, J. F. & Pitocchelli, J. Using stable isotopes to determine seabird trophic relationships. J. Anim. Ecol. 63, 786–798 (1994).Article 

    Google Scholar 
    Guiry, E. & Buckley, M. Urban rats have less variable, higher protein diets. Proc. R. Soc. B Biol. Sci. 285, 20181441 (2018).Article 
    CAS 

    Google Scholar 
    Bicknell, A. W. J. et al. Stable isotopes reveal the importance of seabirds and marine foods in the diet of St Kilda field mice. Sci. Rep. 10, 1–12 (2020).Article 
    CAS 

    Google Scholar 
    Hoffmann, R. C. Medieval fishing. In Working with Water in Medieval Europe. Technology and Resource-Use (ed. Squatriti, P.) 331–393 (Brill, 2000).
    Google Scholar 
    Gillies, C. & Clout, M. The prey of domestic cats (Felis catus) in two suburbs of Auckland City, New Zealand. J. Zool. 259, 309–315 (2003).Article 

    Google Scholar 
    Brickner-Braun, I., Geffen, E. & Yom-Tov, Y. The domestic cat as a predator of Israeli wildlife. Isr. J. Ecol. Evol. 53, 129–142 (2007).Article 

    Google Scholar 
    Flockhart, D. T. T., Norris, D. R. & Coe, J. B. Predicting free-roaming cat population densities in urban areas. Anim. Conserv. 19, 472–483 (2016).Article 

    Google Scholar 
    Castañeda, I., Zarzoso-Lacoste, D. & Bonnaud, E. Feeding behaviour of red fox and domestic cat populations in suburban areas in the south of Paris. Urban Ecosyst. 23, 731–743 (2020).Article 

    Google Scholar 
    Zhu, Y., Siegwolf, R. T. W., Durka, W. & Körner, C. Phylogenetically balanced evidence for structural and carbon isotope responses in plants along elevational gradients. Oecologia 162, 853–863 (2010).ADS 
    PubMed 
    Article 

    Google Scholar 
    Männel, T. T., Auerswald, K. & Schnyder, H. Altitudinal gradients of grassland carbon and nitrogen isotope composition are recorded in the hair of grazers. Glob. Ecol. Biogeogr. 16, 583–592 (2007).Article 

    Google Scholar 
    Pińska, K. & Badura, M. Warunki przyrodnicze i dieta roślinna mieszkańców Pucka w późnym średniowieczu. In Puck – kultura materialna małego miasta w późnym średniowieczu (ed. Starski, M.) 517 (Uniwersytet Warszawski, 2017).
    Google Scholar 
    Lefebvre, A. et al. Morphology of estuarine bedforms, Weser Estuary, Germany. Earth Surf. Process. Landforms 47, 242–256 (2022).ADS 
    Article 

    Google Scholar 
    Bischop, D. & Von der Küchelmann, H. C. Küche in den Graben – Bremens Stadtgraben und die Essgewohnheiten seiner Anwohner an der Wende zur Frühen Neuzeit. In Lebensmittel im Mittelalter und in der frühen Neuzeit. Erzeugung, Verarbeitung, Versorgung. Beiträge des 16. Kolloquiums des Arbeitskreises zur archäologischen Erforschung des mittelalterlichen Handwerks, Soester Beiträge zur Archäologie 15 (ed. Melzer, W.) 137–151 (Mocker und Jahn, 2018).
    Google Scholar 
    Elmshäuser, K. & Pordzik, V. V. Lachsgarnen, Tomen und Kumpanen – Die älteste Bremer Fischeramtsrolle. Bremisches Jahrb. 98, 13–72 (2019).
    Google Scholar 
    Küchelmann, H. C. Viel Butter bei wenig Fisch. Zwei Fischknochenkomplexe des 12.–13. Jahrhunderts aus der Bremer Altstadt. In Grenzen überwinden. Archäologie zwischen Disziplin und Disziplinen. Festschrift für Uta Halle zum 65. Geburtstag, Internationale Archäologie Studia Honoraria 40 (eds Kahlow, S. et al.) 413–426 (Verlag Marie Leidorf GmbH, 2021).
    Google Scholar 
    Schwarcz, H. P. & Schoeninger, M. J. Stable isotope analyses in human nutritional ecology. Am. J. Phys. Anthropol. 34, 283–321 (1991).Article 

    Google Scholar 
    Wallace, M. et al. Stable carbon isotope analysis as a direct means of inferring crop water status and water management practices. World Archaeol. 45, 388–409 (2013).Article 

    Google Scholar 
    van der Merwe, N. J. & Medina, E. The canopy effect, carbon isotope ratios and foodwebs in amazonia. J. Archaeol. Sci. 18, 249–259 (1991).Article 

    Google Scholar 
    Ervynck, A. Orant, pugnant, laborant. The diet of the three orders in the feudal society of medieval north-western Europe. In Behaviour Behind Bones. The Zooarchaeology of Ritual, Religion, Status and Identity (eds O’Day, S. J. et al.) 215–223 (Oxbow Books, 2004).
    Google Scholar 
    von den Driesch, A. A guide to the measurement of animal bones from archaeological sites. Peabody Museum Bull. 1, 1–137 (1976).
    Google Scholar 
    O’Connor, T. P. Wild or domestic? Biometric variation in the cat Felis silvestris Schreber. Int. J. Osteoarchaeol. 17, 581–595 (2007).Article 

    Google Scholar 
    Kratochvíl, Z. Schadelkriterien der Wild- und Hauskatze (Felis silvestris silvestris Schreber 1777 und Felis s. f. catus L. 1758). Acta Sci. Nat. Brno 7, 1–50 (1973).
    Google Scholar 
    Kratochvíl, Z. Das Postkranialskelett der Wild- und Hauskatze (Felis silvestris und F. lybica f. catus). Acta Sci. Nat. Brno 10, 1–43 (1976).
    Google Scholar 
    Dyce, K. M., Sack, W. O. & Wensing, C. J. G. Textbook of Veterinary Anatomy (Saunders/Elsevier, 2010).
    Google Scholar 
    Krajcarz, M. et al. On the trail of the oldest domestic cat in Poland. An insight from morphometry, ancient DNA and radiocarbon dating. Int. J. Osteoarchaeol. 26, 912–919 (2016).Article 

    Google Scholar 
    Bronk Ramsey, C. Radiocarbon calibration and analysis of stratigraphy: The OxCal program. Radiocarbon 37, 425–430 (1995).CAS 
    Article 

    Google Scholar 
    Bronk Ramsey, C., Dee, M., Lee, S., Nakagawa, T. & Staff, R. Developments in the calibration and modeling of radiocarbon dates. Radiocarbon 52, 953–961 (2010).Article 

    Google Scholar 
    Ferreira, J. P., Leitão, I., Santos-Reis, M. & Revilla, E. Human-related factors regulate the spatial ecology of domestic cats in sensitive areas for conservation. PLoS ONE 6, e25970 (2011).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pirie, T. J., Thomas, R. L. & Fellowes, M. D. E. Pet cats (Felis catus) from urban boundaries use different habitats, have larger home ranges and kill more prey than cats from the suburbs. Landsc. Urban Plan. 220, 104338 (2022).Article 

    Google Scholar 
    Bocherens, H. et al. Paleobiological implications of the isotopic signatures (13C, 15N) of fossil mammal collagen in Scladina cave (Sclayn, Belgium). Quat. Res. 48, 370–380 (1997).Article 

    Google Scholar 
    Longin, R. New method of collagen extraction for radiocarbon dating. Nature 230, 241–242 (1971).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Boudin, M., Boeckx, P., Vandenabeele, P. & Van Strydonck, M. Improved radiocarbon dating of contaminated protein-containing archaeological samples via cross-flow nanofiltrated amino acids. Rapid Commun. Mass Spectrom. 27, 2039–2050 (2013).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Wojcieszak, M., Van Den Brande, T., Ligovich, G. & Boudin, M. Pretreatment protocols performed at the Royal Institute for Cultural Heritage (RICH) prior to AMS 14C measurements. Radiocarbon 62, e14–e24 (2020).Article 

    Google Scholar 
    Hammer, Ø. PAST. PAleontological Statistics. Version 4.05 Reference manual (Natural History Museum University of Oslo, 2021).
    Google Scholar 
    Hammer, Ø., Harper, D. A. T. & Ryan, P. D. PAST: Paleontological statistics software package for education and data analysis. Palaeontol. Electron. 4, 1–9 (2001).
    Google Scholar 
    Rohland, N., Glocke, I., Aximu-Petri, A. & Meyer, M. Extraction of highly degraded DNA from ancient bones, teeth and sediments for high-throughput sequencing. Nat. Protoc. 13, 2447–2461 (2018).CAS 
    PubMed 
    Article 

    Google Scholar 
    Nguyen, L. T., Schmidt, H. A., Von Haeseler, A. & Minh, B. Q. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol. Biol. Evol. 32, 268–274 (2015).CAS 
    PubMed 
    Article 

    Google Scholar  More

  • in

    Using metabarcoding and droplet digital PCR to investigate drivers of historical shifts in cyanobacteria from six contrasting lakes

    Paerl, H. W. & Huisman, J. Climate change: a catalyst for global expansion of harmful cyanobacterial blooms. Environ. Microbiol. Rep. 1, 27–37 (2009).CAS 
    PubMed 
    Article 

    Google Scholar 
    Paerl, H. W. & Paul, V. J. Climate change: links to global expansion of harmful cyanobacteria. Water Res. 46, 1349–1363 (2012).CAS 
    PubMed 
    Article 

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

    Google Scholar 
    Reissig, M., Trochine, C., Queimaliños, C., Balseiro, E. & Modenutti, B. Impact of fish introduction on planktonic food webs in lakes of the Patagonian Plateau. Biol. Conserv. 132, 437–447 (2006).Article 

    Google Scholar 
    Britton, J. R., Davies, G. D. & Harrod, C. Trophic interactions and consequent impacts of the invasive fish Pseudorasbora parva in a native aquatic foodweb: a field investigation in the UK. Biol. Invasions 12, 1533–1542 (2010).Article 

    Google Scholar 
    Beaulieu, M., Pick, F. & Gregory-Eaves, I. Nutrients and water temperature are significant predictors of cyanobacterial biomass in a 1147 lakes data set. Limnol. Oceanogr. 58, 1736–1746 (2013).ADS 
    CAS 
    Article 

    Google Scholar 
    O’Neil, J. M., Davis, T. W., Burford, M. A. & Gobler, C. J. The rise of harmful cyanobacteria blooms: the potential roles of eutrophication and climate change. Harmful Algae 14, 313–334 (2012).Article 
    CAS 

    Google Scholar 
    Paerl, H. W. & Huisman, J. Blooms like it hot. Science 320, 57–58 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Toxic Cyanobacteria in Water: A Guide to Their Public Health Consequences, Monitoring, and Management. (E & FN Spon, 1999).Sukenik, A., Quesada, A. & Salmaso, N. Global expansion of toxic and non-toxic cyanobacteria: effect on ecosystem functioning. Biodivers. Conserv. 24, 889–908 (2015).Article 

    Google Scholar 
    Ibelings, B. W., Bormans, M., Fastner, J. & Visser, P. M. CYANOCOST special issue on cyanobacterial blooms: synopsis—a critical review of the management options for their prevention, control and mitigation. Aquat. Ecol. 50, 595–605 (2016).CAS 
    Article 

    Google Scholar 
    Paerl, H. W. Mitigating harmful cyanobacterial blooms in a human- and climatically-impacted world. Life 4, 988–1012 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Rastogi, R. P., Madamwar, D. & Incharoensakdi, A. Bloom dynamics of cyanobacteria and their toxins: environmental health impacts and mitigation strategies. Front. Microbiol. https://doi.org/10.3389/fmicb.2015.01254 (2015).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Ewing, H. A. et al. “New” cyanobacterial blooms are not new: two centuries of lake production are related to ice cover and land use. Ecosphere 11, e03170 (2020).Article 

    Google Scholar 
    McGlone, M. S. & Wilmshurst, J. M. Dating initial Maori environmental impact in New Zealand. Quat. Int. 59, 5–16 (1999).Article 

    Google Scholar 
    Brooking, A. P. D. of H. T. & Brooking, T. The History of New Zealand. (Greenwood Publishing Group, 2004).Wilmshurst, J. M., Anderson, A. J., Higham, T. F. G. & Worthy, T. H. Dating the late prehistoric dispersal of Polynesians to New Zealand using the commensal Pacific rat. PNAS 105, 7676–7680 (2008).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McGlone, M. S. The Polynesian settlement of New Zealand in relation to environmental and biotic changes. N. Z. J. Ecol. 12, 115–129 (1989).
    Google Scholar 
    McGlone, M. S. Polynesian deforestation of New Zealand: a preliminary synthesis. Archaeol. Ocean. 18, 11–25 (1983).Article 

    Google Scholar 
    McWethy, D. B. et al. Rapid landscape transformation in South Island, New Zealand, following initial Polynesian settlement. PNAS 107, 21343–21348 (2010).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McWethy, D. B., Wilmshurst, J. M., Whitlock, C., Wood, J. R. & McGlone, M. S. A high-resolution chronology of rapid forest transitions following Polynesian arrival in New Zealand. PLoS ONE 9, e111328 (2014).ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Star, P. New Zealand environmental history: a question of attitudes. Environ. Hist. Camb. 9, 463–475 (2003).Article 

    Google Scholar 
    Clark, A. H. The Invasion of New Zealand by Plants, People, and Animals (Rutgers University Press, 1949).
    Google Scholar 
    Wilmshurst, J. M. Human effects on the environment: European impact. Te Ara: The Encyclopedia of New Zealand https://teara.govt.nz/en/human-effects-on-the-environment/page-3 (2007).Smol, J. P. The ratio of diatom frustules to chrysophycean statospores: a useful paleolimnological index. Hydrobiologia 123, 199–208 (1985).Article 

    Google Scholar 
    Rees, A. B. H., Cwynar, L. C. & Cranston, P. S. Midges (Chironomidae, Ceratopogonidae, Chaoboridae) as a temperature proxy: a training set from Tasmania, Australia. J. Paleolimnol. 40, 1159–1178 (2008).ADS 
    Article 

    Google Scholar 
    Epp, L. S., Stoof, K. R., Trauth, M. H. & Tiedemann, R. Historical genetics on a sediment core from a Kenyan lake: intraspecific genotype turnover in a tropical rotifer is related to past environmental changes. J. Paleolimnol. 43, 939–954 (2010).ADS 
    Article 

    Google Scholar 
    Buchaca, T. et al. Rapid ecological shift following piscivorous fish introduction to increasingly eutrophic and warmer Lake Furnas (Azores Archipelago, Portugal): a paleoecological approach. Ecosystems 14, 458–477 (2011).CAS 
    Article 

    Google Scholar 
    Cristescu, M. E. & Hebert, P. D. N. Uses and misuses of environmental DNA in biodiversity science and conservation. Annu. Rev. Ecol. Evol. Syst. 49, 209–230 (2018).Article 

    Google Scholar 
    Giguet-Covex, C. et al. Long livestock farming history and human landscape shaping revealed by lake sediment DNA. Nat. Commun. 5, 3211 (2014).ADS 
    PubMed 
    Article 
    CAS 

