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.     

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.     

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 northwest North American training set: distribution of freshwater midges in relation to air temperature and lake depth

Freshwater midges, consisting of Chironomidae, Chaoboridae and Ceratopogonidae, were assessed as a biological proxy for palaeoclimate in eastern Beringia. The northwest North American training set consists of midge assemblages and data for 17 environmental variables collected from 145 lakes in Alaska, British Columbia, Yukon, Northwest Territories, and the Canadian Arctic Islands. Canonical correspondence analyses (CCA) revealed that mean July air temperature, lake depth, arctic tundra vegetation, alpine tundra vegetation, pH, dissolved organic carbon, lichen woodland vegetation and surface area contributed significantly to explaining midge distribution. Weighted averaging partial least squares (WA-PLS) was used to develop midge inference models for mean July air temperature (r _boot² = 0.818, RMSEP = 1.46°C), and transformed depth (ln (x+1); r _boot² = 0.38, and RMSEP = 0.58).     

Modern influences on chironomid distribution in western Ireland: potential for palaeoenvironmental reconstruction

Ireland provides a unique setting for the study of past climates, as its climate is dominated by westerly airflow from the North Atlantic and readily responsive to changes in North Atlantic circulation patterns. Although there has been substantial research on Ireland’s past environments, quantitative palaeolimnological research, especially chironomid-based research, has been lacking. In order to further develop chironomid-based palaeolimnological investigations, a calibration set was constructed to determine the dominant environmental controls on modern chironomids in western Ireland. Chironomid subfossils were collected from surface sediments of 50 lakes. The lakes were characterised with 36 environmental variables, including physical attributes, lake water characteristics, lake sediment characteristics and land cover within each catchment. In this exploratory study, no specific environmental variable was targeted and lakes were chosen to span gradients of latitude, elevation, depth and trophic status. Redundancy analysis showed that six environmental variables—mean July air temperature, lake depth, dissolved organic carbon, and percentage catchment land cover of agriculture, peat bog and scrubland—captured a large and statistically significant portion of the variance in the chironomid data. July temperature and agricultural land cover were the most dominant environmental variables, with July temperature proving the most suitable for inference model development. A classical weighted-averaging model was developed to estimate July air temperature, with a coefficient of determination (r _jack ² ) of 0.60 and root mean square error of prediction (RMSEP) of 0.57 °C. Results suggest that summer temperature is the dominant influence on chironomid distribution across a wide variety of lake types, and the relatively small RMSEP should allow for more accurate reconstructions of Ireland’s relatively subdued Holocene temperature fluctuations.     

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-inference models for surface-water temperature and salinity developed from a 57-lake calibration set from the Sierra Nevada, California, USA

Physical, chemical, and biological data were collected from a suite of 57 lakes that span an elevational gradient of 1360 m (2115 to 3475 m a.s.l.) in the eastern Sierra Nevada, California, USA as part of a multiproxy study aimed at developing transfer functions from which to infer past drought events. Multivariate statistical techniques, including canonical correspondence analysis (CCA), were used to determine the main environmental variables influencing diatom distributions in the study lakes. Lakewater depth, surface-water temperature, salinity, total Kjeldahl nitrogen, and total phosphorus were important variables in explaining variance in the diatom distributions. Weighted-averaging (WA) and weighted-averaging partial least squares (WA-PLS) were used to develop diatom-based surface-water temperature and salinity inference models. The two best diatom-inference models for surface-water temperature were developed using simple WA and inverse deshrinking. One model covered a larger surface-water temperature gradient (13.7 °C) and performed slightly poorer (r² = 0.72, RMSE = 1.4 °C, RMSEP_jack = 2.1 °C) than a second model, which covered a smaller gradient (9.5 °C) and performed slightly better (r² = 0.89, RMSE = 0.7 °C, RMSEP_jack = 1.5 °C). The best diatom-inference model for salinity was developed using WA-PLS with three components (r² = 0.96, RMSE = 4.06 mg L^–1, RMSEP_jack = 11.13 mg L^–1). These are presently the only diatom-based inference models for surface-water temperature and salinity developed for the southwestern United States. Application of these models to fossil-diatom assemblages preserved in Sierra Nevada lake sediments offers great potential for reconstructing a high-resolution time-series of Holocene and late Pleistocene climate and drought for California.     

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.     

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.     

