in

Cascading effects of moth outbreaks on subarctic soil food webs

  • 1.

    Pickett, S. T. A. & White, P. S. The Ecology of Natural Disturbance and Patch Dynamics (Academic Press, 1985).

    Google Scholar 

  • 2.

    IPBES. Global assessment report on biodiversity and ecosystem services of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES Secretariat, 2019).

    Google Scholar 

  • 3.

    Brun, P. et al. Large-scale early-wilting response of Central European forests to the 2018 extreme drought. Glob. Change Biol. 00, 1–15 (2020).

    CAS 

    Google Scholar 

  • 4.

    Cardinale, B. J., Gonzalez, A., Allington, G. R. H. & Loreau, M. Is local biodiversity declining or not? A summary of the debate over analysis of species richness time trends. Biol. Conserv. 219, 175–183 (2018).

    Article 

    Google Scholar 

  • 5.

    Vellend, M. et al. Global meta-analysis reveals no net change in local-scale plant biodiversity over time. Proc. Natl. Acad. Sci. U.S.A. 110, 19456–19459 (2013).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 6.

    Bardgett, R. D. & Wardle, D. A. Aboveground-Belowground Linkages: Biotic Interactions, Ecosystem Processes, and Global Change (Oxford University Press, 2010).

    Google Scholar 

  • 7.

    Bardgett, R. D. & van der Putten, W. H. Belowground biodiversity and ecosystem functioning. Nature 515, 505–511 (2014).

    ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 8.

    Bardgett, R. D. & Caruso, T. Soil microbial community responses to climate extremes: Resistance, resilience and transitions to alternative states. Philos. Trans. R. Soc. Lond. B Biol. Sci. 375, 20190112 (2020).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 9.

    Thom, D. & Seidl, R. Natural disturbance impacts on ecosystem services and biodiversity in temperate and boreal forests: Disturbance impacts on biodiversity and services. Biol. Rev. 91, 760–781 (2016).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 10.

    van der Putten, W. H. et al. Trophic interactions in a changing world. Basic Appl. Ecol. 5, 487–494 (2004).

    Article 

    Google Scholar 

  • 11.

    Lafferty, K. D. & Suchanek, T. H. Revisiting Paine’s 1966 sea star removal experiment, the most-cited empirical article in the American Naturalist. Am. Nat. 188, 365–378 (2016).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 12.

    Scherber, C. et al. Bottom-up effects of plant diversity on multitrophic interactions in a biodiversity experiment. Nature 468, 553–556 (2010).

    ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 13.

    Barnes, A. D. et al. Direct and cascading impacts of tropical land-use change on multi-trophic biodiversity. Nat. Ecol. Evol. 1, 1511–1519 (2017).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 14.

    Barbier, M. & Loreau, M. Pyramids and cascades: A synthesis of food chain functioning and stability. Ecol. Lett. 22, 405–419 (2019).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 15.

    Mancinelli, G. & Mulder, C. Chapter three—detrital dynamics and cascading effects on supporting ecosystem services. In Advances in ecological research Vol. 53 (eds Woodward, G. & Bohan, D. A.) 97–160 (Academic Press, 2015).

    Google Scholar 

  • 16.

    Mulder, C., Vonk, J. A., Hollander, H. A. D., Hendriks, A. J. & Breure, A. M. How allometric scaling relates to soil abiotics. Oikos 120, 529–536 (2011).

    Article 

    Google Scholar 

  • 17.

    Allen, A. P. & Gillooly, J. F. Towards an integration of ecological stoichiometry and the metabolic theory of ecology to better understand nutrient cycling. Ecol. Lett. 12, 369–384 (2009).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 18.

    de Ruiter, P. C., Neutel, A.-M. & Moore, J. C. Energetics, patterns of interaction strengths, and stability in real ecosystems. Science 269, 1257–1260 (1995).

    ADS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 19.

    Estes, J. A. et al. Trophic downgrading of planet earth. Science 333, 301–306 (2011).

    ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 20.

    Taberlet, P., Bonin, A., Zinger, L. & Coissac, E. Environmental DNA: For Biodiversity Research and Monitoring (Oxford University Press, 2018).

    Book 

    Google Scholar 

  • 21.

