RELATIONSHIPS BETWEEN LITTORAL DIATOMS AND THEIR CHEMICAL ENVIRONMENT IN NORTHEASTERN GERMAN LAKES AND RIVERS¹

Abstract

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.

Spatial distribution of benthic algae in the Gangqu River, Shangrila, China

“…Major nutrients [i.e., nitrogen (N) and phosphorus (P)] concentration of surface waters was a primary factor contributing to variation in benthic-algal assemblages (Leland and Porter 2000). These results were similar to the studies of Christie and Smol (1993) and Schönfelder et al (2002), and they also demonstrated that TN and TP were two of the important ecological variables that explained significant (P \ 0.05) directions of variance in the distribution of benthic-algal taxa. TDS was another significant variable affecting the spatial pattern of benthic algae, which was negatively correlated with the third CCA axis (r = -0.509, P = 0.002).…”

Seasonal and interannual dynamics of diatom assemblages in Sacrower See (NE Germany): a sediment trap study

“…This suggests that on short time scales the response of diatom communities to seasonal temperature variations may be more prominent than the forcing by mean annual temperatures. Other studies focused on the annual succession of diatoms in dimictic lowland lakes (Raubitschek et al, 1999;Schönfelder et al, 2002;Köster & Pienitz, 2006). These studies demonstrate that the seasonal succession of diatoms differs among lakes depending on factors, such as stratification, temperature, nutrients, pH, oxygen saturation, dissolved iron and calcium, maximum water depth, and dissolved organic carbon.…”

Spatial and temporal patterns of benthic diatom flora in Lake Stechlin, Germany

“…Scheffler and Schönfelder (2004) reported the microflora of Lake Stechlin and their list contains the species number of benthic diatoms. Schönfelder et al (2002) estimated the relationship between littoral diatom composition and environmental factors in northeastern German lakes including Lake Stechlin. In addition, Stechlin is included in the Water Framework Directive monitoring program of Brandenburg and related reports define reference conditions by means of analysis of diatoms (Schönfelder, 2002;Schönfelder et al, 2005).…”

“…Schönfelder et al (2002) estimated the relationship between littoral diatom composition and environmental factors in northeastern German lakes including Lake Stechlin. In addition, Stechlin is included in the Water Framework Directive monitoring program of Brandenburg and related reports define reference conditions by means of analysis of diatoms (Schönfelder, 2002;Schönfelder et al, 2005). However, international publications concerning diversity and spatial and temporal distribution of benthic diatoms are lacking.…”