Diatoms as indicators of climatic and limnological change in Swedish Lapland: a 100-lake calibration set and its validation for paleoecological reconstructions

This study investigated the distribution of subfossil diatom assemblages in surficial sediments of 100 lakes along steep ecological and climatic gradients in northernmost Sweden (Abisko region, 67.07° N to 68.48° N latitude, 17.67° E to 23.52° E longitude) to develop and cross-validate transfer functions for paleoenvironmental reconstruction. Of 19 environmental variables determined for each site, 15 were included in the statistical analysis. Lake-water pH (8.0%), sedimentary loss-on-ignition (LOI, 5.9% and estimated mean July air temperature (July T, 4.8%) explained the greatest amounts of variation in the distribution of diatom taxa among the 100 lakes. Temperature and pH optima and tolerances were calculated for abundant taxa. Transfer functions, based on WA-PLS (weighted averaging partial least squares), were developed for pH (r² = 0.77, root-mean-square-error of prediction (RMSEP) = 0.19 pH units, maximum bias = 0.31, as assessed by leave-one-out cross-validation) based on 99 lakes and for July T (r² = 0.75, RMSEP = 0.96 °C, max. bias = 1.37 °C) based on the full 100 lake set. We subsequently assessed the ability of the diatom transfer functions to estimate lake-water pH and July T using a form of independent cross-validation. To do this, the 100-lake set was divided in two subsets. An 85-lake training-set (based on single limnological measurements) was used to develop transfer functions with similar performance as those based on the full 100 lakes, and a 15-lake test-set (with 2 years of monthly limnological measurements throughout the ice-free seasons) was used to test the transfer functions developed from the 85-lake training-set. Results from the intra-set cross-validation exercise demonstrated that lake-specific prediction errors (RMSEP) for the 15-lake test-set corresponded closely with the median measured values (pH) and the estimations based on spatial interpolations of data from weather stations (July T). The prediction errors associated with diatom inferences were usually within the range of seasonal and interannual variability. Overall, our results confirm that diatoms can provide reliable and robust estimates of lake-water pH and July T, that WA-PLS is a robust calibration method and that long-term environmental data are needed for further improvement of paleolimnological transfer functions.     

A diatom-conductivity transfer function for Spanish salt lakes

Diatom-salinity transfer functions for interpretation of palaeosalinity and palaeoclimate change have been developed successfully for parts of North America and North and East Africa, but there is a need for data-sets in other saline lake regions of the world. A data-set of 74 modern diatom samples and associated water chemistry data is described from Spain. The influence of conductivity and other environmental variables on diatom distribution is explored using canonical correspondence analysis (CCA) and partial CCAs. A transfer function is derived for conductivity (70 samples) whose apparent predictive ability is high (apparent r² = 0.91). Performance under jackknifing is poor due to the heterogeneous nature of the data-set and poor coverage of the freshwater end of the salinity gradient. There is a lack of suitable low-salinity sites in Spain, and the accuracy of estimated salinity optima and tolerance ranges may be improved by merging this data-set with those of other regions. The Spanish transfer function has strong affinities with the African data-set and contributes important ecological data for diatom taxa which are absent or poorly represented in the modern flora of African lakes, and for which, in fossil material, there were previously no good modern analogues.     

Diatom-based total phosphorus (TP) and pH transfer functions for the Irish Ecoregion

