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1.
This study investigated the distribution of subfossil diatom assemblages in surficial sediments of 100 lakes along steep ecological and climatic gradients in northernmost Sweden (Abisko region, 67.07° N to 68.48° N latitude, 17.67° E to 23.52° E longitude) to develop and cross-validate transfer functions for paleoenvironmental reconstruction. Of 19 environmental variables determined for each site, 15 were included in the statistical analysis. Lake-water pH (8.0%), sedimentary loss-on-ignition (LOI, 5.9% and estimated mean July air temperature (July T, 4.8%) explained the greatest amounts of variation in the distribution of diatom taxa among the 100 lakes. Temperature and pH optima and tolerances were calculated for abundant taxa. Transfer functions, based on WA-PLS (weighted averaging partial least squares), were developed for pH (r2 = 0.77, root-mean-square-error of prediction (RMSEP) = 0.19 pH units, maximum bias = 0.31, as assessed by leave-one-out cross-validation) based on 99 lakes and for July T (r2 = 0.75, RMSEP = 0.96 °C, max. bias = 1.37 °C) based on the full 100 lake set. We subsequently assessed the ability of the diatom transfer functions to estimate lake-water pH and July T using a form of independent cross-validation. To do this, the 100-lake set was divided in two subsets. An 85-lake training-set (based on single limnological measurements) was used to develop transfer functions with similar performance as those based on the full 100 lakes, and a 15-lake test-set (with 2 years of monthly limnological measurements throughout the ice-free seasons) was used to test the transfer functions developed from the 85-lake training-set. Results from the intra-set cross-validation exercise demonstrated that lake-specific prediction errors (RMSEP) for the 15-lake test-set corresponded closely with the median measured values (pH) and the estimations based on spatial interpolations of data from weather stations (July T). The prediction errors associated with diatom inferences were usually within the range of seasonal and interannual variability. Overall, our results confirm that diatoms can provide reliable and robust estimates of lake-water pH and July T, that WA-PLS is a robust calibration method and that long-term environmental data are needed for further improvement of paleolimnological transfer functions.  相似文献   

2.
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.  相似文献   

3.
Ecological optima and tolerances with respect to autumn pH were estimated for 63 diatom taxa in 47 Finnish lakes. The methods used were weighted averaging (WA), least squares (LS) and maximum likelihood (ML), the two latter methods assuming the Gaussian response model.WA produces optimum estimates which are necessarily within the observed lake pH range, whereas there is no such restriction in ML and LS. When the most extreme estimates of ML and LS were excluded, a reasonably close agreement among the results of different estimation methods was observed. When the species with unrealistic optima were excluded, the tolerance estimates were also rather similar, although the ML estimates were systematically greater.The parameter estimates were used to predict the autumn pH of 34 other lakes by weighted averaging. The ML and LS estimates including the extreme optima produced inferior predictions. A good prediction was obtained, however, when prediction with these estimates was additionally scaled with inverse squared tolerances, or when the extreme values were removed (censored). Tolerance downweighting was perhaps more efficient, and when it was used, no additional improvement was gained by censoring. The WA estimates produced good predictions without any manipulations, but these predictions tended to be biased towards the centroid of the observed range of pH values.At best, the average bias in prediction, as measured by mean difference between predicted and observed pH, was 0.082 pH units and the standard deviation of the differences, measuring the average random prediction error, was 0.256 pH units.  相似文献   

4.
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   

5.
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   

6.
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   

7.
The fossil diatom records preserved in radiometrically dated sediment cores from four shallow lakes in the Norfolk Broads, UK (Barton Broad, Rollesby Broad, Wroxham Broad and Upton Broad) were analysed. A weighted-averaging partial least squares (WA-PLS) diatom-total phosphorus (TP) transfer function, based on a training set of 152 mostly shallow (maximum depth < 3 m) lakes in northwest Europe, was applied to the full diatom dataset for each core to reconstruct the past TP concentrations of the lakes. Owing to the dominance of non-planktonic Staurosira, Pseudostaurosira and Staurosirella spp. (formerly classified in the genus Fragilaria) throughout the diatom records, the quantitative diatom inferred TP (DI-TP) concentrations did not adequately reflect the changes that occurred in the lakes as indicated by shifts in the other diatom taxa, or as reported in the literature. This was most apparent at Barton Broad and Rollesby Broad, where there was a marked increase in the importance of planktonic taxa associated with highly nutrient-rich waters but no increase in DI-TP. The modern and fossil data were thus square-root transformed to downweight the dominant taxa and the new transfer function was applied to the cores. An improvement was seen only in the reconstruction for Barton Broad. Finally, the Staurosira, Pseudostaurosira and Staurosirella spp. were removed from the modern and fossil diatom data, and the transfer function was re-applied. The trends in DI-TP became less clear, particularly for Upton Broad and Barton Broad, owing to a paucity of data for calibration once these taxa were deleted from the counts data. The problems associated with reconstructing trophic status and determining TP targets for restoration from fossil diatom assemblages in these systems are discussed.  相似文献   

8.
The relationship between surface-sediment cladoceran and chironomid communities to lake depth was analysed in 53 lakes distributed across timberline in northern Fennoscandia using multivariate statistical approaches. The study sites are small and bathymerically simple, with water depth ranging from 0.85-27.0 m (mean 6.36 m). Maximum lake depth was the most important factor in explaining the cladoceran distributions and the second most important factor in explaining the chironomid distributions in these subarctic lakes, as assessed on the basis of a series of constrained RDAs, Monte Carlo permutation tests, and variance partitioning. Quantitative inference models for maximum lake depth were created for both groups of animals. Well-performing calibration functions for predicting lake depth were obtained in each case using linear partial least squares (PLS) regression and calibration, weighted averaging (WA) with an 'inverse' deshrinking regression, and weighted averaging partial least squares (WA-PLS). Quantitative reconstructions of lake level fluctuations should be possible from cladoceran and chironomid core data with a root mean squared error of prediction (RMSEP), as estimated by jack-knifing, of about 1.6-3.0 m.  相似文献   