    Gravel, D., Albouy, C. & Thuiller, W. The meaning of functional trait composition of food webs for ecosystem functioning. Philos. Trans. R. Soc. Lond. B Biol. Sci. 371, 20150268 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 22.

    Barnes, A. D. et al. Energy flux: The link between multitrophic biodiversity and ecosystem functioning. Trends Ecol. Evol. 33, 186–197 (2018).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 23.

    Elton, C. S. Animal Ecology 1–256 (Macmillan Co., 1927). https://doi.org/10.5962/bhl.title.7435.

    Book 

    Google Scholar 

  • 24.

    Bohan, D. A. et al. Next-generation global biomonitoring: Large-scale, automated reconstruction of ecological networks. Trends Ecol. Evol. 32, 477–487 (2017).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 25.

    Roslin, T. & Majaneva, S. The use of DNA barcodes in food web construction—terrestrial and aquatic ecologists unite!. Genome 59, 603–628 (2016).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 26.

    Cohen, J. E. et al. Improving food webs. Ecology 74, 252–258 (1993).

    Article 

    Google Scholar 

  • 27.

    Buzhdygan, O. Y. et al. Biodiversity increases multitrophic energy use efficiency, flow and storage in grasslands. Nat. Ecol. Evol. 4, 393–405 (2020).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 28.

    Martinez, N. D. Effects of resolution on food web structure. Oikos 66, 403 (1993).

    Article 

    Google Scholar 

  • 29.

    Thompson, R. M. et al. Food webs: Reconciling the structure and function of biodiversity. Trends Ecol. Evol. 27, 689–697 (2012).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 30.

    Kardol, P., Throop, H. L., Adkins, J. & de Graaff, M.-A. A hierarchical framework for studying the role of biodiversity in soil food web processes and ecosystem services. Soil Biol. Biochem. 102, 33–36 (2016).

    CAS 
    Article 

    Google Scholar 

  • 31.

    Ohlmann, M. et al. Diversity indices for ecological networks: A unifying framework using Hill numbers. Ecol. Lett. 22, 737–747 (2019).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 32.

    Pellissier, L. et al. Comparing species interaction networks along environmental gradients. Biol. Rev. 93, 785–800 (2017).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 33.

    Jepsen, J. U. et al. Ecosystem impacts of a range expanding forest defoliator at the forest-tundra ecotone. Ecosystems 16, 561–575 (2013).

    Article 

    Google Scholar 

  • 34.

    Karlsen, S. R., Jepsen, J. U., Odland, A., Ims, R. A. & Elvebakk, A. Outbreaks by canopy-feeding geometrid moth cause state-dependent shifts in understorey plant communities. Oecologia 173, 859–870 (2013).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 35.

    Jepsen, J. U., Hagen, S. B., Ims, R. A. & Yoccoz, N. G. Climate change and outbreaks of the geometrids Operophtera brumata and Epirrita autumnata in subarctic birch forest: Evidence of a recent outbreak range expansion. J. Anim. Ecol. 77, 257–264 (2008).

    PubMed 
    Article 

    Google Scholar 

  • 36.

    Vindstad, O. P. L., Jepsen, J. U., Ek, M., Pepi, A. & Ims, R. A. Can novel pest outbreaks drive ecosystem transitions in northern-boreal birch forest?. J. Ecol. 107, 1141–1153 (2019).

    Article 

    Google Scholar 

  • 37.

    Sandén, H. et al. Moth outbreaks reduce decomposition in subarctic forest soils. Ecosystems 23, 151–163 (2019).

    Article 
    CAS 

    Google Scholar 

  • 38.

    Vindstad, O. P. L. et al. Numerical responses of saproxylic beetles to rapid increases in dead wood availability following geometrid moth outbreaks in sub-arctic mountain birch forest. PLoS ONE 9, e99624 (2014).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 39.

    Nilsson, M.-C. & Wardle, D. A. Understory vegetation as a forest ecosystem driver: Evidence from the northern Swedish boreal forest. Front. Ecol. Environ. 3, 421–428 (2005).

    Article 

    Google Scholar 

  • 40.