A 72-lake diatom training set was developed for the Irish Ecoregion to examine the response of surface sediment diatom assemblages to measured environmental variables. A variety of multivariate data analyses was used to investigate environmental and biological data structure and their inter-relationships. Of the variables used in determining a typology for lakes in the Irish Ecoregion, alkalinity was the only one found to have a significant effect on diatom assemblages. A total of 602 diatom taxa were identified, with 233 recorded at three or more sites with abundances ≥1%. Generally diatom data displayed a high degree of heterogeneity at the species level and non-linear ecological responses. Both pH and total phosphorus (TP) (in the ranges of 5.1–8.5 and 4.0–142.3 μg l⁻¹ respectively) were shown to be the most significant variables in determining the surface sediment diatom assemblages. The calibration models for pH and TP were developed using the weighted averaging (WA) method; data manipulation showed strong influences on model performances. The optima WA models based on 70 lakes produced a jack-knifed coefficient of determination (r ² _jack) of 0.89 with a root mean squared error (RMSEP) of 0.32 for pH and r ² _jack of 0.74 and RMSEP of 0.21 (log₁₀ μg l⁻¹) for TP. Both models showed strong performances in comparison with existing models for Ireland and elsewhere. Application of the pH and TP transfer functions developed here will enable the generation of quantitative water quality data from the expanding number of palaeolimnological records available for the Irish Ecoregion, and thus facilitate the use of palaeolimnological approaches in the reconstruction of past lake water quality, ecological assessment and restoration.     

Diatom assemblages from Adirondack lakes (New York,USA) and the development of inference models for retrospective environmental assessment

Detrended canonical coreespondence analysis (DCCA) was used to examine the relationships between diatom species distributions and environmental variables from 62 drainage lakes in the Adirondack region, New York (USA). The contribution of lakewater pH, Al_m (monomeric Al), NH₄, maximum depth, Mg, and DOC (dissolved organic carbon) were statistically significant in explaining the patterns of variation in the diatom species composition. Twenty-three and sixteen diatom taxa were identified as potential indicator species for pH and Al_m, respectively (i.e. a taxon with a strong statistical relationship to the environmental variable of interest, a well defined optimum, and a narrow tolerance to the variable of interest). Using weighted-averaging regression and calibration, predictive models were developed to infer lakewater pH (r ²=0.91), Al_m (r ²=0.83), DOC (dissolved organic carbon) (r ²=0.64), and ANC (acid neutralizing capacity; r ²=0.90). These variables are of key importance in understanding watershed acidification processes. These predictive models have been used in the PIRLA-II (Paleoecological Investigation of Recent Lake Acidification-II) project to answer policy-related questions concerning acidification, recovery, and fisheries loss.     

Diatom-environmental relationships in 64 alkaline southeastern Ontario (Canada) lakes: a diatom-based model for water quality reconstructions

Lake eutrophication is a problem in many areas of Ontario, although the history of nutrient enrichment is poorly documented. The aim of this study was to construct a diatom-based transfer function to infer past phosphorus levels in Ontario lakes using paleolimnological analyses. The relationship between diatom assemblages and limnological conditions was explored from a survey of diatoms preserved in the surface sediments of 64 Southern Ontario lakes, spanning a total phosphorus gradient of 0.004 to 0.054 mg L^-1. Over 420 diatom taxa were identified, 98 of which were sufficiently common to be considered in statistical analyses. Canonical correspondence analysis (CCA) determined that pH, ammonium, aluminum, spring total phosphorus (TP), strontium, total nitrogen (TN), maximum depth (MaxZ), chlorophyll a (Chla) and mean depth were significant variables in explaining the variance in the diatom species data. The environmental optima of common diatom taxa for the limnologically important variables (TP, pH, TN, MaxZ, Chla) were calculated using weighted averaging (WA) regression and calibration techniques, and transfer functions were generated. The diatom inference model for spring TP provided a robust reconstructive relationship (r² = 0.637; RMSE = 0.007 mg L^-1; r² _boot = 0.466; RMSE_boot = 0.010 mg L^-1). Other variables, including pH (r² = 0.702; RMSE = 0.208; r² _boot = 0.485; RMSE_boot = 0.234), TN (r² = 0.574; RMSE = 0.0899 mg L^-1; r² _boot = 0.380; RMSE_boot = 0.127 mg L^-1) and MaxZ (r² = 0.554; RMSE = 1.05 m; r² _boot = 0.380; RMSE_boot = 1.490 m), were also strong, indicating that they may also be reconstructed from fossil diatom communities. This study shows that it is possible to reliably infer lakewater TP and other limnological variables in alkaline Southern Ontario lakes using the WA technique. This method has the potential to aid rehabilitation programs, as it can provide water quality managers with the means to estimate pre-enrichment phosphorus concentrations and an indication of the onset and development of nutrient enrichment in a lake.     

