Automatic Drought Tolerance Measurement of the Soil-Living Microarthropod, Folsomia Candida
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Abstract
Soil is a complex habitat where microarthropods, such as mites (Acari) and springtails (Collembola) species occur in high number and species diversity. Microarthropods play an essential role in organic matter decomposition and provide an important ecosystem service in soil. The soil-dwelling microarthropods are sensitive to environmental changes; therefore, their ecological characteristics are used to evaluate soil conditions. In modern environmental ecology, several species are involved in assessing the ecological consequences of drought periods. The growth rate is a standard sublethal parameter by which the body size of individuals is measured. Extracting microarthropods from the soil is difficult and time-consuming, requiring a high amount of human resources. Only a few samples can be processed due to laboratory limitations and high costs. However, nowadays the rapidly developing artificial intelligence (AI) technologies promise new opportunities in many research areas.
Data on soil-dwelling microarthropods could be collected quickly and automatically using our new digital soil extractor device, the Edapholog, equipped with image analysis based on AI. This device recognizes living individuals, classifies them, and measures their body length automatically. Using this system, the growth and reproductive success of various species in the same experimental culture could be rapidly and simultaneously monitored. In this study, we aimed to analyse the applicability of the Edapholog for measuring the body size of Collembola species and Folsomia candida through a set of drought tolerance tests with three soil moisture treatment levels. Moisture content was set based on the maximum water holding capacity (Wmax) of the soil applied. The three levels were set to Wmax:35%, 40%, and 50%. Furthermore, we aimed to test the reliability of the detection and recognition of the species and the accuracy and reliability of the automatic body size measurement of individuals.
Significant correlation (r= 0.94) exists between the automatically and manually measured body sizes. Although the different soil moisture treatments did not show marked differences in the collembolan body sizes between the moisture treatments, we found a significant difference in the reproduction rates between W50 and the other two (W35 and W40) treated groups. The Edapholog can greatly contribute to quick and precise data extraction and can have vast applicability in environmental ecology.
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Funding data
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European Commission
Grant numbers NYBZK/52/2023
References
Agatz, A., Hammers-Wirtz, M., Gergs, A., Mayer, T., Preuss, T.G. 2015. Family-portraits for daphnids: Scanning living individuals and populations to measure body length. Ecotoxicology 24(6), 1385–1394. https://doi.org/10.1007/s10646-015-1490-0
Aszálymonitoring. (n.d.). Retrieved 6 July 2023, from https://aszalymonitoring.vizugy.hu/
Balla, E., Flórián, N., Gergócs, V., Gránicz, L., Tóth, F., Németh, T., Dombos, M. 2020. An Opto-Electronic Sensor-Ring to Detect Arthropods of Significantly Different Body Sizes. Sensors 20(4), 982. https://doi.org/10.3390/s20040982
Bánszegi, O., Kosztolányi, A., Bakonyi, G., Szabó, B., Dombos, M. 2014. New Method for Automatic Body Length Measurement of the Collembolan, Folsomia candida Willem 1902 (Insecta: Collembola). PLoS ONE 9(6), e98230. https://doi.org/10.1371/journal.pone.0098230
Bardgett, R.D. 2005. The biology of soil: A community and ecosystem approach (34-37). Oxford University Press, New York (USA), p. 254.