Development of a diatom-based model for inferring total phosphorus in southeastern Australian water storages

Diatom-based transfer functions for inferring epilimnetic total phosphorus (TP) have been developed from a data set of 33 southeastern Australian water storages. Regular institutional monitoring of these sites has allowed comparison of models developed from TP data covering different time periods. A model based on mean annual TP performs better than models derived from winter maximum TP, spring minimum TP or TP nearest the time of diatom sampling. A mean annual TP model (WA-PLS 2 component) has a jack-knifed diatom-inferred versus measured TP correlation coefficient (r ² _jack) of 0.69 and a root-mean-square-error of prediction (RMSEP) of 0.246 log₁₀g TP l^–1, while alternative models have RMSEP > 0.27. Deletion of two samples with uncharacteristic species composition and environmental conditions improved performance of the mean annual TP model (r ² _jack= 0.74; RMSEP = 0.233 log₁₀g TP l^–1). Comparison with other published diatom-TP calibration models indicates that this model performs relatively well, with possible contributing factors including the extensive characterisation of TP (with an average 15 determinations making up the annual mean) and the dominance of planktonic diatoms in most sites. Downcore application of the model will allow the reconstruction of reservoir nutrient histories since commissioning, and thus provide a basis for understanding and management of reservoirs.     

Fourier-transform Infrared Spectroscopy (FTIRS), a New Method to Infer Past Changes in Tree-line Position and TOC using Lake Sediment

This study tests the hypothesis that Fourier-transform infrared spectroscopy (FTIRS) of lake sediments can be used to infer past changes in tree-line position and total organic carbon (TOC) content of lake water. A training set of 100 lakes from northern Sweden spanning a broad altitudinal and TOC gradient from 0.7 to 14.9 mg/l was used to assess whether vegetation zones and TOC can be modelled from FTIR spectra of surface sediments (0–1 cm) using principal component analysis (PCA) and partial least squares (PLS) regression. Preliminary results show that FTIRS of lake sediments can be used to reconstruct past changes in tree line and the TOC content of lake water, which is hardly surprising since FTIRS registers the properties of organic and minerogenic material derived from the water mass and the drainage area. The FTIRS model for TOC gives a root mean squared error (RMSECV) of calibration of 1.4 mg/l (10% of the gradient) assessed by internal cross-validation (CV) yielding an R_cv² of 0.64. This should be compared with a near-infrared spectroscopy (NIRS) and diatom transfer function for TOC from the same set of lakes, which have a R_cv² of 0.61 and 0.31, and RMSECV of 1.6 and 2.3 mg/l, respectively. The FTIRS-TOC model was applied to a Holocene sediment core from a tree-line lake and the results show similar trends as inferences from NIRS and pollen from the same core. Overall, the results indicate that changes in FTIR spectra from lake sediments reflect differences in catchment vegetation and TOC, and that FTIRS-models based on surface-sediment samples can be applied to sediment cores for retrospective analysis.     

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.     

Surface-sediment and epilithic diatom pH calibration sets for remote European mountain lakes (AL:PE Project) and their comparison with the Surface Waters Acidification Programme (SWAP) calibration set

A modern diatom-pH calibration data-set consisting of surface-sediment diatom assemblages from 118 lakes and 530 taxa is presented. The AL:PE data-set is from high-altitude or high-latitude lakes in the Alps, Norway, Svalbard, Kola Peninsula, UK, Slovenia, Slovakia, Poland, Portugal, and Spain (pH range = 4.5-8.0; DOC range = 0.2-3.2 mg l^-1). In addition, 92 epilithon samples from 22 high-altitude or high-latitude lakes comprise an AL:PE epilithon diatom-pH data-set. Weighted averaging partial least squares regression is used to develop pH-inference models. The AL:PE data-set has a root-mean-square-error of prediction (RMSEP) of 0.33 and a maximum bias of 0.36 pH units and r² of 0.82, as assessed by leave-one-out cross-validation. The epilithon data-set has, after data-screening and the deletion of one very obvious outlier, a RMSEP of 0.23 and a maximum bias of 0.18 pH units and r² of 0.88. The 167 sample SWAP diatom-pH data-set from lowland or upland lakes in the UK, Norway, and Sweden has a RMSEP of 0.29 and a maximum bias of 0.23 pH units and r² of 0.86.The pH optima, as estimated by weighted averaging and Gaussian regression, are compared for the three data-sets (AL:PE, SWAP, AL:PE epilithon). There is a good correspondence between the AL:PE and the AL:PE epilithon optima, but a consistent bias between the AL:PE and SWAP optima, with the SWAP optima being lower than the AL:PE estimates.The predictive performances of the AL:PE and SWAP calibration data-sets are compared using independent test samples and six core sequences, all from high-altitude lakes, one in south-east Siberia and five in eastern Scotland. The results show the importance of using the AL:PE data-set for inferring lake-water pH from diatom assemblages in high-altitude or high latitude lakes with low DOC concentrations.     