Water-chemistry transfer functions for epiphytic diatoms in standing freshwaters and a comparison with models based on littoral sediment assemblages (Flanders, Belgium)

Quantitative inference models for water-chemistry variables are derived from epiphytic diatom assemblages in 186 lentic and mostly shallow freshwaters in lower Belgium (Flanders). When the complete pH range is considered (pH 3.4–9.3), robust transfer functions are obtained for median pH (jack-knifed r ² = 0.88, RMSEP = 0.38 pH units or 6.4% of the observed range) and dissolved inorganic carbon concentration (jack-knifed r ² = 0.86, RMSEP = 0.194 log₁₀ mg DIC l⁻¹ or 10.2% of the observed range) by means of weighted-averaging partial least squares regression (WA-PLS). For these variables, the calibration models are as reliable as those based on sedimentary diatom assemblages. Inferences of pH may be improved by combining estimates from epiphytic and sediment assemblages. In circumneutral and alkaline conditions, WA-PLS calibration of maximum or median total phosphorus is possible (log-transformed; jack-knifed r ² = 0.64 or 0.66 and RMSEP = 14% or 12.3% of the observed range, respectively). It makes little difference if taxa showing no response to TP are taken into consideration or not. These models considerably expand the prospects of using historical herbarium materials to hindcast environmental conditions and also allow more accurate interpretation of current compositional changes in epiphytic communities. Compared to littoral sediment assemblages, fewer water-column variables can be inferred reliably from epiphyton. This probably results from differences between the effective gradients in both habitats, together with lower in situ species diversity and less effective spatial integration (i.e. lower recruitment of phytoplankton) in the epiphyton. A comparison of the HOF response-model types and WA-optima of diatom taxa for epiphytic and sediment assemblages shows that the relationship to individual variables, and in particular to those related to trophic status, may differ with habitat. Thus, the combination of samples from both habitat types in the same calibration model is not recommended. Electronic Supplementary Material Supplementary material is available and is accessible for authorised users in the online version of this article at     

Spatial variability of diatom assemblages in surface lake sediments and its implications for transfer functions

The variability of diatom species composition in lake surface sediments was studied along transects in four lakes in northeastern Germany. Three dimictic lakes (Dudinghausener See, Tiefer See, and Cambser See) and one shallow lake (Groß Peetscher See) were sampled. Large differences in diatom composition were found between adjoined samples from different depths within one lake. These differences were mainly displayed by planktonic species. For example, the relative frequency of Stephanodiscus alpinus varied between 4% and 43% within the surface sediment samples of the open-water region of Dudinghausener See. Using transfer functions for total phosphorus (TP) based on the European Diatom data-base (EDDI) combined TP data-set and a local data-set, the inferred TP values differed strongly within one lake when using Weighted Averaging-Partial Least Squares (WA-PLS) regression. In Tiefer See (average of measured TP: 30 μg l^?1), the inferred TP values range from 45 to 110 μg l^?1 using the transfer function based on WA-PLS regression and the EDDI data-set; and from 16 to 100 μg l^?1 using WA-PLS and a local data-set. Performing Maximum Likelihood (ML) regression reduced the difference between measured and inferred values. For Tiefer See, the inferred TP values range between 16 and 45 μg l^?1 using ML regression and the local data-set. Therefore, it seems that ML regression can deal better with the natural variability in species composition than WA-PLS regression. In general, it was shown that by using ML regression and the local data-set, the error of the inferred values was significant lower for all lakes than using WA-PLS regression and the EDDI data-set. The Root Mean Square Error of Prediction (RMSEP) was not useful in selecting the most stable transfer function.     