    Bråthen, K. A. & Ravolainen, V. T. Niche construction by growth forms is as strong a predictor of species diversity as environmental gradients. J. Ecol. 103, 701–713 (2015).

    Article 

    Google Scholar 

  • 41.

    Bråthen, K. A., Gonzalez, V. T. & Yoccoz, N. G. Gatekeepers to the effects of climate warming? Niche construction restricts plant community changes along a temperature gradient. Perspect. Plant Ecol. Evol. Syst. 30, 71–81 (2018).

    Article 

    Google Scholar 

  • 42.

    Vindstad, O. P. L., Jepsen, J. U. & Ims, R. A. Resistance of a sub-arctic bird community to severe forest damage caused by geometrid moth outbreaks. Eur. J. For. Res. 134, 725–736 (2015).

    Article 

    Google Scholar 

  • 43.

    Parker, T. C. et al. Slowed biogeochemical cycling in sub-arctic birch forest linked to reduced mycorrhizal growth and community change after a defoliation event. Ecosystems 20, 316–330 (2017).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 44.

    Saravesi, K. et al. Moth outbreaks alter root-associated fungal communities in subarctic mountain birch forests. Microb. Ecol. 69, 788–797 (2015).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 45.

    Dunne, J. A. The network structure of food webs. In Ecological Networks: Linking Structure to Dynamics in Food Webs (eds Pascual, M. & Dunne, J. A.) 27–86 (Oxford University Press, 2006).

    Google Scholar 

  • 46.

    Rodriguez-Ramos, J. C. et al. Changes in soil fungal community composition depend on functional group and forest disturbance type. New Phytol. 00, 1–13 (2020).

    Google Scholar 

  • 47.

    Decaëns, T. Macroecological patterns in soil communities. Glob. Ecol. Biogeogr. 19, 287–302 (2010).

    Article 

    Google Scholar 

  • 48.

    Bardgett, R. D., Yeates, G. W. & Anderson, J. M. Patterns and determinants of soil biological diversity. In Biological Diversity and Function in Soils (eds Hopkins, D. et al.) 100–118 (Cambridge University Press, 2005).

    Chapter 

    Google Scholar 

  • 49.

    Worm, B. & Duffy, J. E. Biodiversity, productivity and stability in real food webs. Trends Ecol. Evol. 18, 628–632 (2003).

    Article 

    Google Scholar 

  • 50.

    Ponsard, S., Arditi, R. & Jost, C. Assessing top-down and bottom-up control in a litter-based soil macroinvertebrate food chain. Oikos 89, 524–540 (2000).

    Article 

    Google Scholar 

  • 51.

    Kristensen, J. Å., Rousk, J. & Metcalfe, D. B. Below-ground responses to insect herbivory in ecosystems with woody plant canopies: A meta-analysis. J. Ecol. 108, 917–930 (2020).

    Article 

    Google Scholar 

  • 52.

    González, V. T. et al. Batatasin-III and the allelopathic capacity of Empetrum nigrum. Nord. J. Bot. 33, 225–231 (2015).

    ADS 
    Article 

    Google Scholar 

  • 53.

    Veen, G. F. et al. The role of plant litter in driving plant-soil feedbacks. Front. Environ. Sci. 7, 168 (2019).

    Article 

    Google Scholar 

  • 54.

    Calizza, E., Rossi, L., Careddu, G., Sporta Caputi, S. & Costantini, M. L. Species richness and vulnerability to disturbance propagation in real food webs. Sci. Rep. 9, 19331 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 55.

    Antiqueira, P. A. P., Petchey, O. L., dos Santos, V. P., de Oliveira, V. M. & Romero, G. Q. Environmental change and predator diversity drive alpha and beta diversity in freshwater macro and microorganisms. Glob. Change Biol. 24, 3715–3728 (2018).

    ADS 
    Article 

    Google Scholar 

  • 56.

    Hedlund, K. et al. Trophic interactions in changing landscapes: Responses of soil food webs. Basic Appl. Ecol. 5, 495–503 (2004).

    Article 

    Google Scholar 

  • 57.

    Ettema, C. H. & Wardle, D. A. Spatial soil ecology. Trends Ecol. Evol. 17, 177–183 (2002).

    Article 

    Google Scholar 

  • 58.