    Google Scholar 
    Alsos, I. G. et al. Plant DNA metabarcoding of lake sediments: how does it represent the contemporary vegetation. PLoS ONE 13, e0195403 (2018).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Nelson-Chorney, H. T. et al. Environmental DNA in lake sediment reveals biogeography of native genetic diversity. Front. Ecol. Environ. 17, 313–318 (2019).
    Google Scholar 
    Capo, E. et al. Lake sedimentary DNA research on past terrestrial and aquatic biodiversity: overview and recommendations. Quaternary 4, 6 (2021).Article 

    Google Scholar 
    Shokralla, S., Spall, J. L., Gibson, J. F. & Hajibabaei, M. Next-generation sequencing technologies for environmental DNA research. Mol. Ecol. 21, 1794–1805 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C. & Willerslev, E. Towards next-generation biodiversity assessment using DNA metabarcoding. Mol. Ecol. 21, 2045–2050 (2012).CAS 
    PubMed 
    Article 

    Google Scholar 
    Thomsen, P. F. & Willerslev, E. Environmental DNA: an emerging tool in conservation for monitoring past and present biodiversity. Biol. Conserv. 183, 4–18 (2015).Article 

    Google Scholar 
    Keeley, N., Wood, S. A. & Pochon, X. Development and preliminary validation of a multi-trophic metabarcoding biotic index for monitoring benthic organic enrichment. Ecol. Ind. 85, 1044–1057 (2018).CAS 
    Article 

    Google Scholar 
    Monchamp, M.-E., Walser, J.-C., Pomati, F. & Spaak, P. Sedimentary DNA reveals cyanobacterial community diversity over 200 years in two perialpine lakes. Appl. Environ. Microbiol. 82, 6472–6482 (2016).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Pal, S., Gregory-Eaves, I. & Pick, F. R. Temporal trends in cyanobacteria revealed through DNA and pigment analyses of temperate lake sediment cores. J. Paleolimnol. 54, 87–101 (2015).ADS 
    Article 

    Google Scholar 
    Dodsworth, W. Temporal Trends in Cyanobacteria Through Paleo-Genetic Analyses. (Université d’Ottawa/University of Ottawa, 2020). https://doi.org/10.20381/ruor-24401.Rinta-Kanto, J. M. et al. The diversity and distribution of toxigenic Microcystis spp. in present day and archived pelagic and sediment samples from Lake Erie. Harmful Algae 8, 385–394 (2009).CAS 
    Article 

    Google Scholar 
    Zastepa, A. et al. Reconstructing a long-term record of microcystins from the analysis of lake sediments. Sci. Total Environ. 579, 893–901 (2017).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Schallenberg, M. et al. Ecosystem services of lakes. In Ecosystem Services in New Zealand (ed. Dymond, J.) 23 (Manaaki Whenua Press, 2013).
    Google Scholar 
    Ministry for the Environment & Ausseil, A.-G. Our freshwater 2020. www.mfe.govt.nz (2020).Takiwa—Map Page. https://lernz.takiwa.co/map.Leathwick, J. et al. Freshwater ecosystems of New Zealand (FENZ) geodatabase. Users guide. (2010).Cochrane, L. Reconstructing Ecological Change, Catchment Disturbance, and Anthropogenic Impact over the last 3000 years at Lake Pounui, Wairarapa, New Zealand. (2017).Burns, C. W. & Mitchell, S. F. Seasonal succession and vertical distribution of phytoplankton in Lake Hayes and Lake Johnson, South Island, New Zealand. N. Z. J. Mar. Freshw. Res. 8, 167–209 (1974).Article 

    Google Scholar 
    Lawa. Land, Air, Water Aotearoa (LAWA) https://www.lawa.org.nz/ (2018).Bunny, T., Perrie, A., Milne, J. & Keenan, L. Lake water quality in the Ruamāhanga Whaitua. 17 (2014).McKinnon, M. Volcanic Plateau region: The lure of trout. Te Ara—The Encyclopedia of New Zealand https://teara.govt.nz/en/volcanic-plateau-region/page-8 (2015).Burns, C. W. & Mitchell, S. F. Seasonal succession and vertical distribution of zooplankton in Lake Hayes and Lake Johnson. N. Z. J. Mar. Freshw. Res. 14, 189–204 (1980).Article 

    Google Scholar 
    Schallenberg, M. & Schallenberg, L. Lake Hayes restoration and monitoring plan. 55 https://a234f952-dbf2-444e-983e-ef311d984ee7.filesusr.com/ugd/c1b10b_d2993ed023cd4bdbac7eef71a89c2de7.pdf (2017).NIWA. NIWA https://niwa.co.nz/.Mackereth, F. J. H. A portable core sampler for lake deposits. Limnol. Oceanogr. 3, 181–191 (1958).ADS 
    Article 

    Google Scholar 
    Howarth, J. D., Fitzsimons, S. J., Norris, R. J. & Jacobsen, G. E. Lake sediments record cycles of sediment flux driven by large earthquakes on the Alpine fault, New Zealand. Geology 40, 1091–1094 (2012).ADS 
    CAS 
    Article 

    Google Scholar 
    Trodahl, M. I., Rees, A. B. H., Newnham, R. M. & Vandergoes, M. J. Late Holocene geomorphic history of Lake Wairarapa, North Island, New Zealand. N. Z. J. Geol. Geophys. 59, 330–340 (2016).CAS 
    Article 

    Google Scholar 
    Khan, S., Puddick, J., Burns, C. W., Closs, G. & Schallenberg, M. Palaeolimnological evaluation of historical nutrient and food web contributions to the eutrophication of two monomictic lakes. Submitted for Journal Publication (2022).Rinta-Kanto, J. M. et al. Quantification of toxic Microcystis spp. during the 2003 and 2004 blooms in Western Lake Erie using quantitative real-time PCR. Environ. Sci. Technol. 39, 4198–4205 (2005).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Nübel, U., Garcia-Pichel, F. & Muyzer, G. PCR primers to amplify 16S rRNA genes from cyanobacteria. Appl. Environ. Microbiol. 63, 3327–3332 (1997).ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    R Core Team. R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2020).RStudio Team. RStudio: Integrated Development for R. RStudio, PBC, Boston, MA. (2020).Wickham, H. et al. Welcome to the Tidyverse. J. Open Sour. Softw. 4, 1686 (2019).ADS 
    Article 

    Google Scholar 
    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, 2016).MATH 
    Book 

    Google Scholar 
    Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).Article 

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

    Google Scholar 
    Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2013).CAS 
    PubMed 
    Article 

    Google Scholar 
    Yilmaz, P. et al. The SILVA and “all-species living tree project (LTP)” taxonomic frameworks. Nucleic Acids Res. 42, D643–D648 (2013).PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Glöckner, F. O. et al. 25 years of serving the community with ribosomal RNA gene reference databases and tools. J. Biotechnol. 261, 169–176 (2017).PubMed 
    Article 
    CAS 

    Google Scholar 
    McMurdie, P. J. & Holmes, S. phyloseq: an R Package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Oksanen, J. et al. vegan: Community Ecology Package. R package version 2.5–6. 2019. (2019).Williams, P. A. & Cameron, E. K. Creating gardens: the diversity and progression of European plant introductions. In Biological Invasions in New Zealand Vol. 186 (eds Allen, R. B. & Lee, W. G.) 33–47 (Springer-Verlag, 2006).Chapter 

    Google Scholar 
    Simpson, G. L. Modelling palaeoecological time series using generalised additive models. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00149 (2018).Article 

    Google Scholar 
    Chen, H. & Boutros, P. C. VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC Bioinform. 12, 35 (2011).Article 

    Google Scholar 
    Juggins, S. rioja: analysis of quaternary science data. (2020).de Vries, A. & Ripley, B. D. ggdendro: create dendrograms and tree diagrams using ‘ggplot2’. (2022).Anderson, M. J. A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32–46 (2001).
    Google Scholar 
    Anderson, M. J. Distance-based tests for homogeneity of multivariate dispersions. Biometrics 62, 245–253 (2006).MathSciNet 
    PubMed 
    MATH 
    Article 

    Google Scholar 
    Soo, R. M. et al. An expanded genomic representation of the phylum Cyanobacteria. Genome Biol. Evol. 6, 1031–1045 (2014).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    MacKeigan, P. W. et al. Comparing microscopy and DNA metabarcoding techniques for identifying cyanobacteria assemblages across hundreds of lakes. Harmful Algae 113, 102187 (2022).CAS 
    PubMed 
    Article 

    Google Scholar 
    Wood, S. A. et al. Trophic state and geographic gradients influence planktonic cyanobacterial diversity and distribution in New Zealand lakes. FEMS Microbiol. Ecol. https://doi.org/10.1093/femsec/fiw234 (2017).Article 
    PubMed 

    Google Scholar 
    Becker, S., Richl, P. & Ernst, A. Seasonal and habitat-related distribution pattern of Synechococcus genotypes in Lake Constance. FEMS Microbiol. Ecol. 62, 64–77 (2007).CAS 
    PubMed 
    Article 

    Google Scholar 
    Sánchez-Baracaldo, P., Handley, B. A. & Hayes, P. K. Picocyanobacterial community structure of freshwater lakes and the Baltic Sea revealed by phylogenetic analyses and clade-specific quantitative PCR. Microbiology (Reading) 154, 3347–3357 (2008).Article 
    CAS 

    Google Scholar 
    Pilon, S. et al. Contrasting histories of microcystin-producing cyanobacteria in two temperate lakes as inferred from quantitative sediment DNA analyses. Lake Reserv. Manag. 35, 102–117 (2019).CAS 
    Article 

    Google Scholar 
    Queenstown’s Pioneering Beginnings. https://www.queenstownnz.co.nz/stories/post/queenstowns-pioneer-beginnings/ (2017).Fish, G. R. A limnological study of four lakes near Rotorua. N. Z. J. Mar. Freshw. Res. 4, 165–194 (1970).Article 

    Google Scholar 
    Lake Rotoehu—Lakes Water Quality Society. https://lakeswaterquality.co.nz/lake-rotoehu/.Bay of Plenty Regional Council, Rotorua District Council, & Te Arawa Lakes Trust. Lake Rotoehu Action Plan. 61 http://www.rotorualakes.co.nz/vdb/document/76 (2007).Hobbs, W. O. et al. Using a lake sediment record to infer the long-term history of cyanobacteria and the recent rise of an anatoxin producing Dolichospermum sp.. Harmful Algae 101, 101971 (2021).CAS 
    PubMed 
    Article 

    Google Scholar 
    de la Escalera, G. M., Antoniades, D., Bonilla, S. & Piccini, C. Application of ancient DNA to the reconstruction of past microbial assemblages and for the detection of toxic cyanobacteria in subtropical freshwater ecosystems. Mol. Ecol. 23, 5791–5802 (2014).Article 
    CAS 

    Google Scholar 
    Retrolens—Historical Imagery Resource. https://retrolens.co.nz/.Strayer, D. L. Alien species in fresh waters: ecological effects, interactions with other stressors, and prospects for the future. Freshw. Biol. 55, 152–174 (2010).Article 

    Google Scholar 
    Hall, S. R. & Mills, E. L. Exotic species in large lakes of the world. Aquat. Ecosyst. Health Manag. 3, 105–135 (2000).Article 

    Google Scholar 
    Gehrke, P. C. & Harris, J. H. The role of fish in cyanobacterial blooms in Australia. Mar. Freshw. Res. 45, 905–915 (1994).Article 

    Google Scholar 
    Burns, C. W. & Schallenberg, M. Impacts of nutrients and zooplankton on the microbial food web of an ultra-oligotrophic lake. J. Plankton Res. 20, 1501–1525 (1998).Article 

    Google Scholar 
    Rowe, D. K. & Schallenberg, M. Food webs in lakes. In Freshwaters of New Zealand (ed. Harding, J. S.) 23 (Wellington, N.Z.: New Zealand Hydrological Society, 2004).Gliwicz, Z. M. & Pijanowska, J. The role of predation in zooplankton succession. In Plankton Ecology: Succession in Plankton Communities (ed. Sommer, U.) 253–296 (Springer, 1989).Chapter 

    Google Scholar 
    Vanni, M. J. & Findlay, D. L. Trophic cascades and phytoplankton community structure. Ecology 71, 921–937 (1990).Article 

    Google Scholar 
    Smith, K. F. & Lester, P. J. Trophic interactions promote dominance by cyanobacteria (Anabaena spp.) in the pelagic zone of lower Karori reservoir, Wellington, New Zealand. N. Z. J. Mar. Freshw. Res. 41, 143–155 (2007).Article 

    Google Scholar 
    Smith, K. F. & Lester, P. J. Cyanobacterial blooms appear to be driven by top-down rather than bottom-up effects in the Lower Karori Reservoir (Wellington, New Zealand). N. Z. J. Mar. Freshw. Res. 40, 53–63 (2006).CAS 
    Article 

    Google Scholar 
    Caroppo, C. Ecology and biodiversity of picoplanktonic cyanobacteria in coastal and brackish environments. Biodivers. Conserv. 24, 949–971 (2015).Article 

    Google Scholar 
    Pulina, S. et al. Picophytoplankton seasonal dynamics and interactions with environmental variables in three Mediterranean coastal lagoons. Estuaries Coasts 40, 469–478 (2017).CAS 
    Article 

    Google Scholar 
    Callieri, C. Picophytoplankton in freshwater ecosystems: the importance of small-sized phototrophs. Freshw. Rev. 1, 1–28 (2008).Article 

    Google Scholar 
    Keefer, D. K. Investigating landslides caused by earthquakes: a historical review. Surv. Geophys. 23, 473–510 (2002).ADS 
    Article 

    Google Scholar 
    Fan, X. et al. Earthquake-induced chains of geologic hazards: patterns, mechanisms, and impacts. Rev. Geophys. 57, 421–503 (2019).ADS 
    Article 

    Google Scholar 
    Manighetti, I. et al. Repeated giant earthquakes on the Wairarapa fault, New Zealand, revealed by Lidar-based paleoseismology. Sci. Rep. 10, 2124 (2020).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    McSaveney, E. Historic earthquakes: the 1942 Wairarapa earthquakes. Te Ara Encyclopedia of New Zealand https://teara.govt.nz/en/historic-earthquakes/page-9 (2006).New Zealand’s environmental reporting series: our atmosphere and climate. (Ministry for the Environment & Stats NZ, 2020).Beng, K. C. & Corlett, R. T. Applications of environmental DNA (eDNA) in ecology and conservation: opportunities, challenges and prospects. Biodivers. Conserv. 29, 2089–2121 (2020).Article 

    Google Scholar 
    Freeland, J. R. The importance of molecular markers and primer design when characterizing biodiversity from environmental DNA. Genome https://doi.org/10.1139/gen-2016-0100 (2016).Article 
    PubMed 

    Google Scholar 
    Barnes, M. A. et al. Environmental conditions influence eDNA persistence in aquatic systems. Environ. Sci. Technol. 48, 1819–1827 (2014).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Barnes, M. A. et al. Environmental conditions influence eDNA particle size distribution in aquatic systems. Environmental DNA https://doi.org/10.1002/edn3.160 (2020).Article 

    Google Scholar 
    Corinaldesi, C., Beolchini, F. & Dell’anno, A. Damage and degradation rates of extracellular DNA in marine sediments: implications for the preservation of gene sequences. Mol. Ecol. 17, 3939–3951 (2008).CAS 
    PubMed 
    Article 

    Google Scholar 
    Eichmiller, J. J., Best, S. E. & Sorensen, P. W. Effects of temperature and trophic state on degradation of environmental DNA in lake water. Environ. Sci. Technol. 50, 1859–1867 (2016).ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 
    Strickler, K. M., Fremier, A. K. & Goldberg, C. S. Quantifying effects of UV-B, temperature, and pH on eDNA degradation in aquatic microcosms. Biol. Conserv. 183, 85–92 (2015).Article 