An ostracod-conductivity transfer function for Tibetan lakes

About 145 freshwater to hypersaline lakes of the eastern Tibetan Plateau were investigated to develop a transfer function for quantitative palaeoenvironmental reconstructions using ostracods. A total of 100 lakes provided sufficient numbers of ostracod shells. Multivariate statistical techniques were used to analyse the influence of a number of environmental variables on the distributions of surface sediment ostracod assemblages. Of 23 variables determined for each site, 19 were included in the statistical analysis. Lake water electrical conductivity (8.2%), Ca% (7.6%) and Fe% (4.8%, ion concentrations as % of the cations) explained the greatest amounts of variation in the distribution of ostracod taxa among the 100 lakes. Electrical conductivity optima and tolerances were calculated for abundant taxa. A transfer function, based on weighted averaging partial least squares regression (WA-PLS), was developed for electrical conductivity (r ² = 0.71, root-mean-square-error of prediction [RMSEP] = 0.35 [12.4% of gradient length], maximum bias = 0.64 [22.4% of gradient length], as assessed by leave-one-out cross-validation) based on 96 lakes. Our results show that ostracods provide reliable estimates of electrical conductivity and can be used for quantitative palaeoenvironmental reconstructions similarly to more commonly used diatom, chironomid or pollen data.     

Paleolimnological evidence of the consequences of recent increased dissolved organic carbon (DOC) in lakes of the northeastern USA

As a result of reductions in sulfate deposition and changing climate, dissolved organic carbon (DOC) concentrations have increased in many lakes situated in forests of northeastern North America and northern Europe since the 1990s. Although this increase is well documented, the associated ecological implications remain unclear. In particular, DOC strongly influences the vertical temperature structure of lakes, with increasing DOC often leading to a shallower epilimnion. We investigated the effect of increased DOC concentrations on lake thermal structure using fossil diatom records from six remote Maine lakes. Sedimentary diatom profiles from three pairs of small (<0.5 km²) lakes were compared, with each pair containing one lake with a documented significant increase in DOC and the other experiencing no change in DOC since the early 1990s. Lake thermal structure was inferred from changes in the relative abundance of Discostella stelligera and Aulacoseira species, two diatom taxa that are associated with changes in thermal stratification. The three lakes without increasing DOC showed no change in diatom-inferred mixing depth over the past few decades. Of the lakes with documented increases in DOC, two showed the highest turnover in diatom community structure over time. Profiles from both of these lakes also indicated directional change in diatom-inferred mixing depth over the past 20 years, but the direction of change differed. This study demonstrates that recent increases in DOC have the potential to alter the physical and biological structure of lakes, but that these responses may differ across lakes.     

Diatom-based models for reconstructing past water quality and productivity in New Zealand lakes

The trophic status of lakes in New Zealand is, on average, low compared to more densely populated areas of the globe. Despite this, trends of eutrophication are currently widespread due to recent intensification in agriculture. In order to better identify baseline productivity and establish long-term trends in lake trophic status, diatom-based transfer functions for productivity-related parameters were developed. Water quality data and surface sediment diatom assemblages from 53 lakes across the North and South Islands of New Zealand were analysed to determine species responses to the principal environmental gradients in the data set. Repeat sampling of water chemistry over a 12-month period enabled examination of species responses to annual means as well as means calculated for stratified and mixed periods. Variables found to be most strongly correlated with diatom species distributions were chlorophyll a (Chl a), total phosphorus (TP), dissolved reactive phosphorus (DRP), ionic concentration (measured as electrical conductivity (EC)) and pH. These variables were used to develop diatom-based transfer functions using weighted averaging regression and calibration (simple, tolerance down-weighted and with partial least squares algorithm applied). Overall, models derived for stratified means were weaker than those using annual or isothermal means. For specific variables, the models derived for the isothermal mean of EC (WA-tol r²_jack = 0.79; RMSEP = 0.15 log₁₀ S cm^–1),the annual mean of pH (WA r²_jack = 0.72; RMSEP = 0.25 pH units) and the isothermal mean of Chl a (WA r²_jack = 0.71; RMSEP = 0.18 log₁₀ mg m^–3 Chl a) performed best. The models derived for TP were weak in comparison (for the annual mean of TP: WA r²_jack = 0.50; RMSEP = 0.24 log₁₀ mg m^–3 TP) and residuals on estimates for this model were correlated with several other water quality variables, suggesting confounding of species responses to TP concentrations. The model derived for the isothermal mean of DRP was relatively strong (WA-tol r²_jack = 0.78; RMSEP = 0.17 log₁₀ mg m^–3 DRP); however, residual values for this model were also found to be strongly correlated with several other water quality variables. It is concluded that the poor performance of the TP and DRP transfer functions relative to that of the Chl a model reflects the coexistence of nitrogen and phosphorus limitation within the lakes in the data set. In spite of this, the suite of transfer functions developed from the training set is regarded as a valuable addition to palaeolimnological studies in NewZealand.     