    O’Brien, S. L. et al. Spatial scale drives patterns in soil bacterial diversity. Environ. Microbiol. 18, 2039–2051 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 59.

    Jiménez, J. J., Decaëns, T., Lavelle, P. & Rossi, J.-P. Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability. BMC Ecol. 14, 26 (2014).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 60.

    Taberlet, P. et al. Soil sampling and isolation of extracellular DNA from large amount of starting material suitable for metabarcoding studies. Mol. Ecol. 21, 1816–1820 (2012).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 61.

    Zinger, L. et al. Extracellular DNA extraction is a fast, cheap and reliable alternative for multi-taxa surveys based on soil DNA. Soil Biol. Biochem. 96, 16–19 (2016).

    CAS 
    Article 

    Google Scholar 

  • 62.

    Binladen, J. et al. The use of coded PCR primers enables high-throughput sequencing of multiple homolog amplification products by 454 parallel sequencing. PLoS ONE 2, e197 (2007).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 63.

    Valentini, A. et al. New perspectives in diet analysis based on DNA barcoding and parallel pyrosequencing: The trnL approach. Mol. Ecol. Resour. 9, 51–60 (2009).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 64.

    Boyer, F. et al. obitools: A unix-inspired software package for DNA metabarcoding. Mol. Ecol. Resour. 16, 176–182 (2016).

    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 65.

    Mercier, C., Boyer, F., Bonin, A. & Coissac, E. SUMATRA and SUMACLUST: fast and exact comparison and clustering of sequences. in Programs and Abstracts of the SeqBio 2013 workshop. Abstract 27–29 (Citeseer, 2013).

  • 66.

    Zinger, L. et al. DNA metabarcoding—Need for robust experimental designs to draw sound ecological conclusions. Mol. Ecol. 28, 1857–1862 (2019).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 67.

    Zinger, L. et al. metabaR : an R package for the evaluation and improvement of DNA metabarcoding data quality. https://doi.org/10.1101/2020.08.28.271817 (2020).

  • 68.

    R Core Team. A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, 2019).

  • 69.

    Nguyen, N. H. et al. FUNGuild: An open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).

    Article 

    Google Scholar 

  • 70.

    Louca, S., Parfrey, L. W. & Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 353, 1272–1277 (2016).

    ADS 
    CAS 
    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 71.

    Adl, S. M. et al. Revisions to the classification, nomenclature, and diversity of eukaryotes. J. Eukaryot. Microbiol. 66, 4–119 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 72.

    Fiore-Donno, A. M. et al. Functional traits and spatio-temporal structure of a major group of soil protists (Rhizaria: Cercozoa) in a temperate grassland. Front. Microbiol. 10, 1332 (2019).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 73.

    Ho, A., Lonardo, D. P. D. & Bodelier, P. L. E. Revisiting life strategy concepts in environmental microbial ecology. FEMS Microbiol. Ecol. 93, 6 (2017).

    Google Scholar 

  • 74.

    Calderón-Sanou, I., Münkemüller, T., Boyer, F., Zinger, L. & Thuiller, W. From environmental DNA sequences to ecological conclusions: How strong is the influence of methodological choices?. J. Biogeogr. 47, 193–206 (2020).

    Article 

    Google Scholar 

  • 75.

    Antunes, P. M. & Koyama, A. Chapter 9 – Mycorrhizas as Nutrient and Energy Pumps of Soil Food Webs: Multitrophic Interactions and Feedbacks. in Mycorrhizal Mediation of Soil Fertility, Structure, and Carbon Storage (eds. Johnson, N. C., Gehring, C. & Jansa, J.) 149–173 (Elsevier, 2017).

  • 76.

    Goodrich, B., Gabry, J., Ali, I. & Brilleman, S. rstanarm: Bayesian applied regression modeling via Stan. (R package version 2.21.1, 2020).

  • 77.

    McArtor, D. B., Lubke, G. H. & Bergeman, C. S. Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic. Psychometrika 82, 1052–1077 (2017).

    MathSciNet 
    PubMed 
    MATH 
    Article 
    PubMed Central 

    Google Scholar 


  • Source: Ecology - nature.com

    A critical review of point-of-use drinking water treatment in the United States

    A material difference