{"id":51691,"date":"2022-09-29T02:26:21","date_gmt":"2022-09-29T06:26:21","guid":{"rendered":"https:\/\/euvolution.com\/open-source-convergence\/uncategorized\/predicting-the-effects-of-winter-water-warming-in-artificial-lakes-on-zooplankton-and-its-environment-using-combined-machine-learning-models.php"},"modified":"2022-09-29T02:26:21","modified_gmt":"2022-09-29T06:26:21","slug":"predicting-the-effects-of-winter-water-warming-in-artificial-lakes-on-zooplankton-and-its-environment-using-combined-machine-learning-models","status":"publish","type":"post","link":"https:\/\/euvolution.com\/open-source-convergence\/machine-learning\/predicting-the-effects-of-winter-water-warming-in-artificial-lakes-on-zooplankton-and-its-environment-using-combined-machine-learning-models.php","title":{"rendered":"Predicting the effects of winter water warming in artificial lakes on zooplankton and its environment using combined machine learning models |&#8230;"},"content":{"rendered":"<p><p>Murphy, G. E. P., Romanuk, T. N. & Worm, B. Cascading effects of climate change on plankton community structure. Ecol. Evol. 10, 21702181. <a href=\"https:\/\/doi.org\/10.1002\/ece3.6055\" rel=\"nofollow\">https:\/\/doi.org\/10.1002\/ece3.6055<\/a> (2020).<\/p>\n<p>Article    PubMed    PubMed Central                        Google Scholar                <\/p>\n<p>Woodward, G., Daniel, M., Perkins, D. M. & Brown, L. E. Climate change and freshwater ecosystems: Impacts across multiple levels of organization. Philos. Trans. R. Soc. B 365, 20932106. <a href=\"https:\/\/doi.org\/10.1098\/rstb.2010.0055\" rel=\"nofollow\">https:\/\/doi.org\/10.1098\/rstb.2010.0055<\/a> (2010).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Lampert, W. Zooplankton research: The contribution of limnology to general ecological paradigms. Aquat. Ecol. 31, 1927. <a href=\"https:\/\/doi.org\/10.1023\/A:1009943402621\" rel=\"nofollow\">https:\/\/doi.org\/10.1023\/A:1009943402621<\/a> (1997).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Gannon, J. E. & Stemberger, R. S. Zooplankton (especially crustaceans and rotifers) as indicators of water quality. Trans. Am. Microsc. Soc. 97, 1635. <a href=\"https:\/\/doi.org\/10.2307\/3225681\" rel=\"nofollow\">https:\/\/doi.org\/10.2307\/3225681<\/a> (1978).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Ferdous, Z. & Muktadir, S. K. M. A review: Potentiality of zooplankton as bioindicator. Am. J. Appl. Sci. 6, 18151819 (2009).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Ejsmont-Karabin, J. The usefulness of zooplankton as lake ecosystem indicators: Rotifer Trophic State Index. Pol. J. Ecol. 60, 339350 (2012). <\/p>\n<p>                    Google Scholar                <\/p>\n<p>Gillooly, J. F. Effect of body size and temperature on generation time in zooplankton. J. Plankton Res. 22(2), 241251 (2000).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Lewandowska, A. M., Hillebrand, H., Lengfellner, K. & Sommer, U. Temperature effects on phytoplankton diversityThe zooplankton link. J. Sea Res. 85, 359364. <a href=\"https:\/\/doi.org\/10.1016\/j.seares.2013.07.003\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.seares.2013.07.003<\/a> (2014).<\/p>\n<p>ADS    Article                        Google Scholar                <\/p>\n<p>Carter, J. L. & Schindler, D. L. Responses of zooplankton populations to four decades of climate warming in Lakes of Southwestern Alaska. Ecosystems 15, 10101026. <a href=\"https:\/\/doi.org\/10.1007\/s10021-012-9560-0\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/s10021-012-9560-0<\/a> (2012).