Chironomid-inferred late-glacial and early-Holocene mean July air temperatures for Kråkenes Lake, western Norway

A chironomid data-set calibrated to July air temperatures, based on 44 lakes in western Norway, is used to reconstruct mean July air temperatures from late-glacial and early-Holocene fossil chironomid assemblages at Kråkenes Lake. The calibration function is based on Weighted Averaging Partial Least Squares regression and has a root mean square error of prediction (RMSEP) of 1.13 °C, a r² of 0.69, and a maximum bias of 2.66 °C. All these statistics are based on leave-one-out cross-validation. A calibration function based on summer surface-water temperatures has a poorer performance (RMSEP = 2.22 °C, r² = 0.30, maximum bias = 5.29 °C). The reconstructed July air temperatures at Kråkenes rise to 10.5 °C soon after deglaciation, are about 11.5 °C in the Allerød, decrease to 9.5-10 °C in the Younger Dryas, and rise rapidly within 15 yrs to 11.5 °C at the onset of the Holocene. There is a two-step rise to 13 °C or more in the early-Holocene. The likely over-estimation of Younger Dryas temperatures and under-estimation of early-Holocene temperatures probably result from the limited temperature range represented by the existing calibration set. The data set is currently being expanded to include lakes with warmer air temperatures (> 14 °C) and with colder air temperatures (< 8 °C).     

WA-PLS diatom-based pH, TP and DOC inference models from 42 lakes in the Abitibi clay belt area (Québec, Canada)

The relationship between surficial sediment diatom species and measured environmental variables was explored in lakes from the Abitibi region of western Quebec. Diatom assemblages in 42 lakes were identified and their relationship with measured environmental variables was examined using multivariate statistical methods. Canonical correspondence analysis with forward selection and Monte Carlo permutation tests revealed that the three environmental variables pH, TP and DOC each accounted for statistically significant fractions of the variation in diatom taxa. A training set with 164 modern diatom taxa was used to derive transfer functions for lake-water pH, TP and DOC using weighted-averaging-partial-least-squares (WA-PLS) techniques. The models were developed to infer lake water pH, TP and DOC within the ranges 4–8 for pH, 2.75–30.0 g l^–1 for TP, and 2.9–18.5 mg l^–1 for DOC. These quantitative inference models may now be used to help identify and estimate the effects of natural disturbances on the biogeochemistry of Abitibi lakes during their historical development.     

Diatom transfer-functions for quantifying past air temperature, pH and total organic carbon concentration from lakes in northern Sweden