Bayley, M., Petersen, S.O., Knigge, T., Köhler, H.-R., Holmstrup, M. 2001. Drought acclimation confers cold tolerance in the soil collembolan Folsomia candida. Journal of Insect Physiology 47(10), 1197–1204. https://doi.org/10.1016/S0022-1910(01)00104-4
Bilyk, Z.I., Shapovalov, Y.B., Shapovalov, V. B., Megalinska, A.P., Andruszkiewicz, F., Dołhańczuk-Śródka, A. 2020. Assessment of mobile phone applications feasibility on plant recognition: Comparison with Google Lens AR-app. [б. в.]. CEUR Workshop Proceedings 2020. Vol. 2731, 61–78. https://doi.org/10.31812/123456789/4403
Briones, M. J.I. 2014. Soil fauna and soil functions: A jigsaw puzzle. Frontiers in Environmental Science 2. https://doi.org/10.3389/fenvs.2014.00007
Brussaard, L., de Ruiter, P.C., Brown, G.G. 2007. Soil biodiversity for agricultural sustainability. Agriculture, Ecosystems & Environment 121(3), 233–244. https://doi.org/10.1016/ j.agee.2006.12.013
Christin, S., Hervet, É., Lecomte, N. 2019. Applications for deep learning in ecology. Methods in Ecology and Evolution 10(10), 1632–1644. https://doi.org/10.1111/2041-210X.13256
Coleman, D.C., Callaham, M.A., Jr, Crossley, D.A., Jr. 2017. Fundamentals of Soil Ecology. Academic Press. https://doi.org/10.1016/C2015-0-04083-7
Crossley, D.A., Blair, J.M. 1991. A high-efficiency, “low-technology” Tullgren-type extractor for soil microarthropods. Agriculture, Ecosystems & Environment 34(1–4), 187–192. https://doi.org/10.1016/0167-8809(91)90104-6
Dombos, M., Kosztolányi, A., Szlávecz, K., Gedeon, C., Flórián, N., Groó, Z., Dudás, P., Bánszegi, O. 2017. EDAPHOLOG monitoring system: Automatic, real‐time detection of soil microarthropods. Methods in Ecology and Evolution 8(3), 313–321. https://doi.org/10.1111/2041-210X.12662
Duckworth, J., Jager, T., Ashauer, R. 2019. Automated, high-throughput measurement of size and growth curves of small organisms in well plates. Scientific Reports 9(1), 10. https://doi.org/10.1038/s41598-018-36877-0
Filser, J. 2002. The role of Collembola in carbon and nitrogen cycling in soil. Pedobiologia 46(3–4), 234–245. https://doi.org/10.1078/0031-4056-00130
Finlay, K., Beisner, B.E., Barnett, A.J.D. 2007. The use of the Laser Optical Plankton Counter to measure zooplankton size, abundance, and biomass in small freshwater lakes: LOPC in freshwater lakes. Limnology and Oceanography: Methods 5(1), 41–49. https://doi.org/10.4319/lom.2007.5.41
Flórián, N., Gránicz, L., Gergócs, V., Tóth, F., Dombos, M. 2020. Detecting Soil Microarthropods with a Camera-Supported Trap. Insects 11(4), 244. https://doi.org/10.3390/ insects11040244
Gedeon, C., Flórián, N., Liszli, P., Hambek-Oláh, B., Bánszegi, O., Schellenberger, J., Dombos, M. 2017. An Opto-Electronic Sensor for Detecting Soil Microarthropods and Estimating Their Size in Field Conditions. Sensors 17(8), 1757. https://doi.org/10.3390/s17081757
Hilligsøe, H., Holmstrup, M. 2003. Effects of starvation and body mass on drought tolerance in the soil collembolan Folsomia candida. Journal of Insect Physiology 49(1), 99–104. https://doi.org/10.1016/S0022-1910(02)00253-6
Høye, T.., Ärje, J., Bjerge, K., Hansen, O.L.P., Iosifidis, A., Leese, F., Mann, H.M.R., Meissner, K., Melvad, C., Raitoharju, J. 2021. Deep learning and computer vision will transform entomology. Proceedings of the National Academy of Sciences 118(2), e2002545117. https://doi.org/10.1073/ pnas.2002545117
IBPM SPSS Statistics for Windows (27.0). (2020). IBM Corp.
ISO (1999) Soil quality–Inhibition of reproduction of Collembola (Folsomia candida) by soil pollutants. ISO 11267. Geneva: International Standardization Organization.
ISO (2006) Soil quality–Sampling of soil invertebrates – Part 2: Sampling and extraction of micro-arthropods (Collembola and Acarina). ISO 23611-2: 2006. Geneva: International Standardization Organization.
ISO (2011) Soil quality–Avoidance test for determining the quality of soils and effects of chemicals on behaviour–Part 2: Test with collembolans (Folsomia candida). ISO 17512-2: 2011. Geneva: International Standardization Organization.