    Google Scholar 
    Seymour, M. et al. Acidity promotes degradation of multi-species environmental DNA in lotic mesocosms. Commun. Biol. https://doi.org/10.1038/s42003-017-0005-3 (2018).Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    Dommain, R. et al. The challenges of reconstructing tropical biodiversity with sedimentary ancient DNA: a 2200-year-long metagenomic record from Bwindi Impenetrable Forest, Uganda. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2020.00218 (2020).Article 

    Google Scholar 
    Jöhnk, K. D. et al. Summer heatwaves promote blooms of harmful cyanobacteria. Glob. Change Biol. 14, 495–512 (2008).ADS 
    Article 

    Google Scholar 
    Sogin, M. L. et al. Microbial diversity in the deep sea and the underexplored “rare biosphere”. PNAS 103, 12115–12120 (2006).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar  More

  • in

    Plant phenology changes and drivers on the Qinghai–Tibetan Plateau

    Lieth, H. Phenology and Seasonality Modeling Vol. 8 (Springer, 2013).Piao, S. et al. Plant phenology and global climate change: current progresses and challenges. Glob. Change Biol. 25, 1922–1940 (2019).Article 

    Google Scholar 
    Shen, M. et al. Can changes in autumn phenology facilitate earlier green-up date of northern vegetation? Agric. For. Meteorol. 291, 108077 (2020).Article 

    Google Scholar 
    Menzel, A. et al. Climate change fingerprints in recent European plant phenology. Glob. Change Biol. 26, 2599–2612 (2020).Article 

    Google Scholar 
    Shen, X. et al. Asymmetric effects of daytime and nighttime warming on spring phenology in the temperate grasslands of China. Agric. For. Meteorol. 259, 240–249 (2018).Article 

    Google Scholar 
    Rudolf, V. H. W. The role of seasonal timing and phenological shifts for species coexistence. Ecol. Lett. 22, 1324–1338 (2019).
    Google Scholar 
    Zhu, J., Zhang, Y. & Wang, W. Interactions between warming and soil moisture increase overlap in reproductive phenology among species in an alpine meadow. Biol. Lett. 12, 20150749 (2016).Article 

    Google Scholar 
    Chen, J. et al. Plants with lengthened phenophases increase their dominance under warming in an alpine plant community. Sci. Total Environ. 728, 138891 (2020).Article 

    Google Scholar 
    Lian, X. et al. Summer soil drying exacerbated by earlier spring greening of northern vegetation. Sci. Adv. 6, eaax0255 (2020).Article 

    Google Scholar 
    Wolkovich, E. M. & Donahue, M. J. How phenological tracking shapes species and communities in non-stationary environments. Biol. Rev. Camb. Philos. Soc. 96, 2810–2827 (2021).Article 

    Google Scholar 
    Xu, X., Riley, W. J., Koven, C. D., Jia, G. & Zhang, X. Earlier leaf-out warms air in the north. Nat. Clim. Chang. 10, 370–375 (2020).Article 

    Google Scholar 
    D’Amato, G. et al. The effects of climate change on respiratory allergy and asthma induced by pollen and mold allergens. Allergy 75, 2219–2228 (2020).Article 

    Google Scholar 
    Garcia-Mozo, H. Poaceae pollen as the leading aeroallergen worldwide: a review. Allergy 72, 1849–1858 (2017).Article 

    Google Scholar 
    Ge, Q., Dai, J., Liu, J., Zhong, S. & Liu, H. The effect of climate change on the fall foliage vacation in China. Tour. Manag. 38, 80–84 (2013).Article 

    Google Scholar 
    Liu, J., Cheng, H., Jiang, D. & Huang, L. Impact of climate-related changes to the timing of autumn foliage colouration on tourism in Japan. Tour. Manag. 70, 262–272 (2019).Article 

    Google Scholar 
    Fan, B. et al. Earlier vegetation green-up has reduced spring dust storms. Sci. Rep. 4, 6749 (2014).Article 

    Google Scholar 
    Minoli, S. et al. Global response patterns of major rainfed crops to adaptation by maintaining current growing periods and irrigation. Earths Future 7, 1464–1480 (2019).Article 

    Google Scholar 
    Shen, M. et al. Plant phenological responses to climate change on the Tibetan Plateau: research status and challenges. Natl Sci. Rev. 22, 454–467 (2015).Article 

    Google Scholar 
    You, Q., Wang, D., Jiang, Z. & Kang, S. Diurnal temperature range in CMIP5 models and observations on the Tibetan Plateau. Q. J. R. Meteorol. Soc. 143, 1978–1989 (2017).Article 

    Google Scholar 
    You, Q. et al. Temperature dataset of CMIP6 models over China: evaluation, trend and uncertainty. Clim. Dyn. 57, 17–35 (2021).Article 

    Google Scholar 
    Zhu, Y.-Y. & Yang, S. Evaluation of CMIP6 for historical temperature and precipitation over the Tibetan Plateau and its comparison with CMIP5. Adv. Clim. Change Res. 11, 239–251 (2020).Article 

    Google Scholar 
    Lun, Y. et al. Assessment of GCMs simulation performance for precipitation and temperature from CMIP5 to CMIP6 over the Tibetan Plateau. Int. J. Climatol. 41, 3994–4018 (2021).Article 

    Google Scholar 
    Song, L., Zhuang, Q., Yin, Y., Wu, S. & Zhu, X. Intercomparison of model-estimated potential evapotranspiration on the Tibetan Plateau during 1981–2010. Earth Interact. 21, 1–22 (2017).Article 

    Google Scholar 
    You, Q., Min, J. & Kang, S. Rapid warming in the Tibetan Plateau from observations and CMIP5 models in recent decades. Int. J. Climatol. 36, 2660–2670 (2016).Article 

    Google Scholar 
    He, J.-S. et al. Above-belowground interactions in alpine ecosystems on the roof of the world. Plant Soil 458, 1–6 (2020).Article 

    Google Scholar 
    Kuang, X. & Jiao, J. J. Review on climate change on the Tibetan Plateau during the last half century. J. Geophys. Res. Atmos. 121, 3979–4007 (2016).Article 

    Google Scholar 
    Shen, M., Piao, S., Cong, N., Zhang, G. & Jassens, I. A. Precipitation impacts on vegetation spring phenology on the Tibetan Plateau. Glob. Change Biol. 21, 3647–3656 (2015).Article 

    Google Scholar 
    Shen, M., Tang, Y., Chen, J., Zhu, X. & Zheng, Y. Influences of temperature and precipitation before the growing season on spring phenology in grasslands of the central and eastern Qinghai-Tibetan Plateau. Agric. For. Meteorol. 151, 1711–1722 (2011).Article 

    Google Scholar 
    Ganjurjav, H. et al. Warming and precipitation addition interact to affect plant spring phenology in alpine meadows on the central Qinghai-Tibetan Plateau. Agric. For. Meteorol. 287, 107943 (2020).Article 

    Google Scholar 
    Peng, J., Wu, C., Wang, X. & Lu, L. Spring phenology outweighed climate change in determining autumn phenology on the Tibetan Plateau. Int. J. Climatol. 41, 3725–3742 (2021).Article 

    Google Scholar 
    Chen, X., An, S., Inouye, D. W. & Schwartz, M. D. Temperature and snowfall trigger alpine vegetation green-up on the world’s roof. Glob. Change Biol. 21, 3635–3646 (2015).Article 

    Google Scholar 
    Zheng, Z. et al. Continuous but diverse advancement of spring-summer phenology in response to climate warming across the Qinghai-Tibetan Plateau. Agric. For. Meteorol. 223, 194–202 (2016).Article 

    Google Scholar 
    Zhu, W. et al. Divergent shifts and responses of plant autumn phenology to climate change on the Qinghai-Tibetan Plateau. Agric. For. Meteorol. 239, 166–175 (2017).Article 

    Google Scholar 
    Sun, Q., Li, B., Jiang, Y., Chen, X. & Zhou, G. Declined trend in herbaceous plant green-up dates on the Qinghai–Tibetan Plateau caused by spring warming slowdown. Sci. Total Environ. 772, 145039 (2021).Article 

    Google Scholar 
    Sun, Q., Li, B., Zhou, G., Jiang, Y. & Yuan, Y. Delayed autumn leaf senescence date prolongs the growing season length of herbaceous plants on the Qinghai–Tibetan Plateau. Agric. For. Meteorol. 284, 107896 (2020).Article 

    Google Scholar 
    Jiang, Y. et al. Divergent shifts in flowering phenology of herbaceous plants on the warming Qinghai–Tibetan plateau. Agric. For. Meteorol. 307, 108502 (2021).Article 

    Google Scholar 
    Cong, N., Shen, M. & Piao, S. Spatial variations in responses of vegetation autumn phenology to climate change on the Tibetan Plateau. J. Plant Ecol. 10, 744–752 (2016).
    Google Scholar 
    Shi, C. et al. Effects of warming on chlorophyll degradation and carbohydrate accumulation of Alpine herbaceous species during plant senescence on the Tibetan Plateau. PLoS ONE 9, e107874 (2014).Article 

    Google Scholar 
    Morisette, J. T. et al. Tracking the rhythm of the seasons in the face of global change: phenological research in the 21st century. Front. Ecol. Environ. 7, 253–260 (2009).Article 

    Google Scholar 
    Kharouba, H. M. et al. Global shifts in the phenological synchrony of species interactions over recent decades. Proc. Natl Acad. Sci. USA 115, 5211–5216 (2018).Article 

    Google Scholar 
    Vitasse, Y. et al. Phenological and elevational shifts of plants, animals and fungi under climate change in the European Alps. Biol. Rev. Camb. Philos. Soc. 96, 1816–1835 (2021).Article 

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

    Google Scholar 
    Keenan, T. F. et al. Net carbon uptake has increased through warming-induced changes in temperate forest phenology. Nat. Clim. Chang. 4, 598–604 (2014).Article 

    Google Scholar 
    Estiarte, M. & Penuelas, J. Alteration of the phenology of leaf senescence and fall in winter deciduous species by climate change: effects on nutrient proficiency. Glob. Change Biol. 21, 1005–1017 (2015).Article 

    Google Scholar 
    Penuelas, J., Rutishauser, T. & Filella, I. Ecology. Phenology feedbacks on climate change. Science 324, 887–888 (2009).Article 

    Google Scholar 
    Piao, S. et al. Weakening temperature control on the interannual variations of spring carbon uptake across northern lands. Nat. Clim. Chang. 7, 359–363 (2017).Article 

    Google Scholar 
    Ran, Y., Li, X. & Cheng, G. Climate warming over the past half century has led to thermal degradation of permafrost on the Qinghai–Tibet Plateau. Cryosphere 12, 595–608 (2018).Article 

    Google Scholar 
    Gao, T. et al. Accelerating permafrost collapse on the eastern Tibetan Plateau. Environ. Res. Lett. 16, 054023 (2021).Article 

    Google Scholar 
    Sun, R. et al. Interannual variability of the North Pacific mixed layer associated with the spring Tibetan Plateau thermal forcing. J. Clim. 32, 3109–3130 (2019).Article 

    Google Scholar 
    Zhang, J., Wu, L., Huang, G., Zhu, W. & Zhang, Y. The role of May vegetation greenness on the southeastern Tibetan Plateau for East Asian summer monsoon prediction. J. Geophys. Res. Atmos. 116, D05106 (2011).Article 

    Google Scholar 
    Wu, G. et al. Tibetan Plateau climate dynamics: recent research progress and outlook. Natl Sci. Rev. 2, 100–116 (2015).Article 

    Google Scholar 
    Wang, Y., Zhao, P., Yu, R. & Rasul, G. Inter-decadal variability of Tibetan spring vegetation and its associations with eastern China spring rainfall. Int. J. Climatol. 30, 856–865 (2010).Article 

    Google Scholar 
    Yu, H., Luedeling, E. & Xu, J. Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proc. Natl Acad. Sci. USA 107, 22151–22156 (2010).Article 

    Google Scholar 
    Shen, M. et al. Increasing altitudinal gradient of spring vegetation phenology during the last decade on the Qinghai–Tibetan Plateau. Agric. For. Meteorol. 189-190, 71–80 (2014).Article 

    Google Scholar 
    Wang, X. et al. No consistent evidence for advancing or delaying trends in spring phenology on the Tibetan Plateau. J. Geophys. Res. Biogeosci. 122, 3288–3305 (2017).Article 

    Google Scholar 
    Wang, C. et al. Assessing phenological change and climatic control of alpine grasslands in the Tibetan Plateau with MODIS time series. Int. J. Biometeorol. 59, 11–23 (2015).Article 

    Google Scholar 
    Wang, K. et al. Snow effects on alpine vegetation in the Qinghai-Tibetan Plateau. Int. J. Digit. Earth 8, 58–75 (2013).Article 

    Google Scholar 
    Meng, F., Huang, L., Chen, A., Zhang, Y. & Piao, S. Spring and autumn phenology across the Tibetan Plateau inferred from normalized difference vegetation index and solar-induced chlorophyll fluorescence. Big Earth Data 5, 182–200 (2021).Article 

    Google Scholar 
    Wang, X., Wu, C., Peng, D., Gonsamo, A. & Liu, Z. Snow cover phenology affects alpine vegetation growth dynamics on the Tibetan Plateau: satellite observed evidence, impacts of different biomes, and climate drivers. Agric. For. Meteorol. 256–257, 61–74 (2018).Article 

    Google Scholar 
    Li, P. et al. Change in autumn vegetation phenology and the climate controls from 1982 to 2012 on the Qinghai–Tibet Plateau. Front. Plant Sci. 10, 1677 (2019).Article 

    Google Scholar 
    Zhu, W., Zheng, Z., Jiang, N. & Zhang, D. A comparative analysis of the spatio-temporal variation in the phenologies of two herbaceous species and associated climatic driving factors on the Tibetan Plateau. Agric. For. Meteorol. 248, 177–184 (2018).Article 

    Google Scholar 
    Xia, J. et al. Interannual variation in the start of vegetation growing season and its response to climate change in the Qinghai–Tibet Plateau derived from MODIS data during 2001 to 2016. J. Appl. Remote Sens. 13, 048506 (2019).Article 

    Google Scholar 
    Huang, K. et al. Impacts of snow cover duration on vegetation spring phenology over the Tibetan Plateau. J. Plant Ecol. 12, 583–592 (2019).Article 

    Google Scholar 
    Li, P. et al. Dynamics of vegetation autumn phenology and its response to multiple environmental factors from 1982 to 2012 on Qinghai-Tibetan Plateau in China. Sci. Total Environ. 637-638, 855–864 (2018).Article 

    Google Scholar 
    Liu, X. et al. Driving forces of the changes in vegetation phenology in the Qinghai–Tibet Plateau. Remote Sens. 13, 4952 (2021).Article 

    Google Scholar 
    Piao, S. et al. Altitude and temperature dependence of change in the spring vegetation green-up date from 1982 to 2006 in the Qinghai–Xizang Plateau. Agric. For. Meteorol. 151, 1599–1608 (2011).Article 

    Google Scholar 
    Wang, Z. et al. Causes for the unimodal pattern of biomass and productivity in alpine grasslands along a large altitudinal gradient in semi-arid regions. J. Veg. Sci. 24, 189–201 (2013).Article 