The relationships between diatoms (Bacillariophyceae) in surface sediments of lakes and summer air temperature, pH and total organic carbon concentration (TOC) were explored along a steep climatic gradient in northern Sweden to provide a tool to infer past climate conditions from sediment cores. The study sites are in an area with low human impact and range from boreal forest to alpine tundra. Canonical correspondence analysis (CCA) constrained to mean July air temperature and pH clearly showed that diatom community composition was different between lakes situated in conifer-, mountain birch- and alpine-vegetation zones. As a consequence, diatoms and multivariate ordination methods can be used to infer past changes in treeline position and dominant forest type. Quantitative inference models were developed to estimate mean July air temperature, pH and TOC from sedimentary diatom assemblages using weighted averaging (WA) and weighted averaging partial least squares (WA-PLS) regression. Relationships between diatoms and mean July air temperature were independent of lake-water pH, TOC, alkalinity and maximum depth. The results demonstrated that diatoms in lake sediments can provide useful and independent quantitative information for estimating past changes in mean July air temperature (R² _jack = 0.62, RMSEP = 0.86 °C; R² and root mean squared error of prediction (RMSEP) based on jack-knifing), pH (R² _jack = 0.61, RMSEP = 0.30) and TOC (R² _jack = 0.49, RMSEP = 1.33 mg l^-1). The paper focuses mainly on the relationship between diatom community composition and mean July air temperature, but the relationships to pH and TOC are also discussed.     

Diatom-based conductivity and water-level inference models from eastern Tibetan (Qinghai-Xizang) Plateau lakes

Climate in central Asia is dominated by the Asian monsoon. The varying impact of the summer monsoon across the Tibetan (Qinghai-Xizang) Plateau provides a strong gradient in precipitation, resulting in lakes of different salinity. Diatoms have been shown to indicate changes in salinity. Thus, transfer functions for diatoms and salinity or related environmental variables represent an excellent tool for paleoclimatic reconstructions in the Tibetan Plateau. Forty freshwater to hypersaline lakes (salinity: 0.1 to 91.7 g l^–1) were investigated in the eastern Tibetan Plateau. The relationship between 120 diatom taxa and conductivity, maximum water depth and major ions were analyzed using an indicator value approach, ordination and taxon response models. Canonical correspondence analysis indicated that conductivity was the most important variable, accounting for 10.8% of the variance in the diatom assemblages. In addition water depth and weathering were influential. Weighted Averaging (WA) and Weighted Averaging Partial Least Square (WA-PLS) regression and calibration models were used to establish diatom-conductivity and water depth transfer functions. An optimal two-component WA-PLS model provided a high jack-knifed coefficient of prediction for conductivity (r² _jack = 0.92), with a moderate root mean squared error of prediction (RMSEP_jack = 0.22), a very low mean bias (0.0003), and a moderate maximum bias (0.26). A WA model with tolerance downweighting resulted in a slightly lower r² _jack (0.89) for water depth, with RMSEP_jack= 0.26, mean bias = –0.0103 and maximum bias = 0.26.     

Diatom and chrysophyte functions and inferences of post-industrial acidification and recent recovery trends in Killarney lakes (Ontario, Canada)

The surface sediment diatom and chrysophyte assemblages from 33 Sudbury lakes were added to our published 72 lake data set to expand and refine the diatom and chrysophyte-based inference models that we had earlier developed for this region. Our calibration data set now includes 105 lakes, representing gradients for multiple environmental variables (e.g., lakewater pH, metals, and transparency). The revised models are based on the weighted averaging calibration and regression approach and include bootstrap error estimates. The pH model was the strongest (r² _boot = 0.75, RMSE _boot = 0.50). The chrysophyte-inferred pH model (r² _boot = 0.79, RMSE _boot = 0.48) that we developed was as robust as the diatom pH model. Diatom and chrysophyte inferred pH models were then applied to top (surface sediments representing current conditions) and bottom (generally from > 30 cm deep representing pre-industrial conditions) sediment diatom and chrysophyte assemblages of 19 Killarney area lakes near Sudbury. The top and bottom inferred pH results were compared to early-1970s measured pH data. These data suggest that, although many of the poorly buffered Killarney lakes had experienced acidification, marked pH recovery has occurred in many lakes within the last 25 years. Despite the stunning pH recovery, the present-day diatom and chrysophyte assemblages are significantly different from assemblages present during pre-industrial times. Our results suggest that biological recovery may require more time than chemical recovery. It is also likely that these lakes may never recover biologically because other anthropogenic stressors (e.g., climate warming and increased exposure to UV-B radiation) may now have greater influence on biological communities in Killarney/Sudbury area lakes than acidification.     

