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.     

A diatom-based inference model for autumn epilimnetic total phosphorus concentration and its application to a presently eutrophic boreal lake

A diatom transfer function to infer epilimnetic total phosphorus (TP) concentration was derived using surface sediment diatom data from 68 medium-sized (10–1000 ha) lakes in Southern Finland. Publicly available monitoring records were used in lake selection to avoid gradients caused by pH and humic substances. Constrained and partially constrained ordinations indicated that TP was an important variable influencing diatom assemblages. A long floristic gradient in relation to TP was also apparent and therefore an inference model was developed for TP using unimodal-based regression and calibration methods. The final model included 61 lakes with epilimnetic TP concentrations between 3 and 89 g P l^–1, measured during the autumnal circulation period. It has a jackknifed-estimated root mean squared error of prediction of 0.16 log g P l^–1, a maximum bias of 0.28 log g P l^–1, and an r² _jack of 0.76.The model was tested in the presently eutrophic Lake Valkjärvi (epilimnetic [TP] 60–85 g P l^–1), located in Southern Finland. It successfully predicted the measured autumnal epilimnetic TP concentration for the past twenty years and the changes in inferred [TP] reflected disturbances known to have occurred before that time. The diatom-based inferences show that Lake Valkjärvi was oligo-mesotrophic as late as the 1930's and has become eutrophic because of nutrient inputs from agriculture and, especially, municipalities. However, epilimnetic TP concentration has not increased further.     

Modern diatom, cladocera, chironomid, and chrysophyte cyst assemblages as quantitative indicators for the reconstruction of past environmental conditions in the Alps. II. Nutrients

Surface sediments from 68 small lakes in the Alps and 9 well-dated sediment core samples that cover a gradient of total phosphorus (TP) concentrations of 6 to 520 g TP l^-1 were studied for diatom, chrysophyte cyst, cladocera, and chironomid assemblages. Inference models for mean circulation log₁₀ TP were developed for diatoms, chironomids, and benthic cladocera using weighted-averaging partial least squares. After screening for outliers, the final transfer functions have coefficients of determination (r², as assessed by cross-validation, of 0.79 (diatoms), 0.68 (chironomids), and 0.49 (benthic cladocera). Planktonic cladocera and chrysophytes show very weak relationships to TP and no TP inference models were developed for these biota. Diatoms showed the best relationship with TP, whereas the other biota all have large secondary gradients, suggesting that variables other than TP have a strong influence on their composition and abundance. Comparison with other diatom – TP inference models shows that our model has high predictive power and a low root mean squared error of prediction, as assessed by cross-validation.     

Relationships between environmental variables and zooplankton subfossils in the surface sediments of 36 shallow coastal brackish lakes with special emphasis on the role of fish

Subfossil zooplankton assemblages (Cladocera 22 taxa, Rotifera 1 taxon) were identified from the surface sediments of 36 shallow (median depth = 0.7 m) Danish coastal brackish lakes differing in epilimnic salinity (SAL, range 0.2–17.4), summer-mean total phosphorus (TP, 27–327 g l^–1) and total nitrogen (TN, 0.850–2.629 mg l^–1), as well as in submerged macrophyte coverage and planktivorous fish density (PL-CPUE). Cladoceran species richness declined significantly with increasing SAL, TP and TN, while no significant correlation was found to either PL-CPUE, macrophyte coverage or lake surface area. Bonferroni-adjusted forward selection within canonical correspondence analysis (CCA) showed that 22.1% of the variation in zooplankton data was explained by PL-CPUE, SAL and TP uniquely; each variable explaining an almost equally significant amount of variation in the zooplankton data. Predictive models to infer PL-CPUE, SAL and TP were developed using variance weighted-averaging (WA) procedures. Almost similar values of boot-strapped coefficient of determination (r²_{boot-strapped} 0.22–0.38) were produced by the WA inference models of PL-CPUE, SAL and TP, while the inference models of TP produced the lowest boot-strapped root-mean-squared-error of prediction (RMSEP_{boot-strapped} 0.29–0.36 log(TP + 1), g l^–1). Yet, zooplankton TP and SAL optima (WA) were strongly correlated (r² = 0.46), while PL-CPUE optima (WA) were independent of both TP and SAL optima, indicating that only the PL-CPUE inference models are suitable for making reconstructions.     

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.     

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     

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.     