    Google Scholar 
    Du, M. et al. in Proc. MODSIM 2007 Int. Congr. Model. Simul. (eds Oxley, L. & Kulasiri, D.) 2146–2152 (Modelling and Simulation Society of Australia and New Zealand, 2007).Wang, S. P. et al. Asymmetric sensitivity of first flowering date to warming and cooling in alpine plants. Ecology 95, 3387–3398 (2014).Article 

    Google Scholar 
    Che, M. et al. Spatial and temporal variations in the end date of the vegetation growing season throughout the Qinghai–Tibetan Plateau from 1982 to 2011. Agric. For. Meteorol. 189–190, 81–90 (2014).Article 

    Google Scholar 
    Zhang, G., Zhang, Y., Dong, J. & Xiao, X. Green-up dates in the Tibetan Plateau have continuously advanced from 1982 to 2011. Proc. Natl Acad. Sci. USA 110, 4309–4314 (2013).Article 

    Google Scholar 
    Maisongrande, P., Duchemin, B. & Dedieu, G. VEGETATION/SPOT: an operational mission for the Earth monitoring; presentation of new standard products. Int. J. Remote Sens. 25, 9–14 (2010).Article 

    Google Scholar 
    Didan, K., Munoz, A. B., Solano, R. & Huete, A. MODIS vegetation index user’s guide (MOD13 series) version 3.00, June 2015 (collection 6) (Univ. Arizona, 2015).Beck, H. E. et al. Global evaluation of four AVHRR–NDVI data sets: intercomparison and assessment against Landsat imagery. Remote Sens. Environ. 115, 2547–2563 (2011).Article 

    Google Scholar 
    Zhang, Y., Song, C., Band, L. E., Sun, G. & Li, J. Reanalysis of global terrestrial vegetation trends from MODIS products: browning or greening? Remote Sens. Environ. 191, 145–155 (2017).Article 

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

    Google Scholar 
    Ding, M. et al. Temperature dependence of variations in the end of the growing season from 1982 to 2012 on the Qinghai–Tibetan Plateau. GISci. Remote Sens. 53, 147–163 (2015).Article 

    Google Scholar 
    Cheng, M., Jin, J. & Jiang, H. Strong impacts of autumn phenology on grassland ecosystem water use efficiency on the Tibetan Plateau. Ecol. Indic. 126, 107682 (2021).Article 

    Google Scholar 
    Pedelty, J. et al. in Proc. 2007 IEEE Int. Geosci. Remote Sensing Symp. 1021–1025 (IEEE, 2007).Pinzon, J. & Tucker, C. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sens. 6, 6929–6960 (2014).Article 

    Google Scholar 
    Liu, Y., Liu, R. & Chen, J. M. Retrospective retrieval of long-term consistent global leaf area index (1981–2011) from combined AVHRR and MODIS data. J. Geophys. Res. Biogeosci. 117, G04003 (2012).Article 

    Google Scholar 
    Yang, B. et al. New perspective on spring vegetation phenology and global climate change based on Tibetan Plateau tree-ring data. Proc. Natl Acad. Sci. USA 114, 6966–6971 (2017).Article 

    Google Scholar 
    Shishov, V. V. et al. VS-oscilloscope: a new tool to parameterize tree radial growth based on climate conditions. Dendrochronologia 39, 42–50 (2016).Article 

    Google Scholar 
    Zhao, Y., Zhou, T., Zhang, W. & Li, J. Change in precipitation over the Tibetan Plateau projected by weighted CMIP6 models. Adv. Atmos. Sci. 39, 1133–1150 (2022).Article 

    Google Scholar 
    Lalande, M., Ménégoz, M., Krinner, G., Naegeli, K. & Wunderle, S. Climate change in the High Mountain Asia in CMIP6. Earth Syst. Dyn. 12, 1061–1098 (2021).Article 

    Google Scholar 
    Jin, Z. et al. Temporal variability in the thermal requirements for vegetation phenology on the Tibetan plateau and its implications for carbon dynamics. Clim. Change 138, 617–632 (2016).Article 

    Google Scholar 
    Eyring, V. et al. Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organization. Geosci. Model Dev. 9, 1937–1958 (2016).Article 

    Google Scholar 
    Cao, R., Shen, M., Zhou, J. & Chen, J. Modeling vegetation green-up dates across the Tibetan Plateau by including both seasonal and daily temperature and precipitation. Agric. For. Meteorol. 249, 176–186 (2018).Article 

    Google Scholar 
    Li, P. et al. Combined control of multiple extreme climate stressors on autumn vegetation phenology on the Tibetan Plateau under past and future climate change. Agric. For. Meteorol. 308–309, 108571 (2021).Article 

    Google Scholar 
    Lang, W., Chen, X., Qian, S., Liu, G. & Piao, S. A new process-based model for predicting autumn phenology: how is leaf senescence controlled by photoperiod and temperature coupling? Agric. For. Meteorol. 268, 124–135 (2019).Article 

    Google Scholar 
    Yang, Z. et al. Phylogenetic conservatism in heat requirement of leaf-out phenology, rather than temperature sensitivity, in Tibetan Plateau. Agric. For. Meteorol. 304-305, 108413 (2021).Article 

    Google Scholar 
    Gao, B., Li, J. & Wang, X. Impact of frozen soil changes on vegetation phenology in the source region of the Yellow River from 2003 to 2015. Theor. Appl. Climatol. 141, 1219–1234 (2020).Article 

    Google Scholar 
    Jiang, H. et al. The impacts of soil freeze/thaw dynamics on soil water transfer and spring phenology in the Tibetan Plateau. Arct. Antarct. Alp. Res. 50, e1439155 (2018).Article 

    Google Scholar 
    Li, G., Jiang, C., Cheng, T. & Bai, J. Grazing alters the phenology of alpine steppe by changing the surface physical environment on the northeast Qinghai-Tibet Plateau, China. J. Environ. Manage. 248, 109257 (2019).Article 

    Google Scholar 
    Du, J. et al. Interacting effects of temperature and precipitation on climatic sensitivity of spring vegetation green-up in arid mountains of China. Agric. For. Meteorol. 269–270, 71–77 (2019).Article 

    Google Scholar 
    Liu, L. et al. Effects of elevation on spring phenological sensitivity to temperature in Tibetan Plateau grasslands. Chin. Sci. Bull. 59, 4856–4863 (2014).Article 

    Google Scholar 
    Cong, N. et al. Little change in heat requirement for vegetation green-up on the Tibetan Plateau over the warming period of 1998–2012. Agric. For. Meteorol. 232, 650–658 (2017).Article 

    Google Scholar 
    Shen, M. et al. Strong impacts of daily minimum temperature on the green-up date and summer greenness of the Tibetan Plateau. Glob. Change Biol. 22, 3057–3066 (2016).Article 

    Google Scholar 
    Du, J. et al. Daily minimum temperature and precipitation control on spring phenology in arid-mountain ecosystems in China. Int. J. Climatol. 40, 2568–2579 (2020).Article 

    Google Scholar 
    Shen, M. Spring phenology was not consistently related to winter warming on the Tibetan Plateau. Proc. Natl Acad. Sci. USA 108, E91–E92 (2011).Article 

    Google Scholar 
    An, S. et al. Precipitation and minimum temperature are primary climatic controls of alpine grassland autumn phenology on the Qinghai-Tibet Plateau. Remote Sens. 12, 431 (2020).Article 

    Google Scholar 
    Zu, J. et al. Biological and climate factors co-regulated spatial-temporal dynamics of vegetation autumn phenology on the Tibetan Plateau. Int. J. Appl. Earth Obs. Geoinf. 69, 198–205 (2018).
    Google Scholar 
    Qiao, C. et al. Vegetation phenology in the Qilian mountains and its response to temperature from 1982 to 2014. Remote Sens. 13, 286 (2021).Article 

    Google Scholar 
    Yang, Z. et al. Asymmetric responses of the end of growing season to daily maximum and minimum temperatures on the Tibetan Plateau. J. Geophys. Res. Atmos. 122, 13,78–13,287 (2017).
    Google Scholar 
    Dorji, T. et al. Plant functional traits mediate reproductive phenology and success in response to experimental warming and snow addition in Tibet. Glob. Change Biol. 19, 459–472 (2013).Article 

    Google Scholar 
    Li, X., Zhang, L. & Luo, T. Rainy season onset mainly drives the spatiotemporal variability of spring vegetation green-up across alpine dry ecosystems on the Tibetan Plateau. Sci. Rep. 10, 18797 (2020).Article 

    Google Scholar 
    Zhang, X. et al. Effects of climate change on the growing season of alpine grassland in Northern Tibet, China. Glob. Ecol. Conserv. 23, e01126 (2020).Article 

    Google Scholar 
    Sun, Q. et al. A prognostic phenology model for alpine meadows on the Qinghai–Tibetan Plateau. Ecol. Indic. 93, 1089–1100 (2018).Article 

    Google Scholar 
    Zhu, J., Zhang, Y. & Jiang, L. Experimental warming drives a seasonal shift of ecosystem carbon exchange in Tibetan alpine meadow. Agric. For. Meteorol. 233, 242–249 (2017).Article 

    Google Scholar 
    Shen, M. et al. No evidence of continuously advanced green-up dates in the Tibetan Plateau over the last decade. Proc. Natl Acad. Sci. USA 110, E2329 (2013).
    Google Scholar 
    Fu, Y. S. et al. Variation in leaf flushing date influences autumnal senescence and next year’s flushing date in two temperate tree species. Proc. Natl Acad. Sci. USA 111, 7355–7360 (2014).Article 

    Google Scholar 
    Delpierre, N. et al. Modelling interannual and spatial variability of leaf senescence for three deciduous tree species in France. Agric. For. Meteorol. 149, 938–948 (2009).Article 

    Google Scholar 
    Keenan, T. F. & Richardson, A. D. The timing of autumn senescence is affected by the timing of spring phenology: implications for predictive models. Glob. Change Biol. 21, 2634–2641 (2015).Article 

    Google Scholar 
    Meng, F. D. et al. Changes in flowering functional group affect responses of community phenological sequences to temperature change. Ecology 98, 734–740 (2017).Article 

    Google Scholar 
    Wang, S. et al. Timing and duration of phenological sequences of alpine plants along an elevation gradient on the Tibetan plateau. Agric. For. Meteorol. 189–190, 220–228 (2014).Article 

    Google Scholar 
    Jiang, L. L. et al. Relatively stable response of fruiting stage to warming and cooling relative to other phenological events. Ecology 97, 1961–1969 (2016).Article 

    Google Scholar 
    Li, X. et al. Responses of sequential and hierarchical phenological events to warming and cooling in alpine meadows. Nat. Commun. 7, 12489 (2016).Article 

    Google Scholar 
    Meng, F. et al. Nonlinear responses of temperature sensitivities of community phenophases to warming and cooling events are mirroring plant functional diversity. Agric. For. Meteorol. 253–254, 31–37 (2018).Article 

    Google Scholar 
    Meng, F. et al. Divergent responses of community reproductive and vegetative phenology to warming and cooling: asymmetry versus symmetry. Front. Plant Sci. 10, 1310 (2019).Article 

    Google Scholar 
    Zhang, Z., Niu, K., Liu, X., Jia, P. & Du, G. Linking flowering and reproductive allocation in response to nitrogen addition in an alpine meadow. J. Plant Ecol. 7, 231–239 (2013).Article 

    Google Scholar 
    Xi, Y. et al. Nitrogen addition alters the phenology of a dominant alpine plant in Northern Tibet. Arct. Antarct. Alp. Res. 47, 511–518 (2018).Article 

    Google Scholar 
    Yin, T.-F., Zheng, L.-L., Cao, G.-M., Song, M.-H. & Yu, F.-H. Species-specific phenological responses to long-term nitrogen fertilization in an alpine meadow. J. Plant Ecol. 10, 301–309 (2016).
    Google Scholar 
    Liu, L. et al. Altered precipitation patterns and simulated nitrogen deposition effects on phenology of common plant species in a Tibetan Plateau alpine meadow. Agric. For. Meteorol. 236, 36–47 (2017).Article 

    Google Scholar 
    Liu, Y. et al. Effects of nitrogen addition and mowing on reproductive phenology of three early-flowering forb species in a Tibetan alpine meadow. Ecol. Eng. 99, 119–125 (2017).Article 

    Google Scholar 
    Zhu, J., Zhang, Y. & Liu, Y. Effects of short-term grazing exclusion on plant phenology and reproductive succession in a Tibetan alpine meadow. Sci. Rep. 6, 27781 (2016).Article 

    Google Scholar 
    Li, Y. et al. The effects of grazing regimes on phenological stages, intervals and divergences of alpine plants on the Qinghai–Tibetan Plateau. J. Veg. Sci. 30, 134–145 (2019).Article 

    Google Scholar 
    Dorji, T. et al. Impacts of climate change on flowering phenology and production in alpine plants: the importance of end of flowering. Agric. Ecosyst. Environ. 291, 106795 (2020).Article 

    Google Scholar 
    Meng, F. et al. Opposite effects of winter day and night temperature changes on early phenophases. Ecology 100, e02775 (2019).Article 

    Google Scholar 
    Meng, F. et al. Temperature sensitivity thresholds to warming and cooling in phenophases of alpine plants. Clim. Change 139, 579–590 (2016).Article 

    Google Scholar 
    Suonan, J., Classen, A. T., Sanders, N. J. & He, J. S. Plant phenological sensitivity to climate change on the Tibetan Plateau and relative to other areas of the world. Ecosphere 10, e02543 (2019).Article 

    Google Scholar 
    Ganjurjav, H. et al. Phenological changes offset the warming effects on biomass production in an alpine meadow on the Qinghai–Tibetan Plateau. J. Ecol. 109, 1014–1025 (2020).Article 

    Google Scholar 
    Jiang, Z. et al. Extreme climate events in China: IPCC-AR4 model evaluation and projection. Clim. Change 110, 385–401 (2011).Article 

    Google Scholar 
    Huang, X. et al. Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China. Cryosphere 10, 2453–2463 (2016).Article 

    Google Scholar 
    Piao, S. et al. Characteristics, drivers and feedbacks of global greening. Nat. Rev. Earth Environ. 1, 14–27 (2019).Article 

    Google Scholar 
    Wang, C. & Tang, Y. Responses of plant phenology to nitrogen addition: a meta-analysis. Oikos 128, 1243–1253 (2019).Article 

    Google Scholar 
    Chen, H., Zhu, Q., Wu, N., Wang, Y. & Peng, C. H. Delayed spring phenology on the Tibetan Plateau may also be attributable to other factors than winter and spring warming. Proc. Natl Acad. Sci. USA 108, E93 (2011).
    Google Scholar 
    Zhang, L. et al. Effect of warming and degradation on phenophases of Kobresia pygmaea and Potentilla multifida on the Tibetan Plateau. Agric. Ecosyst. Environ. 300, 106998 (2020).Article 

    Google Scholar 
    Lin, X. et al. Fluxes of CO2, CH4, and N2O in an alpine meadow affected by yak excreta on the Qinghai-Tibetan plateau during summer grazing periods. Soil Biol. Biochem. 41, 718–725 (2009).Article 

    Google Scholar 
    Sa, C. et al. Spatiotemporal variation in snow cover and its effects on grassland phenology on the Mongolian Plateau. J. Arid Land 13, 332–349 (2021).Article 

    Google Scholar 
    Zheng, J., Xu, X., Jia, G. & Wu, W. Understanding the spring phenology of Arctic tundra using multiple satellite data products and ground observations. Sci. China Earth Sci. 63, 1599–1612 (2020).Article 

