{"refrec":{"BRefID":287928,"RR":"<b>Brey, T.</b> (2010). An empirical model for estimating aquatic invertebrate respiration. <i>Methods Ecol. Evol. 1(1)</i>: 92-101. <a href=\"https://dx.doi.org/10.1111/j.2041-210x.2009.00008.x\" target=\"_blank\">https://dx.doi.org/10.1111/j.2041-210x.2009.00008.x</a>","BEntID":279953,"PublicFlag":1,"CheckedFlag":1,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Methods Ecol. Evol. 1(1)</i>: 92-101. <a href=\"https://dx.doi.org/10.1111/j.2041-210x.2009.00008.x\" target=\"_blank\">https://dx.doi.org/10.1111/j.2041-210x.2009.00008.x</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Brey, T.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Brey, T.","Englishabstract":"1. The role of metazoan respiration in aquatic system energetics has been neglected to some extent, particularly because limited resources hamper the simultaneous determination of individual respiration rates across many taxa. As global warming will affect poikilotherm metabolism on an ecosystem scale, we need versatile models to estimate respiration from 'easy-to-obtain' parameters. 2. Artificial neural networks were trained to estimate mass specific respiration of aquatic metazoans from 28 parameters: temperature, water depth, 19 taxon categories, body mass and 6 lifestyle parameters. The data base includes 22 920 data sets referring to 915 taxa (836 identified to species, 67 to genus, 12 to higher taxon) from 452 different sources. 3. Overall model fit is good (R-2 = 0.847), but there is considerable residual variability of up to two orders of magnitude. 4. Variability of same species measurements between sources is almost as large as same-source variability between species, i.e. a substantial part of the residual variability in the data may represent methodical bias. 5. There are no universally valid scaling factors in the relationships of respiration to body mass and temperature, but a wide range of species-specific factors. 6. 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