New Zealand chironomids as proxies for human-induced and natural environmental change: Transfer functions for temperature and lake production (chlorophyll a)

The analysis of chironomid taxa and environmental datasets from 46 New Zealand lakes identified temperature (February mean air temperature) and lake production (chlorophyll a (Chl a)) as the main drivers of chironomid distribution. Temperature was the strongest driver of chironomid distribution and consequently produced the most robust inference models. We present two possible temperature transfer functions from this dataset. The most robust model (weighted averaging-partial least squares (WA-PLS), n = 36) was based on a dataset with the most productive (Chl a > 10 μg l⁻¹) lakes removed. This model produced a coefficient of determination () of 0.77, and a root mean squared error of prediction (RMSEP_jack) of 1.31°C. The Chl a transfer function (partial least squares (PLS), n = 37) was far less reliable, with an of 0.49 and an RMSEP_jack of 0.46 Log₁₀μg l⁻¹. Both of these transfer functions could be improved by a revision of the taxonomy for the New Zealand chironomid taxa, particularly the genus Chironomus. The Chironomus morphotype was common in high altitude, cool, oligotrophic lakes and lowland, warm, eutrophic lakes. This could reflect the widespread distribution of one eurythermic species, or the collective distribution of a number of different Chironomus species with more limited tolerances. The Chl a transfer function could also be improved by inputting mean Chl a values into the inference model rather than the spot measurements that were available for this study.     

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.     

Quantitative inferences of past hypolimnetic anoxia and nutrient levels from a Canadan Precambrian Shield lake

Paleolimnological analyses were used to infer limnological changes during the past ~ 300 yrs in the west basin of Peninsula Lake, a small (853 ha) Precambrian Shield lake in Ontario, Canada, that has been subjected to moderate cultural disturbances (forest clearance, cottage and resort development). This study represents a pioneering attempt to use sedimentary chironomid assemblages and weighted-averaging models to quantify past hypolimnetic anoxia (expressed as the anoxic factor, AF). Impacts of forest clearance and human land-use on deepwater oxygen availability and surface water quality were assessed by comparing chironomid-inferred AF and diatom-inferred total phosphorus concentration ([TP]) to changes in terrestrial pollen and historical data. This study also discusses the ability of chironomids to quantitatively infer changes in AF.Pre-disturbance chironomid assemblages were stable and dominated by taxa indicative of oxygen-rich hypolimnetic conditions (e.g., Protanypus, Heterotrissocladius, Micropsectra type), while diatoms indicated oligotrophic lake status (diatom inferred [TP] = 5-7 g·l^-1). Chironomids characteristic of lower oxygen availability (e.g., Chironomus, Procladius) increased following land-clearance, road construction, establishment of a grist mill and lakeshore development beginning ca. 1870. Increased abundances of Tanytarsus s. lat., a multigeneric group of mainly littoral chironomids, since 1900, indicated that littoral chironomids may have comprised a greater proportion of fossil assemblages during periods of eutrophication and prolonged anoxia. Abundances of meso-eutrophic diatom taxa (e.g., Fragilaria crotonensis, Asterionella formosa, Aulacoseira ambigua, A. subarctica) increased concurrent with European settlement (ca. 1870) and diatom-inferred [TP] doubled (~ 6-12 g·l^-1), further indicating that naturally-oligotrophic Precambrian Shield lakes were extremely sensitive to initial land-clearance activities.Recent increases in oligotrophic diatom taxa (e.g., Cyclotella stelligera) indicate a shift to more oligotrophic conditions since ca. mid-1960s, with greatest changes since ca. 1980. The chironomids Heterotrissocladius and Micropsectra type also increased at this time suggesting greater deepwater oxygen availability. These recent water-quality improvements, possibly in response to enhanced nutrient removal from detergents and sewage, climate-related reductions in external phosphorus loads, and catchment (but not lake) acidification and reforestation, suggest that habitat for commercially-valuable cold-water fishes has improved in recent decades despite greater recreational lake-use.Paleolimnological assessment of trophic status changes in Peninsula Lake using fossil diatom and chironomid assemblages were in good agreement. Diatom inferences of [TP] and chironomid inferences of AF both suggest that Peninsula Lake was historically oligotrophic, became oligo-mesotrophic after European settlement, and returned to oligotrophy in recent yrs. Chironomid inferences of [TP] consistently underestimated the trophic status of Peninsula Lake, possibly due to its relatively large hypolimnion. These results suggest that AF represents a useful tool for quantitatively reconstructing the past trophic status of deeper, stratified lakes.     

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.     

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).     

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.     

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.     