    Google Scholar 
    Wu, W., Sun, Y., Xiao, K. & Xin, Q. Development of a global annual land surface phenology dataset for 1982–2018 from the AVHRR data by implementing multiple phenology retrieving methods. Int. J. Appl. Earth Obs. Geoinf. 103, 102487 (2021).
    Google Scholar 
    Karkauskaite, P., Tagesson, T. & Fensholt, R. Evaluation of the plant phenology index (PPI), NDVI and EVI for start-of-season trend analysis of the Northern Hemisphere boreal zone. Remote Sens. 9, 485 (2017).Article 

    Google Scholar 
    Yang, Y., Guan, H., Shen, M., Liang, W. & Jiang, L. Changes in autumn vegetation dormancy onset date and the climate controls across temperate ecosystems in China from 1982 to 2010. Glob. Change Biol. 21, 652–665 (2015).Article 

    Google Scholar 
    Zhang, J. et al. Comparison of land surface phenology in the Northern Hemisphere based on AVHRR GIMMS3g and MODIS datasets. ISPRS J. Photogramm. Remote Sens. 169, 1–16 (2020).Article 

    Google Scholar 
    Shen, M. et al. Earlier-season vegetation has greater temperature sensitivity of spring phenology in northern hemisphere. PLoS ONE 9, e88178 (2014).Article 

    Google Scholar 
    Zhang, H., Yuan, W., Liu, S., Dong, W. & Fu, Y. Sensitivity of flowering phenology to changing temperature in China. J. Geophys. Res. Biogeosci. 120, 1658–1665 (2015).Article 

    Google Scholar 
    Cook, B. I. et al. Sensitivity of spring phenology to warming across temporal and spatial climate gradients in two independent databases. Ecosystems 15, 1283–1294 (2012).Article 

    Google Scholar 
    Wang, C., Cao, R., Chen, J., Rao, Y. & Tang, Y. Temperature sensitivity of spring vegetation phenology correlates to within-spring warming speed over the Northern Hemisphere. Ecol. Indic. 50, 62–68 (2015).Article 

    Google Scholar 
    Gao, M. et al. Three-dimensional change in temperature sensitivity of northern vegetation phenology. Glob. Change Biol. 26, 5189–5201 (2020).Article 

    Google Scholar 
    Zohner, C. M., Benito, B. M., Fridley, J. D., Svenning, J. C. & Renner, S. S. Spring predictability explains different leaf-out strategies in the woody floras of North America, Europe and East Asia. Ecol. Lett. 20, 452–460 (2017).Article 

    Google Scholar 
    Fu, Y. H. et al. Daylength helps temperate deciduous trees to leaf-out at the optimal time. Glob. Change Biol. 25, 2410–2418 (2019).Article 

    Google Scholar 
    Huang, J. G. et al. Photoperiod and temperature as dominant environmental drivers triggering secondary growth resumption in Northern Hemisphere conifers. Proc. Natl Acad. Sci. USA 117, 20645–20652 (2020).Article 

    Google Scholar 
    Iler, A. M., CaraDonna, P. J., Forrest, J. R. K. & Post, E. Demographic consequences of phenological shifts in response to climate change. Annu. Rev. Ecol. Evol. Syst. 52, 221–245 (2021).Article 

    Google Scholar 
    Chen, S., Huang, Y., Gao, S. & Wang, G. Impact of physiological and phenological change on carbon uptake on the Tibetan Plateau revealed through GPP estimation based on spaceborne solar-induced fluorescence. Sci. Total Environ. 663, 45–59 (2019).Article 

    Google Scholar 
    Jin, J. et al. Grassland production in response to changes in biological metrics over the Tibetan Plateau. Sci. Total Environ. 666, 641–651 (2019).Article 

    Google Scholar 
    Kang, X. et al. Variability and changes in climate, phenology, and gross primary production of an alpine wetland ecosystem. Remote Sens. 8, 391 (2016).Article 

    Google Scholar 
    Zheng, Z., Zhu, W. & Zhang, Y. Direct and lagged effects of spring phenology on net primary productivity in the alpine grasslands on the Tibetan Plateau. Remote Sens. 12, 1223 (2020).Article 

    Google Scholar 
    Wang, S. et al. Responses of net primary productivity to phenological dynamics in the Tibetan Plateau, China. Agric. For. Meteorol. 232, 235–246 (2017).Article 

    Google Scholar 
    Li, S., Zhang, H., Zhou, X., Yu, H. & Li, W. Enhancing protected areas for biodiversity and ecosystem services in the Qinghai–Tibet Plateau. Ecosyst. Serv. 43, 101090 (2020).Article 

    Google Scholar 
    Meng, F. et al. Enhanced spring temperature sensitivity of carbon emission links to earlier phenology. Sci. Total Environ. 745, 140999 (2020).Article 

    Google Scholar 
    Hu, G. et al. The divergent impact of phenology change on the productivity of alpine grassland due to different timing of drought on the Tibetan Plateau. Land Degrad. Dev. 32, 4033–4041 (2021).Article 

    Google Scholar 
    Li, P., Zhu, W. & Xie, Z. Diverse and divergent influences of phenology on herbaceous aboveground biomass across the Tibetan Plateau alpine grasslands. Ecol. Indic. 121, 107036 (2021).Article 

    Google Scholar 
    He, M. et al. Relationships between wood formation and cambium phenology on the Tibetan Plateau during 1960–2014. Forests 9, 86 (2018).Article 

    Google Scholar 
    Wang, J., Li, M., Yu, C. & Fu, G. The change in environmental variables linked to climate change has a stronger effect on aboveground net primary productivity than does phenological change in alpine grasslands. Front. Plant Sci. 12, 798633 (2022).Article 

    Google Scholar 
    Shen, W., Zhang, L. & Luo, T. Causes for the increase of early-season freezing events under a warmer climate at alpine treelines in southeast Tibet. Agric. For. Meteorol. 316, 108863 (2022).Article 

    Google Scholar 
    Ye, D.-Z. & Wu, G.-X. The role of the heat source of the Tibetan Plateau in the general circulation. Meteorol. Atmos. Phys. 67, 181–198 (1998).Article 

    Google Scholar 
    Cao, R., Feng, Y., Liu, X., Shen, M. & Zhou, J. Uncertainty of vegetation green-up date estimated from vegetation indices due to snowmelt at northern middle and high latitudes. Remote Sens. 12, 190 (2020).Article 

    Google Scholar 
    Zeng, L., Wardlow, B. D., Xiang, D., Hu, S. & Li, D. A review of vegetation phenological metrics extraction using time-series, multispectral satellite data. Remote Sens. Environ. 237, 111511 (2020).Article 

    Google Scholar 
    Cao, R. et al. A simple method to improve the quality of NDVI time-series data by integrating spatiotemporal information with the Savitzky-Golay filter. Remote Sens. Environ. 217, 244–257 (2018).Article 

    Google Scholar 
    Chen, J. et al. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky–Golay filter. Remote Sens. Environ. 91, 332–344 (2004).Article 

    Google Scholar 
    Wang, C. et al. A snow-free vegetation index for improved monitoring of vegetation spring green-up date in deciduous ecosystems. Remote Sens. Environ. 196, 1–12 (2017).Article 

    Google Scholar 
    Yang, W. et al. A semi-analytical snow-free vegetation index for improving estimation of plant phenology in tundra and grassland ecosystems. Remote Sens. Environ. 228, 31–44 (2019).Article 

    Google Scholar 
    Wang, C., Chen, J., Tang, Y., Black, T. A. & Zhu, K. A novel method for removing snow melting-induced fluctuation in GIMMS NDVI3g data for vegetation phenology monitoring: a case study in deciduous forests of North America. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 11, 800–807 (2018).Article 

    Google Scholar 
    Helman, D. Land surface phenology: What do we really ‘see’ from space? Sci. Total Environ. 618, 665–673 (2018).Article 

    Google Scholar 
    Steltzer, H. & Post, E. Ecology. Seasons and life cycles. Science 324, 886–887 (2009).Article 

    Google Scholar 
    Liang, L., Schwartz, M. D. & Fei, S. Validating satellite phenology through intensive ground observation and landscape scaling in a mixed seasonal forest. Remote Sens. Environ. 115, 143–157 (2011).Article 

    Google Scholar 
    Li, R. et al. Leaf unfolding of Tibetan alpine meadows captures the arrival of monsoon rainfall. Sci. Rep. 6, 20985 (2016).Article 

    Google Scholar 
    Tang, J. et al. Emerging opportunities and challenges in phenology: a review. Ecosphere 7, e01436 (2016).Article 

    Google Scholar 
    Van Nuland, M. E. et al. Natural soil microbiome variation affects spring foliar phenology with consequences for plant productivity and climate-driven range shifts. New Phytol. 232, 762–775 (2021).Article 

    Google Scholar 
    Mutz, J., McClory, R., van Dijk, L. J. A., Ehrlen, J. & Tack, A. J. M. Pathogen infection influences the relationship between spring and autumn phenology at the seedling and leaf level. Oecologia 197, 447–457 (2021).Article 

    Google Scholar 
    Radville, L., McCormack, M. L., Post, E. & Eissenstat, D. M. Root phenology in a changing climate. J. Exp. Bot. 67, 3617–3628 (2016).Article 

    Google Scholar 
    Gao, M. et al. Divergent changes in the elevational gradient of vegetation activities over the last 30 years. Nat. Commun. 10, 2970 (2019).Article 

    Google Scholar  More

  • in

    Win-win opportunities combining high yields with high multi-taxa biodiversity in tropical agroforestry

    Ethical statementEthics approval was obtained for this study from the ethics committee of the University of Goettingen (Chair: Prof. Dr. Peter-Tobias Stoll) under the reference number 17./04.22Wurz.Study areaAll plots were situated in northeastern Madagascar in the SAVA region (Supplementary Fig. 1). The natural vegetation is tropical lowland rainforest, but deforestation rates are high30,67.The region is globally and nationally one of the most biodiverse places with high levels of endemism17,68. Forest loss is mainly driven by slash-and-burn shifting hill rice cultivation58. The region is characterized by a warm and humid climate with an annual rainfall of 2255 mm and a mean annual temperature of 23,9 °C (mean value of 60 plots extracted from CHELSA climatology69). Vanilla is the main cash crop in the SAVA region, making Madagascar the main vanilla producer globally21,22. Vanilla prices have shown strong fluctuations over the past years, with a price boom between 2014 and 2019 triggering an expansion of vanilla agroforestry in the region22,23.Study designWe selected 10 villages based on the 60 villages selected within the Diversity Turn in Land Use Science project22 (Supplementary Fig. 1). We selected the villages based on the list of villages for our study region from official election lists which listed all villages within a fokontany individually22. Village boundaries, demographics, infrastructure were defined based on a rapid survey with the village chief. Among the 60 villages, we considered all villages without coconut plantations, with less than 40% water (river, sea, and lakes) to avoid a strong influence of water elements and with forest fragments and shifting cultivation present within a 2 km radius around the village. Two of these 17 villages overlapped within a 2 km radius of the villages, thus we randomly selected one of them, resulting in 14 villages. We visited these 14 villages in a randomized order and stopped after we found 10 villages which fulfilled the necessary criteria (all land-use types present, willing to participate). In each of the 10 villages, we selected three vanilla agroforests, one forest fragment, and two fallows. Overall, we studied 60 plots across 10 villages and 10 plots in one protected old-growth forest (Marojejy National Park). All plots had a minimum distance of 260 m and a mean minimum distance of 794 m (SD = 468 m) to each other. Plot elevation ranged between 10 and 819 m.a.s.l. (mean  = 205 m, SD = 213 m; Supplementary Table 20).Plot selectionIn each of the 10 villages, we selected three vanilla agroforests with low, medium, and high canopy closure, respectively, covering a within village canopy cover gradient. To refine our vanilla agroforest classification, we used interviews with the plot owners to categorize all vanilla agroforests based on land-use history into fallow- and forest-derived agroforests15. Forest-derived vanilla agroforests are established within forest fragments, which have been manually thinned of dense understory vegetation. Fallow-derived vanilla agroforests are established on formerly slashed and burned plots, where vegetation has been cleared for hill rice production (shifting cultivation system locally called tavy). Out of our 30 vanilla agroforests, 20 vanilla agroforests were fallow-derived and 10 vanilla agroforests were forest-derived, roughly matching the proportion of fallow- and forest-derived vanilla agroforests across the study region (70% are fallow-derived vanilla agroforests, 27% are forest-derived vanilla agroforests and 3% of unknown origin22.In addition to vanilla agroforests, we selected one forest fragment in each village. Forest fragments were located inside the agricultural landscape and were remnants of the once continuous forest; these fragments are frequently used for natural product extraction. Forest fragments have not been burned or clear cut in living memory, yet the ongoing resource extraction results in a much simplified stand structure and fewer large trees compared to old-growth forest12. Furthermore, we chose one herbaceous and one woody fallow in each of the 10 study villages. Both fallow types form part of the shifting hill rice production cycle and represent the fallow period at different stages after the crop production. Herbaceous fallows have been slashed and burned multiple times with the last cultivation cycle at the end of 2016, one year prior to the first species data collection in 2017, and thereafter left fallow11. The continuous succession of herbaceous fallows turns them into woody fallows with the domination of woody plants including shrubs, trees, and sometimes bamboo. Our 10 woody fallows have last burned 4–16 years before data collection. In this study, we combine both herbaceous and woody fallows into the category “fallow”. Generally, fallows occur in different forms in the study region. The characteristics of fallows depend on the frequency of past fires and the length of fallow periods in between crop cultivation11. Frequent burning results in a loss of native and woody species and a dominance of exotic species and grasses11. In later fallow cycles, fern species increasingly appear11.Due to the commonly repeated slashing and burning, secondary forests are very rare in the study region. Shifting cultivation prevails in Madagascar70, because it is an important option for people to grow food because means for agricultural intensification are scarce. According to our baseline survey (performed in 60 villages in our study region), 90% of the interviewed farmers grow rice for subsistence in addition to growing vanilla22. Out of this sample, 64% of farmers grow rice in irrigated paddies and 26% of farmers use shifting cultivation.We also studied 10 plots at two sites in Marojejy National Park, the only remaining, continuous old-growth forest at a low altitude in our study area71. We chose accessible old-growth forest plots with a minimum distance of 250 m from the forest edge. Five of the 10 old-growth forest plots were located in Manantenina Valley, the other five old-growth forest plots were situated in the eastern part of Marojejy National Park, called Bangoabe area. Illegal selective logging has occurred in some parts of the park. During our plot selection, we avoided sites with traces of selective logging.Land-use history classificationTo collect information on the land-use history or farm history, interviews with farmers are common72,73. We did interviews with the plot owner. Questions on land-use history were binary (forest-derived or fallow-derived) and did not include information on the detailed land-use history (e.g. frequency of burning, past crop systems). Thus, we consider this selfreported data very reliable. The land-use categorization derived by farmers was confirmed by our visual plot inspections (forest-derived vanilla agroforests do have a quite distinctive vegetation structure compared to fallow-derived vanilla agroforests). Additionally, data on tree species composition and soil characteristics show evident differences between the categories and back up the binary land-use history categorization. Analysis of tree species composition showed that fallow- and forest-derived vanilla agroforests differ significantly in tree species composition12. Soil analysis (see Fig. S9) showed that our fallow-derived vanilla agroforests are associated with fertility-related variables such as an increase in calcium, pH, nitrogen, and phosphorus, which is common after slas-and-burn agriculture74,75.Plot designWe collected species data on plots with a radius of 25 m (1964 m2, 0.1964 ha). We established our circular plots in a homogeneous area of the land-use type or forest. Adjacent land uses were usually different because farmers generally own small-scale land with a mean size of 0.66 ha (mean size of agroforests). We assessed vanilla plant data (yield, vine length, vine age, planting density) on 36 vanilla pieds on each of 30 circular vanilla plots (Supplementary Fig. 8). We defined one vanilla pied (foot in French) as the combination of a vanilla vine and a minimum of one support tree. The 36 vanilla pieds were evenly selected in each of the circular plots based on a sampling protocol to ensure comprehensive and unbiased sampling. We chose vanilla pieds independent of age, length or health condition. We marked the 36 selected vanilla pieds per plot with a unique barcode to assess vanilla yield (April 2018) and other plant health variables on the same plant (not used in this study). However, for 37 vanilla pieds (out of a total of 1080 marked vanilla pieds), the barcodes were lost or unreadable and we selected a new plant closest to the original position (independent of age, length, or condition) and marked it with a new unique barcode. We measured the size of the vanilla agroforest by walking with the agroforest owner and a hand-held GPS device at the perimeter of the plot.Vanilla planting densityWe counted each vanilla pied on each 25 m circular plot by dividing the plot in four-quarter segments. We calculated the area of each 25 m radius plot including slope correction and calculated vanilla planting density (vanilla pieds per hectare) by dividing the number of vanilla pieds by the slope-corrected plot area.Vanilla yieldWe measured yield on 30 vanilla plantations (10 forest-derived vanilla plantations and 20 fallow-derived vanilla plantations); three in each of our 10 study villages. We measured vanilla yield on a total of 36 vanilla pieds between March and April 2018. We assessed the vanilla yield before harvest to ensure an accurate yield assessment due to two reasons. Firstly, vanilla pods are commonly harvested successively due to their differing pollination date and maturity requiring multiple visits over several weeks. Secondly, theft of vanilla pods is commonplace around harvest time. We, therefore, estimated the weight of the on-plant-hanging vanilla pods by measuring pod volume and relating this to a prior established volume–weight correlation. This is possible because vanilla pods only grow in length and width in the first 8 weeks of their development76. Our yield assessment consisted of one interview part with the plot owner and one measurement part. The interview part included questions about the occurrence of theft and early harvest on the plantation. During the measurement part, we assessed the number, diameter, and length of all vanilla pods. We measured vanilla pod length with a ruler starting at the junction of stem and pod until the tip of the pod without considering the bending of the pod. We measured the diameter at the widest part of the pod using a caliper. We firstly calculated pod volume based on the standard volume cylinder formula using the measured diameter (cm) and length (cm): V = πr2h.Secondly, we calculated the weight (g) of each pod by using the linear regression equation (y = bx + a) of a weight–volume correlation of 114 vanilla pods from 114 different agroforests (weight, length, and diameter of these 114 green vanilla was assessed post-harvest in 2017). We calculated the weight of all measured pods of the harvest in 2018 based on the formula:$${{{{{rm{volume}}}}}}={{{{{rm{pi }}}}}}({{{{{rm{diameter}}}}}}({{{{{rm{mm}}}}}})/20)^wedge 2ast {{{{{rm{length}}}}}}({{{{{rm{cm}}}}}})$$Here, we divided the pod diameter (mm) by 20 to obtain the radius and to transform millimeters to centimeters. Weight was defined as volume*0.5662 + 0.9699. No vanilla pods were stolen or already harvested on our 36 vanilla pieds and hence we did not need to account for it in our vanilla yield calculation.Vanilla vine lengthWe assessed vanilla vine length for all 36 vanilla pieds (same vanilla pieds as used for the yield assessment) on each plot by measuring the total length of the vine from the lowest to the highest part with a measuring stick. If the vanilla vine was looped on the support tree (= vanilla vine is hanging in multiple loops on the support tree), we measured from the top height of the looping of the vanilla vine until the lowest height of the vine. At the medium height of the vanilla vine, we counted the number of times the vanilla vine passed through. We calculated the total length of the liana by multiplying the maximum height of the vanilla vine by the number of times the vine passed through the middle. In some cases, the vanilla vine looped at two different heights, we thus considered the middle between the two looping heights as the top height. If vanilla vines grew on two different support trees, we considered them as one vanilla pieds if support trees were More

