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1.
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.  相似文献   

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

3.
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.  相似文献   

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

5.
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.  相似文献   

6.
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.  相似文献   

7.
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.  相似文献   

8.
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  相似文献   

9.
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).  相似文献   

10.
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, RMSEPjack = 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, RMSEPjack = 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, RMSEPjack = 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.  相似文献   

11.
The 167 sample lake-water pH-diatom calibration data-set created as part of the Palaeolimnology Programme within the Surface Water Acidification Project (SWAP) is re-analysed numerically using nine different numerical methods, six based on simple two-way weighted-averaging (WA), and the other three involving Gaussian logit regression (GLR) and maximum-likelihood (ML) calibration, the modern analogue technique, or weighted-averaging partial least-squares regression and calibration. Root mean squared error of prediction and maximum bias were estimated for all nine methods based on 10,000 internal and 10,000 external cross-validations involving a training-set, an optimisation-set, and a test-set. The results show that WA with a monotonic deshrinking spline equals or slightly outperforms WA with linear inverse deshrinking, especially in external cross-validation. Methods that employ tolerance downweighting generally have an inferior performance except when combined with monotonic deshrinking. It appears that simple two-way WA extensively used in SWAP cannot be significantly bettered. Thanks to increased computing power, better software, and more rigorous cross-validations, GLR shows good performance, especially in external cross-validation.  相似文献   

12.
The resolution achievable for chironomid identifications has increased in recent years because of significant improvements in taxonomic literature. However, high taxonomic resolution requires more training for analysts. Furthermore, with greater taxonomic resolution, misidentifications and the number of rare, poorly represented taxa in chironomid calibration datasets may increase. We assessed the effects of various levels of taxonomic resolution on the performance of chironomid-based temperature inference models (transfer functions) and temperature reconstruction. A calibration dataset consisting of chironomid assemblage and temperature data from 100 lakes was examined at four levels of taxonomic detail. The coarsest taxonomic resolution primarily represented identifications to genus or suprageneric level. At the highest level of taxonomic resolution, identification to genus level was possible for 37% of taxa, and identification below genus was possible for 60% of taxa. Transfer functions were obtained using Weighted Averaging (WA) and Weighted Averaging-Partial Least Squares (WA-PLS) regression. Cross-validated performance statistics, such as the root mean square error of prediction (RMSEP) and the coefficient of determination (r 2) between inferred and observed values improved considerably from the lowest taxonomic resolution level (WA: RMSEP 1.91°C, r 2 0.78; WA-PLS: RMSEP 1.59°C, r 2 0.86) to the highest taxonomic resolution level (WA: RMSEP 1.66°C, r 2 0.84; WA-PLS: RMSEP 1.41°C, r 2 0.89). Reconstructed July air temperatures during the Lateglacial period based on fossil chironomid assemblages from Hijkermeer (The Netherlands) were similar for all levels of taxonomic resolution, except the coarsest level. At the coarsest taxonomic level, reconstruction failed to infer one of the known Lateglacial cold episodes in the record. Also, the difference in reconstructed values based on lowest and highest taxonomic resolutions exceeded sample-specific estimated standard errors of prediction in several instances. Our results suggest that chironomid-based transfer functions at the highest taxonomic resolution outperform models based on lower-resolution calibration data. However, transfer functions of intermediate taxonomic resolution produced results very similar to models based on high-resolution taxonomic data. In studies that include analysts with different levels of expertise, inference models based on intermediate taxonomic resolution, therefore, might provide an alternative to transfer functions of maximum taxonomic detail in order to ensure taxonomic consistency between calibration datasets and down-core records produced by different analysts.  相似文献   

13.
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.  相似文献   

14.
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, RMSEjackknife = 0.45, mean bias = 0.14, maximum bias = 1.13) gives a better predictive power than the WA model (R2 jackknife = 0.56, RMSEjackknife = 0.5, mean bias = –0.09, maximum bias = –1.07) or WA-PLS model (R2 jackknife = 0.58, RMSEjackknife = 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.  相似文献   