A chironomid-based salinity inference model from lakes on the Tibetan Plateau

Previous studies have shown chironomids to be excellent indicators of environmental change and training sets have been developed in order to allow these changes to be reconstructed quantitatively from subfossil sequences. Here we present the results of an investigation into the relationships between surface sediment subfossil chironomid distribution and lake environmental variables from 42 lakes on the Tibetan Plateau. Canonical correspondence analysis (CCA) revealed that of the 11 measured environmental variables, salinity (measured as total dissolved solids TDS) was most important, accounting for 10.5% of the variance in the chironomid data. This variable was significant enough to allow the development of quantitative inference models. A range of TDS inference models were developed using Weighted Averaging (WA), Partial Least Squares (PLS), Weighted Averaging–Partial Least Squares (WA–PLS), Maximum Likelihood (ML), Modern Analogues Technique (MAT) and Modern Analogues Techniques weighted by similarity (WMAT). Evaluation of the site data indicated that four lakes were major outliers, and after omitting these from the training set the models produced jack-knifed coefficients of determination (r ²) between 0.60 and 0.80, and root-mean-squared errors of prediction (RMSEP) between 0.29 and 0.44 log₁₀ TDS. The best performing model was the two-component WA–PLS model with r ² _jack = 0.80 and RMSEP_jack = 0.29 log₁₀ TDS. The model results were similar to other chironomid-salinity models developed in different regions, and they also showed similar ecological groupings along the salinity gradient with respect to freshwater/salinity thresholds and community diversity. These results therefore indicate that similar processes may be controlling chironomid distribution across salinity gradients irrespective of biogeographical constraints. The performance of the transfer functions illustrates that chironomid assemblages from the Tibetan Plateau lakes are clearly sensitive indicators of salinity. The models will therefore allow the quantification of long-term records of past water salinity for lacustrine sites across the Tibetan Plateau, which has important implications for future hydrological research in the region.     

Environmental controls on peatland testate amoebae (Protozoa: Rhizopoda) in the North of Ireland: Implications for Holocene palaeoclimate studies

The environmental controls on modern peatland testate amoebae (Protozoa: Rhizopoda) in the North of Ireland were investigated to assess the potential for Holocene palaeoclimate research within this region. Canonical Correspondence Analysis (CCA) revealed that hydrological factors (water table depth and moisture content) are the most important abiotic controls on organism distribution. A series of partial CCAs showed that water table depth explains 15.8% and moisture content explains 5.5% of the total variance. Monte-Carlo permutation tests showed that the results are highly significant (p < 0.002; p < 0.040 respectively). Transfer functions were generated for water table depth using weighted averaging tolerance downweighted (WA-Tol) regression and for moisture content using weighted averaging partial least squares regression (WA-PLS). The performance of the models was assessed using leave-one-out cross-validation (jacknifing). After removal of outlier samples, the improved transfer functions were found to perform well with an r _jack² and root mean square error of prediction_jack of 0.83, 4.99 cm for water table depth and 0.76, 4.60% for moisture content respectively. The water table transfer function was applied to a fossil peat sequence from this region and reconstruction errors were generated by 1,000 bootstrap cycles. The water table reconstruction was also carried out using an established pan-European transfer function and was found to be similar to that based on the North of Ireland dataset. This demonstrates the persistent and comparable control of hydrological variables on the distribution of testate amoebae taxa across Europe and implies that regional training sets can suffice as long as no-analogue situations are not encountered.

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.     

Use of sedimentary pigments to infer past phosphorus concentration in lakes

We propose a palaeolimnological method for inferring past total phosphorus (TP) concentrations in lake water from spectrophotometrically-measured sedimentary pigments, particularly total carotenoids (TC). Our approach is based on a highly significant statistical correlation (P < 0.0001) between pigment concentrations (total carotenoids) in the surface sediment of 28 Italian lakes (subalpine, large, deep, shallow, volcanic) and TP concentrations measured in these lakes at overturn when the core was collected. A transfer function was developed from this “training” set, and used to estimate past TP concentrations from pigment concentrations in sediment cores. The results generally agreed with TP values as measured by long-term water quality monitoring programs. Contrasting results were obtained by a comparison with diatom-inferred TP. While the diatom model showed a tendency to overestimate TP values higher than 100 μg l⁻¹, the pigment model correctly estimated TP in lakes when TP was <100 μg l⁻¹, but not when lakes were rich in macrophytes. In fact, lakes with extensive populations of aquatic submersed macrophytes and epiphytes are outliers in terms of the TC versus TP relationship. The root mean square error of prediction of the pigment model is lower than those derived from certain diatom—based inference models. The predicted and residual values are not related to the estimated values and their average is not statistically different from zero. Errors were estimated via a ‘leave-one-out’ re-sampling technique. The proposed method permits rapid and relatively inexpensive determination of reference trophic conditions.