A comparison between diatom-based pH inference models using Artificial Neural Networks (ANN), Weighted Averaging (WA) and Weighted Averaging Partial Least Squares (WA-PLS) regressions

We explored the possibility of using artificial neural networks (ANN) to develop quantitative inference models in paleolimnology. ANNs are dynamic computer systems able to learn the relations between input and output data. We developed ANN models to infer pH from fossil diatom assemblages using a calibration data set of 76 lakes in Quebec. We evaluated the predictive power of these models in comparison with the two most commonly methods used in paleolimnology: Weighted Averaging (WA) and Weighted Averaging Partial Least Squares (WA-PLS). Results show that the relationship between species assemblages and environmental variables of interest can be modelled by a 3-layer back-propagation network, with apparent R² and RMSE of 0.9 and 0.24 pH units, respectively. Leave-one-out cross-validation was used to access the reliabilities of the WA, WA-PLS and ANN models. Validation results show that the ANN model (R² _jackknife = 0.63, RMSE_jackknife = 0.45, mean bias = 0.14, maximum bias = 1.13) gives a better predictive power than the WA model (R² _jackknife = 0.56, RMSE_jackknife = 0.5, mean bias = –0.09, maximum bias = –1.07) or WA-PLS model (R² _jackknife = 0.58, RMSE_jackknife = 0.48, mean bias = –0.15, maximum bias = –1.08). We also evaluated whether the removal of certain taxa according to their tolerance changed the performance of the models. Overall, we found that the removal of taxa with high tolerances for pH improved the predictive power of WA-PLS models whereas the removal of low tolerance taxa lowered its performance. However, ANN models were generally much less affected by the removal of taxa of either low or high pH tolerance. Moreover, the best model was obtained by averaging the predictions of WA-PLS and ANN models. This implies that the two modelling approaches capture and extract complementary information from diatom assemblages. We suggest that future modelling efforts might achieve better results using analogous multi-model strategies.     

Estimation of pH optima and tolerances of diatoms in lake sediments by the methods of weighted averaging,least squares and maximum likelihood,and their use for the prediction of lake acidity

Ecological optima and tolerances with respect to autumn pH were estimated for 63 diatom taxa in 47 Finnish lakes. The methods used were weighted averaging (WA), least squares (LS) and maximum likelihood (ML), the two latter methods assuming the Gaussian response model.WA produces optimum estimates which are necessarily within the observed lake pH range, whereas there is no such restriction in ML and LS. When the most extreme estimates of ML and LS were excluded, a reasonably close agreement among the results of different estimation methods was observed. When the species with unrealistic optima were excluded, the tolerance estimates were also rather similar, although the ML estimates were systematically greater.The parameter estimates were used to predict the autumn pH of 34 other lakes by weighted averaging. The ML and LS estimates including the extreme optima produced inferior predictions. A good prediction was obtained, however, when prediction with these estimates was additionally scaled with inverse squared tolerances, or when the extreme values were removed (censored). Tolerance downweighting was perhaps more efficient, and when it was used, no additional improvement was gained by censoring. The WA estimates produced good predictions without any manipulations, but these predictions tended to be biased towards the centroid of the observed range of pH values.At best, the average bias in prediction, as measured by mean difference between predicted and observed pH, was 0.082 pH units and the standard deviation of the differences, measuring the average random prediction error, was 0.256 pH units.     

A diatom dataset and diatom-salinity inference model for southeast Australian estuaries and coastal lakes

To quantify the relationship between diatom species assemblages and the water chemistry of southeast Australian estuaries and coastal lakes, a new dataset of 81 modern diatom samples and water chemistry data was created. Three hundred and ninety-nine species from 53 genera were identified in 36 samples from 32 coastal water bodies in eastern Tasmania and 45 samples from 13 coastal water bodies in southern Victoria. Multivariate statistical analyses revealed that the sampling sites were primarily distributed along salinity and nutrient gradients, and that salinity, nitrate + nitrite, phosphate and turbidity explained independent portions of variance in the diatom data. Species salinity optima and tolerances were determined and a diatom-salinity inference model (WAinv r ² = 0.72, r ²jack = 0.58, RMSEP = 0.09 log ppt) was developed. This new information on diatom species’ salinity preferences provides a useful tool for quantitatively reconstructing salinity changes over time from diatom microfossils preserved in the sediments of a range of estuaries and coastal lakes in southeast Australia. This is valuable for studies investigating long-term human impacts and climate change in the region.     

