Search

Aim (1) To resolve theoretical debates regarding the role of environment versus dispersal limitation, the conservatism of niches across distances and the prevalence of environmental specialists in diatom communities. (2) To provide guidance on the use of diatom communities and other microbial analogues to analyse ecological response to environmental change. Location Eight hundred and ninety-one lakes in five regional datasets from north-western Europe and four regional datasets from north-eastern North America. Methods Lacustrine diatom communities were analysed at three scales: inter-continental, intra-continental and regional. Nested partial redundancy analyses (RDAs) were used to determine spatial versus environmental components of community variation. Weighted-averaging (WA) regression and calibration, as well as logistic and quadratic regressions, were used to detect niche conservatism and the prevalence of environmental specialists. Results Community patterns indicate that dispersal limitation acts predominantly at the inter-continental scale, while at the regional (less than c. 1,000,000 km2) scale, a single environmental variable (pH) explains more than five times the community variation as spatial (dispersal-related) variables. In addition, pH niche components appear to be conserved at the inter-continental scale, and environmental specialization does not impose relative rarity, as specialists apparently readily disperse to suitable environments. Main conclusions Analysis at multiple scales is clearly important in determining the influences of community variation. For diatom communities, dispersal limitation acts most strongly at the broadest scales, giving way to environment at the scales considered by most analyses. The availability of a wide variety of propagules with consistent niches across regions indicates that diatom communities reflect the succession of taxa according to local environmental conditions, rather than disequilibrium with the environment or adaptation of local populations. While multi-scale analyses must be undertaken for other groups to resolve debates over community drivers and determine appropriate scales for prediction, for diatoms (and probably other microbial communities), responses to environmental change can be inferred using analogue datasets from large geographic areas. [ABSTRACT FROM AUTHOR]

The relationships between diatom assemblages and important limnological variables were investigated in 494 lakes from northeastern North America (Pennsylvania, USA, to Nova Scotia, Canada). The limnological variable most significantly related to diatom assemblages was lake water pH, although dissolved organic carbon and nutrients were also important. Based on these strong relationships, highly significant diatom-based inference models were developed to reconstruct key limnological variables based on diatom assemblages using weighted averaging (WA), maximum likelihood (ML), and modern analogs technique (MAT). The performances of the pH-inference models were high, similar, and significant (WA: r2boot = 0.89, root mean squared error of prediction (RMSEP) = 0.43; ML: r2boot = 0.89, RMSEP = 0.45; MAT: r2boot = 0.89, RMSEP = 0.46). In addition, distribution of sites along a pH gradient did not have the anticipated bias, especially with respect to the WA model, although an evenly distributed study set did result in slightly less noise. While some regionally specific information may be lost by utilizing a large number of lakes from a wide geographic area, the broad limnological gradients allow a more realistic, accurate, and complete description of the ecological characteristics of diatom species. In addition to providing new autecological data on diatoms for northeastern North America, these inference models can now be used to infer accurately and precisely lake water pH and associated variables for limnologists and lake managers. [ABSTRACT FROM AUTHOR]

The relationship between 23 scaled chrysophyte taxa (Chrysophyceae and Synurophyceae) and measured limnolgoical variables in 62 Adirondack, New York, drainage lakes were examined by canonical correspondence analysis (CCA). The major proportion of variation in chrysophyte species distributions was strongly related to total monomeric Al (Al[SUBm]) and Mg concentrations, and their close correlates pH, Na, Ca, and acid-neutralizing capacity (ANC). Total monomeric Al concentrations explain a greater proportion of species variation than pH, suggesting that al[SUBm] concentrations may be more important in governing the distribution of chrysophyte laxa in these lakes. Gaussian logit (GL) and linear logit (LL) regressions of the relative percentages of individual chrysophyte taxa to lakewater pH and Al[SUBm] concentrations and the examination of pH-Al[SUBm] response surfaces show that many chrysophyte taxa exhibit unique responses to these environmental gradients; taxa can be characterized as alkaline, circumneutral, acidic, and pH indifferent. Within each of these groups, taxa can be characterized further based upon their optima and tolerances to Al[SUBm] concentrations.Chrysophyte indicator species (i.e. a taxon with a strong statistical relationship to the environmental variables of interest, a well-defined optimum, and a narrow tolerance to the variable of interest) for pH include Mallomonas hindonii, M. crassisquama, M. pseudocoronata, and Synura uvella; M. hindonii, M. crassiquama, M. pseudocoronata, S. petersenii, and S. Spinosa are good indicators of Al[SUBm] concentrations. Highly significant predictive models were developed to infer lakewater pH and Al[SUBm] concentrations from the relative percentages of chrysophyte scales in the study lakes. Model evaluation was based on th eir correlation coefficients and the root-mean-squared error of predictions (RMSE) derived from bootstrapping. Weighted averaging regression and calibration with tolerance downweighting (i.e. weighting taxa inversely to their variance) produced superior results when compared to the computationally and data-demanding maximum likelihood methods and to simple weighted average regression and calibration. [ABSTRACT FROM AUTHOR]