Effects of soil core handling, transport and storage on numbers and body sizes of edaphic predatory mites (Gamasina)
DOI:
https://doi.org/10.25674/so94iss3id304Keywords:
Biodiversity, extraction, sampling, soil fauna, soil microarthropodsAbstract
In recent years, a number of collaborative projects began to collect consistent data on soil animal communities with the aim to understand, model, and map edaphic biodiversity, and to support environmental planning and decision making. Especially when operating on an international scale, it is vital for these programs to develop standardized protocols for properly sampling and processing soil cores. While guidelines for sampling, extracting, identifying and enumerating animals from soils have been published, the influence of transport and storage conditions on the recovery of animals has received very little attention. In this paper, the effects of improper treatment of cores on the extraction efficiency of predatory mites (Gamasina) from a temperate deciduous forest soil are investigated. Neither prolonged storage, shaking, compression or any of two combination treatments (compression + prolonged storage; shaking + prolonged storage) exerted a significant influence on the total abundance or the body size distributions of the mites. In contrast, both warming over 25°C and overfilling the sample containers of the Tullgren extractor significantly and drastically reduced the recovery of the animals, irrespective of body size. In conclusion, while the total (group) abundance of gamasid mites seems to be rather insensitive against improper sample treatment, the temperature of cores during transport and storage and a suitable volume of material in the extractor containers need to be adressed when planning the logistics of large scale sampling campaigns. Further studies on this topic are encouraged that also include other animal groups, other climate zones, and preferrably work on the level of species.
Downloads
References
André, H. M., X. Ducarme & P. Lebrun (2002): Soil biodiversity: myth, reality or conning? – Oikos 96: 3–24.
Aragão, O. O. S., S. M. Oliveira-Longatti, A. A. Souza, E. C. Jesus, M. N. Merlo, E. P. Oliveira & F. M. S. Moreira (2020): The Effectiveness of a Microbiological Attribute as a Soil Quality Indicator Depends on the Storage Time of the Sample. – Journal of Soil Science and Plant Nutrition 20: 2525–2535.
Brandt, F. B., B. Breidenbach, K. Brenzinger & R. Conrad (2014): Impact of short-term storage temperature on determination of microbial community composition and abundance in aerated forestsoil and anoxic pond sediment samples. – Systematic and Applied Microbiology 37: 570–577.
Bruckner A. (1998): Augers may bias field samples of soil mesofauna. – Pedobiologia 42: 309–315.
Dunger, W. & H. J. Fiedler (1997): Methoden der Bodenbiologie. 2nd ed. Gustav Fischer, Jena: 539 pp.
Edwards C. A. & K. E. Fletcher (1971): A comparison of extraction methods for terrestrial arthropods. – In: J. Phillipson (ed.): Methods of Study in Quantitative Soil Ecology: Population, production, and energy flow. – IBP Handbook 18, Blackwell Scientific Publishers, Oxford: 150–185.
Ellenberg, H., H. E. Weber, R. Düll, V. Wirth, W. Werner & D. Paulißen (1992): Zeigerwerte von Pflanzen in Mitteleuropa. – Scripta Geobotanica 18: 1–258.
Food and Agriculture Organization (2020): State of knowledge of soil biodiversity – Status, challenges and potentialities. – Report 2020, Rome: 583 pp.
Guerra, C. A., A. Heintz-Buschart, J. Sikorski, A. Chatzinotas, N. Guerrero-Ramírez, S. Cesarz, L. Beaumelle, M. C. Rillig, F. T. Maestre, M. Delgado-Baquerizo & et al. (2020): Blind spots in global soil biodiversity and ecosystem function research. – Nature Communications 11: 3870.
Guerra C. A., R. D. Bardgett, L. Caon, T. W. Crowther, M. Delgado-Baquerizo, L. Montanarella, L. M. Navarro, A. Orgiazzi, B. K. Singh, L. Tedersoo & et al. (2021a): Tracking, targeting, and conserving soil biodiversity. A monitoring and indicator system can inform policy. – Science 371: 239–241.
Guerra, C. A., D. H. Wall & N. Eisenhauer (2021b): Unearthing soil ecological observations. – Soil Organisms 93: 79–81.