Kardol, P., Reynolds, W.N., Norby, R.J., & Classen, A.T. 2011. Climate change effects on soil microarthropod abundance and community structure. Applied Soil Ecology 47(1), 37–44. https://doi.org/10.1016/j.apsoil.2010.11.001
Laursen, S.F., Hansen, L.S., Bahrndorff, S., Nielsen, H. M., Noer, N.K., Renault, D., Sahana, G., Sørensen, J.G., Kristensen, T.N. 2021. Contrasting Manual and Automated Assessment of Thermal Stress Responses and Larval Body Size in Black Soldier Flies and Houseflies. Insects 12(5), 380. https://doi.org/10.3390/insects12050380
Liu, Z., Peng, C., Work, T., Candau, J.-N., DesRochers, A., Kneeshaw, D. 2018. Application of machine-learning methods in forest ecology: Recent progress and future challenges. Environmental Reviews 26(4), 339–350. https://doi.org/10.1139/er-2018-0034
Lock, K., Janssen, C.R. 2002. Ecotoxicity of nickel to Eisenia fetida, Enchytraeus albidus and Folsomia candida. Chemosphere 46(2), 197–200. https://doi.org/10.1016/S0045-6535(01)00112-6
Makkonen, M., Berg, M.P., van Hal, J.R., Callaghan, T.V., Press, M.C., Aerts, R. 2011. Traits explain the responses of a sub-arctic Collembola community to climate manipulation. Soil Biology and Biochemistry 43(2), 377–384. https://doi.org/10.1016/j.soilbio.2010.11.004
Mallard, F., Le Bourlot, V., Tully, T. 2013. An Automated Image Analysis System to Measure and Count Organisms in Laboratory Microcosms. PLoS ONE 8(5), e64387. https://doi.org/10.1371/journal.pone.0064387
Meehan, M.L., Barreto, C., Turnbull, M.S., Bradley, R. L., Bellenger, J.-P., Darnajoux, R., Lindo, Z. 2020. Response of soil fauna to simulated global change factors depends on ambient climate conditions. Pedobiologia 83, 150672. https://doi.org/10.1016/j.pedobi.2020.150672
Menta, C., Conti, F.D., Pinto, S., Bodini, A. 2018. Soil Biological Quality index (QBS-ar): 15 years of application at global scale. Ecological Indicators 85, 773–780. https://doi.org/10.1016/j.ecolind.2017.11.030
Ninon, R., Cyrille, D., Phillip, B. 2019. Fossil amber reveals springtails’ longstanding dispersal by social insects [Preprint]. Paleontology. https://doi.org/10.1101/699611
OECD, 2009. OECD Guidelines for Testing Chemicals 232 Collembolan Reproduction Test in Soil.
Pereira, P., Bogunovic, I., Muñoz-Rojas, M., Brevik, E.C. 2018. Soil ecosystem services, sustainability, valuation and management. Current Opinion in Environmental Science & Health 5, 7–13. https://doi.org/10.1016/j.coesh.2017.12.003
Silvertown, J. 2009. A new dawn for citizen science. Trends in Ecology & Evolution 24(9), 467–471. https://doi.org/10.1016/ j.tree.2009.03.017
Sjursen, H., Bayley, M., Holmstrup, M. 2001. Enhanced drought tolerance of a soil-dwelling springtail by pre-acclimation to a mild drought stress. Journal of Insect Physiology 47(9), 1021–1027. https://doi.org/10.1016/S0022-1910(01)00078-6
Sørensen, T.S., Holmstrup, M. 2005. A comparative analysis of the toxicity of eight common soil contaminants and their effects on drought tolerance in the collembolan Folsomia candida. Ecotoxicology and Environmental Safety 60(2), 132–139. https://doi.org/10.1016/j.ecoenv.2004.02.001
Steffen, W., Crutzen, P.J., McNeill, J.R. 2007. The Anthropocene: Are Humans Now Overwhelming the Great Forces of Nature? Ambio 36(8), 614–621. https://doi.org/10.1579/0044-7447(2007)36[614:TAAHNO]2.0.CO;2
Sys, S., Weißbach, S., Jakob, L., Gerber, S., Schneider, C. 2022. CollembolAI, a macrophotography and computer vision workflow to digitize and characterize samples of soil invertebrate communities preserved in fluid. Methods in Ecology and Evolution 13(12), 2729–2742. https://doi.org/10.1111/2041-210X.14001
Szabó, B., Bálint, B., Balogh, K., Mézes, M., Seres, A. 2022. Changes in soil moisture and temperature modify the toxicity of sodium selenite and sodium selenate for Folsomia candida (Collembola) Willem 1902. Applied Soil Ecology 177, 104543. https://doi.org/10.1016/j.apsoil.2022.104543
Wang, Y., Slotsbo, S., Holmstrup, M. 2022. Soil dwelling springtails are resilient to extreme drought in soil, but their reproduction is highly sensitive to small decreases in soil water potential. Geoderma 421, 115913. https://doi.org/10.1016/ j.geoderma.2022.115913