  • in

    Invasive brown treesnakes (Boiga irregularis) move short distances and have small activity areas in a high prey environment

    Nathan, R. et al. A movement ecology paradigm for unifying organismal movement research. Proc. Natl. Acad. Sci. 105, 19052–19059 (2008).ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lima, S. L. & Dill, L. M. Behavioral decisions made under the risk of predation: A review and prospectus. Can. J. Zool. 68, 619–640 (1990).Article 

    Google Scholar 
    Kays, R., Crofoot, M. C., Jetz, W. & Wikelski, M. Terrestrial animal tracking as an eye on life and planet. Science 348, 1122–1133. https://doi.org/10.1126/science.aaa2478 (2015).CAS 
    Article 

    Google Scholar 
    Allen, A. M. & Singh, N. J. Linking movement ecology with wildlife management and conservation. Front. Ecol. Evol. 3, 1–13. https://doi.org/10.3389/fevo.2015.00155 (2016).ADS 
    Article 

    Google Scholar 
    Fraser, K. C. et al. Tracking the conservation promise of movement ecology. Front. Ecol. Evol. https://doi.org/10.3389/fevo.2018.00150 (2018).Article 

    Google Scholar 
    Boutin, S. Food supplementation experiments with terrestrial vertebrates: Patterns, problems, and the future. Can. J. Zool. 68, 203–220 (1990).Article 

    Google Scholar 
    Adams, E. S. Approaches to the study of territory size and shape. Annu. Rev. Ecol. Syst. 32, 277–303. https://doi.org/10.1146/annurev.ecolsys.32.081501.114034 (2001).Article 

    Google Scholar 
    Ruffino, L., Salo, P., Koivisto, E., Banks, P. B. & Korpimaki, E. Reproductive responses of birds to experimental food supplementation: A meta-analysis. Front. Ecol. Evol. 11, 1–13. https://doi.org/10.1186/s12983-014-0080-y (2014).CAS 
    Article 

    Google Scholar 
    Taylor, E. N., Malawy, M. A., Browning, D. M., Lemar, S. V. & DeNardo, D. F. Effects of food supplementation on the physiological ecology of female western diamond-backed rattlesnakes (Crotalus atrox). Oecologia 144, 206–213. https://doi.org/10.1007/s00442-005-0056-x (2005).ADS 
    Article 
    PubMed 

    Google Scholar 
    Wasko, D. K. & Sasa, M. Food resources influence spatial ecology, habitat selection, and foraging behavior in an ambush-hunting snake (Viperidae: Bothrops asper): An experimental study. Zoology 115, 179–187. https://doi.org/10.1016/j.zool.2011.10.001 (2012).Article 
    PubMed 

    Google Scholar 
    Glaudas, X. & Alexander, G. J. Food supplementation affects the foraging ecology of a low-energy, ambush-foraging snake. Behav. Ecol. Sociobiol. 71, 1–11. https://doi.org/10.1007/s00265-016-2239-3 (2017).Article 

    Google Scholar 
    Secor, S. M. & Nagy, K. A. Bioenergetic correlates of foraging mode for the snakes Crotalus cerastes and Masticophis flagellum. Ecology 75, 1600–1614 (1994).Article 

    Google Scholar 
    Christy, M. T., Savidge, J. A., Yackel Adams, A. A., Gragg, J. E. & Rodda, G. H. Experimental landscape reduction of wild rodents increases movements in the invasive brown treesnake (Boiga irregularis). Manag. Biol. Invasions 8, 455–467. https://doi.org/10.3391/mbi.2017.8.4.01 (2017).Article 

    Google Scholar 
    Neilson, E. W., Avgar, T., Burton, A. C., Broadley, K. & Boutin, S. Animal movement affects interpretation of occupancy models from camera-trap surveys of unmarked animals. Ecosphere 9, 1–15. https://doi.org/10.1002/ecs2.2092 (2018).Article 

    Google Scholar 
    Efford, M. G. & Dawson, D. K. Occupancy in continuous habitat. Ecosphere 3, 1–15. https://doi.org/10.1890/ES11-00308.1 (2012).Article 

    Google Scholar 
    Tang, Z., Huang, Q., Wu, H., Kuang, L. & Fu, S. The behavioral response of prey fish to predators: The role of predator size. PeerJ 5, 1–13. https://doi.org/10.7717/peerj.3222 (2017).Article 

    Google Scholar 
    Thorsen, M., Shorten, R., Lucking, R. & Lucking, V. Norway rats (Rattus norvegicus) on Fregate Island, Seychelles: The invasion; subsequent eradication attempts and implications for the island’s fauna. Biol. Cons. 96, 133–138 (2000).Article 

    Google Scholar 
    Rodda, G. H. Foraging behavior of the brown tree snake, Boiga irregularis. Herpetol. J. 2, 110–114 (1992).
    Google Scholar 
    Savidge, J. A. Extinction of an island forest avifauna by an introduced snake. Ecology 68, 660–668 (1987).Article 

    Google Scholar 
    Rodda, G. H., McCoid, M. J., Fritts, T. H. & Campbell, E. W. III. Population trends and limiting factors in Boiga irregularis. In Problem Snake Management: The Habu and the Brown Treesnake (eds Rodda, G. H. et al.) 236–256 (Cornell University Press, 1999).Chapter 

    Google Scholar 
    Yackel Adams, A. A., Lardner, B., Knox, A. J. & Reed, R. N. Inferring the absence of an incipient population during a rapid response for an invasive species. PLoS ONE 13, 1–13 (2018).Article 
    CAS 

    Google Scholar 
    Clark, L., Clark, C. & Siers, S. Brown tree snake methods and approaches for control. In Ecology and Management of Terrestrial Vertebrate Invasive Species in the United States (eds Pitt, W. C. et al.) 107–134 (CRC Press, 2018).
    Google Scholar 
    Christy, M. T., Yackel Adams, A. A., Rodda, G. H., Savidge, J. A. & Tyrrell, C. L. Modelling detection probabilities to evaluate management and control tools for an invasive species. J. Appl. Ecol. 47, 106–113 (2010).Article 

    Google Scholar 
    Tyrrell, C. L. et al. Evaluation of trap capture in a geographically closed population of brown treesnakes on Guam. J. Appl. Ecol. 46, 128–135 (2009).Article 

    Google Scholar 
    Siers, S. R., Yackel Adams, A. A. & Reed, R. N. Behavioral differences following ingestion of large meals and consequences for management of a harmful invasive snake: A field experiment. Ecol. Evol. 8, 10075–10093 (2018).PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Santana-Bendix, M. A. Movements, Activity Patterns and Habitat Use of Boiga irregularis (Colubridae), an Introduced Predator in the Island of Guam (University of Arizona, 1994).
    Google Scholar 
    Tobin, M. E., Sugihara, R. T., Pochop, P. A. & Linnell, M. A. Nightly and seasonal movements of Boiga irregularis on Guam. J. Herpetol. 33, 281–291 (1999).Article 

    Google Scholar 
    Lardner, B., Savidge, J. A., Reed, R. N. & Rodda, G. H. Movements and activity of juvenile brown treesnakes (Boiga irregularis). Copeia 2014, 428–436 (2014).Article 

    Google Scholar 
    Siers, S. R., Savidge, J. A. & Reed, R. N. Invasive brown treesnake movements at road edges indicate road-crossing avoidance. J. Herpetol. 48, 500–505 (2014).Article 

    Google Scholar 
    Wiewel, A. S., Yackel Adams, A. A. & Rodda, G. H. Distribution, density, and biomass of introduced small mammals in the southern Marian Islands. Pac. Sci. 63, 205–222 (2009).Article 

    Google Scholar 
    Camp, R. J., Amidon, F. A., Marshall, A. P. & Pratt, T. K. Bird populations on the island of Tinian; Persistence despite wholesale loss of native forests. Pac. Sci. 66, 283–298. https://doi.org/10.2984/66.3.3 (2012).Article 

    Google Scholar 
    Lardner, B., Yackel Adams, A. A., Knox, A. J., Savidge, J. A. & Reed, R. N. Do observer fatigue and taxon bias compromise visual encounter surveys for small vertebrates?. Wildl. Res. 46, 127–135 (2019).Article 

    Google Scholar 
    Mathies, T., Levine, B., Engeman, R. & Savidge, J. A. Pheromonal control of the invasive brown treesnake: Potency of female sexual attractiveness pheromone varies with ovarian state. Int. J. Pest Manag. https://doi.org/10.1080/09670874.2013.784374 (2013).Article 

    Google Scholar 
    Boback, S. M., Nafus, M. G., Yackel Adams, A. A. & Reed, R. N. Use of visual surveys and radiotelemetry reveals sources of detection bias for a cryptic snake at low densities. Ecosphere https://doi.org/10.1002/ecs2.3000 (2020).Article 

    Google Scholar 
    Harper, G. A. & Rutherford, M. Home range and population density of black rats (Rattus rattus) on a seabird island: A case for a marine subsidised effect?. N. Z. J. Ecol. 40, 219–228 (2016).
    Google Scholar 
    Hochachka, W. M., Martin, K., Doyle, F. & Krebs, C. J. Monitoring vertebrate populations using observational data. Can. J. Zool. 78, 521–529 (2000).Article 

    Google Scholar 
    Wiewel, A. S., Yackel Adams, A. A. & Rodda, G. H. Evaluating abundance estimate precision and the assumptions of a count-based index for small mammals. J. Wildl. Manag. 73, 761–771. https://doi.org/10.2193/2008-180 (2009).Article 

    Google Scholar 
    Fauteux, D. et al. Evaluation of invasive and non-invasive methods to monitor rodent abundance in the Arctic. Ecosphere 9, 1–18. https://doi.org/10.1002/ecs2.2124 (2018).Article 

    Google Scholar 
    Siers, S. R. et al. Assessment of brown treesnake activity and bait take following large-scale snake suppression in Guam. (ed APHIS USDA, WS, NWRC) (Final Report QA-2438, Hilo, HI, 2018).McQueen, D. J., Post, J. R. & Mills, E. L. Trophic relationships in fresh-water pelagic ecosystems. Can. J. Fish. Aquat. Sci. 43, 1571–1581 (1986).Article 

    Google Scholar 
    Sih, A., Crowley, P., McPeek, M., Petranka, J. & Strohmeier, K. Predation, competition, and prey communities: A review of field experiments. Annu. Rev. Ecol. Syst. 16, 269–311 (1985).Article 

    Google Scholar 
    Dorcas, M. E. et al. Severe mammal declines coincide with proliferation of invasive Burmese pythons in Everglades National Park. Proc. Natl. Acad. Sci. 109, 2418–2422. https://doi.org/10.1073/pnas.1115226109 (2012).ADS 
    Article 
    PubMed 
    PubMed Central 

    Google Scholar 
    de Miranda, E. B. P. The plight of reptiles as ecological actors in the tropics. Front. Ecol. Evol. 5, 1–15. https://doi.org/10.3389/fevo.2017.00159 (2017).Article 

    Google Scholar 
    Campbell, E. W. III., Yackel Adams, A. A., Converse, S. J., Fritts, T. H. & Rodda, G. H. Do predators control prey species abundance? An experimental test with brown treesnakes on Guam. Ecology 93, 1194–1203 (2012).PubMed 
    Article 

