Journal
JOURNAL OF PHYCOLOGY
Volume 38, Issue 1, Pages 66-82Publisher
WILEY-BLACKWELL
DOI: 10.1046/j.1529-8817.2002.01056.x
Keywords
biodiversity; calibration data set; canonical correspondence analysis; dissolved organic carbon; inference models; littoral diatoms; total nitrogen; total phosphorus; weighted averaging
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We explored statistical relationships between the composition of littoral diatom assemblages and 21 chemical and physical environmental variables in 69 lakes and 15 river sites in the lowland of northeastern Germany. Canonical correspondence analysis with single treatment and with forward selection of environmental variables was used to detect 11 important ecological variables (dissolved inorganic carbon [DIC], Na+, total phosphorus [TP], dissolved organic carbon [DOC], total nitrogen [TN], pH, oxygen saturation, dissolved iron, SO42-, NH4+, soluble reactive silicium) and maximum water depth or Ca2+ or soluble reactive phosphorus that most independently explain major proportions of the total diatom variance among the habitats. Monte Carlo permutation tests showed that each contributed a significant additional proportion (P < 0.05) of the variance in species composition. Together, these 11 most important environmental variables explained 34% of the total variance in species composition among the sites and captured 73% of the explained variance from the full 21 parameters model. Weighted-averaging regression and calibration of 304 indicator taxa with tolerance down-weighting and classic deshrinking was used to develop transfer functions between littoral diatoms and DIC, pH, TP, TN, and Cl-. The DOC:TP ratio was introduced and a weighted-averaging model was developed to infer allochthonous DOC effects in freshwater ecosystems. This diatom-DOC/TP model was significant (P < 0.001) and explained 7.6% of the total diatom variance among the sites, surpassing the inferential power of the diatom-TP-transfer function (7.3% explained variance). The root-mean-square errors of prediction of the models were estimated by jack-knifing and were comparable with published data sets from surface sediment diatom samples. The data set of littoral diatoms and environmental variables allows use of the diatom-environmental transfer functions in biomonitoring and paleolimnological approaches across a broad array of natural water resources (such as floodplains, flushed lakes, estuaries, shallow lakes) in the central European lowland ecoregion.
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