<\/p>\n<p>CAS    Article                        Google Scholar                <\/p>\n<p>Ejsmont-Karabin, J. & Wgleska, T. Disturbances in zooplankton seasonality in Lake Gosawskie (Poland) affected by permanent heating and heavy fish stocking. Ekol. Pol. 36, 245260 (1988).<\/p>\n<p>                    Google Scholar                <\/p>\n<p>Ejsmont-Karabin, J. et al. Rotifers in Heated Konin LakesA review of long-term observations. Water 12, 1660. <a href=\"https:\/\/doi.org\/10.3390\/w12061660\" rel=\"nofollow\">https:\/\/doi.org\/10.3390\/w12061660<\/a> (2020).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Evans, L. E., Hirst, A. G., Kratina, P. & Beaugrand, G. Temperature-mediated changes in zooplankton body size: Large scale temporal and spatial analysis. Ecography 43, 581590. <a href=\"https:\/\/doi.org\/10.1111\/ecog.04631\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/ecog.04631<\/a> (2020).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Wang, L. et al. Is zooplankton body size an indicator of water quality in (sub)tropical reservoirs in China?. Ecosystems 25, 656662. <a href=\"https:\/\/doi.org\/10.1007\/s10021-021-00656-2\" rel=\"nofollow\">https:\/\/doi.org\/10.1007\/s10021-021-00656-2<\/a> (2021).<\/p>\n<p>CAS    Article                        Google Scholar                <\/p>\n<p>Williamson, C. E., Saros, J. E., Vincent, W. F. & Smol, J. P. Lakes and reservoirs as sentinels, integrators, and regulators of climate change. Limnol. Oceanogr. 54(6), 22732282 (2009).<\/p>\n<p>ADS    Article                        Google Scholar                <\/p>\n<p>Richardson, A. J. In hot water: Zooplankton and climate change. ICES J. Mar. Sci. 65, 279295. <a href=\"https:\/\/doi.org\/10.1093\/icesjms\/fsn028\" rel=\"nofollow\">https:\/\/doi.org\/10.1093\/icesjms\/fsn028<\/a> (2008).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Visconti, A., Manca, M. & De Bernardi, R. Eutrophication-like response to climate warming: An analysis of Lago Maggiore (N. Italy) zooplankton in contrasting years. J. Limnol. 67(2), 8792 (2008).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Vandysh, O. I. The effect of thermal flow of large power facilities on zooplankton community under subarctic conditions. Water Res. 36(3), 310318. <a href=\"https:\/\/doi.org\/10.1134\/S0097807809030063\" rel=\"nofollow\">https:\/\/doi.org\/10.1134\/S0097807809030063<\/a> (2009).<\/p>\n<p>CAS    Article                        Google Scholar                <\/p>\n<p>Alric, B. et al. Local forcings affect lake zooplankton vulnerability and response to climate warming. Ecology 94(12), 27672780 (2013).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Daufresne, M., Lengfellner, K. & Sommer, U. Global warming benefits the small in aquatic ecosystems. PNAS 106(31), 1278812793. <a href=\"https:\/\/doi.org\/10.1073\/pnas.0902080106\" rel=\"nofollow\">https:\/\/doi.org\/10.1073\/pnas.0902080106<\/a> (2009).<\/p>\n<p>ADS    Article    PubMed    PubMed Central                        Google Scholar                <\/p>\n<p>Gutierrez, M. F. et al. Is recovery of large-bodied zooplankton after nutrient loading reduction hampered by climate warming? A long-term study of shallow hypertrophic Lake Sbygaard, Denmark. Water 8, 341. <a href=\"https:\/\/doi.org\/10.3390\/w8080341\" rel=\"nofollow\">https:\/\/doi.org\/10.3390\/w8080341<\/a> (2016).