    Google Scholar 
    Lindell, L. E. & Forsman, A. Density effects and snake predation: Prey limitation and reduced growth rate of adders at high density of conspecifics. Can. J. Zool. 74, 1000–1007 (1996).Article 

    Google Scholar 
    Schoener, T. W., Spiller, D. A. & Losos, J. B. Predation on a common Anolis lizard: Can the food-web effects of a devastating predator be reversed?. Ecol. Monogr. 72, 383–407 (2002).Article 

    Google Scholar 
    McCleery, R. A. et al. Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades. Proc. R. Soc. Lond. 282, 20150120. https://doi.org/10.1098/rspb.2015.0120 (2015).Article 

    Google Scholar 
    Plummer, M. V. & Congdon, J. D. Radiotelemetric study of activity and movements of racers (Coluber constrictor) associated with a Carolina bay in South Carolina. Copeia 1994, 20–26 (1994).Article 

    Google Scholar 
    Madsen, T. & Shine, R. Seasonal migration of predators and prey—A study of pythons, and rats in tropical Australia. Ecology 77, 149–156 (1996).Article 

    Google Scholar 
    Chandler, C. J., Van Helden, B., Close, P. G. & Speldewinde, P. C. 2D or not 2D? Three-dimensional home range analysis better represents space use by an arboreal mammal. Acta Oecol. 105, 103576. https://doi.org/10.1016/j.actao.2020.103576 (2020).Article 

    Google Scholar 
    Udyawer, V., Simpfendorfer, C. A. & Heupel, M. R. Diel patterns in three-dimensional use of space by sea snakes. Anim. Biotelem. 3, 1–9. https://doi.org/10.1186/s40317-015-0063-6 (2015).Article 

    Google Scholar 
    Shine, R. Reproduction in Australian elapid snakes II. Female reproductive cycles. Aust. J. Zool. 25, 655–666 (1977).Article 

    Google Scholar 
    Murcia, C. Edge effects in fragmented forests: Implications for conservation. Trends Ecol. Evol. 10, 58–62 (1995).CAS 
    PubMed 
    Article 

    Google Scholar 
    Matlack, G. R. Microenvironment variation within and among forest edge sites in the eastern United States. Biol. Cons. 66, 185–194 (1993).Article 

    Google Scholar 
    Kapos, V. Effects of isolation on the water status of forest patches in the Brazilian Amazon. Trop. Ecol. 5, 173–185 (1989).Article 

    Google Scholar 
    Williams-Linera, G. Vegetation structure and environmental conditions of forest edges in Panama. J. Ecol. 78, 356–373 (1990).Article 

    Google Scholar 
    Matlack, G. R. Vegetation dynamics of the forest edge: Trends in space and successional time. J. Ecol. 82, 113–123 (1994).Article 

    Google Scholar 
    Chen, J., Franklin, J. F. & Spies, T. A. Vegetation responses to edge environments in old-growth douglas-fir forests. Ecol. Appl. 2, 387–396 (1992).PubMed 
    Article 

    Google Scholar 
    Gates, J. E. Powerline corridors, edge effects, and wildlife in forested landscapes of the central Appalachians. In Wildlife and Habitats in Managed Landscapes (eds Rodiek, J. E. & Bolen, E. G.) 13–32 (Island Press, 1991).
    Google Scholar 
    Kroodsma, R. L. Edge effect on breeding forest birds along a power-line corridor. J. Appl. Ecol. 19, 361–370 (1982).Article 

    Google Scholar 
    Morgan, K. A. & Gates, J. E. Bird population patterns in forest edge and strip vegetation at Remington Farms, Maryland. J. Wildl. Manag. 46, 933–944 (1982).Article 

    Google Scholar 
    Weatherhead, P. J. & Charland, M. B. Habitat selection in an Ontario population of the snake, Elaphe obsoleta. J. Herpetol. 19, 12–19 (1985).Article 

    Google Scholar 
    Durner, G. M. & Gates, J. E. Spatial ecology of black rat snakes on Remington Farms, Maryland. J. Wildl. Manag. 57, 812–826 (1993).Article 

    Google Scholar 
    Mushinsky, H. R. Foraging ecology. In Snakes: Ecology and Evolutionary Biology (eds Seigel, R. A. et al.) 302–334 (Macmillan Publishing Company, 1987).
    Google Scholar 
    Fritts, T. H., Scott, N. J. Jr. & Smith, B. J. Trapping Boiga irregularis on Guam using bird odors. J. Herpetol. 23, 189–192 (1989).Article 

    Google Scholar 
    Shivik, J. A. Brown tree snake response to visual and olfactory cues. J. Wildl. Manag. 62, 105–111 (1998).Article 

    Google Scholar 
    Simkova, O., Frydlova, P., Zampachova, B., Frynta, D. & Landova, E. Development of behavioral profile in the Northern common boa (Boa imperator): Repeatable independent traits or personality?. PLoS ONE 12, 1–35. https://doi.org/10.1371/journal.pone.0177911 (2017).CAS 
    Article 

    Google Scholar 
    Fritts, T. H., McCoid, M. J. & Gomez, D. M. Dispersal of snakes to extralimital islands: Incidents of the brown treesnake, Boiga irregularis, dispersing to islands in ships and aircraft. In Problem Snake Management: The Habu and the Brown Treesnake (eds Rodda, G. H. et al.) 209–223 (Cornell University Press, 1999).
    Google Scholar 
    Yackel Adams, A. A. et al. Can we prove that an undetected species is absent? Evaluating whether brown treesnakes are established on the island of Saipan using surveillance and expert opinion. Manag. Biol. Invas. 12, 901–926 (2021).Article 

    Google Scholar 
    Siers, S. R. & Savidge, J. A. Restoration Plan for the Habitat Management Unit, Naval Support Activity Andersen, Guam 1–238 (Colorado State University, 2017).
    Google Scholar 
    Dorr, B. S., Clark, C. S. & Savarie, P. (USDA APHIS WS National Wildlife Research Center, Fort Collins, CO, 2016).Reinert, H. K. & Cundall, D. An improved surgical implantation method for radio-tracking snakes. Copeia 1982, 702–705 (1982).Article 

    Google Scholar 
    Shine, R. Strangers in a strange land: Ecology of the Australian colubrid snakes. Copeia 1991, 120–131 (1991).Article 

    Google Scholar 
    Savidge, J. A., Qualls, F. J. & Rodda, G. H. Reproductive biology of the brown tree snake, Boiga irregularis (Reptilia: Colubridae), during colonization of Guam and comparison with that in their native range. Pac. Sci. 61, 191–199 (2007).Article 

    Google Scholar 
    Yackel Adams, A. A. & Nafus, M. G. Brown Treesnake visual survey and radiotelemetry data, Guam 2015: U.S. Geological Survey data release. https://doi.org/10.5066/P939BM0W (2020).Savidge, J. A. Food habits of Boiga irregularis, an introduced predator on Guam. J. Herpetol. 22, 275–282 (1988).Article 

    Google Scholar 
    Reed, R. N. & Boback, S. M. Does body size predict dates of species description among North American and Australian reptiles and amphibians?. Glob. Ecol. Biogeogr. 11, 41–47 (2002).Article 

    Google Scholar 
    Duong, T. ks: Kernel density estimation and kernel discriminant analysis for multivariate data in R. J. Stat. Softw. 21, 1–16 (2007).Article 

    Google Scholar 
    R Foundation for Statistical Computing. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2017).
    Google Scholar 
    Simpfendorfer, C. A., Olsen, E. M., Heupel, M. R. & Moland, E. Three-dimensional kernel utilization distributions improve estimates of space use in aquatic animals. Can. J. Fish. Aquat. Sci. 69, 565–572 (2012).Article 

    Google Scholar 
    Gitzen, R. A., Millspaugh, J. J. & Kernohan, B. J. Bandwidth selection for fixed-kernel analysis of animal utilization distributions. J. Wildl. Manag. 70, 1334–1344 (2006).Article 

    Google Scholar 
    Cooper, N. W., Sherry, T. W. & Marra, P. P. Modeling three-dimensional space use and overlap in birds. Auk 131, 681–693 (2014).Article 

    Google Scholar 
    ArcGIS Desktop (Environmental Systems Research, 2017).Nafus, M. G., Boback, S. M., Klug, P. E., Yackel Adams, A. A. & Reed, R. N. Brown treesnake movement following snake suppression in the Habitat Management Unit on Northern Guam from 2015. U.S Geological Survey data release. https://doi.org/10.5066/P95QJ2PE (2022). More

  • in

    Soil inoculum identity and rate jointly steer microbiomes and plant communities in the field

    Hu ZM, Li SG, Guo Q, Niu SL, He NP, Li LH. et al. A synthesis of the effect of grazing exclusion on carbon dynamics in grasslands in China. Global Change Biol. 2016;22:1385–93.Article 

    Google Scholar 
    Lyu X, Li XB, Gong JR, Wang H, Dang DL, Dou HS, et al. Comprehensive grassland degradation monitoring by remote sensing in Xilinhot, Inner Mongolia, China. Sustainability. 2020;12:3682.Article 

    Google Scholar 
    O’Mara FP. The role of grasslands in food security and climate change. Ann Bot-London. 2012;110:1263–70.Article 

    Google Scholar 
    Bryan BA, Gao L, Ye YQ, Sun XF, Connor JD, Crossman ND, et al. China’s response to a national land-system sustainability emergency. Nature. 2018;559:193–204.CAS 
    PubMed 
    Article 

    Google Scholar 
    Bardgett RD, Bullock JM, Lavorel S, Manning P, Schaffner U, Ostle N. et al. Combatting global grassland degradation. Nat Rev Earth Environ. 2021;2:720–35.Article 

    Google Scholar 
    Chang JF, Ciais P, Gasser T, Smith P, Herrero M, Havlik P, et al. Climate warming from managed grasslands cancels the cooling effect of carbon sinks in sparsely grazed and natural grasslands. Nat Commun. 2021;12:118.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Wardle DA, Bardgett RD, Klironomos JN, Setälä H, van der Putten WH, Wall DH. Ecological linkages between aboveground and belowground biota. Science. 2004;304:1629–33.CAS 
    PubMed 
    Article 

    Google Scholar 
    Feeney DS, Crawford JW, Daniell T, Hallett PD, Nunan N, Ritz K, et al. Three-dimensional microorganization of the soil-root-microbe system. Microb Ecol. 2006;52:151–8.PubMed 
    Article 

    Google Scholar 
    Harris J. Soil microbial communities and restoration ecology: Facilitators or followers? Science. 2009;325:573–4.CAS 
    PubMed 
    Article 

    Google Scholar 
    Vecrin MP, Muller S. Top-soil translocation as a technique in the re-creation of species-rich meadows. Appl Veg Sci. 2003;6:271–8.Article 

    Google Scholar 
    Middleton EL, Bever JD. Inoculation with a native soil community advances succession in a grassland restoration. Restor Ecol. 2012;20:218–26.Article 

    Google Scholar 
    Wubs ERJ, van der Putten WH, Bosch M, Bezemer TM. Soil inoculation steers restoration of terrestrial ecosystems. Nat Plants. 2016;2:16107.PubMed 
    Article 

    Google Scholar 
    Wubs ERJ, van Heusden T, Melchers PD, Bezemer TM. Soil inoculation steers plant-soil feedback, suppressing ruderal plant species. Front Ecol Evol. 2019;7:451.Article 

    Google Scholar 
    Bever JD. Feedback between plants and their soil communities in an old field community. Ecology. 1994;75:1965–77.Article 

    Google Scholar 
    Bennett JA, Maherali H, Reinhart KO, Lekberg Y, Hart MM, Klironomos J. Plant-soil feedbacks and mycorrhizal type influence temperate forest population dynamics. Science. 2017;355:181–4.CAS 
    PubMed 
    Article 

    Google Scholar 
    Contos P, Wood JL, Murphy NP, Gibb H. Rewilding with invertebrates and microbes to restore ecosystems: Present trends and future directions. Ecol Evol. 2021;11:7187–200.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Emam T. Local soil, but not commercial AMF inoculum, increases native and non-native grass growth at a mine restoration site. Restor Ecol. 2016;24:35–44.Article 

    Google Scholar 
    Moradi J, Vicentini F, Simackova H, Pizl V, Tajovsky K, Stary J. An investigation into the long-term effect of soil transplant in bare spoil heaps on survival and migration of soil meso and macrofauna. Ecol Eng. 2018;110:158–64.Article 

    Google Scholar 
    Carbajo V, den Braber B, van der Putten WH, De Deyn GB. Enhancement of late successional plants on ex-arable land by soil inoculations. Plos One. 2011;6:e21943.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Ma W, Liang XS, Wang ZW, Luo WT, Yu Q, Han XG. Resistance of steppe communities to extreme drought in northeast China. Plant Soil. 2022;473:181–194.IUSS Working Group WRB. World Reference Base for Soil Resources 2014, update 2015 International soil classification system for naming soils and creating legends for soil maps. World Soil Resources Reports No. 106. FAO, Rome, 2015.Jaunatre R, Buisson E, Dutoit T. Topsoil removal improves various restoration treatments of a Mediterranean steppe (La Crau, southeast France). Appl Veg Sci. 2014;17:236–45.Article 

    Google Scholar 
    Kuo S. Methods of soil analysis. Part 3: chemical methods. Soil Science Society of America: Madison, 1996.Biddle JF, Fitz-Gibbon S, Schuster SC, Brenchley JE, House CH. Metagenomic signatures of the Peru Margin subseafloor biosphere show a genetically distinct environment. P Natl Acad Sci USA. 2008;105:10583–8.CAS 
    Article 

    Google Scholar 
    De Beeck MO, Lievens B, Busschaert P, Declerck S, Vangronsveld J, Colpaert JV. Comparison and validation of some ITS primer pairs useful for fungal metabarcoding studies. Plos One. 2014;9:e97629.Article 

    Google Scholar 
    Magoč T, Salzberg SL. FLASH: Fast length adjustment of short reads to improve genome assemblies. Bioinformatics. 2011;27:2957–63.PubMed 
    PubMed Central 
    Article 
    CAS 

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

    Google Scholar 
    Chen SF, Zhou YQ, Chen YR, Gu J. Fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34:i884–90.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Edgar RC. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat Methods. 2013;10:996–8.CAS 
    PubMed 
    Article 

    Google Scholar 
    Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microb. 2007;73:5261–7.CAS 
    Article 

    Google Scholar 
    Quast C, Pruesse E, Gerken J, Peplies J, Yarza P, Yilmaz P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2012;41:590–6.Article 
    CAS 

    Google Scholar 
    Kõljalg U, Larsson K-H, Abarenkov K, Nilsson RH, Alexander IJ, Eberhardt U, et al. UNITE: a database providing web-based methods for the molecular identification of ectomycorrhizal fungi. New Phytol. 2005;166:1063–8.PubMed 
    Article 
    CAS 

    Google Scholar 
    Oostenbrink M. Estimating nematode populations by some selected methods. Nematology, Chapel Hill, 1960.Townshend JL. A modification and evaluation of the apparatus for the Oostenbrink direct cotton wool filter extraction method. Nematologica. 1963;9:106–10.Article 

