The modern distribution of chironomid sub-fossils (Insecta: Diptera) in the Sierra Nevada, California: Potential for paleoclimatic reconstructions

Surface lake sediment was recovered from 57 lakes along an elevation gradient in the central, eastern Sierra Nevada of California. The surface sediment was analysed for subfossil chironomid remains in order to assess the modern distribution of chironomids in the region. The lakes sampled for the calibration dataset were between 2.0 and 40.0 m in depth, spanned an altitudinal gradient of 1360 m and a surface water temperature gradient of approximately 14 °C. Redundancy analysis (RDA) identified that five of the measured environmental variables – surface water temperature, elevation, depth, strontium, particulate organic carbon – accounted for a statistically significant amount of the variance in chironomid community composition. Quantitative transfer functions, based on weighted-averaging (WA), partial least squares (PLS) and weighted-averaging partial least squares (WA-PLS), were developed to estimate surface water temperature from the chironomid assemblages. The best model was a WA model with classical deshrinking, which had a relatively high coefficient of determination (r² = 0.73), low root mean square error of prediction (RMSEP = 1.2 °C) and a low maximum bias (0.90 °C). The results from this study suggest that robust quantitative estimates of past surface water temperature can be derived from the application of these models to fossil chironomid assemblages preserved in late-Quaternary lake sediment in this region.     

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-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-salinity relationships in 111 lakes from the Interior Plateau of British Columbia,Canada: the development of diatom-based models for paleosalinity reconstructions

Diatoms were identified and enumerated from the surface sediments of 111 lakes, 45 from the Kamloops region and 66 from the Cariboo/Chilcotin region, located on the southern Interior Plateau of British Columbia, Canada. This paper is an extension of another study which investigated the relationship of diatoms to salinity and ionic composition in 65 lakes from the Cariboo/Chilcotin region. The 111 lakes spanned a large gradient in salinity, ranging from fresh through hypersaline (late-summer salinity values ranged from 0.04 to 369 g l^–1), and included both carbonate- and sulphate-dominated lakes with sodium and magnesium as the dominant cations. The Kamloops region had more sulphate-dominated, hypersaline lakes and fewer carbonate-rich lakes than the Cariboo/Chilcotin region. Most lakes had higher salinities in the late-summer compared to the spring.Both salinity and brine-type were important variables that could explain the different diatom assemblages present in the lakes. The majority of diatom taxa had salinity optima in the freshwater to subsaline range (<3 g l^–1), and the taxa displayed a range of both narrow and broad tolerances along the salinity gradient. Weighted-averaging regression and calibration, and maximum likelihood techniques were used to develop salinity inference models from the diatom assemblages based on their relationship to the spring, late-summer and average lakewater salinity measurements. Simple weighted-averaging (WA) models generally produced the same or lower bootstrapped RMSEs of prediction than weighted-averaging with tolerance downweighting (WA(tol)) in the two regional and the combined datasets. Weighted averaging partial least squares (WA-PLS) showed little or no improvement in the predictive abilities of the datasets, as judged by the jackknifed RMSE of prediction. In all cases, the combined dataset of 102 lakes performed better than either of the smaller regional datasets, with relatively little difference between spring, average and late-summer salinity models. The maximum likelihood models gave lower apparent RMSEs of prediction in comparison to other methods; however, independent validation of this technique using methods such as bootstrapping were not undertaken because of the computer intensive nature of such analyses. These diatom-based salinity models are now available for reconstructing salinity and climatic trends from appropriately chosen closed-basin lakes in the Interior region of British Columbia.This is the second in a series of papers published in this issue on the paleolimnology of arid regions. These papers were presented at the Sixth International Palaeolimnology Symposium held 19–21 April, 1993 at the Australian National University, Canberra, Australia. Dr A. R. Chivas served as guest editor for these papers.     

A weighted-averaging regression and calibration model for inferring lakewater salinity from fossil diatom assemblages in saline lakes of the Vestfold Hills: a new tool for interpreting Holocene lake histories in Antarctica

The relationship between surface sediment diatom assemblages and measured limnological variables in thirty-three coastal Antarctic lakes from the Vestfold Hills was examined by constructing a diatom-water chemistry dataset. Previous analysis of this dataset by canonical correspondence analysis revealed that salinity accounted for a significant amount of the variation in the distribution of the diatom assemblages. Weighted-averaging regression and calibration of this diatom-salinity relationship was used to establish a transfer function for the reconstruction of past lakewater salinity from fossil diatom assemblages. Weighted-averaging regression and calibration with classical deshrinking provided the best model for salinity reconstructions and this was applied to the fossil diatom assemblages from one of the saline lakes in the Vestfold Hills in order to assess its potential for palaeosalinity and palaeoclimate reconstruction.     