<\/p>\n<p>ADS    CAS    Article                        Google Scholar                <\/p>\n<p>Edwards, M. & Richardson, A. J. Impact of climate change on marine pelagic phenology and trophic mismatch. Nature 430, 881884. <a href=\"https:\/\/doi.org\/10.1038\/nature02808\" rel=\"nofollow\">https:\/\/doi.org\/10.1038\/nature02808<\/a> (2004).<\/p>\n<p>ADS    CAS    Article    PubMed                        Google Scholar                <\/p>\n<p>Thackeray, S. J., Jones, I. D. & Maberly, S. C. Long-term change in the phenology of spring phytoplankton: Species-specific responses to nutrient enrichment and climatic change. J. Ecol. 96, 523535. <a href=\"https:\/\/doi.org\/10.1111\/j.1365-2745.2008.01355.x\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/j.1365-2745.2008.01355.x<\/a> (2008).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Adrian, A., Wilhelm, S. & Gerten, D. Life-history traits of lake plankton species may govern their phenological response to climate warming. Life-history traits of lake plankton species may govern their phenological response to climate warming. Glob. Change Biol. 12, 652661. <a href=\"https:\/\/doi.org\/10.1111\/j.1365-2486.2006.01125.x\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/j.1365-2486.2006.01125.x<\/a> (2006).<\/p>\n<p>ADS    Article                        Google Scholar                <\/p>\n<p>Costello, J. H., Sullivan, B. K. & Gifford, D. J. A physicalbiological interaction underlying variable phenological responses to climate change by coastal zooplankton. J. Plankton Res. 28(11), 10991105. <a href=\"https:\/\/doi.org\/10.1093\/plankt\/fbl042\" rel=\"nofollow\">https:\/\/doi.org\/10.1093\/plankt\/fbl042<\/a> (2006).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Lewandowska, A. M. et al. Effects of sea surface warming on marine plankton. Ecol. Lett. 17, 614623. <a href=\"https:\/\/doi.org\/10.1111\/ele.12265\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/ele.12265<\/a> (2014).<\/p>\n<p>Article    PubMed                        Google Scholar                <\/p>\n<p>Wagner, C. & Adrian, R. Exploring lake ecosystems: Hierarchy responses to long-term change?. Glob. Change Biol. 15, 11041115. <a href=\"https:\/\/doi.org\/10.1111\/j.1365-2486.2008.01833.x\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/j.1365-2486.2008.01833.x<\/a> (2009).<\/p>\n<p>ADS    Article                        Google Scholar                <\/p>\n<p>Hart, R. C. Zooplankton feeding rates in relation to suspended sediment content: Potential influences on community structure in a turbid reservoir. Fresh. Biol. 19, 123139. <a href=\"https:\/\/doi.org\/10.1111\/j.1365-2427.1988.tb00334.x\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/j.1365-2427.1988.tb00334.x<\/a> (1988).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Carter, J. L., Schindler, D. E. & Francis, T. B. Effects of climate change on zooplankton community interactions in an Alaskan lake. Climate Change Resp. 4, 3. <a href=\"https:\/\/doi.org\/10.1186\/s40665-017-0031-x\" rel=\"nofollow\">https:\/\/doi.org\/10.1186\/s40665-017-0031-x<\/a> (2017).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Calbet, A. The trophic roles of microzooplankton in marine systems. ICES J. Mar. Sci. 65, 325331 (2008).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Wollrab, S. et al. Climate change-driven regime shifts in a planktonic food web. Am. Natur. 197, 281295. <a href=\"https:\/\/doi.org\/10.1086\/712813\" rel=\"nofollow\">https:\/\/doi.org\/10.1086\/712813<\/a> (2021).<\/p>\n<p>Article    PubMed                        Google Scholar                <\/p>\n<p>Recknagel, F., Adrian, R. & Khler, J. Quantifying phenological asynchrony of phyto- and zooplankton in response to changing temperature and nutrient conditions in Lake Mggelsee (Germany) by means of evolutionary computation. Environ. Model. Softw. 