Calibration of Littoral Diatoms to Water Chemistry in Standing Fresh Waters (Flanders, Lower Belgium): Inference Models for Historical Sediment Assemblages

Relationships between littoral surface-sediment diatom assemblages and ambient limnological conditions were examined in 186 lentic fresh waters throughout lower Belgium (Flanders). Most of these waters were small, unstratified, alkaline and rich in nutrients. Using weighted-averaging techniques, robust and accurate transfer functions were developed for median pH-values ranging from 3.4 to 9.3 and dissolved inorganic carbon concentrations from <1.6 to 63 mg l⁻¹ (jackknifed r ²≈ 0.87, RMSEP <10% of the observed range), while a less precise model was obtained for sodium (2–571 mg l⁻¹; jackknifed r ² 0.69, RMSEP 9.9% of the range). Restricting the data set to circumneutral and alkaline sites (pH≥6.5) revealed the importance of additional variables, including calcium, silica, chemical oxygen demand and potential gross oxygen production (a proxy for metabolic activity and phytoplankton abundance). Calibration models for these variables were strong enough to be useful (jackknifed r ² 0.57–0.59, RMSEP 13.1–16.4% of the observed range), although estimations should not always be considered entirely independent. Except for the predominant pH gradient, removal of all taxa with a distribution unrelated to the variable of interest improved model performance. In general, such taxa were proportionally represented among taxa classified according to their principal habitat. Application of the present models to diatom assemblages of shallow-water sediments obtained from historical samples and, most importantly, herbarium-macrophyte specimens, will improve hindsight into regional freshwater conditions and add to base-line setting of ecological quality standards in a highly impacted region. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

Modelling diatom responses to climate induced fluctuations in the moisture balance in continental Antarctic lakes

The water chemistry of lake systems on the edge of the Antarctic continent responds quickly to changes in the moisture balance. This is expressed as increasing salinity and decreasing lake water level during dry periods, and the opposite during wet periods. The diatom composition of the lakes also changes with these fluctuations in salinity and lake water depth. This is important, as their siliceous remains become incorporated into lake sediments and can provide long-term records of past salinity using transfer functions. In order to develop transfer functions, diatoms and water chemistry data were inter-calibrated from five different East Antarctic oases, namely the Larsemann Hills, the Bølingen Islands, the Vestfold Hills, the Rauer Islands and the Windmill Islands. Results indicate that salinity is the most important environmental variable explaining the variance in the diatom flora in East Antarctic lakes. In oligo- saline lakes the variance is mainly explained by lake water depth. This dataset was used to construct a weighted averaging transfer function for salinity in order to infer historical changes in the moisture balance. This model has a jack-knifed r² of 0.83 and a RMSEP of 0.31. The disadvantage of this transfer function is that salinity changes in oligo-saline lakes are reconstructed inaccurately due to the edge effect and due to the low species turnover along the salinity gradient at its lower end. In order to infer changes in the moisture balance in these lakes, a second transfer function using weighted averaging partial least squares (with two components) for depth was constructed. This model has a jack-knifed r² of 0.76 and a RMSEP of 0.22. Both transfer functions can be used to infer climate driven changes in the moisture balance in lake sediment cores from oligo-, hypo-, meso- and hyper-saline lakes in East Antarctic oases between 102–75°E. The transfer function for lake water depth is promising to track trends in the moisture balance of small freshwater lakes, where changes in shallow and deep-water sediments are readily reflected in changing diatom composition.