Distribution of diatoms among intermittent ponds on the Atlantic Coastal Plain: development of a model to preduct drought periodicity from surface-sediment assemblages

Inferences of past climate from the fossil record in lakes rely on the accurate quantification of a relationship of fossilizing organisms to their environment. Whereas the relationship of diatoms to water chemistry parameters has been modeled in many systems, few studies adequately address the relationship of diatoms to physical properties, such as water depth or hydrology, that may be more directly tied to climate. We examined the composition of modern diatoms in surface sediments of 75 isolated ponds (mostly Carolina bays) of the Atlantic Coastal Plain to: (1) assess the influence of physical and chemical variables on the distribution of diatoms among ponds of the region, and (2) develop a model that predicts hydroperiod (a measure of pond permanence) from diatom assemblages. We constructed two hydroperiod calibration models: the first infers hydroperiod from the weighted-average optima and tolerances of taxa along the hydroperiod gradient, the second bases inferences on the hydroperiod estimates of compositionally similar samples. Both approaches incorporate a-priori and post-hoc tests of assumptions often inherent in the construction of transfer functions. Diatom assemblage composition had strong, approximately linear relationships to hydroperiod, water depth, and calcium concentration in non-metric multidimensional ordination space; effects of other variables, including pH, were non-linear or ambiguous. Overall, the assemblages reflected the dilute, acidic chemical characteristics of bays. The assemblages contained differing abundances of euterrestrial, benthic and planktonic taxa, depending on a pond's susceptibility to drying. A weighted-averaging regression model based on taxon-specific hydroperiod optima generated adequate, unbiased hydroperiod inferences from diatom species composition (r² = 0.81). This model may be used to infer past drought episodes from fossil diatom assemblages at appropriate sites on the Atlantic Coastal Plain.     

Assessment of freshwater diatoms as quantitative indicators of past climatic change in the Yukon and Northwest Territories,Canada

We identified, enumerated, and interpreted the diatom assemblages preserved in the surface sediments of 59 lakes located between Whitehorse in the Yukon and Tuktoyaktuk in the Northwest Territories (Canada). The lakes are distributed along a latitudinal gradient that includes several ecoclimatic zones. It also spans large gradients in limnological variables. Thus, the study lakes are ideal for environmental calibration of modern diatom assemblages. Canonical correspondence analysis, with forward selection and Monte Carlo permutation tests, showed that maximum lake depth and summer surface-water temperature were the two environmental variables that accounted for most of the variance in the diatom data. The concentrations of sodium and calcium were also important explanatory variables. Using weighted-averaging regression and calibration techniques, we developed a predictive statistical model to infer lake surface-water temperature, and we evaluated the feasibility of using diatoms as paleoclimate proxies. This model may be used to derive paleotemperature inferences from fossil diatom assemblages at appropriate sites in the western Canadian Arctic.     

Calibration of diatoms along a nutrient gradient in Florida Everglades Water Conservation Area-2A, USA

The relationship between diatom taxa preserved in surface soils and environmental variables at 31 sites in Water Conservation Area 2A (WCA-2A) of the Florida Everglades was explored using multivariate analyses. Surface soils were collected along a phosphorus (P) gradient and analyzed for diatoms, total P, % nitrogen (N), %carbon (C), calcium (Ca), and biogenic silica (BSi). Phosphorus varied from 315-1781 g g^-1, and was not found to be correlated with the other geochemical variables. Canonical correspondence analysis (CCA) was used to examine which environmental variables correlated most closely with the distributions in diatom taxa. Canonical correspondence analysis with forward selection, constrained and partial CCA, and Monte Carlo permutation tests of significance show the most significant changes in diatom assemblages along the P gradient (p < 0.01), with additional species differences correlated with soil C, N, Ca, and BSi.Weighted-averaging (WA) regression and calibration models of diatom assemblages to P and BSi were developed. The diatom-based inference model for soil [P] had a high apparent r² (0.86) with RMSE_boot = 218 g g^-1. Indicator diatom species identified by assessing species WA optima and WA tolerance to [P], such as Nitzschia amphibia and N. palea for high [P] (~1300-1400 g^-1) and Achnanthes minutissima var. scotica and Mastogloia smithii for low [P] (~400-600 g g^-1), may be useful as monitoring tools for eutrophication in WCA-2A as well as other areas of the Everglades. Diatom assemblages analyzed by cluster analysis were related to location within WCA-2A, and dominant taxa within clusters are discussed in relation to the geochemical variables measured as well as hydrology and pH. Diversity of diatom assemblages and a Disturbance Index based on diatom data are discussed in relation to the historically P-limited Everglades ecosystem. Diatom assemblages should be very useful for reconstructions of [P] through time in the Florida Everglades, provided diatoms are well preserved in soil cores.     