146, 105224. <a href=\"https:\/\/doi.org\/10.1016\/j.envsoft.2021.105224\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.envsoft.2021.105224<\/a> (2021).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>EEA. Projected changes in annual, summer and winter temperature. European Environmental Agency. <a href=\"https:\/\/www.eea.europa.eu\/data-and-maps\/figures\/projected-changes-in-annual-summer-1\" rel=\"nofollow\">https:\/\/www.eea.europa.eu\/data-and-maps\/figures\/projected-changes-in-annual-summer-1<\/a> (2014).<\/p>\n<p>IPCC. Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2021).<\/p>\n<p>Hutchinson, G. E. Concluding remarks. Cold Spring Harb. Symp. Quant. Biol. 22, 415427. <a href=\"https:\/\/doi.org\/10.1101\/SQB.1957.022.01.039\" rel=\"nofollow\">https:\/\/doi.org\/10.1101\/SQB.1957.022.01.039<\/a> (1957).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Ferrario, A. & Hmmerli, R. On Boosting: Theory and Applications. SSRN: <a href=\"https:\/\/ssrn.com\/abstract=3402687\" rel=\"nofollow\">https:\/\/ssrn.com\/abstract=3402687<\/a> (2019).<\/p>\n<p>Meysman, F. J. R. & Bruers, S. Ecosystem functioning and maximum entropy production: A quantitative test of hypotheses. Philos. Trans. R. Soc. B 365, 14051416. <a href=\"https:\/\/doi.org\/10.1098\/rstb.2009.0300\" rel=\"nofollow\">https:\/\/doi.org\/10.1098\/rstb.2009.0300<\/a> (2010).<\/p>\n<p>CAS    Article                        Google Scholar                <\/p>\n<p>Yu, Q., Ji, W., Prihodko, L., Anchang, J. Y. & Hanan, N. P. Study becomes insight: Ecological learning from machine learning. Methods Ecol. Evol. 12, 2172128. <a href=\"https:\/\/doi.org\/10.1111\/2041-210X.13686\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/2041-210X.13686<\/a> (2021).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Park, J. et al. Interpretation of ensemble learning to predict water quality using explainable artificial intelligence. Sci. Total Environ. 832, 155070. <a href=\"https:\/\/doi.org\/10.1016\/j.scitotenv.2022.155070\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.scitotenv.2022.155070<\/a> (2022).<\/p>\n<p>ADS    CAS    Article    PubMed                        Google Scholar                <\/p>\n<p>Grbi, L. et al. Coastal water quality prediction based on machine learning with feature interpretation and spatio-temporal analysis. Environ. Model. Softw. 155, 105458. <a href=\"https:\/\/doi.org\/10.1016\/j.envsoft.2022.105458\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.envsoft.2022.105458<\/a> (2022).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Kruk, M., Artiemjew, P. & Paturej, E. The application of game theory-based machine learning modelling to assess climate variability effects on the sensitivity of lagoon ecosystem parameters. Ecol. Inf. 66, 101462. <a href=\"https:\/\/doi.org\/10.1016\/j.ecoinf.2021.101462\" rel=\"nofollow\">https:\/\/doi.org\/10.1016\/j.ecoinf.2021.101462<\/a> (2021).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Hebert, P. D. N. Competition in zooplankton communities. Ann. Zool. Fennici 19, 349356 (1982).<\/p>\n<p>                    Google Scholar                <\/p>\n<p>Eigen, M. & Winkler, R. Laws of the Game. How the Principles of Nature Govern Chance (Princeton University Press, 1993).<\/p>\n<p>                    Google Scholar                <\/p>\n<p>Tilman, A. R., Plotkin, J. B. & Akay, E. Evolutionary games with environmental feedbacks. Nat. Commun. 