Response of diatom community in Lugu Lake (Yunnan–Guizhou Plateau,China) to climate change over the past century

A mean annual temperature increase has been recorded on the Yunnan–Guizhou Plateau of China during the last century. This temperature increase has been significantly greater since the 1950s. Thus, paleolimnological analyses may be utilized to better understand ecological responses to recent changing climate over decadal to centennial timescales, especially in regions with sparse lake monitoring data. Here, we present paleolimnological results from a ²¹⁰Pb/¹³⁷Cs-dated sediment core spanning approximately the last ~250 years from a remote, alpine, semi-closed oligotrophic lake (Lugu Lake) on the northwestern Yunnan–Guizhou Plateau. Sediment profiles of diatoms, geochemical variables (LOI₅₅₀, TOC and C/N) and median grain size were analyzed and compared with the climate data (1951 AD–2010 AD) from the Lijiang weather station. Endogenous productivity of Lugu Lake has increased gradually over the last 30 years. The majority of diatom taxa encountered in the core are typical of alkaline oligotrophic lakes. Diatom assemblages were dominated by Cyclostephanos dubius, Cyclotella taxa, and fragilarioid taxa. Diatom species composition has changed significantly with three assemblage shifts at different scales over the ~250-year period. Diatom species diversity reveals a distinct increase before ~1970 AD, followed by a decline. In addition, a decreasing trend in diatom cell-size was consistent with recent warming trends. Redundancy analysis (RDA) shows that regional air temperature trends (annual, spring, summer, and winter) have played a significant role (p < 0.05) in determining diatom compositional changes over the past six decades. Results of this study suggest that regional warming is the main driving force behind recent changes in diatom composition at Lugu Lake, while nutrients may also have impact on the diatom change in recent 10 years.     

Diatom-inference models for acid neutralizing capacity and nitrate based on 41 calibration lakes in the Sierra Nevada, California, USA

We investigated relationships among modern diatom species composition and physical and chemical characteristics of high-elevation lakes of the Sierra Nevada (California), to develop transfer functions that can be used to infer historic lake conditions. Data were collected from 50 lakes in National Parks and Forests of the central and southern Sierra Nevada. Multivariate statistical methods revealed that acid neutralizing capacity (ANC) and nitrate accounted for significant variation in diatom taxa. A training set with 242 modern diatom taxa from a subset of 41 lakes was used to develop transfer functions for ANC and nitrate using weighted averaging techniques. ANC and nitrate calibration ranges were 23.0–137 μEq/L and 0.18–9.5 μM, respectively. Coefficients of determination for the models were: ANC: R² = 0.76, and R _jackknife ²  = 0.44; NO₃: R² = 0.67, and R _jackknife ²  = 0.27. The ANC model was applied to the top 50 cm of sediments in Moat Lake to reconstruct ANC from ca. AD 350 to 2005. The reconstruction suggests that ANC declined by about 40 % (101–60 μEq/L) between the 1920s and the 1960s and then recovered to pre-1920s levels during 1980–2000. The magnitude of this ANC excursion was the largest observed during the past 1,600 years. We hypothesize that temporal variations in ANC were influenced by: (1) changes in rates of acid deposition, especially nitric acid and (2) variations in the timing and magnitude of snowmelt runoff.     

Diatom-based transfer functions for western Quebec lakes (Abitibiand Haute Mauricie): the possible role of epilimnetic CO2 concentration in influencing diatom assemblages

Surficial sediments from 76 lakes from two western Quebec regions(Abitibi and Haute Mauricie) were sampled to identify the relationships betweendiatoms and environmental variables. Because the two regions containedradically different diatom communities, we then investigated which factors maybe responsible for the large community discrepancies in the two nearbygeographical areas. Standard lake chemistry variables showed little differencesbetween the regions, although epilimnetic light regimes were slightly lower inAbitibi. Nevertheless, lakes of the two regions with similar light regimes andchemistry still showed a clear separation in their diatoms, implying that otherimportant factors are influencing assemblages. We found that the calculatedconcentration of CO₂ in the open water can explain some of thediscrepancy in diatom assemblages. A pCCA constrained to the concentration ofCO₂ with alkalinity and pH as covariables explained 12.5% of speciesvariance and was significant. Given the lack of a relationship between DOC andCO₂, and because the lakes are heavily supersaturated withCO₂ in the calibration set, lake-to-lake variations inCO₂ concentrations are likely due to groundwater inputs; thepossibility that this environmental variable may be influencing diatomcommunities might allow, in some cases, the reconstruction of historicalchanges in groundwater inputs to lakes. Finally, new calibration models werebuilt in Quebec by using weighted averaging partial least square(WA-PLS) techniques in order to infer pH, CO₂, TP, TN, and, DOC fromdiatom assemblages preserved in the surface sediments.     