    Google Scholar 
    Bongers T. De Nematoden van Nederland. In: Vormgeving en technische realisatie. Uitgeverij Pirola, Schoorl, 1994.Ahmad W, Jairjpuri MS. Mononchida: the predaceous nematodes. Nematology Monographs and Perspectives. Brill, Boston, 2010.Li Q, Liang WJ, Zhang XK, Mahamood M. Soil nematodes of grasslands in Northern China. Academic Press: San Diego, 2017.Wu ZY, Raven PH, Hong DY. Flora of China. Science Press: Beijing, 2013.Munson SM, Long AL, Wallace CSA, Webb RH. Cumulative drought and land-use impacts on perennial vegetation across a North American dryland region. Appl Veg Sci. 2016;19:430–41.Article 

    Google Scholar 
    Li YH, Wang W, Liu ZL, Jiang S. Grazing gradient versus restoration succession of leymus chinensis (Trin.) Tzvel. grassland in inner mongolia. Restor Ecol. 2008;16:572–83.Article 

    Google Scholar 
    Liang C, Michalk DL, Millar GD. The ecology and growth patterns of Cleistogenes species in degraded grasslands of eastern Inner Mongolia, China. J Appl Ecol. 2002;39:584–94.Article 

    Google Scholar 
    Liu ZG, Li ZQ. Effects of different grazing regimes on the morphological traits of Carex duriuscula on the Inner Mongolia steppe. China. New Zeal J Agr Res. 2010;53:5–12.Article 

    Google Scholar 
    Liu M, Gong JR, Pan Y, Luo QP, Zhai ZW, Yang LL, et al. Response of dominant grassland species in the temperate steppe of Inner Mongolia to different land uses at leaf and ecosystem levels. Photosynthetica. 2018;56:921–31.Article 

    Google Scholar 
    Bates D, Machler M, Bolker BM, Walker SC. Fitting linear mixed-effects models using lme4. J Stat Softw. 2015;67:1–48.Article 
    CAS 

    Google Scholar 
    Dixon P. Vegan, a package of R functions for community ecology. J Veg Sci. 2003;14:927–30.Article 

    Google Scholar 
    McMurdie PJ, Holmes S. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. Plos One. 2013;8:e61217.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Robinson MD, McCarthy DJ, Smyth GK. edgeR: a bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2010;26:139–40.CAS 
    PubMed 
    Article 

    Google Scholar 
    De Cáceres M, Legendre P, Moretti M. Improving indicator species analysis by combining groups of sites. Oikos. 2010;119:1674–84.Article 

    Google Scholar 
    Hartman K, van der Heijden MGA, Wittwer RA, Banerjee S, Walser JC, Schlaeppi K. Cropping practices manipulate abundance patterns of root and soil microbiome members paving the way to smart farming. Microbiome. 2018;6:14.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Aitchison J. A new approach to null correlations of proportions. Mathematical Geology. 1981;13:175–89.Article 

    Google Scholar 
    Kurtz ZD, Müller CL, Miraldi ER, Littman DR, Blaser MJ, Bonneau RA. Sparse and compositionally robust inference of microbial ecological networks. Plos Comput Biol. 2015;11:e1004226.PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 
    Cao YP, Lin W, Li HZ. Two-sample tests of high-dimensional means for compositional data. Biometrika. 2018;105:115–32.Article 

    Google Scholar 
    Csardi G, Nepusz T. The igraph software package for complex network research. InterJ Complex Syst. 2006;1695:1–9.Banerjee S, Schlaeppi K, van der Heijden MGA. Keystone taxa as drivers of microbiome structure and functioning. Nat Rev Microbiol. 2018;16:567–76.CAS 
    PubMed 
    Article 

    Google Scholar 
    Banerjee S, Schlaeppi K, van der Heijden MGA. Reply to ‘Can we predict microbial keystones?’. Nat Rev Microbiol. 2019;17:194–194.CAS 
    PubMed 
    Article 

    Google Scholar 
    Zheng HP, Yang TJ, Bao YZ, He PP, Yang KM, Mei XL, et al. Network analysis and subsequent culturing reveal keystone taxa involved in microbial litter decomposition dynamics. Soil Biol Biochem. 2021;157:108230.CAS 
    Article 

    Google Scholar 
    Kardol P, Wardle DA. How understanding aboveground-belowground linkages can assist restoration ecology. Trends Ecol Evol. 2010;25:670–9.PubMed 
    Article 

    Google Scholar 
    Wubs ERJ, van der Putten WH, Mortimer SR, Korthals GW, Duyts H, Wagenaar R, et al. Single introductions of soil biota and plants generate long-term legacies in soil and plant community assembly. Ecol Lett. 2019;22:1145–51.PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    St-Denis A, Kneeshaw D, Belanger N, Simard S, Laforest-Lapointe I, Messier C. Species-specific responses to forest soil inoculum in planted trees in an abandoned agricultural field. Appl Soil Ecol. 2017;112:1–10.Article 

    Google Scholar 
    Kitto JAJ, Gray DP, Greig HS, Niyogi DK, Harding JS. Meta-community theory and stream restoration: evidence that spatial position constrains stream invertebrate communities in a mine impacted landscape. Restor Ecol. 2015;23:284–91.Article 

    Google Scholar 
    Ofek M, Hadar Y, Minz D. Ecology of root colonizing Massilia (Oxalobacteraceae). Plos One. 2012;7:e40117.CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 
    Lyu D, Backer R, Smith DL. Three plant growth-promoting rhizobacteria alter morphological development, physiology, and flower yield of Cannabis sativa L. Ind Crop Prod. 2022;178:114583.CAS 
    Article 

    Google Scholar 
    Kulmatiski A, Beard KH. Long-term plant growth legacies overwhelm short-term plant growth effects on soil microbial community structure. Soil Biol Biochem. 2011;43:823–30.CAS 
    Article 

    Google Scholar 
    Brewer TE, Handley KM, Carini P, Gilbert JA, Fierer N. Genome reduction in an abundant and ubiquitous soil bacterium ‘Candidatus Udaeobacter copiosus’. Nat Microbiol. 2017;2:16198.Article 
    CAS 

    Google Scholar 
    Reme J. Development and present state of close-to-nature silviculture. J Landscape Ecol. 2018;11:17–32.Article 

    Google Scholar  More

  • in

    The scientists who switched focus to fight climate change

    Sophie Gilbert left a tenured position to join a start-up that allows small private landowners to sell carbon credits for preserving forests on their land.Credit: Sophie Gilbert

    It was during a car journey to California in temperatures sometimes exceeding 40 °C that Sophie Gilbert decided she needed to make a major career change.Driving to visit family from her home in Moscow, Idaho, she passed columns of wildfire smoke, the oppressive heat limiting the time she could spend out of her air-conditioned car. The two-day drive midway through last year helped to crystallize a feeling that she urgently needed to do something more concrete to help deal with the threat of climate change.“It hit at a gut level,” says Gilbert. “Climate change isn’t something that’s going to happen to someone else later on. It felt deeply, viscerally real for me and my family and what I care about.”Given her role as a wildlife ecologist at the University of Idaho in Moscow, it might seem that Gilbert was already well placed to have a positive impact on climate change. But the slow, incremental pace of academia, and the difficulty of getting policymakers to act on her findings, left her feeling that she was not making as much of a difference as she’d hoped.“I’ve been studying how wildlife responds to environmental change to inform conservation planning for 15 years now, researching and publishing and waiting for something to happen and then having it not happen, even when I’ve worked closely with wildlife and land-management agencies,” she says. “The system just isn’t designed to respond to the urgent challenges we’re facing,” she says.Gilbert took stock of her skills and knowledge, and how they could be put to use, settling on nature-based solutions such as forest-carbon storage and biodiversity. She made a shortlist of companies and non-governmental organizations (NGOs) doing that kind of work and started contacting them to discuss her options.In April this year, a month after securing tenure, Gilbert joined Natural Capital Exchange, a start-up firm based in San Francisco, California. The company allows small private landowners to sell carbon credits for preserving forests on their land. Gilbert’s role as senior lead for natural capital involves adding biodiversity credits to the company’s offerings, to provide incentives for conserving functioning, well-managed forests.Giving up the security and freedom that tenure offers was a big step, but Gilbert says that the hardest part of the decision was actually breaking the news to her graduate students, whose reactions ranged from anger, to understanding, to some combination of the two. “There’s a lot of mentoring and mutual responsibility there, so telling them and helping them through the process of finding a new adviser has been by far the most emotionally gruelling part,” she says.But she is excited to be taking up the challenge of working in the fast-paced world of a start-up company. “The company is full of rigorous, smart people who want to do good work,” she says. “It’s going to be a wild and exciting ride.”Spreading the wordIt’s a ride that Alice Bell knows well. By 2015, she had spent 11 years working as a lecturer in science communication at Imperial College London, and as a research fellow in the Science Policy Research Unit at the University of Sussex in Brighton, UK. She decided to leave academia for good and took up a position as head of communications at the climate-change campaign group Possible, based in London.The move came about partly by necessity — Bell’s contract was due to end, and she felt that UK government cuts were making academia an ever-more precarious occupation — but it stemmed mainly from a desire to be more directly involved in tackling the climate crisis.While at Imperial, she had built and launched a college-wide interdisciplinary course on climate change that had forced her to look more deeply into the issue. “I felt a greater urgency to put my skills somewhere they would be best utilized,” she says.Bell says leaving academia was the right choice. She thinks she is having a bigger impact on the climate crisis, and that her work–life balance has improved; she also feels more engaged in her work. “I feel more intellectually stimulated in workshops with NGOs than I did in most academic meetings,” she says, adding that she finds it liberating to be freed from academia’s pressure to publish, and from the weight of that pressure on career progression.But there are some drawbacks. “When you’re working for a small charity, no one knows who you are,” says Bell. “I was taken more seriously when I could say I was from Imperial.”Some might fear that leaving academia could arouse suspicions that they weren’t good enough to stay. “Ignore that voice,” she advises. “For many individuals, it could well be the best decision to give up.”Change from withinNot everyone, however, is ready or willing to give up on an academic career that they have spend years building up. And some find opportunities to get more involved in concrete climate solutions from within academia.

    Meade Krosby provides natural-resource managers and policymakers with scientific evidence on climate-change impacts and adaptation actions.Credit: Eric Bruns

    Since 2017, Meade Krosby has combined an academic post as a senior scientist at the University of Washington’s Climate Impacts Group in Seattle, where she works on climate vulnerability assessment and adaptation planning, with a director’s role at the university’s Northwest Climate Adaptation Science Center. The centre provides natural-resource managers and policymakers in the region with scientific evidence on climate-change impacts and adaptation actions. Krosby calls it a “boundary organization”, an interface between science and society, “acting as a conduit between the two”.“We bring applied science to decision-making around climate change, and bring decision-makers’ and communities’ concerns and knowledge back into academia to inform the kind of research that is done,” she says.Between 2016 and 2018, Krosby collaborated with Indigenous scholars, tribal organizations and other university scientists to develop the Tribal Climate Tool, a free online resource that aims to get the best available climate projections into the hands of Indigenous communities, to inform their planning for climate change. The tool, which launched in 2018, is now being used in many hazard-mitigation plans, such as the Samish Indian Nation’s 2019 climate-change vulnerability assessment. Krosby is also writing a paper on its development and use, producing a more conventional academic output to complement a tool that makes a difference in the real world.“You can do really useful work that doesn’t look like basic science, but it’s not always a trade-off between doing cool science and useful science,” she says.Funding challengeKrosby knew early on in her academic career that she wanted to make practical contributions that would help society to prepare for climate change. She started looking for this kind of applied work in 2009, during her postdoctoral research at the University of Washington, but found it hard at first to find funding — either from federal funding agencies or from private foundations. Then, in 2010, she received funding from the US Department of the Interior to look at species mobility and connectivity, and was able to use that to create a position for herself in the Climate Impacts Group.But she quickly found that her experience in more conventional academic settings had not prepared her for the kinds of project that the group undertook, with the aim of making science useful for policymakers and the public. “It was shocking how ill-prepared I was for transdisciplinary work,” she says. “We’re not trained to do, or to value, those kinds of collaborations.” The centre now supports fellowships and training in societally engaged research, and Krosby teaches a graduate course on how to connect science to society. “It’s an opportunity to train early-career scientists to do the work we never got trained to do,” she says. In 2020, she co-authored a paper1 calling for changes in how scientists are trained, by emphasizing skills such as collaboration and communication1.Academic career structures are not set up to promote and reward work that requires lots of collaboration with people outside the university, and which doesn’t necessarily result in a typical scientific publication, says Krosby. “The work I want to do wouldn’t be rewarded in a tenure-track position,” she adds. “To do this effectively, universities need to think about their incentive structure. Is a peer-reviewed paper really the most important outcome?”Reef encounterJulia Baum, a marine ecologist at the University of Victoria in Canada, has found a way to do practical, climate-focused work in a standard academic job. For her, the turning point came in 2015, when a massive marine heatwave nearly wiped out the tropical reef she was studying. “I watched a beautiful pristine reef melt down in 10 months,” she says. “I used to think overfishing was the biggest threat — then climate change came and hit me over the head.”

    Julia Baum records data on the Pacific atoll of Kiritimati, after a marine heatwave in 2015 nearly destroyed the coral reef.Credit: Kristina Tietjen

    That experience prompted her to completely overhaul her research programme to focus exclusively on climate impacts and how to mitigate them. “I want to do more than just document a sinking ship — I want to help right it,” she says.Baum’s tenured position offers her the flexibility of making that change, and she says she felt a moral obligation to apply her knowledge in a way that would help address the biggest threat facing the planet. As well as redirecting her research, Baum is designing a cross-university graduate-training programme focused on coastal climate solutions. This will offer training in professional skills that are crucial for climate work but are rarely taught in universities — such as how to collaborate and negotiate with non-academic partners, and how to deal with the media.But, like Krosby, Baum says she and many of her colleagues feel frustrated that a lot of universities don’t seem to value or support any kind of work outside conventional academic publications. Those who want to apply their findings to real-world problems often have to do it on their own, with no real benefit to their academic career. “Universities need to rise to the challenge and find innovative ways to support their faculty, by valuing and rewarding solutions work in their hiring and promotion criteria,” she says.If they don’t, universities risk losing more dedicated researchers such as Gilbert and Bell to the private sector. “If there comes a point when the climate-solutions impact I can have within academia seems too small, then yes, I would make the leap,” says Baum.Maximum impactFor academics looking for a way to take on a bigger role in the fight against climate change, there are a lot of options — from finding or making your own position in a university, to leaving for a company or charity that is doing more immediate, hands-on work. But the first step is working out where you can have the most impact, and what you can bring to the table. “For many people, the biggest impact you can have is through your students,” says Gilbert. “If you can focus on that and feel satisfied, that’s great.”For those who choose to leave, however, it pays to spend some time doing your research, finding companies and organizations that are doing the kind of work you are interested in, and talking to them about what you could offer. You might be surprised to find just how useful your skills can be outside academia — not just the disciplinary knowledge you have gained, but transferable skills such as technical writing and the ability to review and synthesize complex research. “The list of things we’re good at is pretty awesome,” says Gilbert. More

  • in

    Author Correction: A new wave of marine fish invasions through the Panama and Suez canals

    Authors and AffiliationsSmithsonian Tropical Research Institute – STRI, Balboa, Republic of PanamaGustavo A. Castellanos-Galindo, D. Ross Robertson, Diana M. T. Sharpe & Mark E. TorchinLeibniz Centre for Tropical Marine Research (ZMT), Bremen, GermanyGustavo A. Castellanos-GalindoAuthorsGustavo A. Castellanos-GalindoD. Ross RobertsonDiana M. T. SharpeMark E. TorchinCorresponding authorCorrespondence to
    Gustavo A. Castellanos-Galindo. More