15.
This paper presents a new method (moving-windows) that optimizes diatom-based paleolimnological reconstructions of past environmental conditions from supra-regional training sets. The moving-window method identifies the best number of nearest neighbours (window size) from a merged supra-regional EDDI and local (MV) training set (n = 429) for each fossil diatom assemblage and the best type of transfer function (ML, WA-PLS) based on the error statistic of each transfer function (highest cross-validated R 2, lowest cross-validated average bias, maximum bias and RMSEP). At first we evaluated the moving-window approach by comparing measured TP-values with inferred TP-values using both the moving-window approach and the WA-PLS method. The relative errors of the moving-window approach were not significantly different for 208 samples that had an error <15 μg/l TP using the WA-PLS method. However, for the remaining 221 samples with errors >>15 μg/l TP using the WA-PLS method, the moving window approach significantly reduced the relative error of the inferred TP levels. Secondly, the moving- window approach was used to reconstruct epilimnetic total phosphorous (TP) for Lake Dudinghausen, Lake Rugensee, Lake Tiefer See and Lake Drewitzer See (Northern Germany) using both the supra-regional EDDI training set and a local training set from Northern Germany (MV training set). The moving-window inferred TP-levels of the four study lakes were compared with published reconstructed TP-values and with inferred TP-values based on the local MV training set. Overall, the moving-window and the published TP-trends agree well with each other. However, the moving-window reconstructions generally indicated lower TP-levels throughout the past ∼5,000 to 12,000 years, including past maxima. Thus, the moving-window method seems to generate more realistic absolute TP levels due to the optimized window size (highest number of modern analogues, best error statistics). The identification of more realistic absolute historic TP-values is important for the validation of reference conditions for inland waters. This study also demonstrates that a robust local training set may, similar to moving-window training sets, also lead to reliable reconstructions, if the geological settings of the local training set lakes and the study lakes are similar.  相似文献   

16.
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 (RMSEPjack = 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 RMSEPjack= 0.26, mean bias = –0.0103 and maximum bias = 0.26.  相似文献   

17.
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).  相似文献   

18.
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 r2jack = 0.79; RMSEP = 0.15 log10 S cm–1),the annual mean of pH (WA r2jack = 0.72; RMSEP = 0.25 pH units) and the isothermal mean of Chl a (WA r2jack = 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 r2jack = 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 r2jack = 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.  相似文献   

19.
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.  相似文献   

20.
We assess Holocene environmental change at alpine Lake Njulla(68°22N, 18°42E, 999 m a.s.l.) innorthernmost Sweden using sedimentary remains of chironomid head capsules anddiatoms. We apply regional calibration sets to quantitatively reconstruct meanJuly air temperature (using chironomids and diatoms) and lake-water pH(using diatoms). Both chironomids and diatoms infer highest temperatures(1.7–2.3°C above present-day estimates, includinga correction for glacio-isostatic land up-lift by0.6°C) during the early Holocene (c.9,500–8,500 cal. yrs BP). Diatoms suggest a decreasing lake-waterpH trend (c. 0.6 pH units) since the early Holocene. Usingdetrended canonical correspondence analysis (DCCA), we compare the Holocenedevelopment of diatom communities in Lake Njulla with four other nearby lakes(Lake 850, Lake Tibetanus, Vuoskkujávri, Vuolep Njakajaure) locatedalong an altitudinal gradient. All five lakes show similar initial DCCA scoresafter deglaciation, suggesting that similar environmental processes such ashigh erosion rates and low light availability associated with high summertemperature appear to have regulated the diatom community, favouring highabundances of Fragilaria species. Subsequently, the diatomassemblages develop in a directional manner, but timing and scale ofdevelopment differ substantially between lakes. This is attributed primarily todifferences in the local geology, which is controlling the lake-waterpH. Imposed on the basic geological setting, site-specific processessuch as vegetation development, climate, hydrological setting andin-lake processes appear to control lake development in northernSweden.  相似文献   

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