9.
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.  相似文献   

10.
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   

11.
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   

12.
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.  相似文献   

13.
Subfossil midge remains were identified in surface sediment recovered from 88 lakes in the central Canadian Arctic. These lakes spanned five vegetation zones, with the southern-most lakes located in boreal forest and the northern-most lakes located in mid-Arctic tundra. The lakes in the calibration are characterized by ranges in depth, summer surface-water temperature (SSWT), average July air temperature (AJAT) and pH of 15.5 m, 10.60°C, 8.40°C and 3.69, respectively. Redundancy analysis (RDA) indicated that maximum depth, pH, AJAT, total nitrogen-unfiltered (TN-UF), Cl and Al capture a large and statistically significant fraction of the overall variance in the midge data. Inference models relating midge abundances and AJAT were developed using different approaches including: weighted averaging (WA), weighted averaging-partial least squares (WA-PLS) and partial least squares (PLS). A chironomid-based inference model, based on a two-component WA-PLS approach, provided robust performance statistics with a high coefficient of determination (r 2 = 0.77) and low root mean square error of prediction (RMSEP = 1.03°C) and low maximum bias. The use of a high-resolution gridded climate data set facilitated the development of the midge-based inference model for AJAT in a region with a paucity of meteorological stations and where previously only the development of a SSWT inference model was possible. David Porinchu and Nicolas Rolland contributed equally to the work.  相似文献   

14.
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.  相似文献   

15.
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   

16.
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   

17.
Detrended canonical coreespondence analysis (DCCA) was used to examine the relationships between diatom species distributions and environmental variables from 62 drainage lakes in the Adirondack region, New York (USA). The contribution of lakewater pH, Alm (monomeric Al), NH4, maximum depth, Mg, and DOC (dissolved organic carbon) were statistically significant in explaining the patterns of variation in the diatom species composition. Twenty-three and sixteen diatom taxa were identified as potential indicator species for pH and Alm, respectively (i.e. a taxon with a strong statistical relationship to the environmental variable of interest, a well defined optimum, and a narrow tolerance to the variable of interest). Using weighted-averaging regression and calibration, predictive models were developed to infer lakewater pH (r 2=0.91), Alm (r 2=0.83), DOC (dissolved organic carbon) (r 2=0.64), and ANC (acid neutralizing capacity; r 2=0.90). These variables are of key importance in understanding watershed acidification processes. These predictive models have been used in the PIRLA-II (Paleoecological Investigation of Recent Lake Acidification-II) project to answer policy-related questions concerning acidification, recovery, and fisheries loss.  相似文献   

18.
Surficial sediments from 76 lakes from two western Quebec regions(Abitibi and Haute Mauricie) were sampled to identify the relationships betweendiatoms and environmental variables. Because the two regions containedradically different diatom communities, we then investigated which factors maybe responsible for the large community discrepancies in the two nearbygeographical areas. Standard lake chemistry variables showed little differencesbetween the regions, although epilimnetic light regimes were slightly lower inAbitibi. Nevertheless, lakes of the two regions with similar light regimes andchemistry still showed a clear separation in their diatoms, implying that otherimportant factors are influencing assemblages. We found that the calculatedconcentration of CO2 in the open water can explain some of thediscrepancy in diatom assemblages. A pCCA constrained to the concentration ofCO2 with alkalinity and pH as covariables explained 12.5% of speciesvariance and was significant. Given the lack of a relationship between DOC andCO2, and because the lakes are heavily supersaturated withCO2 in the calibration set, lake-to-lake variations inCO2 concentrations are likely due to groundwater inputs; thepossibility that this environmental variable may be influencing diatomcommunities might allow, in some cases, the reconstruction of historicalchanges in groundwater inputs to lakes. Finally, new calibration models werebuilt in Quebec by using weighted averaging partial least square(WA-PLS) techniques in order to infer pH, CO2, TP, TN, and, DOC fromdiatom assemblages preserved in the surface sediments.  相似文献   

19.
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   

20.
Chrysophyte cysts were identified from the surface sediment of 105 mountain lakes in the Pyrenees (NE Spain), and their statistical relationship to water chemistry was examined using canonical correspondence analysis (CCA). The chemical parameters that explained significant and independent amounts of variability were alkalinity, pH, potassium, nitrate and magnesium. In a CCA using these parameters, the first canonical axis was related to a gradient of alkalinity and pH, which reflected the varying nature of the watershed bedrock in the Pyrenees, while the second axis was correlated with potassium (negatively) and nitrate (positively). The potential for environmental reconstructions of the five chemical parameters was further studied by: (i) analyzing the distribution of optima and tolerances calculated by weighted-averaging (WA); (ii) carrying out detrended canonical correspondence analysis (DCCA) with a single environmental variable; and (iii) examining the performance of WA-PLS transfer functions. Acceptable transfer functions were obtained for alkalinity, pH and nitrate. However, for potassium and magnesium the tolerance of cysts was too broad and the distribution of optima too skewed, respectively. The possibility of reconstructing nitrogen-related issues using chrysophyte cysts is particularly interesting because of the lack of direct chemical records of nitrogen compounds in sediments. Nitrate reconstructions using transfer functions may be complemented by a holistic reconstruction using partial CCA, where, after subtracting the effects of other chemicals, samples are ordered on a plain defined by potassium and nitrate. This ordination could show down-core trends in lake productivity and renewal time.  相似文献   

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