Tracking Holocene environmental changes in an alpine lake sediment core: application of regional diatom calibration, geochemistry, and pollen

Diatom abundances in the surface sediment samples of 41 mountain lakes in the central Austrian Alps (Niedere Tauern) were related to environmental variables using multi-variate techniques. Canonical correspondence analysis (CCA) revealed that the pH, date of autumn mixing (A _mix), mean August water temperature (T _Aug), dissolved organic carbon (DOC), and relative water depth (Z _rel) made significant contributions to explain the diatom assemblage variation in the lakes of the training set. A weighted averaging partial least square regression and calibration model was used to establish Di-pH (R ² _boot= 0.72, RMSEP_boot= 0.131), and a thermistor measurements-based PLS model for A _mix (R ² _boot= 0.71, RMSEP_boot= 0.006 log₁₀ Julian days). The latter showed a better prediction than T _Aug, and was used in terms of climate change. These transfer functions, together with analyses of loss on ignition (LOI), the total carbon/nitrogen (C/N)-ratios, and selected pollen, were applied to an early to mid-Holocene (11.5–4 cal. ky BP) sediment core section from an Austrian Alpine treeline lake on crystalline bedrock. Additionally, passive sample scores in the CCA of the diatom training set were used to show trends in the variables DOC and Z _rel. During the early Holocene, diatoms indicative of increased pH, extended warm summers, and low water levels dominated. Between 10.2 and 7.6 cal. ky BP it was followed by diatom assemblages that indicated an increase in lake water depth and an earlier A _mix. The multi-proxy data suggest that the A _mix decline is the result of a series of snow-rich summer cool and wet climate fluctuations, which were divided by climate warming at ∼9 cal. ky BP. Increased A _mix, LOI and DOC, and the correspondent decline in the C/N-ratios, show subsequent climate warming between 7.3 and 6 cal. ky BP. The long-term trend in Di-pH indicates the impact of catchment-related processes during the early-Holocene, that were superimposed by climate.     

A high resolution multi-proxy record of pronounced recent environmental change at Baker Lake,Nunavut

Arctic aquatic systems are considered to be especially sensitive to anthropogenic disturbance, which can have cascading effects on biological communities as aquatic food-web structure is altered. Bio-indicators that respond to major limnological changes can be used to detect and infer major environmental change, such as climate warming, with the use of paleolimnological techniques. A multi-proxy approach was used to quantify recent environmental changes at Baker Lake, Nunavut, Arctic Canada. Analyses of fossilized remains of chironomids and diatoms were conducted on a sediment core of 20 cm in length sampled at 0.5-cm intervals. A new surface sediment training set of subfossil chironomid assemblages from 65 lakes across the eastern Canadian Arctic generated a robust (r _jack² = 0.79) surface water paleotemperature transfer function. The transfer function was applied to stratigraphic intervals from the Baker Lake sediment core to generate a paleotemperature reconstruction of sub-decadal resolution. The surface water temperature reconstruction inferred a 2°C increase in mid-summer surface water temperature for Baker Lake over the last 60 years, which was corroborated by the local instrumental record spanning the period of 1950–2007 AD. The chironomid record shows a recent decline of several cold-water taxa and appearance of warm-water indicators. This shift in community structure began circa 1906 AD, and intensified after 1940 AD. The corresponding fossil diatom record showed an increase in small planktonic Cyclotella taxa over the past 60 years, intensifying in the last 5 years, which also suggests a warmer climate and longer ice-free periods. The shifts in the diatom assemblages began later than the shifts in the chironomid assemblages, and were of lower magnitude, reflecting differences in the mechanisms in which these two indicators respond to environmental change.     

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).     

The importance of model choice on pH inferences from scaled chrysophyte assemblages in North America

The selection of a reliable inference model is a crucial step in developing ecologically sound reconstructions of environmental variables in the past. We compared intra- and inter-regional regression-based models, and an inter-regional Modern Analogue Technique (MAT) model in their ability to infer lakewater pH from scaled chrysophyte assemblages. The performance of each model was assessed by examining cross-validated coefficients of determination and prediction errors, and through reconstructing the pH of 50 modern and fossil samples in south-central Ontario, Canada. Using the intra- and inter-regional data sets, we found little difference in the ability of the regression-based models to infer present-day pH. Partial Least Squares (PLS) regression, Weighted Averaging (WA), and Weighted Averaging Partial Least Squares (WA-PLS) inference models showed similar values for jack-knifed coefficients of determination (r² _jack), root mean squared errors of prediction (RMSEP_jack), and mean and maximum biases. Based on an analogue matching approach, the inferred values from 48 fossil sediment samples suggested that the intra-regional model did not provide reliable reconstructions for approximately half of the fossil samples. However, inferences from the inter-regional MAT and regression-based models were found to have appropriate analogues and thus considered to be more reliable.