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-based water chemistry reconstructions from northern Sweden: a comparison of reconstruction techniques

The diatom composition in surface sediments from 119 northern Swedish lakes was studied to examine the relationship with lake-water pH, alkalinity, and colour. Diatom-based predictive models, using weighted-averaging (WA) regression and calibration, partial least squares (PLS) regression and calibration, and weighted-averaging partial least squares (WA-PLS) regression and calibration, were developed for inferences of water chemistry conditions. The non-linear response between the diatom assemblages and pH and alkalinity was best modelled by weighted-averaging methods. The lowest prediction error for pH was obtained using weighted averaging, with or without tolerance downweighting. For alkalinity there was still some information in the residual structure after extracting the first weighted-averaging component, which resulted in a slight improvement of predictions when using a two component WA-PLS model. The best colour predictions were obtained using a two component PLS model. Principal component analysis (PCA) of the prediction errors, with some characteristics of the training set included as passive variables, was performed to compare the results for the different alkalinity predictive models. The results indicate that calibration techniques utilizing more than one component (PLS and WA-PLS) can improve the predictions for lakes with diatom taxa that have broad tolerances. Furthermore, we show that WA-PLS performs best compared with the other techniques for those lakes that have a high relative abundance of the most dominant taxa and a corresponding low sample heterogeneity.     

An expanded weighted-averaging model for inferring past total phosphorus concentrations from diatom assemblages in eutrophic British Columbia (Canada) lakes

Eighteen lakes were added to a published training set of 46 British Columbia (BC) lakes in order to expand the original range of total phosphorus (TP) concentrations. Canonical correspondence analysis (CCA) was used to analyze the relationship between diatom assemblages and environmental variables. Specific conductivity and [TP] each explained significant (P0.05) directions of variance in the distribution of the diatoms. The relationship between diatom assemblages and [TP] was sufficiently strong to warrant the development of a weighted-averaging (WA) regression and calibration model that can be used to infer past trophic status from fossil diatom assemblages.The relationship between observed and inferred [TP] was not improved by the addition of more eutrophic lakes, however the [TP] range and the number of taxa used in the transfer function are now superior to the original model. Diatom species assemblages changed very little in lakes with TP concentrations greater than 85 µg 1^–1, so we document the development of a model containing lakes with TP85 µg 1^–1. The updated model uses 59 training lakes and covers a range of species optima from 6 to 41.9 µg 1^–1 TP, and a total of 150 diatom taxa.The updated inference model provided a more realistic reconstruction of the anthropogenic history of a highly eutrophic BC lake. The model can now be used to infer past nutrient conditions in other BC lakes in order to assess changes in trophic status.     

Relationship between diatoms and water quality (TN, TP) in sub-tropical east Australian estuaries