Kilian, W., F. Müller & F. Starlinger (1993): Die forstlichen Wuchsgebiete Österreichs. Eine Naturraumgliederung nach waldökologischen Gesichtspunkten. – Berichte der forstlichen Bundesversuchsanstalt Wien 82: 1–60.
Lakly, M. B. & D. A. Crossley (2000): Tullgren extraction of soil mites (Acarina): Effect of refrigeration time on extraction efficiency. – Experimental and Applied Acarology 24: 135–140.
Lawrence, K. S., G. W. Lawrence & E. van Santan (2005): Effect of controlled cold storage on recovery of Rotylenchulus reniformis from naturally infested soil. – Journal of Nematology 37: 272–275.
Lüdecke, D., M. S. Ben-Shachar, I. Patil, P. Waggoner & D. Makowski (2021): performance: An R Package for Assessment, Comparison and Testing of Statistical Models. – Journal of Open Source Software 6: 1–8.
Maestre, F. T. & N. Eisenhauer (2019): Recommendations for establishing global collaborative networks in Soil Ecology. – Soil Organisms 91: 73–85.
Mathieu, J., A. C. Antunes, S. Barot, A. E. Bonato Asato, M. L. C. Bartz, G. G. Brown, I. Calderon-Sanou, T. Decaëns, S. J. Fonte, P. Ganault & et al. (2022): sOilFauna - a global synthesis effort on the drivers of soil macrofauna communities and functioning. – Soil Organisms 94: 111–126.
Murphy P. W. (1962): Extraction methods for soil animals. I. Dynamic methods with particular reference to funnel processes. – In: Murphy, P. W. (ed): Progress in Soil Zoology. – Butterworths, London: 75–114.
Nestroy O., O. H. Danneberg, M. Englisch, A. Geßl, H. Hager, E. Herzberger, W. Kilian, P. Nelhiebel, E. Pecina, A. Pehamberger & et al. (2000): Systematische Gliederung der Böden Österreichs (Österreichische Bodensystematik 2000). – Mitteilungen der Österreichischen Bodenkundlichen Gesellschaft 60: 1–124.
Potapov, A. M., X. Sun, A. D. Barnes, M. J. I. Briones, G. G. Brown, E. K. Cameron, C.-H. Chang, J. Cortet, N. Eisenhauer, A. L. C. Franco & et al. (2022): Global monitoring of soil animal communities using a common methodology. – Soil Organisms 94: 55–68.
Pulleman, M., R. Creamer, U. Hamer, J. Helder, C. Pelosi, G. Pérès & M. Rutgers (2012): Soil biodiversity, biological indicators and soil ecosystem services - an overview of European approaches. – Current Opinion in Environmental Sustainability 4: 529–538.
R Core Team (2021). R: A language and environment for statistical computing. – R Foundation for Statistical Computing, Vienna, Austria.
Rubin, B. E. R., S. M. Gibbons, S. Kennedy, J. Hampton-Marcell, S. Owens & J. A. Gilbert (2013): Investigating the Impact of Storage Conditions on Microbial Community Composition in Soil Samples. – PLOS ONE 8: e70460.
Stone D., P. Blomkvist, N. Bohse Hendriksen, M. Bonkowski, H.Bracht Jørgensen, F. Carvalho, M. B. Dunbar, C. Gardi, S. Geisen, R. Griffiths & et al. (2016): A method of establishing a transect for biodiversity and ecosystem function monitoring across Europe. – Applied Soil Ecology 97: 3–11.
Venables, W. N. & B. D. Ripley (2002): Modern Applied Statistics with S. 4th ed. Springer, New York: 495 pp.
Wallnöfer S., L. Mucina & V. Grass (1993): Querco-Fagetea – In: Mucina L., G. Grabherr & S. Wallnöfer (eds): Die Pflanzengesellschaften Österreichs. Teil III: Wälder und Gebüsche. – Gustav Fischer, Jena: 85–236.
Zeileis, A., C. Kleiber & S. Jackman (2008): Regression Models for count data in R. – Journal of Statistical Software 27: 1–25.
Downloads
Additional Files
Published
Issue
Section
License
Copyright (c) 2022 SOIL ORGANISMS
This work is licensed under a Creative Commons Attribution 4.0 International License.
All articles on www.soil-organisms.org may be read, copied, distributed, and (in limited quantity) printed for non-commercial, private, scientific purposes.