11, 915. <a href=\"https:\/\/doi.org\/10.1038\/s41467-020-14531-6\" rel=\"nofollow\">https:\/\/doi.org\/10.1038\/s41467-020-14531-6<\/a> (2020).<\/p>\n<p>ADS    CAS    Article    PubMed    PubMed Central                        Google Scholar                <\/p>\n<p>Shapley, L. S. A Value for n-Person Games. In Contributions to the Theory of Games II (eds Kuhn, H. W. & Tucker, A. W.) 315317 (Princeton University Press, 1953).<\/p>\n<p>                    Google Scholar                <\/p>\n<p>Lundberg, S. M. & Lee, S. A unified approach to interpreting model predictions. Adv. Neural Inf. Process. Syst. 30, 47654774 (2017).<\/p>\n<p>                    Google Scholar                <\/p>\n<p>trumbelj, E. & Kononenko, I. An efficient explanation of individual classifications using game theory. J. Mach. Learn. Res. 11, 118 <a href=\"http:\/\/dl.acm.org\/citation.cfm?id=1756006.1756007\" rel=\"nofollow\">http:\/\/dl.acm.org\/citation.cfm?id=1756006.1756007<\/a> (2010).<\/p>\n<p>Gan, G., Ma, C. & Wu, J. Data clustering: Theory, algorithms, and applications. ASA-SIAM Ser. Stat. Appl. Math. <a href=\"https:\/\/doi.org\/10.1137\/1.9780898718348\" rel=\"nofollow\">https:\/\/doi.org\/10.1137\/1.9780898718348<\/a> (2007).<\/p>\n<p>Article    MATH                        Google Scholar                <\/p>\n<p>Riechert, S. E. & Hammerstein, P. Game theory in the ecological context. Ann. Rev. Ecol. Syst. 14, 377409. <a href=\"https:\/\/doi.org\/10.1146\/annurev.es.14.110183.002113\" rel=\"nofollow\">https:\/\/doi.org\/10.1146\/annurev.es.14.110183.002113<\/a> (1983).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Maynard-Smith, J. Evolution and the Theory of Games (Cambridge University Press, 1982).<\/p>\n<p>Book                        Google Scholar                <\/p>\n<p>Nowak, M. A. & Sigmund, K. Evolutionary dynamics of biological games. Science 303(5659), 793799. <a href=\"https:\/\/doi.org\/10.1126\/science.1093411\" rel=\"nofollow\">https:\/\/doi.org\/10.1126\/science.1093411<\/a> (2004).<\/p>\n<p>ADS    CAS    Article    PubMed                        Google Scholar                <\/p>\n<p>Maloney, K. O., Schmid, M. & Weller, D. E. Applying additive modelling and gradient boosting to assess the effects of watershed and reach characteristics on riverine assemblages. Methods Ecol. Evol. 3, 116128. <a href=\"https:\/\/doi.org\/10.1111\/j.2041-210X.2011.00124.x\" rel=\"nofollow\">https:\/\/doi.org\/10.1111\/j.2041-210X.2011.00124.x<\/a> (2012).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p>Cao, H., Recknagel, F. & Orr, P. T. Parameter optimization algorithms for evolving rule models applied to freshwater ecosystems. IEEE Trans. Evol. Comput. 18, 793806. <a href=\"https:\/\/doi.org\/10.1109\/TEVC.2013.2286404\" rel=\"nofollow\">https:\/\/doi.org\/10.1109\/TEVC.2013.2286404<\/a> (2014).<\/p>\n<p>Article                        Google Scholar                <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Visit link:<br \/>\n<a target=\"_blank\" href=\"https:\/\/www.nature.com\/articles\/s41598-022-20604-x\" title=\"Predicting the effects of winter water warming in artificial lakes on zooplankton and its environment using combined machine learning models |...\" rel=\"noopener\">Predicting the effects of winter water warming in artificial lakes on zooplankton and its environment using combined machine learning models |...<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Murphy, G. 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