Nutrient over-enrichment of estuarine environments is increasing globally. However, it is difficult to determine the eutrophication trend in estuaries over long periods of time because long-term monitoring records are scarce and do not permit the identification of baseline environmental conditions. In this study, preliminary diatom based transfer functions for the inference of total phosphorus (TP) and total nitrogen (TN) in east-Australian sub-tropical estuaries were developed to address the deficiency in knowledge relating to historical estuary water quality trends. The transfer functions were created from a calibration set consisting of water quality and associated surface sediment diatom assemblage data from fifty-two sub-tropical estuaries in New South Wales and Queensland, Australia. Following data screening processes, Canonical Correspondence Analysis confirmed that TP and TN both explained significant, independent variation in the diatom assemblages. Variance partitioning, however, indicated that the TP was confounded with and may receive some strength from TN. WA and WA-PLS 2 component models for TP that included all calibration set sites yielded statistically weak results based on the jack-knifed r ² scores $ \left( {r_{\text{jack}}^{{^{ 2} }} \, = 0.22\;{\text{and}}\;0. 2 2 {\text{ respectively}}} \right) $ . Removal from the calibration set of 12 sites that had all PO₄, NH₄, NO₂, and NO_x concentrations below detection limit resulted in a substantial improvement in WA-PLS 2 component TP model scores $ \left( {r_{\text{jack}}^{{^{ 2} }} \; = \;\,0.69} \right) $ , indicating that this model is statistically robust, and thus suitable for down core nutrient reconstructions. Caution, however, is required when developing diatom based inference models in Australian estuaries as nutrient cycling processes may have the potential to influence diatom based transfer functions. The model reported on here provides a foundation for reconstructing nutrient histories in eastern Australian sub-tropical estuaries in the absence of monitoring data.     

Factors affecting diatom distribution in floodplain lakes of the southeast Murray Basin,Australia and implications for palaeolimnological studies

Diatom assemblages of surface sediments in 46 billabongs from four river floodplains in the southeast Murray-Darling Basin, Australia were sampled to investigate drivers of species distribution. The principal purpose of the study was to derive information to aid interpretation of diatom-based palaeoecological studies of these systems and of floodplain lakes more generally. Patterns in billabong diatom assemblages in relation to river reach, hydrology and farming intensity on surrounding land were examined, as were correlations with water quality variables. Seasonal variation in billabong water quality was high relative to spatial variation, and spatial patterns in billabong water quality were weak. In contrast, strong patterns were evident in diatom assemblages. Three main patterns were observed: (1) a distinction between billabongs dominated by planktonic diatoms from those dominated by benthic and attached forms; (2) differences in diatom assemblages in billabongs on different river reaches; and (3) differences in assemblages in billabongs with different hydrology. Of all water quality variables tested, total phosphorus (TP), total nitrogen (TN) and pH exerted the strongest independent influence on diatom distribution; however, only TP remained an important variable when species variation due to river reach, hydrology, and aquatic plant cover was taken into account. The weak influence of water quality on diatom distribution is interpreted as reflecting the dichotomy between plankton and non-plankton-dominated billabongs, the influence of hydrology and biogeography, the lack of strong spatial water quality gradients and the high degree of temporal variability in water quality. The findings show that diatom records from billabong sediments can provide evidence of long-term changes in the abundance of aquatic macrophytes and hydrology. They also suggest that merging calibration data sets across regions for the purpose of improving diatom transfer functions for water quality reconstruction is of limited value for floodplain lakes, and that performance is more likely to be gained by boosting site numbers within regions.     

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.     

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.     

Diatom-based inference models and reconstructions revisited: methods and transformations

Different calibration methods and data manipulations are being employed for quantitative paleoenvironmental reconstructions, but are rarely compared using the same data. Here, we compare several diatom-based models [weighted averaging (WA), weighted averaging with tolerance-downweighting (WAT), weighted averaging partial least squares, artificial neural networks (ANN) and Gaussian logit regression (GLR)] in different situations of data manipulation. We tested whether log-transformation of environmental gradients and square-root transformation of species data improved the predictive abilities and the reconstruction capabilities of the different calibration methods and discussed them in regard to species response models along environmental gradients. Using a calibration data set from New England, we showed that all methods adequately modelled the variables pH, alkalinity and total phosphorus (TP), as indicated by similar root mean square errors of prediction. However, WAT had lower performance statistics than simple WA and showed some unusual values in reconstruction, but setting a minimum tolerance for the modern species, such as available in the new computer program C² version 1.4, resolved these problems. Validation with the instrumental record from Walden Pond (Massachusetts, USA) showed that WA and WAT reconstructed most closely pH and that GLR reconstructions showed the best agreement with measured alkalinity, whereas ANN and GLR models were superior in reconstructing the secondary gradient variable TP. Log-transformation of environmental gradients improved model performance for alkalinity, but not much for TP. While square-root transformation of species data improved the performance of the ANN models, they did not affect the WA models. Untransformed species data resulted in better accordance of the TP inferences with the instrumental record using WA, indicating that, in some cases, ecological information encoded in the modern and fossil species data might be lost by square-root transformation. Thus it may be useful to consider different species data transformations for different environmental reconstructions. This study showed that the tested methods are equally suitable for the reconstruction of parameters that mainly control the diatom assemblages, but that ANN and GLR may be superior in modelling a secondary gradient variable. For example, ANN and GLR may be advantageous for modelling lake nutrient levels in North America, where TP gradients are relatively short.     

A caveat regarding diatom-inferred nitrogen concentrations in oligotrophic lakes

Atmospheric deposition of reactive nitrogen (Nr) has enriched oligotrophic lakes with nitrogen (N) in many regions of the world and elicited dramatic changes in diatom community structure. The lakewater concentrations of nitrate that cause these community changes remain unclear, raising interest in the development of diatom-based transfer functions to infer nitrate. We developed a diatom calibration set using surface sediment samples from 46 high-elevation lakes across the Rocky Mountains of the western US, a region spanning an N deposition gradient from very low to moderate levels (<1 to 3.2 kg Nr ha⁻¹ year⁻¹ in wet deposition). Out of the fourteen measured environmental variables for these 46 lakes, ordination analysis identified that nitrate, specific conductance, total phosphorus, and hypolimnetic water temperature were related to diatom distributions. A transfer function was developed for nitrate and applied to a sedimentary diatom profile from Heart Lake in the central Rockies. The model coefficient of determination (bootstrapping validation) of 0.61 suggested potential for diatom-inferred reconstructions of lakewater nitrate concentrations over time, but a comparison of observed versus diatom-inferred nitrate values revealed the poor performance of this model at low nitrate concentrations. Resource physiology experiments revealed that nitrogen requirements of two key taxa were opposite to nitrate optima defined in the transfer function. Our data set reveals two underlying ecological constraints that impede the development of nitrate transfer functions in oligotrophic lakes: (1) even in lakes with nitrate concentrations below quantification (<1 μg L⁻¹), diatom assemblages were already dominated by species indicative of moderate N enrichment; (2) N-limited oligotrophic lakes switch to P limitation after receiving only modest inputs of reactive N, shifting the controls on diatom species changes along the length of the nitrate gradient. These constraints suggest that quantitative inferences of nitrate from diatom assemblages will likely require experimental approaches.     

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     

A comparison of three Eurasian chironomid–climate calibration datasets on a W–E continentality gradient and the implications for quantitative temperature reconstructions

Multiple regional chironomid–climate calibration datasets are available to reconstruct quantitatively July air temperatures from fossil chironomid assemblages. We examined the relationship between July air temperature and the 40 most common chironomid taxa in three independent Eurasian calibration (training) sets. The estimated temperature optimum of each chironomid taxon is systematically lower (by ~1–2 °C) in a Norwegian calibration set compared to Finnish and Russian calibration sets. This result might partly be explained by the fact that the Norwegian calibration set extends further at the cold end of the temperature gradient. A difference in continentality between the Russian sites and the European sites might also contribute to this pattern. The number of taxa that show a statistically significant unimodal response to temperature is higher in the Norwegian calibration set (34 out of 40 taxa) compared to the modern Finnish (11 of 37 taxa; 3 common taxa absent) and the Russian calibration set (20 of 40 taxa), probably due to the longer temperature gradient incorporated in the Norwegian calibration set. We applied all three calibration sets to fossil chironomid assemblages from the high-latitude study site of Sokli (northeast Finland), a site with a unique series of lacustrine deposits covering (amongst others) the Holocene, part of early MIS 3 (at ~53 ka) and MIS 5d–c (at ~110–95 ka) and with independent proxy-records for comparison. In the early Holocene and during MIS 5c, the chironomid-based temperature inferences from all three inference models had similar values. Temperature reconstructions based on the Norwegian calibration set are 2–4 °C lower for the late Holocene, early MIS 3 and MIS 5d than the inferred temperatures based on the other calibration sets. Although the lakes included in the Finnish calibration set are located closest to the site of Sokli, evaluation tests and a comparison with independent proxy data suggests that the Norwegian calibration set provides the most suitable analogues for reconstruction purposes for most of the fossil assemblages. Our results imply that when choosing a calibration set for quantitative climate reconstructions on glacial timescales, regional proximity of the fossil site may not be a sufficient basis, and the length of the temperature gradient of the calibration dataset and factors such as the continentality gradient covered by the calibration set must also be considered.